A NEW FUZZY NEURAL NETWORK BASED INSULATOR CONTAMINATION DETECTION

摘要：

The contamination condition of insulators is usually estimated by detecting the root mean square (r.m.s) of surface leakage current via online monitoring system, ignoring the influence of environment factors, such as temperature,humidity, etc. For the detection factors have fuzzy characters,a new method based on Fuzzy Neural Network is proposed in order to overcome the disadvantages of traditional insulation condition detection. It is through the build of the structure of Fuzzy Neural Network and the establishment of net weights by training samples as well to estimate the contamination severity of insulators. The test samples simulation experiment result proves the validity of the method presented in this paper,which shows an instructive significance for the prevention the insulator from flashover fault and the condition-based maintenance(CBM).

关键词： Insulators Fuzzy Neural network Contamination detection

作者: YU-PING LU MIN YU L.L.LAI XIA LIN

作者单位: Dept of Electrical Engineering Southeast University, Nanjing 210096, China Energy Systems Group, City University, London, UK EC1V0HB

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 4099-4104

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）