An Infrared-Induced Terahertz Imaging Modality for Foreign Object Detection in a Lightweight Honeycomb Composite Structure / Zhang Hai [et al.]

Уровень набора: IEEE Transactions on Industrial InformaticsАльтернативный автор-лицо: Zhang Hai;Sfarra, S., specialist in the field of non-destructive testing, Researcher of Tomsk Polytechnic University, 1979-, Stefano;Osman, A., Ahmad;Szielasko, K., Klaus;Stumm, Ch., Christopher;Genest, M., Mark;Maldague, X., XavierКоллективный автор (вторичный): Национальный исследовательский Томский политехнический университет, Инженерная школа неразрушающего контроля и безопасности, Центр промышленной томографии, Научно-производственная лаборатория "Тепловой контроль"Язык: английский.Страна: .Резюме или реферат: 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..Примечания о наличии в документе библиографии/указателя: [References: 50 tit.].Аудитория: .Тематика: труды учёных ТПУ | электронный ресурс | Empirical orthogonal function (EOF) | fourier transform | lightweight honeycomb | polynomial fitting | terahertz (THz) | ортогональные функции | преобразование Фурье | полиномиальные алгоритмы Ресурсы он-лайн:Щелкните здесь для доступа в онлайн
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[References: 50 tit.]

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.

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