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Feature detection and monitoring of eddy current imaging data by means of wavelet based singularity analysis.

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Feature detection and monitoring of eddy current imaging data by means of wavelet based singularity analysis. / Ma, X.; Peyton, A. J.

In: NDT and E International, Vol. 43, No. 8, 11.2010, p. 687-694.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Ma X, Peyton AJ. Feature detection and monitoring of eddy current imaging data by means of wavelet based singularity analysis. NDT and E International. 2010 Nov;43(8):687-694. doi: 10.1016/j.ndteint.2010.07.006

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Ma, X. ; Peyton, A. J. / Feature detection and monitoring of eddy current imaging data by means of wavelet based singularity analysis. In: NDT and E International. 2010 ; Vol. 43, No. 8. pp. 687-694.

Bibtex

@article{204c11668cc64d40ab34a2da81c51359,
title = "Feature detection and monitoring of eddy current imaging data by means of wavelet based singularity analysis.",
abstract = "The objective of the paper is to apply a wavelet based singularity method to detect and monitor transient activity in the eddy current data, which is of particular interest for industrial use in order to check signal levels. The paper begins with a description of the fundamentals of methodologies for singularity measurement including calculation of Lipschitz indexes and selection of effective wavelets suitable for the applications. An electromagnetic induction system from which eddy current data are obtained is briefly described for this case study. Applications of this method to eddy current imaging data are therefore explored. The paper demonstrates that the wavelet based singularity method can be effectively employed in identifying transient features in the electromagnetic data and locating the signal changes to determine the time period of the transients. Turbulent features in the signals due to the dedicated movement of metal flow can also be identified.",
keywords = "Magnetic induction, Eddy current, Wavelet transform, Singularity, Lipschitz index",
author = "X. Ma and Peyton, {A. J.}",
year = "2010",
month = nov,
doi = "10.1016/j.ndteint.2010.07.006",
language = "English",
volume = "43",
pages = "687--694",
journal = "NDT and E International",
issn = "0963-8695",
publisher = "Elsevier Limited",
number = "8",

}

RIS

TY - JOUR

T1 - Feature detection and monitoring of eddy current imaging data by means of wavelet based singularity analysis.

AU - Ma, X.

AU - Peyton, A. J.

PY - 2010/11

Y1 - 2010/11

N2 - The objective of the paper is to apply a wavelet based singularity method to detect and monitor transient activity in the eddy current data, which is of particular interest for industrial use in order to check signal levels. The paper begins with a description of the fundamentals of methodologies for singularity measurement including calculation of Lipschitz indexes and selection of effective wavelets suitable for the applications. An electromagnetic induction system from which eddy current data are obtained is briefly described for this case study. Applications of this method to eddy current imaging data are therefore explored. The paper demonstrates that the wavelet based singularity method can be effectively employed in identifying transient features in the electromagnetic data and locating the signal changes to determine the time period of the transients. Turbulent features in the signals due to the dedicated movement of metal flow can also be identified.

AB - The objective of the paper is to apply a wavelet based singularity method to detect and monitor transient activity in the eddy current data, which is of particular interest for industrial use in order to check signal levels. The paper begins with a description of the fundamentals of methodologies for singularity measurement including calculation of Lipschitz indexes and selection of effective wavelets suitable for the applications. An electromagnetic induction system from which eddy current data are obtained is briefly described for this case study. Applications of this method to eddy current imaging data are therefore explored. The paper demonstrates that the wavelet based singularity method can be effectively employed in identifying transient features in the electromagnetic data and locating the signal changes to determine the time period of the transients. Turbulent features in the signals due to the dedicated movement of metal flow can also be identified.

KW - Magnetic induction

KW - Eddy current

KW - Wavelet transform

KW - Singularity

KW - Lipschitz index

U2 - 10.1016/j.ndteint.2010.07.006

DO - 10.1016/j.ndteint.2010.07.006

M3 - Journal article

VL - 43

SP - 687

EP - 694

JO - NDT and E International

JF - NDT and E International

SN - 0963-8695

IS - 8

ER -