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Transactions of China Electrotechnical Society. 2019, (19) Core

Remaining Lifetime Prediction of AC Contactor Based on Statistical Regression and Nonlinear Wiener ProcessChinese Full TextEnglish Full Text (MT)

Li Kui;Gao Zhicheng;Wu Yi;Zheng Shumei;Li Zhengguang;State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology;Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province Hebei University of Technology;

Abstract: The contact mass of AC contactor reduces under the influence of arc erosion, which lead to the degradation of electrical contact, and the residual life can be predicted based on the degradation processes. In this paper, first, three order function degradation path model was established based on the complete historical degradation information of the mass loss of contact. Then the time-scale transformation model is established to transform the time of nonlinear field data. Second, the reliability assessment method and the residual life prediction model were established bsed on the linearizable nonlinear Wiener process. And failure criteria was proposed based on the accumulate contact mass loss arrived the failure threshold for the first time. Besides, based on the electrical life test of AC contactor, the performance degradation model and the residual life prediction method were verified that they can be used to predict the residual life of the AC contactor. Finally, the maximum likelihood estimation of the residual life of the AC contactor is performed through the test data. And the prediction accuracy of different data processing methods is compared and analyzed, which verify the accuracy of the residual life prediction method in this paper.
Keywords：

AC contactor; mass loss of contact; Wiener process; statistical regression; life prediction;

  • DOI：

    10.19595/j.cnki.1000-6753.tces.180764

  • Series：

    (C) Architecture/ Energy/ Traffic/ Electromechanics, etc

  • Subject：

    Electric Power Industry

  • Classification Code：

    TM572.2

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