Experiments in acoustic structural health monitoring of airplane parts

In this preliminary study we investigate the application of statistical classifiers for structural health monitoring of materials commonly used in airplanes. Our approach is based on the propagation of ultrasonic guided waves through materials like aluminum or carbon fiber reinforced plastic (CFRP). When the material gets damaged, the sound propagation changes. There are two ways of detecting these changes: we can use a physical model of the wave propagation or we can use a statistical approach. In this paper we focus on the latter. We present results using classifiers based on Hidden Markov Models (HMM) and Support Vector Machines (SVM). We compare these results to acoustic travel time tomography as a representative of the physical model based methods.