测绘通报 ›› 2022, Vol. 0 ›› Issue (9): 12-17.doi: 10.13474/j.cnki.11-2246.2022.0256

• 交通建设工程测绘技术应用研究 • 上一篇    下一篇

城市轨道交通盾构隧道病害空间分布特征量化研究

王宁1,2, 任传斌3, 姜伟玲4   

  1. 1. 陕西工业职业技术学院, 陕西 咸阳 712000;
    2. 咸阳市数字城市与地理空间大数据技术重点实验室, 陕西 咸阳 712000;
    3. 北京城建勘测设计研究院有限责任公司, 北京 100101;
    4. 北京城建集团有限 责任公司, 北京 100088
  • 收稿日期:2022-07-18 发布日期:2022-09-30
  • 通讯作者: 任传斌。E-mail:renchb@126.com
  • 作者简介:王宁(1987—),男,硕士,讲师,研究方向为点云数据处理与应用。E-mail:814838428@qq.com
  • 基金资助:
    陕西工业职业技术学院青年科技创新团队(KCTD2022-01)

Quantitative study on spatial distribution characteristics of diseases in shield tunnel of urban rail transit

WANG Ning1,2, REN Chuanbin3, JIANG Weiling4   

  1. 1. Shanxi Polytechnic Institute, Xianyang 712000, China;
    2. Xian yang Key Laboratory of Digital Geospatial Big Data, Xianyang 712000, China;
    3. Beijing Urban Construction Exploration & Surveying Design Research Institute Co., Ltd., Beijing 100101, China;
    4. Beijing Urban Construction Group Co., Ltd., Beijing 100088, China
  • Received:2022-07-18 Published:2022-09-30

摘要: 随着地铁的不断建设与投入使用,我国正在逐步进入地铁运营养护期,地铁病害检测与运营养护也逐渐得到重视。随着地铁运营年限的增加,病害也呈现加重趋势。通过三维激光扫描技术获取隧道病害全面信息,利用空间自相关性分析地铁隧道病害的地理空间分布特征,对于认识病害形成机理,防治病害具有重要意义。本文以某地铁隧道通过三维激光扫描所获得的水平收敛数据为基础,利用空间自相关分析法定量分析了病害在地理空间上的分布特征,以及与周边水文地质环境的关系。结果表明,隧道病害在地理空间分布上呈现显著的空间正相关与空间集聚特性,且病害严重区与隧道周边水文地质环境密切相关。本文结果为隧道病害地理空间分布特征研究、认识病害分布规律及后期病害治理提供了有效依据。

关键词: 三维激光扫描, 隧道病害, 空间自相关, 集聚

Abstract: With the continuous construction and operation of subways, China is gradually entering the subway operation and maintenance period, and subway disease detection and operation and maintenance have gradually attracted people's attention. With the increase of subway operation years, the disease also shows an aggravating trend. Obtaining comprehensive information on tunnel diseases through 3D laser scanning technology, and using spatial autocorrelation to analyze the geospatial distribution characteristics of subway tunnel diseases is of great significance for understanding the mechanism of disease formation and disease prevention. Based on the horizontal convergence data obtained by 3D laser scanning of a subway tunnel, the spatial autocorrelation analysis method is used to quantitatively analyze the distribution characteristics of the disease in geographic space, and the relationship with the surrounding hydrogeological environment is analyzed. The results show that the geospatial distribution of tunnel diseases presents a significant positive spatial correlation and spatial agglomeration characteristics, and the serious disease area is closely related to the hydrogeological environment around the tunnel. This paper provides an effective basis for studying the characteristics of the geospatial distribution of tunnel diseases, understanding the law of disease distribution and later disease management.

Key words: 3D laser scanning, tunnel disease, spatial autocorrelation, agglomeration

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