A symbolic reasoning approach to fault detection and isolation applied to electrical machines

Author

Combastel, Christophe ; Gentil, Sylviane ; Rognon, Jean-Pierre

Author_Institution

Lab. d´´Autom. de Grenoble, St Martin d´´Heres, France

Volume

1

fYear

1998

fDate

1-4 Sep 1998

Firstpage

475

Abstract

This paper describes a model-based fault isolation method using fuzzy logic and applied it to the diagnosis of a DC motor current control loop. The global model is divided into multiple local models. Instead of using crisp thresholds to detect an abnormal state of the system, fuzzy information processing is implemented, which allows the fusion of various information (numerical or symbolic) in the decision-making procedure, and thus improves the isolation ability

Keywords

DC motors; diagnostic expert systems; fault diagnosis; fuzzy logic; fuzzy set theory; inference mechanisms; sensor fusion; symbol manipulation; DC motors; current control loop; data fusion; fault detection; fault isolation; fuzzy decision-making; fuzzy logic; fuzzy set theory; qualitative reasoning; symbolic reasoning; Additive noise; Choppers; Current control; DC motors; Electrical fault detection; Fault diagnosis; Fuzzy logic; Fuzzy reasoning; Noise measurement; Voltage;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Applications, 1998. Proceedings of the 1998 IEEE International Conference on

Conference_Location

Trieste

Print_ISBN

0-7803-4104-X

Type

conf

DOI

10.1109/CCA.1998.728494

Filename

728494