Tunnel infrastructure health management: A state-of-the-art review on defect development mechanism and robot-aided inspection system

Yujing Jiang , Zhutian Pan , Xuepeng Zhang

Smart Underground Engineering ›› 2025, Vol. 1 ›› Issue (1) : 26 -39.

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Smart Underground Engineering ›› 2025, Vol. 1 ›› Issue (1) : 26 -39. DOI: 10.1016/j.sue.2025.05.003
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Tunnel infrastructure health management: A state-of-the-art review on defect development mechanism and robot-aided inspection system

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Abstract

Underground structures are subjected to progressive structural deterioration over their lifespans. This poses a significant challenge to the operational safety. Accurate classification and subsequent in-depth root cause analysis can contribute to the optimization of operational efficiency, informed decision-making, and proactive prevention. This study investigated the defect development mechanism using chain rules for the classification of tunnel defects. Six common non-destructive testing methods and advanced robotic inspection systems were reviewed for their ability to facilitate rapid and accurate defect detection. Finally, the current challenges in tunnel infrastructure health management are presented, and future prospects are suggested.

Keywords

Tunnel / Lining defect / Development mechanism / Intelligent inspection robot

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Yujing Jiang, Zhutian Pan, Xuepeng Zhang. Tunnel infrastructure health management: A state-of-the-art review on defect development mechanism and robot-aided inspection system. Smart Underground Engineering, 2025, 1(1): 26-39 DOI:10.1016/j.sue.2025.05.003

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CRediT authorship contribution statement

Yujing Jiang: Writing -review & editing, Methodology, Formal analysis, Conceptualization. Zhutian Pan: Writing -original draft, Resources, Investigation. Xuepeng Zhang: Writing -review & editing, Resources, Methodology, Funding acquisition.

Declaration of competing interest

Yujing Jiang is an Editorial Board Member for this journal, and was not involved in the editorial review or the decision to publish this article. All authors declare that there are no competing interests.

Acknowledgements

This study was funded by the Program for the Youth Innovative Research Team in the Universities of Shandong Province (2024KJH065).

References

[1]

Y. Jiang, L. Wang, B. Zhang, X. Dai, J. Ye, B. Sun, N. Liu, Z. Wang, Y. Zhao, Tunnel lining detection and retrofitting, Autom. Constr. 152 (2023) 104881, doi: 10.1016/j.autcon.2023.104881.

[2]

E. Menendez, J.G. Victores, R. Montero, S. Martínez, C. Balaguer, Tunnel structural inspection and assessment using an autonomous robotic system, Autom. Constr. 87 (2018) 117-126, doi: 10.1016/j.autcon.2017.12.001.

[3]

Y. Yuan, Y. Bai, J. Liu, Assessment service state of tunnel structure, Tunn. Undergr. Space Technol. 27 (2012) 72-85, doi: 10.1016/j.tust.2011.07.002.

[4]

H. Yi, T. Qi, W. Qian, B. Lei, B. Pu, Y. Yu, Y. Liu, Z. Li, Influence of long-term dynamic load induced by high-speed trains on the accumulative deformation of shallow buried tunnel linings, Tunn. Undergr. Space Technol. 84 (2019) 166-176, doi: 10.1016/j.tust.2018.11.005.

[5]

X. Han, K. Gao, F. Ye, X. Han, Time-variant probabilistic random degradation model on flexural capacity of road tunnel linings, Struct. Infrastruct. Eng. 17 (2021) 1175-1193, doi: 10.1080/15732479.2020.1801766.

[6]

G. Yao, Loess tunnel lining cracking analysis and monitoring system research, in: The 1st International Conference on Transportation Infrastructure and Materials (ICTIM 2016), DEStech Publishing, Xi’an, China, 2016, pp. 760-766.

[7]

D.M. Zhang, L.X. Ma, J. Zhang, P.Y. Hicher, C.H. Juang, Ground and tunnel re-sponses induced by partial leakage in saturated clay with anisotropic permeability, Eng. Geol. 189 (2015) 104-115, doi: 10.1016/j.enggeo.2015.02.005.

[8]

H. Zi, Z. Ding, X. Ji, Z. Liu, C. Shi, Effect of voids on the seismic vul-nerability of mountain tunnels, Soil Dyn. Earthq. Eng. 148 (2021) 106833, doi: 10.1016/j.soildyn.2021.106833.

[9]

M.L. Sun, H.W. Liang, Y.Q. Zhu, X.Q. Gao, H. Liu, Z.G. Zhu, Deformation and failure mode analysis of the tunnel structure based on the tunnel-related landslides cases, Front. Earth Sci. 10 (2022) 906884, doi: 10.3389/feart.2022.906884.

[10]

C. Liu, D. Zhang, S. Zhang, Characteristics and treatment measures of lining dam-age: a case study on a mountain tunnel, Eng. Fail. Anal. 128 (2021) 105595, doi: 10.1016/j.engfailanal.2021.105595.

[11]

J.X. Yan, Achievements and challenges of tunneling technology in China over past 40 years, Tunn. Constr. 39 (2019) 537-544, doi: 10.3973/i.issn.2096-4498.2019.04.002.

[12]

X. Ding, Q. Huang, H. Zhu, H. Hu, Z. Liu, Subway tunnel disease associations min-ing based on fault tree analysis algorithm, Math. Probl. Eng. 1 (2017) 2621493, 10.1155/2017/2621493.

[13]

H. Mashimo, T. Ishimura, State of the art and future prospect of maintenance and operation of road tunnel, in: 23th International Symposium on Automation and Robotics in Construction ISARC, IAARC, Tokyo, Japan, 2006, pp. 299-302.

[14]

F.W. Wang, S.W. Liang, A.J. Feng, Statistics and development analysis of urban rail transit in China in 2022, Tunn. Constr. 43 (2023) 521, doi: 10.3973/j.issn.2096-4498.2024.02.018.

[15]

H. Ding, S.Q. Deng, S. Liu, W.F. Li, J.T. Chen, Advances in oper-ation resilience of highway tunnels, Tunn. Constr. 44 (2024) 1723, doi: 10.3973/j.issn.2096-4498.2024.09.001.

[16]

B.Q. Wang, H.J. Chen, L. Guo, P. Gao, Z.L. Ma, Development and application of tunnel structure intelligent comprehensive inspection equipment, Tunn. Constr. 44 (2024) 467, doi: 10.3973/j.issn.2096-4498.2024.S1.050.

[17]

J. Huang, D.L. Zhang, W.H. Liang, F. Dong, A. Li, Research status of safety control technology for tunnel structures during service period, Railw. Stand. Des. 68 (2024) 1-21, doi: 10.13238/j.issn.1004-2954.202402020003.

[18]

Y. Jiang, X. Zhang, T. Taniguchi, Quantitative condition inspection and assessment of tunnel lining, Autom. Constr. 102 (2019) 258-269, doi: 10.1016/j.autcon.2019.03.001.

[19]

Y. Jiang, X. Zhang, Research on automatic detection and health assessment of tunnel lining, Tunn. Constr. 41 (2021) 341, doi: 10.3973/j.issn.2096-4498.2021.03.001.

[20]

H. Huang, Y. Sun, Y. Xue, F. Wang, Inspection equipment study for subway tun-nel defects by grey-scale image processing, Adv. Eng. Inform. 32 (2017) 188-201, doi: 10.1016/j.aei.2017.03.003.

[21]

H.W. Huang, Q.T. Li, D.M. Zhang, Deep learning based image recognition for crack and leakage defects of metro shield tunnel, Tunn. Undergr. Space Technol. 77 (2018) 166-176, doi: 10.1016/j.tust.2018.04.002.

[22]

T. Yasuda, H. Yamamoto, R. Kitazawa, Cavity detection behind tunnel lining using non-contact radar at 50km/h, Constr. Mach. Constr. 66 (2014) 51-56.

[23]

J. Chen, D. Zhang, H. Huang, M. Shadabfar, M. Zhou, T. Yang, Image-based segmen-tation and quantification of weak interlayers in rock tunnel face via deep learning, Autom. Constr. 120 (2020) 103371, doi: 10.1016/j.autcon.2020.103371.

[24]

H. Liu, Y. Yue, Y. Lian, X. Meng, Y. Du, J. Cui, Reverse-time migration of GPR data for imaging cavities behind a reinforced shield tunnel, Tunn. Undergr. Space Technol. 146 (2024) 105649, doi: 10.1016/j.tust.2024.105649.

[25]

K. Shinri, M. Katsuhiro, K. Toshiyuki, H. Noboru, O. Hajime, K. Shuji, N. Masaharu, K. Tetsuya, S. Yoshiori, Yoshiori, Recent research and development programs for infrastruc-tures maintenance, renovation and management in Japan. J. Appl. Remote Sens. 12 (2018) 1, doi: 10.1117/1.JRS.12.015009.

[26]

M. Ammar, T. Zayed, O. Moselhi, Fuzzy-based life-cycle cost model for deci-sion making under subjectivity, J. Constr. Eng. Manag. 139 (2013) 556-563, doi: 10.1061/(ASCE)CO.1943-7862.0000576.

[27]

T. Asakura, Y. Sato, Damage to mountain tunnels in hazard area, Soils Found. 36 (1996) 301-310, doi: 10.3208/sandf.36.Special_301.

[28]

A. Inokuma, S. Inano, Road tunnels in Japan: deterioration and coun-termeasures, Tunn. Undergr. Space Technol. 11 (1996) 305-309, doi: 10.1016/0886-7798(96)00026-0.

[29]

Japan Ministry of Land, Annual report on railway, Infrastructure, Transport and Tourism2017 https://www.mlit.go.jp/tetudo/tetudo_tk6_000032.html.

[30]

X. Zhang, Y. Jiang, S. Sugimoto, Seismic damage assessment of moun-tain tunnel: a case study on the Tawarayama tunnel due to the 2016 Ku-mamoto Earthquake, Tunn. Undergr. Space Technol. 71 (2018) 138-148, doi: 10.1016/j.tust.2017.07.019.

[31]

Z. Chen, C. Shi, T. Li, Y. Yuan, Damage characteristics and influence factors of mountain tunnels under strong earthquakes, Nat. Haz. 61 (2012) 387-401, doi: 10.1007/s11069-011-9924-3.

[32]

H. Wang, X. Liu, N. Li, D.W. Xie, Safety evaluation of tunnel lining with longitudinal cracks and reinforcement design, Chin. J. Rock Mech. Eng. 29 (2010) 2651-2656.

[33]

T.T. Wang, Y.C. Chiu, K.J. Li, Index for assessing spalling in tunnel lining based on displacement monitoring and crack mapping, Tunn. Undergr. Space Technol. 153 (2024) 105975, doi: 10.1016/j.tust.2024.105975.

[34]

C. Gong, M. Cheng, Y. Ge, J. Song, Z. Zhou, Leakage mechanisms of an operational underwater shield tunnel and countermeasures: a case study, Tunn. Undergr. Space Technol. 152 (2024) 105892, doi: 10.1016/j.tust.2024.105892.

[35]

Z. Wang, B. Gao, Y. Jiang, S. Yuan, Yuan, Investigation and assessment on mountain tunnels and geotechnical damage after the Wenchuan earthquake, Sci. China, Ser. E: Technol. Sci. 52 (2009) 546-558, doi: 10.1007/s11431-009-0054-z.

[36]

Z. Chen, C. Shi, T. Li, Y. Yuan, Damage characteristics and influence factors of mountain tunnels under strong earthquakes, Nat. Haz. 61 (2012) 387-401, doi: 10.1007/s11069-011-9924-3.

[37]

W. Ding, Y. Wu, P. Xu, K. Hu, Research on the mechanism of frost heaves caused by void water accumulation behind the lining of high-speed railway tunnels in cold regions, Appl. Sci. 14 (2) (2024) 750, 10.3390/app14020750.

[38]

D. Zhang, T. Liu, Y. Shao, Weathering carbonation behavior of concrete sub-ject to early-age carbonation curing, J. Mater. Civil Eng. 32 (2020) 04020038, doi: 10.1061/(ASCE)MT.1943-5533.0003087.

[39]

Z. Li, H. Jin, S. Yu, Investigation of corrosion rate and rust expansion form of seg-ment reinforcement for shield tunnel by combined action of soil loading, chloride ion and stray current, Sustainability 13 (2021) 3444, 10.3390/su13063444.

[40]

B. Wang, A. Belarbi, M. Dawood, R. Kahraman, Corrosion behavior of corrosion-resistant steel reinforcements in normal-strength and high-performance con-crete: large-scale column tests and analysis, ACI Mater. J. 119 (2022), doi: 10.14359/51735975.

[41]

W. Lin, P. Li, X. Xie, A novel detection and assessment method for operational defects of pipe jacking tunnel based on 3D longitudinal deformation curve: a case study, Sensors. 22 (2022) 7648, 10.3390/s22197648.

[42]

M. Sun, H. Liang, Y. Zhu, X. Gao, H. Liu, Z. Zhu, Deformation and failure mode analysis of the tunnel structure based on the tunnel-related landslides cases, Front. Earth Sci. 10 (2022) 906884, doi: 10.3389/feart.2022.906884.

[43]

A. Ibrahim, S. Abdelkhalek, T. Zayed, A.H. Qureshi, E.Mohammed Abdelkader, A comprehensive review of the key deterioration factors of concrete bridge decks, Buildings. 14 (2024) 3425, 10.3390/buildings14113425.

[44]

P. Xu, Y. Wu, L. Huang, K. Zhang, Study on the progressive deterioration of tun-nel lining structures in cold regions experiencing freeze-thaw cycles, Appl. Sci. 11 (2021) 5903, 10.3390/app11135903.

[45]

Z. Lv, M. Wu, F. Huang, Y. Cai, Analytical solution of mechanical response in cold region tunnels under transversely isotropic freeze-thaw circle induced by unidirectional freeze-thaw damage, Front. Earth Sci. 10 (2022) 1016605, doi: 10.3389/feart.2022.1016605.

[46]

D. Liu, W. Zhang, Y. Jian, Y. Tang, K. Cao, Damage precursors of sulfate erosion concrete based on acoustic emission multifractal characteristics and b-value, Con-str. Build. Mater. 419 (2024) 135380, doi: 10.1016/j.conbuildmat.2024.135380.

[47]

J. Tong, L. Xiang, Y. Cai, M. Wang, P. Ye, X. Miao, A study on the sulfate erosion de-terioration law and damage model of shotcrete in high geothermal tunnels, Struct. Concr. 25 (2024) 3993-4011, doi: 10.1002/suco.202301117.

[48]

C. Butscher, S. Scheidler, H. Farhadian, H. Dresmann, P. Huggenberger, Swelling potential of clay-sulfate rocks in tunneling in complex geological settings and im-pact of hydraulic measures assessed by 3D groundwater modeling, Eng. Geol. 221 (2017) 143-153, doi: 10.1016/j.enggeo.2017.03.010.

[49]

W. Liu, S. He, Dynamic simulation of a mountain disaster chain: land-slides, barrier lakes, and outburst floods, Nat. Haz. 90 (2018) 757-775, doi: 10.1007/s11069-017-3073-2.

[50]

F. Gao, K. Zhou, X. Chen, X. Luo, Disaster chains induced by mining and chain-cut-ting disaster mitigation technology, Disaster Adv. 5 (2012) 971-975.

[51]

Y. Wang, Z. Shu, Y. Li, Research of slope disaster chain-stage and evolvement rules, IOP Conference Series:Earth and Environmental Science, IOP Publishing, Chengdu, China, 2020.

[52]

Z. Huang, L. Peng, S. Li, W. Wu, F. Liu, Determining geo-disaster chains probabil-ities and disaster mitigation mode: a meta-analytical perspective, Ecol. Ind. 163 (2024) 112074, doi: 10.1016/j.ecolind.2024.112074.

[53]

D. Zhan, L. Yu, J. Xiao, T. Chen, Multi-camera and structured-light vision system (MSVS) for dynamic high-accuracy 3D measurements of railway tunnels, Sensors. 15 (2015) 8664-8684, doi: 10.3390/s150408664.

[54]

N.P. Avdelidis, A. Moropoulou, Applications of infrared thermography for the investigation of historic structures, J. Cult. Herit. 5 (2004) 119-127, doi: 10.1016/j.culher.2003.07.002.

[55]

X. Xie, C. Zeng, Non-destructive evaluation of shield tunnel condition using GPR and 3D laser scanning, in: 2012 14th International Conference on Ground Pene-trating Radar (GPR), IEEE, Shanghai, China, 2012, pp. 479-484.

[56]

J. Hugenschmidt, R. Mastrangelo, GPR inspection of concrete bridges, Cem. Concr. Compos. 28 (2006) 384-392, doi: 10.1016/j.cemconcomp.2006.02.016.

[57]

E. Yahaghi, A. Movafeghi, N. Mohmmadzadeh, Enhanced radiographic imaging of defects in aircraft structure materials with the dehazing method, Nondestruct. Test. Eval. 30 (2015) 138-146, doi: 10.1080/10589759.2015.1018254.

[58]

J. Lee, K. Kim, M. Kang, E.S. Hong, S. Choi, Void detection for tun-nel lining backfill using impact-echo method based on continuous wavelet transform and convolutional neural network, Geomech. Eng. 36 (2024) 1-8, doi: 10.12989/gae.2024.36.1.001.

[59]

D.S. Xu, Y.M. Zhao, H.B. Liu, H.H. Zhu, Deformation monitoring of metro tunnel with a new ultrasonic-based system, Sensors 17 (2017) 1758, 10.3390/s17081758.

[60]

Y. Wang, G. Li, L. Zhou, R. Wang, Optimization of tunnel grouting detection tech-nology based on ultrasonic phased array, Meas. Sci. Technol. 35 (2024) 086126, 10.1088/1361-6501/ad3f37.

[61]

N. Miyata, Tunnel inspection vehicle equipped with infrared/CCD cam-era and image processing technology, Concr. Eng. 38 (2000) 79-80, doi: 10.3151/coj1975.38.1_79.

[62]

J.H. Wang, Q.Y. Xie, J. Liu, A. Koizumi, Research on diseases and cur-rent situation of operation maintenance management of Japanese rail-way tunnels and suggestions, Tunn. Constr. 40 (2020) 1824-1833, doi: 10.3973/j.issn.2096-4498.2020.12.018.

[63]

R. Montero, J.G. Victores, S. Martinez, A. Jardón, C. Balaguer, Past, present and future of robotic tunnel inspection, Autom. Constr. 59 (2015) 99-112 (2015), doi: 10.1016/j.autcon.2015.02.003.

[64]

S. Stent, R. Gherardi, B. Stenger, K. Soga, R. Cipolla, Visual change detection on tun-nel linings, Mach. Vis. Appl. 27 (2016) 319-330, doi: 10.1007/s00138-014-0648-8.

[65]

T. Yasuda, H. Yamamoto, Y. Shigeta, Tunnel inspection system by using high-speed mobile 3D survey vehicle: MIMM-R, J. Robot. Soc. Japan. 34 (2016) 589-590.

[66]

T. Yasuda, H. Yamamoto, M. Enomoto, Y. Nitta, Smart tunnel inspection and as-sessment using mobile inspection vehicle, non-contact radar and AI,in:37th In-ternational Symposium on Automation and Robotics in Construction, IAARC, Ki-takyushu, Japan, 2020, pp. 1373-1379.

[67]

Y. Wang, Z.L. An, W.B. Ma, Z.F. Zheng, X.X. Guo, State-of-art and development trend of tunnel inspection technology in China, Japan, and South, Korea, Tunn. Constr. 42 (2022) 1135, doi: 10.3973/j.issn.2096-4498.2022.07.002.

[68]

K. Loupos, A. Amditis, C. Stentoumis, P. Chrobocinski, J. Victores, M. Wietek, R. Lopez, Robotic intelligent vision and control for tunnel inspection and eval-uation-the ROBINSPECT EC project, in: 2014 IEEE International Symposium on Robotic and Sensors Environments (ROSE) Proceedings, IEEE, Timi șoara, Roma-nia, 2014, pp. 72-77.

[69]

K. Tabrizi, M. Celaya, B.S. Miller, A. Wittwer, L. Ruzzi, Damage assessment of tunnel lining by mobile laser scanning: Pittsburgh, Pennsylvania, implementation phase of FHWA SHRP 2 R06G project, Transport. Res. Rec. 2642 (2017) 166-179.

[70]

Y. Jiang, X. Zhang, T. Taniguchi, Quantitative condition inspection and assessment of tunnel lining, Autom. Constr. 102 (2019) 258-269, doi: 10.1016/j.autcon.2019.03.001.

[71]

J. Liao, Y. Yue, D. Zhang, W. Tu, R. Cao, Q. Zou, Q. Li, Automatic tunnel crack inspection using an efficient mobile imaging module and a lightweight CNN, IEEE Trans. Intell. Transp. Syst. 23 (2022) 15190-15203, doi: 10.1109/TITS.2021.3138428.

[72]

C. Liu, Y. Liu, Y. Chen, C. Zhao, J. Qiu, D. Wu, K. Tang, A state-of-the-practice review of three-dimensional laser scanning technology for tun-nel distress monitoring, J. Perform. Construct. Facil. 37 (2023) 03123001, doi: 10.1061/JPCFEV.CFENG-4205.

[73]

H. Huang, W. Cheng, M. Zhou, J. Chen, S. Zhao, Towards automated 3D inspection of water leakages in shield tunnel linings using mobile laser scanning data, Sensors 20 (2020) 6669, 10.3390/s20226669.

[74]

G. Song, Y. Huang, Z. Wang, Q. Feng, F. Jia, S. Wang, Review of railway operation tunnel inspection system and condition assessment method, Acta Polytech. Hungar. 21 (2024).

[75]

L. Attard, C.J. Debono, G. Valentino, M. Di Castro, Tunnel inspection using pho-togrammetric techniques and image processing: A review, ISPRS J. Photogramm. Remote Sens. 144 (2018) 180-188, doi: 10.1016/j.isprsjprs.2018.07.010.

[76]

S. Zhao, D.M. Zhang, H.W. Huang, Deep learning-based image instance segmenta-tion for moisture marks of shield tunnel lining, Tunn. Undergr. Space Technol. 95 (2020) 103156 https://doi.org/10.1016/j.tust.2019.103156.

[77]

H. Huang, Y. Sun, Y. Xue, F. Wang, Inspection equipment study for subway tun-nel defects by grey-scale image processing, Adv. Eng. Inform. 32 (2017) 188-201, doi: 10.1016/j.aei.2017.03.003.

[78]

R. Montero, J.G. Victores, S. Martinez, A. Jardón, C. Balaguer, Past, present and future of robotic tunnel inspection, Autom. Constr. 59 (2015) 99-112, doi: 10.1016/j.autcon.2015.02.003.

[79]

Y. Li, H. Li, H. Wang, Pixel-wise crack detection using deep local pattern predictor for robot application, Sensors. 18 (2018) 3042, 10.3390/s18093042.

[80]

M. Soilán, A. Sánchez-Rodríguez, P. del Río-Barral, C. Perez-Collazo, P. Arias, B. Riveiro, Review of laser scanning technologies and their applications for road and railway infrastructure monitoring, Infrastructures. 4 (2019) 58, 10.3390/in-frastructures4040058.

[81]

CORDIS-EU research results, AutoScan. https://cordis.europa.eu/project/rcn/ 203338/factsheet/en/, (accessed 20 February 2025).

[82]

I. Puente, H. González-Jorge, J. Martínez-Sánchez, P. Arias, Review of mo-bile mapping and surveying technologies, Measurement 46 (2013) 2127-2145, doi: 10.1016/j.measurement.2013.03.006.

[83]

L. Ma, Y. Li, J. Li, C. Wang, R. Wang, M.A. Chapman, Mobile laser scanned point-clouds for road object detection and extraction: a review, Rem. Sens. 10 (2018) 1531, 10.3390/rs10101531.

[84]

H. Cui, X. Ren, Q. Mao, Q. Hu, W. Wang, Shield subway tunnel deformation detection based on mobile laser scanning, Autom.Constr. 16 (2019) 102889 https://doi.org/10.1016/j.autcon.2019.102889.

[85]

M. Kubo, I. Amano, S. Nakayama, Development and application of concrete inspec-tion and diagnostic analysis system with infrared and visible images, Concr. J. 52 (2014), doi: 10.3151/coj.52.644.

[86]

M. Solla, V. Pérez-Gracia, S. Fontul, A review of GPR application on transport infrastructures: troubleshooting and best practices, Rem. Sens. 13 (2021) 672, 10.3390/rs13040672.

[87]

W.W.L. Lai, X. Derobert, P. Annan, A review of Ground Penetrating Radar appli-cation in civil engineering: a 30-year journey from locating and testing to imaging and diagnosis, NDT & E Int. 96 (2018) 58-78.

[88]

Y. Lei, B. Jiang, G. Su, Y. Zou, F. Qi, B. Li, Q. Qu, Application of air-coupled ground penetrating radar based on FK filtering and BP migration in high-speed railway tunnel detection, Sensors 23 (2023) 4343, 10.3390/s23094343.

[89]

T. Dawood, Z. Zhu, T. Zayed, Deterioration mapping in subway infrastruc-ture using sensory data of GPR, Tunn. Undergr. Sp. Tech 103 (2020) 103487, doi: 10.1016/j.tust.2020.103487.

[90]

X. Liu, M. Fang, D. Wu, Y. Li, X. Liu, G. Li, Status and development of rapid detection technology for tunnel structural defeets, Tunn. Constr. 45 (2025) 657, doi: 10.3973/j.issn.2096-4498.2025.04.001.

[91]

S. Kurahashi, Y. Shimada, O. Kotyaev, T. Norimatsu, Y. Kono, S. Nakata, M. Ishii, Measurement of depth of surface cracks in concrete by laser ultrasonic technique with multichannel detector, in: AIP Conference Proceedings, American Institute of Physics, Denver, Colorado, USA, 2013, pp. 317-323.

[92]

Y. Gao, Y. Jiang, B. Li, Voids delineation behind tunnel lining based on the vi-bration intensity of microtremors, Tunn. Undergr. Sp. Tech. 51 (2016) 338-345, doi: 10.1016/j.tust.2015.10.032.

[93]

Y. Gao, Y. Jiang, B. Li, Estimation of effect of voids on frequency response of mountain tunnel lining based on microtremor method, Tunn. Undergr. Sp. Tech 42 (2014) 184-194, doi: 10.1016/j.tust.2014.03.004.

[94]

X. Zhang, B. Li, Y. Jiang, F. Wu, Y. Gao, Ambient vibration-based quantitative assessment on tunnel lining defect using laser Doppler vibrometer, Measurement 239 (2025) 115481, doi: 10.1016/j.measurement.2024.115481.

[95]

H. Sun, Z. Xu, L. Yao, R. Zhong, L. Du, H. Wu, Tunnel monitoring and measuring system using mobile laser scanning: design and deployment, Rem. Sens. 12 (2020) 730, 10.3390/rs12040730.

[96]

N. Yasuda, N. Misaki, Y. Shimada, O. Kotyaev, Applicability of non-contact inspec-tion using laser ablation-induced vibration in a reinforced concrete tunnel lining, Tunn. Undergr. Sp. Tech. 113 (2021) 103977, doi: 10.1016/j.tust.2021.103977.

[97]

Y. Wang, G. Li, L. Zhou, R. Wang, Optimization of tunnel grouting detection tech-nology based on ultrasonic phased array, Meas. Sci. Tech. 35 (8) (2024) 086126, 10.1088/1361-6501/ad3f37.

[98]

K. Mori, S. Tokuomi, Remote hammering test of structures by water jet, J. Inst. Electr. Eng. Jpn. 139 (2019) 292-295, doi: 10.1541/ieejjournal.139.292.

[99]

C.J.O. Salaan, Y. Okada, S. Mizutani, T. Ishii, K. Koura, K. Ohno, S. Tadokoro, Close visual bridge inspection using a UAV with a passive rotating spherical shell, J. Fld. Robot. 35 (2018) 850-867, doi: 10.1002/rob.21781.

[100]

D. Chen, A tunnel detection method based on wall-climbing robot device, Railw. Eng. (5) (2017) 79-82, doi: 10.3969/i.issn.1003-1995.2017.05.22.

[101]

T. Nakamura, T. Fujimoto, H. Okada, T. Shimizu, S. Ikemoto, A. Wada, T. Miyamoto, Multirotor for hammering test with wall adhesion based on uni-versal vacuum gripper, Trans. Soc. Inst. Control Eng. 54 (2018) 440-446, doi: 10.9746/sicetr.54.440.

[102]

S. Huang, Z. Wu, Z. Ren, H.J. Liu, Y. Gui, Review of electric power intelligent inspection robot, Electr. Meas. Instrum. 57 (2020) 26-38, doi: 10.19753/j.issn1001-1390.2020.002.005.

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