[1]邱益,郭柳冰,梁杰.主-被动混合控制的火电厂翻车机摘钩机器人系统设计[J].郑州大学学报(工学版),2026,47(5):17-25.[doi:10.13705/j.issn.1671-6833.2026.02.010]
　QIU Yi,GUO Liubing,LIANG Jie.Design of a Hybrid Active-Passive Control Robotic System for Coupler Unhooking in Thermal Power Plant Wagon Tippers[J].Journal of Zhengzhou University (Engineering Science),2026,47(5):17-25.[doi:10.13705/j.issn.1671-6833.2026.02.010]
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主-被动混合控制的火电厂翻车机摘钩机器人系统设计()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
47
期数:
2026年5期
页码:
17-25
栏目:
出版日期:
2026-09-09

文章信息/Info

Title:
Design of a Hybrid Active-Passive Control Robotic System for Coupler Unhooking in Thermal Power Plant Wagon Tippers
文章编号:
1671-6833(2026)05-0017-09
作者:
邱益,郭柳冰,梁杰
郑州大学 机械与动力工程学院,河南 郑州 450001
Author(s):
QIU Yi, GUO Liubing, LIANG Jie
School of Mechanical and Power Engineering, Zhengzhou University, Zhengzhou 450001, China
关键词:
摘钩机器人;  主被动构型;  D-H 法;  线激光
Keywords:
hook-unloading robot;  active-passive hybrid configuration;  D-H method;  line laser
分类号:
TP242. 2TP273
DOI:
10.13705/j.issn.1671-6833.2026.02.010
文献标志码:
A
摘要:
为解决火电厂翻车机卸煤系统中人工摘钩作业存在的环境恶劣、劳动强度大及安全隐患等问题，提出了一种主‑被动混合控制构型的翻车机摘钩机器人。首先，对机器人机械结构进行设计，其本体由3个主动移动副、1个主动旋转副、1个被动移动副和1个被动旋转副组成。随后，通过图解法分析被动结构的运动适应性，并采用D‑H方法建立了整机的正、逆运动学模型，为运动控制奠定理论基础。在控制系统方面，设计了硬件架构，并结合线激光位移传感器的测量数据，提出一种车钩手柄识别算法，可获取末端夹爪与车钩手柄之间的位置信息P_g(x_g,z_g)，实现手柄的精确定位与夹取。为验证方案的有效性，开展了中试实验。结果表明：在50次摘钩操作中，机器人摘钩成功率达到100%，且所有关节力矩均未超过额定值。摘取高位车钩平均用时25 s，摘取低位车钩平均用时为30 s，均满足生产要求。各关节最大瞬时力矩为62.1 N·m，仅占系统极限的43.7%，显示出充足的安全裕度。实验结果体现出所设计的机器人对车钩轨迹不确定性的自适应能力，能够适配不同车型或同车型的路径偏差，同时证明了所提识别算法的精确性。
Abstract:
To address the issues of harsh environmental conditions, high labor intensity, and safety risks in manual hook removal operations in thermal power plant tipper unloading systems, in this study a tipping machine hook‑removal robot with a hybrid active‑passive control configuration was proposed. Firstly, the mechanical structure of the robot was designed, with three active moving joints, one active rotating joint, one passive moving joint, and one passive rotating joint. The movement adaptability of the passive structure was analyzed using a graphical method, and the forward and inverse kinematic models of the entire system were established using the D‑H method, providing a theoretical foundation for motion control. In terms of the control system, a hardware architecture was designed, and a hook handle recognition algorithm was proposed, based on measurement data from a linear laser displacement sensor. This algorithm was used to obtain the position information P_g(x_g,z_g) between the end effector and the hook handle, enabling precise positioning and gripping of the hook handle. A pilot test was conducted to verify the effectiveness of the proposed solution. The results showed that out of 50 hook removal operations, the robot achieved a 100% success rate, with all joint torques within the rated limits. The average time for high‑position hook removal was 25 seconds, and 30 seconds for low‑position hooks, both meeting the production requirements. The maximum instantaneous torque at each joint was 62.1 N·m, only 43.7% of the system’s limit, demonstrating sufficient safety margin. The experimental results reflected the robot’s adaptive ability to handle trajectory uncertainties of hooks, allowing it to accommodate deviations in the path of different models or variations of the same model. Furthermore, the precision of the proposed recognition algorithm was validated.

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更新日期/Last Update: 2026-09-03