Structural Health Monitoring with Data Fusion Method

In structural health monitoring, damage detection results have uncertainty due to the measurement noise, modeling error and environment changes. In this paper, data fusion based on the Dempster-Shafer (D-S) evidence theory was employed to decrease the uncertainty level and improve the accuracy of damage identification. A weighted fusion damage index (WFDI) was proposed to perform damage identification. A two-story concrete frame was fabricated as the object for the structural health monitoring test. Experimental results have verified the effectiveness of the proposed method, which will improve damage identification accuracy and increase the reliability of damage identification.