Damage Detection Using Outlier Analysis

Damage localization using transmissibility functions: A critical review

“…In contrast, the zeros are only sensitive to a certain subset of mass and stiffness parameters that are localized in specific regions of the structure (see equation (14)). This difference in sensitivity to global/local changes can be exploited by selecting a damage feature based on TFs, which are independent of the poles and solely dependent on zeros.…”

“…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 example treated was a numerical 3 degrees of freedom (dofs) chainlike mass spring system. Another numerical example involving a 3 dofs system was studied a few years later by the same research group [14]. In this contribution, outlier analysis based on frequency lines in the TFs was used for damage detection.…”

“…On the contrary to admittance functions (usually called frequency response functions FRF) which are frequency responses between conjugate variables (motion response/ force input), TFs are obtained by taking the ratio of two response spectra of like variables (motion response/motion input) xi and xj, for a given input located at degree of freedom (DOF) k : (4) It can be observed that the common denominator det(K-ω 2 M), whose roots are the system's poles, disappears by taking the ratio of the two response spectra. Consequently, poles or zeros of the TF correspond to the zeros of both FRFs.…”

“…By following the dynamic behavior of the structure in real time, it is possible to apply statistical methods in order to detect small damages and remove the effects of the environment ( [3], [4], [5] and [6]). This opens the way to the development of automated damage detection systems and could allow going from an "on schedule" maintenance to an "on demand" maintenance, therefore greatly reducing the costs and the risks of failure between two maintenances.…”