Robust Structural Damage Detection Using Analysis of the CMSE Residual’s Sensitivity to Damage

• Main Authors: Mingqiang Xu, Shuqing Wang, Jian Guo, Yingchao Li
• Format: Article
• Language: English
• Published: MDPI AG 2020-04-01
• Series: Applied Sciences
• Subjects: noise robustness; sensitivity analysis; cross-modal strain energy; damage detection
• Online Access: https://www.mdpi.com/2076-3417/10/8/2826

This paper presents a robust damage identification scheme in which damage is predicted by solving the cross-modal strain energy (CMSE) linear system of equations. This study aims to address the excessive equations issue faced in the assemblage of the CMSE system. A sensitivity index that, to some extent, measures how the actual damage level vector satisfies each CMSE equation, is derived by performing an analysis of the defined residual’s sensitivity to damage. The index can be used to eliminate redundant equations and enhance the robustness of the CMSE system. Moreover, to circumvent a potentially ill-conditioned problem, a previously published iterative Tikhonov regularization method is adopted to solve the CMSE system. Some improvements to this method for determining the iterative regularization parameter and regularization operator are given. The numerical robustness of the proposed damage identification scheme against measurement noise is proved by analyzing a 2-D truss structure. The effects of location and extent of damage on the damage identification results are investigated. Furthermore, the feasibility of the proposed scheme for damage identification is experimentally validated on a beam structure.