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Proceedings Paper

Real-time dynamic measurement of geometric parameters of catenary
Author(s): Fanchang Meng; Zili Zhang; Can Hao; Jia Deng; Weihu Zhou
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Paper Abstract

Catenary is an important part of electrified railway, and its geometric parameters are important parameters reflecting the safe and stable operation of locomotives. With the improvement of its speed, there are higher requirements for high-accuracy and real-time detection of geometric parameters of catenary. The existing systems have problems of long sampling interval, low real-time performance, and light-sensitive. Aiming at the actual requirement of dynamic measurement of catenary geometric parameters, a non-contact catenary geometric parameter detection system based on machine vision was developed. Firstly, a measurement model based on high-power line lasers and high-resolution area cameras was established to meet the application requirements. The measurement principle of the system was analyzed and the detailed formulas were deduced. Secondly, image difference, laser spot roundness analysis and other image processing algorithms were used to quickly and accurately detect the characteristics of laser points on the contact line with complex background. Based on the measurement model and algorithms mentioned above, the hardware and software platform of the system were built, and fast image acquisition and processing was realized by using multi-thread programming technology on high-performance industrial computer, which solved the problems of long sampling interval and low real-time performance during the measurement. Real-time image storage and display and preservation of detection results were realized in the software. Finally, a preliminary experiment was performed on the prototype, and the accuracy of the measurement results was analyzed. Experiment results showed that the system works stably and has high accuracy, which meets the practical application requirements.

Paper Details

Date Published: 18 December 2019
PDF: 9 pages
Proc. SPIE 11338, AOPC 2019: Optical Sensing and Imaging Technology, 113383D (18 December 2019); doi: 10.1117/12.2548060
Show Author Affiliations
Fanchang Meng, Institute of Microelectronics (China)
Zili Zhang, Institute of Microelectronics (China)
Univ. of Chinese Academy of Sciences (China)
Can Hao, Institute of Microelectronics (China)
Jia Deng, Beijing Information Science & Technology Univ. (China)
Weihu Zhou, Institute of Microelectronics (China)
Univ. of Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 11338:
AOPC 2019: Optical Sensing and Imaging Technology
John E. Greivenkamp; Jun Tanida; Yadong Jiang; HaiMei Gong; Jin Lu; Dong Liu, Editor(s)

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