Acoustic emission-based structural health monitoring concept for corrosion of aluminum aircraft structures

Abstract

In the aircraft industry, where highly optimized aluminum structures and most stringent safety requirements meet, corrosion of aluminum is an important issue to be controlled. To this end, several structural health monitoring (SHM) methods have already been demonstrated, including the acoustic emission (AE) method, which has shown potential for corrosion monitoring. Typically, immersion-like setups are used for demonstration. However, recent results at the authors’ research group also show the potential of the AE method to monitor atmospheric corrosion of aluminum aircraft structures. This contribution presents a SHM concept for the identification, i.e., detection, localization, quantification, and typification, of corrosion of thinwalled aluminum structures by AE. The proposed monitoring concept combines time and frequency domain features of corrosion triggered AE signals and AE source localization-based imaging with a-priori knowledge of structural configuration and loading by the utilization of machine learning methods to quantify and typify corrosion. Successful detection of atmospheric corrosion of aluminum by AE is briefly presented. Furthermore, the concept is theoretically discussed for quantification and typification of corrosion forms typical for atmospheric corrosion conditions.