Output coding of spatially dependent subclassifiers in evidential framework. Application to the diagnosis of railway track/vehicle transmission system

A. Debiolles, L. Oukhellou, T. Denoeux, P. Aknin
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引用次数: 11

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
证据框架下空间相关子分类器的输出编码。在铁路轨道/车辆传动系统诊断中的应用
本文研究了由多个空间相关子系统组成的复杂系统的故障检测问题。该诊断方法是在信念函数理论的框架内,结合子分类器的输出分数,对系统缺陷进行检测和定位。本文的研究重点是分类器输出的编码和组合,以反映子系统之间的空间关系。在上游/下游依赖的特殊情况下,详细介绍了两种输出编码策略。最后以铁路设备诊断为例说明了该方法的应用。结果表明,选择合适的编码方案可以改善分类结果
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