基于机器视觉的隧道表观病害监测技术研究  

Research on Tunnel Apparent Disease Monitoring Technology Based on Machine Vision

作　　者：郭鸿雁 梁肖[2,3] 李科 景强[4] Guo Hongyan;Liang Xiao;Li Ke;Jing Qiang(School of Civil Engineering,Chongqing University,Chongqing 400044,P.R.China;China Merchants Chongqing Transportation Research and Design Institute Co.,Ltd.,Chongqing 400067,P.R.China;School of Civil Engineering,Chongqing Jiaotong University,Chongqing 400074,P.R.China;HZMB Administrative Authority,Zhuhai,Guangdong 519060,P.R.China)

机构地区：[1]重庆大学土木工程学院,重庆400044 [2]招商局重庆交通科研设计院有限公司,重庆400067 [3]重庆交通大学土木工程学院,重庆400074 [4]港珠澳大桥管理局,珠海519060

出　　处：《地下空间与工程学报》2023年第5期1633-1645,1664,共14页Chinese Journal of Underground Space and Engineering

基　　金：国家重点研发计划(2021YFC3002000);国家重点研发计划(2021YFC3002005);国家重点研发计划(2019YFB1600702)。

摘　　要：随着在役隧道运营年限的增长,会产生诸如裂缝、渗漏水等典型表观病害,影响隧道的安全运营。如何通过有效的技术手段识别出各种病害,并将结果反馈给养护单位显得尤为重要。通过调研国内外隧道病害检测技术与方法,分析利用机器视觉技术对隧道典型表观病害的测量原理,结合计算机技术,开发基于变焦摄像头的隧道典型表观病害智能监测系统,实现了对隧道衬砌表观病害的智能识别与监测,并利用标定板在实体隧道中模拟裂缝和渗漏水情况。经实验测试,该监测系统可实现对隧道病害7×24 h实时监测,隧道表观病害在拍摄环境优良情况下,识别率可达95%,监测裂缝最小宽度0.2 mm,最小渗漏水面积50 cm2。采用该系统,可实现多处、多类型病害的识别与全天候监测。As the number of years of operation of an in-service tunnel increases,typical apparent diseases such as cracks and water leakage,occurs,affecting the safe operation of the tunnels.How to identify various diseases through effective technical means and feedback the results to the maintenance unit is particularly important.Through the investigation of tunnel disease detection technologies and methods at home and abroad,the principle of using machine vision technology to measure typical apparent diseases of tunnels is analyzed.Combined with computer technology,an intelligent identification system for typical apparent diseases of tunnels based on zoom cameras is developed to realize the appearance of tunnel linings.Intelligent identification and monitoring of diseases,and the use of calibration plates to simulate cracks and water seepage in solid tunnels.After experimental tests,the monitoring system can realize 7×24 hours real-time monitoring of tunnel diseases.Under the condition of excellent shooting environment,the recognition rate of tunnel apparent diseases can reach 95%.The minimum width of monitoring cracks is 0.2mm,and the minimum leakage area is 50 cm2.That is to say,the system can realize the identification and allweather monitoring of multiple diseases in multiple locations and types.

关 键 词：公路隧道 机器视觉 裂缝识别 病害监测 图像处理 

分 类 号：TU96[建筑科学]