用于天然气分离器的多自由度工业机器人清洗装备设计与试验研究

Design and experimental study of a multi-degree-of-freedom industrial robotic cleaning system for natural gas separators

  • 摘要: 针对石油天然气输配系统中天然气分离器等密闭高危设备内部存在的结构复杂、空间狭小和作业风险高等清洗作业难题,提出了一种基于差速-连杆复合机构驱动的多自由度工业机器人清洗装备系统设计方案。该系统采用模块化构型,融合旋转云台、差速齿轮组与多连杆联动机构,实现了喷淋装置在复杂工业设备内部空间的高可达性与柔性轨迹控制。针对系统核心机构,建立了差速-连杆复合机构的运动学模型与动力学分析模型,揭示了末端喷头姿态与机械臂主梁运动的几何协调规律,为系统的精确控制提供了理论基础。设计了基于STM32F407嵌入式平台的协同控制系统,通过无线通信实现远程控制,满足工业环境中对安全性与高效性的严格要求。通过搭建实验平台进行性能测试,结果表明该系统能够实现设备内部清洗覆盖率超过90%,重复定位精度优于±1.5 mm,具备良好的清洗一致性与环境适应性。研究成果为工业设备,尤其是密闭空间设备的智能化清洗提供了可行的工程实现路径,并为多自由度工业机器人智能清洗系统的设计与控制方法研究提供了理论支撑。

     

    Abstract: To address the challenges of cleaning operations in confined and hazardous environments within natural gas transmission and distribution systems, such as natural gas separators with complex internal structures, limited operating space, and high operational risks, a multi-degree-of-freedom industrial robotic cleaning system driven by a differential-linkage hybrid mechanism is proposed. The system adopts a modular architecture integrating a rotary platform, differential gear assembly, and multi-linkage actuation structure, enabling high accessibility and flexible trajectory control of the spray unit within intricate internal geometries of industrial equipment. A kinematic and dynamic model of the core mechanism is developed to elucidate the geometric coordination between the end-effector posture and the main beam motion of the robotic arm, thereby providing a theoretical foundation for precise trajectory control. A collaborative control system based on the STM32F407 embedded platform is implemented, with wireless communication enabling remote operation and meeting the stringent safety and efficiency requirements of high-risk industrial scenarios. Experimental validation conducted on a prototype system demonstrates a cleaning coverage rate exceeding 90% and a repeatability error within ±1.5 mm, confirming good cleaning consistency and environmental adaptability. The results offer a practical engineering pathway for intelligent cleaning of industrial equipment, particularly those in sealed and hazardous environments, and contribute theoretical and technical insights into the design and control of multi-degree-of-freedom robotic cleaning systems for specialized applications in the oil and gas industry.

     

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