基于大数据的叶丝干燥过程内在规律挖掘  

Mining Inherent Law of Cut Tobacco Drying Process Based on Large Data

作　　者：唐军 何邦华 唐丽 温亚东 陈文 付亮 周冰 TANG Jun;HE Banghua;TANG Li;WEN Yadong;CHEN Wen;FU Liang;ZHOU Bing(Technology Center,China Tobacco Yunnan Industrial Co.,Ltd.,Kunming 650231,China)

机构地区：[1]云南中烟工业有限责任公司技术中心

出　　处：《中国农业科技导报》2019年第12期94-101,共8页Journal of Agricultural Science and Technology

基　　金：云南中烟工业有限责任公司科技计划项目(2015CP02);烟草行业卷烟工艺与装备研究重点实验室2017年开放课题(2017GYSYS04)

摘　　要：为挖掘卷烟生产过程数据的潜在价值和规律,采用大数据分析方法,对2017年叶丝干燥工序生产数据进行挖掘与分析,着重分析了重点质量指标和工艺参数的稳定性,及工艺参数与质量指标的内在关系。结果表明:①重点质量指标稳定性控制水平从高到低的顺序为冷却出口含水率M岀口温度M出口含水率,其中6月份波动较大;②重点工艺参数稳定性控制水平从高到低的顺序为I区筒壁温度M热风温度Mil区筒壁温度,其中II区筒壁温度的波动主要是反馈控制模式所造成的;③冷却出口含水率与负压、I区筒壁温度、I区筒壁蒸汽阀门开度具有较强的正相关关系,与叶丝增温增湿膨胀单元蒸汽流量、SX蒸汽阀门开度和II区筒壁温度、II区筒壁蒸汽阀门开度、排潮阀门开度具有较强的负相关性;④出口温度与所考察的各工艺参数之间均无明显的相关性;⑤建立了叶丝干燥冷却出口含水率预测模型,具有较好的预测精度。可以预见,大数据分析方法将在烟草工艺领域中具有较好的应用前景。In order to mine and analyze potential values and rules of the data of cigarette production process, theproduction data of cut tobacco drying process were excavated and analyzed based on the analytic technology andmethod of large data. The stabilities of the key quality indexes and process parameters of cut tobacco drying processwere mostly analyzed, and the internal relationship between quality indexes and process parameters as well. Resultsshowed that:① The stability control level of key quality indexes was determined as from high to low, dischargemoisture content after cooling discharge temperature M discharge moisture content, and there was great fluctuation inJune.② The stability control level of key process parameters was determined as from high to low, wall temperature ofI areaMhot air temperaturewall temperature of II area, and the fluctuation of wall temperature of II area was mainlycaused by feedback control mode.③ There were strong positive correlations between the discharge moisture contentafter cooling and negative pressure, wall temperature of I area, steam valve opening of I area, and strong negativecorrelations between the discharge moisture content after cooling and the steam flow of expansion unit, steam valveopening of SX, wall temperature of II area, steam valve opening of II area, opening of moisture exhaust valve.④ There were no obvious correlation between discharge temperature and these process parameters considered inpresent study.⑤ The prediction model of discharge moisture content after cooling was established, which had goodprediction accuracy. It could be predicted that the large data analysis method would have a good application prospectin tobacco technology field.

关 键 词：大数据 叶丝干燥 内在规律 数据挖掘 预测模型 

分 类 号：S572[农业科学—烟草工业] TS452[农业科学—作物学]