基于关联规则的XLPE电缆局部放电模糊识别研究

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Abstract The article applies association rule mining and fuzzy inference mechanism to pattern recognition of partial discharge (PD) in XLPE cable, uses competitive agglomeration method in section division to show its discretization quality, and finds the relation between sections to collect classifying rules by association method. Then, the paper uses the fuzzy rules into pattern recoganition. This method can effectively discover the potential rules among characteristic parameters and the defect type. So it has great reference values for pattern recognition and fault diagnosis. Aiming at several typical XLPE cable discharge data, this paper extractes the relevant statistical characteristic parameters, classifies the defects by this method and makes a contrast analysis with the results from neutral network and C4.5 methods. Experimental results demonstrate the verification algorithm effective, furthermore, this technique has the advantage of better interpretation, time saving and dynamic interval, which makes it a new solution available for the pattern recognition of PD.

Key words： Partial discharge XLPE cable association rule fuzzy inference pattern recognition

Received: 01 September 2010 Published: 20 March 2014

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TM855

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	Yao Linpeng
	Xu Yingmin
	Qian Yong
	Huang Chengjun
	Jiang Xiuchen

Cite this article:

Yao Linpeng,Xu Yingmin,Qian Yong等. Fuzzy Pattern Recognition of Partial Discharge in XLPE Cable Based on Association Rule[J]. Transactions of China Electrotechnical Society, 2012, 27(5): 92-98.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2012/V27/I5/92

[1] 张强. 电力电缆局部放电检测与模式识别的研究[D]. 天津: 天津大学, 2007.
[2] 郭灿新, 张丽, 钱勇, 等. XLPE电力电缆中局部放电检测及定位技术的研究现状[J]. 高压电器, 2009, 45(3): 56-60.
Guo Canxin, Zhang Li, Qian Yong, et al. Current status of partial discharge detection and location techniques in XLPE power cable[J]. High Voltage Apparatus, 2009, 45(3): 56-60.
[3] 陈小林, 成永红, 谢小军, 等. XLPE绝缘电老化中局放特性试验研究[J]. 高电压技术, 2006, 32(4): 22-24.
Chen Xiaolin, Ceng Yonghong, Xie Xiaojun, et al. Experimental study on partial discharge in XLPE insulation during electrical aging[J]. High Voltage Engineering, 2006, 32(4): 22-24.
[4] Evagorou D, Kyprianou A, Lewin P L, et al. Classification of partial discharge signals using probabilistic neural network[C]. Proceedings of IEEE International Conference on the Solid Dielectrics (ICPSD), 2007: 8-13.
[5] Wen Yeau C. Partial discharge pattern recognition using radial basis function neural network[C]. Proceedings of the Power and Energy Engineering Conference (APPEEC), Asia-Pacific, 2010: 28-31.
[6] Chen X, Cavallini A, Montanari G C. Statistical analysis and fuzzy logic identification of partial discharge in paper-oil insulation system[C]. Proceedings of IEEE 9th International Conference on the Properties and Applications of Dielectric Materials (ICPADM), 2009: 19-23.
[7] Abdel-Galil TK, Sharkawy RM, et al. Partial discharge pulse pattern recognition using an inductive inference algorithm[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2005, 12(2): 320-327.
[8] Agrawal R, Imielinski T, Swami A. Mining association rules between sets of items in large databases[C]. Proceedings of the ACM SIGMOD Conference on Management of Data, 1993: 207-216.
[9] Liu B, Hsu W, Ma Y. Integrating classification and association rule mining[C]. Proceedings of the International Conference on Knowledge Discovery and Data Mining, 1998: 80-86.
[10] 陆建江, 宋自林, 钱祖平. 挖掘语言值关联规则[J]. 软件学报, 2001, 12(4): 38-39, 42.
Lu Jianjiang, Song Zilin, Qian Zuping. Mining linguistic value association rules[J]. Journal of Software, 2001, 12(4): 38-39, 42.
[11] Frigui H, Krishnapuram R. Clustering by competitive agglomeration[J]. Pattern Recognition, 1997, 30(7): 1109-1119.
[12] Agrawal R, Srikant R. Fast algorithm for mining association rules[C]. Proceedings of the 20th Very Large Data Bases(VLDB'94)Conference, Santiago, Chile, 1994: 487-499.
[13] 陈莉, 焦李成. 基于关系代数的关联规则挖掘算法[J]. 西北大学学报(自然科学版), 2005, 35(6): 691-694, 698.
Chen Li, Jiao Licheng. Association rule mining algorithm based on relation algebra theory[J]. Journal of Northwest University(Natural Science Edition), 2005, 35(6): 691-694, 698.
[14] Kuncheva L I. How good are fuzzy If-Then classifiers[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2000, 30(4): 501-509.
[15] Salama M M A, Bartnikas R. Fuzzy logic applied to PD pattern classification [J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2000, 7(1): 118-123.
[16] Park S H, Jung H E, Yun J H, et al. Classification of defects and evaluation of electrical tree degradation in cable insulation using pattern recognition method and weibull process of partial discharge[C]. International Conference on Condition Monitoring an Diagnosis, 2008: 1-4.
[17] 韦斌, 李颖. 基于VHF的交联电缆附件局放检测的研究[J]. 高电压技术, 2006, 32(2): 30-31, 53.
Wei Bin, Li Ying. Study on PD detection of HV XLPE cable accessories based on VHF technique[J]. High Voltage Engineering, 2006, 32(2): 30-31, 53.
[18] Sahoo N C, Salama M M A, Bartnikas R. Trends in partial discharge pattern classification: a survey[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2005, 12(2): 248-264.