Fault detection in dynamic systems by a Fuzzy/Bayesian network formulation

被引：30

作者：

D'Angelo, Marcos F. S. V. ^{[1
]}

Palhares, Reinaldo M. ^{[2
]}

Cosme, Luciana B. ^{[3
]}

Aguiar, Lucas A. ^{[1
]}

Fonseca, Felipe S. ^{[1
]}

Caminhas, Walmir M. ^{[2
]}

机构：

[1] Univ Estadual Montes Claros, Dept Comp Sci, BR-39401089 Montes Claros, MG, Brazil

[2] Univ Fed Minas Gerais, Dept Elect Engn, BR-31270901 Belo Horizonte, MG, Brazil

[3] IFNMG, BR-39404058 Montes Claros, MG, Brazil

来源：

APPLIED SOFT COMPUTING | 2014年 / 21卷

关键词：

Fault detection; Inter-turn faults; Induction machine; Fuzzy sets; Bayesian networks; DAMADICS BENCHMARK PROBLEM; ARTIFICIAL IMMUNE-SYSTEM; QUANTITATIVE MODEL; EXPERT-SYSTEM; DIAGNOSIS; OBSERVERS; DESIGN; IDENTIFICATION; STRATEGIES; ALGORITHM;

D O I：

10.1016/j.asoc.2014.04.007

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper the fault detection problem is solved using an alternative methodology based on a fuzzy/Bayesian strategy combining a Bayesian network and the fuzzy set theory. The new important issue in this proposed methodology is to address uncertainties in the input of the Bayesian Network. This contribution is possible since the fuzzy set theory is used as the knowledge representation. To illustrate the technique, the fault detection problem in induction machine stator-winding is considered. Specifically, the faults in the induction machine stator-winding are detected by a state change of stator current. Simulation results are presented to illustrate the advance of the proposed methodology when compared to standard Bayesian network. (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：647 / 653

页数：7

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