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Support vector machine for fault diagnosis of the broken rotor bars of squirrel-cage induction motor

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Abstract

The paper presents an automatic computerized system for the diagnosis of the rotor bars of the induction electrical motor by applying the support vector machine. Two solutions of diagnostic system have been elaborated. The first one, called fault detection, discovers only the case of the fault occurrence. The second one (complex diagnosis) is able to find which bars have been damaged. The most important problem is concerned with the generation and selection of the diagnostic features, on the basis of which the recognition of the state of the rotor bars is done. In our approach, we use the spectral information of the motor current, voltage and shaft field of one phase registered in an instantaneous form. The selected features form the input vector applied to the support vector machine, used as the classifier. The results of the numerical experiments are presented and discussed in the paper.

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Authors and Affiliations

  1. Warsaw University of Technology, Warsaw, Poland

    Stanislaw Osowski

  2. Military University of Technology, Warsaw, Poland

    Stanislaw Osowski

  3. University of Life Sciences, Warsaw, Poland

    Jaroslaw Kurek

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  1. Jaroslaw Kurek
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  2. Stanislaw Osowski
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Correspondence to Stanislaw Osowski.

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Kurek, J., Osowski, S. Support vector machine for fault diagnosis of the broken rotor bars of squirrel-cage induction motor. Neural Comput & Applic 19, 557–564 (2010). https://doi.org/10.1007/s00521-009-0316-5

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  • DOI: https://doi.org/10.1007/s00521-009-0316-5

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