Conflict Intersection as Diagnostic Model

Author

Benkaci, Mourad ; Doncescu, Andrei ; Takizawa, Makoyo

Author_Institution

Technopole du Madrillet, IRSEEM-ESIGELEC, St. Etienne du Rouvray, France

fYear

2012

fDate

26-29 March 2012

Firstpage

1172

Lastpage

1177

Abstract

In this paper, we propose a new approach for feature selection using fuzzy-ARTMAP classification and conflict characterization in fault diagnosis process. This approach is realized in two stages. In the first one, we classify the unfaulty functioning data of system using the fuzzy-ARTMAP classification. In the second stage, a conflict is accounted between features of test data based on the hyper-cubes resulted in the first stage. Two features are in conflict if her intersection does not belong to the model elaborated by fuzzy-ARTMAP classification. This approach is applied with success in automotive application in which the relevant features are detected and isolated.

Keywords

ART neural nets; automotive engineering; fault diagnosis; feature extraction; fuzzy neural nets; fuzzy set theory; signal classification; automotive application; conflict characterization; conflict intersection; diagnostic model; fault diagnosis process; feature detection; feature isolation; feature selection; fuzzy-ARTMAP classification; hypercubes; unfaulty functioning data; Classification algorithms; Computational modeling; Databases; Fault detection; Feature extraction; Support vector machine classification; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Information Networking and Applications Workshops (WAINA), 2012 26th International Conference on

Conference_Location

Fukuoka

Print_ISBN

978-1-4673-0867-0

Type

conf

DOI

10.1109/WAINA.2012.224

Filename

6185408