基于BP神经网络的烟草制丝工艺参数优化研究

付永民; 范磊; 李长进; 吴庆华

doi:10.12187/2023.05.014

October 2023

Article Contents

FU Yongmin, FAN Lei, LI Changjin and et al. Research on optimization of tobacco silk processing parameters based on BP neural network[J]. Journal of Light Industry, 2023, 38(5): 104-111. doi: 10.12187/2023.05.014

Citation: FU Yongmin, FAN Lei, LI Changjin and et al. Research on optimization of tobacco silk processing parameters based on BP neural network[J]. Journal of Light Industry, 2023, 38(5): 104-111. doi: 10.12187/2023.05.014 shu

Research on optimization of tobacco silk processing parameters based on BP neural network

Xuchang Cigarette Factory, Henan China Tobacco Industry Co., Ltd., Xuchang 461000, China

Received Date: 2021-12-28
Accepted Date: 2022-03-22

Abstract

In order to improve the quality of tobacco silk, the processing parameters of tobacco silk were optimized by using BP Neural Network (BPNN), taking the physical properties of tobacco silk, the physical properties of cigarettes and the chemical composition of cigarettes as quality control indicators. The BPNN optimization results were compared with the orthogonal test results, and the optimized parameters were verified. The results showed that the prediction results of the established BPNN model had high reliability and accuracy, and the optimal silk-making processing parameters combination predicted by BPNN was unique and accurate. There were differences in the parameter settings of steam flow and hot air temperature for the optimal combination of tobacco silk-making process parameters obtained by the orthogonal test method. After the parameters of the tobacco silk-making processing parameters were optimized, the whole cut rate and filling value of tobacco silk had been improved, the broken cut rate had been reduced, the standard deviation of single cigarette weight and cigarette suction resistance had decreased, and the CO, tar, and nicotine releases had been reduced, and the overall optimization effect was obvious. BPNN accurately predicted the optimal parameters of tobacco silkmaking, which avoided misjudgment, improved processing efficiency, and reduced time cost and resource waste.
- tobacco silk,
- quality control,
- BP neural network,
- orthogonal test,
- physical properties of tobacco silk
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Research on optimization of tobacco silk processing parameters based on BP neural network

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