A Smart Flow Measurement System Adaptive to Different Variation Using Ultrasonic Flowmeter

A Smart Flow Measurement System Adaptive to
Different Variation Using Ultrasonic Flowmeter
Sheikh Rafik Manihar Ahmed, Souvik Das
Control System Engineer
Fluor Daniel India Private Limited, Gurgaon
New Delhi, India
Abstract- This Paper Explain the Design of a Smart Flow
measurement Technique using Ultrasonic Flow Meter for
custody transfer quality. The objective of the work are; (i) to
extend the linearity range of measurement to 100% of the input
range, (ii) to make the measurement system adaptive to
variations in pipe diameter, liquid density, and liquid
temperature. An Accurate flow measurement is an essential
requirement both from qualitative and economic points of view.
Among the non contact type of flow measurement, ultrasonic
flow measurement is widely used to measure flow, because of its
advantage like high resolution and less interference of noise on
output. However, non linear characteristics of Ultrasonic flow
meters have restricted its use. An optimal Computational Logic is
considered by comparing various schemes and algorithms based
on minimization of Mean Square Error and Regression close to
one. The output of ultrasonic flow meter is frequency. It is
converted to voltage by using a frequency to voltage converter.
An optimal Computational logic block is added in cascade to
frequency to voltage converter. This arrangement helps to
linearise the overall system for 100% of full scale and makes it
adaptive to variations in pipe diameter, liquid density, and liquid
temperature. Since the proposed Smart flow measurement
technique produces output which is adaptive to variations in pipe
diameter, liquid density, and liquid temperature, the present
technique avoids the requirement of repeated calibration every
time there is change in liquid, and/or pipe diameter, and/or liquid
temperature. The results show that proposed measurement
technique achieves the objectives quite satisfactorily.
Keywords- Computational Logic, Sensor Modeling, Ultrasonic
transreceiver, Instrumentation Amplifier, Frequency to voltage
converter, Ultrasonic flow meter, Calibration Scale (CS), Full Scale
(FS), Temperature Compensation, Absolute Error, Mean Square
Error.
I. INTRODUCTION
Flow measurement has evolved over the years in response
to measure new products, measure old products with new
condition of flow, and for tightened accuracy requirement as
the value of the fluid is gone up. Flow measurement is the
quantification of bulk fluid movement. Flow can be measured
in a variety of ways, may be by contact type or non-contact
type of sensor. Positive-displacement flow meters accumulate
a fixed volume of fluid and then count the number of times the
volume is filled to measure flow. Other indirect flow
measurement methods rely on forces produced by the flowing
stream as it overcomes a known constriction. Flow may be
measured by measuring the velocity of fluid over a known
area. Accurate flow measurement is an essential requirement
both from qualitative and economic points of view. Among
the non contact type of flow measurement, ultrasonic flow
measurement is widely used to measure flow, because of its
advantage like high resolution and less interference of noise
on output. However, non linear characteristics of Ultrasonic
flow meters have restricted its use.
When flowmeters accuracy is stated in % CS or % FS
units, its absolute error will rise as the measured flow rate
drops. If meter error is stated in % AR, the error in absolute
terms stays the same at high or low flows. Because full scale
(FS) is always a larger quantity than the calibrated span (CS),
a sensor with a % FS performance will always have a larger
error than one with the same % CS specification. Therefore, in
order to compare all bids fairly, it is advisable to convert all
quoted error statements into the same % AR units. It is also
recommended that the user compare installations on the basis
of the total error of the loop. For example, the inaccuracy of
an orifice plate is stated in % AR, while the error of the
associated d/p cell is in % CS or % FS. Similarly, the
inaccuracy of a Coriolis meter is the sum of two errors, one
given in % AR, and the other as a % FS value. Total
inaccuracy is calculated by taking the root of the sum of the
squares of the component inaccuracies at the desired flow
rates. In well-prepared flowmeter specifications, all accuracy
statements are converted into uniform % AR units and these %
AR requirements are specified separately for minimum,
normal, and maximum flows. All flowmeter specifications and
bids should clearly state both the accuracy and the
repeatability of the meter at minimum, normal, and maximum
flows.
To overcome the restriction faced due to nonlinear
response characteristics of the ultrasonic flow meter, several
techniques have been suggested. But some of these are tedious
and time consuming. Further, the process of calibration needs
to be repeated or calibration circuit needs to be replaced/ tuned
every time there is a change in pipe diameter or liquid density.
The problem of nonlinear response characteristics of an
Ultrasonic Flowmeter further aggravates when there is a
change in liquid temperature, since the output of an Ultrasonic
Flowmeter is dependent on temperature also.
To overcome the above difficulties, a Smart flow
measurement technique is proposed in this paper. The optimal
Computational Logic is achieved considering different
algorithms and schemes and comparing their least Mean
Square Error and Regression close to one. This optimized
Computational Logic is used to train the system to obtain
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linearity and makes the output adaptive to variations in pipe
diameter, liquid density, and liquid temperature, all within a
range.
Literature review suggests that several techniques are
adopted to calibrate the Ultrasonic Flowmeter. In [1],
linearization of Ultrasonic Flowmeter with the help of neural
network algorithm is done. In [2], [4-7] calibration of flow
meter using several hardware circuits is discussed. In [3]
design of Ultrasonic Flowmeter is discussed in order to
achieve maximum accuracy and implementation of
microcontroller to linearise the output. In [8] linearization of
Ultrasonic Flowmeter and making its output independent of
physical parameters using Computational Logic is discussed.
II. BLOCK DIAGRAM OF THE PROPOSED SYSTEM
The project was undertaken with consideration of the
prevailing methodologies and service with particular emphasis
to extend the linearity range of measurement to 100% of the
input range, to make the measurement system adaptive to
temperature and other major motivating factors being as
shown in Block Diagram.
Figure.1: Block Diagram of the proposed measuring
Technique.
The Block Diagram of the above Proposed Measuring System
is consisting of Ultrasonic Flow Measurements, Frequency to
Voltage Converter, Computational Logic Blocks.
A. Ultrasonic Flow Meter
Ultrasonic flow meters have gained a lot of attention over
the past years, primarily because of their ability for measuring
custody transfer of natural gas. They are replacing differential
pressure and turbine flow meters in many natural gas
applications. Ultrasonic Flowmeters are also widely used to
measure liquid flow. This is not limited to clean liquids either.
A special type of Ultrasonic Flowmeter can accurately
measure the flow of slurries and liquids with many impurities
Ultrasonic flow meters are one of the most interesting
types of meters used to measure flow in pipes. The most
common variety, transit time, has both a sending and a
receiving transducer. Figure 1 shows the arrangement of one
such Ultrasonic Flowmeter. Both sending and receiving
transducers are mounted on either side of the flow meter, or
the pipe wall. The sending transducer sends an ultrasonic
signal at an angle from one side of the pipe which is received
by the receiving transducer. The flow meter measures the time
that the ultrasonic signal takes to travel across the pipe in
forward and reverse direction. When the signal travels along
the direction of the flow, it travels more quickly compared to
the condition of no flow. On the other hand, when the signal
travels against the direction of flow, it slows down. The
difference between the “transit times” of the two signals is
proportional to flow rate [5, 10-13].
Figure.2: Ultrasonic Transreceiver.
From Figure 2, we have
Tup =
𝑀+ 𝐷
𝐶𝑜𝑠𝜃
𝐶𝑜+𝑉𝑠𝑖𝑛𝜃
(1)
Tdown=
𝑀+ 𝐷
𝐶𝑜𝑠𝜃
𝐶𝑜−𝑉𝑠𝑖𝑛𝜃
(2)
ΔT = Tup – Tdown (3)
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Frequency, FIN = 1/ΔT
Where: -
M – No of times ultrasonic signal travels in forward/
backward direction
Co – Velocity of ultrasonic signal in static fluid
D – Pipe diameter
V – Velocity of fluid
The velocity of ultrasonic signal depends on [13] density of
liquid as shown in Figure.3,
𝑘/𝜌 (4)
With k – bulk modulus and
ρ – Density of liquid
Effect of temperature on density [14-15] can be given by
⟦
𝜌°
1+𝛼(𝑡1−𝑡ₒ)
⟧
1−(𝑃𝑡₁−𝑃𝑡ₒ)
𝐸
(5)
Where:-
ρ1 – specific density of liquid at temperature t1
ρ0 - specific density of liquid at temperature t0
Pt1 – pressure at temperature t1
Pt0 – pressure at temperature t0
E– Modulus of elasticity of the liquid
α – temperature coefficient of liquid
Figure.3: Ultrasonic Flowmeter with Control
Arrangement.
B. Ultrasonic Flowmeter Characteristics
Meters are chosen for their application by their
performance characteristics. The Ultrasonic Flowmeter is a
high accuracy (custody transfer quality), wide flow range
meter capable of high accuracy as shown in Figure.3 at high or
low flow rates. Ultrasonic Flowmeters are large capacity
meters for their diametric size. They are calibrated meters and
commonly replace multiple parallel orifice meters with only
one Ultrasonic Flowmeter. They are more tolerant to tube wall
build-up than most meters. They are full-bore with no
restriction. Ce Flowmeters measure very low flow rates or
rates as fast as you would operate a line without causing
component erosion. The meter’s wet-gas performance is
excellent compared to conventional high accuracy metering
technologies. Ultrasonic meters operate well at high pressures.
They are in operation in gas injection applications up to
10,000 PSI. The characteristics alone offer a wide choice of
applications; however, it is interesting that only a few meter
tube design configurations are necessary to accomplish the
entire range of applications. There are numerous site
configurations possible. Designers should plan site tie-ins
carefully.
III. DATA CONVERSION AND AMPLIFYING UNIT
The block diagram representation of the proposed technique is
given in Figure.1 & 3.
A. Frequency to Voltage Converter
IC LM2917 IC chip is designed specifically as a
Frequency to Voltage Converter or Frequency to Voltage
converter. In its use to applications Frequency to Voltage
Converter IC LM2917 requires few external components. The
LM2917 series is a monolithic frequency to voltage converters
with high gain op amp/comparator designed to operate a relay,
lamp, or other load when the input frequency reaches or
exceeds a selected rate [14-15]. The op-amp/comparator is
fully compatible with the sensors and has a floating transistor
as its output. The collector may be taken above VCC up to a
maximum VCE of 28V.
VOUT = FIN x R x C x VCC (6)
The advantages of single chip LM2917 Frequency to Voltage
Converter is able to provide instantaneous volt output o at
time of frequency change 0 Hz. Very easy to apply in
measuring the output frequency with the formulation of
single-chip Frequency to Voltage Converter VOUT = FIN x
VCC x R1 x C1. Then the single-chip LM2917 Frequency to
Voltage Converter This configuration requires only the RC
only in frequency doublings. And has an internal zener
regulator to aimlessly accuracy and stability in frequency-to-
voltage conversion process.
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 Frequency to Voltage Converter
 Feature-owned single-chip LM2917
Frequency to Voltage Converter
 Reference to ground directly with variable
reluctance
 Op-Amp / Comparator with transistor output
 50 mA maximum output currents for
application directly to the load
 Frequency doubling until low ripel
 Build in zener
 Linear output ± 0.3%
Figure.4: Circuit Diagram of Frequency to
Voltage Converter IC LM2917.
B. Instrument Amplifier
A traditional method for building an instrumentation
amplifier is to use three op amps and seven resistors as shown
in Figure 5. This approach requires four precision matched
resistors for a good common-mode rejection ratio (CMRR).
Errors in matching will produce errors at the final output. An
imbalance of one or two picofarads on certain nodes will
drastically degrade the high frequency CMRR, a fact often
overlooked. This circuit uses a monolithic difference amplifier
with laser trimmed thin film resistors for the output amplifier,
thereby providing good dc and ac accuracy with fewer
components than the traditional approach.
Figure.5: Circuit Diagram of Instrument
Amplifier.
This circuit utilizes difference amplifier and
two Non-Inverting amplifiers, which have low noise, low drift,
low offset, and high speed. For high impedance sources, the
Non-Inverting Amplifier is an ideal choice for the input stage
amplifiers due to the extremely low input bias current of their
JFET inputs.
The op amps selected for the input stage must also
have low offset voltage and low offset voltage drift with
temperature. They also need to have good drive
characteristics. This allows the use of low value resistors to
minimize resistor thermal noise. Headroom issues relating to
the op amp must be considered in this circuit for proper
operation.
When working with any op amp having a gain-
bandwidth product greater than a few MHz, careful layout and
bypassing are essential. A typical decoupling network consists
of a 1 μF to 10 μF electrolytic capacitor in parallel with a 0.01
μF to 0.1 μF low inductance ceramic MLCC type.
For the lowest noise with low impedance sources
only, low voltage noise is important. The Inverting
Amplifier has lower noise, lower offset voltage drift, and
lower supply current; but the input bias currents are much
higher, and the bandwidth will be lower than that obtained
with the Non-Inverting Amplifier. The measured −3 dB points
are 56.6 kHz and 87.6 kHz for the Inverting Amplifier and
Non-Inverting Amplifier, respectively.
With high impedance sources, the input bias current and the
input noise current of a bipolar op amp can result in errors.
The bias current creates an I × R drop, which will be
multiplied by the overall circuit gain. This can result in several
volts of offset at the output. The input noise current is also
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multiplied by the source impedances, creating an additional
noise voltage. To avoid this, a JFET input op amp, such as the
Non-Inverting Amplifier, should be used. Even though the
voltage noise is slightly higher than the Inverting Amplifier,
the current noise is significantly lower, resulting in lower
overall noise when used with high impedance sources.
As Figure 5 and Figure 6 show, the Inverting Amplifier is the
proper choice with low source impedances, and the Non-
Inverting Amplifier is better with higher source impedances.
There is a trade-off: the input capacitance of JFET op amps is
higher than bipolar op amps, so the RC time constant must be
considered.
Figure.6: Graph between Gain and Frequency
IV. RESULTS AND CONCLUSIONS
The output voltage of data conversion and
Amplifying unit for a particular flow, pipe diameter, liquid
density, and liquid temperature is stored as a row of input data.
Various such combinations of input flow, pipe diameter, liquid
density, liquid temperature, and their corresponding voltages
at the output of data conversion and Amplifying unit are used
to form the other rows of input data. The output of the
Computational logic Block is the target matrix consisting of
data having a linear relation with the flow and adaptive to
temperature.
Mean Squared Error is the average squared difference
between outputs and targets. Lower value of MSE is better.
Zero means no error. Regression measures the correlation
between output and target. Regression equal to 1 means a
close relationship and 0 means a random relationship.
It is subjected to various test inputs corresponding to
different pipe diameters, liquid densities, and temperatures of
liquid, all within the respective specified ranges. For testing
purposes, the range of flow is considered from 0.0 to
0.0025m³/s, range of pipe diameter is 4 inches to 12 inches,
range of liquid density is 1500 to 2500 Kg/m³, and liquid
temperature is 25 to 75 Celsius. The flow measured by the
proposed technique corresponding to sample test inputs are
tabulated in Table 1. It shows that the actual flow rates and the
measured flow rates by the proposed technique are same.
Table.1: Result of Measuring System using Ultrasonic Flowmeter.
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V. REFERENCES
[1]. T. T. Yeh, P. I. Espina and S. A. Osella, “An Intelligent
Ultrasonic Flow Meter for Improved Flow Measurement and
Flow Calibration Facility”, Proc. IEEE Conf. On Instrument and
Measurement Technology, Budapest, Hungary, (2001), pp. 1741-
1746.
[2]. O. Keitmann-Curdes and B. Funck, “A new calibration method
for ultrasonic clamp-on transducers”, IEEE Symposium on
Ultrasonic’s, Berlin, (2008), pp. 517-520.
[3]. Ch. Buess, “Transit-Time Ultrasonic Airflow Meter for Medical
Application”, Thesis, Swiss Federal Institute of Technology,
(1988).
[4]. Santhosh KV and BK Roy, “An Intelligent Flow Measuring
Scheme Using Ultrasonic Flowmeter”, 31st International
Conference on Modelling, Identification and Control (2012)
April, Thailand.
[5]. J. Yang and H. Jiao, “Design of Multi-channel Ultrasonic
Flowmeter based on ARM”, Proc. IEEE Conf. on Electrical and
Control Engineering, Yichang, China, (2010), pp. 758-761.
[6]. E. Aziz, Z. Kanev, M. Barboucha, R. Maimouni and M.
Staroswiecki, “An ultrasonic flowmeter designed according to
smart sensors concept”, Proc. IEEE 8th Mediterranean Electro
technical conference, France, (1996), pp. 1371-1374.
[7]. L. Guowei and C. Wuchang, “The Measurement Technology of
Flow Rate and Instrument”, China Machine Press, (2002) June.
[8]. P. I. Espina, P. I. Rothfleisch, T. T. Yeh and S. A. Osella,
“Telemetrology and advanced ultrasonic flow metering”, Proc. of
the 4th International Symposium on Fluid Flow Measurement,
Denver, USA, (1999).
[9]. L. C. Lynnworth, “Ultrasonic measurements for process control”,
Academic Press, San Diego, CA, (1989).
[10]. L. Z. Yang, Z. Zhang and Dongsheng, “The Experiment Study of
Ultrasonic Flowmeter Precision”, Journal of Xi’an University of
Technology, vol. 22, no. 1, (2006), pp. 70-72 .
[11]. J. Yoder, “Many Paths to Successful Flow Measurement”, Flow
Control Network, (2006) February.
[12]. R. J. Plaza, “Sink or Swim: The Effects of Temperature on Liquid
Density and Buoyancy”, California state science fair, (2006).
[13]. B. G. Liptak, “Instrument Engineers' Handbook: Process
Measurement and Analysis”, 4th Edition, CRC Press, (2003)
June.
[14]. D. Karaboga, “An idea based on honey bee swarm for numerical
optimization”, Technical report-tr06, Erciyes university,
engineering faculty, computer engineering department (2005).
[15]. F. M. Dias, A. Antunes, J. Vieira and A. M. Mota, “Implementing
the Levenberg-Marquardt Algorithm On-line: a sliding window
approach with early stopping”, Int. Conf. Proc. IFAC, USA,
(2004).
ABOUT THE AUTHOR
1.) Sheikh Rafik Manihar Ahmed received his Bachelor
of Engineering Scholar from Chhattisgarh Swami
Vivekananda Technical University, Bhilai,
Chhattisgarh. At Present he is Associate Design
Engineer I, Control System in Fluor Daniel India
Private Limited. He has published many Books &
Research paper in International & National Journal in
the field of Electronics, Robotics & Automation. He
also got many Awards related to Research Projects
like NIT, Kozhikode National Award for Best B.Tech
Project given by ISTE (Indian Society for Technical
Education), Best Innovative Idea Award given by IIT
Roorkee; Best Innovative Project Certificate of Merit
Awarded by O.P Jindal College.
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A Smart Flow Measurement System Adaptive to Different Variation Using Ultrasonic Flowmeter

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