Journal of Textile Research ›› 2020, Vol. 41 ›› Issue (06): 141-146.doi: 10.13475/j.fzxb.20190801106

• Machinery & Accessories • Previous Articles     Next Articles

Online cheese package yarn density detection system based on machine vision

ZHANG Jianxin(), LI Qi   

  1. College of Mechanical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China
  • Received:2019-08-05 Revised:2020-02-25 Online:2020-06-15 Published:2020-06-28

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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

CLC Number: 

  • TS152.2

Fig.1

Composition of detection system"

Fig.2

Overall flow chart of on-line detection system for cheese yarn density"

Fig.3

Original image"

Fig.4

Side image of package yarn after preprocessing"

Fig.5

Model Image"

Fig.6

Correction model of a point on surface of cheese yarn"

Fig.7

Corrected side image of cheese yarn"

Fig.8

Density measurement results"

Fig.9

Relative error"

Tab.1

Stablity experimental results"

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
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