摘要
采用一种基于粒子群优化算法和人工神经网络相结合的混合算法应用于电力电子整流电路的故障诊断。文中首先论述了粒子群优化算法以及实现粒子群和神经网络的混合算法的操作步骤,然后将这种诊断方法应用于电力电子整流电路的故障诊断。仿真诊断结果表明,这种混合诊断方法可用于电力电子三相整流电路的故障诊断。它具有较快的收敛速度和较高的诊断精度,它具有工程的应用价值。
The application is based on particle-group optimal algorithm and neural network in fault diagnosis of power electronic rectification circuit. First the article discusses the particle-group optimal algorithm and operational procedure to the hybrid algorithm of particle-group and neural network, then the diagnosis method is applied to fault diagnosis of power electronic rectification circuit. According to the simulation result, the hybrid algorithm can be used to the fault diagnosis of three-phase rectification circuit. It has the faster rate of convergence and greater diagnosis accuracy, and it is suitable for practical applications.
出处
《电工电能新技术》
CSCD
北大核心
2006年第4期23-26,共4页
Advanced Technology of Electrical Engineering and Energy
基金
福建省教育厅基金资助项目(JB03060)
关键词
粒子群算法
神经网络
故障诊断
particle swarm optimization algorithm
artificial neural network
fault diagnosis
