智能钢轨磨耗检测方法的研究

计算机科学 ›› 2018, Vol. 45 ›› Issue (11A): 274-277.

智能钢轨磨耗检测方法的研究

张秀峰, 王娟, 丁强

大连民族大学机电工程学院辽宁大连116600

出版日期:2019-02-26 发布日期:2019-02-26
作者简介:张秀峰(1975-),男,博士,副教授,主要研究方向为光电检测技术与仪器、生物特征识别、图像处理,E-mail:zhxf7710@dlnu.edu.cn;王娟(1975-),女,副教授,主要研究方向为控制科学与工程;丁强(1993-),男,硕士生,主要研究方向为检测技术与仪器。
基金资助:
本文受中央高学自主科研项目(wd01046),大连市科学技术基金计划项目(2013J21DW015)资助。

Research on Intelligent Detection Method of Steel Rail Abrasion

ZHANG Xiu-feng, WANG Juan, DING Qiang

College of Electromechanical Engineering,Dalian Nationalities University,Dalian,Liaoning 116600,China

Online:2019-02-26 Published:2019-02-26

摘要/Abstract

摘要： 在分析了目前国内外钢轨磨耗检测方法及技术特点的基础上,结合实际需求,提出了基于一字线激光图像处理的钢轨磨耗检测方法。利用一字线激光图像在磨耗钢轨上的弯曲程度检测钢轨磨耗的宽度与深度,通过屋脊形边缘检测法寻找激光图像的中心点和边缘点,并拟合直线;确定磨耗检测的特征量组,利用特征量间的相关系数,去除冗余特征,选择最优特征组合。实验测试结果表明,该方法能够有效提取特征量值,并准确计算钢轨磨耗的宽度和深度值,具有计算信息量小、算法简便、精度高的特点,为钢轨磨耗检测装置的开发奠定了基础。

关键词: 边缘检测, 钢轨磨耗, 图像处理, 相关系数

Abstract: In order to meet the actual demand,a new detection method of steel rail abrasion based on line laser image processing was proposed after analyzing current methods and characteristics of steel rail abrasion detecting equipment at home and abroad.The bending degree of line laser image on the wear of rail was used to determine the width and depth of steel rail abrasion.The edge points and centre points could be found by using roof-type edge detection method,then straight lines can be fitted by using these points.The optimal features combination is selected by removing the redundant features with high correlation.Finally,the experiment results show that the method could extract features amount effectively,and obtain the width and depth of the steel rail abrasion accurately.The characteristics of algorithm inculde small amount,simple and high precision.It lays the foundation for the development of steel rail abrasion detection device.

Key words: Correlation coefficient, Edge detection, Image processing, Steel rail abrasion

中图分类号:

TH74

张秀峰, 王娟, 丁强. 智能钢轨磨耗检测方法的研究[J]. 计算机科学, 2018, 45(11A): 274-277. https://doi.org/

ZHANG Xiu-feng, WANG Juan, DING Qiang. Research on Intelligent Detection Method of Steel Rail Abrasion[J]. Computer Science, 2018, 45(11A): 274-277. https://doi.org/

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