摘要
为解决目前接触式纱线张力检测易对纱线运动产生干扰的现状,设计了基于图像处理的非接触式纱线张力测量系统。使用高速相机结合纱线弦振动理论基础和图像处理技术采集运动状态纱线图像信息。利用奇异值分解算法通过视频图像数据降维、重组振动位移提取、迭代去噪等操作获取振幅频率信息。借助快速傅里叶变换将纱线振动时域特性转换为频域特性并绘制频域图及时域图,最后搭建纱线振动监测实验平台检验算法的可行性和可靠性。结果表明:纱线张力和纱线频率具有正相关性,当纱线张力在50~80 cN之间时,通过对比实验得到算法求解的纱线张力与实际测量的张力绝对误差小于10%,可较好地反映纱线实时张力情况。基于机器视觉的非接触式纱线张力具有安装简单,实时性强,精度高等特点,避免了接触式张力测量方法存在的损伤纱线和测量精度受工艺环境干扰等弊端。
Objective Yarn tension is closely related to product quality and production efficiency.The size and stability of tension run through each process from spinning to manufacturing.The excessive tension of yarn will lead to irreversible deformation of yarn,which will not only increase the yarn breaking rate,but also affect the mechanical strength,surface performance,dyeing performance and process structure of the fabric.The excessive tension of yarn will lead to poor formation of fabric organization,poor structure and poor elasticity.Modern technology requires the size and stability of yarn tension is increasingly high,so it is extremely important to realize the real-time measurement of yarn tension in operation.Method The singular value decomposition(SVD)algorithm is adopted to obtain the amplitude frequency information by reducing the dimension of video image data,recombining vibration displacement extraction,and iterative denoising.With the help of fast Fourier transform,the yarn vibration time domain characteristics are converted into frequency domain characteristics and draw the frequency domain map,and finally,the yarn vibration monitoring experiment platform is built to test the feasibility and reliability of the algorithm.Results An experimental set-up was built and experimentally verified to test the feasibility and reliability of the provided scheme.Different yarn running speeds were set and the experimentally derived tensions were compared with the measured tension magnitudes during yarn movement.The results indicated that when the speed of yarn movement was increased,the vibration amplitude of the yarn became smaller,the vibration frequency of the yarn larger,and the tension of the yarn larger.The tension of the yarn and the vibration frequency of the yarn were positively correlated,which is consistent with the theoretical equation of yarn vibration.Statistical results of yarn tension calculated by conventional image processing showed that when the yarn motion speed was 50-70 mm/s,the experimental value of yarn tension was close to the measured value of yarn tension with an absolute error of no more than 4%.However,when the yarn speed exceeded 75 mm/s.the yarn was irreversibly deformed due to the excessive tension and friction between the yarn and mechanical structure such as yarn guide wheels,and the yarn demonstrated a sudden change in the linear density,resulting in an absolute error of more than 10%occurs between the experimental and test values.The algorithm was computationally fast and accurate,and the yarn tension could be measured in real time with good performance.Conclusion The results of experiments show that the non-contact yarn tension measurement based on machine vision successfully solves the problem of inaccurate tension values caused by the contact between the yarn and the measuring element during the contact yarn tension measurement,and the measurement accuracy can meet the performance requirements of most textile processes for yarn tension.
作者
蒋静
彭来湖
史伟民
袁豪伟
JIANG Jing;PENG Laihu;SHI Weimin;YUAN Haowei(School of Mechanical Engineering,Zhejiang Sci-Tech University,Hangzhou,Zhejiang 310018,China;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,Wenzhou,Zhejiang 325000,China)
出处
《纺织学报》
EI
CAS
CSCD
北大核心
2024年第9期204-211,共8页
Journal of Textile Research
关键词
奇异值分解算法
纱线振动
图像处理
纱线张力
非接触式检测
singular value decomposition algorithm
yarn vibration
image processing
yarn tension
non-contact detection
