DOI QR코드

DOI QR Code

A MOM-based algorithm for moving force identification: Part I - Theory and numerical simulation

  • Yu, Ling (Key Lab of Disaster Forecast and Control in Engineering, Ministry of Education of the People's Republic of China (Jinan University), Department of Civil and Structural Engineering, The Hong Kong Polytechnic University) ;
  • Chan, Tommy H.T. (School of Urban Development, Faculty of Built Environment & Engineering, Queensland University of Technology, Department of Civil and Structural Engineering, The Hong Kong Polytechnic University) ;
  • Zhu, Jun-Hua (Key Lab of Disaster Forecast and Control in Engineering, Ministry of Education of the People's Republic of China (Jinan University), Changjiang River Scientific Research Institute)
  • 투고 : 2006.08.30
  • 심사 : 2007.08.07
  • 발행 : 2008.05.30

초록

The moving vehicle loads on a bridge deck is one of the most important live loads of bridges. They should be understood, monitored and controlled before the bridge design as well as when the bridge is open for traffic. A MOM-based algorithm (MOMA) is proposed for identifying the timevarying moving vehicle loads from the responses of bridge deck in this paper. It aims at an acceptable solution to the ill-conditioning problem that often exists in the inverse problem of moving force identification. The moving vehicle loads are described as a combination of whole basis functions, such as orthogonal Legendre polynomials or Fourier series, and further estimated by solving the new system equations developed with the basis functions. A number of responses have been combined, some numerical simulations on single axle, two axle and multiple-axle loads, being either constant or timevarying, have been carried out and compared with the existing time domain method (TDM) in this paper. The illustrated results show that the MOMA has higher identification accuracy and robust noise immunity as well as producing an acceptable solution to ill-conditioning cases to some extent when it is used to identify the moving force from bridge responses.

키워드

참고문헌

  1. Busby, H.R. and Trujillo, D.M. (1997), "Optimal regularization of an inverse dynamic problem", Comput. Struct., 63(2), 243-248 https://doi.org/10.1016/S0045-7949(96)00340-9
  2. Cantineni, R. (1992), "Dynamic behaviour of highway bridges under the passage of heavy vehicles", Swiss Federal Laboratories for Materials Testing and Research (EMPA) Report No. 220, 240
  3. Chan, T.H.T. and O'Conner, C. (1990), "Wheel loads from highway bridge strains: Field studies", J. Struct. Eng., ASCE, 116(7), 1751-1771 https://doi.org/10.1061/(ASCE)0733-9445(1990)116:7(1751)
  4. Chan, T.H.T., Yu, L. and Law, S.S. and Yung, T.H. (2001), "Moving Force Identification Studies II: Comparative Studies", J. Sound Vib., 247(1), 77-95 https://doi.org/10.1006/jsvi.2001.3629
  5. Chan, T.H.T., Yu, L., Law, S.S. and Yung, T.H. (2001), "Moving Force Identification Studies I: Theory", J. Sound Vib., 247(1), 59-76 https://doi.org/10.1006/jsvi.2001.3630
  6. Fast and efficient algorithms in computational electromagnetics. Chew W.C., Jin J.M. Michielssen E., Song J. Eds. Artech House. Norwood. MA, 2001
  7. Harriington, R.F. (1968), Field Computation by Moment Methods. New York: Macmillan
  8. Heywood, R.J. (1994), "Influence of truck suspensions on the dynamic response of a short span bridge", Int. J. Vehicle Des
  9. Jorgensen, E., Volakis, J.L., Meincke, P. and Breinbjerg, O. (2004), "Higher order hierarchical Legendre basis functions for electromagnetic modeling", IEEE T. Antenn. Propag., 52(11), 2985-2995 https://doi.org/10.1109/TAP.2004.835279
  10. Law, S.S., Chan, T.H.T. and Zeng, Q.H. (1997), "Moving force identification: A time domain method", J. Sound Vib., 201(1), 1-22 https://doi.org/10.1006/jsvi.1996.0774
  11. Law, S.S., Chan, T.H.T., Zhu, X.Q. and Zeng, Q.H. (2001), "Regularization in moving force identification", J. Eng. Mech., ASCE, 127(2), 136-148 https://doi.org/10.1061/(ASCE)0733-9399(2001)127:2(136)
  12. Liao, S.X. and Pawlak, M. (1996), "On image analysis by moments", IEEE T. Pattern Anal., 18(3), 254-266 https://doi.org/10.1109/34.485554
  13. Lindfield, G. and Penny, J. (1995), Numerical Method using Matlab. London: Ellis Horwood Limit
  14. Pawlak, M. (1992), "On the reconstruction aspects of moment descriptors", IEEE T. Inform. Theory, 38(6), 1698-1708 https://doi.org/10.1109/18.165444
  15. Peters, R.J. (1984), "A system to obtain vehicle axle weights", Proc. of 12th ARRB Conf., 12, 10-18
  16. Peters, R.J. (1986), "An unmanned and undetectable highway speed vehicle weighing system", Proc. of 13th ARRB and 5th REAAA Combined Conf. Part 6, 70-83
  17. Poularikas, A.D. (1999), Legendre Polynomial. In. The Handbook of Formulas and Tables for Signal Processing. Ed. Alexander D. Poularikas. Boca Raton: CRC Press LLC
  18. Qjidaa, H. and Radouane, L. (1999), "Robust line fitting in a noisy image by the method of moments", IEEE T. Pattern Anal., 21(11), 1216-1223 https://doi.org/10.1109/34.809115
  19. Santantamarina, J.C. and Fratta, D. (1998), "Introduction to discrete signals and inverse problems in civil engineering", ASCE, Reston. Va., 200-238
  20. Tikhonov, A.N. and Arsenin, V.Y. (1977), Solution of Ill-posed Problems. Wiley. New York
  21. Ting, E.C. and Yener, M. (1983), "Vehicle-structure interaction in bridge dynamic", Shock Vib. Dig., 15(2), 3-9
  22. Yu, L. (2002), "Accounting for bridge dynamic loads using moving force identification system (MFIS)", Hong Kong: The Hong Kong Polytechnic University

피인용 문헌

  1. Recent developments in inverse problems of vehicle–bridge interaction dynamics vol.6, pp.1, 2016, https://doi.org/10.1007/s13349-016-0155-x
  2. A MOM-based algorithm for moving force identification: Part II - Experiment and comparative studies vol.29, pp.2, 2008, https://doi.org/10.12989/sem.2008.29.2.155
  3. Moving train loads and parameters identification on a steel truss girder model vol.15, pp.1, 2015, https://doi.org/10.1007/s13296-015-3012-6
  4. Numerical study on moving train parameter identification system through a simply supported bridge vol.26, pp.9, 2012, https://doi.org/10.1007/s12206-012-0720-0
  5. A truncated generalized singular value decomposition algorithm for moving force identification with ill-posed problems vol.401, 2017, https://doi.org/10.1016/j.jsv.2017.05.004
  6. Experimental Study on Moving Train Loads Identification from Bridge Responses vol.143-144, pp.1662-8985, 2010, https://doi.org/10.4028/www.scientific.net/AMR.143-144.32
  7. Multi-Axle Moving Train Loads Identification by Using Fuzzy Pattern Recognition Technique vol.29-32, pp.1662-7482, 2010, https://doi.org/10.4028/www.scientific.net/AMM.29-32.1307
  8. Multi-Axle Moving Train Loads Identification on Continuous Bridge from Bridge Displacement Responses vol.239-240, pp.1662-7482, 2012, https://doi.org/10.4028/www.scientific.net/AMM.239-240.670
  9. A new conjugate gradient algorithm for solving dynamic load identification vol.64, pp.2, 2008, https://doi.org/10.12989/sem.2017.64.2.271
  10. A sparse self-estimated sensor-network for reconstructing moving vehicle forces vol.28, pp.8, 2008, https://doi.org/10.1088/1361-665x/ab28ed
  11. Onsite Identification of Moving Vehicle Loads on Multispan Continuous Bridge Using Both Dictionary Expansion and Sparse Regularization vol.34, pp.3, 2008, https://doi.org/10.1061/(asce)as.1943-5525.0001258