Thermal-fluid-structural coupling analysis model of embedded intelligent bearing

This paper establishes a modified thermal-fluid-structural coupling analysis model for embedded intelligent bearings by integrating bearing mechanical contact theory, a transient thermal grid model, and an elastohydrodynamic lubrication algorithm. To address the effect of embedded groove on embedded intelligent bearings and the limitation of conventional thermal models in capturing uneven heat generation, this paper proposes an embedded groove correction algorithm and a modified thermal grid model that accounts for uneven heat distribution. The proposed model fully incorporates key thermal-fluid-structural coupling effects—such as thermal expansion and viscosity-temperature effects—enabling comprehensive coupling analysis for embedded intelligent bearings and calculation of critical service state parameters, including contact load, contact stress, temperature, lubricant pressure, lubricant film thickness, and measured point strain/temperature. Taking a tapered roller bearing as the research subject, this study first calculates its service state parameters under a typical operating condition. After verifying the accuracy of the embedded groove correction algorithm through finite element analysis, a comparative analysis is conducted on the parameter differences before and after introducing the embedded groove correction module and the thermal-fluid-structural coupling module. A comparative analysis of multiple operating conditions is then conducted to verify the versatility and robustness of the proposed model under various operating conditions, and the operating patterns of the bearing under different working scenarios are analyzed. Finally, experiments confirm both the model’s accuracy on strain and temperature of measurement point and the significant improvement in calculation precision driven by the proposed thermal-fluid-structural coupling module, temperature distribution module, and embedded groove correction module.