| 激光点云在地铁盾构隧道病害诊断中的应用 |
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| 引用本文： | 王晓静,唐超,杨晓飞.激光点云在地铁盾构隧道病害诊断中的应用[J].测绘通报,2020,0(9):33-37. |
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| 作者姓名： | 王晓静 唐超 杨晓飞 |
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| 作者单位： | 北京城建勘测设计研究院有限责任公司, 北京 100101 |
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| 摘 要： | 移动式三维激光扫描技术在地铁盾构隧道安全监测工作中应用较为成熟。本文以地铁盾构隧道监测点云数据为基础进行研究，实现了地铁盾构隧道病害智能诊断。首先通过激光点云生成灰度图像；在此基础上运用卷积神经网络CNN，对地铁盾构隧道中的渗漏水和裂缝的识别技术进行了深入研究；最终生成隧道病害智能诊断系统，为地铁安全运营提供了智能监测方法，有效提高了我国地铁运营监测的技术水准。
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| 关 键 词： | 地铁盾构隧道 渗漏水 裂缝 病害诊断 激光点云 机器学习 |
| 收稿时间： | 2020-06-30 |
Application of laser point cloud for disease diagnosis in subway shield tunnel |
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| WANG Xiaojing,TANG Chao,YANG Xiaofei.Application of laser point cloud for disease diagnosis in subway shield tunnel[J].Bulletin of Surveying and Mapping,2020,0(9):33-37. |
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| Authors: | WANG Xiaojing TANG Chao YANG Xiaofei |
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| Affiliation: | Beijing Urban Construction Exploration and Surveying Design Research Institute Co., Ltd., Beijing 100101, China |
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| Abstract: | As a new type of measurement technology, mobile three-dimensional laser scanning technology is maturely used in subway tunnel safety monitoring. In this paper, we study 3D laser point cloud data to realize intelligent diagnosis of subway shield tunnel diseases. Firstly, the 3D laser point cloud data is converted into grayscale images, and on this basis, a convolutional neural network CNN is used to study the identification technology of water leakage and cracks in subway shield tunnels. Finally, an intelligent diagnosis system for tunnel diseases is generated. This technology provides an intelligent monitoring method for the safe operation of subways and effectively improves the technical level of subway operation monitoring in our country. |
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| Keywords: | subway shield tunnel seepage water crack disease diagnosis laser point cloud machine learning |
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