[1] 田四明,巩江峰.截至2019年底中国铁路隧道情况统计[J].隧道建设,2020,40(2):292-297. TIAN Si-ming, GONG Jiang-feng. Statistics of railway tunnels in China as of end of 2019[J]. Tunnel Construction, 2020, 40(2): 292-297.(in Chinese)
[2] 卢春房.高速铁路桥隧工程养修模式与关键技术[J].中国铁路,2017(7):1-8. LU Chun-fang. Maintenance and repair mode and technologies for high speed railway bridges and tunnels[J]. Chinese Railways, 2017(7): 1-8.(in Chinese)
[3] 中国铁路总公司运输局.铁路隧道现况[J].隧道建设,2015(6):534. Transportation Bureau of China Railway Corporation. Current situation of railway tunnel[J]. Tunnel Construction, 2015(6): 534.(in Chinese)
[4] 牛道安.铁路基础设施全寿命检测技术与发展[J].铁道建筑,2020,60(4):5-8,16. NIU Dao-an. Technology and development of railway infrastructure lifetime inspection[J]. Railway Engineering, 2020, 60(4): 5-8, 16.(in Chinese)
[5] 马伟斌,柴金飞.运营铁路隧道病害检测、监测、评估及整治技术发展现状[J].隧道建设,2019,39(10):1553-1562. MA Wei-bin, CHAI Jin-fei. Development status of disease detection, monitoring, evaluation and treatment technology of railway tunnels in operation[J]. Tunnel Construction, 2019, 39(10): 1553-1562.(in Chinese)
[6] 肖广智.从当前铁路隧道衬砌典型病害谈设计施工改进措施[J].隧道建设,2018,38(9):1416-1422. XIAO Guang-zhi. Discussion on design and construction improvement measures based on current typical diseases of railway tunnel lining[J]. Tunnel Construction, 2018, 38(9): 1416-1422.(in Chinese)
[7] SASAMA H, UKAI M, OHTA M, et al. Inspection system for railway facilities using a continuously scanned image[J]. Electrical Engineering in Japan, 1998, 125(2): 52-64.
[8] STENT S, GHERARDI R, STENGER B, et al. Visual change detection on tunnel linings[J]. Machine Vision and Applications, 2016, 27(3): 319-330.
[9] 宮田信裕.赤外線·CCD カメラを搭載したトンネル検査車と画像処理技術[J].コンクリート工学,2000,38(1):79-80. MIYATA N. Tunnel inspection vehicle equipped with infrared/CCD camera and image processing technology[J]. Concrete Engineering, 2000, 38(1): 79-80.(in Japanese)
[10] MONTERO R, VICTORES J G, MARTINEZ S, et al. Past, present and future of robotic tunnel inspection[J]. Automation in Construction, 2015, 59: 99-112.
[11] FUJINO Y, SIRINGORINGO D M. Recent research and development programs for infrastructures maintenance, renovation and management in Japan[J]. Structure and Infrastructure Engineering, 2020, 16(1): 3-25.
[12] TABRIZI K, CELAYA M, MILLER B S, et al. Damage assessment of tunnel lining by mobile laser scanning: Pittsburgh, Pennsylvania, implementation phase of FHWA SHRP 2 R06G Project[J]. Transportation Research Record, 2017(2642): 166-179.
[13] 李健超,张翠兵,柴雪松,等.基于图像识别技术的隧道衬砌裂缝检测系统研究[J].铁道建筑,2018,58(1):20-24. LI Jian-chao, ZHANG Chui-bing, CHAI Xue-song, et al. Research on crack detection system of tunnel lining based on image recognition technology[J]. Railway Engineering, 2018, 58(1): 20-24.(in Chinese)
[14] HUANG Hong-wei, SUN Yan, XUE Ya-dong, et al. Inspection equipment study for subway tunnel defects by grey-scale image processing[J]. Advanced Engineering Informatics, 2017, 32: 188-201.
[15] 王平让,黄宏伟,薛亚东.隧道衬砌裂缝自动检测性能影响因素模型试验研究[J].岩石力学与工程学报,2012,31(8):1705-1714. WANG Ping-rang, HUANG Hong-wei, XUE Ya-dong. Model test study of factors affecting automatic detection performance of cracks in tunnel lining[J]. Chinese Journal of Rock Mechanics and Engineering, 2012, 31(8): 1705-1714.(in Chinese)
[16] 李庆桐,黄宏伟,薛亚东,等.隧道衬砌图像清晰度影响因素的模型试验研究[J].岩石力学与工程学报,2017,36(增2):3915-3926. LI Qing-tong, HUANG Hong-wei, XUE Ya-dong, et al. Model test study on factors affecting image sharpness of tunnel lining[J]. Chinese Journal of Rock Mechanics and Engineering, 2017, 36(S2): 3915-3926.(in Chinese)
[17] 豆海涛,黄宏伟,薛亚东.隧道渗漏水红外辐射特征模型试验及图像处理[J].岩石力学与工程学报,2011,30(增2):3386-3391. DOU Hai-tao, HUANG Hong-wei, XUE Ya-dong. Model test on infrared radiation feature of tunnel seepage and image processing[J]. Chinese Journal of Rock Mechanics and Engineering, 2011, 30(S2): 3386-3391.(in Chinese)
[18] ATTARD L, DEBONO C J, VALENTINO G, et al. Tunnel inspection using photogrammetric techniques and image processing: areview[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2018, 144: 180-188.
[19] UKAI M. Development of image processing technique for detection of tunnel wall deformation using continuously scanned image[J]. Quarterly Report of RTRI, 2000, 41(3): 120-126.
[20] 刘学增,叶 康.隧道衬砌裂缝的远距离图像测量技术[J].同济大学学报(自然科学版),2012,40(6):829-836. LIU Xue-zeng, YE Kang. A long-distance image measuring technique for crack on tunnel lining[J]. Journal of Tongji University(Natural Science), 2012, 40(6): 829-836.(in Chinese)
[21] 王 睿,漆泰岳,胡 燊,等.隧道衬砌裂缝检测中的背景处理和断点连接算法[J].应用基础与工程科学学报,2017,25(4):742-750. WANG Rui, QI Tai-yue, HU Shen, et al. Background processing of tunnel lining crack detection and breakpoint connection algorithm[J]. Journal of Basic Science and Engineering, 2017, 25(4): 742-750.(in Chinese)
[22] 王平让,黄宏伟,薛亚东.基于图像局部网格特征的隧道衬砌裂缝自动识别[J].岩石力学与工程学报,2012,31(5):991-999. WANG Ping-rang, HUANG Hong-wei, XUE Ya-dong. Automatic recognition of cracks in tunnel lining based on characteristics of local grids in images[J]. Chinese Journal of Rock Mechanics and Engineering, 2012, 31(5): 991-999.(in Chinese)
[23] 蒲炳荣,漆泰岳,黄晓东,等.隧道衬砌分岔裂缝特征提取研究[J].铁道标准设计,2019,63(10):135-141. PU Bing-rong, QI Tai-yue, HUANG Xiao-dong, et al. Study on characteristics extraction of bifurcated crack of tunnel lining[J]. Railway Standard Design, 2019, 63(10): 135-141.(in Chinese)
[24] 黄宏伟,孙 龑,薛亚东.基于机器视觉的隧道衬砌表面病害检测技术研究进展[J].现代隧道技术,2014,51(增1):19-31. HUANG Hong-wei,SUN Yan,XUE Ya-dong. Research progress of machine vision based disease detecting techniques for the tunnel lining surface[J]. Modern Tunneling Technology, 2014, 51(S1): 19-31.(in Chinese)
[25] MAKANTASIS K, PROTOPAPADAKIS E, DOULAMIS A, et al. Deep convolutional neural networks for efficient vision based tunnel inspection[C]∥IEEE. 2015 IEEE International Conference on Intelligent Computer Communication and Processing(ICCP). New York: IEEE, 2015: 335-342.
[26] CHA Y J, CHOI W, BÜYÜKÖZTÜRK O. Deep learning-based crack damage detection using convolutional neural networks[J]. Computer-Aided Civil and Infrastructure Engineering, 2017, 32(5): 361-378.
[27] 薛亚东,李宜城.基于深度学习的盾构隧道衬砌病害识别方法[J].湖南大学学报(自然科学版),2018,45(3):100-109. XUE Ya-dong, LI Yi-cheng. A method of disease recognition for shield tunnel lining based on deep learning[J]. Journal of Hunan University(Natural Sciences), 2018, 45(3): 100-109.(in Chinese)
[28] 黄宏伟,李庆桐.基于深度学习的盾构隧道渗漏水病害图像识别[J].岩石力学与工程学报,2017,36(12):2861-2871. HUANG Hong-wei, LI Qing-tong. Water leakage image recognition of shield tunnel by deep learning[J]. Chinese Journal of Rock Mechanics and Engineering, 2017, 36(12): 2861-2871.(in Chinese)
[29] HUANG Hong-wei, LI Qing-tong, ZHANG Dong-ming. Deep learning based image recognition for crack and leakage defects of metro shield tunnel[J]. Tunnelling and Underground Space Technology, 2018, 77: 166-176.
[30] 柴雪松,朱兴永,李健超,等.基于深度卷积神经网络的隧道衬砌裂缝识别算法[J].铁道建筑,2018,58(6):60-65. CHAI Xue-song, ZHU Xing-yong, LI Jian-chao, et al. Tunnel lining crack identification algorithm based on deep convolutional neural network[J]. Railway Engineering, 2018, 58(6): 60-65.(in Chinese)
[31] WIMSATT A, WHITE J, LEUNG C, et al. Mapping voids, debonding, delamination, moisture, and other defects behind or within tunnel linings[R].Washington DC:Transportation Research Board, 2013.
[32] 松沼政明,鈴木尊.電磁波レーダを用いたトンネル覆工検査車の検証[J].建設の施工企画,2011(736):34-38. MATSUNUMA M, SUZUKI T. Verification of tunnel lining inspection car using electromagnetic radar[J].Construction Project, 2011(736): 34-38.(in Japanese)
[33] 齐法琳,黎国清,江 波.铁路隧道状态检查车的研制及应用[J].中国铁路,2013(9):75-77,99. QI Fa-lin, LI Guo-qing, JIANG Bo. Development and application of railway tunnel state inspection vehicle[J]. Chinese Railways, 2013(9): 75-77, 99.(in Chinese)
[34] ZAN Yue-wen, LI Zhi-lin, SU Guo-feng, et al. An innovative vehicle-mounted GPR technique for fast and efficient monitoring of tunnel lining structural conditions[J]. Case Studies in Nondestructive Testing and Evaluation, 2016, 6:63-69.
[35] 昝月稳,苏国锋,魏文涛,等.高铁隧道车载探地雷达检测技术及其应用[J].现代隧道技术,2018,55(增2):1288-1294. ZAN Yue-wen, SU Guo-feng, WEI Wen-tao, et al. Detection technology of the vehicle-mounted GPR and its application in high-speed railway tunnels[J]. Modern Tunneling Technology, 2018, 55(S2): 1288-1294.(in Chinese)
[36] 杨艳青,贺少辉,江 波,等.铁路隧道整体式衬砌地质雷达检测模拟试验研究[J].铁道学报,2012,34(9):93-98. YANG Yan-qing, HE Shao-hui, JIANG Bo, et al. Simulation test of GPR detection of integral lining of railway tunnel[J]. Journal of the China Railway Society, 2012, 34(9): 93-98.(in Chinese)
[37] 徐 俊.地下工程结构多类型缺陷的雷达信号自动辨识方法与工程应用[D].北京:北京科技大学,2019. XU Jun. GPR signal automatic identification method and engineering application for multi-type defects in underground structures[D]. Beijing: University of Science and Technology Beijing, 2019.(in Chinese)
[38] 徐 辉.基于深度学习的隧道衬砌病害GPR探测智能反演与识别方法[D].济南:山东大学,2019. XU Hui. Tunnel lining diseases GPR detection intelligent inversion and identification methods based on deep learning[D]. Jinan: Shandong University, 2019.(in Chinese)
[39] LALAGÜE A, LEBENS M A, HOFF I, et al. Detection of rockfall on a tunnel concrete lining with ground-penetrating radar(GPR)[J]. Rock Mechanics and Rock Engineering, 2016, 49(7): 2811-2823.
[40] 安田亨,山本秀樹,北澤隆一.時速50 km·h-1 でトンネル空洞探査: 高速走行型非接触レーダーによるトンネル覆工巻厚·空洞探査を実現:MIMM-R(ミーム-アール)[J].建設機械施工,2014,66(12):51-56. YASUDA T, YAMAMOTO H, KITAZAWA R. Tunnel cavity exploration at 50 km·h-1: realization of tunnel lining thickness and cavity exploration by high speed non-contact radar[J]. Construction Machine, 2014, 66(12): 51-56.(in Japanese)
[41] XU Xian-lei, XIA Tian, VENKATACHALAM A S, et al. Development of high-speed ultrawideband ground-penetrating radar for rebar detection[J]. Journal of Engineering Mechanics, 2013, 139(3): 272-285.
[42] 尹 德,叶盛波,刘晋伟,等.一种用于高速公路探地雷达的新型时域超宽带TEM喇叭天线[J].雷达学报,2017,6(6):611-618. YIN De, YE Sheng-bo, LIU Jin-wei, et al. Novel time-domain ultra-wide band tem horn antenna for highway GPR applications[J]. Journal of Radars, 2017, 6(6): 611-618.(in Chinese)
[43] 苏国锋.车载GPR检测高铁隧道的试验研究[D].成都:西南交通大学,2017. SU Guo-feng. Experimental study on vehicle-mounted GPR monitoring high-speed railway tunnel[D]. Chengdu: Southwest Jiaotong University, 2017.(in Chinese)
[44] 熊洪强.车载GPR数据合成孔径聚焦成像技术研究[D].成都:西南交通大学,2018. XIONG Hong-qiang. Research on synthetic aperture focusing imaging technique of the vehicle-mounted GPR data[D]. Chengdu: Southwest Jiaotong University, 2018.(in Chinese)
[45] LEI Yang, TIAN Tian. The vibration characteristic and impact analysis of the tunnel lining detection device based on arc rotating multi-section mechanism[J]. Advances in Mechanical Engineering, 2020, 12(4): 1-18.
[46] 川上幸一,小西真治,篠原秀明,等.赤外線熱計測による地下鉄覆工コンクリートの浮き検出方法の検討とその応用[J].土木学会論文集 F1(トンネル工学),2018,74(1):25-39. KAWAKAMI K, KONISHI S, SHINOHARAH, et al. Infrared thermometry application to the detection of voidin the subway tunnel lining surface[J]. Journal of Japan Society of Civil Engineers F1(Tunnel Engineering), 2018, 74(1): 25-39.(in Japanese)
[47] KURAHASHI S, MIKAMI K, KITAMURA T, et al. Demonstration of 25 Hz inspection speed laser remote sensing for internal concrete defects[J]. Journal of Applied Remote Sensing, 2018, 12(1): 1-11.
[48] 水口尚司,大西有三,徳田浩一郎,等.道路トンネル走行型計測車両におけるひび割れ精度検証の報告[J].土木学会論文集 F2(地下空間研究),2017,73(1):1-10. MIZUGUCHI T, OHNISHI Y, TOKUDA K,et al. Inspection of the crack measurement of the road tunnel by mobile imaging technology[J]. Journal of Japan Society of Civil Engineers F2(Underground Space Research), 2017, 73(1): 1-10.(in Japanese)
[49] 水口尚司,大西有三, 西山哲,等.道路トンネルにおける画像及びレーザデータを用いたマネジメント手法の研究[J].土木学会論文集 F2(地下空間研究),2015,71(1):20-30. MIZUGUCHI T, OHNISHI Y, NISHIYAMA S, et al. Research of maintenance of road tunnel by MIMM[J]. Journal of Japan Society of Civil Engineers F2(Underground Space Research), 2015, 71(1): 20-30.(in Japanese)
[50] 段培勇,薛 峰,谢锦妹,等.激光扫描技术在铁路限界检测中的应用研究[J].铁道建筑,2013(8):89-92. DUAN Pei-yong, XUE Feng, XIE Jin-mei, et al. Research on the application of laser scanning technology in railway gauge inspection[J]. Railway Engineering, 2013(8): 89-92.(in Chinese)
[51] 杜兆宇.移动三维激光扫描系统在铁路限界测量中的应用研究[J].测绘通报,2019(增2):185-187. DU Zhao-yu. Application research of mobile 3D laser scanning system in railway limit measurement[J]. Bulletin of Surveying and Mapping, 2019(S2): 185-187.(in Chinese)
[52] AI Qing, YUAN Yong, BI Xiang-li. Acquiring sectional profile of metro tunnels using charge-coupled device cameras[J]. Structure and Infrastructure Engineering, 2016, 12(9): 1065-1075.
[53] ZHAN Dong, YU Long, XIAO Jian, et al. Multi-camera and structured-light vision system(MSVS)for dynamic high-accuracy 3D measurements of railway tunnels[J]. Sensors, 2015(15): 8664-8684.
[54] 王雪梅,倪文波.铁路轨道几何参数捷联惯性测量基准的建立[J].西南交通大学学报,2012,47(3):355-360. WANG Xue-mei, NI Wen-bo. Measurement foundation of railway track geometrical parameters based on strapdown inertial technique[J]. Journal of Southwest Jiaotong University, 2012, 47(3): 355-360.(in Chinese)
[55] 李 盛,胡文彬,杨 燕,等.基于光纤陀螺的大跨桥梁连续线形检测技术研究[J].桥梁建设,2014,44(5):69-74. LI Sheng, HU Wen-bin, YANG Yan, et al. Research of fog-based measurement technique for continuous curve modes of long span bridge[J]. Bridge Construction, 2014, 44(5): 69-74.(in Chinese)
[56] GAN Wei-bing, HU Wen-bin, LIU Fang, et al. Bridge continuous deformation measurement technology based on fiber optic gyro[J]. Photonic Sensors, 2016, 6(1): 71-77.
[57] 高橋英二,迫田尚和,朝日賢一,等.高精細高速画像処理カメラによるトンネル形状自動計測装置[J].計測自動制御学会論文集,2012,48(12):863-871. EIJI T, NAOKAZU S, KENICHI A, et al. Three dimensional profile measurement system for tunnel surface using 1.3 mega-pixels high speed image processing camera[J]. Journal of Control, Measurement, and System Integration, 2012, 48(12): 863-871.(in Japanese)
[58] MENENDEZ E, VICTORES J G, MONTERO R, et al. Tunnel structural inspection and assessment using an autonomous robotic system[J]. Automation in Construction, 2018, 87: 117-126.