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Structural Engineering and Mechanics Volume 29, Number 2, May30 2008 , pages 135-154 DOI: https://doi.org/10.12989/sem.2008.29.2.135 |
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A MOM-based algorithm for moving force identification: Part I . Theory and numerical simulation |
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Ling Yu, Tommy H.T. Chan and Jun-hua Zhu
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| Abstract | ||
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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. | ||
| Key Words | ||
| moving force identification; method of moments (MOM); bridge-vehicle interaction; time domain method; legendre polynomials; fourier series. | ||
| Address | ||
| Ling Yu: Key Lab of Disaster Forecast and Control in Engineering, Ministry of Education of the People?s Republic of China (Jinan University), Guangzhou 510632, P. R. China Department of Civil and Structural Engineering, The Hong Kong Polytechnic University, Hong Kong, P. R. China Tommy H.T. Chan: School of Urban Development, Faculty of Built Environment & Engineering, Queensland University of Technology, GPO Box 2434, Queensland 4001, Australia Department of Civil and Structural Engineering, The Hong Kong Polytechnic University, Hong Kong, P. R. China Jun-hua Zhu: Key Lab of Disaster Forecast and Control in Engineering, Ministry of Education of the People?s Republic of China (Jinan University), Guangzhou 510632, P. R. China Changjiang River Scientific Research Institute, Wuhan 430010, P. R. China | ||