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《High Voltage Engineering》 2005-06
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Transmission Line Fault Diagnosis Based on RBF Network with HCM Clustering Algorithm

JIANG Huilan1, GUAN Ying1, LIU Fei1, XU Jianqiang2 (1. Tianjin University, Tianjin 300072, China; 2. Daqing Oil Field Management Board, Daqing 163000, China)  
On the basis of analyzing the methods of accomplishing high voltage transmission line fault diagnosis, this paper proposes to adopt RBF network to complete high voltage transmission line fault diagnosis by using radial basis function network’s capability of being adapt to solving pattern recognition problem, and builds a RBF network model structure used for transmission line fault diagnosis. Meanwhile optimization theory based HCM clustering algorithm is used to cluster sample data to determine the number of node of hidden layer, so that the efficiency of RBF network in use is high. By simulation analysis and test for fault tolerance of network, the results show that the method in this paper not only can accomplish correct fault diagnosis for high voltage transmission line but also has higher fault tolerance performance for distorted input signal than BPNN, therefore, it has a practical application value for real time information processing system.
【Fund】: 天津大学留学回国人员基金资助项目(200447)
【CateGory Index】: TM75
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