Research on Automatic Docking System of LNG Marine Loading Arm Based on Machine Vision

IF 5.2 2区 计算机科学 Q2 ROBOTICS
Zhicheng Ma, Yonghua Lu, Chuan Huang, Shigong Feng, Jing Chen
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引用次数: 0

Abstract

Liquefied Natural Gas is widely used as a clean energy source in production and daily life. The transfer of LNG between receiving terminals and cargo ships is accomplished using LNG marine loading arms. During the loading and unloading of LNG, the flange position on the LNG ship is typically determined manually, and the connection is controlled manually as well. This method is inefficient, dangerous, and its success rate and accuracy do not meet the demands of modern productivity. Moreover, there is limited research on the automatic docking system of LNG marine loading arm and their docking accuracy is not high. To address the need for automated docking of loading arms, this paper proposes a two-step positioning method, combining coarse positioning and fine positioning. It integrates deep learning, edge detection algorithms, and ellipse fitting algorithms to obtain the image coordinates of the flange center. The motion trajectory of the loading arm's end is planned and automatic docking is achieved through PID control. Through testing at the established experimental site, the system achieves a port recognition accuracy of 99.99%, with the maximum docking error of 7.79 mm and the average error of 5.80 mm, thus validating the feasibility of automatic docking for LNG loading arms.

Abstract Image

基于机器视觉的LNG船用装货臂自动对接系统研究
液化天然气作为一种清洁能源在生产和生活中得到了广泛的应用。LNG在接收站和货船之间的转移是使用LNG海上装载臂完成的。在LNG装卸过程中,LNG船上的法兰位置通常由人工确定,连接也由人工控制。这种方法效率低、危险性大,成功率和准确率都不能满足现代生产力的要求。此外,LNG船用装货臂自动对接系统研究有限,对接精度不高。针对装载臂自动对接的需要,本文提出了粗定位与精定位相结合的两步定位方法。它集成了深度学习、边缘检测算法和椭圆拟合算法来获取凸缘中心的图像坐标。规划装载臂末端的运动轨迹,通过PID控制实现自动对接。通过在已建立的实验现场进行测试,系统的端口识别精度达到99.99%,最大对接误差为7.79 mm,平均误差为5.80 mm,验证了LNG装载臂自动对接的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Field Robotics
Journal of Field Robotics 工程技术-机器人学
CiteScore
15.00
自引率
3.60%
发文量
80
审稿时长
6 months
期刊介绍: The Journal of Field Robotics seeks to promote scholarly publications dealing with the fundamentals of robotics in unstructured and dynamic environments. The Journal focuses on experimental robotics and encourages publication of work that has both theoretical and practical significance.
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