A technique for autonomous structural damage detection with smart wireless sensor network

Abstract

In this paper, a distributed structural damage detection approach is proposed for large size structures under limited input and output measurements. A large size structure is decomposed into small size substructures based on its finite element formulation. Interaction effect between adjacent substructures is considered as 'additional unknown inputs' to each substructure. By sequentially utilizing the extended Kalman estimator for the extended state vector and the least squares estimation for the unmeasured inputs, the approach can not only estimate the 'additional unknown inputs' based on their formulations but also identify structural dynamic parameters, such as the stiffness and damping of each substructure. Local structural damage in the large size structure can be detected by tracking the changes in the identified values of structural dynamic parameters at element level, e.g., the degrading of stiffness parameters. Numerical example of detecting structural local damages in a large-size plane truss bridge illustrates the efficiency of the proposed approach. A new smart wireless sensor network is developed by the authors to combine with the proposed approach for autonomous structural damage detection of large size structures. The distributed structural damage detection approach can be embedded into the smart wireless sensor network based on its two-level cluster-tree topology architecture and the distributed computation capacity of each cluster head.