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Proceedings Paper

The research of knitting needle status monitoring setup
Author(s): Lu Liu; Xiao-qing Liao; Yong-kang Zhu; Wei Yang; Pei Zhang; Yong-kai Zhao; Hui-jie Huang
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Paper Abstract

In textile production, quality control and testing is the key to ensure the process and improve the efficiency. Defect of the knitting needles is the main factor affecting the quality of the appearance of textiles. Defect detection method based on machine vision and image processing technology is universal. This approach does not effectively identify the defect generated by damaged knitting needles and raise the alarm. We developed a knitting needle status monitoring setup using optical imaging, photoelectric detection and weak signal processing technology to achieve real-time monitoring of weaving needles’ position. Depending on the shape of the knitting needle, we designed a kind of Glass Optical Fiber (GOF) light guides with a rectangular port used for transmission of the signal light. To be able to capture the signal of knitting needles accurately, we adopt a optical 4F system which has better imaging quality and simple structure and there is a rectangle image on the focal plane after the system. When a knitting needle passes through position of the rectangle image, the reflected light from needle surface will back to the GOF light guides along the same optical system. According to the intensity of signals, the computer control unit distinguish that the knitting needle is broken or curving. The experimental results show that this system can accurately detect the broken needles and the curving needles on the knitting machine in operating condition.

Paper Details

Date Published: 19 September 2013
PDF: 7 pages
Proc. SPIE 8905, International Symposium on Photoelectronic Detection and Imaging 2013: Laser Sensing and Imaging and Applications, 89052B (19 September 2013); doi: 10.1117/12.2034928
Show Author Affiliations
Lu Liu, Shanghai Institute of Optics and Fine Mechanics (China)
Univ. of Chinese Academy of Sciences (China)
Xiao-qing Liao, Shanghai Institute of Optics and Fine Mechanics (China)
Yong-kang Zhu, Shanghai Institute of Optics and Fine Mechanics (China)
Wei Yang, Shanghai Institute of Optics and Fine Mechanics (China)
Pei Zhang, Shanghai Institute of Optics and Fine Mechanics (China)
Univ. of Chinese Academy of Sciences (China)
Yong-kai Zhao, Shanghai Institute of Optics and Fine Mechanics (China)
Univ. of Chinese Academy of Sciences (China)
Hui-jie Huang, Shanghai Institute of Optics and Fine Mechanics (China)
Univ. of Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 8905:
International Symposium on Photoelectronic Detection and Imaging 2013: Laser Sensing and Imaging and Applications
Farzin Amzajerdian; Astrid Aksnes; Weibiao Chen; Chunqing Gao; Yongchao Zheng; Cheng Wang, Editor(s)

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