基于机器视觉的受电弓滑板厚度检测方法研究
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内蒙古科技大学 机械工程学院, 包头 014010

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TP391

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Pantograph slide thickness detection method research based on machine vision
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School of Mechanical Engineering, Inner Mongolia University of Science and Technology, Baotou 014010 China

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    摘要:

    良好的弓网关系是电气化铁路正常运行的重要因素之一,应用机器视觉技术对滑板厚度进行测量,可以减少由人为误差导致的弓网事故。通过对实验室环境下拍摄的滑板图片进行图像灰度处理、透视校正、滑板图像滤波、滑板图像增强处理完成图像预处理,本文提出对滑板图像进行边缘检测和形态学开闭运算后采用图像追踪的方法,实现滑板边缘提取和定位,计算得到滑板厚度最小值。对滑板进行测量实验,由本方法得到的数值与实测值进行对比分析,得到的测量结果误差基本在±0.5mm。结果表明本文提出的图像处理方法可以实现滑板磨耗检测,对现场实际应用研究有很大的价值。

    Abstract:

    Good pantograph net relationship is one of the important factors for the normal run of electrified railway. Using machine vision technology to measure the thickness of pantograph slide can reduce the pantograph net accidents caused by human error. The pantograph slide pictures taken in the laboratory environment were processed by image grayscale processing, perspective correction, pantograph slide image filtering and pantograph slide image enhancement. This paper proposes a method of image tracking after edge detection and morphology open and close operation on pantograph slide image, realize the pantograph slide edge detection and positioning, The minimum value of pantograph slide thickness is calculated. Carry out measurement experiment to the pantograph slide, and the results obtained by this method were compared with the measured values, and the measure error was basically ±0.5mm. The results show that the image processing method proposed in this paper can realize the pantograph slide abrasion detection and has great value to the practical application research.

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刘文婧,赵俊,王少锋.基于机器视觉的受电弓滑板厚度检测方法研究[J].电子测量技术,2021,44(24):128-133

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  • 在线发布日期: 2024-07-02
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