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Structural Engineering and Mechanics Volume 29, Number 2, May30 2008 , pages 155-169 DOI: https://doi.org/10.12989/sem.2008.29.2.155 |
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A MOM-based algorithm for moving force identification: Part II . Experiment and comparative studies |
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Ling Yu, Tommy H.T. Chan and Jun-hua Zhu
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Abstract | ||
A MOM-based algorithm (MOMA) has been developed for moving force identification from dynamic responses of bridge in the companion paper. This paper further evaluates and investigates the properties of the developed MOMA by experiment in laboratory. A simply supported bridge model and a few vehicle models were designed and constructed in laboratory. A series of experiments have then been conducted for moving force identification. The bending moment and acceleration responses at several measurement stations of the bridge model are simultaneously measured when the model vehicle moves across the bridge deck at different speeds. In order to compare with the existing time domain method (TDM), the best method for moving force identification to date, a carefully comparative study scheme was planned and conducted, which includes considering the effect of a few main parameters, such as basis function terms, mode number involved in the identification calculation, measurement stations, executive CPU time, Nyquist fraction of digital filter, and two different solutions to the ill-posed system equation of moving force identification. It was observed that the MOMA has many good properties same as the TDM, but its CPU execution time is just less than one tenth of the TDM, which indicates an achievement in which the MOMA can be used directly for real-time analysis of moving force identification in field. | ||
Key Words | ||
moving force identification; method of moments (MOM); bridge loads; time domain method (TDM); dynamic responses. | ||
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 | ||