工矿自动化2017，Vol.43Issue(3)：61-65,5.DOI:10.13272/j.issn.1671-251x.2017.03.014
基于机器视觉的工矿现场粉尘实时监测
Real-time dust monitoring for industrial site based on machine vision
摘要
Abstract
In view of problems of poor real-time performance and incomplete coverage of traditional dust monitoring methods,two kinds of design scheme of dust monitoring system based on machine vision were proposed,namely dust monitoring systems based on monocular vision and binocular vision.The dust monitoring system based on monocular vision uses frame difference method and corrosion expansion algorithm to realize rapid recognition of the dust target in the field of view.Based on monocular vision,the dust monitoring system based on binocular vision uses calibration target and three-dimensional space reconstruction to achieve dust positioning.The experimental results show that the dust monitoring system based on monocular vision can capture formation process of dust cluster,and the real-time processing rate is four frames per second;the dust monitoring system based on binocular vision can further measure the position information of dust clusters,and positioning error is less than 10％.关键词
粉尘监测/机器视觉/单目视觉/双目视觉/三维定位Key words
dust monitoring/machine vision/monocular vision/binocular vision/three-dimensional localization分类
矿业与冶金引用本文复制引用
谢鹏程,陈青山,李响..基于机器视觉的工矿现场粉尘实时监测[J].工矿自动化,2017,43(3):61-65,5.基金项目
北京市自然科学基金项目(4154071) （4154071）
北京市组织部优秀人才项目(2014000020124G105). （2014000020124G105）
