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作 者:李杨 彭来湖[1,2] 刘建廷 胡旭东[1] 郑秋扬 LI Yang;PENG Laihu;LIU Jianting;HU Xudong;ZHENG Qiuyang(Key Laboratory of Modern Textile Machinery&Technology of Zhejiang Province,Zhejiang Sci-Tech University,Hangzhou,Zhejiang 310018,China;Zhejiang Sci-Tech University Longgang Research Institute Co.,Ltd.,Wenzhou,Zhejiang 325000,China)
机构地区:[1]浙江理工大学浙江省现代纺织装备技术重点实验室,浙江杭州310018 [2]浙江理工大学龙港研究院有限公司,浙江温州325000
出 处:《纺织学报》2023年第6期72-77,共6页Journal of Textile Research
基 金:浙江省博士后科研项目特别资助项目(ZJ2020004)。
摘 要:为高效、便捷地检测纱线张力,构建了一种基于横向振动频率的非接触检测纱线张力方法。利用弦振动原理推导出纱线横向振动方程,根据纱线振动方程计算纱线振动频率。以轴向运动纱线的张力、速度和频率的拟合公式,通过测量纱线的振动频率可方便快捷地计算出纱线张力。将计算结果经过广义回归神经网络(GRNN)模型进行拟合,进一步提高测量结果的准确性。采用高速相机测量纱线的横向振动位移,并检测纱线的振动频率。利用频率法对32 tex纱线在设定张力分别为40和60 cN,速度分别为6和2 m/s时的张力进行测量。结果表明,利用振动频率测量纱线张力的数据经GRNN拟合,其曲线整体趋势与张力传感器测量的张力趋势相同且更加平滑,便于对生产过程中张力的控制,该方法具有有效性和准确性。Objective In the process of textile production,constant yarn tension is essential to ensure product quality,and excessive tension during yarn transmission will cause sudden stress change or even yarn breakage and will affect fabric formation,resulting in inelastic fabric structure and seriously affecting the quality of products.In order to detect yarn tension efficiently and conveniently,a method based on transverse vibration frequency non-contact detection of yarn tension is developed.Method The transverse vibration characteristics of a moving yarn were studied by combining theoretical modeling,numerical analysis and experimental verification.The equation of yarn transverse vibration was derived based on chord vibration theory,and the yarn vibration frequency was obtained.The yarn tension was further calculated according to the relationship between frequency and tension.A yarn tension measurement method based on transverse vibration frequency measurement was proposed,and an open structure yarn transmission experimental platform was designed and built for experimental verification.The measured values were fitted to the generalized regression neural network model.Results When the linear density is constant,the yarn vibration frequency increases with the increasing velocity;the greater the linear density,the smaller the yarn vibration frequency.First,the geometric parameters of the moving yarn are determined,and the fitting formula among the yarn motion speed,vibration frequency and tension is established.Then,the yarn vibration frequency and velocity data were obtained experimentally,and the vibration frequency and motion velocity were substituted into the fitting formula to obtain the yarn tension.Finally,the calculated yarn tension was fitted using the GRNN model to obtain the final tension results.The data generalized regression neural network fitting curve using the vibration frequency for measuring the yarn tension is on the same overall trend as the tension trend measured by the tension sensor(Fig.5 and Fig.
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