Application of Guided Wave Technology and DSP Techniques for Fault Detection and Characterization

Nondestructive materials evaluation is the science of identifying the physical and mechanical properties of a piece of material without altering its end-use capabilities and using this information to make decisions regarding appropriate applications [7]. Most importantly, the detection and characterization of new, or existing, faults can provide important insight into the integrity of a given structure or material. Currently, a wide variety of research efforts are under investigation for nondestructive inspection methods for use in automatic fault monitoring of mechanical systems. This paper focuses upon the development of a collection of signal processing algorithms, enabling fault detection and characterization. A combination of principal component analysis, Fourier transform, and self-organizing map are employed to identify the patterns that are present in the data sets. Through the use of magnetostrictive (MsS) and guided wave technology, a set of algorithms is developed to reliably detect fault presence, and discriminate between different fault orientations and sizes.