An intelligent online fault diagnostic scheme for nonlinear systems

作     者：Hing Tung MOK 

作者机构：Department of Mechanical EngineeringThe University of Hong Kong 

出 版 物：《控制理论与应用（英文版）》 (J. Control Theory Appl.)

年 卷 期：2008年第6卷第3期

页      面：267-272页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This paper was presented at the 25th Chinese Control Conference and was supported by the HKSAR RGC Grant (HKU 7050/02E) 

主　　题：Fault diagnosis Nonlinear systems Neurofuzzy networks 

摘      要：An online fault diagnostic scheme for nonlinear systems based on neurofuzzy networks is proposed in this paper. The scheme involves two stages. In the first stage, the nonlinear system is approximated by a neurofuzzy network, which is trained offline from data obtained during the normal operation of the system. In the second stage, residual is generated online from this network and is modelled by another neurofuzzy network trained online. Fuzzy rules are extracted from this network, and are compared with those in the fault database obtained under different faulty operations, from which faults are diagnosed. The performance of the proposed intelligent fault scheme is illustrated using a two-tank water level control system under different faulty conditions .