A practically validated intelligent calibration technique using optimized ANN for ultrasonic flow meter

Design of an intelligent flow measurement technique by ultrasonic transducers using an Optimized Artificial Neural Network (OANN) is discussed in this paper. The objectives of the present work are (i) to extend the linearity range of flow measurement to 100% of full scale input range, (ii) to make the flow measurement technique adaptive to variations in (a) pipe diameter, (b) liquid density, (c) liquid temperature, and (iii) to achieve objectives (i) and (ii) by using an optimized artificial neural network. The output of an ultrasonic transducer is frequency. It is converted to voltage by using a suitable data conversion circuit. A suitable optimal ANN is added, in place of conventional calibration circuit, in cascade to data conversion circuit. ANN is trained, and tested with simulated data considering various values of pipe diameter, liquid density, and liquid temperature. The proposed technique is then subjected to practical data for validation. Results show that the proposed technique has fulfilled the desired objectives.

[1]  Cheng-Ta Chiang,et al.  A Semicylindrical Capacitive Sensor With Interface Circuit Used for Flow Rate Measurement , 2006, IEEE Sensors Journal.

[2]  Romesh Nagarajah,et al.  A Neural Network Approach to Fluid Quantity Measurement in Dynamic Environments , 2012 .

[3]  Volker Hans,et al.  Self-Monitoring Ultrasonic Gas Flow Meter Based on Vortex and Correlation Method , 2007, IEEE Transactions on Instrumentation and Measurement.

[4]  O. Keitmann-Curdes,et al.  A new calibration method for ultrasonic clamp-on transducers , 2008, 2008 IEEE Ultrasonics Symposium.

[5]  Michitsugu Mori,et al.  Ultrasonic pulse-Doppler flow meter application for hydraulic power plants , 2008 .

[6]  Lawrence C. Lynnworth,et al.  Ultrasonic measurements for process control , 1989 .

[7]  Wei-Yun Yau,et al.  A Pulsed Neural Network With On-Chip Learning and Its Practical Applications , 2007, IEEE Transactions on Industrial Electronics.

[8]  R. Fletcher.  Practical Methods of Optimization , 1988 .

[9]  Michitsugu Mori,et al.  A study of ultrasonic propagation for ultrasonic flow rate measurement , 2008 .

[10]  M. Staroswiecki,et al.  An ultrasonic flowmeter designed according to smart sensors concept , 1996, Proceedings of 8th Mediterranean Electrotechnical Conference on Industrial Applications in Power Systems, Computer Science and Telecommunications (MELECON 96).

[11]  Béla G. Lipták,et al.  Instrument Engineers Handbook Process Measurement And Analysis , 2005 .

[12]  Zhang Ha,et al.  A New Design for Ultrasonic Gas Flowmeter , 2006, 2006 6th World Congress on Intelligent Control and Automation.

[13]  Yingtao Jiang,et al.  Flow Rate Measurement in a High-Temperature, Radioactive, and Corrosive Environment , 2011, IEEE Transactions on Instrumentation and Measurement.

[14]  Seul Jung,et al.  Hardware Implementation of a Real-Time Neural Network Controller With a DSP and an FPGA for Nonlinear Systems , 2007, IEEE Transactions on Industrial Electronics.

[15]  Fernando Morgado Dias,et al.  Implementing the Levenberg-Marquardt Algorithm on-line: A Sliding Window Approach with Early Stopping , 2004 .

[16]  Simon Haykin,et al.  Regularized radial basis functional networks: theory and applications , 2001 .

[17]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[18]  Yun-Kung Chung,et al.  A Novel Back-propagation Neural Network Training Algorithm Designed by an Ant Colony Optimization , 2005, 2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific.

[19]  Badal Chakraborty,et al.  A Novel Technique of Flow Measurement for a Conducting Liquid , 2009, IEEE Transactions on Instrumentation and Measurement.

[20]  Rainer Haldenwang,et al.  Optimisation of Pulsed Ultrasonic Velocimetry system and transducer technology for industrial applications. , 2013, Ultrasonics.

[21]  Malcolm J. W. Povey,et al.  Ultrasonic Techniques for Fluids Characterization , 1997 .

[22]  Béla G. Lipták,et al.  Instrument engineers' handbook , 2012 .

[23]  F. Girosi,et al.  Networks for approximation and learning , 1990, Proc. IEEE.

[24]  Lei Qi,et al.  Development of a gas flow and velocity calibration facility , 2012, 2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet).

[25]  Dervis Karaboga,et al.  AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .

[26]  Kourosh Kolahi,et al.  Model-based density measurement with Coriolis flowmeter , 2006, IEEE Transactions on Instrumentation and Measurement.

[27]  D. Kouame,et al.  Methodology for developing a high-precision ultrasound flow meter and fluid velocity profile reconstruction , 2008, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[28]  Bryant D. Taylor,et al.  A Wireless Fluid-Level Measurement Technique , 2007 .

[29]  Roger Fletcher,et al.  Practical methods of optimization; (2nd ed.) , 1987 .

[30]  J. Navarro-Pedreño.  Numerical Methods for Least Squares Problems , 1996 .

[31]  Luca Maria Gambardella,et al.  An Ant Colony Optimization Approach to the Probabilistic Traveling Salesman Problem , 2002, PPSN.

[32]  Lianfen Qian,et al.  Regularized Radial Basis Function Networks: Theory and Applications , 2002, Technometrics.