基于关联规则的粗纱工序断头影响因素分析

Influence factor analysis of roving process broken ends based on association rule

为了降低粗纱在生产过程中的断头率,提高纱线生产质量和效率,通过生产实践收集纺制C 14.6 tex和JC 24.3 tex两个品种的粗纱工序断头影响因素。使用K⁃means聚类算法对影响因素指标分别进行聚类,然后使用Apriori算法将聚类后的断头影响因素指标数据集进行关联规则挖掘。结果表明:纺制C 14.6 tex品种的粗纱工序断头影响因素关联规则有粗纱回潮率和末并定量湿重,粗纱条干CV和末并定量湿重,末并定量湿重和粗纱条干CV;纺制JC 24.3 tex品种的粗纱工序断头影响因素关联规则有粗纱捻系数和粗纱定量湿重,粗纱捻系数、粗纱条干CV和粗纱定量湿重,粗纱定量湿重和粗纱捻系数;当关联规则中的影响因素同时升高时,粗纱工序断头率增加。通过关联规则中挖掘出的信息,可为纺纱企业减少粗纱工序断头、提高纱线质量提供帮助。

In order to reduce the breakage rate of roving during the production process and improve the quality and efficiency of yarn production,the influence factors of roving process broken ends of C 14.6 tex and JC 24.3 tex yarn were collected in production.The influencing factor indicators were clustered by K-means clustering algorithm,Apriori algorithm was used to mine the association rules of the clustered breakage influencing factor indicator datasets.The results showed that the association rule of factors affecting of roving process broken in spinning C 14.6 tex yarn included roving moisture regain and the final doubling wet weight,the roving evenness CV and the final doubling wet weight,the final doubling wet weight and the yarn evenness CV.The association rule of factors affecting of roving process broken in spinning JC 24.3 tex yarn included roving twist coefficient and roving quantitative wet weight,roving twist coefficient,roving evenness CV and roving quantitative wet weight,roving quantitative wet weight and roving twist coefficient.When the influence factors of association rules were increased at the same time,the breakage rate of roving process was increased.The information mined from association rules could help spinning enterprises to reduce broken ends in roving process and improve yarn quality.