基于图像处理的受电弓滑板裂纹检测技术研究与发展  

Research and Development of Pantograph Slipper Crack Detection Technology Based on Image Processing

作　　者：陈燕萍[1] CHEN Yan-ping(Hunan Vocational College of Railway Technology,Zhuzhou 412000,China)

机构地区：[1]湖南铁路科技职业技术学院,株洲412000

出　　处：《内燃机与配件》2020年第22期135-136,共2页Internal Combustion Engine & Parts

基　　金：2017年湖南省教育厅科学研究项目——“基于图像处理的受电弓裂纹故障检测技术研究”(项目编号:17C1047)的研究成果。

摘　　要：受电弓滑板是直接与接触网接触的部件,一旦发生故障会影响机车受流质量,甚至会造成刮弓等重大安全事故,因此受电弓滑板故障在线检测对保障铁路安全运行意义重大。本文通过分析现有滑板裂纹检测方法,指出基于图像处理技术的滑板裂纹检测是一种发展趋势,并提出继续探究优化图像边缘检测算法和裂纹识别算法,对有一定运行速度的电力机车受电弓整体碳滑板裂纹检测有着重要意义。Pantograph slipper is a component that is in direct contact with the catenary.Once the fault occurs,it will affect the current quality of the locomotive and even cause major safety accidents such as bow-scraping.Therefore,online fault detection of pantograph slipper is signality to ensure the safe operation of railway.Based on the analysis of the existing slipper crack detection methods,this paper points out that the slipper crack detection based on image processing technology is a development trend,and proposes to continue to explore and optimize the image edge detection algorithm and crack recognition algorithm,which is of great significance to the whole pantograph carbon strip crack detection of electric locomotive with a certain running speed.

关 键 词：图像处理 受电弓 滑板 裂纹检测 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]