Fast rail corrugation detection based on texture filtering

Jie Xiao; Kaixia Lu

doi:10.1117/12.2285990

19 February 2018 Fast rail corrugation detection based on texture filtering

Jie Xiao, Kaixia Lu

Proceedings Volume 10607, MIPPR 2017: Multispectral Image Acquisition, Processing, and Analysis; 106070Q (2018) https://doi.org/10.1117/12.2285990
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China

Abstract

The condition detection of rails in high-speed railway is one of the important means to ensure the safety of railway transportation. In order to replace the traditional manual inspection, save manpower and material resources, and improve the detection speed and accuracy, it is of great significance to develop a machine vision system for locating and identifying defects on rails automatically. Rail defects exhibit different properties and are divided into various categories related to the type and position of flaws on the rail. Several kinds of interrelated factors cause rail defects such as type of rail, construction conditions, and speed and/or frequency of trains using the rail. Rail corrugation is a particular kind of defects that produce an undulatory deformation on the rail heads. In high speed train, the corrugation induces harmful vibrations on wheels and its components and reduces the lifetime of rails. This type of defects should be detected to avoid rail fractures. In this paper, a novel method for fast rail corrugation detection based on texture filtering was proposed.

Citation Download Citation

Jie Xiao and Kaixia Lu "Fast rail corrugation detection based on texture filtering", Proc. SPIE 10607, MIPPR 2017: Multispectral Image Acquisition, Processing, and Analysis, 106070Q (19 February 2018); https://doi.org/10.1117/12.2285990

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