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A novel model for the thermoelastic hydrodynamic lubrication characteristics of the slipper pair in radial piston pumps

物理 润滑 活塞(光学) 机械 热弹性阻尼 活塞泵 径向柱塞泵 热力学 液压泵 光学 热的 变量泵 波前
作者
Zhengang Yun,Shaonian Li,Fuhao Li,Kaifeng Wang,Li Fu,C. Q. Ru
出处
期刊:Physics of Fluids [American Institute of Physics]
卷期号:37 (2) 被引量:4
标识
DOI:10.1063/5.0249230
摘要

Relying on heat conduction and thermoelastic mechanics theories and Takeuti's research, a novel TEHL (thermoelastic hydrodynamic lubrication) model considering thermal effect-induced thermoelastic deformation was developed. The impact of the radial piston pump's slipper pair's working and structural parameters on lubrication under heavy oscillating load was studied. The model was shown to be valid and superior in simulating oil film changes in TEHL, EHL (elastic hydrodynamic lubrication), and HL (hydrodynamic lubrication). It was first used to analyze how different conditions and parameters affect slipper pair lubrication. Thermoelastic deformation simulations were more accurate than previous elastic ones, making results more comprehensive. Friction experiments gave a coefficient of about 0.25 at 400–600 r/min and 0.23 at 600–1000 r/min, while the simulation result was 0.215. The HL model had a thin film, high temperature, and asymmetric pressure at x1 during suction, and increased thickness, decreased temperature, and uniform pressure at y1 during high pressure. In the HL model without deformations, the film was 12.9–14.0 μm thick and 345.7–354.0 K in temperature. In the EHL model with elastic deformation (0.6–2.6 μm), the thickness was 13.6–15.9 μm. In the TEHL model with thermoelastic deformation (0.5–2.1 μm), the thickness was 13.2–15.6 μm and the temperature was 344.4–354.0 K. Also, film thickness, speed, pressure, angle, radius, and ratio significantly affect slipper pair TEHL. This series of simulations proved the proposed model's feasibility for studying TEHL under heavy, variable loads and different structures. The model can optimize pump design parameters, boosting efficiency, and extending service life, and also enables fault prediction and prevention and maintenance strategy optimization, enhancing equipment reliability and production efficiency.
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