Application of Principal Component Analysis in Dynamic Thermal Testing Data Processing; Russian Journal of Nondestructive Testing; Vol. 44, iss. 7
| Parent link: | Russian Journal of Nondestructive Testing Vol. 44, iss. 7.— 2008.— [P. 509-516] |
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| Awdur Corfforaethol: | |
| Awduron Eraill: | , , , |
| Crynodeb: | Title screen The principles and features of the application of statistical principal component analysis (PCA) in active thermal testing are considered. A comparison between PCA and Fourier analysis in finding defects in composite materials, detecting corrosion in aluminum, and determining moisture content in construction materials is performed. It is concluded that, generally, images of principal components increase the signal-to-noise ratio and are close in performance to phase diagrams; nevertheless, the results of this method are poorly predictable and require further analysis Режим доступа: по договору с организацией-держателем ресурса |
| Iaith: | Saesneg |
| Cyhoeddwyd: |
2008
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| Pynciau: | |
| Mynediad Ar-lein: | http://link.springer.com/article/10.1134/S1061830908070097 |
| Fformat: | Electronig Pennod Llyfr |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=636957 |
| Crynodeb: | Title screen The principles and features of the application of statistical principal component analysis (PCA) in active thermal testing are considered. A comparison between PCA and Fourier analysis in finding defects in composite materials, detecting corrosion in aluminum, and determining moisture content in construction materials is performed. It is concluded that, generally, images of principal components increase the signal-to-noise ratio and are close in performance to phase diagrams; nevertheless, the results of this method are poorly predictable and require further analysis Режим доступа: по договору с организацией-держателем ресурса |
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