基于自适应神经网络的非线性系统的智能故障诊断  

THE INTELLIGENT FAULT DIAGNOSIS OF NONLINEAR SYSTEM BASED ON ADAPTIVE NEURAL NETWORKS

作　　者：林涛[1] 刘仰魁[1] 徐秀妮[1] 

机构地区：[1]陇东学院电气工程学院,甘肃庆阳745000

出　　处：《井冈山大学学报（自然科学版）》2013年第2期69-74,共6页Journal of Jinggangshan University (Natural Science)

基　　金：陇东学院青年科技创新项目(XYZK1009)

摘　　要：针对一类模型未知的非线性系统,提出了一种基于自适应神经网络的故障诊断方法,用RBF神经网络构造了状态估计器和故障估计器,解决了非线性系统状态不可测时的故障诊断问题。并用Lyapunov方法研究了故障误差和状态误差的收敛性,结果表明了该方法实用、有效。According to a class of unknown model of nonlinear systems, the fault diagnosis method based on adaptive neural networks is proposed. The state estimator and fault estimator are constituted by RBF neural network, which can solve the nonlinear system fault diagnosis problem when the nonlinear system＇s state is uncertain. The convergence on fault error and state error is researched by Lyapunov method. The results show that this method is practical and effective.

关 键 词：神经网络 非线性系统 故障诊断 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]