Title :
Output coding of spatially dependent subclassifiers in evidential framework. Application to the diagnosis of railway track/vehicle transmission system
Author :
Debiolles, A. ; Oukhellou, L. ; Denoeux, Th. ; Aknin, P.
Author_Institution :
SNCF Infrastructure, Paris
Abstract :
This paper addresses the problem of fault detection in a complex system made up of several spatially dependent subsystems. The diagnosis method consists of both detecting and localizing a defect on the system by combining the outputs scores of subclassifiers within the framework of belief function theory. This paper is focused on the coding and the combination of classifier outputs that can reflect the spatial relationship between the subsystems. In the particular case of upstream/downstream dependency, two strategies of output coding are detailed. The proposed methodology is illustrated on a railway device diagnosis application. It will be shown that the choice of an appropriate coding scheme improves the classification results
Keywords :
belief networks; encoding; fault location; large-scale systems; pattern classification; railways; belief function theory; complex system; fault diagnosis; output coding; railway track; spatially dependent subclassifiers; upstream-downstream dependency; vehicle transmission system; Fault detection; Inspection; Neural networks; Pattern recognition; Rail transportation; Tin; Uncertainty; Vehicles; Classification; Dempster-Shafer theory; belief functions; data fusion; diagnosis; neural network;
Conference_Titel :
Information Fusion, 2006 9th International Conference on
Conference_Location :
Florence
Print_ISBN :
1-4244-0953-5
Electronic_ISBN :
0-9721844-6-5
DOI :
10.1109/ICIF.2006.301611