圆钢表面缺陷视觉检测技术研究现状与展望
Development and Perspective of Vision Inspection Technology for Surface Defect of Steel Bar
摘 要
随着工业上对原材料质量要求的提高，圆钢表面缺陷检测成了工业生产中必不可少的组成环节。表面缺陷检测技术主要分为传统无损检测方法和机器视觉检测方法两类，机器视觉检测方法由于高实时性和高准确性而使用更加广泛。文章介绍了基于机器视觉的圆钢表面缺陷检测技术特点以及国内外最新研究进展，分析了视觉检测技术工作原理和几个关键问题，指出该领域内同仁应该积极吸收国内外先进技术并推陈出新，共同促进机器视觉检测技术的进步。
圆钢表面缺陷
在线检测
图像处理
Machine vision
Steel bar surface defect
On-line inspection
Digital image processing
Abstract
With the increasing demand of requirement for the quality of raw materials in industry, surface defect inspection of steel bar became an essential part of industrial production. Surface defect inspection technology mainly included traditional NDT and machine vision detection method, and the later was more and more widely used because of its rapidity and high accuracy. The characteristics of vision-based detection technology for steel bar surface defect and the newest research development were introduced. The working principle of vision inspection technology and key issues were analyzed. It was proposed that advanced technology both in home and abroad should be actively absorbed and innovations be then made to promote the development of machine vision inspection technology.
中图分类号 TG335.6 TP274
所属栏目 综述
基金项目 山东大学研究生自主创新基金资助项目(yzc11056)
收稿日期 2011/5/5
修改稿日期
网络出版日期
作者单位点击查看
备注李武斌(1986-)，男，博士研究生，主要研究方向为图像处理、模式识别。
引用该论文: LI Wu-Bin,LU Chang-Hou,LI Jun,ZHANG Jian-Chuan. Development and Perspective of Vision Inspection Technology for Surface Defect of Steel Bar[J]. Nondestructive Testing, 2012, 34(5): 54～57
李武斌,路长厚,李君,张建川. 圆钢表面缺陷视觉检测技术研究现状与展望[J]. 无损检测, 2012, 34(5): 54～57
被引情况:
【1】刘彬,董世运, "激光熔覆层厚度对超声表面波评价表层缺陷深度的影响",无损检测 37, 7-10(2015)
【2】孙阔原,蒋理兴,王俊亚,张峰,韩硕, "轴类工件表面视觉自动检测系统",无损检测 38, 53-57(2016)
共有人对该论文发表了看法，其中：
人认为该论文很差
人认为该论文较差
人认为该论文一般
人认为该论文较好
人认为该论文很好
参考文献
【1】Huang H, Gutchess D, Chang T. Imaging-based in-line surface defect inspection for bar rolling［C］. Proceedings of The Iron & Steel Conference and Exposi-tion. Nashville, USA: Heat Transfer and Fluid Flow Laboratory,2004:1-12.
【2】Jia H, Murphey Y L, Shi J, et al. An intelligent real-time vision system for surface defect detection［C］. Proceedings of International Conference on Pattern Recognition. Cambridge, UK: Image Vision Computing Group,2004:239-242.
【3】Malamas E N, Petrakis E G M, Zervakis M, et al. A survey on industrial vision systems, applications and tools［J］. Image and Vision Computing,2003,21(2):171-188.
【4】鲍凯，王俊涛，吴东流.新兴的无损检测技术——红外热波成像检测［J］.无损检测,2006,28(8):393-397.
【5】Morris, J W. Method and Apparatus for Real Time Defect Inspection of Metal at Elevated Temperature［P］. United States, 5654977: 1997-08-05.
【6】Chang T S, Gutchess D, Huang, et al. Apparatus and Method for Detecting Surface Defects on a Workpiece Such As a Rolled/Drawn Metal Bar［P］. United States, 20080063426: 2008-03-13.
【7】徐长航，陈国明，谢静.红外图像处理技术在金属表面缺陷检测中的应用［J］.制造业自动化,2009,31(10):51-54.
【8】Yun J P, Park Y S, Seo B, et al. Development of real-time defect detection algorithm for high-speed steel bar in coil(BIC)［C］. Proceedings of SICE-ICASE International Joint Conference. Bexco, Korea: Universitt Siegen,2006:2495-2498.
【9】Choi S H, Bae H M, Hwang H W, et al. Device and Method for Optically Detecting Surface Defect of Round Wire Rod［P］. United States, 20100246974: 2010-09-30.
【10】张子恕，史建军.影像式线棒材在线表面检测系统［J］.轧钢,2009,26(3):46-48.
【11】Liu Y C, Hsu Y L, Sun Y N, et al. A computer vision system for automatic steel surface inspection［C］. Proceedings of IEEE Conference on Industrial Electronics and Applications. Taichung, Taiwan: ACM Press,2010:1667-1670.
【2】Jia H, Murphey Y L, Shi J, et al. An intelligent real-time vision system for surface defect detection［C］. Proceedings of International Conference on Pattern Recognition. Cambridge, UK: Image Vision Computing Group,2004:239-242.
【3】Malamas E N, Petrakis E G M, Zervakis M, et al. A survey on industrial vision systems, applications and tools［J］. Image and Vision Computing,2003,21(2):171-188.
【4】鲍凯，王俊涛，吴东流.新兴的无损检测技术——红外热波成像检测［J］.无损检测,2006,28(8):393-397.
【5】Morris, J W. Method and Apparatus for Real Time Defect Inspection of Metal at Elevated Temperature［P］. United States, 5654977: 1997-08-05.
【6】Chang T S, Gutchess D, Huang, et al. Apparatus and Method for Detecting Surface Defects on a Workpiece Such As a Rolled/Drawn Metal Bar［P］. United States, 20080063426: 2008-03-13.
【7】徐长航，陈国明，谢静.红外图像处理技术在金属表面缺陷检测中的应用［J］.制造业自动化,2009,31(10):51-54.
【8】Yun J P, Park Y S, Seo B, et al. Development of real-time defect detection algorithm for high-speed steel bar in coil(BIC)［C］. Proceedings of SICE-ICASE International Joint Conference. Bexco, Korea: Universitt Siegen,2006:2495-2498.
【9】Choi S H, Bae H M, Hwang H W, et al. Device and Method for Optically Detecting Surface Defect of Round Wire Rod［P］. United States, 20100246974: 2010-09-30.
【10】张子恕，史建军.影像式线棒材在线表面检测系统［J］.轧钢,2009,26(3):46-48.
【11】Liu Y C, Hsu Y L, Sun Y N, et al. A computer vision system for automatic steel surface inspection［C］. Proceedings of IEEE Conference on Industrial Electronics and Applications. Taichung, Taiwan: ACM Press,2010:1667-1670.
相关信息
