摘要
针对目前煤质分析过程中人工操作程序繁琐、时间长,数据记录、分析易出错等实际问题,开展了智能化煤质分析平台计算机辅助设计系统研究。提出采用图像识别与智能数据分析相结合的方式,减少试验过程中的人为干预,提高煤质分析效率和准确性,实现煤质分析智能化,简化煤质分析操作程序,节约时间,降低成本。
In view of the practical problems in coal quality analysis,such as complicated manual operation procedure,long time,error prone data recording and analysis,the research on intelligent coal quality analysis platform computer aided design system is carried out.The method of combining image recognition and intelligent data analysis is proposed to reduce the human intervention in the process of testing,improve the efficiency and accuracy of coal quality analysis,and realize the intelligent coal quality analysis.In this paper,the image recognition technology is used to obtain the coal quality analysis vessel number,and simultaneously transfer the balance weighing data and vessel number to the computer,and automatically perform data analysis and calculation to obtain the coal quality analysis data,and form a file for storage.At the same time,the data can also be transmitted to the mobile phone client in real time to achieve remote monitoring.The computer aided design and development of intelligent coal quality analysis system will greatly simplify the operation procedure of coal quality analysis,save time,reduce cost,and have practical significance of industrial application and promotion.
作者
徐梦雅
方舒扬
吴莞怡
肖扬航
张真兴
郝娟
王海锋
XU Meng-ya;FANG Shu-yang;WU Wan-yi;XIAO Yang-hang;ZHANG Zhen-xing;HAO Juan;WANG Hai-feng(School of Chemical Engineering,China University of Mining and Technology,Xuzhou,Jiangsu 221116,China)
出处
《煤炭加工与综合利用》
CAS
2023年第1期94-98,共5页
Coal Processing & Comprehensive Utilization
基金
国家自然科学基金面上项目,细粒煤流态化摩擦电选的基础研究(51674257)
江苏省大学生创新创业训练计划(省级校企合作项目),智能化煤质检测系统(202110290254H)。
关键词
智能化
煤质分析
图像识别
lenet-5卷积神经网络
辅助设计
intelligent
coal quality analysis
image identification
lenet-5 convolutional neural network
aided design
