Abstract

Although an extensive research effort on the structural constraint role in bearing heating was done by scholars, often many researchers either neglected the sub structure effect for model simplification or considered more influencing factors to construct a complicated thermal model for higher evaluation precision. As a result, a lightweight and accurate assessment has been not available so far. Furthermore, they usually only made some basic assumptions and qualitative analyses when creating and improving the thermal predictive models to explore the heat transfer of bearings, and hence their findings usually lack sufficient theoretical supports, especially the quantitative bases. For an efficient assessment, this paper devotes to exploring how the structural constraint impact on the heat conduction of bearings, and accordingly present a more practical thermal grid to evaluate bearing heating efficiently. Firstly, the structure and installation notes of bearings were statistically analyzed. Next, a formula was constructed to implement the contrast of the heat transfer capacity between the axial and radial directions of bearing rings, and then a novel radial thermal equivalent resistance was proposed to represent the heat conduction capacity of bearing rings. We accordingly optimized the bearing node setting scheme to develop an efficient semi-empirical thermal grid for high-speed angular contact ball bearings, in which the oil-air separation and gray-box theory was also introduced to describe the heat convection in bearing cavities. Finally the improved thermal network for a motored spindle was planned to verify the above-proposed work, and the simulation results based on the current thermal models of bearings were also obtained and contrasted with the experimental values. For a further validation, the polynomial interpolation on test data, meanwhile, was performed to observe the temperature variation trend. The result of comparative analysis indicates that we show a more proper thermal assessment on bearing temperature.

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