SVD-based approach for damage detection of pre-stressed structures
Résumé
Vibration-based methods are well-established and effective tools to assess the health state of civil, mechanical and aerospace engineering structures. However, their reliability is still affected by the variability of the features commonly used for damage detection. Environmental effects and changes in operational conditions are the main sources of variability in the structural response. As a consequence, the modal identification used to extract damage sensitive features has to face constricting requirements in terms of signals stationarity and performance accuracy. Moreover, with reference to the damage assessment, large variations of monitored features mask subtle effects due to damage, which remain undetected. This study is conceived to address both these issues by focusing, in particular, on the non-stationarity of the loading conditions of tensioned structures, such as cables and pre-stressed beams. The capability of spectral methods to deal with the modal identification of non-stationary systems is enhanced by a curve-fitting procedure based on nonlinear least squares optimisation. Wavelet analysis is also applied for comparison and validation of the FFT-based technique. Identified natural frequencies are then used for the damage detection, exploiting the capacity of singular values decomposition to discriminate between damage-related events and the intrinsic non-stationary nature of the structural response. A reduced order realization of the features set is performed to amplify changes not belonging to measurement variability but deriving from exogenous events, such as damage. The proposed methodology is validated by experimental analyses carried out on a beam subjected to time-varying loading conditions in order to simulate the health monitoring of quasi-stationary systems.