3D Detection Research And Analysis Of Coarse Aggregate Particles Based On Structured Light

The coarse aggregates gradation of mineral mixture was expected to measure accurately and rapidly, and which has gradually been paid more attention to by scientific experts in the field of road construction and maintenance. With the development of computer technology and digital image processing technology, the study on characteristics of coarse aggregates has been developed rapidly based on two-dimensional(2D) image, and the study is fruitful. But there is also limitation that 2D research is unable to reflect the three-dimensional(3D) information of coarse aggregates factually. In this context, the research based 3D feature has been developed.Based on the 3D optical imaging principle of structured light, a 3D detection system was designed to obtain the 3D contour information of coarse aggregates truly and accurately. And the MATLAB software was used to accomplish 3D image reconstruction. According to the characteristics of the noise existing in the 3D image, the paper tried two denoising filtering algorithms of average smoothing filter and median smoothing filter. After comparing the filtering effect of two methods, the results showed median filtering effect using 5*5 template is better. Considering the complex background existing in the image, average method and method based on datum plane were put forward to finish optimal processing of 3D image background. Because of the machinery and complexity of average method, the background difference method could be implemented more simply, and the optimization effect is better. Then, to carry algorithm research of particle volume and particle size of coarse aggregate, the differential method was put forward to calculate volume of coarse aggregate particles, and error causes were analyzed with weighing method as reference. And the correlation coefficients between differential method and artificial weighing method were calculated at the 4.75 mm, 9.5mm, 13.2mm and 16 mm of coarse aggregates respectively, the results show that there is strong correlation between two methods, and the differential method is feasible to calculate the volume. At the meantime, the algorithms of the sphere equivalent diameter and minimum circumscribed cuboid were put forward to calculate the particle size. Compared with the measurements through vernier calipers, the error showed results of the sphere equivalent diameter is more accurate.Since the laser cannot reach to sunken part of coarse aggregate bottom during structured light imaging, the sunken part was filled when the 3D image was reconstructed and which resulted in the particle volume bigger. To study the computing method of coarse aggregates gradation based on 3D detection, the paper proposed a hypothesis : the sunken part volume of coarse aggregate particle was proportional to this particle volume. The result that formula from the hypothesis was deduced was consistent with the conclusion of correlation analysis about coarse aggregate particles volume, so the hypothesis was verified and 3D virtual sieving theory was put forward via this.The sunken part of coarse aggregates was filled, which also leaded to the particle size was bigger. So the correction coefficient ? was adopted to correct the particle size of coarse aggregates. After the particle size was corrected, the accuracy of graded screening has been improved significantly. After that, based on the 3D virtual sieving theory of coarse aggregates and particle size correction method, the 3D virtual sieving model was given. Finally, the paper carried out 3D virtual sieving to calculate coarse aggregates gradation of 5-10 mm and 10-15 mm, the results show that the grading curve of 3D virtual sieving coincides with the grading curve of artificial sieving well, and the average error is just 1.583%. So the 3D detection of coarse aggregate particles based on structured light is feasible.