基于BP人工神经网络改进算法的绝缘子污秽预测  

A Study on the Prediction of the Pollution Severity of the Insulator Based on an Improved Algorithm of BP Artificial Neural Network

作　　者：苏渊[1] 刘赟[1] 

机构地区：[1]重庆电力高等专科学校,重庆400053

出　　处：《重庆电力高等专科学校学报》2013年第3期46-49,共4页Journal of Chongqing Electric Power College

摘　　要：研究用BP人工神经网络结合湿度、电压及泄露电流等参数对绝缘子等值附盐密度进行在线预测。结果表明,基于BP人工神经网络改进算法的绝缘子表面污秽预测方法是可行和有效的。This essay studies a new measuring method of predicting the equivalent salt deposit density（ESDD）of the insulator online by using an improved algorithm which combines BP artificial neural network with parameters like humidity,voltage and leakage current.The result proves its feasibility and effectiveness.

关 键 词：绝缘子 等值附盐密度 人工神经网络 

分 类 号：TM855[电气工程—高电压与绝缘技术]