基于机器视觉的筒子纱密度在线检测系统

doi:10.13475/j.fzxb.20190801106

摘要/Abstract

摘要：

为提高筒子纱密度检测自动化程度,解决传统筒子纱密度测量方法效率低、操作复杂等问题,设计了一种基于机器视觉的筒子纱密度在线检测系统。该系统由质量传感器、光电传感器、蓝色面光源、工业摄像机、传送装置和工控机组成。研究了筒子纱图像校正算法,根据透视投影理论建立了筒子纱校正模型,还原了筒子纱上下边界的直线特性,得到了理想的筒子纱侧面图像,用积分法得到筒子纱的精确体积。150个筒子纱密度检测结果表明:通过像素当量折算出筒子纱实际最大直径和体积参数,再结合高精度质量传感器的数据,最终可计算出筒子纱密度,基于机器视觉的筒子纱密度在线检测系统的检测精度和稳定性能可满足生产要求。

关键词: 筒子纱密度, 机器视觉, 在线检测, 筒子纱校正模型

Abstract:

In order to solve the problems of low efficiency and complex operation of the traditional measurement methods of package density, and improve the automation of the detection of package density, an on-line detection system for cheese package yarn density based on machine vision was designed. The system consists of a weight sensor, a photoelectric sensor, a blue light source, an industrial camera, a transmission device and an industrial computer. This research studied the image correction algorithm of the package yarn, established the package yarn correction model according to the perspective projection theory, restored the linear characteristics of the upper and lower boundaries of the package yarn, obtained the ideal side image of the package yarn, and achieved the accurate volume of the package yarn by the integration method. Through testing yarn density of 150 cheese packages, it is shown that the yarn density is able to be calculated by combining the weight data of high-precision weight sensor through converting the actual maximum diameter and volume parameters to pixel equivalent. The work illustrates that the detection system is able to detect the yarn package density online with acceptable detection accuracy and stability.

Key words: cheese yarn package density, machine vision, on-line detection, cheese yarn corrected model

中图分类号:

TS152.2

张建新, 李琦. 基于机器视觉的筒子纱密度在线检测系统[J]. 纺织学报, 2020, 41(06): 141-146.

ZHANG Jianxin, LI Qi. Online cheese package yarn density detection system based on machine vision[J]. Journal of Textile Research, 2020, 41(06): 141-146.

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参考文献 20

[1]	丛树筠. 涤棉筒子纱染色工艺条件与质量关系浅析[J]. 北京纺织, 1989(6):21-25.
	CONG Shuyun. Preliminary analysis on the relation between dyeing process conditions and quality of polyester/cotton cheese yarn[J]. Beijing Textile, 1989(6):21-25.
[2]	郝霄鹏, 杨建成. 络筒机筒子卷绕密度分析研究[J]. 纺织机械, 2004(5):15-17.
	HAO Xiaopeng, YANG Jiancheng. Research on winding density of winder drum[J]. Textile Machinery, 2004(5):15-17.
[3]	王元昌, 翁云菊. 筒子卷绕密度的计算[J]. 无锡轻工大学学报, 1999(4):99-103.
	WANG Yuanchang, WENG Yunju. The calculation of winding density of cheese[J]. Journal of Wunxi University of Light Industry, 1999(4):99-103.
[4]	刘增川. 筒子纱紧密度测量仪:中国,202393663U[P]. 2012-08-22.
	LIU Zengchuan. Drum yarn density meter:CN202393663U[P]. 2012-08-22.
[5]	MOSER B V, SRDAN M D. Method for investigating the quality of the yarn winding density on a yarn bobbin: EP2497734[P]. 2015-05-13.
[6]	陆兴华, 魏盼. 基于机器视觉的柱状弹簧质量综合检测系统[J]. 工具技术, 2017,51(12):110-114.
	LU Xinghua, WEI Pan. Quality measuring system of cylindrical spring based on machine vision[J]. Tool Engineering, 2017,51(12):110-114.
[7]	崔凌燕. 基于机器视觉的眼镜镜片轮廓提取系统[D]. 太原:中北大学, 2018: 3-5.
	CUI Lingyan. The contour extraction system of glass lens based on machine vision[D]. Taiyuan:North Universty of China, 2018: 3-5.
[8]	冀瑜. 基于机器视觉的高精度尺寸检测技术及应用研究[D]. 北京:中国计量科学研究院, 2006: 45-46.
	JI Yu. Research on high precision dimension detection technology and application based on machine vision[D]. Beijing:Chinese Academy of Metrology, 2006: 45-46.
[9]	陈芳. 大尺寸零件在线视觉测量关键技术研究[D]. 南京:东南大学, 2015: 3-8.
	CHEN Fang. Study on key technologies of online vision measurement for large cale parts[D]. Nanjing:Southeast University, 2015: 3-8.
[10]	赵立阳. 基于数字图像处理技术的智能纱线检测系统的开发与应用[D]. 长春:吉林大学, 2014: 36-37.
	ZHAO Liyang. Development and application of intelligent yarn detection system based on digital image processing technology[D]. Changchun:Jilin University, 2014: 36-37.
[11]	盛遵冰. 机器视觉图像检测与定位系统关键技术研究[D]. 哈尔滨:哈尔滨工业大学, 2009: 22-23.
	SHENG Zunbing. Research on key technologies of machine vision image inspection and positioning system[D]. Harbin:Harbin Institute of Technology, 2009: 22-23.
[12]	许光明, 吴昭, 周春兰, 等. 基于视觉的零件尺寸测量[J]. 工业控制计算机, 2015,28(4):111-113.
	XU Guangming, WU Zhao, ZHOU Chunlan, et al. Size measurement of parts based on vision technology[J]. Industrial Control Computer, 2015,28(4):111-113.
[13]	GUO Qingzhou. Distortion model selecting and accuracy evaluation for CCD camera calibration[C]// Proceedings of 3rd international conference on signal processing(ICSP'96). Beijing:IEEE, 1996: 86-89.
[14]	王向军, 白皓月, 吴凡璐, 等. 基于改进球面透视投影的鱼眼图像畸变校正方法[J]. 图学学报, 2018,39(1):43-49.
	WANG Xiangjun, BAI Haoyue, WU Fanlu, et al. Fish eye lens distortion correction method based on improved pherical perspective projection[J]. Journal of Graphics, 2018,39(1):43-49.
[15]	NIE H M . Research on camera calibration basing OpenCV[C]// Proceedings of the 2014 international conference on informatics, networking and intelligent computing(INIC 2014).Shanghai:Advanced Science and Industry Research Center, 2014: 26-29.
[16]	王伟, 何卫平, 郭改放, 等. 基于标定的任意半径柱面上二维条形码畸变校正[J]. 中国图象图形学报, 2014,19(1):69-75.
	WANG Wei, HE Weiping, GUO Gaifang, et al. Restoration of distorted 2D barcode marked on arbitrary radius cylinder based on calibrated camera[J]. Journal of Image and Graphics, 2014,19(1):69-75.
[17]	何博侠, 张志胜, 徐孙浩, 等. 大尺寸机械零件的机器视觉高精度测量方法[J]. 中国机械工程, 2009,20(1):5-10.
	HE Boxia, ZHANG Zhisheng, XU Sunhao, et al. Research on high-precision machine vision measurement method for large scale parts[J]. China Mechanical Engineering, 2009,20(1):5-10.
[18]	孙钊, 许增朴, 王永强, 等. 机器视觉测量中透视投影误差分析控制与补偿[J]. 计算机工程与应用, 2018,54(2):266-270.
	SUN Zhao, XU Zengpu, WANG Yongqiang, et al. Control and compensation of perspective projection error analysis in machine vision measurement[J]. Computer Engineering and Applications, 2018,54(2):266-270.
[19]	闫霞. 基于机器视觉的体积测量系统研究[D]. 洛阳:河南科技大学, 2011: 48-52.
	YAN Xia. Study of volume measurement system based on machine vision[D]. Luoyang:Henan University of Science and Technology, 2011: 48-52.
[20]	李志荣, 陶跃珍, 王东, 等. 任意截面旋转体体积计算公式研究及应用[J]. 机械设计, 2012,29(7):93-96.
	LI Zhirong, TAO Yuezhen, WANG Dong, et al. Research and application on volume calculation formula of rotating body with arbitrary section[J]. Journal of Machine Design, 2012,29(7):93-96.

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序号	密度参考值/(g·cm^-3)	稳定性系数
1	0.465	0.012
2	0.470	0.014
3	0.467	0.021
4	0.488	0.006
5	0.452	0.003
6	0.500	0.022
7	0.498	0.039
8	0.458	0.003
9	0.477	0.031
10	0.455	0.030