Seismic damage identification of floating non-structural components based on computer vision techniques
Non-structural components are essential to building functions.Damage to non-structural components(NSCs)often affects the post-earthquake normal functionality of buildings,and in severe cases,can lead to prolonged functional paralysis.As a result,the seismic damage of NSCs is a critical factor affecting the seismic resilience of buildings.The existing approaches for post-earthquake performance assessment of buildings like health monitoring and remote sensing are only suitable for structural components.There has been limited research on non-structural component damage identification.This study proposes a damage identification method specific for freestanding non-structural components.Considering the characteristic differences in seismic response patterns of fixed,suspended,and freestanding NSCs,this study develops a method for seismic damage recognition of freestanding NSCs based on YOLOF object detection algorithm and the Slowfast video understanding model.The proposed method was validated based on a database of videos containing the seismic response and damage of floating NSCs which was collected in a series of scaled shake table tests.The results indicate that the proposed method is effective in identifying the response and damage patterns of freestanding non-structural components with an accuracy rate of 83.4%.
NETL
NSTL
万方数据
