An Infrared-Induced Terahertz Imaging Modality for Foreign Object Detection in a Lightweight Honeycomb Composite Structure; IEEE Transactions on Industrial Informatics; Vol. 14, iss. 12
| Parent link: | IEEE Transactions on Industrial Informatics Vol. 14, iss. 12.— 2018.— [P. 5629-5636] |
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| Institution som forfatter: | |
| Andre forfattere: | , , , , , , |
| Summary: | Title screen In this paper, terahertz time-domain spectroscopy (THz-TDS) is used for the first time to detect fabricated defects in a glass fiber-skinned lightweight honeycomb composite panel. A novel amplitude polynomial regression (APR) algorithm is proposed as a preprocessing method. This method segments the amplitude-frequency curves to simulate the heating and the cooling monotonic behavior as in infrared thermography. Then, the method of empirical orthogonal function (EOF) imaging is applied on the APR preprocessed data as a postprocessing algorithm. Signal-to-noise ratio analysis is performed to verify the image improvement of the proposed APR-EOF modality from a quantitative point of view. Finally, the experimental results and the physical analysis show that THz is more suitable with respect to the detection of defects in glass fiber lightweight honeycomb composites. Режим доступа: по договору с организацией-держателем ресурса |
| Sprog: | engelsk |
| Udgivet: |
2018
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| Fag: | |
| Online adgang: | https://doi.org/10.1109/TII.2018.2832244 |
| Format: | Electronisk Book Chapter |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=660066 |
MARC
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| 200 | 1 | |a An Infrared-Induced Terahertz Imaging Modality for Foreign Object Detection in a Lightweight Honeycomb Composite Structure |f Zhang Hai [et al.] | |
| 203 | |a Text |c electronic | ||
| 300 | |a Title screen | ||
| 320 | |a [References: 50 tit.] | ||
| 330 | |a In this paper, terahertz time-domain spectroscopy (THz-TDS) is used for the first time to detect fabricated defects in a glass fiber-skinned lightweight honeycomb composite panel. A novel amplitude polynomial regression (APR) algorithm is proposed as a preprocessing method. This method segments the amplitude-frequency curves to simulate the heating and the cooling monotonic behavior as in infrared thermography. Then, the method of empirical orthogonal function (EOF) imaging is applied on the APR preprocessed data as a postprocessing algorithm. Signal-to-noise ratio analysis is performed to verify the image improvement of the proposed APR-EOF modality from a quantitative point of view. Finally, the experimental results and the physical analysis show that THz is more suitable with respect to the detection of defects in glass fiber lightweight honeycomb composites. | ||
| 333 | |a Режим доступа: по договору с организацией-держателем ресурса | ||
| 461 | |t IEEE Transactions on Industrial Informatics | ||
| 463 | |t Vol. 14, iss. 12 |v [P. 5629-5636] |d 2018 | ||
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a Empirical orthogonal function (EOF) | |
| 610 | 1 | |a fourier transform | |
| 610 | 1 | |a lightweight honeycomb | |
| 610 | 1 | |a polynomial fitting | |
| 610 | 1 | |a terahertz (THz) | |
| 610 | 1 | |a ортогональные функции | |
| 610 | 1 | |a преобразование Фурье | |
| 610 | 1 | |a полиномиальные алгоритмы | |
| 701 | 0 | |a Zhang Hai | |
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