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	Insulating fault diagnosis of XLPE power cables using multi-parameter based on artificial neural networks
	Chen, XL ; Cheng, YH ; Zhu, ZL ; Yue, B ; Xie, XJ
	2010-05-10 ; 2010-05-10
会议名称	ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS ; 2nd International Symposium on Neural Networks ; Chongqing, PEOPLES R CHINA ; Web of Science
关键词	Computer Science, Theory & Methods
中文摘要	An online monitoring system of XLPE power cables was introduced in the research at first. It could detect the parameters, including partial discharge, dielectric loss, and central insulation resistance and sheathing resistance. The BP artificial neural networks were applied to diagnose the insulating status of XLPE cables using the 16 parameters. The adopted transfer functions in the neural networks were hyperbolic tangent function and S-type function, In order to reduce the training time, the Levenberg-Marquardt training method was used. The experimental results showed that the BP artificial neural networks could be applied in fault diagnosis of XLPE power cables using Multiparameter and when the number of nerve unit in the implied layer was fourteen, the output error was least.
会议录出版者	SPRINGER-VERLAG BERLIN ; BERLIN ; HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
语种	英语 ; 英语
内容类型	会议论文
源URL	[http://hdl.handle.net/123456789/19934]
专题	清华大学
推荐引用方式 GB/T 7714	Chen, XL,Cheng, YH,Zhu, ZL,et al. Insulating fault diagnosis of XLPE power cables using multi-parameter based on artificial neural networks[C]. 见:ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS, 2nd International Symposium on Neural Networks, Chongqing, PEOPLES R CHINA, Web of Science.

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