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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 is solved by a block that links together pre-processing phase, choice of the representation space, detection then decision. The resolution of the global problem is carried out by a sequential arrangement of the blocks 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, SVM - are used. All these methods have been validated on a rail surface defect detection application in subway context.
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http://docnum.univ-lorraine.fr/prive/SCD_T_2004_0159_BENTOUMI.pdf
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Submitted on : Thursday, March 29, 2018 - 10:44:34 AM
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Mohamed Bentoumi. Outils pour la détection et la classification : Application au diagnostic de défauts de surface de rail. Autre. Université Henri Poincaré - Nancy 1, 2004. Français. ⟨NNT : 2004NAN10159⟩. ⟨tel-01746771⟩

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