电选粉煤灰颗粒图像识别与烧失量预测模型  

Image recognition and ignition loss prediction model for triboelectrostatic beneficiation of fly ash particles

作　　者：陈师杰 李海生[1,2] 陈英华[1,2] 温晓龙 章新喜[1,2] 孙猛 陈明 CHEN Shijie;LI Haisheng;CHEN Yinghua;WEN Xiaolong;ZHANG Xinxi;SUN Meng;CHEN Ming(School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou 221116, China;Key Laboratory of Coal Processing and Efficient Utilization of Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China;The First Mining Company of China Pingmei Shenma Group, Pingdingshan 467000, China)

机构地区：[1]中国矿业大学化工学院,江苏徐州221116 [2]中国矿业大学煤炭加工与高效洁净利用教育部重点实验室,江苏徐州221116 [3]中国平煤神马集团一矿,河南平顶山467000

出　　处：《中国粉体技术》2018年第6期30-35,共6页China Powder Science and Technology

基　　金：国家自然科学基金项目;编号:51674259

摘　　要：在相同光照条件下,运用MATLAB软件控制工业相机获取不同烧失量粉煤灰的图像信息,根据粉煤灰中不同组分对于光反射的差异性,提取脱炭粉煤灰不同组分的图像特征参数,利用极限学习机神经网络建立烧失量与图像特征的数学模型,对比烧失量的预测效果获得最佳的激活函数,实现脱炭粉煤灰烧失量的在线快速检测。结果表明,极限学习机建立的预测模型能够准确识别电选粉煤灰的图像特征,快速获得粉煤灰烧失量数据,准确度高,可用于工业生产中电选粉煤灰烧失量的快速在线检测。Under the same lighting conditions,the MATLAB software was used to control the industrial camera in order to obtain the image information of the different ignition loss for fly ash.Taking into account the light reflectance differences of different components in the fly ash,extraction of different components of the triboelectrostatic beneficiation fly ash Image feature parameters,the extreme learning machine neural network was used to establish a mathematical model between the ignition loss and image characteristics,and the best activation function was got by comparing the prediction effect of loss on ignition,and the on-line rapid detection of the ignition loss was realized.The results show that the prediction model established by extreme learning machine can accurately identify the image characteristics,and quickly obtain the the ignition loss of fly ash.The extreme learning machine is high precision,and it provides a technical reference for the rapid online testing of the fly ash ignition loss in industrial production.

关 键 词：粉煤灰 烧失量 图像特征 数学模型 极限学习机 

分 类 号：TD97[矿业工程—选矿]