接触网绝缘子表面容易积累污秽并诱发污闪,这对于电气化铁路的安全运营是一个极大的隐患.针对此问题,将机器视觉技术应用于接触网绝缘子污秽检测,提出了基于SURF特征样本库对绝缘子进行识别,采用双目摄像头计算出绝缘子的位置信息,根据HSV的色彩范围对绝缘子污秽进行分类.实验室测试表明,通过这些方法能够有效的判断绝缘子的污秽状况.%The surface of the overhead line insulators easily accumulates pollution and induces pollution flashover,which is a great hidden danger for the safe operation of electrified railways.In order to solve the problem,the machine vision technology was applied to detect contamination of overhead line insulators.This study proposed to identify insulators based on a SURF feature sample database,to calculate insulators' location information with binocular cameras,and to classify insulator contamination based on the color range of HSV.Laboratory tests show that these methods can effectively determine the conditions of insulator contamination.
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