机器视觉技术在轨道交通中弯道测距的应用研究

doi:10.16180/j.cnki.issn1007-7820.2023.06.006

Abstract

Abstract:

Real-time detection of the distance between trains is an important way to ensure the safety of rail transit and improve train capacity. In particular, the distance measurement between trains on curved rails is difficult to distance measurement. In order to calculate and optimize the real-time distance measurement formula of the train at the curve, a method of distance measurement of the train at the curve based on machine vision is proposed. In this method, monocular camera is used for track image acquisition, OpenCV algorithm is used to process and analyze the acquired images, and neural network method is used to fit the track line of curved rail, realizing the dynamic extraction of track feature points. The distance formula between trains can be calculated and optimized by building a mathematical model. The experimental results show that the overall error rate of the testing system is less than 9.11% when the duration interval is 40~50 ms. The method for the spacing measurement can be integrated together with other information in the collected images for the information fusion and referred as an important condition in the rail system for a train running.

Key words: track detection, neural network, OpenCV, machine vision, curve distance, distance measurement, monocular ranging, mathematical modeling

CLC Number:

TN99

WANG Huimin,BI Jiazhen,SHEN Tuo,ZHANG Xuanxiong. A Research on the Spacing Measurement Between Two Trains Located at A Curved Track by Machine Vision Technology[J].Electronic Science and Technology, 2023, 36(6): 34-40.

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图片编号	实际距离 /m	测量距离 /m	测量持续时间 /m·s^-1	错误率 /%
1	40	37.56	39	5.50
2	60	56.33	42	5.17
3	80	75.11	37	4.88
4	100	93.89	42	3.90
5	120	112.67	39	3.92
6	140	131.45	40	4.86
7	160	150.22	43	5.31
8	180	169.00	29	6.17
9	200	187.78	36	6.90

A Research on the Spacing Measurement Between Two Trains Located at A Curved Track by Machine Vision Technology

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