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

被引：21

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

页码：695 / 704

页数：10

共 18 条

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ISERMANN R, 1994, IFAC S SAFEPROCESS 9

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