铁路路基层面的检测与跟踪
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摘要
利用小波变换将原始雷达记录变换为层面突变信息占主要成分的信号,根据电磁波在层面位置反射回波的特征,设计出层面检测算法,提取出所有道数据的层面点信息,针对层面出现的断裂、跳跃、分岔、交叉等现象,提出层面点归类原则,从而智能地实现层面的跟踪.通过实际资料验证表明,该算法能快速地绘制出铁路路基的层面曲线图,并能反映地下结构层的真实情况,适用于海量数据处理,将技术人员从繁重的读图任务中解脱出来.
Based on the wavelet transform method,the primitive Ground Penetrating Radar(GPR) data were transformed into the signal whose principal constituent was only the sudden changes of the interface information.An interface-test algorithm strategy is designed according to the characteristic of reflection echo from interfaces.By extracting the information of individual points of the interfaces from all traced data,an interface classification principle is proposed to distinguish the rupture,fluctuation,branching and intersection of the interface,so that the interfaces are intelligently traced.The actual testing shows that the method can be used to plot the graph of railroad trackbed interfaces swiftly,reflect the actual conditions of railroad substructures,and process a mass of data.The engineering technicians are released from the burden of the image interpretation.
Based on the wavelet transform method,the primitive Ground Penetrating Radar(GPR) data were transformed into the signal whose principal constituent was only the sudden changes of the interface information.An interface-test algorithm strategy is designed according to the characteristic of reflection echo from interfaces.By extracting the information of individual points of the interfaces from all traced data,an interface classification principle is proposed to distinguish the rupture,fluctuation,branching and intersection of the interface,so that the interfaces are intelligently traced.The actual testing shows that the method can be used to plot the graph of railroad trackbed interfaces swiftly,reflect the actual conditions of railroad substructures,and process a mass of data.The engineering technicians are released from the burden of the image interpretation.
引文
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[2]师学明.小波变换在地质雷达干扰波压制中的应用[J].工程地球物理学报,2008,5(3):279.SHI Xueming.Application of wavelet transform in de-nosingground penetrating radar data[J].Chinese Journal ofEngineering Geophysics,2008,5(3):279.
[3]李才明,王良书,徐鸣洁.基于小波能谱分析的岩溶区探地雷达目标识别[J].地球物理学报,2006,49(5):1499.LI Caiming,WANG Liangshu,XU Mingjie.Objectsrecognition of ground penetrating radar in karst regions usingwavelet energy spectrum analysis[J].Chinese Journal ofGeophsics,2006,49(5):1499.
[4]杨新安,高艳灵.沪宁铁路翻浆冒泥病害的地质雷达检测[J].岩石力学与工程学报,2004,23(1):116.YANG Xin’an,GAO Yanling.GPR Inspection for Shanghai-Nanjing railway trackbed[J].Chinese Journal of RockMechanics and Engineering,2004,23(1):116.
[5]Theodore R Sussmann,Ernest T Selig,James P Hyslip.Railway track condition indicators from ground penetratingradar[J].NDT&E International,2003,36(3):157.
[6]Carpenter D,Jackson P J,Jay A.Enhancement of the GPRmethod of railway trackbed investigation by the installation ofradar detectable geosynthetics[J].NDT&E International,2004,37(2):95.
[7]粟毅,黄春琳,雷文太.探地雷达理论与应用[M].北京:科学出版社,2006.SU Yi,HUANG Chunlin,LEI Wentai.Theory and applicationof GPR[M].Beijing:Science Press,2006.
[8]Ram M Narayanan,Justin W Jakub,Dingqing Li,et al.Railroad track modulus estimation using ground penetratingradar measurements[J].NDT&E International,2004,37(2):141.
[9]董长虹.Matlab小波分析工具箱原理与应用[M].北京:国防工业出版社,2004.DONG Changhong.Theory and application of wavelet toolboxof matlab[M].Beijing:National Defence Industry Press,2004.
[10]廖立坚,杨新安,叶培旭,等.基于时空域的探地雷达杂波的去除[J].勘察科学技术,2008,(3):59.LIAO Lijian,YANG Xin’an,YE Pengxu,et al.Removingclutter of GPR based on temporal and spatial domain[J].SiteInvestigation Science and Technology,2008,(3):59.
[11]周青.地质雷达探测铁路路基数据处理技术研究[D].上海:同济大学土木工程学院,2002.ZHOU Qing.Study on technology of GPR data processingfrom railroad trackbed inspection[D].Shanghai:TongjiUniversity.School of Civil Engineering,2002.
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