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A New Method to Characterize the Stone-Stone Contact Degree of Asphalt Mixture Using X-ray Computed Tomography Images

並列摘要


Until now, voids in the Coarse Aggregate (YCA) parameter were used to judge whether the coarse aggregate skeleton is formed in asphalt mixtures. However, this method has several shortcomings and deficiencies. In this paper, the X-ray Computed Tomography (CT) is used to obtain two-dimensional (2D) images through a series of digital image processing methods to separate the aggregates successfully. A contact searching method was established to find all the contacting pixels surrounding each particle. All pixels found were stored and analyzed. The contact degree changes, along with the different depths of the specimen, and the contacting pixel values calculated by the algorithm concentrate to approximately 0-20 pixels, which equals about 0-2 mm. Three quantitative indicators, Cl , C2, and C3, were established. Their input data were fitted by 4 different probability density functions (PDFs): Normal distribution, Lognormal distribution, Gamma distribution, and Weibull distribution. The goodness of the fit was simultaneously tested through two different formal statistical tests (Kolmogorov-Smirnov and Chi-square) to provide mathematical support. Finally, the Lognormal PDF was found to be the most suitable for describing the input data distributions, and C1 was recommended as the quantitative indicator for the assessment of stone-stone contact degree.

被引用紀錄


Liu, H. T. (2012). 利用可適性彈性蛇變曲線模型從事核磁共振影像之腦部區域分割 [master's thesis, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU.2012.00967
陳亮廷(2009)。時間派翠網路的工作流程分析〔碩士論文,朝陽科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0078-1111200915521557

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