矿产保护与利用2026，Vol.46Issue(2)：73-81,9.DOI:10.13779/j.cnki.issn1001-0076.2026.02.004
基于边缘检测算法的煤炭细颗粒识别与粒径分析研究
Particle Identification and Size Analysis for Fine Coal Based on Edge Detection
摘要
Abstract
This study aims to solve the problems of low detection accuracy in the quantity and particle size of fine particles during coal preparation,as well as strong background interference on small-aperture screens.Coal particle groups ranging from 0.5 mm to 3 mm were selected as the research object.A machine vision detection device was established,and image acquisition and data augmentation experiments were carried out to improve image quality.The recognition effects of different edge detection algorithms on coal particles were compared and analyzed.Finally,the particle quantity,spatial distribution and particle size were quantitatively analyzed and interpreted.Experimental results show that the optimal image enhancement parameters are determined as brightness increased by 20%,gamma correction increased by 15%,grayscale processing increased by 15%and spatial filtering increased by 20%.Under these parameters,the peak signal-to-noise ratio(PSNR)is 31.62 dB and the structural similarity index(SSIM)is 0.91.The edge detection algorithm combining threshold segmentation,morphological operation and connected domain analysis(AMC)presents better recognition performance than other algorithms,with a recognition accuracy of 86.6%.Coal particles show a multi-center aggregation and local non-uniform distribution on the screen surface.The detected particle size distribution curve is basically consistent with the trend of real values.This study proves that the AMC edge detection algorithm is effective in identifying fine coal particles and can reliably reflect particle size distribution.The method requires no model training and features fast processing speed,which provides a practical basis for the research and development of intelligent detection equipment in the coal preparation process.关键词
煤炭细颗粒/图像增强/边缘检测/阈值分割/形态学Key words
coal fine particles/image enhancement/edge detection/threshold segmentation/morphological分类
矿业与冶金引用本文复制引用
王传真,许亚雷,刘则庆,陈伟,谢保冈,赵雅琦,林紫君,马翊硕..基于边缘检测算法的煤炭细颗粒识别与粒径分析研究[J].矿产保护与利用,2026,46(2):73-81,9.基金项目
国家自然科学基金面上基金项目(52574308) （52574308）
安徽高校自然科学研究项目(2024AH050339) （2024AH050339）
安徽省自然科学基金(2508085ME133) （2508085ME133）
