Experimental Validation of a Structural Health Monitoring Methodology: Part I. Novelty Detection on a Laboratory Structure

Damage localization using transmissibility functions: A critical review

“…In this contribution, outlier analysis based on frequency lines in the TFs was used for damage detection. A few years later, experimental validations on the use of TFs for damage detection ( [15], [16] and [17]) and localization [18] have been performed using vibration data from a laboratory wing box structure and a gnat aircraft wing. Detection was based on three different novelty detection techniques (outlier analysis, auto-associative neural networks and kernel density estimation), while localization was based on supervised learning using a multi-layer perception (MLP) neural network.…”

“…For damage detection, one should find the frequency bands for which the features are highly sensitive to damage and insensitive to variability in the normal condition [15]- [16]. For damage localization, an additional requirement is to find frequency bands in which the features are highly sensitive to one type of damage, and almost insensitive to the others [18].…”

“…The difference of TFs between the undamaged and the damaged conditions was used for damage localization, in a very similar way to the method presented in [25]. One important aspect of these methods is the fact that they are based on the data measured on the intact structure only, therefore avoiding the need of training data emphasized in [14], [15] and [16]. The authors note however that while the approach seems to work well at low frequencies, the results deteriorate when increasing the frequency band, raising again the question of the frequency band to be used.…”

“…Indeed, for these TFs, the damage is located in a subsystem which has no effect on the TF (C or D). Equation (15) shows that TFs are not sensitive to a structural variation located in these subsystems. T23 contains the damaged stiffness.…”

The State-of-the-Art on Framework of Vibration-Based Structural Damage Identification for Decision Making

“…The motivation of using transmissibility for damage detection relies on the fact that the transmissibility is a local quantity, suggesting a higher sensitivity than the modal parameters to detect structure changes [71]. For example, Worden et al [72] detected damage using the novelty detection algorithm based on the measured transmissibility. Canales et al [73] studied the output-only modal identification using transmissibility under variable load conditions.…”