基于小波变换的煤矸石自动分选方法  

Automatic separation method of coal and gangue based on wavelet transform

作　　者：陈立 杜文华[1] 曾志强[1] 王俊元[1] 王日俊 CHEN Li;DU Wenhua;ZENG Zhiqiang;WANG Junyuan;WANG Rijun(School of Mechanical Engineering,North University of China,Taiyuan 030051,China)

机构地区：[1]中北大学机械工程学院,山西太原030051

出　　处：《工矿自动化》2018年第12期60-64,共5页Journal Of Mine Automation

基　　金：山西省自然科学基金资助项目(20161D102025)

摘　　要：针对现有基于图像处理的煤矸石识别分选方法存在识别准确度较低、提取参数多、实时处理效率不高等问题,提出了一种基于小波变换的煤矸石自动分选方法。利用小波分析对采集到的煤与矸石图像进行降噪处理,并通过构造小波矩对煤和矸石进行特征提取分析,计算得到特征值,找出煤与矸石特征参数的明显差异,将其作为煤和矸石识别分选的依据。实验结果表明,该方法提高了煤与矸石在线识别分选的工作效率,准确度高。In view of the problems of low recognition accuracy,multiple extraction parameters and low real-time processing efficiency of existing coal gangue recognition and separation methods based on image processing,an automatic separation method of coal gangue based on wavelet transform was proposed.The method uses wavelet analysis to do noise reduction processing of coal and coal gangue image,and adopts constructing wavelet moment to extract and analyze features of coal and gangue,calculates the feature value,and find out the obvious differences of characteristic parameters between coal and gangue,the characteristic parameters can take as the basis of coal and gangue recognition.The experimental results show that the method improves the efficiency and of on-line identification and separation of coal and gangue with high accuracy.

关 键 词：煤矸石分选 图像处理 小波分析 小波矩构造 特征提取 灰度值 

分 类 号：TD67[矿业工程—矿山机电]