An online expert system for fault diagnosis in hydraulic systems

被引:19
|
作者
Angeli, C [1 ]
机构
[1] Technol Inst Piraeus, GR-17121 Athens, Greece
关键词
expert systems; fault diagnosis; online process; hybrid systems; hydraulic systems;
D O I
10.1111/1468-0394.00100
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Fault diagnosis has become increasingly important for industrial automation and many approaches have been investigated for the online diagnostic task. This work demonstrates a new online expert system for dynamic industrial automated processes. The emphasis of this diagnostic system lies in the functions provided for fault detection, prediction, compensation and diagnosis. The system uses experiential knowledge cooperatively with scientific knowledge in a new interactive formation. It is developed in two parts using the DASYLab software for the numerical computations and the KPWin development tool for the symbolic representations. The system was developed in collaboration with the company Automation Systems S.A., which specializes in hydraulic systems, and is used for fault detection in production machines.
引用
收藏
页码:115 / 120
页数:6
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