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Damage detection and quantitative analysis of shield tunnel structure

The damage of lining widely exists in metro shield tunnels, which may weaken the structural performance, affect the durability of the structure and even cause accidents. Investigation and evaluation of the lining damage is an essential work to reduce the risk grade during the service life of the str...

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Bibliographic Details
Published in:Automation in construction 2018-10, Vol.94, p.303-316
Main Authors: Huang, Zhen, Fu, Helin, Chen, Wei, Zhang, Jiabing, Huang, Hongwei
Format: Article
Language:English
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Summary:The damage of lining widely exists in metro shield tunnels, which may weaken the structural performance, affect the durability of the structure and even cause accidents. Investigation and evaluation of the lining damage is an essential work to reduce the risk grade during the service life of the structure. A rapid detection and analysis system has been applied in the shield tunnel of Metro Line 2 in Changsha, China for surveying the damage of lining. The system can obtain high definition image information of tunnel surface through multiple array CCD cameras at high speed, and use intelligent analysis method to identify and quantify the damage. The types, morphological characteristics and distribution characteristics of structural damages were analyzed based on the automatic detection results. The causes and the factors influencing the structural damages have been concluded. Finally, the existing problems and development prospects of metro tunnel structure management are discussed from the point of view of construction and maintenance. •Damage investigation by a rapid detection and intelligent analysis system in Changsha metro is taken as a case study.•The types and distribution characteristics of structural damages are investigated.•The causes and influencing factors of the damages are analyzed.•The existing problems and development trend of tunnel structure maintenance and management are discussed.
ISSN:0926-5805
1872-7891
DOI:10.1016/j.autcon.2018.07.006