Response analysis and experimental research on control characteristics of pipeline intelligent plugging robot autonomous plugging hydraulic system
APPLIED OCEAN RESEARCH(2024)
摘要
To efficiently and accurately complete the plugging task and enable rapid maintenance and repair operations of submarine pipelines by pipeline intelligent plugging robot (PIPR), this study innovatively designs an autonomous plugging hydraulic control system for PIPR. Based on this, the simulation is used to confirm the viability of the control system, and the changes in displacement, flow, speed, and load of the control system are analyzed. A plugging hydraulic control experimental device was built to study the changes in hydraulic cylinder parameters and axial displacement of the rubber cylinder during the plugging process, as well as the influence of the law of different output flow rates on the plugging speed. The results show that the control cycle of the designed hydraulic control system can make the robot's actuators operate in an orderly manner without interference, and the displacement, flow, and speed of the hydraulic cylinders are consistent with the theoretical design values. When the rubber cylinder deformation axial displacement reaches 50.1 mm, the rubber cylinder enters the constrained deformation stage, and the axial displacement reaches 61.55 mm, the system can realize 10 MPa pressure oil and gas plugging. The hydraulic system flow rate has a significant effect on the plugging speed, as the flow rate of the hydraulic system increases, the rate at which the hydraulic cylinder squeezes the rubber cylinder reaches the axial displacement standard of 61.55 mm increases, but the growth trend gradually slows. This study provides data reference and theoretical guidance for the design of autonomous plugging control system of PIPR, which is an important guideline for the research and development of PIPR.
更多查看译文
关键词
Pipeline intelligent plugging robot,Autonomous plugging,Hydraulic control system,Plugging speed,Rubber cylinder deformation
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要