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SHEN Zhi-fu, SUN Tian-you, BAI Yu-fan, JIANG Ming-jing, ZHOU Feng. Extraction method for micro-structure parameters of clay based on imaging principles of scanning electron microscope[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(5): 933-939. DOI: 10.11779/CJGE202105018
Citation: SHEN Zhi-fu, SUN Tian-you, BAI Yu-fan, JIANG Ming-jing, ZHOU Feng. Extraction method for micro-structure parameters of clay based on imaging principles of scanning electron microscope[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(5): 933-939. DOI: 10.11779/CJGE202105018

Extraction method for micro-structure parameters of clay based on imaging principles of scanning electron microscope

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  • Received Date: July 05, 2020
  • Available Online: December 04, 2022
  • Soil deformation under static or dynamic loads is accompanied by adjustment of its microscopic structure. It is an essential and challenging task to quantitatively describe the micro-structure evolutions of soil for micro-to-macro geomechanics. This study proposes a method to extract information of relative arrangement of clay plates from scanning electron microscope (SEM) images based on the physical principles of SEM imaging techniques. First, a theoretical relationship between the grey scale of SEM images in the high-contrast transition zone (with very high and very low grey scales) and the local geometric quantity describing the clay plate arrangement is derived. This relationship considers the laws and functions about the generation rate and angular intensity distribution of the secondary electrons. The local geometric quantities include inclinations of the scanned clay plates and the distance between the two neighboring clay plates. Then, the proposed method is validated by applying it to the analysis of a real SEM image. The distance and relative inclination of two neighboring clay plates are successfully extracted. The relationship between the shadow factor and the distance predicted theoretically by this method and that obtained from the real SEM image are consistent, validating the correctness and capability of the proposed method. Theoretically, the proposed method is not sensitive to the defects in the SEM image such as overexposure, underexposure and random noise.
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