Localized damage detection in a large-scale moment connection using a strain gauge sensor network

摘要

In order to maintain healthy structures, it is important to find means of Structural Health Monitoring (SHM) that are effective, economical, and easy to implement. A localized damage detection algorithm based on measured data from a densely clustered sensor network has been previously presented. This method has been validated using both wired and wireless accelerometers applied to a small-scale idealized beam-column connection. However, to progress towards real-world implementation, there is a need to verify that this algorithm is effective and applicable for full-scale structures with unknown progressive damage. Moreover, it is important to verify the use of other commonly used sensor types, in this case strain gauges, which represent different response parameters. In this paper, the performance of the damage detection algorithm is evaluated for a large-scale steel moment connection constructed at the ATLSS Center at Lehigh University, which was being tested for use in an earthquake-prone structure. This test specimen was instrumented with a network of strain gauges and cyclically loaded to failure. The strain responses from the test are analyzed using the local damage detection algorithm. The resulting changes in the damage indicating parameters compared to the damage observations to both determine the point of earliest detection and to verify the locations of the damage. By successfully implementing this local damage detection algorithm using strain gauges instrumented on a large-scale structure, the versatility of this method is demonstrated.