| Autor: |
Vesala, G. T., Ghali, V. S., Rama Sastry, D. V. A., Naik, R. B. |
| Zdroj: |
Mapan; Mar2023, Vol. 38 Issue 1, p133-145, 13p |
| Abstrakt: |
The past two decades witnessed the evolution of non-stationary thermal wave imaging (NSTWI) techniques for active infrared non-destructive testing of various industrial components. The non-stationary temporal thermal response from the test sample in NSTWI comprises of different components, where a proper signal decomposition algorithm decomposes all these components and provides actual thermal response of the test object for defect detection. The present article qualitatively analyses the three signal decomposition algorithms such as empirical mode decomposition (EMD), Hilbert vibrational decomposition (HVD) and variational mode decomposition (VMD) for thermal signal decomposition and defect detection. A mild steel specimen with artificially simulated defects of same size lying at various depths is used to experimentally validate the three signal decomposition algorithms. Further, the defect detection is carried out by employing Fourier transform phase on each intrinsic mode function (IMF) of the three decomposition algorithms. Defect signal-to-noise ratio is considered for qualitative comparison of three signal decomposition techniques in NSTWI. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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