基于神经网络的储纬器恒张力控制策略的设计与实现  

Design and Implementation of Constant Tension Control Solution of Weft Feeder based on Neural Network

作　　者：王凯旋 彭来湖[1] 胡旭东[1] WANG Kaixuan;PENG Laihu;HU Xudong(Key Laboratory of Modern Textile Equipment Technology,Zhejiang Sci-tech University,Hangzhou 310018,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

出　　处：《软件工程》2021年第9期51-54,共4页Software Engineering

摘　　要：纱线的张力控制对纺织品的质量具有重要意义,针对纺织过程中纱线的张力波动大、非线性等问题,提出了基于神经网络的储纬器恒张力控制策略。将神经网络应用于储纬器控制算法,实时调整权重分配,提高性能,再将矢量控制应用于储纬器的电机控制,实现良好的电机控制效果,最终实现纱线张力的稳定控制。经测试表明:该纱线控制策略实时性良好,纱线张力控制精确稳定,能够有效实现储纬器的恒张力控制。Tension control of the yarn is of great significance to the quality of textiles.Aiming at the problems of large fluctuations and non-linearity of the yarn tension during the weaving process,this paper proposes a constant tension control solution for the weft feeder based on neural network.Neural network is applied to the weft feeder control algorithm and weight distribution is adjusted in real time,so to improve system performance.Then,vector control is applied to motor control of the weft feeder to achieve a good motor control effect,and stable control of the yarn tension is finally realized.Tests show that the proposed yarn control solution has good real-time performance,precise and stable yarn tension control,and can effectively control the constant tension of the weft feeder.

关 键 词：储纬器 恒张力控制 神经网络 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]