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Real time bridge dynamic response: Bridge condition assessment and early warning system
Riyansyah M.a, Wijayanto P.B.a, Trilaksono B.R.a, Putra S.A.b, Laila D.S.c
a Faculty of Civil and Environmental Engineering, Institute of Technology Bandung, Bandung, 40132, Indonesia
b Faculty of Industrial Engineering, Telkom University, Bandung, 40257, Indonesia
c School of Mechanical, Aerospace and Automotive Engineering, Coventry University, Coventry, CV1 2TL, United Kingdom
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© Insight Society.The present study investigates the use of wireless sensor networks (WSNs) in the assessment of bridge conditions as well as an early warning system. The WSNs are used to measure the acceleration that occurred on the bridge and the mode shape of the bridge as the excitation loads passing through the bridge. Fast Fourier Transform (FFT) is applied to transform the measured acceleration to get the frequency of the dynamic bridge response. Numerical integration is applied to determine the acceleration to get the displacement of the bridge dynamic response. Implementing the structural dynamics equation, the effective stiffness of the bridge can be determined using the frequency. The effective stiffness and the bridge dynamic response are then used to obtain the bridge condition and load ratings. A scaled model of steel truss bridge and miniature truck with various loads were used to simulate the use of WSNs in bridge assessment, which were also used to validate the finite element model. The finite element model was then used to simulate various scenarios, including the scenarios in which the bridge elements had the various level of damages. The behaviors of bridge with various level of damages can be used to identify the location and the level of damages in the bridge and were found to be useful as early warning system for bridges condition and load ratings.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Bridge condition assessment,Bridge load rating,Fast fourier transform,Structural dynamics,Structural health monitoring[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]We would like to thank the Royal Academy of Engineering for the Newton Funds award IAPP1\100018 to support this research, and the LPDP (Indonesia Endowment for Education) to sponsor S. A Putra’s PhD project.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.18517/ijaseit.10.1.9463[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]