基于混沌神经网络的发电机定子绕组匝间短路故障诊断

本文采用耦合的混沌振荡子作为单个混沌神经元构造混沌神经网络模型，用改进Hebb算法设计网络的连接权值。在此基础上，实现了混沌神经网络的动态联想记忆并应用该混沌神经网络模型对发电机定子绕组匝间短路故障进行诊断。结果表明，该种方法有助于故障模式的记

Fault Diagnosis of Short Circuit in Stator Windings of Generator Based on Chaotic Neural Network

A chaotic neural network has been builded up with interconnected chaotic neurons in this paper,and each chaotic neuron has two coupled chaotic oscillators.In order to realize dynamic associative memory of the chaotic neural network,the interconnected matrix is designed by means of improved Hebb algorithm.Based on the proposed network and algorithm,the fault of short circuit in stator windings of generator is diagnosed.Diagnose results suggest that the chaotic neural network is beneficial to dynamic memory retrieval and faults identification.