Damage identification of long-span bridges based on the correlation of probability distribution of monitored quasi-static responses

Abstract

Structural health diagnosis is one of the most critical issues in structural health monitoring (SHM). Vibration-based methods have been extensively investigated in the last few decades in the SHM community, but they encounter the challenges of local damage insensitivity and environmental sensitivity. However, the study of structural health diagnosis based on structural quasi-static response data, which has well-defined spatial coordinates and is sensitive to the local condition of the structure, is insufficient. It is difficult to extract structural models or parameters that directly indicate structural damage owing to the coupling effect of the damage and unknown external loads in the quasi-static response data. This study proposes a method based on the correlation of the probability distribution of the quasi-static response data for damage identification, and it is proved that the variation in the structural condition can be inferred from the variation in the correlation of the probability distribution of multiple quasi-static response data. The earth mover’s distance (EMD) is introduced as a quantitative indicator of the variation in the probability distribution function. The difference in the EMD (DEMD) between two monitored quasi-static responses was adopted as the damage indicator. The monitored strain on the steel box girder of a multi-tower cable-stayed bridge and the monitored cable tension of the cable-stayed bridge were employed to validate the proposed method. The results show that the proposed method successfully identifies the damage to the steel box girders and stay cables.