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针对传统HXD型机车受电弓滑板缺陷检测方法存在检测时间长、检测精度低、检测结果不准确的问题,提出基于机器视觉的HXD型机车受电弓滑板缺陷检测方法.采用差异性的融合跟踪识别方法对HXD型机车受电弓滑板缺陷图像进行采集,根据采集结果,构建HXD型机车受电弓滑板缺陷红外成像模型,采用超声成像方法进行HXD型机车受电弓滑板缺陷的边缘轮廓检测,在此基础上,采用多重分形技术进行HXD型机车受电弓滑板缺陷视觉重构,根据空间区域重构结果对HXD型机车受电弓滑板缺陷特征进行提取,采用VR虚拟现实重构方法,进行HXD型机车受电弓滑板缺陷检测.仿真结果表明,所提方法进行HXD型机车受电弓滑板缺陷检测的精度较高,检测结果准确,且缩短了检测时间,提高了HXD型机车受电弓滑板缺陷主动定位检测能力.
Abstract：In view of the problems of traditional HXD locomotive pantograph slide defects detection method,such as long detection time,low detection accuracy and inaccurate detection results,this paper proposes a machine-vision-based detection method for HXD locomotive pantograph slide defects.The difference fusion tracking recognition method is used to collect the defect image of HXD locomotive pantograph slide plate.According to the collection result,the infrared imaging model is built,and the edge contour is detected by ultrasonic imaging method.On this basis,the multi fractal technology is used to reconstruct the defect vision of slide plate,and the defect characteristics are extracted according to the reconstruction result of space area.Finally,VR reconstruction method is used to reconstruct the image inspect the defects of pantograph slide plate of HXD locomotive.The simulation results show that this detection method has high accuracy,accurate results,short detection time,and improved the active detection ability of HXD locomotive pantograph slide plate defects.
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基本信息:
DOI：10.16393/j.cnki.37-1436/z.2020.02.006
中图分类号:U269.6
引用信息:
[1]金光,杨培义.基于机器视觉的HXD型机车受电弓滑板缺陷的检测研究[J].菏泽学院学报,2020,42(02):28-33.DOI:10.16393/j.cnki.37-1436/z.2020.02.006.
基金信息:
2018年河南省高等学校青年骨干教师基金项目(2018GGJS232)
2020-04-25
2020-04-25