Intelligent identification of moving forces based on visual perception

Abstract

The task of identifying moving forces presents a challenging inverse problem for bridge health monitoring and condition assessment. Existing methods for identifying moving loads rely on complex structural response measurement equipment, resulting in inefficiency and elevated costs. To address these challenges, this study introduces an innovative intelligent identification method for moving forces on bridges using visual perception techniques. The proposed method utilizes cameras to capture displacement changes at specific points on the bridge surface to reconstruct moving forces in the time domain. Initially, numerical simulations were conducted to ascertain the feasibility and robustness of identifying moving forces based solely on the structural displacement response. This phase also investigates the influence of different measurement point combinations on identification accuracy. Subsequently, the accuracy of the proposed method in measuring the dynamic displacement response of the structure was carefully evaluated by an outdoor shaking table test. Furthermore, a meticulously designed simply supported beam model was fabricated, followed by the execution of precise vehicle-bridge coupling dynamic experiments. This phase rigorously validates the effectiveness and accuracy of the proposed moving force identification method at varying vehicle speeds. The obtained results substantiate the proposed approach's capability not only to comprehensively capture bridge response data for full-area monitoring but also to consistently and reliably identify information on moving vehicle forces. This study underscores a pioneering application of intelligent visual perception technology in the field of identifying moving forces. The introduced noncontact intelligent identification method is an effective solution for monitoring moving forces on bridges, which has a wide range of applications in the future.