摘要
在基于双能X射线透射技术的废有色金属分选中,可识别的物料厚度范围较小,无法满足废有色金属分选的需求。为解决该问题,对现有识别算法进行了分析,针对现有算法的不足,提出了一种基于低能透射信号值和双能R值双参数联合的区域分块废金属识别算法,提高了识别算法的适用厚度范围,并通过实验对算法的识别率进行了验证。
The range of identifiable material thickness is small in the sorting process of waste non-ferrous metals based on dual- energy X-ray transmission technology, so it can not meet the demand. For this, this paper analyzes the existing recognition algorithms and proposes a zone division scrap metal recognition algorithm based on R and low energy transmission signal. The new algorithm can be used to increase the applicable thickness range and its accuracy is verified by experiments.
作者
黄河
叶文华
熊田忠
胡品龙
黄艰生
HUANG He;YE Wenhua;XIONG Tianzhong;HU Pinlong;HUANG Jiansheng(College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;Jiangsu Huahong Technology Stock Co.,Ltd., Jiangyin 214423, China)
出处
《机械制造与自动化》
2019年第4期26-29,共4页
Machine Building & Automation
基金
江苏省重点研发计划项目(BE2016758)
江苏省科技成果转化专项资金项目(BA2014067)
关键词
双能X射线
物质识别
废金属分选
区域分块
dual-energy X-ray
material identification
scrap metal sorting
zone division
