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Outils pour la détection et la classification
Application au diagnostic de défauts de surface de rail

Abstract : The works concern with detection and classification problems for fault diagnosis. Two approaches are treated. The first one, where the K-classes global problem is splitted into sub problems, is called simultaneous detection and classification. Each sub problem consists of one or several classes detection, and it is solved by a block that links together pre-processing phase, choice of the representation space, detection then decision. The complete resolution of the K-classes problem is carried out by a sequential arrangement of the blocks - in accordance with a hierarchic decision tree - or a parallel decision scheme.
The second approach is the successive detection and classification approach. It consits of a first basic signal
processing for alarm generation that indicates the possible existence of default. Then, high-level processings are activated in order to precisely analyze the default signature. Classification tools - linear classifiers, neural classifiers, support vector machines - are detailed. A section is focused on the margins tuning and generalisation capabilities of the classifiers.
All these methods have been validated on a rail surface defect detection application in subway context. A real
time prototype allows testing the simultaneous detection and classification solutions in running conditions. The
good detection and false alarm rates have been calculated for 4 classes of rail defect. The wavelet transform, the inverse filtering and the independent component analysis are particularly detailed for the pre-processing phase.
A set of on-site labelled measurings allows to statistically qualifying the solutions of the successive
classification and detection approach. A hierarchical presentation of the methods is proposed, in terms of
generalisation capability, complexity and also ability to solve the problem with or without optimisation of the
representation space.
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Submitted on : Saturday, December 23, 2006 - 8:35:43 PM
Last modification on : Friday, October 23, 2020 - 4:38:59 PM
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  • HAL Id : tel-00122046, version 1

Citation

Mohamed Bentoumi. Outils pour la détection et la classification
Application au diagnostic de défauts de surface de rail. Interface homme-machine [cs.HC]. Université Henri Poincaré - Nancy I, 2004. Français. ⟨tel-00122046⟩

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