Rail surface crack defect based on HALCON
-
摘要: 针对当前检测钢轨表面缺陷存在的效率低、易漏检误检问题,提出一种基于HALCON图像处理软件开发的钢轨表面缺陷检测方法,实现测量过程中对缺陷图像的识别和处理。通过钢轨模拟检测平台采集钢轨表面图像,利用HALCON软件对获取的原始图像进行预处理、边缘检测、目标特征提取,计算相关几何特征信息并定位钢轨表面缺陷。实验表明,该方法具有较高的测量精度和测量效率,能够满足实际应用,为钢轨表面缺陷在线检测提供了新的途径。Abstract: Aiming at the existing problems of inefficiency, leak and error in the detection of rail surface defects, this article presented a method to detect the surface defects of rail based on HALCON software, and implement functions of recognizing and processing of defect images. The method was to acquire rail surface images by a simulative rail test platform, preprocess the original images, detect edge, extract features by using HALCON software, calculate and calibrate the relevant geometrical information of defects, get the position of different kinds of defects finally. The experiment showed that this method was with high measuring precision and efficiency, and could meet the practical application, provided a new way for on-line measurement for rail surface defects.
-
Key words:
- rail detection /
- HALCON /
- image processing /
- defect
-
[1] 刘泽,王平,王嵬.钢轨表面缺陷检测机器视觉系统的设计[J].电子测量与仪器学报,2010,24(11):1013-1014. [2] 官鑫,赵智雅,高晓蓉.图像处理技术在钢轨表面缺陷检测和分类中的应用[J].铁路计算机应用,2009,18(6):27-28. [3] 陈黎,黄心汉,王敏,等.带钢缺陷图像的自动阈值分割研究[J].计算机工程与应用,2002,38(7):244-245. [4] 孟佳. 钢轨表面缺陷识别系统的设计与研究[D].成都:西南交通大学,2005:68-75. [5] 米曾真,谢志江,陈涛,等.重轨图像增强与边缘提取的关键技术[J].光学精密工程,2012,20(7):1648. [6] 孟佳,高晓蓉.便携式钢轨磨耗自动检测系统[J].中国铁路,2005,(7):58. [7] 张晶,王黎,高晓蓉,等.数字图像处理中的图像分割技术及其应用[J].信息技术,2010,(10):37-38. [8] 刘蕴辉,刘铁,王权良,等.基于图像处理的铁轨表面缺陷检测算法[J].计算机工程,2007,11(7):236-237. [9] 吴凤和. 基于计算机视觉测量技术的图像轮廓提取方法研究[J].计量学报,2007,28(1):19-21. [10] 段瑞玲,李庆祥,李玉和. 图像边缘检测方法研究综述[C].光学技术 ,2005,(31):25-27. [11] 陈果,左洪福. 图像的自适应模糊阈值分割法[J].自动化学报,2003(29):33-36. [12] Qingyong Li, Shengwei Ren, Member. A Real-Time Visual Inspection System for Discrete Surface Defects of Rail Heads[J].IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,2012,61(8): 2190-2191. [13] E. Deutschl, C. Gasser, A. Niel, J. Werschonig.Defect Detec-tion on Rail Surfaces by a Vision based System[J].IEEE Intelligent Vehicles Symposium,2004 (7): 508-510. [14] 许桢英,李健康,凌俊,等.基于Halcon的电连接器壳体缺陷检测系统设计[J].制造业自动化,2015(18):135-138. [15] 王文成. 基于Halcon的齿轮缺陷检测系统设计[J].机械传动,2014,38(9):61.
点击查看大图
下载:
