Forming method and quality detection method of concrete aggregate detection model

Abstract

The invention discloses a forming method of a concrete aggregate detection model. The method comprises the following steps: building a closed acquisition environment without sun illumination; in the closed acquisition environment, under the irradiation of a light source, acquiring an original image of the concrete aggregate by utilizing an image acquisition module; acquiring original images of different types of concrete aggregates, performing quality scoring on the original images to divide the original images into a plurality of grades, and taking the graded original images of the concrete aggregates as a deep learning training set; carrying out image preprocessing on the original images of the concrete aggregates in the deep learning training set; and training the deep learning trainingset subjected to image preprocessing by adopting a deep learning training model to obtain a concrete aggregate detection model. The invention further discloses a concrete aggregate quality detectionmethod. The method is high in detection precision and high in detection efficiency, can meet the requirement of real-time processing, and can also meet the requirement of stable detection in actual production or offline monitoring.

Description

technical field [0001] The invention relates to the technical field of aggregate detection, in particular to a method for forming a concrete aggregate detection model and a quality detection method. Background technique [0002] Concrete is the most important material in the construction process of the construction industry. As the most important component of concrete, aggregate accounts for 75% of the volume and weight. Its particle shape, size ratio, stone powder content, porosity, etc. determine the concrete. quality. In practical applications, cubic or spherical aggregates are easier to form a denser gradation structure than fine needle aggregates, have better overall stability and durability, and are conducive to pumping and construction, and are not easy to block the delivery pipeline. Therefore, it is of great significance to inspect the quality of concrete aggregates according to the particle shape and particle size distribution of aggregates, so as to evaluate the ...

AI Technical Summary

Problems solved by technology

This method can measure and detect the defects of aggregate particle shape online, but the defects of this method are that the detection accuracy is not high, the result is unstable, the algorithm is complicated, and it is very affected by the ambient light, etc., so it is difficult to use in the actual production environment

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