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Proceedings Paper

Applications of time-frequency analysis for aging aircraft component diagnostics and prognostics
Author(s): Kwangik Cho; David Coats; John Abrams; Nicholas Goodman; Yong-June Shin; Abdel E. Bayoumi
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Paper Abstract

The classical time-frequency distributions represent time- and frequency-localized energy. However, it is not an easy task to analyze multiple signals that have been simultaneously collected. In this paper, a new concept of non-parametric detection and classification of the signals is proposed using the mutual information measures in the time-frequency domain. The time-frequency-based self and mutual information is defined in terms of cross time-frequency distribution. Based on the time-frequency mutual information theory, this paper presents applications of the proposed technique to real-world vibration data. The baseline and misaligned experimental settings are quantitatively distinguished by the proposed technique.

Paper Details

Date Published: 3 September 2008
PDF: 10 pages
Proc. SPIE 7074, Advanced Signal Processing Algorithms, Architectures, and Implementations XVIII, 70740Y (3 September 2008); doi: 10.1117/12.795289
Show Author Affiliations
Kwangik Cho, Univ. of South Carolina (United States)
David Coats, Univ. of South Carolina (United States)
John Abrams, Univ. of South Carolina (United States)
Nicholas Goodman, Univ. of South Carolina (United States)
Yong-June Shin, Univ. of South Carolina (United States)
Abdel E. Bayoumi, Univ. of South Carolina (United States)


Published in SPIE Proceedings Vol. 7074:
Advanced Signal Processing Algorithms, Architectures, and Implementations XVIII
Franklin T. Luk, Editor(s)

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