Application of substructural damage identification using adaptive Kalman filter

Abstract

Substructure identification is a method to address the numerical difficulty and insufficient sensors involved in structural identification of a large system. This method divides a large structure into certain number of small substructures and identifies them separately. In substructure identification, various structural identification algorithms have been used for identifying constant structural parameters. This paper used adaptive Kalman filter to identify varying properties of substructures. Numerical studies were performed on a shear building, a plane frame, and a plane truss bridge to investigate the effectiveness of the adaptive Kalman filter in substructure identification. The results demonstrated that the stiffness and damping of substructures can be identified successfully from the limited acceleration responses, and abrupt changes of the properties can be tracked well. The studies in this paper are useful for structural health monitoring and structural model updating.