[1]中华人民共和国交通部.公路隧道养护技术规范:JTG H12—2015[S].北京:人民交通出版社股份有限公司,2015.
[2]王石磊,高岩,齐法琳,等.铁路运营隧道检测技术综述[J].交通运输工程学报,2020,20(5):17-19.
WANG Shilei,GAO Yan,QI Falin,et al.Overview of railway operation tunnel detection technology [J].Journal of Transportation Engineering,2020,20(5):17-19.
[3]王耀东,余祖俊,白彪,等.基于图像处理的地铁隧道裂缝识别算法研究[J].仪器仪表学报,2014,35(7):1489-1496.
WANG Yaodong,YU Zujun,BAI Biao,et al.Research on subway tunnel crack recognition algorithm based on image processing [J].Journal of Instrumentation,2014,35(7):1489-1496.
[4]毕俊,冯琰,顾星晔,等.三维激光扫描技术在地铁隧道收敛变形监测中的应用研究[J].测绘科学,2008(S2):14-15.
BI Jun,FENG Yan,GU Xingye,et al.Application of 3D laser scanning technology in subway tunnel convergence deformation monitoring [J].Surveying and Mapping Science,2008(S2):14-15.
[5]TAO R,SONG Y.An automatic traffic peak picking method based on max tree[C]// 2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE),IEEE,2020(10):1456-1459.
[6]CHENG L,PENG X,LI N,et al.Tunnel crack detection using coarse-to-fine region localization and edge detection[J].Wiley Interdisciplinary Reviews:Data Mining and Knowledge Discovery,2019,4(11):34-37.
[7]DAI C,JIANG K,WANG Q.Recognition of tunnel lining cracks based on digital image processing[J].Mathematical Problems in Engineering,2020,11(4):51-57.
[8]REN Y,JIANG H B,ZHANG C,et al.Image-based concrete crack detection in tunnels using deep fully convolutional networks[J].Construction and Building Materials,2011(10):97-101.
[9]LEI M,LIU L,SHI C,et al.A novel tunnel-lining crack recognition system based on digital image technology[J].Tunnelling and Underground Space Technology,2020,108:103724.
[10]HUANG H,CHENG W,ZHOU M,et al.Towards automated 3d inspection of water leakages in shield tunnel linings using mobile laser scanning data[J].Sensors,2020(13):23-29.
[11]HOANG N D,NGUYEN Q L.A novel method for asphalt pavement crack classification based on image processing and machine learning[J].Engineering With Computers,2018,17(6):9-15.
[12]鲜晴羽,仇文革,王泓颖,等.基于卷积神经网络的隧道掌子面图像质量评价方法研究[J].铁道科学与工程学报,2020,17(3):37-46.
XIAN Qingyu,QIU Wenge,WANG Hongying,et al.Research on image quality evaluation method of tunnel face based on convolutional Neural network [J].Journal of Railway Science and Engineering,2020,17(3):37-46.
[13]TAO R,SONG Y.Component tree computation of 2D Images[M].Beijing:2020.
[14]SALEMBIER P,LIESEGANG S,LOPEZ-MARTINEZ C.Ship detection in sar images based on maxtree representation and graph signal processing[J].IEEE Transactions on Geoscience and Remote Sensing,2018,6(5):1-16.
[15]NAJMAN L,COUPRIE M.Building the component tree in quasi-linear time[J].Transactions on Image Processing A Publication of the IEEE Signal Processing Society,2006,15(11):3531-3539.
[16]刘宇飞,樊健生.结构表面裂缝数字图像法识别研究综述与前景展望[J].土木工程学报,2021,54(6):79-98.
LIU Yufei,FAN Jiansheng.Review and prospect of structural surface crack recognition by digital image method [J].China Civil Engineering Journal,2021,54(6):79-98.
[17]张琨,陈定方.有监督学习下的市域铁路隧道结构裂缝边缘识别方法[J].中国机械工程,2021,32(4):446-453.
ZHANG Kun,CHEN Dingfang.Recognition method of crack edge of urban railway tunnel structure under supervised learning[J].China Mechanical Engineering,2021,32(4):446-453.
[18]周颖,刘彤.基于计算机视觉的混凝土裂缝识别[J].同济大学学报(自然科学版),2019,47(9):1277-1285.
ZHOU Ying,LIU Tong.Concrete crack identification based on computer vision [J].Journal of Tongji University (Natural Science),2019,47(9):1277-1285.
[19]韩晓健,赵志成.基于计算机视觉技术的结构表面裂缝检测方法研究[J].建筑结构学报,2018,39(S1):418-427.
HAN Xiaojian,ZHAO Zhicheng.Research on the detection method of structural surface cracks based on computer vision technology[J].Journal of Building Structures,2018,39(S1):418-427.
[1]田迎华,张旭.隧道施工生产安全网络平台系统的技术研究[J].中国安全生产科学技术,2010,6(5):97.
TIAN Ying-hua,ZHANG Xu.Study on network platform system technology of work safety in tunnel construction[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2010,6(6):97.