Identification of vehicle axle loads from bridge responses using preconditioned least square QR-factorization algorithm

Chen, Zhen and Chan, Tommy H.T. and Nguyen, Andy and Yu, Ling (2019) Identification of vehicle axle loads from bridge responses using preconditioned least square QR-factorization algorithm. Mechanical Systems and Signal Processing, 128. pp. 479-496. ISSN 0888-3270

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Abstract

This paper develops a novel method for moving force identification (MFI) called preconditioned least square QR-factorization (PLSQR) method. The algorithm seeks to reduce the impact of identification errors caused by unknown noise. The biaxial moving forces travel on a simply supported bridge at three different speeds is used to generate numerical simulations to assess the effectiveness and applicability of the algorithm. Results indicate that the method is more robust towards ill-posed problem and has higher identification precision than the conventional time domain method (TDM). In addition, the robustness and ill-posed immunity of PLSQR are directly affected by two kinds of regularization parameters, namely, number of iterations j and regularization matrix L. Compared with the standard form of least square QR-factorization (LSQR), i.e., the regularization matrix L being the identity matrix I_n, the PLSQR with the optimal number of iterations j and regularization matrix L has many advantages on MFI and it is more suitable for field trials due to better adaptability with type of sensors and number of sensors.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Accepted version made available in accordance with the copyright policy of the publisher.
Faculty/School / Institute/Centre: Current - Institute for Advanced Engineering and Space Sciences - Centre for Future Materials
Date Deposited: 24 May 2019 00:49
Last Modified: 13 Jun 2019 02:57
Uncontrolled Keywords: moving force identification; preconditioned least square QR-factorization; time domain method; regularization parameter; preconditioner
Fields of Research : 09 Engineering > 0905 Civil Engineering > 090506 Structural Engineering
09 Engineering > 0913 Mechanical Engineering > 091304 Dynamics, Vibration and Vibration Control
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
Identification Number or DOI: 10.1016/j.ymssp.2019.03.043
URI: http://eprints.usq.edu.au/id/eprint/36305

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