Technical Papers
Mar 29, 2012

Damage Detection in Pipes under Changing Environmental Conditions Using Embedded Piezoelectric Transducers and Pattern Recognition Techniques

Publication: Journal of Pipeline Systems Engineering and Practice
Volume 4, Issue 1

Abstract

This paper presents the preliminary results of a research project that investigates the feasibility of continuous monitoring techniques using piezoelectric transducers (PZTs) permanently installed on steel pipes. The ultrasonic waves generated by PZTs are multimodal and dispersive. Therefore, it is difficult to detect changes created by the presence of damage, and it is even more difficult to differentiate changes produced by damage from benign changes produced by variation in environmental and operational conditions. In this paper, the results are reported of applying pattern recognition techniques to detect a mass scatterer (a proxy for damage) under ambient variations primarily due to varying internal pressure of a pipe. Using wavelet methods, 303 features are extracted, and adaptive boosting, modified adaptive boosting, and support vector machines for damage detection are employed. The performances of the three classifiers are evaluated over 41 trials with different combinations of training and testing data, resulting in the average accuracies of 85, 89, and 94%, respectively. Finally, the effectiveness of wavelet processing and features selected are discussed.

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Acknowledgments

The work is based on an earlier project (the Instrumented Pipeline Initiative) that was supported by Department of Energy through Concurrent Technologies Corporation and by the Pennsylvania Infrastructure Technology Alliance; this work is funded by the Westinghouse Electric Company. The authors would also like to thank Professor Lawrence Cartwright at Carnegie Mellon University for his advice on operating the experimental apparatus, and Dr. Yuanwei Jin at University of Maryland Eastern Shore and Mr. Xuan Zhu at University of Pittsburgh for their discussions on this work.

References

Burges, C. J. (1998). “A tutorial on support vector machines for pattern recognition.” Data Min. Knowl. Discov., 2(2), 121–167.
Chang, C., and Lin, C. (2001). “LIBSVM: A library for support vector machines.” Software available at 〈http://www.csie.ntu.edu.tw/~cjlin/libsvm〉 (Nov. 8, 2012).
Cortes, C., and Vapnik, V. (1995). “Support-vector networks.” Mach. Learn., 3(20), 273–297.
Freund, Y., and Schapire, R. E. (1997). “A decision-theoretic generalization of on-line learning and an application to boosting.” J. Comput. Syst. Sci., 55(1), 119–139.
Lowe, M. J. S., Alleyne, D. N., and Cawley, P. (1998). “Defect detection in pipes using guided waves.” Ultrasonics, 36(1–5), 147–154.
Lu, Y., and Michaels, J. E. (2009). “Feature extraction and sensor fusion for ultrasonic structural health monitoring under changing environmental conditions.” IEEE Sensor. J., 9(11), 1462–1471.
Mallat, S. G. (1999). A wavelet tour of signal processing, Academic Press, New York.
Rizzo, P., Bartoli, I., Marzani, A., and di Scalea, F. L. (2005). “Defect classification in pipes by neural networks using multiple guided ultrasonic wave features extracted after wavelet processing.” J. Pressure Vessel Technol., 127(3), 294–303.
Sohn, H., Farrar, C. R., Hunter, N. F., and Worden, K. (2001). “Structural health monitoring using statistical pattern recognition techniques.” J. Dyn. Syst. Meas. Contr., 123(4), 706–711.
Worden, K., and Manson, G. (2007). “The application of machine learning to structural health monitoring.” Philos. Trans. R. Soc., A, 365(1851), 515–537.
Ying, Y., et al. (2010). “Time reversal for damage detection in pipes.” Proc. SPIE, 7647, 76473S.1–12.
Ying, Y., et al. (2011). “Applications of machine learning in pipeline monitoring.” Proc., 2011 ASCE Int. Workshop on Computing in Civil Engineering, Miami, FL, ASCE, Reston, VA, 242–249.

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Information

Published In

Go to Journal of Pipeline Systems Engineering and Practice
Journal of Pipeline Systems Engineering and Practice
Volume 4Issue 1February 2013
Pages: 17 - 23

History

Received: Jul 18, 2011
Accepted: Mar 26, 2012
Published online: Mar 29, 2012
Published in print: Feb 1, 2013

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Authors

Affiliations

Yujie Ying, Ph.D. [email protected]
M.ASCE
Dept. of Civil and Environmental Engineering, Carnegie Mellon Univ., Pittsburgh, PA 15213 (corresponding author). E-mail: [email protected]
James H. Garrett Jr., Ph.D. [email protected]
P.E.
F.ASCE
Dept. of Civil and Environmental Engineering, Carnegie Mellon Univ., Pittsburgh, PA 15213. E-mail: [email protected]
Joel Harley [email protected]
Dept. of Electrical and Computer Engineering, Carnegie Mellon Univ., Pittsburgh, PA 15213. E-mail: [email protected]
Irving J. Oppenheim, Ph.D. [email protected]
P.E.
M.ASCE
Dept. of Civil and Environmental Engineering, Carnegie Mellon Univ., Pittsburgh, PA 15213. E-mail: [email protected]
P.E.
Dept. of Civil and Environmental Engineering, Carnegie Mellon Univ., Pittsburgh, PA 15213. E-mail: [email protected]
Lucio Soibelman, Ph.D. [email protected]
M.ASCE
Dept. of Civil and Environmental Engineering, Carnegie Mellon Univ., Pittsburgh, PA 15213. E-mail: [email protected]

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