Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human 2009
DOI: 10.1145/1655925.1656181
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Feature extraction and reconstruction of particles reinforced metal matrix composite microstructure

Abstract: The issue on mechanical properties of ceramic particles reinforced metal matrix composite is a key to design and application, and multi-particles primitive cell method is an effective method to predict its mechanical properties. The construction method of primitive cell is discussed and studied in this paper. Firstly, the 256 bit gray process of composite's SEM image has been done, and the gray scale threshold of different material phase in composite's image is determined by gray scale histogram; secondly, the… Show more

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“…Based on this, the quantitative content of each phase was calculated from the analysis of micrographs of longitudinal and cross sections of the pseudo-alloy samples with a large visible field of 5 × 5 mm (Tables 2 and 3). This method is sometimes used to analyze the composition and microstructural features of various composites, including alloys, based on the results of electron microscopy or X-ray computed tomography [26][27][28][29]. No examples of using this technique for studying W-Cu composites were found in the literature.…”
Section: Microstructure Of the W-cu Pseudo Alloy Depending On The Ann...mentioning
confidence: 99%
“…Based on this, the quantitative content of each phase was calculated from the analysis of micrographs of longitudinal and cross sections of the pseudo-alloy samples with a large visible field of 5 × 5 mm (Tables 2 and 3). This method is sometimes used to analyze the composition and microstructural features of various composites, including alloys, based on the results of electron microscopy or X-ray computed tomography [26][27][28][29]. No examples of using this technique for studying W-Cu composites were found in the literature.…”
Section: Microstructure Of the W-cu Pseudo Alloy Depending On The Ann...mentioning
confidence: 99%