Structural Damage Detection Using Local Damage Factor

Abstract

Damage in a structure alters its dynamic characteristics. Significant research has been conducted in damage detection and structural health monitoring using dynamics-based techniques. But simultaneously determining the presence, severity, and location of damage using the existing damage detection methods can still prove challenging. In this study, a new practical method of structural damage detection called Local Damage Factor (LDF) is presented, which is capable of determining the presence, severity, and location of structural damage at the same time. By including the dynamic characteristics of the intact local structure in the LDF method, the influence of structural nonlinearity, imperfections, and system noise is considered, so that the accuracy of damage detection is improved. Furthermore, a modified LDF (MLDF) method is proposed, which can detect damage without requiring benchmark data for the intact local structure. As a demonstration, the proposed LDF and MLDF methods are applied to damage detection in a 3-D steel frame structure, and the experimental results indicate that both methods can effectively determine the presence, severity, and location of a crack cut into one of the pillars in the frame with a saw. The LDF method is effective in a way that can eliminate both the nonlinear severity effect of structure itself and the ambient noise inherent in the intact structure, whereas the MLDF method is advantageous in that it does not require information about the intact local structure, which is often unavailable for damage detection. The proposed LDF method of in situ damage detection is illustrated using the concrete columns in a wharf structure. The successful detection of damage in the 3-D steel frame, as well as the wharf, demonstrates that the proposed local damage factor technique can be effectively and efficiently used in damage detection and structural health monitoring of structures.