Purpose of the paper is to present an innovative application inside the Non Destructive Testing field based on vibrations measurements, developed by the authors during the last three years, and already tested for analysing damage of many structural elements. The proposed new method is based on the acquisition and comparison of Frequency Response Functions (FRFs) of the monitored structure before and after an occurred damage. Structural damage modify the dynamical behaviour of the structure such as mass, stiffened and damping, and consequently the FRFs of the damaged structure in comparison with the FRFs of the sound structure, making possible to identify, to localize and quantify a structural damage. The activities, presented in the paper, mostly focused on a new FRFs processing technique based on the determining of a representative "Damage Index" for identifying and analysing damage both on real scale aeronautical structural components, like large-scale fuselage reinforced panels, and on aeronautical composite panels. Besides it has been carried out a dedicated neural network algorithm aiming at obtaining a "recognition-based learning"; this kind of learning methodology permits to train the neural network in order to let it recognises only "positive" examples discarding as a consequence the "negative" ones. Within the structural NDT a "positive" example means "healthy" state of the analysed structural component and, obviously, a "negative" one means a "damaged" or perturbed state. From an architectural point of view piezoceramic patches have been tested as actuators and sensors. Besides it has been used a laser-scanning vibrometer system to validate the behaviour of the piezoceramic patches.