摘要
在水泥熟料流动状态换热研究中,一般认为颗粒的旋转运动对整体换热效果具有一定影响。在所建立的颗粒角速度实验装置上,利用姿态传感器采集颗粒转角信号,对多工况下颗粒的旋转角速度进行了实验测定。研究发现角速度随推料速度的增大而增大,颗粒的推程运动角速度大于返程运动角速度,在一个推程内,颗粒自旋角度占颗粒圆周的17%~25%,对颗粒堆积体的换热有较大影响。基于神经网络理论对实验数据进行处理,建立了颗粒转角的BP神经网络模型,预测值相对于实验值平均误差为14%,该模型为考虑颗粒旋转的水泥熟料流态换热研究提供了分析及验证基础,同时对于其他颗粒的角速度研究具有一定的借鉴意义。
In the study of heat transfer of cement clinker in flowing state,it is generally considered that the rotation of particles has a certain influence on the overall heat transfer effect.On the established particle angular velocity experimental device,the attitude sensor was used to collect the particle rotation angle signal,and the rotation angular velocity of the particle under multiple working conditions was measured experimentally.It is found that the angular velocity increases with the increase of the pushing speed,and the angular velocity of the particles in the pushing process is greater than that in the return direction.And in one push range,the spin angle of particles accounts for 17%-25%of the circumference of particles,which has a great influence on the heat transfer of particles.Based on the theory of neural network,the experimental data were processed,and the BP neural network model of particle rotation angle was established.The average error of the predicted value is 14%compared with the experimental value.This model provides the basis for the analysis and verification of the heat transfer of cement clinker in flowing state considering of particle rotation,and it also has some reference significance for the study on angular velocity of other particles.
作者
闻岩
鞠艳旭
黄泊霖
袁林
WEN Yan;JU Yanxu;HUANG Bolin;YUAN Lin(School of Mechanical Engineering,Yanshan University,Qinhuangdao 066004,China)
出处
《硅酸盐通报》
CAS
北大核心
2020年第7期2099-2105,共7页
Bulletin of the Chinese Ceramic Society
基金
国家自然科学基金(51076135)
河北省自然科学基金(E2018203398)。
关键词
熟料颗粒
角速度
BP神经网络
预测
clinker particle
angular velocity
BP neural network
prediction
