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计算机工程

• 图形图像处理 • 上一篇    下一篇

高铁接触网悬挂装置的等电位线故障检测方法

胡冉冉,刘志刚   

  1. (西南交通大学 电气工程学院,成都 610031)
  • 收稿日期:2016-11-10 出版日期:2018-01-15 发布日期:2018-01-15
  • 作者简介:胡冉冉(1992—),女,硕士研究生,主研方向为图像处理;刘志刚,教授、博士生导师。

Fault Detection Method of Electric Potential Line in Catenary Support and Suspension Devices of High-speed Railway

HU Ranran,LIU Zhigang   

  1. (School of Electrical Engineering,Southwest Jiaotong University,Chengdu 610031,China)
  • Received:2016-11-10 Online:2018-01-15 Published:2018-01-15

摘要: 针对高铁接触网支撑与悬挂装置中的等电位线散股问题,提出一种基于机器视觉技术的自动化等电位线散股检测方法。提取包含等电位线的图像方向梯度直方图特征,训练AdaBoost级联与支持向量机混合分类器,实现等电位线的定位。通过衡量等电位线的面积给出评价等电位线故障的判据。实验结果表明,该方法具有较高的准确性,可以大幅降低接触网运营与维护的工作强度,具有一定的推广价值。

关键词: 等电位线, 方向梯度直方图特征, 级联混合分类器, 大津法, 面积判断

Abstract: In terms of the loose strands problem of electric potential line in the catenary support and suspension devices of high-speed railway,an automatic electric potential line loose strands detection method based on machine vision technology is proposed.The Histogram of Oriented Gradient(HOG) characteristics of the part are extracted.The hybrid classifier of AdaBoost cascade and Support Vector Machine(SVM) are trained to realize electric potential line location.A criterion for evaluating electric potential line faults is given by measuring the area of electric potential.Experimental results show that the proposed method has high detection accuracy.The method can reduce the intensity of catenary operation and maintenance work significantly and has a certain popularization value.

Key words: electric potential line, Histogram of Oriented Gradient(HOG) characteristic, cascade hybrid classifier, Otsu method, area judgment

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