Feature extraction and gating techniques for ultrasonic shaft signal classification

Lee, Kyungmi, and Estivill-Castro, Vladimir (2007) Feature extraction and gating techniques for ultrasonic shaft signal classification. Applied Soft Computing, 7 (1). pp. 156-165.

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Abstract

Discrete wavelet transform (DWT) coefficients of ultrasonic test signals are considered useful features for input into classifiers due to their effective time–frequency representation of non-stationary signals. However, DWT exhibits a time-variance problem that has resulted in reservations for its wide acceptance. In this paper, a new technique to derive a preprocessing method for time-domain A-scans signal is presented. This technique offers consistent extraction of a segment of the signal from long signals that occur in the non-destructive testing of shafts. Two different classifiers using artificial neural networks and support vector machines are supplied with features generated by our new preprocessing method and their classification performance are compared and evaluated. Their performances are also compared with other alternatives and report the results here. This investigation establishes experimentally that DWT coefficients can be used as a feature extraction scheme more reliably by using our new preprocessing technique.

Item ID: 10121
Item Type: Article (Refereed Research - C1)
Keywords: feature extraction; signal processing; non-destructive evaluation; pattern classification
ISSN: 1872-9681
Date Deposited: 10 Apr 2010 01:38
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining @ 70%
08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080199 Artificial Intelligence and Image Processing not elsewhere classified @ 10%
08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080108 Neural, Evolutionary and Fuzzy Computation @ 20%
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