Experimental Study of an Adaptive Sequential Nonlinear LSE with Unknown Inputs for Structural Damage Tracking

摘要

An improved adaptive sequential nonlinear LSE with unknown inputs (ASNLSE-UI) approach was proposed to real-time-track the structural damage when it occurs for structural safety and management after emergency event. Experimental studies are presented to verify the capability of the improved ASNLSE-UI approach. A series of tests using a small-scale 3-story base-isolated building have been performed. White noise and earthquake excitations, applied to the base of the model, have been used. To simulate structural damages during the test, an innovative device is designed and manufactured to reduce the stiffness of some stories. With the measured response data of different damage scenarios, the improved ASNLSE-UI approach is used to track the variation of structural physical parameters. Besides, the unknown inputs are simultaneously identified. Experimental results demonstrate that the improved ASNLSE-UI approach is capable of tracking the variation of stiffness parameters leading to the detection of structural damages.