Power transformer fault diagnosis based on genetic support vector machine and gray artificial immune algorithm

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering

Volumn 31, Issue 7, 2011, Pages 56-63

  Zheng, Ruirui ^a   Zhao, Jiyin ^a   Zhao, Tingting ^b   Li, Min ^c  

^a JILIN UNIVERSITY   (China)

^b ZHEJIANG UNIVERSITY   (China)

^c DALIAN NATIONALITIES UNIVERSITY   (China)

Author keywords

Dynamic vaccine; Fault diagnosis; Genetic algorithm; Gray artificial immune algorithm; Power transformer; Support vector machine (SVM)

Indexed keywords

ANTIBODIES; DECISION MAKING; DYNAMICS; GENETIC ALGORITHMS; LEARNING ALGORITHMS; SUPPORT VECTOR MACHINES; TRANSFORMER SUBSTATIONS; VACCINES; VECTORS;

ARTIFICIAL IMMUNE; ARTIFICIAL IMMUNE ALGORITHMS; BIOLOGICAL IMMUNE SYSTEM; DIAGNOSIS ALGORITHMS; FAULT DIAGNOSIS; FAULT TYPES; GRAY ARTIFICIAL IMMUNE ALGORITHM; GRAY-RELATION; HIGH FREQUENCY HF; INTEGRATED DECISION; KERNEL FUNCTION PARAMETERS; NORMAL STATE; ON DYNAMICS; POWER TRANSFORMER FAULT DIAGNOSIS;

POWER TRANSFORMERS;

EID: 79953812659     PISSN: 02588013     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (20)

1. Dong Ming, Yan Zhang, Yang Li, et al. An evidential reasoning approach to transformer fault diagnosis[J]. Proceedings of the CSEE, 2006, 26(1): 107-114(in Chinese).
2. Chen Weigen, Pan Chong, Yun Yuxin, et al. Fault diagnosis method of power transformers based on wavelet networks and dissolved gas analysis[J]. Proceedings of the CSEE, 2008, 28(7): 121-126(in Chinese).
3. State Economic and Trade Commission. DL/T722-2000 Guide to the analysis and the diagnosis of gases dissolved in transformer oil [S]. Beijing: China Electric Power Press, 2001(in Chinese).
4. Xiong Hao, Sun Caixin, Chen Weigen, et al. Artifical immune network classification algorithm for fault diagnosis of power transformer [J]. Automation of Electric Power Systems, 2006, 30(6): 57-60(in Chinese).
5. Liao Ruijin, Liao Yuxiang, Yang Lijun, et al. Study on synthetic diagnosis method of transformer fault using multi-neural network and evidence theory[J]. Proceedings of the CSEE, 2006, 26(3): 119-124(in Chinese).
6. Xiong Hao, Li Weiguo, Chang Guanghui, et al. Application of fuzzy rough set theory to power transformer faults diagnosis[J]. Proceedings of the CSEE, 2008, 28(7): 141-147(in Chinese).
7. Dong Ming, Meng Yuanyuan, Xu Changxiang, et al. Fault diagnosis model for power transformer based on support vector machine and dissolved gas analysis[J]. Proceedings of the CSEE, 2003, 23(7): 88-92(in Chinese).
8. Fei Shengwei, Sun Yu. Fault prediction of power transformer by combination of fought set and grey theory[J]. Proceedings of the CSEE, 2008, 28(16): 154-160(in Chinese).
9. Li Hongfang, Zhang Qinghua, Xie Keming. Application of a novel immue network learning algorithm to fault diagnosis[J]. CAAI Transactions on Intelligent Systems, 2008, 3(5): 449-454(in Chinese).
10. Pang Mao, Zhou Xiaojun, Meng Qinghua. Study and application of on-line fault testing algorithm based on immunology[J]. Proceedings of the CSEE, 2005, 25(24): 149-153(in Chinese).
11. Zhao Wenqing, Zhu Yongli, Zhang Xiaoqi. combinational forecast for transformer faults based on support vector machine[J]. Proceedings of the CSEE, 2008, 28(25): 14-19(in Chinese).
12. Hu Qing, Wang Rongjie, Zhan Yiju. Fault diagnosis technology based on SVM in power electronics circuit[J]. Proceedings of the CSEE, 2008, 28(12): 107-111(in Chinese).
13. Jiao Licheng, Du Haifeng, Liu Fang, et al. Immunological Computation for Optimization, Learning and Recognition[M]. Beijing: Science Press, 2006: 1-120(in Chinese).
14. Tang Hongcheng, Li Zhuxin, Wu Huafeng, et al. Asynchronous motor fault diagnosis based on artificial immunity[J]. Proceedings of the CSEE, 2005, 25(23): 158-162(in Chinese).
15. Zhou Aihua, Zhang Bide, Zhang Houxuan. Power transformer fault diagnosis by using the artificial immune classification algorithm [J]. High Voltage Engineering, 2007, 33(8): 77-80(in Chinese).
16. Watkins A, Timms J, Boggess L. Artificial immune recognition systems(AIRS): an immune-inspired supervised learning algorithm [J]. Genetic Programming and Evolvable Machines, 2004, 5(3): 291-317.
17. Zheng Haiping, Sun Caixin, Li Jian, et al. A model and method of degree of grey incidence analysis on transformer fault diagnosis [J]. Proceedings of the CSEE, 2001, 21(10): 106-109(in Chinese).
18. Song Shaomin, Wang Yaonan, Sun Wei, et al. Fault diagnosis method with transformer DGA data based on immune recognition algorithm [J]. Transformer, 2008, 45(8): 70-72(in Chinese).
19. Tian Yuling. Research on multi-layered immune fault diagnosis model[J].Computer Engineering and Application, 2008, 44(9): 245-248(in Chinese).
20. Deng Julong, Gray Theory Basis[M]. Wuhan: Huazhong University of Science and Technology Press, 2002: 122-141(in Chinese).