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Study of the Extraction and Quantitative Characterization of the Microstructural Features of Aggregates

Pinhui ZhaoDongxing GaoKechao HanLingyun KongYi LuoZeyu ZhangFei BiZiqiao Yang

出版	ASTM International, 2019
URL	http://books.google.com.hk/books?id=fQx2zgEACAAJ&hl=&source=gbs_api

註釋Aggregates are one of the important parts of an asphalt mixture. Their structural features have a significant effect on the adhesion of asphalt aggregates and influence the service life of the asphalt mixture. By using cold-field-emission scanning electron microscope technology, this study investigates the fine characterizations of the microstructures of different aggregates. This study illustrates a method to obtain high-resolution micrographs in large horizons by using the technology of continuously spliced high-resolution micrographs, which can be used to acquire graphs within the scope of hundreds of square microns with nanometer resolution. By employing Image-Pro Plus processing software (Media Cybernetics, Rockville, MD), the microstructural features of aggregates were recognized and indexes were proposed to acquire various data, such as area, perimeter, length, width, length-width ratio, and the shape factor. These data could reflect the microstructural features of aggregates. On this basis, a quantitative characterization based on the feature analysis of the shape factor was established for qualitative and quantitative analyses of aggregate microstructures and to fully obtain structural characteristic parameters of specimens under high resolutions in a large horizon. The collected data were further judged in terms of disparity and consistency by using principal component analysis. Moreover, the position vector function criterion acquired an experimental scheme with the minimal number of random observation groups that were able to represent the overall features of specimens. The study can recognize the complete microstructural features of the aggregate surfaces and further realize a quantitative analysis based on indexation by applying the optimized experimental method and software.