Design and Fabrication of a Maneuverable Robot for
In-Pipe Leak Detection
by
You Wu
Submitted to the Department of Mechanical Engineering
in partial fulfillment of the requirements for the degree of
Master of Science in Mechanical Engineering
MASSACHUSETTS INSTITUTE
OF TECHNOLOGY
AUG 15 2014
at the
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
LIBRARIES
June 2014
@ Massachusetts Institute of Technology 2014. All rights reserved.
Signature redacted
............
A uthor ..................
Department of Mechanical Engineering
May 20, 2014
Certified by.
redacted
...Si gnature
I
Kamal Youcef-Toumi
Professor
Thesis Supervisor
Signature redacted
Accepted by............
..........
David E Hardt
Chairman, Department Committee on Graduate Theses
Design and Fabrication of a Maneuverable Robot for In-Pipe
Leak Detection
by
You Wu
Submitted to the Department of Mechanical Engineering
on May 20, 2014, in partial fulfillment of the
requirements for the degree of
Master of Science in Mechanical Engineering
Abstract
Leaks in pipelines have been causing a significant amount of financial losses and
serious damages to the community and the environment. The recent development of
in-pipe leak detection technologies at Massachusetts Institute of Technology made it
possible to find the accurate location of leaks in underground pipes. However, like
all in-pipe leak sensors, they need a maneuverable robot to transport them inside
the pipes. In the pipe networks, the robot must be able to perform complicated
movements such as sharp turns at Tee junctions. This thesis presents a solution to
this in-pipe leak detection challenge and the design and a prototype of such robot.
The design and fabrication of a small in-pipe swimming robot of high maneuverability
is presented. The robot is equipped with a pair of customized micro RIM driven
propellers which provide a powerful and safe propulsion. A prototype robot that
operates in 10 cm diameter pipes is built and tested experimentally. This robot
demonstrated experimentally abilities to follow straight lines and make turns with
radii smaller than a fraction of its body length.
Thesis Supervisor: Kamal Youcef-Toumi
Title: Professor
3
4
Acknowledgments
I would like to first thank my advisor, Prof. Kamal Youcef-Toumi, for guiding me
through my two years of study at MIT. With the guidance and help from Kamal, I
feel I have become a better researcher, a better engineer and a better presenter. It
was a great honor to have a great advisor like Kamal.
I am also extremely grateful to my colleagues on my thesis project, Dimitris
Chatzigeorgiou, Dalei Wu, David Donghyun Kim and Antoine Noel. This project is
a collaborative effort. Without the support and help from each one of them, I could
not have accomplished so much on this project. Moreover, they are a big part of my
life at MIT.
I gratefully acknowledge King Fahd University of Petroleum and Minerals and
MIT Clean Water and Clean Energy Center for their generous support of this work.
I would like to thank Dr. Rached Ben Mansour, the Co Principle Investigator of
this project from King Fahd University of Petroleum and Minerals and my fellow
boilermaker. Dr. Rached provided me with valuable insights on my research, but
more importantly, he introduced me to the Saudi Arabia culture.
Last but not least, I sincerely appreciate my family and my friends. I was far
away from my family but they constantly sent their love to me over the internet. My
friends here in Boston made my life fun every day. One of them is Josh Adler. Josh
took us on a journey to explore the potential commercial space of our research work.
I left a startup to come to MIT, but as I was work with Josh, I felt I had never left
my entrepreneurial spirit behind.
5
6
Contents
1.1
Motivation For In-pipe Leak Detection . . . . . . . . . . . . . . . .
17
1.2
Challenges for In-Pipe Robots . . . . . . . . . . . . . . . . . . . . .
19
1.3
The Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21
.
.
.
17
23
2.1
Functional Requirements . . . . . . . . . . . . . . . . . . . . . . . .
23
2.2
Design Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . .
25
2.3
Hydrodynamic Design
29
2.4
.
.
Robot Design
.
. . . . . . . . . . . . . . . . . . . . . . . . .
2.3.1
Notations and Assumptions
2.3.2
Design for Low Axial Drag Force
. . . . . . . . . . . . . . .
31
2.3.3
Design for Angular Stability . . . . . . . . . . . . . . . . . .
32
2.3.4
Design for Radial Stability . . . . . . . . . . . . . . . . . . .
33
2.3.5
Design for Minimal Turning Radius . . . . . . . . . . . . . .
34
2.3.6
Conclusion of Hydrodynamic Design
. . . . . . . . . . . . .
38
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
40
.
.
.
.
.
. . . . . . . . . . . . . . . . . .
Summary
.
2
Introduction
.
1
3 Actuation System
30
41
Actuation System Alternatives . . . . . . . .
. . . . . . . .
41
3.2
Actuation System Design . . . . . . . . . . .
. . . . . . . .
42
3.3
Propeller Sizing . . . . . . . . . . . . . . . .
. . . . . . . .
43
3.3.1
Scenario 1: Moving in A Straight Pipe
. . . . . . . .
44
3.3.2
Scenario 2: Turning at A Tee Junction
. . . . . . . .
46
.
.
.
3.1
7
3.6
3.7
3.4.1
Stator . . . . . . . . . . . . .
52
3.4.2
Rotor
. . . . . . . . . . . . .
53
3.4.3
Propeller Blade . . . . . . . .
54
3.4.4
Bearing
. . . . . . . . . . . .
57
Performance . . . . . . . . . . . . . .
59
3.5.1
Experiment Setup . . . . . . .
60
3.5.2
Experiment Results . . . . . .
61
Propeller Characterization . . . . . .
62
.
.
.
.
.
.
51
.
3.5
Design and Fabrication of the RIM Propeller
.
3.4
3.6.1
input-output mapping.....
63
3.6.2
Dynamics of the RIM propeller
64
Summary
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4 Integration
67
Robot Housing
. . . . . . . . . . . . . .
4.2
Electronic Subsystems
67
.
4.1
68
4.2.1
Power . . . . . . . . . . . . . . .
68
4.2.2
Sensing
. . . . . . . . . . . . . .
69
4.2.3
Communication . . . . . . . . . .
70
4.2.4
Control
70
4.2.5
Integration of Electronic Subsystems
.
.
.
.
. . . . . . . . . .
.
. . . . . . . . . . . . . .
71
Packaging . . . . . . . . . . . . . . . . .
72
4.4
Waterproofing . . . . . . . . . . . . . . .
74
4.5
Summary
75
.
.
4.3
.
. . . . . . . . . . . . . . . . .
Control
. . . . .
77
5.1.1
Robot Modeling . . . . . . . . . .
. . . . .
77
5.1.2
Onboard Controller Design . . . .
. . . . .
79
. . . . . . . . .
. . . . .
81
. . . . . . . . . . . . . . . . .
. . . . .
86
.
.
.
Onboard Controller . . . . . . . . . . . .
5.2
Remote Control System
5.3
Summary
.
5.1
77
.
5
66
8
87
6.1
Overview ........................
87
6.2
Experiment Setup ...............
87
6.3
Results and Discussion ...............
89
6.3.1
Following Straight Lines . . . . . .
89
6.3.2
Follow Straight Lines and Overcoming disturbances
91
6.3.3
90-degree Turns . . . . . . . . . . .
92
6.3.4
Minimum Turning Radius . . . . .
94
6.4
7
Summary of Results
.
.
.
Experimental Results
. . . . . . . . . . . .
.
6
Conclusion and Recommandations
A Robot CAD Model
96
97
99
B RIM Propeller CAD Model
105
C CFD Simulation Setup
107
D LabVIEW Block Diagram
111
9
10
List of Figures
1-1
Picture of MIT MRL leak Detection robot [9, 101
. . . . . . . . . . .
21
1-2 Prototype of the maneuverable robot . . . . . . . . . . . . . . . . . .
22
2-1
Simplified problem . . . . . . . .. . . . . . . . . . . . . . . . . . . . .
24
2-2
Illustration of a multi-module crawler turning at a Tee junction
26
2-3
Sketch of the composition of a typical Tee Junction. A Tee junction
. . .
usually has a different diameter than the pipes it is connected to. Steps
are formed at the joints. . . . . . . . . . . . . . . . . . . . . . . . . .
26
2-4
Illustration of an omnidirectional crawler turning at a Tee junction
.
27
2-5
Illustration of a swimming robot at a Tee junction . . . . . . . . . . .
28
2-6
Body Fixed Reference Frame used in the hydrodynamic analysis. Top
view . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2-7
Fluid accelerates around the robot in a pipe and increases the drag
force dram atically . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2-8
30
32
Fluid forces and moments on different shapes at different angular offset. (A) and (B): a robot with different profiles in x and y direction
experiences a Munk moment.
(C) and (D): a robot with the same
profile in x and y direction experiences no Munk moment.
2-9
. . . . . .
33
Illustration of Venturi's Effect on an in-pipe robot . . . . . . . . . . .
34
2-10 Isometric view of the robot body
. . . . . . . . . . . . . . . . . . . .
38
2-11 Frontal view of the robot body . . . . . . . . . . . . . . . . . . . . . .
39
3-1
43
Isometric view of the robot with two ducted RIM propellers .....
11
3-2
Schematic of the horizontal cross section view of the robot with two
ducted RIM propellers
3-3
. . . . . . . . . . . . . . . . . . . . . . . . . .
44
Cross-section view of the pipe and the robot in the simulation. The
robot is placed at the center of a circular pipe of diameter D and length
2L,.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3-4
Horizontal cross-section view of the simulated robot placed in the fluid
3-5
Cross-section view of the Tee junction and the robot in the simulation.
The robot is placed at the center of the Tee junction. . . . . . . . . .
3-6
47
48
Flow visualization for the robot inside a Tee junction. FD and force
Fs are measured.
3-7
45
. . . . . . . . . . . . . . . . . . . . . . . . . . . . .
49
Flow visualization for the robot inside a Tee junction. Location B has
higher flow speed and lower static pressure than location C.
. . . . .
50
3-8
Simulated force on the improved robot at different angular positions
51
3-9
Stator and rotor assembly of the RIM propeller
. . . . . . . . . . . .
52
3-10 Design of the rotor . . . . . . . . . . . . . . . . .. . . . . . . . . . . .
54
3-11 Specifications input to the OpenProp software . . . . . . . . . . . . .
55
3-12 CAD model of the rotor with optimal blades . . . . . . . . . . . . . .
56
3-13 Plot of maximum thrust measured on rotors with different center opening size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
56
3-14 Three different kinds of bearings for the RIM propeller . . . . . . . .
57
3-15 The RIM propeller placed inside the bearing of design C. Three set
screws are placed inside 3 holes. The back side of the bearing has the
same configuration
. . . . . . . . . . . . . . . . . . . . . . . . . . . .
59
3-16 The experiment setup for testing RIM propellers . . . . . . . . . . . .
61
3-17 Picture of the experiment for testing RIM propellers . . . . . . . . . .
62
3-18 Plot of rotational speed and thrust . . . . . . . . . . . . . . . . . . .
63
3-19 Plot of rotational speed and power consumption . . . . . . . . . . . .
63
. . . . . . . . . . . . . . . . .
64
3-21 Plot of input command vs measured steady state rotational speed . .
64
3-22 Plot of input command vs measured steady state thrust . . . . . . . .
65
3-20 Plot of thrust and power consumption
12
3-23 Measured step responses of the RIM propeller . . . . . . . . . . . . .6
4-1
66
Exploded view of the robot housing. Part A is the main body, B is the
cap, C and D are the RIM propeller bearings.
. . . . . . . . . . . . .
68
4-2
Simplified electronics diagram . . . . . . . . . . . . . . . . . . . . . .
71
4-3
Layout of electronics inside the robot . . . . . . . . . . . . . . . . . .
73
4-4
Three views of the cap. (A) side view, (B) bottom view and (C) bottom
view of the the cap with a silicone ring . . . . . . . . . . . . . . . . .
75
4-5
Picture of the fully assembled robot . . . . . . . . . . . . . . . . . . .
75
5-1
Block diagram of the closed loop robot system . . . . . . . . . . . . .
79
5-2
Response of the closed loop robot system to a 90 degree step (1.57 rad)
input.........
....................................
82
5-3
Image of the LabVIEW interface for robot control . . . . . . . . . . .
83
5-4
Plot of speed command vs measured steady state rotational speed . .
85
5-5
Plot of speed command vs measured steady state thrust
. . . . . . .
85
6-1
Picture of the water tank used in the experiment
. . . . . . . . . . .
88
6-2
Picture of the robot following a straight line . . . . . . . . . . . . . .
90
6-3
Picture of the robot following an straight path and overcoming an
obstacle
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
92
6-4
Picture of the robot going straight and then making a 90 degree turn
93
6-5
Picture of the robot during the spinning motion . . . . . . . . . . . .
95
A-1 Technical drawing of the robot main body, page 1/2.
. . . . . . . . .
100
A-2 Technical drawing of the robot main body, page 2/2.
. . . . . . . . .
101
A-3 Technical drawing of the cap.
. . . . . . . . . . . . . . . . . . . . . . 102
A-4 Technical drawing of the RIM propeller bearing. . . . . . . . . . . . .
103
B-1 Technical drawing of the stator in the RIM propeller. .........
106
C-1 CFD mesh settings. . . . . . . . . . . . . . . . . . . . . . . . . . . . .
107
13
C-2 CFD setups. (A) General solver settings, (B)Viscous model settings
and (C) material settings.
. . . . . . . . . . . . . . . . . . . . . . . .
108
C-3 CFD boundary conditions at four boundaries: (A) inlet, (B) robot
surface (C) outlet, and (D) pipe wall. . . , . . . . . . . . . . . . . . . 109
C-4 CFD calculation settings. (A) reference values, (B) solution methods
and (C) solution initialization. . . . . . . . . . . . . . . . . . . . . . . 110
D-1 Main block diagram of the remote control interface in LabVIEW. Area
A surrounded by the red dash lines is a stack of 9 frames of codes. The
first frame is shown in this Figure. The other 8 frames are shown in
Figure D -2.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
D-2 8 subsequent frames of codes for area A in Figure D-1.
. . . . . . . .
112
D-3 Block diagrams of two subVIs. The first subVI "Decode V2" is used in
Figure D-2. The second subVI, "PID conv string" is used in Figure D-1. 113
14
Functional requirements for the robot . . . . . . . .
24
2.2
Comparison of Design Alternatives
. . . . . . . . .
29
2.3
Notations used to describe the robot hydrodynamics
30
2.4
Physical meanings of hydrodynamic coefficients
. .
35
2.5
Dimension of the robot . . . . . . . . . . . . . . . .
40
3.1
Parameters of the simulated robot . . . . . .
. . . . . . . . . . .
44
3.2
Parameters considered in the CFD simulation
. . . . . . . . . . .
46
3.3
Desired parameters of the RIM propeller . .
. . . . . . . . . . .
52
3.4
Measured parameters of the RIM propeller .
. . . . . . . . . . .
57
4.1
List of electronic components
5.1
List of physical properties of the robot
5.2
Mapping between commands, wireless signals and controller input
.
.
.
.
.
.
.
2.1
.
List of Tables
. . . . . . . .
.
72
15
.
. . .
. . . . .
79
84
16
Chapter 1
Introduction
1.1
Motivation For In-pipe Leak Detection
Leak in pipelines is a widely spread problem. Millions of miles of underground pipes
carry all kinds of resources-water, oil and natural gas around the globe every day.
Leak happens here and there along those pipelines due to cracking, corrosion, aging
and damage. Pipeline leaks result in loss of the precious natural resource, significant
financial loss and serious environmental contamination.
There are incredible amounts of scarce resources leaked out every year. In gaspowered states like Massachusetts, more than one-hundred-million-dollars worth of
natural gas is leaked from the aged underground gas pipelines every year [3]. Water
leaks account for 15 percent to 25 percent of treated water production in U.S. municipalities every year [14], and it is on average 20 percent in Canada [19]. In dry regions
such as the Kingdom of Saudi Arabia, the water leak loss is even more significant.
Saudi Arabia has more than 70 of the water supply comes from seawater desalination [1], but its pipeline underneath the desert is losing 30 percent of this expensive
product [2]. It is estimated that Saudi Arabia loses around 500 million U.S. dollars
annually from water pipe leakage.
In addition to financial and product loss, leaks are dangerous to the community
and the environment. Gas leaks are very dangerous: it caused the 2010 San Bruno
Explosion which wiped out blocks of streets, took 8 lives and injured 51 people [20].
17
Water leaks, on the other hand, are less life threatening, but still could cause structural losses to cities. In addition, the remaining water is prone to get contaminated
from these pipe leaks. Pipe leaks force cities to draw more water from local bodies of
water than what would otherwise be needed, which accelerates the decline of wetland
ecosystems. Leak detection and overhaul in both gas and water pipelines is critical
to make communities safer and more sustainable.
Leak detection can be performed from outside and inside of the pipes. Some leaks
can be found from outside of the pipe using geophones and sniffers. On straight
pipes, multiple acoustic sensors can be deployed along the pipe and listen to the noise
created by the leaks. Through cross correlation of the received signals, the location of
the leak can be determined. To find leaks from inside of the pipes, robots are usually
deployed into the pipe. Those robots can carry acoustic sensors and magnetic flux
leakage sensors to pinpoint the location of the leaks.
In-pipe leak detection is particularly good for a range of leak problems. Most
underground pipelines are hard to reach, and the majority of leaks are too small
to be found remotely.
Fluid leaked from underground pipes can take a complex
path before it reach the ground, making it difficult for above ground leak detection
techniques such as geophones and sniffers to locate the leaks accurately. At the same
time, small leaks of low flow rate can remain undetected and be left leaking for years.
In-pipe leak detection techniques can find the accurate location of those leaks.
However, it is still challenging to find leaks in plastic and small diameter pipes. Inpipe leak detection systems using acoustic sensors and magnetic flux leakage sensors
can find leaks accurately in metallic pipes, but they are less effective on plastic pipes.
In the Kingdom of Saudi Arabia and many newly developed regions in the world,
PVC pipes are commonly used in the transportation of water and sometimes gas.
Such PVC pipes need a leak detection solution. Most of the pipes in local water
distribution networks are of small diameter, 10cm for example. The sensors and the
robotic platform that carry the sensors must be made small enough to fit into those
pipes. The Mechatronics Research Laboratory (MRL) at Massachusetts Institute of
Technology (MIT) has been developing in-pipe leak detection technologies targeting
18
those small leaks in underground small diameter pipes [5, 4, 6, 7, 81. This leak detector
can sense the fluid pressure gradient in the vicinity of the leaks. The pressure gradient
exists in all fluid, such as gas, water or oil, and it happens on pipes of any kind of
material, for example, plastic and metallic. In experiments, the this leak detector
is able to find leaks of pressure difference as low as 0.7 Bar and leak flow rate as
long as 61 liter/min (2.14 ft 3 /min). Therefore this leak detector can detect leaks in
pipes made of any material that carries any fluid, as long as there is a robot that can
transport it inside the pipe.
1.2
Challenges for In-Pipe Robots
In-pipe robots developed for pipeline inspection exist in various forms. They are
generally designed to carry sensors to evaluate the integrity of the pipelines that
transport natural gas, water, oil or all other products. Based on their locomotion
methods, robots are divided into two main categories, passive ones and active ones.
Passive robots float with the fluid inside the pipe, such as the SmartBall system
from Pure Technologies, Ltd and most pig robots for oil pipelines. Active robots
use a wide range of actuation mechanisms to crawl and/or swim inside the pipe,
such as the Explorer robot from Carnegie Mellon University [11] and the MIT leak
detection robot [6, 7]. In-pipe robots can be tethered or tetherless. Tethered robots
are connected to a remote power source and control center via cables.
Power is
supplied to these robots via cables and communication is also handed by another
set of cables.
Tetherless robots do not use any cables and are powered by their
onboard batteries. The Smartball, the Explorer and the MIT leak detection robot
are all tetherless robots. Tetherless robots can communicate with the control center
wirelessly, such as the Explorer and the MIT leak detection robot do. They can also
save information onboard when they are in the pipe and download the information
when they are outside the pipe, such as the Smartball does.
In-pipe robots are faced with a number of challenges. Those challenges are in
power, range, communication, deployment, localization and maneuverability.
19
Power, range and communication challenges are faced by all in-pipe robots. A
Tethered robot has secure power supply and communication via a cable, but its range
is limited by the length of the cable. When the tethered robot is operating inside a
complex pipe network, its range is more limited as it is difficult to pull cables around
pipe bends and junctions. A tetherless robot operates on its onboard battery, so its
range is dependent on the battery life. A tetherless robot has to communicate with
a remote control center wirelessly and it is difficult. When the robot is operating
in an underground pipeline, the wireless signal can be significantly attenuated and
hindered by the soil and metal pipe.
The deployment of in-pipe robots, including insertion and retrieval is another
challenge. Special tools are needed to insert the robots into pipelines safely. The
robot must have appropriate size so it can be deployed in the pipes. Robots, such
as the MIT leak detection robot [6, 7], can only enter pipes through appropriate
openings.
In-pipe robots must have localization capabilities in order to navigate through a
pipe network. Localization is the process to recognize where the robot is in the pipe
globally and locally. The global location of the robot is necessary for pinpointing the
robot and the points of interest such as cracks, leaks, corrosion, damage or blockages.
It has always been a challenge to obtain the accurate position of the robot especially in
long-distance or underground pipelines. In a short range, the robot needs to recognize
its location with respect to pipe features such as Tee junctions, Y junctions and bends.
The robot cannot successfully navigate through a complex pipe network without the
local information.
Besides the localization capability, in-pipe robots must have proper maneuverability. In a pipe network there are many Tee junctions, Y junctions and bends. A robot
should also be able to perform controlled turning at those locations in order to inspect
specific sections of the pipe and get to the retrieval point. To closely investigate a
pipe condition such as a leak, a maneuverable robot is also required to control its
speed and sometimes maintain stationary in the moving fluid inside the pipe.
The majority of the current in-pipe robot cannot meet the maneuverability re20
quirement, particularly the turning capability.
For example, the initial prototype
of the MIT MRL leak detection robot [6, 71 as shown in Figure 1-1 can operate in
straight pipes only. One of the most frequently asked question is, "Can it turn at a
Tee junction?" Over the last 20 years, a wide range of crawlers have been developed
[131. However, most of the state-of-the-art robots are designed to operate in empty
pipes. Pipe operators prefer to conduct maintenance when pipe is in service to avoid
the loss of revenue.
Figure 1-1: Picture of MIT MRL leak Detection robot [9, 10]
1.3
The Contribution
Two technical contributions are made in this thesis. The first one is the design of the
robot of high maneuverability. The second contribution is a safe and powerful micro
propulsion system.
A swimming robot is designed and fabricated to perform maneuvers in pipes. It
is capable of maneuvers such as maintaining its heading direction and making sharp
turns. These are required for the robot to operate inside common pipe networks that
consist of straight sections and Tee junctions.
A prototype of this robot is shown
in Figure 1-2. Its shape is that of an ellipsoid. All its subsystems, including power,
21
control, communication, sensing and actuation, are integrated within the robot. It
utilizes a pair of hub-less micro propulsion systems to perform maneuvers.
Figure 1-2: Prototype of the maneuverable robot
A safe and powerful micro propulsion system is developed. For a robot to operate
in a small confined environment such as the water pipes of small diameter, compact,
safe and powerful actuators are needed.
A propulsion system based on the RIM
driven propeller concept is designed and fabricated. It achieves strong propulsion
while occupying a very small volume. It satisfies the actuation requirement of this
in pipe robot, and it can be one of the best actuation solutions for all small scale
underwater robots.
This Thesis is organized as follows: Chapter 2 describes the robot design. Chapter 3 focuses on the actuation systems. Chapter 4 illustrates the integration of the
robot. Chapter 5 shows the control system design and its implementation. Chapter
6 discusses the performance of the robot and Chapter 7 provides conclusions and
recommendations.
22
Chapter 2
Robot Design
In this chapter, the design of the in-pipe swimming robot is presented.
Different
designs are compared, and a most reliable design is chosen. A design methodology
for this robot is described.
2.1
Functional Requirements
The goal of this project is to design a robot with a high degree of maneuverability
inside the pipe. Since it is an application-driven project, the robot was designed
for a real water distribution network. Once real pipe information was collected, a
simplified representation of the problem was formulated and functional requirements
were derived.
The information about water pipes in the Kingdom of Saudi Arabia was collected.
The common water pipes used in the distribution network are 10 cm (4 inches) in
diameter and made out of PVC. The pipe elements include straight sections, Tee
junctions and 90 degrees bends. These elements are in both vertical and horizontal
orientations. It is known that the interior of the water pipe is not perfectly smooth
or clean due to scales. When the pipe is in service, the water speed can vary from
zero up to 2.5 m/s. The total pressure in the pipe can be as high as 5 Bars.
A simplified scenario as shown in Figure 2-1 is considered in this work.
The
simplified pipe network contains a straight section and two Tee junctions. The average
23
inner diameter of the pipe is D. The diameter of the pipes in this networks is not
uniform. The fluid in the straight pipe section flows at a constant speed U. The goal
of this work is to design a robot that can operate in such a network. The robot needs
to follow the straight pipe and make a turn at a specific Tee junction. The parameters
of this pipe network are chosen to be similar to the real ones in our Saudi Arabia:
D = 10cm and U r1m/s.
A few assumptions are made. In this work, we assume both the straight section
and the Tee junctions are in horizontal orientation. The robot is assumed to be stable
in the vertical plane and it only needs to control its motion in the horizontal plane.
It is also assumed that the robot only needs to move in the direction of the flow.
Flow speed U
D
Figure 2-1: Simplified problem
From this simplified scenario, the functional requirements are defined as Table
2.1.
Table 2.1: Functional requirements for the robot
1.
2.
3.
4.
The robot must be able to
fit in a 10 cm diameter pipe.
operate in the direction of the fluid flow with a speed up to 1 m/s.
turn 90 degrees at a chosen Tee junction.
adapt to small variations in the pipe diameter.
24
2.2
Design Alternatives
For a robot to operate in a water pipe, it can either crawl or swim. Crawling is
moving based on interaction with the pipe wall.
Swimming is moving based on
interaction with the fluid. Three general concepts, including two crawlers and one
swimming robot, are evaluated.
Considering functionality and efficiency in small
diameter operating water pipes, a swimming robot is the best choice. Reasons for
this design choice are given in the following paragraphs.
The first basic concept is a multi-module crawler. There are two or more modules
in the robot connected by joints, as shown in Figure 2-2. It is similar to existing
in-pipe robots in [9] and [18]. All modules have wheels or actuated legs. Some or all
of the joints are actuated as well. The robot can coordinate the appropriate modules
and joints to perform motions such as following a straight line, braking and turning.
This design has the space advantage. Each module of the robot provides space
for hosting subsystems. The robot can carry many subsystems and achieve a range
of useful functions. For example, the robot can carry a large amount of batteries for
long missions. It can also carry multiple sensors for comprehensive pipe inspection.
There is a significant drawback of this multi-module crawler. It is difficult for this
kind of crawlers to adapt to small variations in the pipe diameter. Most of this type
of robots are designed for empty, perfectly smooth pipes [9, 18]. At a Tee junction of
a real water pipe, the junction can be of a bigger diameter than the straight pipes,
as illustrated in Figure 2-3. The wheels or the legs of a multi-module robot may get
stuck at the step formed when the pipe joins the junction. In addition, if there is a
crack or obstacle on the walls of the Tee junction, the wheels or legs of the robot may
get stuck. It may be even worse when there is a flow pushing the robot in the back.
The fluid force can prevent the robot from backing out of the stalled situation. Thus
the reliability of this crawling robot operating in a water pipe may be low.
The second basic concept is a single-module omnidirectional crawler. As shown
in Figure 2-4, the robot main body represented by the grey circle will be connected
to four legs by actuated joints. This is very similar to the work in [15]. The legs are
25
1
+
2
Force/torque
Figure 2-2: Illustration of a multi-module crawler turning at a Tee junction
I
U
7
Figure 2-3: Sketch of the composition of a typical Tee Junction. A Tee junction
usually has a different diameter than the pipes it is connected to. Steps are formed
at the joints.
spring-loaded, and the robot can actuate the joints to change the angular position
of the legs. In a straight pipe, the robot can retract all legs a little bit to squeeze
through sections of smaller diameter. When approaching a Tee junction, the robot
can actuate the joints and expand the angle between legs A and C as well as that
between legs B and D. This increases the tension in the legs and thus friction on
the wall. The robot can then slow down. Once the robot reaches a Tee junction as
shown in Figure 2-4, the robot will lose support from the pipe wall on legs C and D.
The tension in the legs C and D is then released allowing the legs to extend into the
side branch of the pipe. The robot can lock the joints and thus lock it position at
the Tee junction as shown in Figure 2-4. Then the robot can either re-orientate its
main propulsion system toward the side pipe or rely on a side propulsion system to
drive the robot into the side pipe. This mechanism can be built with 3 actuators,
26
one for joint control, another for main propulsion and a third for rotating the main
propulsion system. A design of this mechanism can be found in [22].
This single-module crawler benefits from its legs. It can easily adapt to the small
variations in the pipe diameter since its legs can extend and contract. The tension
in the legs can be used for sensing. The sudden drop in the tension can indicate the
arrival of the robot at a Tee junction.
However, the single-module crawler may fail at cracks and obstacles. Similar to
the multi-module crawler, a single-module crawler can get stuck at cracks, obstacles
and the steps formed at the Tee junction as shown in Figure 2-3. It is also difficult
for this mechanism to back out of a stuck situation. In addition, in a forced flow,
the robot may start to spin at the Tee junction if the legs are not locked firmly. The
performance of this single module crawler can not be consistent in pipes of rough
walls and flow conditions.
-.
A
B
A
B
C
D
C
D
, direction of motion
Figure 2-4: Illustration of an omnidirectional crawler turning at a Tee junction
The third basic concept is a swimming robot. As shown in Figure 2-5, a swimming
robot can utilize a couple of thrusters and perform differential drive to turn at a Tee
junction. It can use the same thrusters to slow down and maintain stationary in a
fluid flow. In long straight sections, the swimming robot can turn off the thrusters
and simply float.
A swimming robot is a reliable solution for pipes of all conditions.
Since the
swimming robot does not rely on supports from the pipe walls, it is less likely to
get stuck at cracks and obstacles inside a pipe. Thus its reliability in this aspect
27
is higher than crawlers. If internal propulsion system such as ducted propellers and
micro pumps are used, the exterior of the robot can be perfectly smooth. In the case
of possible collisions, actuators inside the rigid shell of the robot are less likely to be
damaged and lose functionality, in comparison to the crawlers that have actuators
outside the robot body.
1
4- -
2
water jet output
Figure 2-5: Illustration of a swimming robot at a Tee junction
Swimming in a pipe is challenging for a robot. A pipe is a confined environment.
The flow inside this pipe interacts with the robot and it may create disturbances on
the robot. The fluid field at a Tee junction can be highly turbulent, and its effects
on the swimming motion of the robot have not been studied sufficiently in the past.
The robot must have accurate control system so it can maneuver safely in the pipes.
Those challenges can be overcome. The next section of this thesis will show with
Computational Fluid Dynamics (CFD) simulation results that a proper shape design
can allow the swimming robot to overcome the fluid disturbances. A properly designed
robot can maneuver inside a fluid flow easily. It can also take advantage of the fluid
field at Tee junctions to detect the Tee junction as well as perform turns.
Swimming robots perform maneuvers more reliably and efficiently. The comparison between the three types of robtos is summarized in Table 2.2. All three concepts
can be designed to fit in 10 cm diameter pipes. They can all turns, but the swimming
robot can perform turns more consistently. With properly sized actuators, all three
robots can operate in forced flow conditions. Although it should take crawlers less
energy to come to a complete stop in a flow, the swimming robot saves more energy
28
floating. While all concepts can meet the functional requirement as listed in Table
2.1, the swimming robot is chosen as it has more potential to reliably and efficiently
maneuver in a water pipe.
Table 2.2: Comparison of Design Alternatives
swimming robot
good
Single
module
omnidirectional
crawler
good
poor
poor
good
poor
poor
good
poor
poor
good
Criteria
Multi-module
crawler
Ability to make 90 degree
turns
Reliability of maneuvering
in an uneven pipes
Ability to directly take ad-
good
vantage of the flow
Overall power efficiency
2.3
Hydrodynamic Design
The desired characteristics of a swimming robot are a large size, a low drag force and
a small turning radius. The robot must be made sufficiently large so all components
can fit inside.
The maximum size of the robot should be smaller than the inner
diameter of the pipe. The second feature is low drag force. In order to operate in a
fluid, the robot must be able to generate enough thrust to overcome the drag force.
If the drag force is low, the thrust and power requirement will be low. The robot can
then operate easily in the fluid and go further on the same power supply. The third
feature is small turning radius. In a small diameter pipe, the space for the robot to
maneuver is very limited. The maximum allowable turning radius decreases as the
size of the robot increases. If the robot can turn with minimum radius of curvature,
it can be made bigger and carry more batteries and sensing components inside. This
is highly desirable for in-pipe robots.
The following section describes the hydrodynamic design process of this swimming
robot. The idea is to design a generally highly maneuverable robot and then check
29
its performance inside a pipe. Computational tools are used to design a swimming
robot with the desired characteristics.
2.3.1
Notations and Assumptions
The notations used in the hydrodynamic analysis are the same as in [17]. The frame
of reference used in this study is fixed to the robot. In this frame of reference as
shown in Figure 2-6, the robot is seen as stationary; the flow and pipe move and
rotate about the robot.
pipe wall
Y
4j
x
z
pipe wall
Figure 2-6: Body Fixed Reference Frame used in the hydrodynamic analysis. Top
view.
The robot has 6 degrees of freedom. The necessary variables are summarized in
Table 2.3, and explained as follows. x, y, z are the linear positions, and u, v, w are
their corresponding linear velocities. 6, V),
# are the angular position about x, y, z axes
as indicated in Figure 2-6. p, q, r are their corresponding angular velocity.
Table 2.3: Notations used to describe the robot hydrodynamics
velocity
x
dx _O
d
dt
z
dz
angular position
angular velocity
P
-
position
dtt
In the simplified scenario, it is assumed that all the robot motion is within the
horizontal plane. The xy plane in the body fixed reference frame coincident with the
30
horizontal plane. It is assumed that the robot is neutrally buoyant so the gravity and
buoyancy forces cancel each other out in the z direction. To study the motion in the
xy plane only, all out of plane variables can be assumed to be zero.
z = 0,w = 0,0 = 0, V) = O,p = 0, q = 0
2.3.2
(2.1)
Design for Low Axial Drag Force
The hydrodynamics of a general swimming robot in a general straight pipe are studied
to determine the geometry of the robot. Similar to robots in the open water, the inpipe robots undergo fluid drag, lift, Munk moment and added mass effects. Unlike
robots in the open water, in-pipe robots are destabilized sideways by Venturi's Effect.
The first challenge is the fluid drag force. The drag force makes it difficult for the
robot to maneuver in and opposite to the direction of the flow and thus should be
kept low. In general, drag force, FD, is defined as follows.
1
FD ~ -pCDAOU 2
2r
where p is the fluid density,
CD
(2.2)
is the drag coefficient, AO is the projected area of
the robot in the direction of the flow and U, is the relative velocity between the fluid
and the robot.
Equation (2.2) is for open water only.
CD
is a dependent on the robot's shape
and the confined environment. Shapes such as ellipsoids have low drag coefficients. A
swimming robot experiences a larger drag force in a confined environment than in an
open fluid medium. The fluid is confined between the pipe wall and the robot. When
the fluid runs into the robot, it must accelerate and go around the robot as illustrated
in Figure 2-7. This flow acceleration resulted in an increased drag coefficient. This
new
CD
can be determined using Computational Fluid Dynamics (CFD) tools.
The cross section area AO should also be carefully selected for low drag force. As
the size of the robot increases, the gap between the robot and the pipe wall become
smaller. When the gap is smaller than certain size, the fluid will no longer be able
31
pipe wall
vehicle
pipe wall
Figure 2-7: Fluid accelerates around the robot in a pipe and increases the drag force
dramatically
to go through it fast enough. The passage of the fluid around the robot is then over
constraint, and the fluid will push the robot instead of going around it. It is then
very difficult for the robot to maneuver against the fluid. This phenomenon puts a
hard cap on the size of the robot. Smaller AO can be achieved by reducing the overall
size of the robot or adjusting the robot's cross-section profile.
2.3.3
Design for Angular Stability
The second challenge is the angular stability. As shown in Figure 2-8, when the x
axis of a robot is not aligned with the flow, or it is at a nonzero angular offset (a),
it will experience some drag, lift and Munk moment. There is always a drag force
when the robot is moving in a fluid. There is also a lift force on the robot since the
fluid speeds are different on each side of the robot. The Munk moment (M) occurs
due to the unevenly distributed fluid pressure on the robot, and it is zero on axial
symmetric shapes. The Munk moment can be calculated as follows.
1
M = -(AyY - A z)U 2 sin(2a)
2
(2.3)
Where AYY and A., are the added mass in the y direction and the added mass in
the x direction, respectively. For shapes that have the same profile in the x and y
directions, A,, will be equivalent to AYY. Thus the Munk moment is zero.
32
The effect of the Munk moment will drive the robot to increase the angular offset
in the same direction of the current angular offset until the robot is perpendicular to
the flow. This destabilizing moment scales with square of relative velocity. For the
stability and the minimum control effort during the turning in the horizontal plane,
it is preferred that the robot have the same profile in the x and y directions.
(A)
(B)
a=0
MOO
M=
ag-+
(C)
a=O
Drag
(D)
(
flowMQ
M=
rag
--
+o
M=O
Drag
Figure 2-8: Fluid forces and moments on different shapes at different angular offset.
(A) and (B): a robot with different profiles in x and y direction experiences a Munk
moment. (C) and (D): a robot with the same profile in x and y direction experiences
no Munk moment.
2.3.4
Design for Radial Stability
The third challenge is stability in the radial direction. This challenge is unique to
in-pipe swimming robots. Robots operating in open water do not have this challenge
in general. When a symmetric robot is moving in the direction of a fluid flow in open
water, it does not experience a lift force or any lateral forces because of symmetry. For
the same robot moving in pipes, it does not experience lift but experiences a radial
force. As indicated in Figure 2-9, when the robot is offset from the center of the pipe
by dy, the space between the robot and the pipe will be smaller on one side than that
on the other side. Due to continuity, the fluid on the smaller opening side will be
faster than the other side. Bernoulli's Principle predicts lower static pressure on the
smaller opening side due to faster flow. The difference in static pressure on each side
of the robot will drive the robot to the side with smaller opening and eventually it
hit the pipe wall. This destabilizing force is the basis of Venturi's Effect. It increases
33
with dy as well as the relative velocity between the fluid and the robot, and it has a
tendency to force the robot to move away from the centerline of the pipe.
Venturi's Effect can be reduced in two ways. The first method is limiting dy by
increasing the size of the robot. If the robot is wide enough, it will not be able to
move left and right much. thus dy will be constrained in a small range. However,
as the robot gets wider, the cross-section area AO would normally increase as well
as the drag force. The solution to reduce drag force is to put ducts through the
robot. Instead of going around the robot, the fluid can go through the ducts. The
second method is to maintain a low relative velocity with the flow. When the robot
is floating, the relative speed is low. The Venturi's Effect is then minimal, and the
robot can easily correct its heading direction.
High Speed, Low Static Pressure
pipe wall
flow
Vent
Force
Low Speed, High Static Pressure
pipe wall
Figure 2-9: Illustration of Venturi's Effect on an in-pipe robot
2.3.5
Design for Minimal Turning Radius
The shape of the robot can be designed for minimum turning radius through the
study of the first order approximation of the hydrodynamic forces. The hydrodynamic
force about the geometric center of the robot in the x direction can be expressed as
X(X, y z, 0, 0, 0, U, V, W, p, q, r, i, , 11b, P, ,.
The same definition can be applied
to hydrodynamic force in the y direction, Y, and hydrodynamic moment about the
z axis, N. Since we assume the robot motion is confined to the horizontal plane,
hydrodynamic forces and moments that are out of the horizontal plane can be assume
to be zero. This is the case if the robot is properly balanced and the flow in the pipe
is not rotating.
34
The hydrodynamic forces are the net forces on the robot. The momentum principle
says the change of momentum is equal to the net force:
+ rZG)p - (q 2 + r2 )xG]
(2.4)
Y = m[b + ru - pw + rXG - PZG + (rzG + pxG)p - (r 2 + p 2 )YG]
(2.5)
X
=
m[ih + qw - rv + 4ZG -
yG + (qyG
N = IzxP + Izy4 + Izzr + (Iyy - Jxx)pq + Ixy(p 2
-
+ m[xG () +ru
q2 ) + Iyzpr - Ixzqr
-
pw) - YG(it + qw - rv)
(2.6)
where m is the mass of the robot. x, y, z are defined as small position deviations
from the zero position in the x, y, z directions. it is the linear acceleration in the
x direction) is defined as the time derivative of u (linear speed in the x direction).
XG, YG, ZG is the position of the center of mass with respect to the center of the
geometry. Iz, Iy,, Iz, are the moment of inertia about x, y and z axes. Ixy is the
coupling between different axes. The hydrodynamic forces can be linearized following
the method described in [17]. the first order approximation of the hydrodynamic force
X can be calculated as follows.
X
=
Xxx+Xyy+Xzz+XoO+XpO+XOb+Xu+Xv+Xw+Xp+Xq+Xr+Xit
+ Xbi + Xjbh + Xpp + X44 + Xtt + . .
(2.7)
The meanings of the hydrodynamic coefficients are summarized in Table. 2.4.
Table 2.4: Physical meanings of hydrodynamic coefficients
Coefficient
Physical Meaning
X, Xy, X, Xo, X0, X, hydrodynamic Force in the x direction due to nonhomogeneous distribution of the fluid property and Venturi's Effect(XY, Xz).
Xu, Xv, Xw, Xp, Xq, Xr damping effect
X, X-, X,, Xp, X4, X added mass
35
Similarly, Force Y and moment N can be calculated with Equations (2.8) and
(2.9).
Y = Yx + YY + Yzz + Yo + Yp
+Y,6
+ Yu + Yv + Yu
+Y~p+Yqq + Yr + Ya
+ Yi) +Yob +YpP + Y44 + Y
.
(2.8)
N = Nxx+Nyy+Nz z+NoO+N N+No+Nuu+Nv+Nw+Npp+Nqq+Nrr+Nit
+Nbi+Nbs +NpP+N44+N4+...
(2.9)
Most of the hydrodynamic coefficients are dependent on the geometry of the robot.
To define the proper robot geometry for the high maneuverability from those coefficients, one need to first simplify those equations. In the case in straight sections with
steady flow, the fluid can be approximated as homogeneous so Xx, Xy, X0, Xp, XO become zero. In the first order approximation the higher order terms can be neglected
as well. Similar assumptions apply to Y and N. In the 2D case studied in this thesis,
the robot is assumed to move in the horizontal plane (xy plane) only, and all out
of plane motion are assumed to be zero referring to Equation (2.1). Including input
forces and moments, the hydrodynamic equations then become as follows.
X = Xuu + Xev + Xrr + Xa6 + X,) + Xtt + Xzput
(2.10)
Y = Yy + Yu+ YV + Y,.r + Yj + yoh + Y + Yinput
(2.11)
N = Nuu + Nov + Nrr + Na6 + Nb+i) + N
+ Nin u
(2.12)
Where Xinpt Yinput and Ninpt represent the input forces and moment generated
by the acutators. Notice that the Venturi's force Yy remains present under those
conditions.
36
And the momentum equations become
X
=
m[it - rv - TYG + rxG]
(2.13)
Y
=
m[i + ru + rxG - r2YG
(2.14)
N = Izzi + m[xG(Lb + ru) - YG(U - rv)]
(2.15)
By decoupling the motions in different axes it is possible to make the robot capable
of turning at minimum radius. In this general form of hydrodynamic equations and
momentum equations, the motions in different axes can be decoupled if a few of the
coefficients are zero. By decoupling the motions in different axes, the robot will be
able to perform maneuvers such as spinning. When the robot is spinning, its turning
radius is zero.
The robot should have multiple planes of symmetry in order to decouple its motion
in different axes. If the robot has multiple planes of symmetry like a circular plate
or a sphere, any motion in the x direction will not result in hydrodynamic forces in
the y direction or torque in yaw direction. The same thing applies to motion in the y
direction and rotating in the xy plane. Therefore Xv, Xr, Xe,, X,, Y, Y, Y&, Ye, Nu,
No, N, Ni, are all zero when the robot have the same symmetric profiles in xy, yz and
xz planes. Furthermore, the added mass in yaw direction N can be approximated
zero if the robot has a circular profile in the horizontal plane.
The coupling among different axes can be further reduced.These two centers should
at least be the same in the XY plane, thus
XG =
0, YG = 0. Then the hydrodynamic
equations and momentum equations for a robot with the same symmetric profiles in
xy, yz and xz planes are expressed as follows.
X
=
m(ii - rv) = Xuu + Xuit + Xinput
Y = m(b + ru) = Yy y + Yv + Y
N = Izzi = Nrr + Nznput
37
+ Ynput
(2.16)
(2.17)
(2.18)
2.3.6
Conclusion of Hydrodynamic Design
To summarize the above hydrodynamic analyses, the desired robot geometry must
meet three criteria. The robot body should be streamlined, wide and symmetric. A
streamlined body guarantees a low drag force on the robot. The robot then requires
low thrust to overcome the fluid drag and perform maneuvers. The robot should be
wide so the space between the robot and the pipe wall is small. When lateral motion
occurs, the Venturi's force developed over this small space is small. It will take little
effort for the robot to overcome the Venturi's force and maintain its position along
the centerline of the pipe. A wide geometry also allows more space inside the robot
and makes it easy to add electronic components. The robot should be symmetric.
It decreases the coupling effect between the motion in different axes and allows the
robot to turn at minimal turning radius.
Figure 2-10: Isometric view of the robot body
A design of the robot body as shown in Figure 2-10 and Figure 2-11 was selected.
As shown in Figure 2-10, the robot is in an ellipsoid shape with two ducts through
its body. It has a circular profile in the horizontal plane, and a streamlined oval
shape in the vertical plane. As shown in Figure 2-11, the width of the robot W is
the largest dimension of the robot. Therefore when the robot is deployed into a pipe,
38
d
d
dm
H
W
Figure 2-11: Frontal view of the robot body
there will be little space between the robot and the pipe wall in the horizontal plane
for Venturi's force to develop. In order for the pipe fluid to pass the robot easily
and create low drag force, more space between the robot and the pipe wall is needed.
Thus the height H of the robot is made smaller than the width W, as indicated in
Figure 2-11. When the robot is swimming in a pipe, the majority of the pipe fluid
can pass the robot from top and bottom.
The two ducts through the robot body is mirror image of each other. They reduce
the frontal cross-section area of the robot and thus lower the drag force on the robot.
The distance between the two ducts is 2d. Each duct is also symmetric about its
centerline, and their walls had a parabolic profile. Parabolic ducts created a smooth
transition for the flow to enter the ducts. The duct has the smallest cross sectional
diameter in the middle section, and the diameter there is d,. Actuation systems such
as propellers can be placed inside ducts.
A robot of this design can turn at a very small turning radius. The robot has
three planes of symmetry, namely xy, yz, and xz planes. It has a circular profile in
the xy plane or the horizontal plane. This geometry decouples the robot's motions in
39
different axes. With proper actuation, it can turn in the horizontal plane at a very
small turning radius.
The dimensions in Table. 2.5 are chosen for the robot prototype. When choosing
dimensions, internal space and clearance with the pipe are considered. With these
dimensions, there is much space inside the robot for placing electronic components.
The Width of the robot is 85 mm and slightly smaller than the target pipe diameter,
100 mm. When placed along the centerline of the pipe, the robot has 7.5 mm clearance
from the pipe wall on the left and right sides. This clearance allows the robot to travel
through the pipe without being affected by small obstacles.
Table 2.5: Dimension of the robot
Parameters
Robot length
Robot width
Robot height
Distance from the robot's center
Minimal cross-section diameter
Duct length
2.4
Values
85 mm
85 mm
60 mm
30 mm
19 mm
65mm
Summary
A swimming robot design is selected for this in-pipe robot. A swimming robot can
operate reliably in pipes that have uneven surfaces and obstacles inside. This robot
has an ellipsoid shape and two ducts. This design allows the robot to operate in the
fluid flow while experiencing a low drag force. It also allows the robot to turn with a
very small turning radius.
40
Chapter 3
Actuation System
The actuation system in this robot is presented in this chapter. Micro RIM propellers are used as the actuation system because they are compact, powerful and
safe. All aspects of the micro RIM propeller, including its design, sizing, fabrication,
performance and characterization, are presented in this chapter.
3.1
Actuation System Alternatives
The robot needs a set of compact, powerful and safe propulsion systems. The ideal
propulsion systems must be compact and easy to integrate into this small robot shown
in Figure 1-2. They must provide enough thrust for the vehicle to overcome the fluid
forces and perform maneuvers. The propulsion systems should not fail when the robot
collides with the pipe walls or obstacles. Otherwise the robot loses its mobility, and
it may block and even contaminate the product in the pipe.
Underwater propulsion consists of external and internal actuation systems. External actuation systems have moveable parts outside of a vehicle. An example of an
external actuation system is the regular propeller. The propellers are usually attached
to the sides or the back of a vehicle. Internal actuation systems are fully enclosed in
the vehicle. Examples of the internal actuation systems are micro pumps and ducted
propellers shown in Figure 1-2. When integrating a micro pump into the robot, it
requires only two ports on the robot body, one being the inlet port and the other
41
the outlet port. Ducted propellers are propeller-based systems placed inside a duct
through the vehicle. The propeller can be either a regular propeller driven from its
hub, or a RIM propeller driven from the rim [12, 21].
External actuation systems are not safe to use in confined environments. In confined environments, the robot may collide with the boundaries of the environments
such as walls in the pipes. When colliding with walls, external actuation systems are
likely to get damaged. Rigid propeller blades can easily get damaged and flexible
blades will deform and lose their thrust outputs.
Compared to the external systems, an internal actuation system is a more reliable
choice for in-pipe robots. The major advantage of the internal actuation system is
safe operation. Internal propulsion systems are contained inside the robot and they
are protected by the robot shell when collision happens.
Ducted RIM propellers are chosen for the robot shown in Figure 1-2. As an
internal actuation system, they are safe to use in confined environments. Similar to
regular propellers, they can be sized to fit this robot while providing a relatively large
thrust output.
In comparison, the other kind of internal actuation system, micro
pumps, are not powerful enough when they are small. For example, one of the most
powerful pump that can fit into this robot is the TCS M400S from TCS Micropumps
Ltd, and it can produce a thrust of up to 0.25N [16]. Considering the size and possible
maximum thrust, ducted RIM propellers are the best internal actuation system for
this robot.
3.2
Actuation System Design
In the design, the robot integrates two ducted RIM propellers. As shown in Figure
3-1, two mirror image ducts are created throughout the robot body. Each duct is
front-back symmetric so the robot can have equal performance in both directions.
Each duct is also symmetric about its centerline, and their walls have a parabolic
profile. Parabolic ducts created a smooth transition for the flow to enter the ducts.
Two reversible, mirror image propellers are placed in the middle of the ducts.
42
This actuation system allows the robot to maneuver in the horizontal plane. Figure 3-2 shows a case when the robot is propelled downstream. Both propellers are
intaking fluid from downstream, and duct openings B and D are the inlets. If the
propellers are operating at the same speed, the robot will be propelled downstream.
If they are operating at a different speed, they create a differential thrust that steers
the robot in the horizontal plane. When the propellers reverse their rotation, duct
openings A and C become the inlets and the robot can be propelled upstream. The
two propellers can be rotating in different directions so duct openings A and D become
inlets. The robot is then propelled to turn fast.
Figure 3-1: Isometric view of the robot with two ducted RIM propellers
3.3
Propeller Sizing
The thrust output requirement for this robot design is determined using Computational Fluid Dynamics (CFD) simulations. The simulated robot is that of an ellipsoid
shape with two ducted RIM propellers inside, as shown in Figure 3-1. Several simulations were performed on robot designs with different duct profiles. A particular
43
upstream
robot shell
downstream
B low
flow out
flow in
C
' D
Figure 3-2: Schematic of the horizontal cross section view of the robot with two
ducted RIM propellers
robot with parameters in Table 3.1 is presented. These parameters are the same as
that in Table 2.5. It experiences the lowest fluid forces and thus the lowest thrust
requirement. Two scenarios are considered for this design to determine the largest
fluid force acting on this robot. Scenario 1 considers the robot moving in a straight
pipe, and scenario 2 considers the robot maneuvering at a Tee junction.
Table 3.1: Parameters of the simulated robot
Parameters
Robot length
Robot width
Robot height
Distance from the robot's center
Minimal cross-section diameter
Duct length
3.3.1
Values
85 mm
85 mm
60 mm
30 mm
19 mm
65mm
Scenario 1: Moving in A Straight Pipe
The simulation is set up as shown in Figure 3-3. The robot is placed stationary at
the center of a circular pipe of diameter D and length 2LP. The ducts of the robot
are aligned with the direction of the flow. The fluid flows from the inlet to the outlet.
At the inlet, the flow is assumed to have a uniform velocity U. Since the robot is
stationary, the relative velocity between the robot and the fluid, U, = U.The relative
motion, between the robot and the fluid flow, results in a fluid drag force FD on the
44
robot. The goal of this simulation is to find the maximum value of FD for all desired
maneuvers. When the robot is moving in a straight pipe, it should float, brake or
maintain a stationary position. All of the desired maneuvers are in the direction of
the fluid, as indicated in Figure 3-3. The fluid drag force scales with the square of
the relative velocity. The relative velocity and FD are the largest when the robot is
stationary.
inlet: flow speed U
I
LPV
I
WVW
I
V
I
robo
FD
L
C
D
outlet:
zero pressure drop
Figure 3-3: Cross-section view of the pipe and the robot in the simulation. The robot
is placed at the center of a circular pipe of diameter D and length 2LP.
Three assumptions are made in this simulation. First the flow is assumed to be
fully developed in order to find a single steady state value of FD. Fully developed
flow can be guaranteed in the simulation by setting the distance LP from the pipe
inlet to the robot multiple times larger than the diameter of the pipe. The second
assumption is that the only significant fluid force in this scenario is FD along the pipe
axial direction. The robot is symmetric and it is placed in the center of the pipe,
the sum of fluid forces in the radial direction should be zero. The third assumption
is that pressure drop along this pipe can be neglected. This section of the pipe is
short when compared to the total pipe network, and the pressure drop is therefore
negligible. Consequently, the average flow speed will be constant along the pipe.
45
Multiple simulations are conducted and their setup parameters are described. ANSYS Fluent R14.5 software is used to perform CFD simulations. The pipe parameters
considered in this CFD simulation are summarized in Table 3.2.
Table 3.2: Parameters considered in the CFD simulation
Parameters
Pipe Diameter D
Flow speed U
Distance L
Reynold's number Re
Values
100 mm
1 m/s
4m
100,000
The CFD simulation predicts FD in the axial direction of 0.722 N. This value
is computed using the function calculator in the ANSYS Fluent software. This drag
force attempts to push the robot toward the outlet. It is the only significant hydrodynamic force in this scenario, and it is more than 100 times bigger than the fluid force
in the radial direction. The close-up horizontal cross section view of the simulation
is shown in Figure 3-4. In this figure, the fluid flows into the pipe from the top. The
flow in front of the robot has an average velocity of 1 m/s. It accelerates to a speed
of 2.135 m/s when it is going through the duct.
3.3.2
Scenario 2: Turning at A Tee Junction
A second CFD simulation is performed to find the fluid forces on the robot when it
is turning at a Tee junction. The simulated scenario is shown in Figure 3-5. The
Tee junction connects three straight pipe sections of diameter D and length Lp. The
robot is located in the center of the Tee junction at the instant of performing a turn.
It is assumed that a fluid flow of uniform speed U enters the inlet. The fluid then
split into two streams, one flowing towards the outlet 1 and the other to outlet 2. The
ducts of the robot are aligned with the direction of the flow at the inlet. The robot
experiences an axial drag force FD and a side force Fs. The goal of this simulation
is to determine the values of these two forces. For consistency with the straight pipe
scenario, the same parameters in Tables 3.1 and 3.2 are used in this simulation.
46
Figure 3-4: Horizontal cross-section view of the simulated robot placed in the fluid
Three assumptions are made in this simulation. The first two assumptions are the
fully developed flow and zero pressure drop in this simulated pipe section. They are
assumed for the same reason described in Section 3.3.1. The third assumption is that
the two outlets have the same pressure. The fluid is driven by its momentum instead
of pressure difference. It is expected that more flow is going straight to outlet 1 than
turning into outlet 2.
The CFD simulation predicts a reversed drag force. A close-up view of the flow
field in terms of velocity vectors is shown in Figure 3-6. The drag force is -0.282 N,
so it is pushing the robot upstreams toward the inlet. Drag force is in the reversed
direction because of the static pressure increase at the Tee junction. As shown in
Figure 3-7, the fluid flow expands and the flow speed decreases as the fluid enters the
Tee junction. The flow speed U decreases due to the conservation of mass, and thus
the static pressure increases. At location B in Figure 3-7, the flow speed is higher and
the static pressure is lower than that at location C. This static pressure difference
will push the robot to move toward location B or toward the inlet. This reverse drag
force effect can help the robot slow down when it arrives at a Tee junction. At the
47
outlet 1:
zero
pressure
T
drop
LP
D
>
>
LP
FD
A-
outlet 2:
D
F_
b
zero
pressure
I
L
drop
A
I
CU
A
A
A
I
I
I
LP
inlet: flow speed U
Figure 3-5: Cross-section view of the Tee junction and the robot in the simulation.
The robot is placed at the center of the Tee junction.
same time, a robot can specifically look for this reverse drag effect and use it as an
indicator of the Tee junction.
The CFD simulation also predicts a Venturi's force. The side force on the robot is
predicted to be -0.337 N. This side force consists mainly of the Venturi's force which
always pull the robot closer to pipe wall A and consequently prevents the robot from
moving toward outlet 2. Since the reversed drag force helps the robot slow down, the
robot can take advantage of it during maneuvers at the Tee junction. A robot needs
to overcome the radial force of at least 0.337 N in order to make it to the side pipe.
Furthermore, the fluid forces were evaluated for the ducted robot at different
orientations. Since there were ducts in the robot, it was no longer symmetric about
the vertical axis. The drag and side forces would change as the robot was turning
inside the Tee junction. The same CFD simulation were performed for the robot at
different angular position in order to find how the fluid forces changed.
The results show that the drag force changes significantly during the turn. The
48
inlet
0.050
0
0.025
-
0.100
(M)
0.075
Figure 3-6: Flow visualization for the robot inside a Tee junction. FD and force Fs
are measured.
results are plotted in Figure 3-8. A positive angular position meaning the robot is
turning left in Figure 3-6. The maximum drag force was predicted to be 0.287 N and
pointing toward the inlet when the robot is at a 10 degree offset. The drag force on
the robot flipped its direction when the robot turned more than 20 degrees to the
left. At this angular offset, flow separation occurs at the ducts on the robot and it
results to a net pressure pointing toward inlet 1.
The side force changed as the robot was turning but it maintained its direction.
The Venturi's effect kept attracting the robot to the wall and prevented it from
entering the side pipe for all robot's possible angular positions. The robot must
be able to overcome this Venturi's effect in order to move into the side pipe. The
49
inlet
002
0.02s
0.050
~
0100 (m)
0.07s
Figure 3-7: Flow visualization for the robot inside a Tee junction. Location B has
higher flow speed and lower static pressure than location C.
maximum lateral force was predicted to be 0.502 N and pointing away from the side
pipe when the robot is at a 30 degrees angular offset.
These two hydrodynamic simulations predicts that the maximum fluid force on
this robot is 0.722 N. This drag force is expected when the robot stops inside the 1 m/s
flow in a straight section. RIM propellers need to be customized for this robot. After
surveying the market, it is found that most of the past and current developments of
RIM driven propellers are of large diameters. The smallest one is 70 mm in diameter
121]. A pair of RIM propellers need to be built to fit into this robot and generate a
total thrust of more than 0.722 N.
50
0.4
0.3
0.2
0.1
Z
0
-20
to
40
60
80
100
-0.2
M
-0.2
-Drag
-0
-0.5
-Lift
-0.6
Angular position(degrees)
Figure 3-8: Simulated force on the improved robot at different angular positions
3.4
Design and Fabrication of the RIM Propeller
The RIM propeller consists of two major components: the stator and the rotor. As
shown in Figure 3-9, the stator is of a ring shape, and it consists of an array of coils.
The rotor is placed in the center surrounded by the stator. It consists of the propeller
blades and the permanent magnets.
The center of the rotor is hollowed out and
replaced with propeller blades. Permanent magnets in alternating sequence cover the
circumference of the rotor. When alternating electrical current is input to the coils
in the stator, it generates a alternating magnetic field that forces the rotor to rotate.
When designing the RIM propeller, size, power consumption and thrust output
were considered. The desired parameters of the RIM propeller is summarized in Table
3.3. The size of the stator is determined as it must fit into the ellipsoid shaped robot
shell of dimensions listed in Table 2.5. The rotor must align with the duct described
in Table 3.1. Since the robot will be powered by batteries, the RIM propeller must be
efficient. It should meet the thrust requirement while consuming a reasonable amount
of electric power.
51
STEEL
RING
ROTOR
MAGNET
DC
Di
STEEL
CORE
CO -1L
WINDING
Figure 3-9: Stator and rotor assembly of the RIM propeller
Table 3.3: Desired parameters of the RIM propeller
Parameters
Do
Description
Max allowable stator outer diameter
Values
36 mm
HRIM
Max allowable thickness
15 mm
Di
PRIM
SF
Rotor inner diameter
Max allowable power consumption
Output safety factor
Target thrust
19 mm
10 W
1.1
0.4 N
FT
3.4.1
Stator
The first component of the stator is the stator core. The stator is very similar to that
of a conventional motor. It is a ring with multiple "T" shaped extrusions that hold
the coils, as shown in Figure 3-9. The stator core should be made out of material of
a high permeability. Thus the magnetic field from the coils can be concentrated to
achieve higher motor efficiency. Each "T" shaped extrusion becomes a pole once coils
are wound on it. The stator core connects all poles together. It acts as a channel
to guide the magnetic field and preserve the magnetic field energy. It increases the
overall efficiency of the motor. It is desired to have more poles for smooth torque
output.
52
The stator core is manufactured in layers. It is made out of 6 layers of 24 gauge
non-oriented laminated steel. This construction reduces the formation of eddy currents. Each layer of the laminated steel is cut to the shape using a waterjet. The
outer diameter of the stator is 36 mm. The outer ring is 2 mm thick. The number of
poles is selected to be 12 due to size constraints. Each pole is 2 mm in width. The
inner diameter of the stator is 25.5 mm.
Coil windings are added to each pole. On each pole, it is also desired to have as
many turns of coil as possible for the best magnetic field generation. With the size
constraint considered, 30 gauge magnetic copper wires are wrapped around each pole
and the maximum number of turns is 40. The actual thickness of the stator with all
coil windings is approximately 8mm.
3.4.2
Rotor
The construction of the rotor is shown in Figure 3-10. It is a ring with magnets attached outside and propeller blades inside. Each two adjacent magnets have different
polarizations. It is desired to have as many magnets as possible on the rotor, so it
will provide evenly distributed magnetic field strength along the circumference of the
rotor. As a common practice of motor design, the number of the magnets must be
an even number and must not be equal the number of poles (12) of the stator. Slots
are designed to hold the magnets.
A set of small, flat and powerful magnets are selected for the rotor. Flat rectangular magnets, NdFeB Grade N42 block magnets from K&J Magnetics, Inc, are
selected for its size and magnetic strength. Each of the magnet is measured 6.350 x
3.175 x 0.794 mm (1/4 x 1/8 -x 1/32 in). Given that the inner diameter of the rotor
is fixed at 19mm, a maximum of 14 magnets can fit onto the outer circumference of
the rotor.
53
Figure 3-10: Design of the rotor
3.4.3
Propeller Blade
The propeller blades are designed with the software OpenProp v3.3.4[101. The software could generate propeller blade profiles based on multiple theories including Blade
Element Theory. Once operational condition and desired output is specified, the software generates the optimal propeller blade that can be output into CAD.
The specifications for the RIM propeller design are summarized in Figure 3-11.
Two parameters, the rotor diameter and required thrust, are set to be the same as
they are in the design specifications in Table 3.3. The rotor speed is chosen to be
similar to that of conventional motors. The ship speed should be the fluid flow speed
at the propeller. This speed is always higher than the normal flow speed in this pipe
because flow accelerates when it enters the ducts. In a pipe with 1 m/s flow, the
flow speed at the propeller is 2.1 m/s as shown in Figure 3-4. Multiple designs using
different values for other parameters including number of blades, hub diameter and
r/R are tried. The parameters of the final design are shown in Figure 3-11. The
hub diameter is made small since there is no hub in the RIM propeller. The lowest
r/R value corresponds to the relative size of the opening in the center of the RIM
propeller. Default values are used for XLma, Cd and tW/D, skew and Xs/D.
54
mas uuewgn vm uu
Nun6er at blades:
-
rR XCLmaI Cd
4
00D Skew
05 .011154 0.01276 0
0.4625 j011154 0.02048 0
X*M
0,0191
0.2
03
Rwpbrdhrust (N):
0.4
0-4
0.425 .011154
0-0282
0
0
SW peed
21
0.5
0.3875 0.01115 0.03592
0
0
0.006
06
0.01115 0.04364
0
0
1023
07
03125 0.01115 0.05136
0
0
S radlpeneb:
20
0.8
0.275 0.01115 0.05908
0
0
8 drdwM panels:
20
09
02375 0.01115 0.0668
0
0
0-95 0.21875 10011151 0.07066
I 0,2 01115107452
0
0
Raion speed
4500
odlmi"a r (m):
(nae):
Hub dMa r (m):
Fhaldsnsay
sp.
ThrustRatio:
r
0008
J
V/nD.
L - onejgaRV
u4
0 75
CT.
18879
KT
WVs
-
uUou@ propaae
EHub
~Vlacaus forces
~
~
JOpmuawaP'.
IPsrormancec.
ANrfoilltyp.n
M"7 M
P
J7I
II
typo
RACA6SAOI
Tools
D4)
Flsnae
2904
0 140625
Load
ductD/propD:
vuuus-
0 Turbie
0,63662
a Tl(rho-n2e
VaNs
0
0
ENon-dwhnnsional Paramemtrs
1
Dud section drag
0.35
nsnow rues
SaM Run OpenPr..
Figure 3-11: Specifications input to the OpenProp software
An optimized four-blade propeller was generated by the OpenProp software. The
blade profile was then output into Solidworks to complete the rotor model as shown
in Figure 3-12. Several different versions of the blades were manufactured, and they
have different center opening sizes. All of them were experimented and their thrusts
at different speeds were measured. The details of the experiment are described in
the Section 3.5. The results are summarized in Figure 3-13. While all rotors can
produce 0.4N at around 4500 rpm, their maximum thrusts are different. The rotor
with smallest center opening diameter, DC in Figure 3-12, can obtain the highest
thrust. In the final design, a rotor with DC = 3.8mm is used. It generates a high
maximum thrust, and its big opening allows debris to get through without damaging
the propeller.
The rotor including the four blades and the exterior ring are 3D printed as one
piece. The 3D printer used here is the Stratasys Fortus 250mc FDM printer. It is
configured to print ABS thermoplastic at a slice height of 0.178mm. The ring of the
rotor is designed to be 1.5mm thick so the 3D printed part can be rigid. The inner
diameter of the rotor is 19 mm and the outer diameter is 22.5 mm after the magnets
55
Figure 3-12: CAD model of the rotor with optimal blades
0.6
0.5
0.4
Z4-
E 0.3
E
0.2
0.1
0
0
1
2
3
4
5
6
7
8
9
Center Openning Diameter (mm)
Figure 3-13: Plot of maximum thrust measured on rotors with different center opening
size
are tightly fit into the slots. Since the inner diameter of the stator is 25.5 mm, there
is a 1.5 mm clearance between the rotor and the stator.
The contact between the stator and rotor is treated with special care. After the
magnets are placed, the rotor is wrapped with a thin Permacel® tape to prevent the
magnets from falling out of rotor assembly. The Permacel® tape also makes the outer
surface of the rotor smooth. On the inner surface of the stator, the same tape was
applied to create a smooth contact with the rotor.
The manufactured RIM propeller meets the size requirements.
parameters of the manufactured RIM propeller are listed in Table 3.4
56
The measured
Table 3.4: Measured parameters of the RIM propeller
Parameters
Stator outer diameter
Stator inner diameter
Stator thickness
Rotor outer diameter
Rotor inner diameter
Rotor depth
Stator weight
Rotor weight
Total weight
3.4.4
Values
36 mm
25.5 mm
8 mm
22.5 mm
19 mm
12 mm
14.3 grams
1.7 grams
16 grams
Bearing
A bearing is designed to properly support the RIM propeller to function consistently.
The bearing should suspend the rotor and maintain the uniform air gap between the
stator poles and rotor poles. It should provide stability to the rotor in both radial and
axial directions. The bearing should also minimize the friction on the rotor during
the operation.
(A)
(B)
(C)
Figure 3-14: Three different kinds of bearings for the RIM propeller
The three different kinds of bearings considered are shown in Figure 3-14. The
design A uses a "C"-shape clamp to hold onto the exterior of the stator and have
two rings in the front and back to support the rotor.
Once the stator is put in,
the "C"-shape clamp acts like a reference for the rotor. The clamp also follows the
57
curvature of the robot so it provide seamless integration of the RIM propeller into the
robot. The rotor is placed in between the two rings. On each of the ring, there are
two perpendicular surfaces that will be in sliding contact with the rotor. The vertical
surface of the ring is in contact with the front or the back of the rotor, maintaining the
rotor in its axial position. The circular surface of the ring will hold the rotor inside,
maintaining the rotor in its radial position. This design theoretically can provide
perfect radial and axial bearings to the rotor. However, there are always defects in
the manufactured rotor and stator. The stator is not perfectly circular, and thus it is
not a great reference for the "C"-shape clamp or the rotor. This design is not flexible
enough to accommodate for manufacturing errors. During operation, the propeller
assembly along with the bearing vibrates. Vibrations can damage the sensors on the
robot and the robot itself.
The design B has an improved bearing with some flexibility for adjustment. Instead of using a "C"-shape clamp and holding the stator with its spring force, the
bearing is divided into front and back pieces. The stator and rotor can be placed
inside more easily. Each circular ring in design A is split into two pieces. The vertical
surface of the ring still maintains the axial position of the rotor. Behind the vertical
surface, a hole of a hybrid shape between triangle and circle will support the outer
circumference of the rotor at three locations. These three locations are on the straight
part of the hole, and they can be filed to loosen the constraint on the rotor. With this
design, the bearing can adapt to the manufacturing errors in the stator after some
careful adjustment. However, the adjustment is irreversible and the accuracy is hard
to control. Multiple copies of this bearing were made before one of them was found
that worked well for the propeller.
The design C improves upon the previous two designs and adds more control to
the adjustment. Three holes are drilled in the radial direction on the front of the
bearing at location 1, 2 and 3 shown in Figure 3-14. They are 120 degrees apart from
each other. The same three holes are made on the back of the bearing. Six set screws,
each one of which has a tiny Teflon ball on top, are inserted into those holes. When
the rotor is placed inside the bearing, the Teflon balls will contact the circumference
58
of the rotor. By adjusting the six setscrews, one can move the rotor around until
it has uniform gap on all sides with the stator. This process is repeatable and the
constraints can be adjusted for the best performance of the RIM propeller. The final
assembly is shown in Figure 3-15. In addition to adding setscrews, the two vertical
supports are removed too because they are structurally weak. Instead, The front
and back potions of the rotor are replaced with 2mm thick Teflon rings of the same
diameter. These two Teflon rings provide low friction contact between the rotor and
the robot wall. The Teflon rings are also in contact with the six Teflon balls. During
operation, the RIM propeller with this support experienced little vibration.
Figure 3-15: The RIM propeller placed inside the bearing of design C. Three set screws
are placed inside 3 holes. The back side of the bearing has the same configuration
3.5
Performance
The performance of the RIM propeller were evaluated experimentally.
The RIM
propeller was commanded to run at all possible speeds. The thrust and power consumption at each speed were recorded. The performance of the RIM propeller was
59
then compared with the desired performance in Table 3.3 to check if it met the requirement.
3.5.1
Experiment Setup
The experiment was setup to measure the thrust and rotational speed of the RIM
propeller. The setup is shown in Figure 3-16. A dynamometer was used to monitor
the thrust generated by the propeller, an encoder to measure the propeller's rotational
speed, and a weight to stabilize the setup underwater. The RIM propeller was placed
inside a holder and hanged down from the dynamometer. A Vernier dynamometer
was used. In the holder, there was an optical encoder monitoring the revolutions of
the propeller. It was made out of an infrared LED and an infrared phototransistor.
The infrared emitted diode was placed on top of the RIM -propeller and pointing
down, while the phototransistor was placed in the bottom of the RIM propeller and
pointing up. Every time a blade moved between these two components, a drop in
voltage reading across the phototransistor would be observed and used to record the
revolutions of the RIM propeller. 10 cm below the RIM propeller was a heavy weight.
This weight helped stabilize the test setup in water. Very thin cables were used for
all connection and they induced minimal disturbance to the fluid.
A power and control system for the RIM propeller was also created. The RIM
propeller is powered by a 7.4V power supply. A Turnigy Plush 6A electronic speed
controller was used to control the RIM propeller. This speed controller was connected
to an Arduino mini Pro 328 5V micro controller. The Arduino sent commands to
the speed controller using its servo library. The exact input-output mapping for this
Arduino, speed controller and RIM propeller was unknown before the experiment,
but it was identified based on the results from this experiment.
The experiment setup was placed inside a water loop during the test as shown
in Figure. 3-17. The pipes used in this experiment setup was 10 cm in diameter, the
same as the pipe network the robot was designed for. Water fills the pipes up to the
dynamometer. The loop structure allowed water to circulate and form a steady flow.
Without a loop, the water stream coming out of the RIM propeller would confront
60
Figure 3-16: The experiment setup for testing RIM propellers
the flow coming back from the bottom and form unstable vortices. The measured
thrust would oscillate and be inconsistent. A loop acts like a long channel, and it
facilitates the development of the flow and results in more accurate thrust readings.
3.5.2
Experiment Results
The performance of the propeller in terms of rotational speed, thrust and power
consumption were evaluated in the experiment.
The results are shown in Figure
3-18, Figure 3-19 and Figure 3-20. Thrust increases quadratically with rotational
speed as in most propellers. The power consumption scales approximately linearly
with the thrust. The maximum rotational speed is about 5550 rpm. The maximum
thrust is about 0.43 N. The maximum power consumption is about 7.4W. The RIM
61
Figure 3-17: Picture of the experiment for testing RIM propellers
propeller reaches 0.4 N of thrust between 5350rpm and 5550 rpm. At this speed and
thrust output, it consumed about 7.1W. The RIM propeller met the performance
requirements listed in Table 3.3.
3.6
Propeller Characterization
The RIM propeller can be fully characterized from the experimental results. There
are two important characteristics of the RIM propeller. The first one is its inputoutput mapping. It is important to know how to control the speed and thrust of
the RIM propeller. The second characteristic is the dynamicd of the propeller. The
dynamics of the RIM propeller is an important part of the dynamics of the robot.
The former must be studied before one can design a control system for the robot.
62
0.5
0.45
0.4
S
0.35
2
0.3
-
0.25
0
0
0
.00
.0
0.2
0
0.15
0
0
0.1
0.05
0
1000
2000
3000
4000
5000
6000
Rotation Speed (RPM)
Figure 3-18: Plot of rotational speed and thrust
6000
5000
4000
0.
3000
0
1000
0
0
1
2
3
4
5
6
7
8
Power Consumption(W)
Figure 3-19: Plot of rotational speed and power consumption
3.6.1
input-output mapping
The input-output mapping of the RIM propeller can be identified from the experimental results. It is the mapping between Arduino input and the RIM propeller
output.
The Arduino send out servo commands to the speed controller. A servo
command is a numerical value usually linked to angular position or angular speed of
the servo device. In the experiment, servo commands from 0 to 180 was tested and it
was found that values from 68 to 120 activated the speed controller. Command values
between 75 and 120 would make the RIM propeller turn, and it turned faster as the
command value increased. The propeller speed and thrust saturated when the command value surpassed 98. The mapping between input command and steady state
rotational speed, input command and steady state thrust are shown in Figure 3-21
and Figure 3-22. In between input command of 78 to 98, the thrust increased almost
63
0.5
0.45
0.4
2.0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0
1
2
3
4
5
6
7
8
Power Consumption(W)
Figure 3-20: Plot of thrust and power consumption
6000
5000
S4000
0C 3000
C
0
*9g.
m 2000
0
1000
0
70
75
80
85
90
95
100
105
1110
Input Command
Figure 3-21: Plot of input command vs measured steady state rotational speed
linearly with the input command, and their approximate mapping can be expressed
as follows:
Thrust = 0.0185 * (Command - 76)
3.6.2
(3.1)
Dynamics of the RIM propeller
The dynamics of the RIM propeller can be identified from the experimental results.
In the experiment, the time series of thrust data were recorded. The RIM propeller's
responses to different step inputs from the Arduino were analyzed and a second order
linear approximation of the system model was developed. in each experiment, the
RIM propeller started from idle and received one of the following step inputs, 80,
85, 90, 95, 100 and 105 from the Arduino. A second order transfer function was fit
64
0.5
0.45
0.4
2
V$
0.35
0.3
0.25
0.2
0.15
0.1
0.05
n
70
75
80
85
90
95
100
105
110
Input Command
Figure 3-22: Plot of input command vs measured steady state thrust
to each of the step response using the Matlab system identification tool box. The
individual data sets and their fits are shown in Figure 3-23. The red curves in the
figure represent the measured data and the blue curves are the fit system response.
An average transfer function is derived. First the static gain is linearized using
the relation between steady state thrust and input command in Equation (3.1). The
input can be substituted with (Command-76) so the approximated static gain for
all substituted commands becomes 0.0185 N. Then the percentage overshoots and
settling times in all cases are averaged to find the average transfer function. The
approximated transfer function for the RIM propeller is as follows.
Thrust(N)
Command - 76
0.0185
0.0013s2 + 0.0294s + 1
This transfer function representation of the RIM propeller has a few limitations.
From Figure 3-23 one can tell the system response to different input has slightly
different settling time values and percentage overshoot values. This difference may
be attributed to the interaction with the fluid. In addition, this transfer function did
not reflect the delay in the system. A delay was also observed during the experiment as
in all cases the RIM propeller did not start right after a command was sent. This time
delay was difficult to characterize but it was within a fraction of a second. Although
this transfer function missed those two characters of this RIM propeller system, it
still captured the main effects of the transient response of the RIM propeller.
65
input 80
-0.06
0.1
15
0.04
S0.02
0
iu
-
0
0.5
1
1.5
0.0 01
0 05
2
time (sec)
input 90
0.4
0.3
0.6
A-
0.2
i~A
6
W Tvv\p
Fy
2
%
2
.
0.8
1.5
1
time (sec)
input 95
-
z
input 85
0. 2
U.LD
0.1
0.4
0.2
0.5
.
n8
1
time (sec)
input 100
1.5
2
(
.Lj..A.
-,.
0.5
1
1.5
2
1.5
2
time (sec)
input 105
1
.
0
U
A
0.6
'
Pn 0.4
4 -Ty -
V
2
0.5
0.2
0
a
0.5
1
1.5
U.
0
2
time (sec)
0.5
1
time (sec)
Figure 3-23: Measured step responses of the RIM propeller
3.7
Summary
In this chapter, the design, fabrication, performance and characterization of the micro
RIM propellers are presented. The RIM propeller consists of a stator and a rotor with
the propeller built into the rotor. The RIM propeller is 36mm in diameter and 12
mm in depth. It is able to produce 0.4N of thrust at around 5400rpm by consuming
7.1W of electric power. From the experiment, the input-output mapping of the RIM
propeller was identified. A second order linear system model was created to represent
the dynamics of the RIM propeller.
66
Chapter 4
Integration
In this chapter, the integration of the robot is presented. A robot housing is designed
to host all sensing, actuation, control, communication and power components inside.
These components and their layout are engineered to minimize the space requirement.
Several waterproofing techniques are described.
4.1
Robot Housing
The robot housing consists of the main body, bearings for the RIM propellers and
a removable cap. An exploded view of the housing components are shown in Figure
4-1. The main body is designed to contain all sensing, control, communication and
power components. Its outer geometry is the same as that of the final robot design
shown in Figure 2-10. The dimensions of this geometry are listed in Table 2.5. Inside
the main body, it is completely empty. This space is left for sensors, controllers and
batteries. Those components are inserted into the main body from its opening on the
top. Once all components are placed inside, the top cap is closed with a tight seal.
Part C and D as shown in Figure 2-10 are the bearings for the RIM propellers. They
can be placed in the side chambers of the main body.
All parts of the robot housing are 3D printed. The robot housing is printed in
a Stratasys Fortus
2 50mc
fused deposition modeling (FDM) printer. It is config-
ured to print acrylonitrile butadiene styrene (ABS) thermoplastic at a slice height of
67
B
A
Figure 4-1: Exploded view of the robot housing. Part A is the main body, B is the
cap, C and D are the RIM propeller bearings.
0.178mm. The main body is a shell and its thickness is 1.9 mm everywhere, making
the robot sufficiently rigid.
4.2
Electronic Subsystems
There are four electronic subsystems in the robot.
They are the power, sensing,
communication and control systems.
4.2.1
Power
The power system consists of a number of batteries. The batteries should have enough
capacity to supply the robot for the entire duration of a mission. If the robot consumes
P Watts of power and a mission is expected to last T minutes, the robot needs at
least Etotal = P * T * 60 Joules of battery capacity. At the same time, a number
of small size batteries are preferred as they are more likely to fit in the robot than
a single large battery do. If each battery has a capacity of E1 Joules, the minimum
number of batteries is n =
Et otal
68
In this robot, the following parameters are used to determine the necessary battery
capacity and quantity. P is chosen to be 15 W since there are two RIM propellers
each of which consumes around 7W. For this prototype, the operation period T is
assumed to be 15 minutes. Thus Etotal = 13500 Joules. A small single cell Lipo
battery of 3.7V and 300mAh was selected for its small size. It corresponds to a
E, = 3.7 * 300 * 3.6 = 3996 Joules. This robot needs 4 of them.
4.2.2
Sensing
This in-pipe robot needs a subsystem to perform localization and sense the environment. Ideally the robot should be able to sense its position, detect Tee junctions,
measure the fluid flow conditions and inspect the pipes. Sensors such as cameras,
proximity sensors, IMU can be used on the robot to provide the location information.
The robot can be equipped with pitot sensor and pressure transducers to measure
the flow velocity and pressure. It can integrate cameras, acoustic sensors and a leak
detection systems such as the MIT leak detector [5, 4, 6, 7, 8] to inspect the pipes.
The sensing system in this implementation of the robot provides the basic localization function. The robot can sense its angular position and nearby Tee junctions.
Angular position is sensed using an IMU. With angular position, the robot can perform closed loop feedback control on its heading direction. This allows the robot to
perform basic maneuvers such as following straight lines and turning. On the other
hand, Tee junctions are detected using a customized light sensor. It is a binary sensor
that tells the robot if it is at a Tee junction. There are two light sensors on both
sides of the robot. Each of them emits a beam of light and monitors the reflection
from the pipe walls. If the robot arrives at a Tee junction, the pipe wall on one side
will be open and thus no reflection will be detected by the light sensor on that side.
This drop in signal indicates the arrival at a Tee junction. In this implementation, a
strong LED is used to emit the light, and a photocell is used to sense the reflection.
This customized light sensor provides a range of 3 cm which is much larger than the
1.5 cm detection range of conventional optical detectors.
69
4.2.3
Communication
This in-pipe robot should be equipped with a wireless communication system. The
robot should be able to receive command as control inputs from a remote operator.
At the same time, it should report its status, the pipe inspection result to an operator
or a control center. In order to perform this two-way communication, the robot is
preferred to have a wireless transceiver. This wireless transceiver should have a high
signal strength and a long range. It will enable the robot to maintain the wireless
connection while traveling in underground pipes and traveling a long distance.
In this robot implementation, wireless transceiver Xbee Pro 900 was selected. It
has a maximum range of 10 km in air. Its transmission power is 50 mW or 17 dB
referenced to one milliwatt.
4.2.4
Control
The robot needs a computational platform to control the other subsystems. The
computational platform should be able to read data from the sensors, interpret and
compile communication signals and control the speed of the RIM propellers. The
capability of the computational platform is dependent on the computational power
requirement.
The platform can be a micro controller, multiple controllers, field-
programmable gate arrays (FPGA) or a combination of them.
The robot also needs motor controllers to interact with the RIM propellers. Motor
controllers regulate the speed and power of the propellers upon receiving commands
from the computational platform. Motor controllers can handle the large amount of
current needed by the propellers.
In this robot implementation, two micro controllers and two motor controllers are
used. One micro controller performs speed control and communication, while the
other is dedicated to sensing. The latter is only used for position sensing during the
experimentation. Its remaining computational power is reserved for future sensing
capabilities such as leak detection and cameras. Two motor controllers are used to
control two RIM propellers individually to allow them to act independently at the
70
same time.
4.2.5
Integration of Electronic Subsystems
Wireless
Transceiver
.
Batteres
Arduino
micro
controller
-
5V
Motor speed
controller 2
Motor speed
controller I
RIM
propeller 2
RIM
propeller 1
Arduino
micro
controller
3.3 V
IMU
Light sensor
Figure 4-2: Simplified electronics diagram
Figure 4-2 shows the schematic diagram of the robot electronics. In this diagram,
all solid arrows indicate the power transfer, while all dashed arrows indicate the
information transfer. Starting from the top left, the batteries are connected directly
to the two motor speed controllers.
Each of them have the capability to regulate
the voltage input and provide a 5 V voltage supply to the Arduino micro controllers.
The first micro controller operates on a 5 V logic level.
It commands the wireless
transceiver via serial communication and the two motor speed controllers via its digital
output ports. The second Arduino micro controller runs on a 3.3 V logic level which is
71
required by the IMU. This Arduino collects and compiles information from the IMU
and the light sensors before it sends simplified information to the 5 V Arduino via
Inter-Integrated Circuit (I2C) communication. The 5 V Arduino then acts upon the
information, creates new speed commands for the motor controllers and commands
the wireless transceiver to report the robots status. The motor controllers, upon
receiving the new commands, modify their alternating current outputs to the RIM
propellers. It results in the RIM propellers changing their rotation speed and thrust
output. A complete list of all electronic components and their suppliers are shown in
Table 4.1.
Table 4.1: List of electronic components
Catagory
Micro controller
Micro controller
Sensor
Sensor
Sensor
Communication
Speed controller
power supply
4.3
Components
Arduino Mini Pro 328 5V 16MHz x1
Arduino Mini Pro 328 3.3V 8MHz x1
9 DOF IMU sensor stick x1
Mini Photocell x2
Super Bright White LED x2
XBee Pro 900 Wire Antenna wireless transceiver x1
Turnigy Plush 6A x2
Turnigy nano-tech 300mAh 3.7 V Lipo Battery x4
Supplier
Sparkfun.com
Sparkfun.com
Sparkfun.com
Sparkfun.com
Sparkfun.com
Sparkfun.com
Hobbyking.com
Hobbyking.com
Packaging
The electronic components and their layout were designed to use the space inside
the robot efficiently. Their layout is shown in Figure 4-3. In the same figure the
horizontal cross-section view of the robot is shown. The semitransparent white boxes
represent the physical boundaries of the components listed in Table 4.1. All electronic
components, except the two motor speed controllers and the wireless transceiver, are
placed in this plane. The two motor speed controllers are placed in the bottom of the
robot and underneath the RIM propellers. The major axes of all the batteries, micro
controllers and the IMU are perpendicular to this view plane. Wireless transceiver is
72
placed on top of the IMU and is not shown in this figure.
Figure 4-3: Layout of electronics inside the robot
Additional weight is added into the robot to make the robot neutrally buoyant.
The robot, with all electronics, sensing and actuation systems, weighs 149 grams.
The volume of the robot measured in Solidworks is 175 cm 3 . For the robot to be
neutrally buoyant, the total weight of the robot should be 175 grams. Another 26
grams of weight must be added. Liquid Mold Star 16 Silicone from Smooth-on.com
was poured into the robot to make up the weight. The robot was placed in an upright
orientation so all the silicone would flow to the bottom of the robot before it solidifies.
This additional weight in the bottom of the robot also improved its stability.
73
4.4
Waterproofing
A waterproof coating is applied to the surface of all housing parts to prevent water
permeation. The American Synthetics Stone Weld Penetrating Epoxy is used as it
bonds well with the ABS plastic. After the epoxy was cured, the robot housing was
placed underwater for one day and no water was found inside the housing. A typical
operation performed by the robot lasts 15 minutes due to the limited capacity of the
onboard battery. This waterproof coating can ensure the safety of all components
inside the robot during the operation.
The interfaces between assembled components are also treated with special care
to prevent water from penetrating. There are two types of interfaces, one between the
RIM propeller and the main body, and the other one between the cap and the robot
main body. Different waterproof techniques are applied to these two types interfaces.
The interface between the RIM propeller and the main body is permanently sealed
to prevent water penetrating. The interface is a hole, where cables from the RIM
propeller enter the main body. There are two holes on the main body for the RIM
propellers. They are permanently sealed by epoxy after installation of the cables.
The interface between the cap and the main body uses multiple sealing techniques.
First, the cap is partially threaded as to provide a perfect seal. As shown in side view
(A) and bottom view (B) of the cap in Figure 4-4, there are two legs that could grab
the interior of the main body once the cap is closed. The legs are tapered. As the
cap is being screwed into the robot, the normal pressure increases on the legs and it
eventually becomes a tight fit. Second, an o-ring is placed between the cap and the
main body. When the cap is closed, the flat surface along the circumference of of
the cap presses against the o-ring. The o-ring deforms and fills up the gaps between
the cap and the main body. A small amount of gaps remain because of the textured
surfaces of the 3D printed parts. To complete the seal, a layer of blue silicone buffer
is deposited onto the flat surface of the cap as shown in part (C) of Figure 4-4. The
silicone is Mold Star 16 from Smooth-on.com.
74
Figure 4-4: Three views of the cap. (A) side view, (B) bottom view and (C) bottom
view of the the cap with a silicone ring
4.5
Summary
A robot prototype as shown in Figure 4-5 is developed.
It is an integrated robot
contains all its power, control, communication, sensing and actuation inside. It is
waterproof and safe to operate in water pipes.
Figure 4-5: Picture of the fully assembled robot
75
76
Chapter 5
Control
The control of this robot is performed at both the micro and macro levels. On the
micro level, an onboard PID controller controls the robot's speed and heading. On the
macro level, a remote control center plans the path for the robot and communicates
with the robot.
5.1
Onboard Controller
In this section, the robot modeling and its heading control are presented.
5.1.1
Robot Modeling
An approximated plant model is developed for robot with a focus on the heading
control. This plant model should describe how the robot yaw angle changes with the
thrust inputs from the RIM propellers. The hydrodynamic equations of the robot
from Section 2.3 are used to derive this plant model. The yaw position is governed
by the following equations.
r =
(5.1)
N = Izzr = Nrr + Ntnpt
(5.2)
Nznt = d * (F1 - F2) = d * A F
(5.3)
77
4'd
(5.4)
I,,q = Nq+ d *AF
The new coefficient, d, is the distance from the center of the RIM propeller to the
center of the robot. The new variables, F and F2 are the thrust forces from right
and left RIM propellers, respectively. The difference between F and F2 can treated
as one variable AF.
Two assumptions are made to develop the approximated robot model. The first
assumption is that the effect of the ducts in the robot on the robot's yaw motion is
negligible. The robot geometry with the ducts is no longer axisymmetric about the
vertical axis so it will experience a Munk moment during the turn. However, the
robot geometry is approximately an axisymmetric ellipsoid, and the Munk moment
should be small. The second assumption is that the coupling between yaw motion
and motions in the other direction is neglected at this stage. The current modeling
and control study is focused on the yaw motion, while the control on the coupled
motions will be investigated later.
The approximated robot model is derived by substituting numerical values into
Equation (5.4). This robot model describes how the robot steers its heading given
the difference in the thrust from left and right propeller. The numerical values of
the coefficients in Equation (5.4) can be estimated from the physical properties of
the robot. The parameters, Iz, d can be found from Table 5.1. N, represents the
damping coefficient during the rotational motion about z axis. Slender Body Theorem
[17] was used to provide a rough estimation of this coefficient with an approximation
that the robot was a perfect ellipsoid. An estimate of N, = -5 * 10-4Nm/s was
obtained. The plant model of the robot with the yaw position as the output can be
approximated as follows.
223.9
robot()
<
AF
-
-IzzS2
78
Nrs
s2 + 3.731s
Table 5.1: List of physical properties of the robot
parameters
L
H
W
d
Ld
Ad
V
m
Ixx
Physical Meaning
Length of the robot (along x)
Height of the robot (along z)
Width of robot (along y)
Distance between the center of
the duct and the center of the
robot
Duct length (along x)
Duct average cross-sectional area
Value
0.085m
0.06m
0.085m
0.03m
0.065 m
7r * (0.02/2)2
1.750 -4m
3.14
*
10- 4m 2
3
Volume of the robot
Iyy
0.175 kg
1/5 * m * (1/4 * W 2 + 1/4 * H2 )
10- 4 kg -m2
1/5 * m * (1/4 * L2 + 1/4 * H2 )
Izz
10-4kg -- 2
1/5 * m * (1/4 * L2 + 1/4 * W 2 )
Mass of the robot
Moment of inertia about x
Moment of inertia about y
Moment of inertia about z
10- 4 kg -M2
Onboard Controller Design
5.1.2
A PID controller is deployed on the robot to ensure the robot can correct its heading
errors fast and perform fast maneuvers. This controller is imbedded onto the robot.
It makes the robot swim in the desired direction and corrects heading errors on the
fly. These errors may be caused by the difference in the propellers. The two RIM
propellers are not exactly the same and therefore differences may exist in their output.
The disturbance from the fluid environment also results in errors in the robot heading.
Controller
GGobts
Oref
|+
1 ...
AW
Robot
RIM Propeller:
G2
Fnom
F
(S)
Gaobot(s)
GRIM(s)
Figure 5-1: Block diagram of the closed loop robot system
79
The block diagram of this closed loop system is illustrated in Figure 5-1. The
inputs to the closed loop system are a reference yaw angle,
nominal propeller speed,
Wnom.
the yaw angle of the robot,
#.
#,ef,
in radians and a
This IMU signal is integrated to obtain an estimate of
In two steps the controller calculates speed commands,
namely w, and W 2 , as shown in Figure 5-1.
Step 1:
Aw = Gc(s) * (0,ef
(5.6)
-
Step 2:
] nom
[
(5.7)
= G2(s)
nom
2
W
Where the necessary speed difference Aw is the necessary speed difference between
the two RIM propellers that can make the robot turn to follow the reference signal
#,e.
Gc(s) is a controller that calculates the necessary Aw. G2(s) is a matrix that
calculates the speed commands w, and w 2 for the RIM propellers. Both Gc(s) and
G2(s) are coded into the Arduino micro controller. The speed commands, w, and
W2 ,
are generated by the micro controllers in the format as described in Section 3.6.1.
The two signals wi and w 2 are sent to the motor controllers of the RIM propellers.
The RIM propellers and the robot act accordingly to the speed commands. The
thrust output of the two RIM propellers, F and F2 can be predicted by the transfer
functions GRIM1(s) and GRIM2(s) respectively. The robot is then propelled to maneuver, and its new angular position, 0, can be predicted by
Grobot(S).
The expressions
of GRIM1(s) and GRIM2(s) are given in Equation (3.2) and Grobot in Equation (5.5).
These are repeated below:
F1
CRImi(s) = CRIM2(8) = wi,
Grobot (S) -
____
0
-
F 1 - F2
0.0185
0.0013s 2 + 0.0294s + 1(5.8)
223.9
239(5.9)
S2 +3.731s
The controller, Gc(s), can be tuned to allow the robot to achieve a desired tran80
sient response. The desired performance includes a short settling time, a small overshoot, a good disturbance rejection and a non-saturated controller output. The first
two criteria are necessary for robot turning. A good disturbance rejection helps the
robot correct small errors in its heading direction. The controller output is the difference command and it should be within the range of the feasible motor command.
The range for the motor command is 78 to 98, making the range of Aw being -20 to
20.
A PID controller was designed in Matlab controller design toolbox, pidtool. After
a few iterations, a functional PID controller that met the criteria was identified. The
controller is shown in Equation (5.10).
Gc(s) = 7.344 +
0.726
S
+ 0.984s
(5.10)
The predicted closed loop system response to a step input had a settling time of
0.993 second and an overshoot of 11.3 percent. The integral gain is in place to reject
noise and reduce errors. The maximum output from the controller for a 90-degreeturn input is slightly smaller than 12 and well below the saturation level. The step
response of the closed loop robot system with this controller for a 90 degree turn is
plotted in Figure 5-2.
This controller serves the purpose of testing the maneuverability of the robot. It
would allow the robot to maintain straight motion and turn a certain degree upon
command. When used in experiments, it would provide preliminary results of the
performance of the robot, and these results can be used to design the more comprehensive controller for the robot.
5.2
Remote Control System
The robot is wirelessly controlled from a remote computer. The robot makes changes
to its path upon receiving wireless commands. The commands include forward speed
command, turn left command, turn right command, stop command and manual override command. Those commands are generated by a LabVIEW interface shown in
81
time (s)
Figure 5-2: Response of the closed loop robot system to a 90 degree step (1.57 rad)
input
Figure 5-3. The LabVIEW interface sends out the command signal through another
wireless transceiver connected to the USB port of the same computer. The wireless
serial communication follows the Zigflee protocol. The baud rate of the commutation
is 115,200 Hz.
A mapping between the commands on the LabVIEW interface, the wireless command signal and the robot controller input is created. The mapping is summarized
in Table 5.2 and described below.
Turn left 90 degree
When a "Turn left 90 degree" is selected, a wireless signal, "CL" will be sent out. "C"
is the header that is used in all communication from the LabVIEW interface to the
robot. It stands for control. "L" means left. When the robot receives this message,
the Arduino onboard will enable the PID controller, read the current yaw angle q5
from the gyroscope, and create a step input of current #
+
i to the PID controller
code. The speed command to each RIM propeller, cmd, will first be set to be the
82
COffffVzk*W OW-W
F ---
,i
Figure 5-3: Image of the LabVIEW interface for robot control
same as the previous value. The PID controller will increase or decrease the cmd
value before the speed commands are output from the Arduino to the motor speed
controllers. The response of the RIM propellers to a speed command can be predicted
by its transfer function in Equation (3.2). The PID controller will do the rest and
the robot will turn 90 degrees to the left.
Turn right 90 degree
When a "Turn right 90 degree" is selected, the wireless signal is "CR" . "R" means
right. When the robot receives this message, the Arduino onboard will enable the
PID controller, read the current yaw angle
input of current
#
# from
the gyroscope, and create a step
- !2 to the PID controller code. The speed command to each
RIM propeller, cmd, will first be set to be the same as the previous value. The PID
controller will increase or decrease the cmd value before the speed commands are
output from the Arduino to the motor speed controllers. The PID controller will do
the rest and the robot will turn 90 degrees to the right.
Propeller speed command
A new propeller speed command will make the two propellers turning at the same
commanded speed. For example, a speed command 90 means that both RIM pro83
Table 5.2: Mapping between commands, wireless signals and controller input
Command
Turn Left 90 deg
Signal
CL
controller input
enable PID controller
#ref= #current + W
Turn Right 90 deg
CR
cmd-previous cmd
enable PID controller
'tref
Propeller speed(e.g 90)
CS090
#ref
Stop the robot
CO
O[current - 2
=
cmd=previous cmd
enable PID controller
=
#current,
cmd=90
disable PID controller
cmd left=68, cmd right=68
Manual average speed(e.g 90) and
manual differential speed(e.g 20)
CM100080
disable PID controller
cmd left=100, cmd right=80
pellers are desired to run at 4200 rpm and each generates 0.23 N of thrust according
to the input-output mappings as shown in Figure 3-21 and Figure 3-22. The mappings are also displayed here in Figure 5-4 and Figure 5-5. When a new propeller
speed 90 is selected, a signal "CSO90" will be sent out. "S" means speed. The 3-digit
number, "090" is for 90, and it will change for different selected speed. When the
robot receives "CSO90", the Arduino onboard will enable the PID controller, read the
current yaw angle
#,
and create a step input of current
# to
the PID controller code.
This step input means the robot is desired to go straight. The speed command to
each RIM propeller, cmd, will first be set to 90. The PID controller will adjust the
cmd value before the speed commands are output from the Arduino to the motor
speed controllers.
Robot stop command
If the "Stop the robot" button on the LabVIEW interface is pressed, a signal of "CO"
will be sent out. When the robot receives this signal, the Arduino onboard will disable
the PID controller and set the speed command, cmd, to both left and right propellers
to 68. Upon receiving speed command 68, the speed controller will shut down the
power to the RIM propellers. The robot then comes to a stop.
84
6000
5000
1Wee~
S4000
3000
C
i2000
1000
0
70
75
80
85
90
95
100
105
110
Input Command
Figure 5-4: Plot of speed command vs measured steady state rotational speed
0.5
0.45
0.4
2
0.35
1W$
0.3
0.25
M
0.2
0.15
0.1
0.05
0
70
75
80
85
90
95
100
105
110
Input Command
Figure 5-5: Plot of speed command vs measured steady state thrust
Manual mode command
If manual mode is activated and Manual average speed (e.g. 90) and manual differential speed(e.g 20) are chosen, a signal of "CM100080" will be sent out. "M" stands
for manual. The first 3 digits are the speed command for the left propeller, and in
this case it is 90 + 20/2 = 100. The next 3 digits are the speed command for the
right propeller, and in the case it is 90 - 20/2 = 80. An extra 0 is added in front of
"80" to keep the length of the signal constant for all manual speed selections. Once
the robot received this signal, the Arduino onboard will disable the PID control and
send out the two speed commands directly to the motor speed controller. In this
case, speed command value 100 is sent to the left propeller.
It will turn at 5500
rpm and generate 0.42N of thrust at steady state according to Figure 5-4 and Figure
5-5. Speed command 80 is sent to the right propeller. It will turn at 1900 rpm and
85
generate 0.06N of thrust at steady state according to Figure 5-4 and Figure 5-5. The
robot will then turn to the right and go in circles when it reaches steady state.
In order to prevent saturation, the speed command is filtered on the Arduino
before being sent to the motor speed controller. Referring to Section 3.5, the range
of speed command accepted by the motor speed controller was between 68 and 120.
Speed command values outside this range will not activate the motor speed controller.
The thrust and rotation speed of the RIM propeller saturates when the speed command is above 98. Therefore, the Arduino should send speed commands between 68
and 98 for effective speed control. After the speed command is adjusted by the PID
controller, it is compared with the lower bound 68 and upper bound 98. If it is below
68, speed command will be changed to 68. If it is above 98, speed command 98 will
be output.
5.3
Summary
The control system of the robot consists of both controllers at both micro and macro
levels. On the micro level, an onboard PID controller controls the robot's speed
and heading. On the macro level, a LabVIEW interface runs on a remote control
center and sends commands to the robot wirelessly. The robot then performs the
commanded maneuvers.
86
Chapter 6
Experimental Results
6.1
Overview
A set of experiments were conducted in open water to test the robot's ability in
performing motions including straight lines and sharp turns. In real pipe scenarios,
the robot would have to move in straight lines and also conduct turns at Tee junctions.
The experiments were conducted in open water instead of in pipes in order to reduce
the robot's in-pipe sensing and control requirements. This part of the project focused
on maneuverability. The results of these experiments would serve as the foundation
for in-pipe robot maneuvering.
6.2
Experiment Setup
A rectangular water tank was prepared for the experiment. As shown in Figure 6-1,
the water tank is 2.5 meters long and 0.6 meters wide providing enough room for the
robot to move in the horizontal plane. It contained about 20 cm deep of static water
during the experiment providing enough room in the vertical plane for the robot.
During all experiments, the robot was fully submerged in the water. The dimensions
of the water tank are much bigger than that of the robot, and it can be considered
an open environment.
The robot was remotely controlled in all experiments. The author used the Lab87
Figure 6-1: Picture of the water tank used in the experiment
VIEW interface and wireless communication system described in Section 5.2 to remotely control the robot. The interface was run on a Lenovo IdeaPad U400 laptop.
The commands used in the experiment include to follow straight lines at various propeller speeds, turn left 90 degrees, turn right 90 degrees and manual speed for finding
out minimal turning radius. The laptop sent out commands wirelessly using the XBee
Pro 900 Wire Antenna wireless transmitter that was connected to the laptop's USB
port. The wireless communication follows the ZigBee protocol, and it is serial. The
baud rate of the communication is 115,200 Hz.
The experimental results were video taped and analyzed manually.
A regular
IPhone 5 camera was used to capture the 1080HD video at 30 frames per second.
The resolution of this IPhone camera is 8 megapixels. A dot tracing technique was
88
used to find the path of the robot. A dot was drawn on the screen for the center
of the robot as the experiment video was played on the screen. All the dots were
connected to form the measured path of the robot. The body length of the robot was
known to be 8.5 cm, and it was used as a reference scale. The actual distance the
robot travelled was calculated by comparing the traced path in each experiment with
the body length of the robot in the image.
6.3
Results and Discussion
6.3.1
Following Straight Lines
In this experiment, the robot's ability to follow straight lines was tested. The robot
was commanded to go forward by running both propellers at the same speed. The
speed was set by selecting command "propeller speed 90" on the LabVIEW interface.
Wireless command signal "CS090" was sent to the robot. According to the speed,
thrust and command mapping in Figure 3-21 and Figure 3-22, each RIM propeller
would turn at 4200 rpm and generate 0.23 N thrust in response to the speed command
90. The robot travelled 1.25 meters, or half of the length of the water tank, in about
4 seconds. The steady state speed of the robot was about 0.3 m/s. Figure 6-2 shows
the captured picture of the robot at the starting point and its path. The blue line
represents desired path, and the black dots represents measured path of the robot.
The measured path shows that the robot was able to correct its initial heading error
and return to its desired heading direction, but it was still slightly offset from the
desired path.
The experimental results showed that the robot was able to follow the straight line
with some errors. Overall the robot was moving in the desired direction. However,
the robot was oscillating about its desired path, and a small offset was observed at
the end. This error can be attributed to the inconsistent manufacturing quality of
the propeller and the limited onboard sensing capability.
Manufacturing errors in the RIM propeller is the first reason for the difference
89
Desired path
.
e eMeasured path
Figure 6-2: Picture of the robot following a straight line
between the measured path and the desired path. When the robot started moving,
it was moving toward the left of the desired path. This was because the right RIM
propeller was producing slightly more thrust than the left RIM propeller at the same
speed command.
This output noise was due to the small difference in the manu-
facturing quality of the left and right RIM propeller. The left RIM propeller might
experience more friction than the right one. Thus the robot was moving to the right
of the desired path.
The onboard micro controller is able to compensate for RIM propeller output
noise. The Arduino micro controller reads the output of the gyroscope in the IMU
and calculate the heading error. It adjusted the heading direction of the robot by
increasing the speed command for the left RIM propeller and decreasing that for
the right one. The robot stopped moving to the left but it had an overshoot to the
right before it converged to the desired heading direction. The same overshoot was
observed in the simulated step response of the closed loop system as shown in Figure
5-2. The controller could be fine tuned to minimize overshoot. Then the robot will
be able to correct its heading direction within a reasonable amount of time.
The second reason for the difference between the measured path and the desired
90
path is the limited onboard sensing capability.
After the robot converged to the
desired heading direction, it was moving in parallel to the desired path instead of
on the desired path. At the end of the path, the robot was about 2 cm away from
its reference path. The robot was not able to eliminate this lateral offset because no
onboard sensors were set up to monitor the robot's lateral position. The accelerometer
signal inside the IMU could be used for this purpose. One has to realize that errors
can be accumulated when integrating the linear acceleration reading. To increase the
precision of the path following function, the robot will require additional position
sensors such as ranger finders and cameras.
6.3.2
Follow Straight Lines and Overcoming disturbances
In the second experiment, the robot's ability to reject disturbance was explored. The
robot was first placed next to an obstacle that in this experiment was a pipe section.
The robot was commanded to go straight and hit the obstacle on the side. A constant
command of "propeller speed 90", was used, and the robot was commanded to move
in a straight line with both RIM propellers turning at around 4200 rpm. It reached
a steady state speed of 0.3 m/s. As shown in Figure 6-3, the robot bumped with its
right side the top of a Tee section. The robot momentarily turned to the right. It
corrects its heading and come back to a path parallel to the original one.
An explanation of how the robot overcome disturbance is as follows. When coming
into contact with the top of the obstacle, the robot turned to the right about the
contact point. The onboard micro controller read the output from the gyroscope in
the IMU unit and calculated the angular offset from the desire heading direction. The
PID controller algorithm corrected the heading within one second and the robot was
able to return to the original heading as indicated by the measured path in Figure
6-3. However, since the robot had no lateral position sensing capability yet, it was not
able to return to its original path. The robot is capable of basic heading control, and
it needs the capability to sense its lateral motion to make more precise maneuvers.
91
-
Desired path
se * * Measured path
Figure 6-3: Picture of the robot following an straight path and overcoming an obstacle
6.3.3
90-degree Turns
In the third experiment, the robot's ability to conduct turns was evaluated. The robot
was commanded to move forward and then make a 90-degree turn. At first, the same
command in the first experiment, "propeller speed 90", was used, and the robot was
commanded to move forward with both RIM propellers turning at around 4200 rpm.
It reached a steady state speed of 0.3 m/s. After 2 seconds, the "turn left 90 deg"
command was selected on the LabVIEW interface, and command signal "CL" was
sent to the robot. The robot responded by setting 90 degrees to the left of its current
heading direction as a new input to its PID controller. Figure 6-4 shows the captured
picture of the robot at the moment of turning. The blue line represents the desired
path and the black dots represents the measured path of the robot. During the turn,
the left RIM propeller was not rotating because the speed command calculated by
the Arduino was lower than 78. 78 was the minimum value for the RIM propeller
to turn. The right RIM propeller increased its rotational speed and thrust at the
92
beginning of the turn, and it decreased its thrust at the end of the turn.
Figure 6-4: Picture of the robot going straight and then making a 90 degree turn
The robot was observed to turn at a radius of curvature of about 4 cm but the
minimal turning radius could be much smaller. A 4 cm turning radius was achieved
at 0.3 m/s approaching speed without reversing the direction of the propeller thrust.
This turning radius was already smaller than half of the robot's body length. If
the left propeller thrust is reversed, the turning radius could be even smaller at this
speed. The propeller thrust was not reversed mainly because the motor controller
was configured to run propellers in only one direction. The motor controller used in
this robot, Turnigy Push 6A ESC, is a common motor controller used in RC airplanes
that does not need to reverse direction. In future work, a customized motor controller
will be built to turn the RIM propeller in both directions.
The robot was able to make a sharp turn, but its performance to maintain its
93
heading after turning 90 degrees needed to be improved. As indicated in Figure 6-4,
the robot had an overshoot in its angular position during the turn. At this moment,
the right RIM propeller was reducing its rotational speed and the left RIM propeller
was supposed to start instantaneously. However, the RIM propeller did not turn on
when needed due to a lag. The large angular momentum kept the robot rotating and
this lag in the left RIM propeller made it difficult for the robot to correct its heading
fast enough. A simple PID controller had limited capability to compensate for the
lag in the actuator, and thus it was not good enough for turning control. Lead-lag
compensators and other strategies will be investigated in the future to improve the
robot's turning stability.
6.3.4
Minimum Turning Radius
In the last experiment, the smallest turning radius of the robot was explored. The
robot was stationary before it was commanded to turn to the right continuously. On
the user interface, manual mode was selected, and the manual average speed was 85,
and the manual differential speed was set to be 30. Command signal "CM100070"
was sent to the robot. The robot responded by setting the left RIM propeller to
maximum rotational speed and the right RIM propeller to zero rotational speed. The
speed command to the left RIM propeller was 100, which corresponds to 5500 rpm
and 0.42 N of thrust at steady state. The speed command to the right RIM propeller
was 70 at which the propeller was not turning.
Each propeller was placed 3 cm
away from the center of gravity of the robot in the horizontal plane, the resulted
torque on the robot body due to 0.42N of thrust from the left propeller is Np
=
0.42N * (-3 * 10- 2 m) = -1.2 * 10- 2 Nm. Based on Equation (5.5) in Section 5.1.1,
the robot was predicted to spin at 24 rad/s or 3.8 revolutions per second at steady
state. However, a rotational speed of 2 revolutions per second was measured in the
experiment.
The robot was almost spinning during the experiment and the minimal turning
radius of the robot was observed. The turning radius was about 1.5 cm, as indicated
by the measured path in Figure 6-5. This turning radius was already smaller than
94
J
Figure 6-5: Picture of the robot during the spinning motion
20 percent of the robot's body length which is 8.5 cm.
Since this turning radius
was achieved with the maximum thrust differential, it is equivalent to the minimal
turning radius. In the current implementation of the robot, the propellers could not
turn in the reverse direction yet due to the limitation of the motor controller. The
minimum turning radius can be even smaller or zero once the robot can have two
RIM propellers producing thrusts in opposite directions.
The maximum turning speed of the robot was also observed. The robot turned
10 revolutions in about 5 seconds so the rotational rate was about 2 revolutions per
second.
At this rate, the robot could turn 90 degrees in 1/8 of a second.
This
rotational speed was lower than the predicted value, 3.8 rev/s. This means that the
estimated damping coefficient, Nr, used in Equation (5.5), was lower than the real
value. The measured rotational speed can be used to update the damping coefficient,
N,
=
9.5 * 10-4Nm/s in Equation (5.5).
The robot would have similar turning performance in pipes with proper sensing
capabilities. In open water, the robot was able to turn at various radius of curvature.
It could turn at a turning radius of 4 cm at 0.3 m/s. It could turn at a radius of
curvature of 1.5 cm if starting from stationary. When turning at a Tee junction, the
95
robot has to turn with a radius smaller than half of the pipe diameter in order to
avoid bumping into the pipe walls. A smaller turning radius will provide the robot
with more freedom in choosing the path of turning. It can then follow the path of the
smallest fluid disturbance, minimal energy consumption or the highest success rate.
The minimal turning radius of this robot is much smaller than 5 cm and thus the robot
meets the turning radius criteria. However, the robot also needs proper sensors in
order to perform a successful turn at the Tee junctions. Sensors like cameras or range
finders are necessary to locate the Tee junction in advance, so the robot can prepare
for the turn and turn at the exact location. Pressure sensors and accelerometers can
help the robot to estimate the disturbance due to fluid forces during the turn.
6.4
Summary of Results
The current robot was capable of both following straight lines and conduct sharp
turns. A simple PID controller implemented on the robot was able to correct errors
in the robot's heading due to RIM propeller output noise and disturbance from the
environment. The robot could turn at a radius of curvature that was a fraction of its
body length. When starting from a stationary condition, the robot could turn with
a radius of 1.5 cm or 18 percent of its body length. When moving at 0.3 m/s, the
robot could turn with a radius of 4 cm or 47 percent of its body length. This small
turning radius is sufficient for a successful turning at a Tee junction, while it can be
improved even further when the reverse thrust function of the robot is enabled. The
current turning radius was achieved without reverse thrust.
The experimental results have two significant implications on the future work on
this in-pipe maneuverable robot. First,. the robot has sufficient actuation performance
for in pipe maneuvers.
It can go straight and turn with a very small radius of
curvature. Different control strategies can be evaluated on this robot for the best
in pipe maneuver performance. Second, this robot needs more sensing capability for
successful in-pipe maneuvers. so far, the robot was tested only in open and static
water.
96
Chapter 7
Conclusion and Recommandations
In this project, a maneuverable robot for in-pipe leak detection is designed, fabricated
and tested experimentally. The robot is of an ellipsoidal shape with a smooth exterior.
This shape minimizes the possibility of damage in the case of collision. This robot
uses two customized micro RIM propellers as actuators. These RIM propellers are
safe and powerful, providing up to 0.8N of total thrust for the robot to maneuver in
a fluid environment. This robot is also equipped with an embedded micro controller
for feedback control.
The robot was tested in open water. It exhibited abilities to follow straight lines
and correct for heading errors. The robot shape allows it to turn in the fluid easily with
very small radius, a fraction of its body length. Following straight lines and making
sharp turns are necessary for the robot to perform missions in confined environments
such as pipes.
Advanced sensing and control are recommended for the future work. The robot
was tested only in open water so far. To successfully operate in pipes, the robot must
have appropriate sensing and control capabilities. It needs sensors and controllers
to monitor and maintain its position in the radial direction. This is important for
the robot to operate in straight pipes. The robot also needs to locate a Tee junction
ahead of time in order to plan for the turn at this location. This is important for a
robot that is going to maneuver in complex pipe networks.
97
98
Appendix A
Robot CAD Model
In this appendix, the technical drawings of the prototyped robot are presented.
99
D
C1
85
54.12
20
1310.7&0-
52.00'
--
-R20. 65
R25.27
5
R21.88
---------------
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--------------- 82 .6 1--- -----------
As per CAD file
All exterior surfaces
---------------------
(0-
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6
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24
USED
COMMENTS:
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SECTION F-F
2.
--- 22.50
-- 12.79
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UNLESS OTHERWISE SPECIFIED:
DIMENSIONS ARE
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NAME
2
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2
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RIGHT VIEW
2 BEARINGS
FOR 1 PROPELLER
TITLE:
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104
Appendix B
RIM Propeller CAD Model
In this appendix, the technical drawing of the prototyped RIM propeller is presented.
105
0
5.17
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-- 4
P
X
z
m
0
0
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0
z
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m
m
0
Figure B-1: Technical drawing of the stator in the RIM propeller.
106
Appendix C
CFD Simulation Setup
In this appendix, the CFD simulation setup is presented. The simulation software
is ANSYS Fluent 14.5. After the robot model is imported to ANSYS Fluent, the
following settings are used for the simulation.
Physics Preference
Solver Preference
Relevance
CFD
Fluent
0
H
Use Advanced Size Function
Relevance Center
Initial Size Seed
Smoothing
Transition
Span Angle Center
Curvature Normal Angle
Min Size
Max Face Size
Max Size
Growth Rate
Minimum Edge Length
On: Curvature
Use Automatic Inflation
Inflation Option
Transition Ratio
Maximum Layers
Growth Rate
Inflation Algorithm
View Advanced Options
None
Smooth Transition
0.272
5
1.2
Pre
No
Coarse
Active Assembly
Medium
Slow
Fine
Default (18.0 *)
Default (4.0493e-002 cm)
Default (.04930 cm)
Default B.09670 cm)
Default (1.20)
0.174230 cm
Figure C-1: CFD mesh settings.
107
A
General
* Vscous
Bme--
Mode
rn
Mesh_
t. -
[.. ;a
k
Report~uby
0.09
spawt-AIuaras (Iewn)
(,-Dm .- --
+ k-pgon (2eqn)
L
kiomega (2eqn)
Tranuitonk-omega (3eqn)
Type
# PRw,.ea.eed
o Denrity-ased
Vdodty Frnulation
o Relatlve
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+ Standard WVM Fncanr
ScalW WdA Func"
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Funcbons
iscot
Numbers
PMPrandd ume
In-"
-1
MRRd umbe
Ecuvature Corection
LIW-I1
LFiiJ
Figure C-2: CFD setups. (A) General solver settings, (B)Viscous model settings and
(C) material settings.
108
A
M Velocity Inlet
B
-,r
Zme Nome
-
Zone NOW
1,iilet
-t-
.
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-
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[.
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ai
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n
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nm
. ... -- ------. 0. . 5 .. -
--
Figure C-3: CFD boundary conditions at four boundaries: (A) inlet, (B) robot surface
(C) outlet, and (D) pipe wall.
109
--
-
------ -- - -
---
Reference Values
c52pTR!!
i-
Solution Methods
oom -hm
-1
SolutionIn~talizati
cou
Prew-acdty
_C
Itabation Meftods
Hvbrid Maniation
SStandard Mtialaon
Reerene V~aues
-frM
ce=e
Spatil Dbpaetzatin
tShear
D
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EnW** v
o
Leng&OQ1) I
Prsr as@
Tererature (k)
0
2816
Velodityn/)
Giradent
Reference Frame
- Relative to Cd Zone
Absolute
Pressure
[Standard
M4mentum
Turbulent
[F'st
Vaiu
Pes
inetic Enoergy
LO(MW
pation Rate
Trwient Di
x Velodt
0
VciyGow)0.001003
Ratio of Spedfi Heats14
Non-Iterative Tae Advancement
Frozen Fiux Formulation
Pseudo Transent
[IH
0
ZVelodty
-/s)
Order Tern Relaxation
"0'.00375
Tubulent risaation Rate(
0. 5S968
IrtP
Rese
urce
pMSues
e IPatch...
et Statst-s
Figure C-4: CFD calculation settings. (A) reference values, (B) solution methods
and (C) solution initialization.
110
Appendix D
LabVIEW Block Diagram
In this appendix, the block diagram of the LabVIEW interface for the robot's remote
control is presented.
-dr'.-*If---d?
_______
II
Area A
Figure D-1: Main block diagram of the remote control interface in LabVIEW. Area
A surrounded by the red dash lines is a stack of 9 frames of codes. The first frame is
shown in this Figure. The other 8 frames are shown in Figure D-2.
111
.......... 0 [0..1) a
Stthe robot
HDT3n
0
-0000c
N
ruLe
I-S
0
1*wrte
.
0[0.1.-w
uffer
T rh
Tum
left
Truefl
um
C RCRCRCC
I
I
tC
13 1
.....o.l '1U -A-a~
Contr0...
rvebfr
FR
ber
0 13131313 M Q Q Q
I'~'~~fl~
11
TMrue
Manual
-vr
0
sed
1000
Anual
0~
Last Message Sent
Cm
ftwritebuffrs
100
O~ft
uffe
------- In
Read ninonnnuooouun
ri i -nooooooouonf
E 071
Re'ad
lou no
g
o 0 0.a L1 0 000000 0
mode
-
pop cmd
True
messae read
reference
fr-n
and read
Controller otu
Actual number read
arefnu oLem
112
Figure D-2: 8 subsequent frames of codes for area A in Figure D-1.
mode
message read
Decod
e
V2
2
-j
po
1 cmd
pro 2 cmd
1
4reference
1
4
value
current value
conoler output
PID
CONY
Knumber
Strng
100
Figure D-3: Block diagrams of two subVIs. The first subVI "Decode V2" is used in
Figure D-2. The second subVI, "PID conv string" is used in Figure D-1.
113
114
Bibliography
[1] About saudi arabia: Water resources.
[2] Quraishi A. A. Al-Dhowalia K. HI., Shammas N. Kh. and Al-Muttair F. F. Assessment of leakage in the riyadh water distribution network. Technical report,
King Abdulaziz City for Science and Technology, 1989.
[3] Shanna Cleveland. Into thin air: How leaking natural gas infrastructure is harming our environment and wasting a valuable resource. Technical report, Conservation Law Foundation, 2013.
[41 A. Khalifa D. Chatzigeorgiou, K. Youcef-Toumi and R. Ben-Mansour. Analysis
and design of an in-pipe system for water leak detection. In ASME International
Design Engineering Technical Conferences and Design Automation Conference,
2011.
[5] A. Khalifa D. Chatzigeorgiou, R. Ben-Mansour and K. Youcef-Toumi. Design
and evaluation of an in-pipe leak detection sensing technique based on force
transduction. In ASME InternationalMechanical Engineering Congress and Exposition, 2012.
[6] K. Youcef-Toumi D. Chatzigeorgiou and R. Ben-Mansour. Design of a novel inpipe reliable leak detector. IEEE/ASME Transactions on Mechatronics, 2014.
[7] K. Youcef-Toumi D. Chatzigeorgiou and R. Ben-Mansour. Modeling and analysis
of an in-pipe robotic leak detector. In IEEE InternationalConference on Robotics
and Automation, 2014.
[81 K. Youcef-Toumi D. Chatzigeorgiou, You Wu and R. Ben-Mansour. Reliable
sensing of leaks in pipelines. In ASME Dynamic Systems and Control Conference,
2013.
[9] E. Dertien and S. Stramigioli. Basic maneuvers for an inspection robot for small
diameter gas distribution mains. In Robotics and Automation (ICRA), 2011
IEEE InternationalConference on, pages 3447-3448, May 2011.
[10] Brenden Epps, Julie Chalfant, Richard Kimball, Alexandra Techet, Kevin Flood,
and Chrysssostomos Chryssostomidis. Openprop: An open-source parametric design and analysis tool for propellers. In Proceedings of the 2009 Grand Challenges
115
&
in Modeling & Simulation Conference, number 104-111. Society for Modeling
Simulation International, 2009.
[11] E. Mutschler H, Schempf and etc. Explorer: Untethered real-time gas main
assessment robot system. In International Workshop on Advances in Service
Robotics, 2003.
[12] J.K. Holt and G.C Kennedy. Propulsion system for submarine vessels. US Patent
5306183, 1994.
[13] Adzly Anuar Iszmir Nazmi Ismail and etc. Development of in-pipe inspection
robot: a review. In IEEE Conference on Sustainable Utilization and Development
in Engineering and Technology (STUDENT), 2012.
[14] Vickers A. L. The future of water conservation: Challenges ahead. Technical
report, Water Resources Update, Universities Council on Water Resources, 1999.
[15] Dongwoo Lee, Jungwan Park, Dongjun Hyun, GyungHwan Yook, and Hyun seok
Yang. Novel mechanisms and simple locomotion strategies for an in-pipe robot
that can inspect various pipe types. Mechanism and Machine Theory, 56(0):52
- 68, 2012.
[16] Anirban Mazumdar. Control Configured Design for Smooth, High-Maneuverable,
Underwater Vehicles. PhD thesis, Massachusetts Institute of Technology, 2013.
[17] Franz S. Hover Michael S. Triantafyllou. Maneuvering and Control of Marine
Vehicles. 2002.
[18] T. Nishimura, A. Kakogawa, and Shugen Ma. Pathway selection mechanism of a
screw drive in-pipe robot in t-branches. In Automation Science and Engineering
(CASE), 2012 IEEE InternationalConference on, pages 612-617, Aug 2012.
[19] National Water Research Institute Meteorological Service of Canada. Threats to
water availability in canada. Environment Canada.
[20] Pipeline and US Department of Transportation Hazardous Materials Safety Administration. Significant pipeline incidents, 2013.
[21] S.H. Lai S.M. Abu Sharkh and S.R. Turnock. Structurally integrated brushless
pm motor for miniature propeller thrusters. In IEEE Proc. Electr. Power Appl.,
volume 151, September 2004.
[22] You Wu. Internal report mrl yw 002a: Design of omnidirectional in-pipe maneuverable vehicle. Technical report, Mechatronics Research laboratory, Massachusetts Institute of Technology, October 2013.
116