Abstract
This study aims to propose a roadway roughness profile identification using the acceleration responses of a vehicle by means of a dynamic regularized least square minimization (DRLS). The DRLS is a method comprising the least square minimization whose cost function is the error between simulated and measured accelerations, a regularization technique to reduce the ill-posedness in the inverse problem, and dynamic programming in the numerical solution. The optimum hyperparameter in the regularization technique can be obtained automatically utilizing the L-curve method, which is a great advantage of the proposed method. The validity of the proposed method is verified via a field experiment on a highway using a test vehicle equipped with accelerometers. The identification accuracy when the vehicle runs at high speed is investigated by comparing it with the roadway roughness measured by laser displacement sensors. The experimental result shows that the proposed method has enough accuracy.
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Acknowledgments
A part of this work is supported by JSPS Bilateral joint research projects, Grant No. JPJSBP120217405, which is greatly appreciated.
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Hasegawa, S., Kim, CW., Kawada, N. (2023). Roadway Roughness Profile Identification from Vehicle Acceleration by Means of Dynamic Regularized Least Square Minimization. In: Limongelli, M.P., Giordano, P.F., Quqa, S., Gentile, C., Cigada, A. (eds) Experimental Vibration Analysis for Civil Engineering Structures. EVACES 2023. Lecture Notes in Civil Engineering, vol 433. Springer, Cham. https://doi.org/10.1007/978-3-031-39117-0_20
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