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Proceedings Paper

Automated visual inspection of brake shoe wear
Author(s): Shengfang Lu; Zhen Liu; Guo Nan; Guangjun Zhang
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Paper Abstract

With the rapid development of high-speed railway, the automated fault inspection is necessary to ensure train’s operation safety. Visual technology is paid more attention in trouble detection and maintenance. For a linear CCD camera, Image alignment is the first step in fault detection. To increase the speed of image processing, an improved scale invariant feature transform (SIFT) method is presented. The image is divided into multiple levels of different resolution. Then, we do not stop to extract the feature from the lowest resolution to the highest level until we get sufficient SIFT key points. At that level, the image is registered and aligned quickly. In the stage of inspection, we devote our efforts to finding the trouble of brake shoe, which is one of the key components in brake system on electrical multiple units train (EMU). Its pre-warning on wear limitation is very important in fault detection. In this paper, we propose an automatic inspection approach to detect the fault of brake shoe. Firstly, we use multi-resolution pyramid template matching technology to fast locate the brake shoe. Then, we employ Hough transform to detect the circles of bolts in brake region. Due to the rigid characteristic of structure, we can identify whether the brake shoe has a fault. The experiments demonstrate that the way we propose has a good performance, and can meet the need of practical applications.

Paper Details

Date Published: 8 October 2015
PDF: 5 pages
Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96752F (8 October 2015); doi: 10.1117/12.2202334
Show Author Affiliations
Shengfang Lu, Beihang Univ. (China)
Zhen Liu, Beihang Univ. (China)
Guo Nan, Beihang Univ. (China)
Guangjun Zhang, Beihang Univ. (China)


Published in SPIE Proceedings Vol. 9675:
AOPC 2015: Image Processing and Analysis
Chunhua Shen; Weiping Yang; Honghai Liu, Editor(s)

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