Non-contact impact load identification based on intelligent visual sensing technology

Abstract

Accurate identification of impact loads is vital for structural assessment and design. Traditional methods rely on complex equipment, such as accelerometers or strain gauge, which can be expensive and prone to failure. This study introduces a non-contact intelligent identification approach incorporating visual sensing technology, providing a convenient means to identify impact loads. Numerical simulations explore the differences in identifying impact forces through acceleration and displacement responses, particularly by considering such variables as measurement noise and number of measurement points. A meticulously designed experiment verified the feasibility of the proposed method for measuring the displacement and velocity of rapidly moving targets, and evaluated its performance in terms of accuracy. A series of impact loading experiments were conducted on a simply supported girder bridge model to validate the effectiveness of the proposed impact force identification method. Results indicate strong agreement between displacement response measurements and percentile meters. The proposed non-contact method accurately identifies single or continuous impact loads, with a minimum peak relative error of 0.2%. This study represents a pioneering application of intelligent visual sensing technology in the field of impact load identification. Moreover, the current research introduces a novel approach to address the challenges faced by conventional methods in identifying impact loads. Future research can leverage the groundwork laid by this study to further optimize and expand the proposed method, enhancing its capabilities and fully harnessing its potential to offer advanced solutions in structural health monitoring.