Wang Yan, Wang Lei, Li Dalin, Liang Yanchun, Huang Lan, Da Haoming, Yang Hui
College of Computer Science and Technology, Jilin University, Changchun 130012, China.
School of Computer Science, Zhuhai College of Science and Technology, Zhuhai 519041, China.
Heliyon. 2024 Aug 12;10(18):e35998. doi: 10.1016/j.heliyon.2024.e35998. eCollection 2024 Sep 30.
In a kind of precision industrial equipment, small diameter abreast optical fibers are used for high-speed communication among functional nodes. The arrangement order at both terminals of the abreast optical fibers need to comply with communication protocols. In this paper, we propose an automatic terminal sequence consistency verification method based on computer vision. The Hue Saturation Value (HSV) color space is used for improving the image feature extraction capability. An abreast optical fiber sequence dictionary which converts the protocol logic into an input-output mapping table is provided to follow protocol confidentiality and improve inspecting speed. A light control baffle position adaptive algorithm is designed for improving the accuracy of optical fiber incident light control. The experimental results show that the method can achieve the conductivity inspection of 1 optical fiber every 50 seconds, and the inspection accuracy is over 96.5%, which generally improves the inspection efficiency by 45% compared with manual inspection.
在一种精密工业设备中，小直径并排光纤用于功能节点之间的高速通信。并排光纤两端的排列顺序需要符合通信协议。本文提出了一种基于计算机视觉的自动终端序列一致性验证方法。采用色调饱和度值（HSV）颜色空间来提高图像特征提取能力。提供了一个将协议逻辑转换为输入输出映射表的并排光纤序列字典，以遵循协议保密性并提高检测速度。设计了一种光控挡板位置自适应算法，以提高光纤入射光控制的精度。实验结果表明，该方法每50秒可实现1根光纤的导通性检测，检测精度超过96.5%，与人工检测相比，检测效率普遍提高了45%。
