基于神经网络MIV算法的烟叶加料均匀性预测分析

doi:10.16180/j.cnki.issn1007-7820.2019.10.008

Abstract

Abstract:

In order to predict and analyze the uniformity of tobacco leaf feeding under different working conditions, a method based on MIV algorithm was proposed in this paper. The neural network training was carried out on the process parameters of tobacco leaf feeding, and the correlation between each parameter and feeding uniformity was calculated by using MIV. The key index influencing the uniformity of feeding was found, and the error was less than 5%. The key indexes that affected the uniformity of feeding were the opening of discharge, process flow, gas pressure and feed liquid flow. The discharge opening, industrial flow and feed liquid flow were negatively correlated with the feeding uniformity. The gas pressure was positively related to the uniformity of feed. The neural network obtained by MIV method was more predictive.

Key words: neural network, MIV, prediction, feeding uniformity, tobacco feeding, MATLAB

CLC Number:

TP183

CHEN Lin,YUAN Ruibo. Forecast and Analysis of Tobacco Leaf Feeding Uniformity Based on Neural Network MIV Algorithm[J].Electronic Science and Technology, 2019, 32(10): 39-42.

Figures/Tables 7

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Table 1

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References 16

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	排潮开度	滚筒转速	工艺流量	气体温度	气压	料液温度	料液流量
均匀性1	-1.56	-0.14	-1.18	0.10	1.12	0.09	-0.98
均匀性2	-1.24	-0.09	-1.23	0.12	1.08	0.06	-0.89
均匀性3	-1.01	-0.09	-0.91	0.05	0.89	0.03	-0.12
均匀性4	-1.22	-0.18	-1.45	0.16	1.69	0.11	-1.02
均匀性5	-1.60	-0.11	-1.22	0.20	1.02	0.08	-0.97

Forecast and Analysis of Tobacco Leaf Feeding Uniformity Based on Neural Network MIV Algorithm

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