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

Jinxin Liu, Guan Wang, Tong Zhao and Li Zhang
Additional contact information
Jinxin Liu: School of Electrical Engineering, Shandong University, Jinan 250061, China
Guan Wang: School of Electrical Engineering, Shandong University, Jinan 250061, China
Tong Zhao: School of Electrical Engineering, Shandong University, Jinan 250061, China
Li Zhang: Shandong Provincial Key Lab of UHV Transmission Technology and Equipment, Jinan 250061, China

Energies, 2017, vol. 10, issue 7, 1-14

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.

Keywords: on-load tap-changer; variational mode decomposition; relevance vector machine; harmony search algorithm; mechanical condition (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/10/7/946/pdf (application/pdf)
https://www.mdpi.com/1996-1073/10/7/946/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:10:y:2017:i:7:p:946-:d:104069

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().