Exploration on feature extraction schemes and classifiers for shaft testing system

Lee, Kyungmi (2010) Exploration on feature extraction schemes and classifiers for shaft testing system. Journal of Computers, 5 (5). pp. 679-686.

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Abstract

A-scans from ultrasonic testing of long shafts are complex signals, thus the discrimination of different types of echoes is of importance for non-destructive testing and equipment maintenance. Research has focused on selecting features of physical significance or exploring classifier like Artificial Neural Networks and Support Vector Machines. This paper summarizes and reports on our comprehensive exploration on efficient feature extraction schemes and classifiers for shaft testing system and further on the diverse possibilities of heterogeneous and homogeneous ensembles.

Item ID: 10115
Item Type: Article (Refereed Research - C1)
Keywords: signal classification; non-destructive testing; signal feature extraction
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Reproduced with permission from Academy Publisher. © Academy Publisher

ISSN: 1796-203X
Date Deposited: 17 Aug 2010 01:03
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 > 0806 Information Systems > 080699 Information Systems 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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