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Quantitative characterization of the carbon/carbon composites components based on video of polarized light microscope.
Li, Yixian; Qi, Lehua; Song, Yongshan; Chao, Xujiang.
Afiliação
  • Li Y; School of Mechatronic Engineering, Northwestern Polytechnical University, Xi'an, 710072, China.
  • Qi L; School of Mechatronic Engineering, Northwestern Polytechnical University, Xi'an, 710072, China.
  • Song Y; School of Mechatronic Engineering, Northwestern Polytechnical University, Xi'an, 710072, China.
  • Chao X; School of Mechatronic Engineering, Northwestern Polytechnical University, Xi'an, 710072, China.
Microsc Res Tech ; 80(6): 644-651, 2017 Jun.
Article em En | MEDLINE | ID: mdl-28194836
The components of carbon/carbon (C/C) composites have significant influence on the thermal and mechanical properties, so a quantitative characterization of component is necessary to study the microstructure of C/C composites, and further to improve the macroscopic properties of C/C composites. Considering the extinction crosses of the pyrocarbon matrix have significant moving features, the polarized light microscope (PLM) video is used to characterize C/C composites quantitatively because it contains sufficiently dynamic and structure information. Then the optical flow method is introduced to compute the optical flow field between the adjacent frames, and segment the components of C/C composites from PLM image by image processing. Meanwhile the matrix with different textures is re-segmented by the length difference of motion vectors, and then the component fraction of each component and extinction angle of pyrocarbon matrix are calculated directly. Finally, the C/C composites are successfully characterized from three aspects of carbon fiber, pyrocarbon, and pores by a series of image processing operators based on PLM video, and the errors of component fractions are less than 15%.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Microsc Res Tech Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2017 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Microsc Res Tech Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2017 Tipo de documento: Article País de afiliação: China
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