Application of energy spectrum entropy vector method and RBF neural networks optimized by the particle swarm in high-voltage circuit breaker mechanical fault diagnosis

Gaodianya Jishu/High Voltage Engineering

Volumn 38, Issue 6, 2012, Pages 1299-1306

  Xu, Jianyuan ^a   Zhang, Bin ^a   Lin, Xin ^a   Li, Bin ^a   Teng, Yun ^a  

^a SHENYANG UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Energy spectrum entropy; Fault diagnosis; High voltage circuit breakers; Model optimization; Neural networks; Particle swarm optimization(PSO) algorithm; Vibration signals; Wavelet packet

Indexed keywords

ENERGY SPECTRA; HIGH VOLTAGE CIRCUIT BREAKER; MODEL OPTIMIZATION; PARTICLE SWARM OPTIMIZATION ALGORITHM; VIBRATION SIGNAL; WAVELET PACKET;

CAPACITANCE; ELECTRIC ARCS; ELECTRIC CIRCUIT BREAKERS; ELECTRICITY; ENTROPY; FAILURE ANALYSIS; MECHANICAL PROPERTIES; NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS; SPECTROSCOPY; VECTORS;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 84864511916     PISSN: 10036520     EISSN: None     Source Type: Journal    
DOI: 10.3969/j.issn.1003-6520.2012.06.003     Document Type: Article

References (26)

1. LIN Xin. Permanent magnetic actuator and vacuam circuit breakers [M]. Beijing, China: China Machine Press, 2002.
2. YIN Ting, CHEN Xuanshu, DU Yan. Design of large capacity high-voltage breakers using tightly coupled reactor [J]. High Voltage Engineering, 2010, 36(6): 1577-1582.
3. LIU Yafang. Accident investigation of the high voltage circuit breaker [J]. International Electric Power for China, 1997, 1(3): 12-15.
4. Brikci F. An improved vibration analysis algorithmas a diagnostictool for detecting mechanical anomalies on power circuit breakers [J]. IEEE Transactions on Power Delivery, 2008, 23(4): 1986-1994.
5. SHI Fei, LIN Xin, XU Jianyuan. Mechanical characteristics and reliability of vacuum circuit breaker with spring operating mechanism [J]. Electrical Equipment, 2005, 6(6): 79-81.
6. CHANG Guang, ZHANG Zhenqian, WANG Yi. Review on mechanical fault diagnosis of high-voltage circuit breakers based on vibration diagnosis [J]. High Voltage Apparatus, 2011, 47(8): 85-90.
7. YU Jihui, ZHANG Huaiqing, LI Yongming. Electromagnetic measurement data processing by using radial basis function in substation [J]. High Voltage Engineering, 2008, 34(11): 2417-2422.
8. HUANG Chun, JIANG Yaqun. Improved window and interpolation algorithm for analysis of power system harmonics [J]. Proceedings of the CSEE, 2005, 25(15): 26-31.
9. JIANG Jianbo, LIU Xianxing, WANG Deming. Application of FFT and wavelet transform to measurement of harmonics in power system [J]. High Voltage Engineering, 2005, 31(11): 85-87.
10. SUN Laijun, HU Xiaoguang, JI Yanchao. Fault diagnosis for high voltage circuit breakers with improved characteristic entropy of wavelet packet [J]. Proceedings of the CSEE, 2007, 27(12): 103-108.
11. ZHAO Hailong, WANG Fang, HU Xiaoguang. Application of wavelet packet-energy spectrum in mechanical fault diagnosis of high voltage circuit breakers [J]. Power System Technology, 2004, 28(6): 46-49.
12. CHEN Weigen, DENG Bangfei. Applying wavelet packet energy entropy and neural networks to diagnose circuit breaker faults [J]. Journal of Chongqing University, 2008, 31(7): 744-748.
13. GUI Zhonghua, HAN Fengqin. Neural network based on wavelet packet-characteristic entropy for fault diagnosis of draft tube [J]. Proceedings of the CSEE, 2005, 25(4): 99-102.
14. LEI Chenghua, LIU Gang, LI Qinhao. Dynamic calculation of conductor temperature of single-cable using BP neural network [J]. High Voltage Engineering, 2011, 37(1): 184-189.
15. WANG Jialin, XIA Li, WU Zhengguo, et al. Analysis of power system transient signal using genetic algorithm and neural network [J]. High Voltage Engineering, 2011, 37(1): 170-175.
16. Yang J M, Kao C Y. A robust evolutionary algorithm for training neural networks [J]. Neural Computing and Application, 2001, 10(3): 214-230.
17. LIU Yan, KANG Haigui, SUN Min. Genetic algorithm-based fuzzy optimization neural network model for pavement performance evaluation [J]. Journal of Dalian University of Technology, 2010, 50(1): 117-122.
18. SUN Laijun, HU Xiaoguang, JI Yanchao. Mechanical fault classification of high voltage circuit breakers based on support vector machine [J]. Transactions of China Electrotechnical Society, 2006, 21(8): 53-58.
19. JIANG Weitao, ZHENG Jianyong, MEI Jun. Simulation research on vibration signal fault diagnosis in high-voltage circuit-breakers based on wavelet transform [J]. Electrotechnics Electric, 2010(1): 5-7.
20. Mallat.S.G.A. theory for muhiresolution. signal decomposition: the wavelet representation [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989, 11(7): 674-693.
21. HE Zhengyou, CHEN Xiaoqin, LUO Guomin, et al. Faulted phase selecting method of transmission lines based on wavelet entropy weight of transient current [J]. Automation of Electric Power Systems, 2006, 30(21): 39-43.
22. ZHANG Sulan, GUO Ping, ZHANG Jifu. Intension weight value acquisition of weighted concept lattice based on information entropy and deviance [J]. Transactions of Beijing Institute of Technology, 2010, 31(1): 59-63.
23. CHEN Xingqiong, DENG Changhong, PAN Zhangda, et al. Power system load modeling based on recurrent RBF neural network [J]. Power System Technology, 2007, 31(17): 56-59.
24. LI Chunxiang, LIU Chenzhe. RBF-neural-network-based harmony superposition method [J]. Journal of Vibration and Shock, 2010, 29(1): 112-116.
25. WANG Xiaoxia, WANG Tao. Power transformer fault diagnosis based on neural network evolved by particle swarm optimization [J]. High Voltage Engineering, 2009, 34(11): 2362-2367.
26. WANG Xiaodong, WANG Ke, WANG Jinshan, et al. Parameter identification of electrostatic discharge model using particle swarm optimization algorithm [J]. High Voltage Engineering, 2010, 36(2): 434-438.