Closed-loop fault diagnosis based on a nonlinear process model and automatic fuzzy rule generation

被引：22
|
作者：
Ballé, P
Fuessel, D
机构：
[1] Tech Univ Darmstadt, Inst Automat Control, D-64283 Darmstadt, Germany
[2] Westend Carree, D-60322 Frankfurt, Germany
来源：
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2000年 / 13卷 / 06期
关键词：
fault detection; fault diagnosis; fuzzy classification; fuzzy model; closed-loop supervision;
D O I：
10.1016/S0952-1976(00)00049-X
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this contribution a new approach for fault detection and diagnosis (FDD) for nonlinear processes is presented. A nonlinear fuzzy model with transparent inner structure is used for the generation of relevant symptoms. The resulting symptom patterns are classified with a new self-learning classification structure based on fuzzy rules. The approach is successfully applied to an electropneumatic valve in a closed control loop. (C) 2000 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码：695 / 704
页数：10
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