Abstract
Aim at improving the energy saving and transmission efficiency of directional drilling rig, the load sensing technology and constant-pressure variable technique are adopted to enable the system to provide the required pressure and flow rate according to the load variation. In order to research the dynamic characteristics of hydraulic control systems, the background and working principle of the load sensing technology were introduced. The dynamic mathematical model of load sensing system is established based on the hydraulic principle. The directional drilling rig mainly consists of two basic circuits: rotary circuit and feed circuit. The dynamic characteristics of rotary circuit are mainly studied. In addition, the hydraulic system of kilometres directional rig is simulated with the software of AMESim. The simulation results show that the load sensing pump could output its required flow and outlet pressure adapted to the load pressure in real time, thus effectively improving the efficiency of the hydraulic system. Furthermore, to verify the validity of the mathematical model and the simulation analysis, an experimental platform of the load sensing hydraulic system was built. The dynamic performance test of load sensing hydraulic system was performed by using the platform. The experimental results demonstrated that the load sensing hydraulic system could output its required flow and pressure when the working condition changed. Finally, they also illustrate the validity of the proposed approach.
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Acknowledgements
The authors acknowledge the National Natural Science Foundation of China (Grant: 51275061), the National Natural Science Foundation of China (Grant: 61672121), the Doctoral Scientific Research Foundation of Liaoning Province (Grant: 20141121), Science and Technology Research Foundation of the Educational Department of Liaoning Province (Grant: LS2010006).
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Wang, J. Structural Modeling and Performance Analysis of Rotary Circuit in Directional Drilling Rig Based on Load Sensing Technology. Int J Wireless Inf Networks 25, 269–278 (2018). https://doi.org/10.1007/s10776-017-0382-z
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DOI: https://doi.org/10.1007/s10776-017-0382-z