基于面向元件神经网络与模糊积分融合技术的电网故障智能诊断

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Abstract This paper presents a novel diagnosis method combining element-oriented artificial neural networks and fuzzy integral fusion. The proposed method models the transmission line, bus and transformer using element-oriented ANNs. When a fault occurs, a primary diagnosis is made by element-oriented ANNs, and then the synthetic diagnosis fuses the primary diagnosis results employing fuzzy integral. The proposed method overcomes the Achilles heel of ANNs at getting training patterns and handling topology changes. And the simulation shows that by the use of synthetic diagnosis, the accuracy of diagnosis system is effectively improved. This method is promising for application in large scale real-time fault diagnosis.

Key words： Power systems fault diagnosis element-oriented artificial neural networks synthetic diagnosis fuzzy integral information fusion

Received: 04 August 2008 Published: 04 March 2014

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TM734

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	Articles by authors
	Guo Chuangxin
	You Jiaxun
	Peng Mingwei
	Tang Yuezhong
	Liu Yi
	Chen Ji

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Guo Chuangxin,You Jiaxun,Peng Mingwei等. A Fault Intelligent Diagnosis Approach Based on Element-Oriented Artificial Neural Networks and Fuzzy Integral Fusion[J]. Transactions of China Electrotechnical Society, 2010, 25(9): 183-190.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2010/V25/I9/183

[1] 毕天姝, 倪以信, 吴复立, 等. 基于新型神经网络的电网故障诊断方法[J]. 中国电机工程学报, 2002, 22(2): 73-78.
[2] 刘应梅, 杨宛辉, 等. 基于ANN的变电站故障诊断系统及其容错性[J]. 继电器, 2000, 28(9): 19-22.
[3] 廖志伟, 叶青华, 王钢, 等. 基于GRNN的多故障自适应电力系统故障诊断[J]. 华南理工大学学报(自然科学版), 2005, 33(9): 6-9.
[4] 赵伟, 白晓民, 丁剑. 基于协同式专家系统及多智能体技术的电网故障诊断方法[J]. 中国电机工程学报, 2006, 26(20): 1-7.
[5] 毕天姝, 严正, 等. 基于径向基函数神经网络的在线分布式故障诊断系统[J]. 电网技术, 2001, 25(11): 27-32.
[6] 郭创新, 朱传柏, 曹一家, 等. 电力系统故障诊断的研究现状与发展趋势[J]. 电力系统自动化, 2006, 30(8): 102-107.
[7] 廖志伟, 孙雅明, 叶青华. 人工智能技术在电力系统故障诊断中应用[J]. 电力系统及其自动化学报, 2003, 15(6): 71-79.
[8] Cardoso G Jr, Rolim J G. Applications of neural- network modules to electric power system fault section estimation[J]. IEEE Transactions on Power Delivery, 2004, 19(3): 1034-1041.
[9] 顾雪平, 张文勤, 高曙, 等. 基于神经网络和元件关联分析的电网故障诊断[J]. 华北电力大学学报, 1999, 26(2): 12-17.
[10] 顾雪平, 张文勤, 高曙, 等. 人工神经网络和专家系统结合运用的电力系统故障诊断方法[J]. 华北电力大学学报, 1994, 21(2): 12-17.
[11] 李安华, 吴达. 模糊数学基础及其应用[M]. 乌鲁木齐: 新疆人民出版社, 1987.
[12] Sugeno M. Theory of fuzzy integrals and its applications[D]. Tokyo: Tokyo Institute of Tech- nology, 1974.
[13] Dymitr Ruta, Bogdan Gabrys. An overview of classifier fusion methods[J]. Computing and Information Systems, 2000, 7(1): 1-10.
[14] 李素文. 模糊积分在多分类融合中的应用[D]. 保定: 河北大学, 2006.
[15] 张德利, 郭彩梅, 吴从炘. 模糊积分论进展[J]. 模糊系统与数学, 2003, 17(4): 1-7.
[16] 张永, 李旭宏, 毛海军. 基于Choquet模糊积分的物流网络二阶段设计方法[J]. 公路交通科技, 2006, 23(10): 142-145, 158.
[17] 徐秉铮, 张百灵, 韦岗. 神经网络理论与应用[M].广州: 华南理工大学出版社, 1994.
[18] 何友, 王国宏, 彭应宇, 等. 多传感器信息融合及应用[M]. 北京: 电子工业出版社, 1999.
[19] Cardoso G Jr, Rolim J G. Interpretation of remote backup protection operation for fault section estimation by a fuzzy expert system[C]. IEEE Power Tech. Conference, Bologua, Italy, 2003: 23-26.
[20] Hong Chan Chin. Fault section diagnosis of power system using fuzzy logic[J]. IEEE Transactions on Power Delivery, 2003, 18(1): 245-250.
[21] Wen Fushuan, Chang C S. Probabilistic approach for fault-section estimation in power systems based upon a refined genetic algorithm[J]. IEE Proceedings of Generation, Transmission and Distribution, 1997, 144 (2): 160-168.