Journal of Changshu Institute of Technology2016，Vol.30Issue(2)：51-55,5.
改进粒子群优化神经网络的高压断路器故障诊断
High-Voltage Circuit Breaker Fault Diagnosis Based on Improved Particle Swarm Optimizer and Neural Network
摘要
Abstract
Based on the analysis of characteristics and problems of traditional error back propagation (BP) algo⁃rithm and standard particle swarm optimization (PSO) algorithm, this paper proposes an improved particle swarm optimization (MPSO) algorithm, improved BP (MBP) algorithm, and established a model of neural network for high-voltage circuit breaker fault diagnosis based on MPSO-MBP hybrid algorithm. By making a simulation com⁃parison and an analysis of training samples and test samples, this method can realize effective diagnosis to differ⁃ent high-voltage circuit breaker fault, and improve the recognition ability of high-voltage circuit breaker fault mode. Therefore, the method has a high accuracy and a fast speed of fault diagnosis.关键词
高压断路器/MPSO-MBP/故障诊断Key words
high-voltage circuit breaker/MPSO-MBP/fault diagnosis分类
信息技术与安全科学引用本文复制引用
乔维德..改进粒子群优化神经网络的高压断路器故障诊断[J].Journal of Changshu Institute of Technology,2016,30(2):51-55,5.基金项目
无锡市社会事业领军人才资助项目“高压断路器的优化控制研究” （）
