USC Mechanical Engineering
LAMSS
Laboratory for Adaptive Materials
and Smart Structures
USC Mechanical Engineering
Outline
 Mechatronics – Micro-controllers Education

Vibration Monitoring Enhancement Program (VMEP)

E/M Impedance Structural Health Monitoring

Wave Propagation Non-destructive Evaluation

Smart Materials Actuation
USC Mechanical Engineering
EMCH 367 - Controllers
Motorola MC68HC11EVB: $200
- Ideal for still applications
- More memory suits bigger programs
- Communicates directly with PC
Same chip:
MC68HC11
Homebuilt: $20 + labor
- Cheaper
- Smaller
- Better suited for autonomous robots
USC Mechanical Engineering
EMCH 367 Projects
Robert
Legg
Dave
Durgin
In memory of Dale Earnhardt 1951-2001
USC Raceway
USC Mechanical Engineering
EMCH 367 Projects
Guided Autonomous Vehicle
David Butts
Thomas Tisdale
USC Mechanical Engineering
Projects – Summer 2000
CD-Bot : Searching light and avoiding objects
Peter James
USC Mechanical Engineering
Projects – Summer 2000
CD-Bot : IR detection
Peter James
USC Mechanical Engineering
Outline

Mechatronics – Micro-controllers Education
 Vibration Monitoring Enhancement Program (VMEP)

E/M Impedance Structural Health Monitoring

Wave Propagation Non-destructive Evaluation

Smart Materials Actuation
VMEP Roadmap
US ARMY
USC Mechanical Engineering
NC, KY, MS-ARNG
SC-ARNG AASF
UH-60
VMEP/VMU SYSTEM PROTOTYPE
BETA TESTING AT SCARNG
AH-64
Raw Data
Crew
Chief’s
Laptop
USC Data
Repository
Condition Crew
Chief’s
Indicators Laptop
VPROCs
AMPs
RT&B and HUMS CI’s
Parts and Maintenance
ULLS-A
O&S Cost
Benefit Analysis
RT&B Vibration
Management
VPROCs
AMPs
HUMS Vibration
Monitoring
Diagnostics
and
Prognostics
R&R
VMU/VMEP
Integrity
VMEP data must be:
• Catalogued
• Time/aircraft synchronized
• Accessible and retrievable
VMU 1-- 50
USC Mechanical Engineering
SCARNG Vibration Management
Enhancement Program (VMEP)
A partnership has been established
to conduct enhanced implementation
of the VMEP project and
experimentally identify life-cycle cost
savings and benefits.
USC Mechanical Engineering
AVA System
© 2000 by SC-ARNG
USC Mechanical Engineering
AVA RT&B Procedure
Initial vibration
patterns at
various speeds
Vibration
reduction after
RT&B
correction
© 2000 by SC-ARNG
USC Mechanical Engineering
VMEP Hardware-Software
Smart Rotor
Smoothing
Algorithms
Gear and Drive
Train Monitoring
Vibration
Management Unit
(VMU)
Engine Vibration
Health Monitoring
Light-weight low-cost data
acquisition and processing unit
(COTS components), with easily
upgradeable open architecture
hardware and software
© 2000 by SC-ARNG
VMEP RT&B Tests
1.5
VERT Magnitude
LAT Magnitude
Vibration, IPS
5/18/1999
Vibration, IPS
USC Mechanical Engineering
1.5
5/19/1999
1.0
5/20/1999
0.5
5/18/1999
1
5/19/1999
5/20/1999
0.5
0
0.0
0
20
40
60
80 100
Flight speed, kt
120
140
0
20
RT&B adjustments
Date and time
Main Rotor Adjustments
Weight
Blade 2
05/18/99; 14:48
Tab 6-10
Blade 1
Tab 6-10
Blade 4
Pitch Link
Blade 3
Pitch Link
Blade 4
05/19/99; 08:54
Tab 8-10
Blade 3
Tab 8-10
Blade 4
40
60
80 100
Flight speed, kt
+100 grams
+2.0 deg
+2.5 deg
+0.5 flats
-1.25 flats
+1.5 deg
-1.0 deg
120
140
USC Mechanical Engineering
USC-VMEP Data Repository
ULLS-A
(tapes)
Engineering
& Info. Tech.
MATLAB
(www)
Data Repository
Math
Statistics
Teradata computer
RITA-HUMS
(www)
Bio
Statistics
AVA
(Kermit)
AH-64 Drive-train Vibration Survey
USC Mechanical Engineering
Tail Rotor Gearbox
Hanger Bearing
Nose Gearbox
Main Transmission
Input and Accessory
T700 Engine
Intermediate Gearbox
USC Mechanical Engineering
Outline

Mechatronics – Micro-controllers Education

Vibration Monitoring Enhancement Program (VMEP)
 E/M Impedance Structural Health Monitoring

Wave Propagation Non-destructive Evaluation

Smart Materials Actuation
Health Monitoring of Aging Aircraft Structures
USC Mechanical Engineering
#1 -- Trailing edge
disbond gauge
#3 -- Main spar
disbond gauge
AGING!
Local-area health monitoring of a helicopter
rotor blade. Giurgiutiu, et al (1997)
Damage
due to aging
Aging aircraft panel with simulated crack
Active piezoelectric sensors on an
engine blade



Z str ( )
Z ( ) = iC  1   312

Z PZT ( ) + Z str ( ) 


175
Data-acquisition
and processing
computer
1
Impedance C hanges for Lap Joint 3
150
No Bolt
B olt
125
Re (Z) (Ohms)
HP 4194A
Impedance
Analyzer
B olt + Washer
100
75
50
25
Signal
multiplexer
Health-monitored
structure instrumented
with wafer transducers
0
0
100
200
300 400 500
Frequency (kHz)
600
700
800
RMS Impedance Change Comparisons
for M-Bond 200 Adhesive
RMS Impedance Change
USC Mechanical Engineering
E/M Impedance Method
160%
140%
120%
100%
80%
60%
40%
20%
0%
Lap Joint 1
Lap Joint 2
Lap Joint 3
Lap Joint 4
Bolt, Nut,
Washer
Bolt + Nut
Free
Results by Giurgiutiu, Turner, 1998
USC Mechanical Engineering
Outline

Mechatronics – Micro-controllers Education

Vibration Monitoring Enhancement Program (VMEP)

E/M Impedance Structural Health Monitoring
 Wave Propagation Non-destructive Evaluation

Smart Materials Actuation
Waves in solid were studied
 Waveform visualization
 Wave speed dispersion

Lamb wave – symmetric mode
Lamb waves and flexure wave velocities dispersion
6.000
Lamb wave S0 mode(d=0.5mm)
Lamb wave – anti-symmetric mode
5.000
Flexure wave
Velocity (mm/micro-s)
USC Mechanical Engineering
Wave Propagation Theories Study
4.000 Lamb wave S0 mode(d=0.8mm)
3.000
2.000
Lamb wave A0 mode(d=0.5mm)
Lamb wave A0 mode(d=0.8mm)
1.000
0.000
0
500
1000
1500
2000
2500
3000
Freqency (kHz)
3500
4000
4500
5000
Embedded piezoelectric active sensor
development
10 kHz:
COL 0
10_A1 Excite at position A1
In  ex
COL
B  ex
COL  1
COL  7
C  ex
D  ex
COL  1 3
E  ex
COL  1 9
4 .5 5
4 0 .9 1

PZT wafer transducers on
beam specimen
Wave propagation experiment
at different frequencies
Wave speed – Frequency
curve
8 6 .3 6
1 3 1 .8 2
In
B 1 0 0
1 7 7 .2 7
C 2 0 0
D 3 0 0
E 4 0 0


2 2 2 .7 3
2 6 8 .1 8
3 1 3 .6 4
3 5 9 .0 9
4 0 4 .5 5
45 0
0 .5
0 .3
0 .1
0 .1
0 .3
0 .5
0 .7
0 .9
1 .1
1 .3
1 .5
1 .7
1 .9
2 .1
2 .3
2 .5
2 .7
2 .9
3 .1
3 .3
3 .5
3 .7
3 .9
4 .1
4 .3
4 .5
time
CO L  7 8
100 k Hz: 100_A1 Ex c ite at posit ion A1
In   ex
 C OL
E   ex
 C OL 1
B   ex
 C OL 7 9
C   ex
 C OL 8 5
D   ex
 C OL 9 1
100
0
100
200
300
6.000
In
B 2 0 0
C 4 0 0 4 0 0
D 6 0 0
E 8 0 0
5.000
500
600
4.000
700
3.000
800
y
2.000
900
Axial
0
0 .0 5
0 .1
0 .1 5
0 .2
0 .2 5
0 .3
0 .3 5
0 .4
0 .4 5
0 .5
0 .5 5
0 .6
0 .6 5
0 .7
0 .7 5
0 .8
0 .8 5
0 .9
0 .9 5
1
1 .0 5
1 .1
1 .1 5
1 .2
1 .2 5
1 .3
1 .3 5
1 .4
1 .4 5
1 .5
time
Flexure
A
1.000
B
C
D
E
x
0.000
0
500
1000
1500
2000
2500
Frequency (kHz)
3000
3500
4000
4500
14mm
Wave speed (mm/s)
USC Mechanical Engineering
50
914mm
USC Mechanical Engineering
Experiment on aircraft panels
Tektronix TDS 210
digital oscilloscope
R7
Data acquisition
laptop PC with
PCMCIA GPIB
card
Aging aircraft panel with
PZT active sensors
HP 33120A
signal
generator
R6
10-mm
EDM crack
R5
Trek 50/750
HV amplifier
Transmitter
R1 R2 R3 R4
T

R1
R2
R3
R4

R5
R6
R7
-250
0
250
500
750
1000
1250
Time, micro-sec
1500
1750
2000
2250
2500
PZT wafer
transducers array on
aircraft panel
Wave analysis
USC Mechanical Engineering
Development of Concepts for Automatic
Health Monitoring System
The future of such sensing is conceptualized as integrated part of real structures
and could be compared with nervous systems of living organisms, so that the
active sensors will “feel” the structure and provide a feedback in terms of
information on the structural health.
Sensors
Cluster 3
Sensors
Cluster 2
Data concentrator
Data concentrator
Central Health
monitoring PC
Sensors
Cluster 1
Wireless health monitoring system on board of civil aircraft
Sensors
Cluster 4
USC Mechanical Engineering
Outline

Mechatronics – Micro-controllers Education

Vibration Monitoring Enhancement Program (VMEP)

E/M Impedance Structural Health Monitoring

Wave Propagation Non-destructive Evaluation
Smart Materials Actuation
Smart Materials
USC Mechanical Engineering

Applied
field
Upon the application
of an external field,
the material expands
or contracts.
Smart material
Smart (active, intelligent, adaptive) materials:
- piezoelectric materials  electric field
- magnetostrictive materials  magnetic field
- shape memory alloys  temperature
Applications:- space technology
- rotorcraft and aircraft industry
- sonar technology
- vibration and noise reduction
Characterization of the PiezoSystems Jena
PAHL120/20 piezoelectric actuator
20 Volts
40 Volts
60 Volts
80 Volts
105 Volts
120 Volts
140 Volts
150 Volts
3000
2500
Force (N)
USC Mechanical Engineering
3500
2000
1500
External
stiffness
1000
500
0
20
40
60
80
100
120
Displacement
(m)
Manufacturer: PiezoSystems Jena
Model # : PAHL120/20
Maximum voltage (V): 150
Max. displ. (m): 120
Blocked force (N): 3500
Capacitance (F): 42
Coupled electro-mechanical behavior of PAHL 120/20
Actuator
ke
ki
Force,
Displacement
Voltage
Etrema actuator
R
UT
RE
LE
ULE
UR
URE
Measured : UT, UR, delay (phase) between
and
fUT
10001050

U
2000
R
100
Manufacturer: Etrema Inc.
Model # : AA –140J013
Maximum current (A RMS): 3
Max. displ. (m): 70
Max. dynamic force (N): 890
Blocked force (N): 1740
DC Resistance (W): 2.3
Inductance (mH): 3.5
Impedance (Ohms)
USC Mechanical Engineering
Impedance measurements on the ETREMA
AA140J130 Magnetostrictive actuator
Impedance analyzer ~0V
PhAngle method 23.0V
PhAngle method 34.5V
PhAngle method 46.4V
PhAngle method 58.6V
80
60
40
20
1000
1200
1400
1600
1800
2000
Frequency (Hz)
Electric impedance change with current and frequency
USC Mechanical Engineering
Summary

Mechatronics – Micro-controllers Education

Vibration Monitoring Enhancement Program (VMEP)

E/M Impedance Structural Health Monitoring

Wave Propagation Non-destructive Evaluation

Smart Materials Actuation