Structural Monitoring and Maintenance

  • 제6권4호
  • /
  • Pages.317-346
  • /
  • 2019
  • /
  • 2288-6605(pISSN)
  • /
  • 2288-6613(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Pavement condition assessment through jointly estimated road roughness and vehicle parameters

  • Shereena, O.A. (Department of Civil Engineering, Indian Institute of Technology Madras) ;
  • Rao, B.N. (Department of Civil Engineering, Indian Institute of Technology Madras)
  • 투고 : 2019.05.14
  • 심사 : 2019.10.04
  • 발행 : 2019.12.25
⟨ 이전 논문 다음 논문 ⟩

초록

Performance assessment of pavements proves useful, in terms of handling the ride quality, controlling the travel time of vehicles and adequate maintenance of pavements. Roughness profiles provide a good measure of the deteriorating condition of the pavement. For the accurate estimates of pavement roughness from dynamic vehicle responses, vehicle parameters should be known accurately. Information on vehicle parameters is uncertain, due to the wear and tear over time. Hence, condition monitoring of pavement requires the identification of pavement roughness along with vehicle parameters. The present study proposes a scheme which estimates the roughness profile of the pavement with the use of accurate estimates of vehicle parameters computed in parallel. Pavement model used in this study is a two-layer Euler-Bernoulli beam resting on a nonlinear Pasternak foundation. The asphalt topping of the pavement in the top layer is modeled as viscoelastic, and the base course bottom layer is modeled as elastic. The viscoelastic response of the top layer is modeled with the help of the Burgers model. The vehicle model considered in this study is a half car model, fitted with accelerometers at specified points. The identification of the coupled system of vehicle-pavement interaction employs a coupled scheme of an unbiased minimum variance estimator and an optimization scheme. The partitioning of observed noisy quantities to be used in the two schemes is investigated in detail before the analysis. The unbiased minimum variance estimator (MVE) make use of a linear state-space formulation including roughness, to overcome the linearization difficulties as in conventional nonlinear filters. MVE gives estimates for the unknown input and fed into the optimization scheme to yield estimates of vehicle parameters. The issue of ill-posedness of the problem is dealt with by introducing a regularization equivalent term in the objective function, specifically where a large number of parameters are to be estimated. Effect of different objective functions is also studied. The outcome of this research is an overall measure of pavement condition.

키워드

참고문헌

  1. Agostinacchio, M., Ciampa, D. and Olita, S. (2014), "The vibrations induced by surface irregularities in road pavements-a $Matlab^{(R)}$ approach", Eur. T. Res.Rev., 6(3), 267.
  2. Alhasan, A., White, D.J. and De Brabanter, K. (2017), "Spatial pavement roughness from stationary laser scanning", Int. J. Pavement Eng., 18(1), 83-96. https://doi.org/10.1080/10298436.2015.1065403
  3. Au, F.T.K., Jiang, R.J. and Cheung, Y.K. (2004), "Parameter identification of vehicles moving on continuous bridges", J. Sound Vib., 269(1-2), 91-111. https://doi.org/10.1016/S0022-460X(03)00005-1
  4. Chen, T.C. and Lee, M.H. (2008), "Research on moving force estimation of the bridge structure using the adaptive input estimation method", J. Struct. Eng., 8, 20-208.
  5. Ding, H., Yang, Y., Chen, L.Q. and Yang, S.P. (2014), "Vibration of vehicle pavement coupled system based on a timoshenko beam on a nonlinear foundation", J.Sound Vib., 333(24), 6623-6636. https://doi.org/10.1016/j.jsv.2014.07.016
  6. Fauriat, W., Mattrand, C., Gayton, N., Beakou, A. and Cembrzynski, T. (2016), "Estimation of road profile variability from measured vehicle responses", Vehicle Syst. Dyn., 54(5), 585-605. https://doi.org/10.1080/00423114.2016.1145243
  7. Gillespie, T.D. and Sayers, M.W. (1985), "Measuring Road Roughness and its Effects on User Cost and Comfort: A Symposium", ASTM Int., 884.
  8. Gillespie, T.D., Karamihas, S.M., Cebon, D., Sayers, M.W., Nasim, M.A., Hansen, W. and Ehsan, N. (2004), "Effects of heavy vehicle characteristics on pavement response and performance", University of Michigan Transportation Research Institute, UMTRI-92-2.
  9. Gillijns, S. and DeMoor, B. (2007), "Unbiased minimum-variance input and state estimation for linear discrete time systems", Automatica, 43(1), 111-116. https://doi.org/10.1016/j.automatica.2006.08.002
  10. Green F. and Cebon D. (1994), "Dynamic responses of highway bridges to heavy vehicle loads", J. Sound Vib.,170, 51-78. https://doi.org/10.1006/jsvi.1994.1046
  11. Gonzalez, A., O'brien, E.J., Li, Y.Y. and Cashell, K. (2008), "The use of vehicle acceleration measurements to estimate road roughness", Vehicle Syst. Dyn., 46(6), 483-499. https://doi.org/10.1080/00423110701485050
  12. Haddar,M., Baslamisli, S.C., Chaari, R., Chaari, F. and Haddar,M. (2018), "Road profile identification with an algebraic estimator", Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, SAGE Publications Sage UK: London, England.
  13. Harris, N.K., Gonzalez, A., OBrien, E.J. and McGetrick, P. (2010), "Characterisation of pavement profile heights using accelerometer readings and a combinatorial optimisation technique", J. Sound Vib., 329(5), 497-508. https://doi.org/10.1016/j.jsv.2009.09.035
  14. Hoshiya, M. and Maruyama, O. (1987), "Identification of running load and beam system", J. Eng. Mech., 113(6), 813-824. https://doi.org/10.1061/(ASCE)0733-9399(1987)113:6(813)
  15. Krishnanunni, C.G., Raj, R.S., Nandan, D., Midhun, C.K., Sajith, A.S. and Ameen, M. (2019), "Sensitivity based damage detection algorithm for structures using vibration data", J. Civil Struct. Health Monit., 9(1), 137-151. https://doi.org/10.1007/s13349-018-0317-0
  16. Krishnanunni, C.G. and Rao, B.N. (2019), "Decoupled technique for dynamic response of vehicle-pavement systems", Eng. Struct., 191, 264-279. https://doi.org/10.1016/j.engstruct.2019.04.042
  17. Lalthlamuana, R. and Talukdar, S. (2015), "Obtaining vehicle parameters from bridge dynamic response: a combined semi-analytical and particle filtering approach", J. Modern T., 23(1), 50- 66. https://doi.org/10.1007/s40534-014-0065-8
  18. Law, S.S., Bu, J.Q., Zhu, X.Q. and Chan, S.L. (2004), "Vehicle axle loads identification using finite element method", Eng. Struct., 26(8), 1143-1153. https://doi.org/10.1016/j.engstruct.2004.03.017
  19. Li, S., Yang, S. and Chen, L. (2016), "Investigation on cornering brake stability of a heavy-duty vehicle based on a nonlinear three-directional coupled model", Appl. Math. Model., 40(13-14), 6310-6323. https://doi.org/10.1016/j.apm.2016.03.001
  20. Loizos, A. (2001), "A simplified application of fuzzy set theory for the evaluation of pavement roughness", Road & T. Res., 10(4), 21.
  21. Loizos, A. and Plati, C. (2002), "Road roughness measured by profilograph in relation to user's perception and the need for repair: A case study", International Conference on Pavement Evaluation.
  22. Lyons, R.G. (2004), Understanding digital signal processing, 3rd edition, Pearson Education India.
  23. Mejlun, L., Judycki, J. and Dolzycki B. (2017), "Comparison of elastic and viscoelastic analysis of asphalt pavement at high temperature", Procedia Eng., 172, 746-753. https://doi.org/10.1016/j.proeng.2017.02.095
  24. Sayers, M.W. and Karamihas, S.M. (1996), "Interpretation of road profile roughness data", University of Michigan Transportation Research Institute, UMTRI-96-19.
  25. Sayers, M.W. and Karamihas, S.M. (1998), The Little Book of Profiling, University of Michigan Transportation Research Institute.
  26. Snehasagar, G., Krishnanunni, C.G. and Rao, B.N. (2019), "Dynamics of vehicle-pavement system based on a viscoelastic Euler-Bernoulli beam model", Int. J. Pavement Eng., 1-14.
  27. Yang, S., Li, S. and Lu, Y. (2010), "Investigation on dynamical interaction between a heavy vehicle and road pavement", Vehicle Syst. Dyn., 48(8), 923-944. https://doi.org/10.1080/00423110903243166
  28. Yang, X.S. and Deb, S. (2009), "Cuckoo search via Levy flights", Proceedings of the 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC). IEEE.
  29. Yang, S., Chen, L. and Li, S. (2015), Dynamics of vehicle-road coupled system, Springer.
  30. Wang, H., Nagayama, T., Zhao, B. and Su, D. (2017), "Identification of moving vehicle parameters using bridge responses and estimated bridge pavement roughness", Eng. Struct., 153, 57-70. https://doi.org/10.1016/j.engstruct.2017.10.006
  31. Wei, W., Shaoyi, B., Lanchun, Z., Yongzhi, W. and Hui, Y. (2015), "1803. Pavement roughness identification research in time domain based on neural network", J. Vibroeng., 17(7).
  32. Wu, S.Q. and Law, S.S. (2011), "Vehicle axle load identification on bridge deck with irregular road surface profile", Eng. Struct., 33(2), 591-601. https://doi.org/10.1016/j.engstruct.2010.11.017