Damage Assessment Using Stiffness Matrix Decomposition and Output-Only Modal Identification

Structural damage detection has been a significant research topic in the last two decades. Many of the damage detection methods that have been proposed do not work accurately for identification of location and severity of damage. This article presents an accurate damage identification method using stiffness matrix decomposition and modal identification method. The total stiffness matrix is decomposed to story stiffness matrices, and damage location and severity will be detected by solving a linear regression problem. Blind Source Separation-Sparse Component Analysis (BSS-SCA) and frequency domain decomposition (FDD) have been used as output-only modal identification methods for calculating structural modal parameters. Modal parameters such as natural frequencies and mode shapes are used to determining the total stiffness matrix of structure in the current state. These methods are output-only and do not need to measure excitation's inputs. Therefore, it is capable of online structural health monitoring. The proposed method is applied in a structure, modeled as a shear building. In order to simulate a real condition, up to +/- 2.5% noise has been added to the calculated responses of the structure. Finally, results show that the presented method with both of the output-only modal identification methods can detect damages and their locations properly, but the detection algorithm with the BSS-SCA method is more accurate than the one with FDD method in diagnosing damage severity. However, the accuracy of the proposed method is decreased when a complicated excitation is applied to the structure and when the damping ratio increases.