Abstract

To investigate the effect of various factors on bearing stress response, Huber-Hencky-von Mises stress serves as a bridge, the equivalent interrelation between radial loading, axial loading, and temperature of bearing is studied using finite element method (FEM). Symbolic regression (SR) algorithm is employed to analyze simulation results, establishing a functional expression between independent and dependent variables by optimizing combinations of variables, constants, and functional forms. The results showed that within the specified force and temperature values, the curved surface of the equivalent correlation function, trained using the SR algorithm, demonstrates smoothness. Both training and validation data exhibit a strong correlation with this curved surface. Among the three factors, temperature exerts the greatest influence on bearing stress values, followed by radial loading, and axial loading components had the smallest impact.

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