Damage Detection with Streamlined Structural Health Monitoring Data
AbstractThe huge amounts of sensor data generated by large scale sensor networks in on-line structural health monitoring (SHM) systems often overwhelms the systems’ capacity for data transmission and analysis. This paper presents a new concept for an integrated SHM system in which a streamlined data flow is used as a unifying thread to integrate the individual components of on-line SHM systems. Such an integrated SHM system has a few desirable functionalities including embedded sensor data compression, interactive sensor data retrieval, and structural knowledge discovery, which aim to enhance the reliability, efficiency, and robustness of on-line SHM systems. Adoption of this new concept will enable the design of an on-line SHM system with more uniform data generation and data handling capacity for its subsystems. To examine this concept in the context of vibration-based SHM systems, real sensor data from an on-line SHM system comprising a scaled steel bridge structure and an on-line data acquisition system with remote data access was used in this study. Vibration test results clearly demonstrated the prominent performance characteristics of the proposed integrated SHM system including rapid data access, interactive data retrieval and knowledge discovery of structural conditions on a global level. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Li, J.; Deng, J.; Xie, W. Damage Detection with Streamlined Structural Health Monitoring Data. Sensors 2015, 15, 8832-8851.
Li J, Deng J, Xie W. Damage Detection with Streamlined Structural Health Monitoring Data. Sensors. 2015; 15(4):8832-8851.Chicago/Turabian Style
Li, Jian; Deng, Jun; Xie, Weizhi. 2015. "Damage Detection with Streamlined Structural Health Monitoring Data." Sensors 15, no. 4: 8832-8851.