FAULT DETECTION ALGORITHM USING DCS METHOD COMBINED WITH FILTERS BANK DERIVED FROM THE WAVELET TRANSFORM

Oussama Mustapha, Mohamad Khalil, Ghaleb Hoblos, Dimitri Lefebvre, Houcine Chafouk

2007

Abstract

The aim of this paper is to detect the faults in industrial systems, such as electrical machines and drives, through on-line monitoring. The faults that are concerned correspond to changes in frequency components of the signal. Thus, early fault detection, which reduces the possibility of catastrophic damage, is possible by detecting the changes of characteristic features of the signal. This approach combines the Filters Bank technique, for extracting frequency and energy characteristic features, and the Dynamic Cumulative Sum method (DCS), which is a recursive calculation of the logarithm of the likelihood ratio between two local hypotheses. The main contribution is to derive the filters coefficients from the wavelet in order to use the filters bank as a wavelet transform. The advantage of our approach is that the filters bank can be hardware implemented and can be used for online detection.

References

  1. Sottile J, Kohler J. An on-line method to detect incipient failure of turn insulation in random wound motors. IEEE Trans Energy Conver 1993;8(4):762-8.
  2. Schoen RR, Habetler TG, Kamran F, Bartheld RG. Motor bearing damage detection using stator current monitoring. IEEE Trans Ind Appl 1995;31(6):1274-9.
  3. Kliman GB, Premerlani WJ, Koegl RA, Hoeweler D. A new approach to on-line turn fault detection in AC motors. In: Proceedings of IEEE-IAS Annual Meeting, 1996:687-93.
  4. Awadallah M.A,Morcos M.M., Application of AI tools in faults diagnosis of electrical machines and drives - an verview, Trans. IEEE Energy Conversion, vol. 18, no. 2, pp. 245-251, june 2003.
  5. Benbouzid M., Vieira M., Theys C., "Induction motor's faults detection and localization using stator current advanced signal processing techniques" IEEE Transaction on Power Electronics, Vol. 14, N° 1, pp 14 - 22, January1999.
  6. Truchetet T. Ondelettes pour le signal numérique, collection traitement du signal, HERMES, Paris, 1998.
  7. Flandrin P. Temps fréquence, HERMES, Paris, 1993.
  8. Krim H., Pesquet J.C. Multiresolution analysis of a class of non stationnary processes. IEEE transaction on information theory, 1995, vol. 41, No 4,pp 1011-1020.
  9. Mallat S., Une exploration des signaux en ondelettes, les éditions de l'école polytechnique, Paris, juillet 2000.
  10. Nikiforov I. Sequential detection of changes in stochastic systems. Lecture notes in Control and information Sciences, NY, USA, 1986, pp. 216-228.
  11. Basseville M., Nikiforov I. Detection of Abrupt Changes: Theory and Application. Prentice-Hall, Englewood Cliffs, NJ, 1993.
  12. Khalil M. Une approche pour la détection fondée sur une somme cumulée dynamique associée à une décomposition multiéchelle. Application à l'EMG utérin. 17ème Colloque GRETSI sur le traitement du signal et des images, Vannes, France,1999.
  13. Li C., Zheng C., Tai C. Detection of ECG characteristic points using wavelet transform. IEEE transaction, BME, 1995, vol.42, No 1, pp 21- 29.
  14. Shenhadji L., Bellanger J.J., Carraut G. Détection temps échelle d'événements paroxystiques intercriptiques en électroencéphalogramme, traitement du signal, 1995, vol.12, No 4, pp 357-371.
  15. Misiti M., Misiti Y., Oppenheim G., Poggi J.M.. Wavelet Toolbox for use with MATLAB® Computation Visualization Programming. The MathWorks User's guide version 4.
  16. Mustapha O., Khalil M., Hoblos G., Chafouk H., Ziadeh H., Lefebvre D., On-Line Fault Detection by Using Filters Bank and Artificial Neural Networks IEEE - ICCTA, Damascus, Syria, April 2006.
  17. Mustapha O, Khalil M., Hoblos G, Chafouk H., Ziadeh H., Lefebvre D., On-Line Change Detection by Using Filters Bank/Wavelet Transform and Dynamic Cumulative Sum Method, 4th FAI International Conference, Lefke, Cyprus, December 2006.
Download


Paper Citation


in Harvard Style

Mustapha O., Khalil M., Hoblos G., Chafouk H. and Lefebvre D. (2007). FAULT DETECTION ALGORITHM USING DCS METHOD COMBINED WITH FILTERS BANK DERIVED FROM THE WAVELET TRANSFORM . In Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 978-972-8865-84-9, pages 226-231. DOI: 10.5220/0001640802260231


in Bibtex Style

@conference{icinco07,
author={Oussama Mustapha and Mohamad Khalil and Ghaleb Hoblos and Houcine Chafouk and Dimitri Lefebvre},
title={FAULT DETECTION ALGORITHM USING DCS METHOD COMBINED WITH FILTERS BANK DERIVED FROM THE WAVELET TRANSFORM},
booktitle={Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2007},
pages={226-231},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001640802260231},
isbn={978-972-8865-84-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - FAULT DETECTION ALGORITHM USING DCS METHOD COMBINED WITH FILTERS BANK DERIVED FROM THE WAVELET TRANSFORM
SN - 978-972-8865-84-9
AU - Mustapha O.
AU - Khalil M.
AU - Hoblos G.
AU - Chafouk H.
AU - Lefebvre D.
PY - 2007
SP - 226
EP - 231
DO - 10.5220/0001640802260231