Fault diagnosis of on-load tap-changer based on variational mode decomposition and relevance vector machine

Energies

Volumn 10, Issue 7, 2017, Pages

  Liu, Jinxin ^a   Wang, Guan ^a   Zhao, Tong ^a   Zhang, Li ^b  

^a SHANDONG UNIVERSITY   (China)

^b Shandong Provincial Key Laboratory of UHV Power Transmission and Gas Discharge   (China)

Author keywords

Harmony search algorithm; Mechanical condition; On load tap changer; Relevance vector machine; Variational mode decomposition

Indexed keywords

FAILURE ANALYSIS; SIGNAL PROCESSING; VECTORS; VOLTAGE CONTROL;

HARMONY SEARCH ALGORITHMS; MECHANICAL CONDITION; MODE DECOMPOSITION; ON- LOAD TAP CHANGERS; RELEVANCE VECTOR MACHINE;

FAULT DETECTION;

EID: 85025126485     PISSN: None     EISSN: 19961073     Source Type: Journal    
DOI: 10.3390/en10070946     Document Type: Article

References (24)

1. Li, Q.; Zhao, T.; Zhang, L.; Liu, J. Mechanical fault diagnostics of on-load tap changer within power transformers based on hidden Markov model. IEEE Trans. Power Deliv. 2012, 27, 596-601. [CrossRef]
2. Picher, P.; Riendeau, S.; Gauvin, M.; Leonard, F.; Dupont, L.; Goulet, J.; Rajotte, C. New technologies for monitoring transformer tap-changers and bushings and their integration into a modern IT infrastructure. In Proceedings of the International Council on Large Electric systems (CIGRE), Paris, France, 26-31 August 2012.
3. Allard, L.; Lorin, P.; Foata, M.; Prajescu, S.; Rajotte, C.; Landry, C. Vibro-acoustic diagnostic: Contributing to an optimized on-load tap changer (OLTC) maintenance strategy. In Proceedings of the International Council on Large Electric systems (CIGRE), Paris, France, 22-27 August 2010.
4. Abeywickrama, N.; Kouzmine, O.; Kornhuber, S.; Picher, P. Application of novel algorithms for continuous bushing and OLTC monitoring for increasing newtwork reliability. In Proceedings of the International Council on Large Electric systems (CIGRE), Paris, France, 24-29 August 2014.
5. Seo, J.; Ma, H.; Saha, T.K. A Joint Vibration and Arcing Measurement System for Online Condition Monitoring of On load Tap Changer of the Power Transformer. IEEE Trans. Power Deliv. 2017, 32, 1031-1038. [CrossRef]
6. Rivas, E.; Burgos, J.C.; Prada, J.C.G. Vibration analysis using envelope wavelet for detecting faults in the OLTC tap selector. IEEE Trans. Power Deliv. 2010, 25, 1629-1636. [CrossRef]
7. Duan, R.C.; Wang, F.H. Fault diagnosis of on-load tap-changer in converter transformer based on time-frequency vibration analysis. IEEE Trans. Ind. Electron. 2016, 63, 3815-3823. [CrossRef]
8. Liu, J.; Wang, G.; Zhao, T.; Shi, L.; Zhang, L. The Research of OLTC On-line Detection System Based on Embedded and Wireless Sensor Networks. In Proceedings of the 2016 IEEE International Conference on High Voltage Engineering and Application, Chengdu, China, 19-22 September 2016.
9. Kang, P.J.; Birtwhistle, D. Condition assessment of power transformer on-load tap changers using wavelet analysis and self-organizing map: Field evaluation. IEEE Trans Power Deliv. 2003, 18, 78-84. [CrossRef]
10. Simas, E.F.; Almeida, L.A.L.; Antonio, C. Vibration monitoring of on-load tap changers using a genetic algorithm. In Proceedings of the IEEE Instrumentation and Measurement Technology Conference, Ottawa, ON, Canada, 16-19 May 2005.
11. Rivas, E.; Burgos, J.C.; Prada, J.C.G. Condition assessment of power OLTC by vibration analysis using wavelet transform. IEEE Trans Power Deliv. 2009, 24, 687-694. [CrossRef]
12. Zhang, H.; Ma, H.; Chen, K.;Wang, C.; Gao, P. Fault diagnosis of power transformer on-load tap changer based on EMD-HT analysis of vibration signal. High Volt. Appar. 2012, 48, 76-81.
13. Hong, X.; Ma, H.; Gao, P.; Chen, K.; Wang, C. Fault diagnosis of on-load tap changer contact loosening based on EEMD. Huadian Technol. 2016, 63, 3815-3823.
14. Sun, G.; Chen, T.; Wei, Z.; Sun, Y.; Zang, H.; Chen, S. A Carbon Price Forecasting Model Based on Variational Mode Decomposition and Spiking Neural Networks. Energies 2016, 9, 54. [CrossRef]
15. Li, T.; Zhou, M.; Guo, C.; Luo, M.; Wu, J.; Pan, F.; Tao, Q.; He, T. Forecasting crude oil price using EEMD and RVM with adaptive PSO-based kernels. Energies 2016, 9, 1014. [CrossRef]
16. Dragomiretskiy, K.; Zosso, D. Variational mode decomposition. IEEE Trans. Signal Process. 2014, 62, 531-544.
17. Huang, N.; Yuan, C.; Cai, G.; Xing, E. Hybrid Short TermWind Speed Forecasting Using Variational Mode Decomposition and aWeighted Regularized Extreme Learning Machine. Energies 2016, 9, 989. [CrossRef]
18. Eguchi, S.; Copas, J. Interpreting Kullback-Leibler divergence with the Neyman-Pearson lemma. J.Multivar. Anal. 2006, 97, 2034-2040. [CrossRef]
19. Harmouche, J.; Delpha, C.; Diallo, D. Incipient fault detection and diagnosis based on Kullback-Leibler divergence using principal component analysis: Part I. Signal Process. 2014, 94, 278-287. [CrossRef]
20. Widodoa, A.; Kimb, E.Y.; Sonc, J.; Yang, B.S.; Tan, A.C.C.; Gu, D.S.; Choi, B.-K.; Mathew, J. Fault diagnosis of low speed bearing based on relevance vector machine and support vector machine. Expert Syst. Appl. 2009, 36, 7252-7261. [CrossRef]
21. Alia, O.M.; Mandavar, R. The variants of the harmony search algorithm: An overview. Artif. Intell. Rev. 2011, 36, 49-68. [CrossRef]
22. Mahdavi, M.; Fesanghary, M.; Damangir, E. An improved harmony search algorithm for solving optimization problems. Appl. Math. Comput. 2007, 188, 1567-1579. [CrossRef]
23. Chen, Y.H.; Hong,W.C.; Shen,W.; Huang, N.N. Electric load forecasting based on a least squares support vector machine with fuzzy time series and global harmony search algorithm. Energies 2016, 9, 70. [CrossRef]
24. Fei, S.W.; He, Y. Wind speed prediction using the hybrid model of wavelet decomposition and artificial bee colony algorithm-based relevance vector machine. Int. J. Electr. Power Energy Syst. 2015, 73, 625-631. [CrossRef]