Wright State University
Department of Mechanical and Materials Engineering
ME 495: THERMAL-FLUID SCIENCES LABORATORY
Flow Meter Calibration
Objective:
Learn how to calibrate an electronic flow meter using a data acquisition system and
LabVIEW software.
References:
The manuals for the flow meter and signal conditioner are given below:
FTB-9506 Turbine Flow Meter: http://www.omega.com/manuals/manualpdf/M2728.pdf
or http://www.cs.wright.edu/people/faculty/sthomas/m2728.pdf
FLSC-61 Signal Conditioner: http://www.omega.com/manuals/manualpdf/M2729.pdf
or http://www.cs.wright.edu/people/faculty/sthomas/m2729.pdf
LabVIEW program for flowmeter calibration:
http://www.cs.wright.edu/people/faculty/sthomas/reader06.vi
Method:
Calibrate an electronic flow meter using a stop watch, lab scale and beaker. Analog DC
signals from the signal conditioner are to be collected using a data acquisition system
using a LabVIEW virtual instrument. This flow meter will be used later in the class
during an experiment.
Data to be collected:
1. The average voltage from the signal conditioner over at least 1 minute at each
setting.
2. The time it took to fill the beaker.
3. The mass of the water collected.
Report:
1. Title page
2. A copy of the table at the end of this document showing the hand-written raw data
collected for the flow meter.
3. A plot of the mass flow rate (gram/sec) versus the voltage reading (volts) (x-axis
= voltage, y-axis = mass flow rate) for the flow meter. Use a regression analysis
to fit a straight line to the data. Show the equation of the straight line and the R2
term on the plot. The equation must be in scientific notation with at least five
significant digits for each coefficient.
4. A plot of the calibration uncertainty of the mass flow rate versus mass flow rate
for the flow meter (x-axis = mass flow rate, y-axis = uncertainty of the mass flow
rate).
5. Sample hand calculations showing the uncertainty analysis.
6. Answer the following questions:
 How does a turbine flow meter work? Provide a reference for your discussion.
 How repeatable was the experimental data? Discuss the variability of the mass
flow rate over the tested range.
 What is the uncertainty of the mass flow rate when the standard deviation is
0.24 g/s over 500 data points with a confidence level of 95%? Show all
calculations.
Discussion
Electronic flow meters are used in many applications where the flow rate within a pipe
must be continuously monitored and the data stored using a data acquisition system.
Attention must be paid to the behavior of the flow meter in order to not make mistakes in
interpreting the data. All flow meters have a stated range of operation. For turbine flow
meters, the DC voltage signal from the signal conditioner is proportional to the flow rate
only in the linear range of the device. If the flow rate approaches the lower flow rate
limit, the propeller in the turbine flow meter can stop intermittently, as shown below.
This will cause the average voltage to be an unreliable measure of the flow rate. A valid
voltage signal is shown in the figure below.
If the y-axis minimum is changed to the automatic setting in Excel, the data looks very
erratic:
The plot above shows that the data is scattered, but it does not have any obvious outliers.
Data sets should always be checked for outliers, which should be removed from the data.
Also, the data in the above plot does not follow a specific trend, either increasing or
decreasing, so the flow rate for this case was quite steady.
The turbine flow meter (Omega, Model FTB-9506) has been placed in a precision flow
loop for calibration as shown in the figure below. This flow loop consists of a constant
head pressure water tank elevated 16 feet above the floor, 1/2-inch copper piping to bring
the water to table level, 3/8-inch plastic flexible tubing, 3/8-inch brass flow straightening
sections (20-diameters long) upstream and downstream of the flow meter, a 90-µm filter
(Swagelok, Model SS-6TF-90) upstream of the flow straightening section, and a ball
valve upstream of the filter for adjusting the flow rate.
A signal conditioner (Omega, Model FLSC-61) is attached to the flow meter, and the
appropriate electrical voltage (12V DC) is applied to the signal conditioner with a power
supply (Hewlitt-Packard, Model 6253A). Voltage readings are detected across a 2500-Ω
resistor on a breadboard.
A data acquisition system is set to acquire voltage data from the signal conditioner by
opening a LabVIEW virtual instrument on the personal computer. The DAS consists of a
DAQ board (National Instruments, Model SCC-68) and a DAQ card (National
Instruments, Model PCI-6221) installed in the PC.
Determine the flow meter/signal conditioner voltage at the maximum mass flow rate
achievable by the flow loop system, and determine the voltage at the minimum mass flow
rate readable by the flow meter. Divide this range into ten equally-spaced nominal mass
flow rate settings for the purpose of obtaining a mass flow rate calibration equation.
Set the mass flow rate to one of the nominal values discussed above using the ball valve.
Start the DAS in order to collect voltage data from the flow meter/signal conditioner.
Measure the mass flow rate by hand five consecutive times while the DAS collects
voltage data at a rate of one reading every 0.2 seconds as follows:
1. Place a water collection container on the laboratory scale (Ohaus, Model EB3)
and zero the lab scale.
2. Place the container under the stream of water exiting the flow meter and
simultaneously start a digital stop watch.
3. Collect water for approximately 60 seconds.
4. Withdraw the container from the water stream, and simultaneously stop the stop
watch.
5. Measure the mass of water in the collection container using the laboratory scale
and recorded it by hand, and record the collection time by hand.
Repeat the above steps for the remaining nine nominal mass flow rate settings.
House
Pressure In
Constant Head
Pressure Tank
Float
Valve
Overflow
DAQ
Board
DAQ
Card
Ball
Valve
90-µm
Filter
PC
Signal
Conditioner
Stop
Watch
Turbine
Flow Meter
20-Dia. Flow
Straightening
Sections
Water
Collection
Container
Lab Scale
The calibration equation for the flow meter is found by plotting the mass flow rate
readings versus the corresponding mean voltage readings, as shown below. As can be
seen, the flow rate is quite linear (although not exactly) with respect to the voltage
reading.
The calibration uncertainty for the flow meter is equal to the root-sum-square (RSS)
uncertainty in each measurement plus the difference between the prediction by the bestfit calibration line and the actual data point.
m CAL  m RSS  m BF
The RSS uncertainty in each mass flow rate measurement can be found as follows:
 m
  m

 
 m   
 t 

m

t

 

2
m RSS
2
where the mass flow rate is given by
m 
m
t
Performing the indicated partial derivatives results in the following equation for the RSS
uncertainty:
 m   m  t 
 
  2 
 t   t 
2
m RSS
2
The uncertainty of the mass measurement can be estimated to be the resolution of the lab
scale, which is the smallest quantity that is readable on the digital readout (Δ𝑚 =
0.1 g). The uncertainty of the time measurement is the average time it takes a person to
start and then stop a stopwatch (Δ𝑡 = 0.15 s). The difference between the calibration
equation and the original data is given by
 BF  (aV  b)  m
 DATA
m
where 𝑎 and 𝑏 are coefficients obtained from the linear regression. The uncertainty of
the mass flow rate measurement can be estimated to be the sum of the total calibration
uncertainty discussed above and the confidence interval of the mass flow rate data
collected at a confidence level of 95%.
m  m CAL  m C95
To be conservative, the maximum calibration uncertainty shown in the plot in #4 above
would be appropriate.
FTB-9506 Turbine Flow Meter with the FLSC-61 Signal Conditioner
Trial
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Mean
Voltage
Time to Fill
Beaker (s)
Mass of
Water
(g)
Mass Flow
Rate (g/s)