Locating Mechanical Damages Using Magnetic Flux Leakage Inspection in Gas Pipeline System

  • Kim, Jae-Joon (School of Computer and Communication Engineering, Daegu University)
  • Received : 2010.10.21
  • Accepted : 2010.12.10
  • Published : 2010.12.30

Abstract

Gas transmission pipelines are often inspected and monitored using the magnetic flux leakage method. An inspection vehicle known as a "pig" is launched into the pipeline and conveyed along the pipe by the pressure of natural gas. The pig contains a magnetizer, an array of sensors and a microprocessor-based data acquisition system for logging data. This paper describes magnetic flux leakage (MFL) signal processing used for detecting mechanical damages during an in-line inspection. The overall approach employs noise removal and clustering technique. The proposed method is computationally efficient and can easily be implemented. Results are presented and verified by field tests from an application of the signal processing.

Keywords

Acknowledgement

Supported by : Daegu University

References

  1. AfZal, M., Kim, J., Udpa, S. S, Udpa, L. and Lord, W. (1999) Enhancement and Detection of Mechanical Damage MFL Signals from Gas Pipeline Inspection, Review of Progress in Quantitative Nondestructive Evaluation, Vol. 18A, pp. 805-812
  2. Blitz, J. (1991) Electrical and Magnetic Methods of Nondestructive Testing, Adam Hilger, Bristol, and Philadelphia and New York.
  3. Canny, John (1986) A Computational Approach to Edge Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 8, No. 6, pp. 679-698
  4. Clapham, L., Wood, I. and Piazza, M. (2008) Understanding Magnetic Flux Leakage(MFL) Signals from Mechanical Damage in Pipelines, Technical Report, United States Department of Transportation
  5. Ivanov, P. A., Zhang, Z., Yeoh, C. H., Udpa, L., Sun, Y., Udpa, S. S. and Lord, W. (1998) Magnetic Flux Leakage Modeling for Mechanical Damage in Transmission Pipelines, IEEE Transaction on Magnetics, Vol. 34, pp. 3020-3023 https://doi.org/10.1109/20.717706
  6. Lee, Jinyi, Hwang, Jiseong, Jun, Jongwoo and Choi, Seho (2008) Nondestructive Testing and Crack Evaluation of Ferromagnetic Material by Using the Linearly Integrated Hall Sensor Array, Journal of Mechanical Science and Technology, Vol. 22, pp. 2310-2317 https://doi.org/10.1007/s12206-008-0908-5
  7. Mandayam, S., Udpa, L., Udpa, S. S. and Lord, W. (1996) Invariance Transformations for Magnetic Flux Leakage Signals, IEEE Transactions on Magnetics, Vol. 32, No. 3, pp. 1577-1580 https://doi.org/10.1109/20.497553
  8. Shapiro, L. G. and Stockman, G. C. (2001) Computer Vision, Prentice Hall
  9. Tou, J. T. and Gonzalez, R. C. (1974) Pattern Recognition Principles, Addison-Wesley Publishing Company, New York, USA
  10. Weisweiler, F. J. and Sergeev, G. N. (1987) Non-Destructive Testing of Large-Diameter Pipe for Oil and Gas Transmission Lines, VCH, Weinheim (Germany)