Prediction and control for local bearing contact-based collaborative grinding of non-orthogonal aerospace spiral bevel gears

Abstract

It is very different with the recent tooth flank grinding, an innovative collaborative optimization considering both geometric accuracy and local bearing contact evaluations is proposed for non-orthogonal aerospace spiral bevel gears. In particular, its data-driven prediction and adaptive control is developed. Firstly, tooth flank grinding using double helical method is simulated to establish mathematical model of the whole tooth flank including work flank and root fillet. Then, prediction of local bearing contact evaluations including geometric topography, loaded contact pressure and loaded contact deformation is performed by correlating with numerical loaded tooth contact analysis (NLTCA). Where, loaded contact pressure and its distribution considering time-varying meshing characteristics are developed, respectively. Moreover, an adaptive collaborative control model is established by extending the conventional machine tool settings modification only considering geometric accuracy to case that collaborative optimization. In the normal direction, loaded contact deformation of material removal point is predicated in the geometric accuracy control. In tooth flank tangential plane, the material removal points are constrained within the prescribed boundary. Finally, the sensitivity analysis strategy is used to select the optimal design variables, and control mode is solved for accurate machine tool settings. The given numerical instances can verify the proposed method.