基于MIV-BP神经网络的成品烟丝质量预测模型构建  

Prediction model building for finished tobacco qualitybased on MIV-BP neural network

作　　者：卓鸣 汪鹏[1] 望开奎 ZHUO Ming;WANG Peng;WANG Kai-kui(China Tobacco Hubei Industrial Co.,Ltd.,Wuhan,Hubei 430040,China)

机构地区：[1]湖北中烟工业有限责任公司,湖北武汉430040

出　　处：《食品与机械》2021年第12期161-166,214,共7页Food and Machinery

基　　金：山东中烟工业有限责任公司科技项目(编号:201802013)

摘　　要：目的:构建卷烟制丝过程成品烟丝质量模拟预测模型。方法:使用平均影响值法(the Mean Impact Value,MIV)对制丝加工过程工艺参数进行筛选,然后通过反向传播(Back-Propagation,BP)神经系统构建起制丝关键工艺参数和成品烟丝质量的模拟模型。结果:通过模拟数据与实测数据比较,填充值的模拟预测平均相对误差为3.16%;整丝率的模拟预测平均相对误差为0.67%;碎丝率的模拟预测平均相对误差为5.33%。结论:该模型预测值与实测值之间相对误差较小,精确性高,该模型适用于卷烟制丝生产过程工艺参数仿真优化。Objective:The simulation and prediction model between the process of silk making and the quality of finished tobacco was established.Methods:The average influence value method was used to screen the process parameters in the process of making silk,and then a simulation model of the key process parameters of the silk and the quality of the final tobacco was constructed through the Back-Propagation neural network.Results:Comparing the simulated data with the measured data,the average relative error of the simulated prediction of the filling value was 3.16%;the average relative error of the simulated prediction of the whole cut rate was 0.67%;the average relative error of the simulated prediction of the broken cut rate was 5.33%.Conclusions:The relative error between the data predicted by this model and the real data is small,and the accuracy is high,which provides a theoretical basis and simulation method for the optimization of process parameters in the tobacco process.

关 键 词：平均影响值 BP神经系统 填充值 整丝率 碎丝率 预测模型 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TS47[自动化与计算机技术—控制科学与工程]