DOI QR코드

DOI QR Code

Robotized inspection and health monitoring in the Gran Sasso National Laboratory

  • Rinaldi, Cecilia (Department of Civil Architectural and Environmental Engineering, University of L'Aquila) ;
  • Di Sabatino, Umberto (Department of Civil Architectural and Environmental Engineering, University of L'Aquila) ;
  • Potenza, Francesco (Department of Engineering and Geology, University G. d'Annunzio of Chieti-Pescara) ;
  • Gattulli, Vincenzo (Department of Structural and Geotechnical Engineering, Sapienza University of Rome)
  • 투고 : 2020.05.02
  • 심사 : 2020.11.18
  • 발행 : 2021.03.25

초록

The Gran Sasso National Laboratory (LNGS) is the largest underground research center in the world devoted to neutrino and astroparticle physics. It is located in galleries below about 1400 meters of rock mass. In this environment, inspection and monitoring actions are challenging for the maintenance and the safety of the infrastructures and they require a combined use of different strategies. The paper address issues related to the structural safety of the whole environment by proposing solutions for inspection and monitoring of different areas and elements, such as the gallery vaults, the structures of the experimental prototypes, the plants and the machinery. A generic framework is discussed to evidence the features of each specific solution and the interaction between different systems. Tunnel structural healthy is the most difficult to evaluate because the vaults are coated by not removable panels which waterproof and insulate the environment. Therefore, specific solutions are proposed for the inspection and monitoring of the vaults which are visible only in the interspace realized from such cladding panels. In this respect, different methodologies based on the use of robotic systems are presented and discussed in order to implement a suitable inspection and monitoring program. The complementary requirements to perform a mechatronic survey are defined also as basis of ongoing activities currently performed in LNGS.

키워드

과제정보

The research leading to these results has received funding from the Italian Government under Cipe resolution no. 135 (Dec. 21, 2012), project INnovating City Planning through Information and Communication Technologies. This work is part of a project that has received funding from the Research Fund for Coal and Steel under grant agreement No 800687. The authors wish to thank Eng. Paolo Martella (Head of Design Service at LNGS) for the very useful technical information and documents on the Laboratories' infrastructures.

참고문헌

  1. Azadi, M. and Hosseini, S.M.M. (2010), "Analyses of the effect of seismic behaviour of shallow tunnels in liquefiable grounds", Tunn. Undergr. Sp. Tech., 25, 543-552. https://doi.org/10.1016/j.tust.2010.03.003
  2. Bremer, K., Wollweber, M., Weigand, F., Rahlves, M., Kuhne, M., Helbig, R. and Roth, B. (2016), "Fibre optic sensors for the structural health monitoring of building structures", Proc. Technol., 26, 524-529. https://doi.org/10.1016/j.protcy.2016.08.065
  3. Castellani, A., Canetta, G., Pace, S. and Guidotti, R. (2012), "The vaults of the Gran Sasso National Laboratory Halls, during the 2009 L'Aquila earthquake. Design of an earthquake-monitoring system", Gallerie e grandi opere sotterranee, 103, 61-75.
  4. Ceci, A.M., Gattulli, V. and Potenza, F. (2013), "Serviceability and damage scenario in irregular RC structures: post-earthquake observations and modelling predictions", J. Perform. Constr. Facil., 27(1), 98-115. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000317
  5. De Luca, G., Del Pezzo, E., Di Luccio, F., Margheriti, L., Milana, G. and Scarpa, R. (1998), "Site response study in Abruzzo (Central Italy): underground array versus surface stations", J. Seismol., 2, 223-236. https://doi.org/10.1023/A:1009786605055
  6. Di Murro, V., Pelecanos, L., Soga, K., Kechavarzi, C., Morton, R.F. and Scibile, L. (2019), "Long-term deformation monitoring of CERN concrete-lined tunnels using distributed fibre-optic sensing", J. Geotech. Eng., 50(2), 1-7.
  7. Domaneschi, M., Sigurdardottir, D. and Glisic, B. (2017), "Damage detection on output-only monitoring of dynamic curvature in composite decks", Struct. Monitor. Maint., Int. J., 4(1), 1-15. https://doi.org/10.12989/smm.2017.4.1.001
  8. Fujita, Y. and Hamamoto, Y. (2011), "A robust automatic crack detection method from noisy concrete surfaces", Mach. Vis. Appl., 22(2), 245-254. https://doi.org/10.1007/s00138-009-0244-5
  9. Gucunski, N., Kee, S., La, H., Basily, B. and Maher, A. (2015), "Delamination and concrete quality assessment of concrete bridge decks using a fully autonomous RABIT platform", Struct. Monitor. Maint., Int. J., 2(1), 19-34. https://doi.org/10.12989/smm.2015.2.1.019
  10. Gue, C.Y., Wilcock, M., Alhaddad, M.M., Elshafie, M.Z.E.B., Soga, K. and Mair, R.J. (2015), "The monitoring of an existing cast iron tunnel with distributed fiber optic sensing (DFOS)", J. Civil Struct., 5(5), 573-586. 1 https://doi.org/100.1007/s13349-015-0109-8
  11. Hashash, Y.M., Hook, J.J., Schmidt, B., John, I. and Yao, C. (2001), "Seismic design and analysis of underground structures", Tunn. Undergr. Sp. Tech., 16, 247-293. https://doi.org/10.1016/S0886-7798(01)00051-7
  12. Ho, S.C.M., Li, W., Wang, B. and Song, G. (2017), "A load measuring anchor plate for rock bolt using fiber optic sensor", Smart Mater. Struct., 26(5), 057003. https://doi.org/10.1088/1361-665X/aa6ae8
  13. Lunardi, P. (1990), "La ricerca e la tecnologia nella realizzazione di grandi cavita sotterranee: il laboratorio di fisica nucleare del Gran Sasso", Proceedings of International Conference "Se vogliamo il verde sopra utilizziamo lo spazio profondo", Milano, Italy.
  14. Merendez, E., Victores, J.G., Montero, R., Martinez, S. and Balaguer, C. (2018), "Tunnel structural inspection and assessment using an autonomous robotic system", Automat. Constr., 87, 117-126. https://doi.org/10.1016/j.autcon.2017.12.001
  15. Mohamad, H., Soga, K., Bennett, P.J., Mair, R.J. and Lim, C.S. (2012), "Monitoring twin tunnel interactions using distributed optical fibre strain measurement", J. Geotech. Geoenviron. Eng., 138(8), 957-967. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000656
  16. Mohan, A. and Poobal, S. (2018), "Crack detection using image processing: A critical review and analysis", Alex. Eng. J., 57(2), 787-798. https://doi.org/10.1016/j.aej.2017.01.020
  17. Montero, R., Victores, J.G., Martinez S., Jardon, A. and Balaguer, C. (2015), "Past, present and future of robotic tunnel inspection", Automat. Constr., 59, 99-112. https://doi.org/10.1016/j.autcon.2015.02.003
  18. Nakamura, S., Yamashita, A., Inoue, F., Inoue, D., Takahashi, Y., Kamimura, N. and Ueno, T. (2019), "Inspection test of a tunnel with an inspection vehicle for tunnel lining concrete", J. Robot. Mechatron. 31(6), 762-771. https://doi.org/10.20965/jrm.2019.p0762
  19. Ottaviano, E. and Rea, P. (2013), "Design and operation of a 2-DOF leg-wheel hybrid robot", Robotica, 31(8), 1319-1325. https://doi.org/10.1017/S0263574713000556
  20. Ottaviano, E., Rea, P. and Castelli, G. (2014), "THROO: a tracked hybrid rover to overpass obstacles", Adv. Robot., 28(10), 683-694. https://doi.org/10.1080/01691864.2014.891949
  21. Oya, T. and Okada, T. (2005), "Development of a steerable, wheel-type, in-pipe robot and its path planning", Adv. Robot., 19(6), 635-650. https://doi.org/10.1163/1568553054255646
  22. Phillips, S. and Narasimhan, S. (2019), "Automating data collection for robotic bridge inspections", J. Bridge Eng., 24(8), 04019075. https://doi.org/10.1061/(ASCE)BE.1943-5592.0001442
  23. Pines, D.J. and Bohorquez, F. (2006), "Challenges facing future micro-air-vehicle development", J. Aircr., 43(2), 290-305. https://doi.org/10.2514/1.4922
  24. Potenza, F. (2018), "Monitoring and maintenance of customized structures for underground environments: The case of Gran Sasso National Laboratory", In: Mechatronics for Cultural Heritage and Civil Engineering, 92, 357-373.
  25. Potenza, F. and Gattulli, V. (2011), "Gli spettri di risposta sismica nelle gallerie dei Laboratori Nazionali del Gran Sasso", Report Cerfis (centro di Ricerca e Formazione in Ingegneria Sismica), 1/2011. [In Italian]
  26. Potenza, F., Rinaldi, C., Ottaviano, E. and Gattulli, V. (2020), "A robotics and computer-aided procedure for defect evaluation in bridge inspection", J. Civil Struct. Health Monitor., 10, 471-484. https://doi.org/10.1007/s13349-020-00395-3
  27. Protopapadakis, E., Voulodimos, A., Doulamis, A., Doulamis, N. and Stathaki, T. (2019), "Automatic crack detection for tunnel inspection using deep learning and heuristic image post-processing", Appl. Intell., 49, 2793-2806. https://doi.org/10.1007/s10489-018-01396-y
  28. Rea, P. and Ottaviano, E. (2018), "Design and development of an Inspection Robotic System for indoor applications", Robot. Comput. Integr. Manuf., 49, 143-151. https://doi.org/10.1016/j.rcim.2017.06.005
  29. Romano, M., Ottaviano, E., Gonzalez-Rodriguez, A., Castillo-Garcia, F.J. and Rodriguez-Rosa, D.A.B. (2019), "Design and simulation of a wall-climbing drone for bridge inspection", ANCRiSST 2019 Procedia, 14th International Workshop on Advanced Smart Materials and Smart Structures Technology, Rome, Italy. (V. Gattulli, O. Bursi, D. Zonta Eds.)
  30. Sakagami, N., Yumoto, Y., Takebayashi, T. and Kawamura, S. (2019), "Development of dam inspection robot with negative pressure effect plate", J. Field Robot., 36, 1422-1435. https://doi.org/10.1002/rob.21911
  31. Santos, D., Heyneman, B., Kim, S., Esparza, N. and Cutkosky, M.R. (2008), "Gecko-inspired climbing behaviors on vertical and overhanging surfaces", Proceedings of IEEE International Conference on Robotics and Automation, Pasadena, Pasadena, CA, USA, May, pp. 1125-1131.
  32. Shi, Z.M., Liu, L., Peng, M., Liu, C.C., Tao, F.J. and Liu, C.S. (2018), "Non-destructive testing of full-length bonded rock bolts based on HHT signal analysis", J. Appl. Geophys., 151, 47-65. https://doi.org/10.1016/j.jappgeo.2018.02.001
  33. Silva, M.F., Machado, A.T. and Tar, J.K. (2008), "A survey of technologies for climbing robots adhesion to surfaces", Proceedings of 2008 IEEE International Conference on Computational Cybernetics, Stara Lesna, Slovakia, November, pp. 127-132.
  34. Song, G., Li, W., Wang, B. and Ho, S. (2017), "A review of rock bolt monitoring using smart sensors", Sensors, 17(4), 776. https://doi.org/10.3390/s17040776
  35. Unver, O., Uneri, A., Aydemir, A. and Sitti M. (2006), "Geckobot: A gecko inspired climbing robot using elastomer adhesives", Proceedings of 2006 IEEE International Conference on Robotics and Automation, Orlando, FL, USA, May, pp. 2329-2335.
  36. Victores, J.G., Martinez, S., Jardon, A. and Balaguer, C. (2011), "Robot-aided tunnel inspection and maintenance system by vision and proximity sensor integration", Automat. Constr., 20(5), 629-636. https://doi.org/10.1016/j.autcon.2010.12.005
  37. Wang, W.L., Wang, T.T., Su, J.J., Lin, C.H., Seng, C.R. and Huang, T.H. (2001), "Assessment of damage in mountain tunnels due to the Taiwan Chi-Chi Earthquake", Tunn. Undergr. Sp. Tech., 16, 133-150. https://doi.org/10.1016/S0886-7798(01)00047-5
  38. White, J., Hurlebaus, S., Shokouhi, P., Wittwer, A. and Wimsatt, A. (2014), "Noncontact techniques for monitoring of tunnel linings", Struct. Monitor. Maint., Int. J., 1(2), 197-211. https://doi.org/10.12989/smm.2014.1.2.197
  39. Yao, F., Shao, G., Tamaki, A., Yamada, H. and Kato, K. (1999), "Development of 3D-ultrasonic-sensor and its application to the construction of large-scale environment model", Proceeding of the 30th International Symposium on Robotics, Tokyo, Japan, pp. 305-310.
  40. Yao, F., Shao, G., Takaue, R. and Tamaki, A. (2003), "Automatic concrete tunnel inspection robot system", Adv. Robot., 17(4), 319-337. https://doi.org/10.1163/156855303765203029
  41. Yu, S.N., Jang, J.H. and Han, C.S. (2007), "Auto inspection system using a mobile robot for detecting concrete cracks in a tunnel", Automat. Constr., 16(3), 255-261. https://doi.org/10.1016/j.autcon.2006.05.003
  42. Yu, H., Zhu, H.P., Weng, S., Gao, F., Luo, H. and Ai, D.M. (2018), "Damage detection of subway tunnel lining through statistical pattern recognition", Struct. Monitor. Maint., Int. J., 5(2), 231-242. https://doi.org/10.12989/smm.2018.5.2.231
  43. Yun, H.-B., Park, S.-H., Mehdawi, N., Mokhtari, S., Chopra, M., Reddi, L.N. and Park, K.-T. (2014), "Monitoring for close proximity tunneling effects on an existing tunnel using principal component analysis technique with limited sensor data", Tunn. Undergr. Sp. Tech., 43, 398-412. https://doi.org/10.1016/j.tust.2014.06.003
  44. Zhou, L., Zhang, C., Ni, Y.Q. and Wang, C.Y. (2018), "Real-time condition assessment of railway tunnel deformation using an FBG-based monitoring system", Smart Struct. Syst., Int. J., 21(5), 537-548. https://doi.org/10.12989/sss.2018.21.5.537