DESIGN OF A FUZZY-LOGIC BASED DIAGNOSTIC MODEL FOR TECHNICAL PROCESSES

被引:16
作者
ULIERU, M
ISERMANN, R
机构
[1] Technical University of Darmstadt, Institute of Automatic Control, Laboratory of Control Engineering and Process Automation, Darmstadt
关键词
FAULT DETECTION AND DIAGNOSIS; POSSIBILITY THEORY; LINGUISTIC MODELING; KNOWLEDGE ACQUISITION; FUZZY NUMBERS; APPROXIMATE REASONING; EXPERT SYSTEMS;
D O I
10.1016/0165-0114(93)90502-9
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The design and implementation of the heuristic knowledge base for a fuzzy logic-based technical diagnostic problem solving strategy integrated as a heuristic level within a computer assisted fault diagnosis system is considered. Based on knowledge acquisition via expert knowledge (linguistically expressed as fuzzy conditional statements); simulation-based observations of the diagnosed process (as a feature extraction technique for technical diagnostic relevant information); process history and fault statistics, a fuzzy diagnostic model is developed as a fuzzy symptoms-faults mapping and implemented within the heuristic knowledge base. Diagnostic reasoning by MATCHING the proposed fuzzy diagnostic model with the current values of the symptoms (either analytically generated or subjectively observed by the operator) is presented as well as the validation of the design method. first by illustrating it on a very simple simulated process (a low-pass filter) and then by applying it to a simulated DC motor.
引用
收藏
页码:249 / 271
页数:23
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