基于BP神经网络高压潜水电机绝缘寿命预测  

High Voltage Submersible Motor Insulation Life Prediction Based on BP Neural Network

作　　者：鲍晓华[1] 刘冰[1] 朱庆龙 刘健[1] 

机构地区：[1]合肥工业大学电气与自动化工程学院,安徽合肥230009 [2]合肥三益江海泵业有限公司,安徽合肥231131

出　　处：《电机与控制应用》2011年第11期57-62,共6页Electric machines & control application

基　　金：合肥工业大学博士基金(GDBJ2008-014);安徽省自然科学基金(11040606M124)

摘　　要：高压潜水电机常年在深水中工作,受到复杂环境的影响,运行绝缘性能恶化,又由于电机安装环境特殊,不能随时被检修,所以预测其绝缘寿命,进而减少因电机绝缘性能恶化而带来的损失具有重大意义。分析了影响高压潜水电机绝缘寿命的因素,同时提出了利用BP神经网络对高压潜水电机绝缘寿命预测的方法,通过加速寿命试验证明,利用BP神经网络对电机寿命预测可达到实际要求。High voltage submersible motor works in deep water all the year, and its operating insulation performance deteriorated by the complex environment. Due to the special installed circumstances of the motor, it can not be readily maintained, so prediction of the insulation life expectancy, reducing the losses caused by motor deterioration have a great significance. The impacting factors of the insulation life-expectancy of the high voltage submersible motor are analyzed, at the same time, the ways of using BP neural network to predict the insulation life-expectancy of the high voltage submersible motor were proposed. The accelerated life experiment proved that using BP neural network to predict motor insulation life-expectancy can gain actual requirements.

关 键 词：神经网络 高压潜水电机 绝缘 寿命预测 

分 类 号：TM305.2[电气工程—电机]