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出 处:《计算机工程》2018年第1期252-257,共6页Computer Engineering
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。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.
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
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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