铁路车载GPR检测隧道底部结构的试验研究

发布时间：2018-03-24 18:32

本文选题：车载探地雷达　切入点：隧道底部结构　出处：《西南交通大学》2017年硕士论文

【摘要】：隧道底部结构作为隧道结构重要组成部分,隧道底部结构的完整性对隧道的整体稳定性以及列车行车的安全有重大影响。随着铁路线路运行时间的增长以及线路运输任务的增重,多数运营时间已久的铁路隧道底部结构存在着道床、基床翻浆冒泥,隧道道床、基床破损,道床下沉等病害,危害着列车行驶的安全。然而,传统的病害检测多通过人工巡检来完成,地表以下的病害和一些隐蔽性病害人工巡检检测不到。因此,为满足对隧道底部结构的健康普查,快速无损的检测方式变得十分重要。铁路车载探地雷达检测系统具有检测速度快、检测效率高等优点。本文基于铁路车载探地雷达检测系统对既有线隧道底部结构进行正演数值模拟和实际检测,主要工作如下:1)通过FDTD正演模拟方法对隧道底部结构的层位,以及隧道道床、基床翻浆冒泥;隧道道床、基床破损;隧道整体道床下沉相关隧道底部病害问题进行了数值模拟,研究得出:(1)300MHz的空气耦合天线可清晰分出道砟层、混凝土填充层和仰拱层的层位。(2)300MHz的空气耦合天线可以检测到隧道道床、基床的翻浆冒泥;翻浆冒泥的雷达反射图形表现为一道向上的倒"V"双曲线;当翻浆冒泥发生在隧道道床时,雷达发射图形更明显,更易识别。(3)300MHz的空气耦合天线可以检测到隧道道床、基床的破损;隧道道床、基床破损的雷达反射图同相轴混乱,表现为混乱的倒"V"双曲线;道床的破损比基床的破损更易识别;破损处充填介质水时雷达图像更易识别。(4)使用300MHz的空气耦合天线模拟时,整体道床下沉的雷达反射图能够清晰地反应模型的特征。2)基于西-康和阳-安两条铁路线的实测数据,结合数值模拟结果和设计施工、养护资料,对比研究得出:(1)车载探地雷达检测时,在整条线上雷达图谱是连续的,在隧道进出口处隧道内外隧道底部结构的雷达图谱有明显的区别;隧道进出口的位置也是路基下沉多发地段,雷达图像可以识别这种不良病害现象。(2)对于仰拱型底部结构的隧道,能够辨别出道砟层、混凝土填充层和仰拱层的厚度;对于基底型的底部结构隧道,能够辨别出道砟层和填充层的上表层,可根据层位特征判别出隧道底部结构的区段类型;(3)车载探地雷达可拾取隧道道床和基床的翻浆冒泥病害、隧道道床、基床破损病害、整体道床下沉病害,雷达图像与前述正演模拟结果基本相似,检测结果与铁路工务段提供的养护维修资料一致。铁路车载探地雷达检测系统,可用于运营隧道的隧道底部结构检测,检测不影响铁路的正常行驶,检测随度快,检测结果好,效率高,可以作为隧道底部结构检测的新方法。
[Abstract]:The bottom structure of the tunnel is an important part of the tunnel structure. The integrity of the structure at the bottom of the tunnel has a great impact on the overall stability of the tunnel and the safety of the train. Most of the long-running railway tunnel bottom structure has a road bed, the foundation bed mud, tunnel bed, bed damage, bed sinking and other diseases, endangering the safety of the train, however, In order to satisfy the general health survey of the bottom structure of the tunnel, the traditional inspection of diseases is accomplished by manual inspection, but the diseases below the surface and some hidden diseases can not be detected by manual inspection. The fast nondestructive testing method becomes very important. The railway on-board ground penetrating radar detection system has the fast detection speed, Based on the railway vehicle ground penetrating radar detection system, the forward numerical simulation and actual detection of the bottom structure of the existing railway tunnel are carried out in this paper. The main work is as follows: 1) the layer of the tunnel bottom structure is simulated by FDTD forward modeling method. And the tunnel bed, the base bed and the mud, the tunnel bed, the foundation bed damage, the tunnel overall bed sinking and the tunnel bottom disease problem are simulated. The study shows that the air coupling antenna of 1: 1 or 300 MHz can clearly separate out the ballast layer. The air-coupled antenna of concrete filling layer and inverted arch layer can detect the mud and mud of the tunnel track bed and the base bed, and the radar reflection pattern of the slurry and mud can be shown as an upward inverted "V" hyperbolic curve, and the air coupling antenna of the concrete filling layer and the inverted arch layer can detect the mud and mud of the tunnel track bed and the base bed. When the mud and mud of the tunnel occur in the tunnel bed, the radar emission pattern is more obvious, and the air-coupled antenna of 300MHz can detect the damage of the tunnel bed and the base bed, and the damaged radar reflection image of the tunnel track bed and the base bed is in the same phase axis disorder. A chaotic inverted "V" hyperbolic; the damage of the track bed is easier to identify than the breakage of the base bed; the radar image is easier to recognize when the damaged area is filled with water; and the radar image is easier to recognize using the air-coupled antenna of 300MHz. The radar reflection map of the subsidence of the whole track bed can clearly reflect the characteristics of the model. 2) based on the measured data of two railway lines, Xi-Kang and Yang-an, combined with the numerical simulation results and the design and construction, the maintenance data, The contrast study shows that the radar atlas is continuous in the whole line, and the radar atlas of the bottom structure of the tunnel inside and outside the tunnel at the entrance and exit of the tunnel is obviously different. The entrance and exit position of the tunnel is also the subgrade subsidence area, the radar image can recognize this kind of bad disease phenomenon. For the tunnel with inverted arch bottom structure, it can distinguish the thickness of the ballast layer, the concrete fill layer and the inverted arch layer. For the bottom structure tunnel of the base type, the upper surface layer of the ballast layer and the filling layer can be distinguished, and the section type of the bottom structure of the tunnel can be identified according to the layer characteristics.) the ground penetrating radar on the vehicle can pick up the mud diseases of the tunnel track bed and the foundation bed. The tunnel track bed, the foundation bed damage, the whole track bed sinking disease, the radar image and the aforementioned forward simulation result basically similar, the detection result and the railway works section provides the maintenance maintenance data. It can be used to detect the bottom structure of the tunnel, which does not affect the normal running of the railway. It can be used as a new method for the detection of the bottom structure of the tunnel.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U456

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