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引用本文:李伦竣,俞 博,胡旭东,陈 炜,徐郁山,方辽辽.影响织疵产生的灰色关联分析[J].软件工程,2024,27(7):52-55.【点击复制】
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影响织疵产生的灰色关联分析
李伦竣1, 俞 博1, 胡旭东1, 陈 炜2, 徐郁山3, 方辽辽1
(1.浙江理工大学机械工程学院, 浙江 杭州 310018;
2.浙江天衡信息技术有限公司, 浙江 绍兴 312500;
3.浙江康立自控科技有限公司, 浙江 绍兴 312500)
158778479@qq.com; 513665714@qq.com; xdhu@zstu.edu.cn; 1163995@qq.com; sales@kl-tec.com.cn; 1152862843@qq.com
摘 要: 织疵是衡量织造质量的关键指标。为了优化织造过程,减少织疵产生,首先分析了织造过程中导致织疵产生的影响因素,其次利用灰色关联分析法提取导致织疵产生的关键影响因素。实验和实际生产结果均表明,织机停车次数和停车时间对织疵产生数量的关联度较高,关联度均为0.83以上。同时,针对双纬、百脚和断经3类织疵进行分析,得出导致双纬产生的主要影响因素是经密和转速,导致百脚产生的主要影响因素是经停时间和转速,导致断经产生的主要影响因素是经停次数、打纬次数、停车时长等。
关键词: 织造;织疵;关键影响因素;灰色关联分析法
中图分类号: TP302.7    文献标识码: A
基金项目: 面向泵阀、低压电器、电梯等特色产业集群智能化提升的网络协同生产平台研发及应用-面向纺织产业集群智能化提升的网络协同生产平台研发及应用(2022C01202)
Analysis of Grey Correlation Affecting Woven Defects
LI Lunjun1, YU Bo1, HU Xudong1, CHEN Wei2, XU Yushan3, FANG Liaoliao1
(1.School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China;
2.Zhejiang Tianheng In f ormation Technology Co., Ltd., Shaoxing 312500, China;
3.Zhejiang Kangli Self-control Technology Co., Ltd., Shaoxing 312500, China)
158778479@qq.com; 513665714@qq.com; xdhu@zstu.edu.cn; 1163995@qq.com; sales@kl-tec.com.cn; 1152862843@qq.com
Abstract: Woven defect is a key indicator of textile quality. To optimize the weaving process and reduce defect formation, this study first analyzes the factors that contribute to woven defects during weaving. Then, the grey correlation analysis method is used to extract the key factors that affect woven defect formation. Both experimental and actual production results demonstrate that the frequency and duration of loom stoppages exhibit a high correlation with the quantity of the woven defects, and the correlation coefficient is above 0.83. Furthermore, analysis of three types of woven defects—double picks, mis-picks, and broken ends—reveals that yarn density and roating speed are primary factors influencing double pick formation, stoppage time and roating speed are major factors for mis-pick formation, and factors such as stoppage frequency, filling insertion frequency, and stoppage duration primarily contribute to broken end formation.
Keywords: weaving; woven defect; key influencing factors; grey correlation analysis


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