Vision‐based displacement and joint rotation tracking of frame structure using feature mix with single consumer‐grade camera

Abstract

A monocular vision-based response tracking method is proposed for simultaneously identifying translational floor displacement and rotational joint deformation of frame structures at multiple locations. The framework incorporates subpixel-level feature matching and tracking and is designed by introducing the feature-mix concept and feature quality evaluation for the initialization and postprocessing stage, respectively. The necessity of monitoring frame joint rotation is presented with the damage observations. A large-scale reinforced concrete frame structure is employed to investigate the proposed response estimation method through comprehensive shaking table tests by using a consumer-grade camera. The initial feature population, time-history agreement, overall estimation accuracy, survival feature ratio, and measurement uncertainty are further analyzed. In addition, the potential values and advantages of the proposed response tracking method for dynamic measurement and seismic evaluation are discussed illustratively.