Structural Engineering and Mechanics

  • 제29권2호
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  • Pages.135-154
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  • 2008
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  • 1225-4568(pISSN)
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  • 1598-6217(eISSN)
테크노프레스 (Techno-Press)
권호 표지
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
⟨ 이전 논문 다음 논문 ⟩

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

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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