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

Content Provider	IEEE Xplore Digital Library
Author	Sauer, C. Emamian, V.
Copyright Year	2007
Description	Author affiliation: Southwest Res. Inst., San Antonio (Sauer, C.)
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.
Starting Page	1
Ending Page	5
File Size	3911549
Page Count	5
File Format	PDF
ISBN	1424411599
DOI	10.1109/SYSOSE.2007.4304235
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-04-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Digital signal processing Fault detection Signal processing algorithms Mechanical factors Inspection Computerized monitoring Mechanical systems Principal component analysis Fourier transforms Magnetostriction self-organizing feature map fault detection characterization signal processing guided wave Magnetostrictive principal component neural network
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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