Title :
Application of Guided Wave Technology and DSP Techniques for Fault Detection and Characterization
Author :
Sauer, Christopher ; Emamian, Vahid
Author_Institution :
Southwest Res. Inst., San Antonio
Abstract :
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.
Keywords :
Fourier transforms; fault diagnosis; mechanical engineering computing; principal component analysis; self-organising feature maps; signal processing; DSP techniques; Fourier transform; automatic fault monitoring; fault detection; guided wave technology; magnetostrictive technology; mechanical systems; nondestructive materials evaluation; principal component analysis; self-organizing map; signal processing algorithms; Computerized monitoring; Digital signal processing; Fault detection; Fourier transforms; Inspection; Magnetostriction; Mechanical factors; Mechanical systems; Principal component analysis; Signal processing algorithms; Magnetostrictive; characterization; fault detection; guided wave; neural network; principal component; self-organizing feature map; signal processing;
Conference_Titel :
System of Systems Engineering, 2007. SoSE '07. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
1-4244-1159-9
Electronic_ISBN :
1-4244-1160-2
DOI :
10.1109/SYSOSE.2007.4304235