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铁路扣件弹条伤损自动检测系统研发与验证 被引量:9

Development and verification of automatic inspection system for high-speed railway fastener
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摘要 针对铁路扣件缺陷自动识别准确率不高等问题,介绍基于三维激光成像技术的高速铁路扣件自动检测系统,重点阐述基于轨道三维图像的弹条型扣件的检测算法。在扣件检测算法中,以先验知识验证扣件位置的方法保证扣件定位的准确率;实现弹条图像的提取;基于正常弹条图像创建真实模拟折断扣件的虚拟负样本。提取图像特征后,利用经过训练的分类器识别扣件缺失、单侧断裂和双侧断裂的状态。最后,结合室内实尺Ⅲ型板轨道模型的数据验证系统的检测效果。研究结果表明,采用提出的扣件缺陷自动检测算法的识别准确率高达97.3%,该系统具有较高的实用潜力。 Aiming at the low recognition accuracy of detection algorithms for railway fastener defects,a novel high-speed railway fastener automatic inspection system was developed using three-dimension(3D)laser imaging and detection algorithm based on track 3D image for hook-shaped fastener.The detection algorithm has some distinctive characteristics.Firstly,the method of verifying fastener location with prior-knowledge was applied to improve the correct rate of locating fasteners.To the best of our knowledge,this is the first time to extract clip images.Secondly,the algorithm of creating visually defective fastener images was proposed to simulate broken fastener based on intact clip images.After extracting the feature of images,the fastener defective statuses,such as missing,one-side broken and two-side broken were identified by the special classifier after training.The experimental results of this detection algorithm verifying with the data of indoor real-scale model indicate that the detection accuracy of this algorithm is as high as 97.3%,and this inspection system has a high potential for field implementation.
作者 代先星 丁世海 阳恩慧 WANG Kelvin Chenping 邱延峻 王平 DAI Xianxing;DING Shihai;YANG Enhui;WANG Kelvin Chenping;QIU Yanjun;WANG Ping(Key Laboratory of Highway Engineering of Sichuan Province,Southwest Jiaotong University,Chengdu 610031,China;Chengdu Hi-tech Investment Development Co.Ltd,Chengdu 610031,China)
出处 《铁道科学与工程学报》 CAS CSCD 北大核心 2018年第10期2478-2486,共9页 Journal of Railway Science and Engineering
基金 国家自然科学基金资助项目(51478398,U1534203,51308477)。
关键词 三维激光成像 扣件定位 虚拟样本 识别算法 准确率 3D laser imaging fastener location visual sample inspection algorithm recognition rate
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  • 1吴章江,李湘敏.计算机图像处理在铁路上的应用[J].中国铁道科学,1993,14(1):36-41. 被引量:4
  • 2王其昌.无砟轨道钢轨扣件[M].成都:西南交通大学出版社,2006.
  • 3Kenneth R,Castleman.Digital Image Processing.北京:清华大学出版社,1997
  • 4Video Inspection System for Railroad Tracks.ENSCO,INC.2000
  • 5K.C.P. Wang.Design and implementation of automated systems for pavement surface distress survey. ASCE Journal of Infrastructure Systems . 2000
  • 6B. Herr.Calibration and Operation of Pavement Profile Scanners. . 2001
  • 7B. Herr.PSI Current Technology Overview. . 2009
  • 8D.H. Mendelsohn.Automated Pavement Crack Detec- tion: An Assessment of Leading Technologies. Pro- ceedings of the Second North American Conference on Managing Pavements . 1987
  • 9D. Crevier,Daniel.Computer Vision and Artificial Intel- ligence. . 1997
  • 10ASSHTO.Standard Practice for Collecting Images of Pavement Surfaces for Distress Detection. AASHTO Designation . 2010

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