Bivariate EMD analysis for aircraft component inspection

In recent years many alternative methodologies and techniques have been proposed to perform non-destructive inspection and maintenance operations of moving structures. In particular, ultrasonic techniques have shown to be very promising for automatic inspection systems. From the literature, it is evident that neural paradigms are considered, by now, the best choice to automatically classify ultrasound data. At the same time the most appropriate pre-processing technique is still undecided. The aim of this paper is to propose a new and innovative data pre-processing technique that converts real-valued ultrasonic signals into complex-valued signals, making it suitable to apply phase synchrony analysis using complex extensions of Empirical Mode Decomposition (EMD), a data driven algorithm for detecting temporal scales in nonlinear and nonstationary data. Experimental tests aiming to detect defective areas in aircraft components are reported and the effectiveness of the proposed methodology is demonstrated.