Suction Performance Optimization of a Grease Suction and Discharge Device for Wind Turbine Bearings Considering Herschel–Bulkley

With the advancement of industrial IoT and artificial intelligence technologies, bearing maintenance is gradually evolving toward predictive maintenance. For large bearings, the internal grease must be replaced promptly once it has deteriorated. As the core lubrication component of such bearings, the suction and discharge device directly determines the efficiency of grease discharge and the operational stability of the bearing. To address the issue of insufficient intake capacity in existing units, this study employs the Herschel–Bulkley non-Newtonian fluid model to analyze intake characteristics and conduct multi-parameter co-optimization, revealing the underlying mechanisms by which vacuum level, grease temperature, and the chamfer structure of the grease inlet pipe influence suction performance. Based on the yield stress and shear thinning characteristics of the grease, the flow equation for the inlet section was derived, and the analytical and CFD results showed consistent trends. With the volumetric flow rate in the inlet section as the optimization objective, a multi-parameter co-optimization of the vacuum level, temperature, and chamfer radius was conducted through orthogonal experiments. The results show that under the optimal parameter combination, the inlet volumetric flow rate was significantly increased, and grease supply stability was markedly improved. The research findings provide a theoretical basis and engineering reference for the design optimization of the suction and discharge device for wind turbine bearings.