基于物联网大数据分析的卷烟包装工艺参数自优化研究

Study on the self-optimization of cigarette packaging process parameters based on big data analysis of Internet of things

为避免因卷烟包装工艺参数误差较大而出现卷烟落丝量高、整丝率低的现象,利用物联网大数据分析技术,对卷烟包装工艺参数进行优化。首先利用物联网技术设计大数据分析模型;然后结合固定分类规则提取蒸梗含水率、浸梗水槽温度等卷烟包装工艺参数,通过数据关联挖掘参数间的内在关联,寻求工艺参数的最优组合,实现对卷烟工艺参数的优化设计。实验结果表明:该方法对包装数据处理的性能较好,参数提取效率和准确率较高,且对卷烟蒸梗含水率的预估误差较小。应用该方法后,端部落丝量约为优化前的1/2,烟卷整丝率明显提高,使得烟丝物理性能和卷烟感官质量明显提升。

In order to avoid the phenomenon of high dropping quantity and low rate of whole tobacco due to the large error of cigarette packaging process parameters,the big data analysis technology of internet of things is used to optimize the cigarette packaging process parameters.First,the big data analysis model is designed by using the Internet of things technology.Then,the fixed classification rules are used to extract the cigarette packaging process parameters,such as moisture content of steam stem,temperature of stem soaking tank,etc.Through the data correlation,the internal correlation between the parameters is explored.The optimal combination of process parameters is sought to achieve the optimal design of cigarette process parameters.The experimental results show that this method has better performance in packaging data processing,higher efficiency and accuracy in parameter extraction,and smaller error in predicting moisture content of cigarette stem.After the application of this method,the amount of end tribe silk is about 1/2 of that before optimization,and the whole silk rate of cigarette is obviously improved,which makes the physical properties of tobacco and the sensory quality of cigarette significantly improved.