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Energies 2017, 10(7), 946; https://doi.org/10.3390/en10070946

Fault Diagnosis of On-Load Tap-Changer Based on Variational Mode Decomposition and Relevance Vector Machine

1
School of Electrical Engineering, Shandong University, Jinan 250061, China
2
Shandong Provincial Key Lab of UHV Transmission Technology and Equipment, Jinan 250061, China
*
Author to whom correspondence should be addressed.
Academic Editor: Issouf Fofana
Received: 30 March 2017 / Revised: 21 June 2017 / Accepted: 4 July 2017 / Published: 8 July 2017
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Abstract

In order to improve the intelligent diagnosis level of an on-load tap-changer’s (OLTC) mechanical condition, a feature extraction method based on variational mode decomposition (VMD) and weight divergence was proposed. The harmony search (HS) algorithm was used to optimize the parameter selection of the relevance vector machine (RVM). Firstly, the OLTC vibration signal was decomposed into a series of finite-bandwidth intrinsic mode function (IMF) by VMD under different working conditions. The weight divergence was extracted to characterize the complexity of the vibration signal. Then, weight divergence was used as training and test samples of the harmony search optimization-relevance vector machine (HS-RVM). The experimental results suggested that the proposed integrated model has high fault diagnosis accuracy. This model can accurately extract the characteristics of the mechanical condition, and provide a reference for the practical OLTC intelligent fault diagnosis. View Full-Text
Keywords: on-load tap-changer; variational mode decomposition; relevance vector machine; harmony search algorithm; mechanical condition on-load tap-changer; variational mode decomposition; relevance vector machine; harmony search algorithm; mechanical condition
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Liu, J.; Wang, G.; Zhao, T.; Zhang, L. Fault Diagnosis of On-Load Tap-Changer Based on Variational Mode Decomposition and Relevance Vector Machine. Energies 2017, 10, 946.

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