基于机器视觉测量技术的城市轨道交通车辆门锁安全监测方法
顾壹1蒋书波1缪小冬1,2
Safety Monitoring of Urban Rail Transit Train Door Lock Based on Embedded Vision Technology
GU YiJIANG ShuboMIAO Xiaodong
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作者信息:1.南京工业大学电气工程与控制科学学院，210009，南京；
2.康尼机电股份有限公司，210009，南京
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Affiliation:College of Electrical Engineering and Control Science, Nanjing University of Technology, 210009, Nanjing, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2019.08.040
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中图分类号/CLCN:U270.38+6
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栏目/Col:研究报告
摘要:
针对城市轨道交通车辆车门中的丝杆锁闭装置长期受到往复冲击和磨损而传统方法难以有效监测的问题，提出了一种基于机器视觉测量技术的监测方法。在机械旋转机构上进行标记，采用圆点标记和直线段标记，分别对圆点和线段进行检测，计算出旋转偏离角度值；对摄像头采集到的轨道车门锁旋转机构图片，通过离散余弦法进行图像预处理，利用阈值分割进行图像二值化，然后对特征标记进行捕获，从而获得角度信息；采用数据统计分析方法，进行门锁安全的判断和预测。试验结果表明，圆点标记比线段标记更易检测，角度值更加精确。
Abstracts:
Since the traditional method could not effectively monitor the screw locking device of urban rail transit door lock because of long-term reciprocating impact, a new monitoring method based on machine vision measurement is proposed. Firstly, the screw locking device is marked with a red dot and a red line, which will be detected respectively to calculate the angle of rotation deviation. Secondly, the images of screw locking device collected by camera are pre-treated by DCT (discrete cosine transformation), the threshold segmentation is used to gain binary images, then to calculate the angle information by capturing the featured marks. Finally, the statistical data analysis method is used to judge and predict the train door lock safety. Experimental results show that the dot marks are detected easier than line marks in collecting more accurate angle information.
引文 / Ref:
顾壹，蒋书波，缪小冬.基于机器视觉测量技术的城市轨道交通车辆门锁安全监测方法[J].城市轨道交通研究，2019，22(08):177.
GU Yi，JIANG Shubo，MIAO Xiaodong.Safety monitoring of urban rail transit train door lock based on embedded vision technology[J].Urban Mass Transit，2019，22(08)：177.
GU Yi，JIANG Shubo，MIAO Xiaodong.Safety monitoring of urban rail transit train door lock based on embedded vision technology[J].Urban Mass Transit，2019，22(08)：177.
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