目的 为实现机械密封润滑性能与泄漏性能的协同提升,缓解传统设计中润滑增强与泄漏增加相互牵制的问题,从而提升其在高转速与长时稳定运行工况下的综合性能。方法 构建基于雷诺方程的动压润滑模型,选取圆形凹坑作为织构单元,通过权重系数kp将润滑与泄漏指标耦合为协调优化目标函数,并结合遗传算法对织构排布进行优化设计。以油膜承载力、摩擦系数与泄漏率为评价指标,系统研究kp、织构周期角与织构深度对性能的影响规律。随后采用飞秒激光加工制备织构化机械密封试样,开展摩擦磨损实验对仿真结果进行验证。结果 优化结果表明,在kp=0.5、周期角30°、织构深度5 µm条件下可获得综合性能较优的织构排布。仿真结果显示,相较非织构化表面,油膜承载力提升216.9%,摩擦系数降低58.3%。相较全织构排布,泄漏率降低75.9%。实验结果与仿真在参数变化趋势及优选方案上保持一致,验证了优化设计的有效性。结论 本研究建立了面向润滑与泄漏协同目标的织构优化设计框架,阐明了关键几何参数对机械密封性能的影响规律,所获优化方案具备加工可行性与工况稳定性,可为高性能机械密封的结构设计提供理论依据与实验支撑。
Abstract
Mechanical seals are indispensable components in modern fluid machinery systems, where their reliability and operational stability are of paramount importance, particularly in demanding application fields such as aerospace, petrochemicals, and advanced manufacturing. The primary function of mechanical seals is to prevent fluid leakage while ensuring adequate lubrication between the rotating and stationary rings at the sealing interface. However, an inherent design paradox still exists. Namely, improving lubrication by generating a thicker hydrodynamic fluid film often exacerbates leakage, whereas enhancing sealing tightness typically sacrifices lubrication quality and increases friction. Resolving this trade-off between lubrication and leakage is of critical significance for prolonging the service life of seals. With focuses on typical mechanical seal faces textured with circular dimples, this study proposes a coordinated design and optimization strategy that integrates hydrodynamic mechanisms with an intelligent algorithm. By establishing a hydrodynamic lubrication model based on the Reynolds equation, the hydrodynamic effect induced by micro-scale surface textures is accurately characterized. A genetic algorithm is employed to optimize the spatial distribution of the circular dimples on the seal face. To reduce the computational cost, the seal face is discretized into a one-twelfth sector model, and the presence or absence of a dimple at the grid nodes is encoded into binary genes. A multi-objective function is constructed by introducing a tunable weighting coefficient kp, achieving dynamic tuning between the enhancement of load-carrying capacity and the suppression of leakage. Optimization results indicate that the optimal distribution scheme is achieved at kp= 0.5, a texture depth of 5 µm, and a texture periodic angle of 30°. Under these optimal conditions, the fluid film load-carrying capacity of the optimized surface is enhanced by 216.9%, and the friction coefficient is reduced by 58.3% compared with the untextured smooth surface. Simultaneously, its leakage rate is drastically decreased by 75.9% compared with a fully textured configuration. Parametric analysis further reveals that excessively shallow textures fail to form effective micro-hydrodynamic converging wedges, thus providing insufficient hydrodynamic support, whereas excessively deep textures exacerbate flow losses and leakage. Adjusting the kp value flexibly guides the optimization algorithm to shift its objective focus between leakage control and load-carrying capacity enhancement. To validate the reliability of the numerical simulations, test specimens featuring both the optimized and reference texture distributions are fabricated using femtosecond laser micromachining technology. Tribological experiments are conducted on a customized test rig at a rotational speed of 8 000 r/min and a radial load of 170 N to measure the friction torque and leakage rate of the system. The experimental results demonstrate excellent agreement with the simulation predictions. Notably, compared with the fully textured configuration, the optimized textured specimen exhibits a 77.67% reduction in leakage rate alongside a significant decrease in friction torque. This fully substantiates the effectiveness of the proposed theoretical method and its robustness under complex operating conditions. In conclusion, this study provides an experimentally validated methodological framework for balancing lubrication and sealing performance in mechanical seals. Furthermore, the concept of integrating hydrodynamic modeling with intelligent optimization offers a generalizable design paradigm for resolving issues in other tribological systems characterized by strongly coupled and mutually constraining performance demands.
关键词
机械密封 /
表面织构 /
泄漏性能 /
润滑性能 /
协调优化
Key words
mechanical seal /
surface texture /
leakage performance /
lubrication performance /
coordinated optimization
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基金
国家自然科学基金面上项目（525752288）; 校企合作横向科研项目（（2024）224JS-0161）
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