Journal
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART F-JOURNAL OF RAIL AND RAPID TRANSIT
Volume 228, Issue 7, Pages 794-806Publisher
SAGE PUBLICATIONS LTD
DOI: 10.1177/0954409713495532
Keywords
Visual inspection; light-level-independent feature; support vector machine; railway safety
Funding
- National Key Scientific Instruments and Equipment Development Program [2012YQ140032]
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Fault inspection is a key part of ensuring safe operation of freight trains. The development of machine vision technology has resulted in vision-based fault inspection becoming the principal means of fault inspection. An angle cock is an important component in the brake system, and a fault in it could lead to a serious accident. In this paper, we propose an automated vision method to inspect for missing handles on an angle cock during operation of a freight train. Images of the angle cock are acquired and they are analyzed using a proposed gradient encoding histogram and support vector machine that combine to create a detection system. Experimental results show that we achieved a fault detection rate of 99.8% using the proposed system, which represents a good real-time performance and high detection accuracy.
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