Abstract
The output-only vibration-based structural health monitoring problem is addressed as the task of detecting damages modeled as changes in the eigenstructure of a linear dynamic system. The proposed damage detection algorithm is based on a residual generated from a subspace-based covariance-driven identification method and on the statistical local approach to the design of detection algorithms. This algorithm computes a global test, which performs a sensitivity analysis of the residuals to the damages, relative to uncertainties and noises. Numerical results are reported, which show the efficiency of the proposed method. They have been obtained on a geometrically simple test article designed, assembled and tested dynamically under impact and random shaker excitation. The method allows detecting damage in an early stage, and it does not require the extraction of the modal parameters from each newly collected data set. This characteristic is very well suited for monitoring purposes: it does not need continuous user interaction and it can easily be made automatic.
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