A 3D image-based equivalent particle size grading method for coarse aggregates

Abstract

The present invention provides a method for grading coarse aggregates based on three-dimensional images. image filling and contour extraction, etc.) to obtain the coordinate points and thickness information of the outer contour of the particles; according to the obtained thickness information and outer contour coordinate points, the equivalent particle size and various particle shape parameters of the coarse aggregate (for example, the pin size) are calculated. , flatness, triangularity and sphericity), by comparing the characterization methods of coarse aggregate thickness; by proposing a new equivalent particle size characterization method for coarse aggregates of different shapes, and further modifying the image method and sieving method The difference between them generates errors to achieve accurate grading. The invention discloses a method for grading the equivalent particle size of coarse aggregate based on a three-dimensional image, which realizes the accurate measurement of the equivalent particle size of the coarse aggregate and improves the grading accuracy of the coarse aggregate particle.

Description

technical field [0001] The invention relates to the field of construction machinery, in particular to a three-dimensional image-based equivalent particle size grading method for coarse aggregates. Background technique [0002] Gradation is the proportional relationship between the size and particle size of aggregates. If the gradation is appropriate, the amount of mortar to fill the voids of the aggregates can be reduced, the water consumption per unit volume and the amount of gel materials can be correspondingly reduced, and the production cost of concrete can be reduced. Material grading must know the equivalent particle size of each aggregate particle. [0003] At present, vibrating sieving method and image method are often used to measure the equivalent particle size of coarse aggregate particles. Vibration sieving method measures the equivalent particle size of coarse aggregate particles. The measurement process is to pour the coarse aggregate into a square-hole sieve,...

AI Technical Summary

Problems solved by technology

[0004] The flatness of the coarse aggregate is manually measured with a vernier caliper. According to the national standard, the highest value of the particles when lying flat is taken as the particle thickness to calculate the flatness. The measurement efficiency of this method is low, and the measurement results are easily affected by human factors. Impact

[0005] The vibratory sieving method can only measure the gradation of coarse aggregate, but cannot measure the morphological parameters of coarse aggregate

And the sieving method is limited by the number of sieve layers because the division of the particle size segment is limited, so the measurement of the particle size distribution is slightly rough, which affects the accuracy of the measurement results to a certain extent. In addition, due to the severe vibration during the sieving process, Some particle types may be highly susceptible to breakage, affecting their particle size distribution

However, the characterization of the coarse aggregate particle size in the image method is mainly based on the contour information of the particles (mainly the front projection contour), so there are some differences with the measurement results of the sieving method in actual operation (the particles will constantly change their positions and directions during the vibration process). error

In addition, in the actual measurement process, a single characterization method is usually used to characterize the equivalent particle size of the particles. Through experiments, it is found that the measurement result of the maximum inscribed circle diameter of the contour is smaller than that of the sieving method, and the maximum inscribed circle diameter of the convex hull is smaller than that of the sieving method. The measurement result of the method is smaller than that of the sieving method, and the measurement accuracy of the other two characterization methods is lower, resulting in a large error in the grading results

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