基于SIFT特征提取的受电弓滑板磨损检测  

Wear Detection of Pantograph Slide Plate Based on SIFT Feature Extraction

作　　者：郅富标 李艳 ZHI Fubiao;LI Yan(Henan Vocational College of Industry and Information Technology,Jiaozuo Henan 454000,China;Jiaozuo Metallurgical Building Materials Senior Technical School,Jiaozuo Henan 454000,China)

机构地区：[1]河南工业和信息化职业学院,河南焦作454000 [2]焦作冶金建材高级技工学校,河南焦作454000

出　　处：《北京工业职业技术学院学报》2023年第1期11-14,共4页Journal of Beijing Polytechnic College

基　　金：2022年河南省高等学校重点科研项目计划(22B120001)。

摘　　要：受电弓影响列车安全,如果其滑板磨损严重,必须及时更换。传统方法很难对滑板的磨损情况进行快速准确的检测。本文采用基于SIFT算法进行特征提取,使用Canny算子进行边缘检测,对受电弓滑板的磨损进行计算。实验结果表明,这一图像检测方法能够对受电弓磨损情况进行准确及时的判定,测量精度符合预期。The pantograph affects the safety of the train. If its sliding plate is seriously worn, it must be replaced in time. It is difficult to detect the wear of sliding plate quickly and accurately by traditional methods. In this paper, the SIFT algorithm is used for feature extraction, and the Canny operator is used for edge detection to calculate the wear of pantograph sliding plate. The experimental results show that this image detection method can accurately and timely determine the pantograph wear, and the measurement accuracy meets the expectations.

关 键 词：受电弓 图像处理 SIFT 特征提取 边缘检测 

分 类 号：TM764.2[电气工程—电力系统及自动化]