电力系统保护与控制Issue(10)：62-67,6.
基于概率神经网络的高压断路器故障诊断
High voltage circuit breaker fault diagnosis of probabilistic neural network
摘要
Abstract
The high voltage circuit breaker is one of the most important electrical equipments, which controls and protects the power system. In order to improve the accuracy of fault diagnosis of high voltage circuit breakers, a fault diagnosis method of high voltage circuit breakers is proposed based on probabilistic neural network (PNN). This paper establishes PNN fault diagnosis model on the basis of analyzing the failure characteristics of high voltage circuit breaker to determine the characteristics of the signal. The model takes the collected feature data as the input of the network to get the class conditional probabilistic density function by Parzen window estimation method, then classifies characteristic data according to the Bayes decision rules. The simulation verifies that the probabilistic neural network fault diagnosis model has fast convergence, high fault diagnosis accuracy, easy to train and so on. Therefore, this method is an effective method of fault diagnosing and has good prospects.关键词
高压断路器/机械故障/概率神经网络/特征信号提取/故障诊断Key words
high voltage circuit breakers/mechanical failure/probability neural network/characteristic signal extraction/fault diagnosis分类
信息技术与安全科学引用本文复制引用
杨凌霄,朱亚丽..基于概率神经网络的高压断路器故障诊断[J].电力系统保护与控制,2015,(10):62-67,6.基金项目
国家自然科学基金资助项目(61104079) （61104079）
