Ultrasonic Sonic Imaging for a Two Phase System Based on Support Vector Machine Classifier

Abstract:

Multiphase flow characterization is an important task for monitoring, measuring or controlling industrial processes. This can be done by means of process tomography. The use of tomographic techniques has been used within the oil industry. One of the potential applications is flow visualization and measurement in producing wells. Research on industrial process tomography consists in obtaining estimated images of a cross section of a pipe or vessel containing or carrying the substances of the process. One category of process tomography is ultrasonic tomography technique. A simple tomography can be built by mounting a number of sensors around the circumference of a horizontal pipe. This includes acquiring and processing ultrasonic signals from the transducers to obtain the information of the spatial distributions of liquid and gas in an experimental column. Analysis on the transducers’ signals will be carrying out to distinguish between the observation time and the Lamb waves. The information obtained from the observation time is useful for further development of the image reconstruction. To obtain the time easily, the time will be calculated from the starting pulse of transmitter signal until the starting peak of receiver signal. Finally Support Vector Machine (SVM) was employed to distinguish of each phase between water and gas.

• Periodical: Advanced Materials Research (Volume 1016)
• Pages: 273-278
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1016.273
• Online since: August 2014
• Authors: Mohd Faizal Mat Desa*, Muhammad Naufal Mansor, Ahmad Kadri Junoh, Amran Ahmed, Wan Suhana Wan Daud, Azrini Idris
• Keywords: Image Reconstruction, Multiphase Tomography, Process Tomography, Support Vector Machine (SVM), Ultrasonic Tomography

References

[1] R. A. Williams, and M. N. Beck, Process Tomography- Principles, Techniques and Application, Butterworth Heinemann Ltd. (1995).

[2] D. Ensminger, Ultrasonics – the Low and High Intensity Applications, New York: Marcel Dekker Inc. (1973).

[3] N. M. Ayob (2008) Optical Based Tomography Imaging For Visualizing Solid Particle In Vertical Column,. FYP Report, University Malaysia Perlis, Malaysia.

[4] M. R. Manan, M. H. F. Rahiman, S. Yaacob, Z. Zakaria and R. Abdul Rahim. Multiphase Ultrasonic Tomography Technique for Homogeneous and Nonhomogeneous Media Identification,. Thesis Tomography Imaging Research Group, School of Mechatronic Engineering Universiti Malaysia Perlis, Malaysia and Process Tomography Research Group (PROTOM), Department of Control and Instrumentation Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia.

DOI: 10.30880/ijie.2020.12.08.003

[5] L. A. Xu, (1987). Pulsed Ultrasound Cross-Correlation Flowmeter for Two – Component Flow Measurement. University of Manchester Institute of Science and Technology: Ph.D. Thesis.

[6] L., Xu, Y., Han, , L. A Xu. and J. Yang, (1997). Application of Ultrasonic Tomography to Monitoring Gas/Liquid Flow. Chemical Engineering Science. 52: 2171-2183.

DOI: 10.1016/s0009-2509(97)00043-2

[7] L. J. Xu, X. M Li, F., Dong, Y. Wang, and L. A. Xu, (2001). Optimum Estimation of the Mean Flow Velocity for the Multi-Electrode Inductance Flowmeter. Measurement Science Technology. 12: 1139–1146.

DOI: 10.1088/0957-0233/12/8/321

[8] L. J. Xu, and L. A. Xu, (1997). Gas/Liquid Two-Phase Flow Regime Identification by Ultrasonic Tomography. Flow Measurement Instrumentation. 8(3/4): 145- 155.

DOI: 10.1016/s0955-5986(98)00002-8

[9] C. K. San, Real Time Image Reconstruction For Fan Beam Optical Tomography System. Universiti Teknologi Malaysia : M. Sc Thesis, (2003).

[10] R. Boylestad and L. Nashelsky. Electronic Devices and Circuit Theory, 7th Edition. United States: Prentice Hall, (1999).

[11] V. Vapnik. The Nature of Statistical Learning Theory. Statistics for Engineering and Information Science. Springer Verlag, Berlin, (2000).

[12] S. Brahnam, F. C. Cgao, Y. S Frank, and R. S. Melinda SVM classification of neonatal facial image of pain, Proceedings of the 6th International Workshop on Fuzzy Login and Applications (WILF05).