首页|General Tikhonov regularization-based load estimation of bridges considering the computer vision-extracted prior information

General Tikhonov regularization-based load estimation of bridges considering the computer vision-extracted prior information

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  • NETL
  • NSTL
  • Wiley
Estimating the load distribution of a bridge structure enables to evaluate thein-service state and predict the structural responses. This paper develops aniterative strategy to inversely estimate the traffic load distribution of a bridgefrom limited measurements. The computer vision technologies, including theYOLO network-based object detection and a pixel coordinate-based positioningapproach, are used to locate the vehicle positions on the bridge deck and forma prior information vector of the input positions. Then, a generalized Tikhonovregularization method is proposed to estimate the load distribution using thebridge response and prior information. The regularization parameter is determinedby the L-curve method. The fusion of computer vision and regularizationcan improve the load identification accuracy and reduce the overfittingeffect. The developed approach is applied to numerical and experimentalexamples under various load conditions. The load can be accurately identifiedin all cases, and the full-field responses of the structures can be reconstructedwith minor errors.

bridgescomputer visionload estimationstructural health monitoringTikhonov regularization

Yixian Li、Limin Sun、Yong Xia、Lanxin Luo、Ao Wang、Xudong Jian

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Department of Bridge Engineering,Tongji University, Shanghai, China,Department of Civil and EnvironmentalEngineering, The Hong Kong PolytechnicUniversity, Hung Hom, Hong Kong

Department of Civil and EnvironmentalEngineering, The Hong Kong PolytechnicUniversity, Hung Hom, Hong Kong,State Key Laboratory of DisasterReduction in Civil Engineering, TongjiUniversity, Shanghai, China

Department of Civil and EnvironmentalEngineering, The Hong Kong PolytechnicUniversity, Hung Hom, Hong Kong,National Observation and ResearchStation of Material Corrosion andStructural Safety of Hong Kong-Zhuhai-Macao Bridge in Guangdong, Guangdong,China

Department of Bridge Engineering,Tongji University, Shanghai, China

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2022

10.1002/stc.3135

Structural control and health monitoring

Structural control and health monitoring

EI
ISSN：1545-2255
年,卷(期)：2022.29(12)
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