科研之友
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摘要
The construction uniformity of asphalt mixture has been widely evaluated, but rarely focused on the surface and internal structure of asphalt pavement simultaneously. To evaluate the aggregate distribution uniformity of asphalt pavement effectively, firstly, the pavement surface image acquisition device (PSIAD) was developed to collect the texture image on the surface of asphalt pavement. Then the sectional images of pavement core samples were acquired by industrial computed tomography (ICI') equipment. Finally, the aggregate distribution uniformity of asphalt pavement was evaluated from pavement surface and internal structure by MATLAB image processing technology. According to the results, the PSIAD based on the camera with charge coupled device (CCD) and shading black-box can avoid the information error of original pavement surface texture image, which is caused by the change of light conditions. The macro-texture width index K can substitute the texture depth to evaluate the aggregate distribution uniformity on the surface of asphalt pavement, and the aggregate distribution uniformity evaluation criterion of pavement surface based on K value was established. The improved iterative threshold segmentation algorithm based on ring-shaped partition can segment coarse aggregate particles on CT image effectively. D-H is the variation coefficient of coarse aggregate area ratio in four regions on the same sectional image. D-V1 is the variation coefficient of average coarse aggregate area ratio on different sectional images in one core sample. D-V2 is the variation coefficient of the ratio of aggregate area with different equivalent diameter on different sectional images in one core sample. The coarse aggregate distribution evaluation indexes of D-H, D-V1 and D-V2 can reflect the distribution uniformity of aggregate inside the asphalt pavement.
