Yan-guo Wang

Mr. Yan-guo Wang

Institute of Infrastructure Inspection, China Academy of Railway Sciences Corporation Limited

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 January 2020
Verified
Book Chapter
Open access
PDF file
YWYan-guo Wang
Yan-guo Wang
DXDapeng Xie
Dapeng Xie
QHQiang Han
Qiang Han
YZYi Zhang
Yi Zhang
WZWei Zhou
Wei Zhou
KTKai Tao
Kai Tao
Defects on catenary components are a major part of device faults as a result of a much higher tension on high-speed catenary, such as looseness of bolts, component broken, and component missing. Traditional inspection on catenary components has to be performed only at night with human eyes. Not only the inspection speed is very slow but also the inspection results are not reliable, as a result of the poor lighting environment and long-time working tiredness. In this chapter, we present an automatic visual inspection system for checking the status of components on catenary. A dedicated designed camera system is mounted on an inspection car, which covers almost all the components to be checked and gives great details of each component. Considering the great data storm at each catenary post, high-performance servers with GPU acceleration are used, and technologies of multi-thread and parallel computing are exploited. Furthermore, an intelligent analysis framework is proposed, which uses structural analysis to localize each component in the image and perform automatic detection based on different features such as geometry, texture, and logic rules. The system has been successfully used in China’s high-speed railways, which shows great advantages in the catenary inspection application.

13 March 2018
Verified
Conference Paper
Closed access
YWYan-guo Wang
Yan-guo Wang
WZWei Zhou
Wei Zhou
DXDapeng Xie
Dapeng Xie
YZYi Zhang
Yi Zhang
WZWenxuan Zhang
Wenxuan Zhang
XXXiantang Xue
Xiantang Xue
Defects on catenary components are a major part of device faults as a result of a much higher tension on high-speed catenary, such as looseness of bolts, component broken, and component missing. Traditional inspection on catenary components has to be performed only at night with human eyes. Not only the inspection speed is very slow, but also the inspection results are not reliable, as a result of the poor lighting environment and long-time working tiredness. In this paper, we present an automatic visual inspection system for checking the status of components on catenary. A dedicated designed camera system is mounted on an inspection car, which is composed of many super-high-resolution area-scan cameras with different directions and fields of view. The camera system covers almost all the components to be checked and gives great details of each component. A post detection module is integrated in order to trigger the cameras and lighting device at a proper location, which utilizes several laser distance sensors pointing at the steady arms. Considering the great data storm at each catenary post, high-performance servers with GPU acceleration are used, and technologies of multi-thread and parallel computing are exploited. Furthermore, an intelligent analysis framework is proposed, which uses structural analysis to localize each component in the image, and perform automatic detection based on different features such as geometry, texture, and logic rules. The system can operate at a maximum speed of 160 km/h in both directions, and has been successfully used in China high-speed railways, which shows great advantages in the catenary inspection application.

1 April 2014
Verified
Journal Article
Closed access
YWYan-guo Wang
Yan-guo Wang
YZYue Zhao
Yue Zhao
XLXi-Mei Li
Xi-Mei Li
BTBo Tang
Bo Tang
YCYa-Nan Chu
Ya-Nan Chu
YZYi Zhang
Yi Zhang