Damage and Loose Rivet Detection on an Airbus A320 Panel Using Non-contact Measurement Techniques

Efficient and reliable detection of damages is of critical importance in the aerospace industry. Within the context of non-destructive testing (NDT), advanced non-contact measurement techniques can be leveraged to obtain full-field responses of a target structure, facilitating the development of structural health monitoring (SHM) methodologies. The motivation of this chapter is to compare several types of measurement techniques, excitation signals, and post-processing methods applied to an Airbus airplane panel with sections of damaged and loose rivets. Its response is obtained using both digital image correlation (DIC) and laser Doppler vibrometry (LDV) techniques. The panel is excited with modal shakers or PZT patches using chirp or pseudorandom signals, for different frequency ranges. Full-field measurements were obtained, along with other more localized measurements on the area containing defects. On a later stage, methodologies inspired on nonlinear analysis and machine learning (ML) techniques were applied for damage detection. A description of the obtained results from these different experimental settings is shown in this chapter, together with a successful structural characterization and detection of damages on the airplane panel.