Research On Digital Image Technology Of Coarse Aggregate Morphology Characteristics

Domestic highways mainly used asphalt concrete pavement. Asphalt mixture is multi-phase composite materials composed by various materials. The aggregate which account for more than 90% of mixture quality is an important factor of the engineering properties of asphalt, especially in the morphological characteristics of aggregates. The traditional aggregate shape test methods are tedious, time-consuming and big workload, influenced by subjective testers, cannot easily get objective timely results. In recent years, with the increasing number of digital image processing technology applied to engineering materials, more and more attention the use of image processing technology to collect and analyze the morphology of aggregates. This paper based on summarizes the domestic and international research on digital imaging technology, mainly to analyze the two-dimensional shape characteristics of coarse aggregate.Testing scheme is acquisition aggregate image in natural light, with aggregate evenly spread. Using matlab processing segmentation images. Because of the aggregate itself characteristics, segmentation methods don't adopt commonly gray threshold segmentation, but directly to segmentation the true color pictures of three-channel respectively, successfully obtained the outlines of each particle projection. Calculated the corresponding outlines indexes, specific indexes are major-axis, minor-axis, major-axis / minor-axis, rectangular, shape index and angularity. Finally calculated the statistics value of aggregate shape feature index, which according to statistical analysis of the probability distribution of the samples.Take single-file aggregate tamping density test, find that the VCADRC from the same set of yard materials decreases as the particle size increasing; In addition, for the aggregate with different rock character of this study, the VCADRC of diabase generally higher than the basalt.Research the relationship of aggregate shape feature index with VCADRC, the VCADRC is not sensitive of size index for the same size aggregate, more sensitive shape characteristic index is Angularity. The "pseudo" three-dimensional index height is derived by two-dimensional; the VCADRC have high sensitive with height and flakiness content. While the height is exactly the opposite index of flakiness, that is, the greater height corresponding of the aggregate flakiness content should be smaller, which is consistent with the trend that VCADRC decreases as height increases and increases as flakiness content increases.