Rapid detection method for ultralimit particles of irregular particle swarm based on machine vision

Abstract

The invention discloses a machine vision-based irregular particle swarm over-limit particle rapid detection method, which comprises the following steps of: collecting particle flow pictures with different illuminance and different contents in advance as a data set, performing real-time over-limit particle granularity detection by using an industrial camera, rapidly identifying a range region in which the over-limit particles are located through YOLOv5, and determining whether the over-limit particles are over-limit particles or not. And segmenting the target region through a watershed algorithm to obtain an overrun particle edge, and calculating the area of the overrun particle edge to judge whether the overrun particle is an overrun particle. According to the method, the ore group pictures with different illuminance and different granularities are collected as the training set, so that the range of the ultralimit particles can be quickly identified and extracted. A watershed algorithm is further used to segment the image in the range to obtain an ultralimit particle contour, and particle size area information is further obtained. According to the method of combining area determination through the neural network and contour segmentation through the watershed algorithm, the speed of detecting the ultralimit particles in real time in industrial application can be increased, the accuracy rate is high, and the real-time performance of detection is achieved.

Description

technical field [0001] The present invention relates to the technical field of particle size detection, in particular to a rapid detection method for particle group out-of-limit particles based on machine vision. Background technique [0002] The ore particle size parameter can be used as the main standard to measure the degree of ore crushing. At the same time, it is also the main reference for influencing the selection of beneficiation methods and technological processes. When it is detected that out-of-limit particles exist in the selected raw materials, it will affect the sorting effect of the main equipment and cause a series of hazards, such as possibly blocking the feeding pump, feeding pipeline and underflow nozzle. The upper limit rate of the product is also one of the main indicators for judging the quality of coal. In actual production scenarios, it is often encountered that the grading sieve plate is damaged or dropped, the crusher is worn, etc., resulting in e...

AI Technical Summary

Problems solved by technology

The latter is a single particle size recognition through the neural network, the algorithm complexity is high, and the identification takes a long time, and the subsequent particle size detection is cumbersome and the accuracy is low.

It cannot meet the online particle size detection during normal production, and the lagged detection results have no reference value for the real-time control of the subsequent control system

Images