Innovative Data Fusion Enabled Structural Health Monitoring Approach

Abstract

Piezoceramic-based active sensing is a useful approach to structural health monitoring. This approach often involves a large number of distributed piezoceramic transducers. It may be confusing to incorporate each sensor data. It is desired to develop an automated health monitoring approach to obtain a comprehensive and accurate health monitoring result by simultaneously interpreting data from all sensors. In this paper, an innovative data fusion enabled structural health monitoring (SHM) approach based on the Dempster-Shafer (D-S) evidence theory is proposed to obtain comprehensive SHM results for a distributed sensor network in a civil infrastructure. Considering that evidence from multiple different information sources (sensor data) has different levels of significance, not all evidence is equivalently effective for the final decision. A weighted fusion damage index (WFDI) is proposed to perform damage identification based on the authors’ recently developed piezoceramic-based smart aggregates. Experimental data of a two-story concrete frame was used to study the effectiveness of the proposed weighted fusion damage index. Analyses show that the proposed weighted fusion damage index can reveal the damage status of different areas of the frame. The results are consistent with the visual inspection of the cracks on the concrete frame.