![]() ![]() The widely studied structural system identification method could be seen as a feature extraction method specially fitting the SHM applications. The detection and location of damage can be formulated as a hypothesis test, with the location often determined by modal parameter estimation. Bayesian methods have been extensively applied to system identification and structural health monitoring. Structural health monitoring can be considered in a statistical framework. Many damage detection methods that examine changes in the vibration characteristics of monitored structures have been devised although quantitative assessment of structural damages using real vibration data collected from civil engineering structures still remains to be a challenging task today. Vibration-based SHM methods have the potential to detect damages in structures in a global sense. The importance of structural health monitoring (SHM) in the design, construction, maintenance and post-extreme event repair of civil engineering structures has been recognized in the past decade. 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. 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. ![]() 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. 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. 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. The 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. ![]()
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