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作 者:刘宏立[1] 刘伟[1] 马子骥[1] 李艳福[1] LIU Hongli;LIU Wei;MA Ziji;LI Yanfu(College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)
机构地区:[1]湖南大学电气与信息工程学院,湖南长沙410082
出 处:《铁道学报》2020年第12期106-112,共7页Journal of the China Railway Society
基 金:国家自然科学基金(61771191)。
摘 要:实时准确地从车载钢轨轮廓检测系统获取的原始廓形中识别出有效轮廓来评估线路状态,是轨道质检工作面临的重要问题。首先分析对比了实际线路中不同区域的钢轨轮廓形态,指出轨头→轨腰的间断性及测量轨腰与标准轨腰的匹配性是识别有效轮廓的重要依据;然后针对测量轮廓轨腰状态未知、剩余区域特征点数不足的缺陷,提出使用轨颚点及轨头内侧直线来构造轮廓配准矩阵;最后依据配准轮廓轨腰重合区的单向Hausdorff距离与统计阈值的比较,实现测量轮廓有效性的精确判别。实际线路上的测试结果表明,本文方法识别出的有效轮廓分布与实际路况基本一致,识别准确率达93.3%,平均识别速度10.8 ms/幅,车体检测速度83.3 km/h,具有一定的理论及工程应用价值。Real-time and accurate recognition of the effective rail profiles from the original ones acquired by the onboard rail profile detection system to assess the quality of track is a key challenge to rail inspection.Firstly,on the basis of the comparative analysis of the rail profiles located in different areas of the railway,the discontinuity between rail head and rail waist and the match between measured rail waist and standard one were used as the important basis to recognize the effective profiles.Then,in view of the defects of the unknown status of rail waist of measured profile and insufficient feature points in other areas,a novel method using the rail jaw point and railhead inner line to construct the curve registration matrix was proposed.Last,the measured profile was classified precisely by computing the directed Hausdorff distance of rail waist overlap areas and comparing it with statistical threshold.The experiment results on actual railway show that the distributions of effective profiles based on the proposed method are accurately coincided with the real conditions,with the recognition accuracy rate reaching 93.3%,and the average recognition speed reaching 10.8ms per frame.The measured system can run at a speed of 83.3 km/h under the experimental setup,which has a definite theoretical and engineering application value.
关 键 词:轨道结构 钢轨轮廓 形态识别 单向Hausdorff距离
分 类 号:U216.3[交通运输工程—道路与铁道工程]
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