Vol. 51

Front:[PDF file] Back:[PDF file]
Latest Volume
All Volumes
All Issues
2015-01-09

Joint Self-Adaptive Correlation Method and Modified Empirical Mode Decomposition for Soft Defect Detection in Cable by Reflectometry

By Soumaya Sallem and Nicolas Ravot
Progress In Electromagnetics Research Letters, Vol. 51, 47-52, 2015
doi:10.2528/PIERL14120503

Abstract

In a previous paper, we have introduced an innovative approach called the self-adaptive correlation method (SACM). It consists in treating the reflectogram in order to amplify the signatures of soft defects and make them more easily detectable. This method allows to highlight the soft defect while attenuating the noise present on the reflectogram and has the advantage of reducing the computational complexity compared to the state of the art. We drew attention to the sensitivity of the performance of this method to noise. In this paper, we propose a solution for the pre-denoising of reflectogram before applying the SACM. This solution consists of an adapted version of the empirical mode decomposition algorithm, we called MEMD for Modified Empirical Mode Decomposition which bypasses some limitations of the conventional EMD.

Citation


Soumaya Sallem and Nicolas Ravot, "Joint Self-Adaptive Correlation Method and Modified Empirical Mode Decomposition for Soft Defect Detection in Cable by Reflectometry," Progress In Electromagnetics Research Letters, Vol. 51, 47-52, 2015.
doi:10.2528/PIERL14120503
http://www.jpier.org/PIERL/pier.php?paper=14120503

References


    1. Pan, T.-W., C.-W. Hsue, and J.-F. Huang, "Time-domain reflectometry using arbitrary incident waveforms," IEEE Transactions on Microwave Theory and Techniques, Vol. 50, No. 11, 2558-2563, 2002.
    doi:10.1109/TMTT.2002.804644

    2. Vanhamme, H., "High resolution frequency-domain reflectometry," IEEE Transactions on Instrumentation and Measurement, Vol. 39, No. 2, 369-375, Apr. 1990.
    doi:10.1109/19.52517

    3. Smith, P., C. Furse, and J. Gunther, "Analysis of spread spectrum time domain reflectometry for wire fault location," IEEE Sensors Journal, Vol. 5, No. 6, 1469-1478, 2005.
    doi:10.1109/JSEN.2005.858964

    4. Auzanneau, F., "Wire troubleshooting and diagnosis: Review and perspectives," Progress In Electromagnetics Research B, Vol. 49, 253-279, 2013.
    doi:10.2528/PIERB13020115

    5. Shin, Y. J., Theory and application of time-frequency analysis to transient phenomena in electric power and other physical systems, Ph.D. Thesis, University of Texas, 2004.

    6. Franchet, M., Procédé de réflectométrie pour la détection de défauts non-francs dans un câble électrique et système mettant en oeuvre le procédé, EP 2769230 A1, Français Brev., 2011.

    7. Proakis, J. G. and D. G. Manolakis, Digital Signal Processing: Principles, Algorithms, and Applications, 3rd Ed., Prentice-Hall, 1996.

    8. Donoho, D. L., "De-noising by soft-thresholding," IEEE Trans. Inform. Theory, Vol. 41, No. 3, 613-627, 1995.
    doi:10.1109/18.382009

    9. Mallat, S. and Z. Zhang, "Matching pursuits with time-frequency dictionaries," IEEE Trans. Sig. Process., Vol. 41, 3397-3415, 1993.
    doi:10.1109/78.258082

    10. Huang, N. E., et al., The empirical mode decomposition and the hilbert spectrum for nonlinear and non-stationary time series analysis, Proc. R. Soc. Lond. A, Vol. 454, 903-995, The Royal Society, 1998.

    11. Sallem, S. and N. Ravot, "Self-adaptive correlation method for soft defect detection in cable by reflectometry," IEEE SENSORS 2014 Conference, 2114-2117, 2014.
    doi:10.1109/ICSENS.2014.6985455