Feature extraction and selection for defect classification of pulsed eddy current NDT
Pulsed eddy current (PEC) is a new emerging nondestructive testing (NDT) technique using a broadband pulse excitation with rich frequency information and has wide application potentials. This technique mainly uses feature points and response signal shapes for defect detection and characterization, i...
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Elsevier
2008
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| Online Access: | http://irep.iium.edu.my/46712/ http://irep.iium.edu.my/46712/ http://irep.iium.edu.my/46712/1/Feature_extraction_and_selection_for_defect_classification_of_pulsed.pdf |
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iium-467122016-10-20T08:06:23Z http://irep.iium.edu.my/46712/ Feature extraction and selection for defect classification of pulsed eddy current NDT Chen, Tianlu Tian, Gui Yun Sophian, Ali Que, Pei Wen TA165 Engineering instruments, meters, etc. Industrial instrumentation Pulsed eddy current (PEC) is a new emerging nondestructive testing (NDT) technique using a broadband pulse excitation with rich frequency information and has wide application potentials. This technique mainly uses feature points and response signal shapes for defect detection and characterization, including peak point, frequency analysis, and statistical methods such as principal component analysis (PCA). This paper introduces the application of Hilbert transform to extract a new descending feature point and use the point as a cutoff point of sampling data for detection and feature estimation. The response signal is then divided by the conventional rising, peak, and the new descending points. Some shape features of the rising part and descending part are extracted. The characters of shape features are also discussed and compared. Various feature selection and integrations are proposed for defect classification. Experimental studies, including blind tests, show the validation of the new features and combination of selected features in defect classification. The robustness of the features and further work are also discussed. Elsevier 2008 Article PeerReviewed application/pdf en http://irep.iium.edu.my/46712/1/Feature_extraction_and_selection_for_defect_classification_of_pulsed.pdf Chen, Tianlu and Tian, Gui Yun and Sophian, Ali and Que, Pei Wen (2008) Feature extraction and selection for defect classification of pulsed eddy current NDT. NDT & E International , 41 (6). 467 - 476. ISSN 0963-8695 http://www.sciencedirect.com/science/article/pii/S0963869508000145 |
| repository_type |
Digital Repository |
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Local University |
| institution |
International Islamic University Malaysia |
| building |
IIUM Repository |
| collection |
Online Access |
| language |
English |
| topic |
TA165 Engineering instruments, meters, etc. Industrial instrumentation |
| spellingShingle |
TA165 Engineering instruments, meters, etc. Industrial instrumentation Chen, Tianlu Tian, Gui Yun Sophian, Ali Que, Pei Wen Feature extraction and selection for defect classification of pulsed eddy current NDT |
| description |
Pulsed eddy current (PEC) is a new emerging nondestructive testing (NDT) technique using a broadband pulse excitation with rich frequency information and has wide application potentials. This technique mainly uses feature points and response signal shapes for defect detection and characterization, including peak point, frequency analysis, and statistical methods such as principal component analysis (PCA). This paper introduces the application of Hilbert transform to extract a new descending feature point and use the point as a cutoff point of sampling data for detection and feature estimation. The response signal is then divided by the conventional rising, peak, and the new descending points. Some shape features of the rising part and descending part are extracted. The characters of shape features are also discussed and compared. Various feature selection and integrations are proposed for defect classification. Experimental studies, including blind tests, show the validation of the new features and combination of selected features in defect classification. The robustness of the features and further work are also discussed. |
| format |
Article |
| author |
Chen, Tianlu Tian, Gui Yun Sophian, Ali Que, Pei Wen |
| author_facet |
Chen, Tianlu Tian, Gui Yun Sophian, Ali Que, Pei Wen |
| author_sort |
Chen, Tianlu |
| title |
Feature extraction and selection for defect classification of pulsed eddy current NDT |
| title_short |
Feature extraction and selection for defect classification of pulsed eddy current NDT |
| title_full |
Feature extraction and selection for defect classification of pulsed eddy current NDT |
| title_fullStr |
Feature extraction and selection for defect classification of pulsed eddy current NDT |
| title_full_unstemmed |
Feature extraction and selection for defect classification of pulsed eddy current NDT |
| title_sort |
feature extraction and selection for defect classification of pulsed eddy current ndt |
| publisher |
Elsevier |
| publishDate |
2008 |
| url |
http://irep.iium.edu.my/46712/ http://irep.iium.edu.my/46712/ http://irep.iium.edu.my/46712/1/Feature_extraction_and_selection_for_defect_classification_of_pulsed.pdf |
| first_indexed |
2023-09-18T21:06:29Z |
| last_indexed |
2023-09-18T21:06:29Z |
| _version_ |
1777410967928307712 |