基于关联规则的粗纱工序断头影响因素分析OACSTPCD

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.