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A structural health assessment method for shield tunnels based on torsional wave speed

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Abstract

Following recent rapid developments in tunnel engineering in China, the heavy structural maintenance work of the future is likely to pose a great challenge. Newly developed vibration-based health assessment and monitoring methods offer good prospects for large-scale structural monitoring, hidden surface detection and disease pre-judgment. However, because the dynamic properties of tunnels are sensitive to the coupling and damping effects of the surrounding soil, there is little relevant research on tunnel structures. Using the PiP (pipe in pipe) model, the intrinsic tunnel modes and their response characteristics are investigated in this paper, and the degree to which the identification of these characteristics is influenced by mode superposition and the soil coupling effect are also considered. The response features of these flexible wave modes are found to be barely recognizable in a tunnel-soil coupled system, while the phase velocity of the torsional wave can be determined by combining phase spectrum analysis and the HHT (Hilbert-Huang transformation) method. A new structural health assessment method based on the torsional wave speed is therefore proposed. In this method, the torsional wave speed is used to determine the tunnel structure’s global stiffness based on a newly developed dispersion algorithm. The calculated stiffness is then used to evaluate the tunnel’s structural service status. A field test was also carried out at a newly built tunnel to validate the proposed method; the tunnel structure’s Young’s modulus was obtained and was very close to the designed value. This indicates that this method is an effective way to assess tunnel service conditions, and also provides a theoretical basis for future applications to health assessment of shield tunnels.

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References

  1. Li J P, Wang R L, Yan J Y. Research on structural status of operating tunnel of metro in Shanghai and treatment ideas. In: Proceeding of the 6th International Symposium on Geotechnical Aspects of Underground Construction in Soft Ground, 2008. 315–320

    Google Scholar 

  2. Asakuraa T, Kojima Y. Tunnel maintenance in Japan. Tunn Undergr Sp Tech, 2003, 18: 161–169

    Article  Google Scholar 

  3. Xie X Y, Li P, Qin H, et al. GPR identification of voids inside concrete based on the support vector machine algorithm. J Geophys Eng, 2013, 10: 42–52

    Google Scholar 

  4. Lin M W, Abatan A O, Zhou Y. Transverse shear response monitoring of concrete cylinder using embedded high-sensitivity ETDR sen sor. In: Liu S C, ed. Smart Structures and Materials 2000: Smart Systems for Bridges, Structures, and Highways, Proceedings of SPIE, 2000. 368–378

    Google Scholar 

  5. Galvagni A, Cawley P. The reflection of guided waves from simple supports in pipes. J Acoust Soc AM, 2011, 129: 1869–1880

    Article  Google Scholar 

  6. Huthwaite P, Ribichini R, Cawley P, et al. Mode selection for corrosion detection in pipes and vessels via guided wave tomography. IEEE T Ultrason Ferr, 2013, 60: 1165–1177

    Article  Google Scholar 

  7. Wang J D, Zhou D, Liu W Q. Study on coupled vibration characteristics of a cylindrical container with multiple elastic annular baffles. Sci China Tech Sci, 2012, 55: 3292–3301

    Article  Google Scholar 

  8. Li A Q, Ding Y L, Wang H, et al. Analysis and assessment of bridge health monitoring mass data-progress in research/development of “Structural Health Monitoring”. Sci China Tech Sci, 2012, 55: 2212–2224

    Article  Google Scholar 

  9. Carden E P, Fanning P. Vibration-based condition monitoring: A review. Struct Health Monit, 2004, 3: 355–377

    Article  Google Scholar 

  10. Bhalla S, Yang Y W, Zhao J, et al. Structural health monitoring of underground facilities-Technological issues and challenges. Tunn Undergr Sp Tech, 2005, 20: 487–500

    Article  Google Scholar 

  11. Zhou B, Xie X Y, Yang Y B, et al. A novel vibration-based structure health monitoring approach for the shallow buried tunnel. CMES-Comp Model Eng, 2012, 86: 321–348

    Google Scholar 

  12. Liu W F, Liu W N, Gupta S, et al. A coupled periodic finite element-boundary element model for prediction of vibrations induced by metro traffic (in Chinese). J Vib Eng, 2009, 22: 480–485

    Google Scholar 

  13. Hwang R N, Lysmer J. Response of buried structures to traveling waves. J Geotech Eng, 1981, 107: 183–200

    Google Scholar 

  14. Clouteau D, Elhabre M L, Aubry D. Periodic BEM and FEM-BEM coupling-Application to seismic behaviour of very long structures. Comput Mech, 2000, 25: 567–577

    Article  MATH  Google Scholar 

  15. Yang Y B, Hung H H. A 2.5D finite/infinite element approach for modelling visco-elastic bodies subjected to moving loads. Int J Numer Meth Eng, 2001, 51: 1317–1336

    Article  MATH  Google Scholar 

  16. Gupta S, Degrande G, Lombaert G. Experimental validation of a numerical model for subway induced vibrations. J Sound Vib, 2009, 321: 786–812

    Article  Google Scholar 

  17. Forrest J A, Hunt H E M. A three-dimensional model for calculation of train-induced ground vibration. J Sound Vib, 2006, 294: 678–705

    Article  Google Scholar 

  18. Forrest J A, Hunt H E M. Ground vibration generated by trains in underground tunnels. J Sound Vib, 2006, 294 (4–5): 706–736

    Article  Google Scholar 

  19. Hussein M F M, Hunt H E M. A numerical model for calculating vibration from a railway tunnel embedded in a full-space. J Sound Vib, 2007, 305: 401–431

    Article  Google Scholar 

  20. Gupta S, Hussein M F M, Degrande G, et al. A comparison of two numerical models for the prediction of vibrations from underground railway traffic. Soil Dyn Earthq Eng, 2007, 27: 608–624

    Article  Google Scholar 

  21. Huang N E, Shen Z, Long S R, et al. The empirical modal decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proc R Soc Lond A, 1971, 454: 903–995

    MathSciNet  Google Scholar 

  22. Flandrin P, Rilling G, Goncalves P. Empirical mode decomposition as a filter bank. IEEE Signal Proc Let, 2004, 11: 112–114

    Article  Google Scholar 

  23. Bao C X, Hao H, Li Z X. Time-varying system identification using a newly improved HHT algorithm. Comput Struct, 2009, 87: 1611–1623

    Article  Google Scholar 

  24. Flügge W. Stresses in Shells. 2nd ed. Berlin: Springer, 1973

    Book  MATH  Google Scholar 

  25. Zhou W J, Ichchou M N, Bareille O. Finite element techniques for calculations of wave modes in one-dimensional structural waveguides. Struct Contrlo Hlth, 2011, 18: 737–751

    Article  Google Scholar 

  26. Sheng X, Jones C J C, Thompson D J. A theoretical study on the influence of the track on train-induced ground vibration. J Sound Vib, 2004, 272: 909–936

    Article  Google Scholar 

  27. AL-Hunaldi M O. Insights on the SASW nondestructive testing method. Can J Civil Eng, 1993, 20: 940–950

    Article  Google Scholar 

  28. Rilling G, Flandrin P, Goncalves P. On empirical modal decomposition and its algorithms. In: IEEE-EURASIP workshop on nonlinear signal and image processing NSIP-03, Grado (I), 2003

    Google Scholar 

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Authors and Affiliations

  1. Key Laboratory of Geotechnical & Underground Engineering, Ministry of Education, Tongji University, Shanghai, 200092, China

    Biao Zhou, XiongYao Xie & YongSheng Li

  2. Department of Geotechnical Engineering, Tongji University, Shanghai, 200092, China

    Biao Zhou, XiongYao Xie & YongSheng Li

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  1. Biao Zhou
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  2. XiongYao Xie
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  3. YongSheng Li
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Correspondence to XiongYao Xie.

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Zhou, B., Xie, X. & Li, Y. A structural health assessment method for shield tunnels based on torsional wave speed. Sci. China Technol. Sci. 57, 1109–1120 (2014). https://doi.org/10.1007/s11431-014-5554-9

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  • DOI: https://doi.org/10.1007/s11431-014-5554-9

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