About Open Access
Feature extraction and selection for defect classification of pulsed eddy current NDT
Lookup NU author(s)
Dr Tao Chen
Professor Gui Yun Tian
Chen T, Tian GY, Sophian A, Que PW
NDT & E International
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
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.
Newcastle University Library, NE2 4HQ, United Kingdom. Tel: 0044 (191) 222 7657
©2015 Newcastle University Library