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Mechanical Fault Diagnosis of a Disconnector Operating Mechanism Based on Vibration and the Motor Current

Author

Listed:
  • Zhenming Zhang

    (School of Electrical Engineering, Shandong University, Jinan 250061, China)

  • Chenlei Liu

    (School of Electrical Engineering, Shandong University, Jinan 250061, China)

  • Rui Wang

    (Shandong Taikai Disconnector Co., Ltd., Tai’an 271000, China)

  • Jian Li

    (Shandong Taikai Disconnector Co., Ltd., Tai’an 271000, China)

  • Di Xiahou

    (School of Electrical Engineering, Shandong University, Jinan 250061, China)

  • Qinzhe Liu

    (School of Electrical Engineering, Shandong University, Jinan 250061, China)

  • Shi Cao

    (School of Electrical Engineering, Shandong University, Jinan 250061, China)

  • Shengrui Zhou

    (School of Electrical Engineering, Shandong University, Jinan 250061, China)

Abstract

The mechanical fault diagnosis of a disconnector operating mechanism using a single signal is not sufficiently accurate and reliable. To address this problem, this paper proposes a new fault diagnosis method based on the vibration signal and the motor current signal. First, based on the analysis of the motor stator current signal envelope, segmented envelope RMS values are extracted. Then, the vibration signal of the operating mechanism is processed with VMD (Variational Mode Decomposition). In this paper, the number of modal decompositions K is selected according to the envelope entropy. Second, the effective value of the current segment envelope is fused with the energy entropy value of each IMF component to construct the feature parameters for fault identification. Finally, a fusion weighting algorithm using AdaBoost is proposed to train an SVM as a strong classifier to improve the correct fault diagnosis rate. In this paper, the proposed new diagnosis method is applied to a 220 kV disconnector operating mechanism. The algorithm can effectively identify three operating states of a disconnector operating mechanism.

Suggested Citation

  • Zhenming Zhang & Chenlei Liu & Rui Wang & Jian Li & Di Xiahou & Qinzhe Liu & Shi Cao & Shengrui Zhou, 2022. "Mechanical Fault Diagnosis of a Disconnector Operating Mechanism Based on Vibration and the Motor Current," Energies, MDPI, vol. 15(14), pages 1-17, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:5194-:d:865184
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    References listed on IDEAS

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    1. Jardine, A. K. S. & Buzacott, J. A., 1985. "Equipment reliability and maintenance," European Journal of Operational Research, Elsevier, vol. 19(3), pages 285-296, March.
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