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- W4317602009 abstract "At present, there are few studies on nondestructive testing of aircraft surface based on hyperspectral imaging at home and abroad. Therefore, an indoor near infrared (NIR) hyperspectral damage detection system with a spectral resolution of 5nm was established, and the paint damage on the sample surface was identified. The reflectance calibration, average reflectance calculation and principal component analysis (PCA) dimensionality reduction were performed on the collected hyperspectral data. On this basis, the unsupervised classification iterative self-organizing Data analysis algorithm (ISODATA) is used to identify the damaged samples. The results show that the spectral curves of the damaged and undamaged pixels of the sample are significantly different at about 910nm. The first 10 principal components selected can contain 97% of the sample data information, which can realize the effective identification of damage samples based on ISODATA. In this study, paint damage was taken as an experimental sample to verify the feasibility of using near-infrared hyperspectral imaging technology for damage identification. In addition, preliminary outfield experiment results also show that it is feasible to apply this technology to aircraft surface damage detection." @default.
- W4317602009 created "2023-01-21" @default.
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- W4317602009 date "2023-01-20" @default.
- W4317602009 modified "2023-09-29" @default.
- W4317602009 title "Damage simulation experiment of aircraft skin coating based on hyperspectrum" @default.
- W4317602009 doi "https://doi.org/10.1117/12.2651910" @default.
- W4317602009 hasPublicationYear "2023" @default.
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