Laser & Optoelectronics Progress, Volume. 57, Issue 8, 081505(2020)

Optical Cable Pitch Detection Method Based on Machine Vision

Zhipeng Wu1, Danping Huang1、*, Kang Guo2, Jianping Tian1, Licheng Wu3, and Shaodong Yu1
Author Affiliations
  • 1College of Mechanical Engineering, Sichuan University of Science & Engineering, Yibin, Sichuan 644000, China;
  • 2Caihong (Hefei) LCD Glass Co., Ltd., Hefei, Anhui 230000, China
  • 3Hebei Economy Management School, Shijiazhuang, Hebei 0 50000, China
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    Traditional length-measurement methods cannot detect pitch. Accordingly, in this work, an optical cable pitch detection method based on machine vision is proposed. This method uses a laser velocimeter for detecting the speed of a production line and generates corresponding pulses to trigger the acquisition information by an industrial camera. A detection system was built by combining low angle with backlight illumination. Furthermore, a preprocessing operation was used to solve the instability of overlapping geometric properties of gray levels. To improve the positioning accuracy, an automatic template construction method is proposed to effectively construct matching templates. A template partition precise-positioning method was used to solve the problem of direct matching misjudgment; then the commutation point was matched and identified and the pitch length was detected. Theoretical analysis and experimental verification reveal that the error between the measured and standard pitch results is within 0.02-0.10 mm, which meets engineering requirements, and the system runs steadily and reliably. The proposed method provides a new way to detect optical cable pitch.

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    Zhipeng Wu, Danping Huang, Kang Guo, Jianping Tian, Licheng Wu, Shaodong Yu. Optical Cable Pitch Detection Method Based on Machine Vision[J]. Laser & Optoelectronics Progress, 2020, 57(8): 081505

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    Paper Information

    Category: Machine Vision

    Received: Aug. 16, 2019

    Accepted: Sep. 24, 2019

    Published Online: Apr. 3, 2020

    The Author Email: Huang Danping (hdpyx2002@163.com)

    DOI:10.3788/LOP57.081505

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