Title :
Conflict Intersection as Diagnostic Model
Author :
Benkaci, Mourad ; Doncescu, Andrei ; Takizawa, Makoyo
Author_Institution :
Technopole du Madrillet, IRSEEM-ESIGELEC, St. Etienne du Rouvray, France
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;
Conference_Titel :
Advanced Information Networking and Applications Workshops (WAINA), 2012 26th International Conference on
Conference_Location :
Fukuoka
Print_ISBN :
978-1-4673-0867-0
DOI :
10.1109/WAINA.2012.224
