Title: Research on moving load identification based on measured acceleration and strain signals

Authors: Yun Zhou; Sai Zhou; Lu Deng; Songbai Chen; Weijian Yi

Addresses: Key Laboratory for Damage Diagnosis of Engineering Structures of Hunan Province, Hunan University, Changsha, Hunan, 410082, China; College of Civil Engineering, Hunan University, Changsha, Hunan, 410082, China ' Key Laboratory of Building Safety and Energy Efficiency of the Ministry of Education, College of Civil Engineering, Hunan University, Changsha, Hunan, 410082, China ' Key Laboratory for Damage Diagnosis of Engineering Structures of Hunan Province, Hunan University, Changsha, Hunan, 410082, China ' Hunan Provincial Key Laboratory of Green Advanced Civil, Engineering Materials and Application Technology, College of Civil Engineering, Hunan University, Changsha, Hunan, 410082, China ' College of Civil Engineering, Hunan University, Changsha, Hunan, 410082, China

Abstract: Moving load identification from the dynamic responses of bridges is a typical inverse problem that is solved to estimate vehicle axle loads in motion from observed data. To reduce the ill-posedness of the problem and improve solution accuracy, this paper proposes a method for reconstructing the dynamic displacement response via combining the measured acceleration and strain signals for moving load identification. The identification accuracy achieved by employing the reconstructed displacement under different vehicle speeds and different identification algorithms was investigated via finite element (FE) analysis, and a laboratory experiment of a simply supported beam model was constructed to validate the effectiveness of the proposed method. Both the computation simulations and experimental results indicate that the reconstructed displacements fit the true values well and the proposed method can effectively overcome the ill-posedness of the problem in terms of equation resolution and achieve a high level of accuracy.

Keywords: moving load identification; acceleration; dynamic strain; signal reconstruction; modal decomposition.

DOI: 10.1504/IJLCPE.2019.103696

International Journal of Lifecycle Performance Engineering, 2019 Vol.3 No.3/4, pp.257 - 288

Received: 24 Jul 2018
Accepted: 02 Jun 2019
Published online: 22 Nov 2019 *

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