全钢子午线轮胎X光图像的缺陷检测研究现状
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摘要
全钢子午线轮胎结构复杂,生产过程中会出现多种缺陷,利用图像处理技术能够对全钢子午线轮胎的X光图像进行缺陷检测。为了更清楚地梳理现存算法,对当前全钢子午线轮胎X光图像的缺陷检测算法做了大量调研。首先,对全钢子午线轮胎缺陷检测的研究现状及发展历程做了梳理和回顾;然后,对全钢子午线轮胎缺陷进行分类,根据不同类型的缺陷分别介绍该类缺陷的主要检测方法,并对检测方法进行优缺点分析;最后,指出未来在全钢子午线轮胎缺陷研究领域中面临的挑战,展望了轮胎缺陷检测技术的发展方向。
All-steel radial tires have complex structures and there may be many defects in their production process. Image processing technology can be used to detect the defects of all-steel radial tires in X-ray images. In order to better sort out the existing algorithms, we have conducted research into the current defect detection algorithms for X-ray images of all-steel radial tires. First, we studied the current status and development history of defect detection for all-steel radial tires. We then classified the defects of all-steel radial tires, and made an introduction to the main detection methods for these defects according to different defect types, and analyzed their advantages and disadvantages. Finally, we pointed out the challenges in future research and look forward to the development direction of defect detection technology.
All-steel radial tires have complex structures and there may be many defects in their production process. Image processing technology can be used to detect the defects of all-steel radial tires in X-ray images. In order to better sort out the existing algorithms, we have conducted research into the current defect detection algorithms for X-ray images of all-steel radial tires. First, we studied the current status and development history of defect detection for all-steel radial tires. We then classified the defects of all-steel radial tires, and made an introduction to the main detection methods for these defects according to different defect types, and analyzed their advantages and disadvantages. Finally, we pointed out the challenges in future research and look forward to the development direction of defect detection technology.
引文
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[14]GUO Qiang,WEI Zhenwen.Tire defect detection using image component decomposition[J].Research j ournal of applied sciences,engineering and technology,2012,4(1):41-44.
[15]张岩,李涛,李庆领.基于全变分模型的子午线轮胎X射线图像胎侧缺陷自动检测方法[J].青岛科技大学学报(自然科学版),2017,38(3):106-112.ZHANG Yan,LI Tao,LI Qingling.Automatic radial tire sidewall defect detection in tire X-ray images based on total variation model[J].Journal of Qingdao University of Science and Technology(Natural Science Edition),201 7,38(3):106-112.
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[19]张茂强.子午轮胎缺陷检测方法与系统设计研究[D].济南:山东大学,2014.ZHANG Maoqiang.Research on detection method and system design of radial tire's defects[D].Jinan:Shandong University,2014.
[20]郑筱智.基于空域与频域结合的轮胎缺陷检测[D].济南:山东财经大学,2016.ZHENG Xiaozhi.Tire defect detection based on integration of spatial and frequency domains[D].Jinan:Shandong University of Finance and Economics,2016.
[21]ZHANG Maoqiang,GUO Qiqng,YANG Xingqiang.Tire defect detection on impurities[J].Computer aided drafting,design and manufacturing,2014,24(1):32-35.
[22]章玲.基于图像放缩算法的轮胎缺陷检测系统研究与实现[D].济南:山东大学,2015.ZHANG Ling.The research and implementation of tire defection system with image scaling function[D].Jinan:Shandong University,2015.
[23]李杰.基于轮胎质量检测成像与常见故障识别算法研究[D].沈阳:东北大学,2012.LI Jie.Research on the image of tyres quality test and common fault recognition algorithms[D].Shenyang:Northeastern University,2012.
[24]张小丽.轮胎缺陷X光检测图像的处理与识別研究[D].天津:天津大学,2007.ZHANG Xiaoli.Processing and recognition of defects in X-ray tire image[D].Tianjin:Tianjin University,2007.
[25]应崎伟.汽车轮胎瑕疵的计算机视觉识别系统[D].杭州:杭州电子科技大学,2012.YING Qiwei.Computer version system for tire defects[D].Hangzhou:Hangzhou Dianzi University,2012.
[26]于向茹,丁健配,李金屏.轮胎帘线交叉重叠缺陷检测[J].济南大学学报(自然科学版),2017,31(6):494-498.YU Xiangru,DING Jianpei,LI Jinping.Detection of cross-over cord defect on tire[J].Journal of University of Jinan(Natural science Edition),2017,3 1(6):494-498.
[27]袁晔.X光轮胎缺陷自动检测系统的研究[D].天津:天津大学,2008.YUAN Ye.X-ray tire defects automatic detection system[D].Tianjin:Tianjin University,2008.
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