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Smart Structures and Systems Volume 26, Number 5, November 2020 , pages 591-603 DOI: https://doi.org/10.12989/sss.2020.26.5.591 |
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Dynamic deflection monitoring of high-speed railway bridges with the optimal inclinometer sensor placement |
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Shunlong Li, Xin Wang, Hongzhan Liu, Yi Zhuo, Wei Su and Hao Di
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Abstract | ||
Dynamic deflection monitoring is an essential and critical part of structural health monitoring for high-speed railway bridges. Two critical problems need to be addressed when using inclinometer sensors for such applications. These include constructing a general representation model of inclination-deflection and addressing the ill-posed inverse problem to obtain the accurate dynamic deflection. This paper provides a dynamic deflection monitoring method with the placement of optimal inclinometer sensors for high-speed railway bridges. The deflection shapes are reconstructed using the inclination-deflection transformation model based on the differential relationship between the inclination and displacement mode shape matrix. The proposed optimal sensor configuration can be used to select inclination-deflection transformation models that meet the required accuracy and stability from all possible sensor locations. In this study, the condition number and information entropy are employed to measure the ill-condition of the selected mode shape matrix and evaluate the prediction performance of different sensor configurations. The particle swarm optimization algorithm, genetic algorithm, and artificial fish swarm algorithm are used to optimize the sensor position placement. Numerical simulation and experimental validation results of a 5-span high-speed railway bridge show that the reconstructed deflection shapes agree well with those of the real bridge. | ||
Key Words | ||
high-speed railway bridge; dynamic deflection; optimal inclinometer sensor placement; inclination-deflection transformation; information entropy | ||
Address | ||
(1) Shunlong Li, Xin Wang: School of Transportation Science and Engineering, Harbin Institute of Technology, 73 Huanghe Road, 150090 Harbin, China (2) Hongzhan Liu, Yi Zhuo, Wei Su, Hao Di: China Railway Design Corporation, 300142 Tianjin, China | ||