Fault diagnosis for HAGC systems based on fuzzy expert system and neural networks

被引：0

作者：

Gao, YJ ^{[1
]}

Kong, XD ^{[1
]}

Qin, Z ^{[1
]}

机构：

[1] Yanshan Univ, Dept Mechatron Control Engn, Qinhuangdao, Peoples R China

来源：

IC-AI'2001: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOLS I-III | 2001年

关键词：

fault diagnosis; expert system; fuzzy reasoning; neural networks; HAGC system;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The multi-layers fuzzy neural networks expert system for fault diagnosis of hydraulic automatic' gauge control (HAGC) system was developed by using the hierarchy decomposing strategy. This system uses cooperation reasoning model and the fuzzy reasoning to detect and diagnose the system. The analysis and experimental results indicate that the established modularization and multi-layers fault diagnosis expert system is not only simple but also specific for fault description. This expert system is able to diagnose the fault of hydraulic system in real time. Besides, the expert system is much flexible and applicable to the actual system. All of these properties make it available for further researching on the fault diagnosis techniques of hydraulic AGC system.

引用

页码：389 / 394

页数：6

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