摘要
为优化选煤厂选煤质量,设计基于神经网络的选煤厂智能化综合平台。用户可在业务层的移动监管客户端登录平台下达操作指令,感知层采集选煤厂的监控视频数据与生产过程数据,通过传输层的统一数据接口总网关传输至业务层,业务层可针对用户所需处理问题,启动煤泥水浓缩智能加药系统或重介分选过程智能控制系统,2种系统采用基于神经网络的煤泥水浓缩剂智能添加模型,控制凝聚剂与絮凝剂的添加量,通过基于神经网络的重介分选密度智能控制模型,以期望灰分值为参照,合理设置重介分选密度。实验结果表明,选煤厂选煤时,凝聚剂、絮凝剂、重介分选密度实际值与指定值一致,不存在明显的异常增量,可优化选煤厂选煤质量。
In order to optimize the coal preparation quality of coal preparation plant,an intelligent comprehensive platform of coal preparation plant based on neural network is designed.The user can issue operation instructions on the mobile supervision client login platform of the business layer,the sensing layer collects the monitoring video data and production process data of the coal preparation plant,and transmits them to the business layer through the general gateway of the unified data interface of the transmission layer.The business layer can start the intelligent dosing system of slime water concentration or the intelligent control system of heavy medium separation process according to the problems required by the user.The two systems adopt the intelligent addition model of slime water concentrate based on neural network to control the addition amount of coagulant and flocculant.Through the intelligent control model of dense medium separation density based on neural network,the dense medium separation density is reasonably set with the expected ash value as the reference.Experimental results:during coal preparation in the coal preparation plant,the actual values of coagulant,flocculant and dense medium separation density are consistent with the specified values,and there is no obvious abnormal increment,which can optimize the coal preparation quality of the coal preparation plant.
作者
杨渊
Yang Yuan(CCTEG Beijing Huayu Engineering Co.,Ltd.,Beijing 100120,China)
出处
《能源与环保》
2023年第4期222-227,共6页
CHINA ENERGY AND ENVIRONMENTAL PROTECTION
基金
国家自然科学基金面上项目(71971015)。
关键词
神经网络
选煤厂
智能化综合平台
煤泥水浓缩
neural network
coal preparation plant
intelligence integrated platform
slime water concentration
