Experimental Validation of a Structural Health Monitoring Methodology: Part Ii. Novelty Detection on a Gnat Aircraft

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.…”

“…The frequency band includes the 8 first flexural modes of the beam. Figure 23 shows the evolution of the 7 damage indicators (computed with (16)) as a function of ω. Damage contained between x5 and x6 should appear in D56.…”

Advanced Feature Selection for Simplified Pattern Recognition within the Damage Identification Framework

“…The first author was involved in a body of research, funded by DERA/QinetiQ [1][2][3][4], on Structural Health Monitoring (SHM) which proposed a health monitoring system based upon novelty detection techniques. The aim of this overall body of research was to make as much progress as possible up the hierarchical fault detection structure [5] whilst retaining, or even improving, the robustness of the lower level solutions.…”