Damage Identification Method Using Additional Virtual Mass Based on Damage Sparsity - Qingxia Zhang; Dengzheng Xu; Jilin Hou; Łukasz Jankowski; Haiyan Wang (Applied Sciences, 2021)
Damage identification methods based on structural modal parameters are influenced by the structure form, number of measuring sensors and noise, resulting in insufficient modal data and low damage identification accuracy. The additional virtual mass method introduced in this study is based on the virtual deformation method for deriving the frequency-domain response equation of the virtual structure and identify its mode to expand the modal information of the original structure. Based on the initial condition assumption that the structural damage was sparse, the damage identification method based on sparsity with <semantics>l1</semantics> and <semantics>l2</semantics> norm of the damage-factor variation and the orthogonal matching pursuit (OMP) method based on the <semantics>l0</semantics> norm were introduced. According to the characteristics of the additional virtual mass method, an improved OMP method (IOMP) was developed to improve the localization of optimal solution determined using the OMP method and the damage substructure selection process, analyze the damage in the entire structure globally, and improve damage identification accuracy. The accuracy and robustness of each damage identification method for multi-damage scenario were analyzed and verified through simulation and experiment.