Artificial Bee Colony Algorithm-Based Optimization for Reducing Tooth Flank Distortion in Form-Grinding

The tooth flank distortion error occurring during the form-grinding (FG) of an involute helical gear can significantly compromise transmission performance. Conventional research approaches often focus on single-parameter optimization—either the grinding wheel installation angle (GWIA) or the contact line (CL)—without adequately accounting for the coupling relationships among GWIA, CL, and the modification curve (MC). To address this limitation, this study proposes an innovative joint optimization approach that simultaneously optimizes GWIA, CL, and MC to effectively minimize tooth flank distortion in FG. Based on the principles of form-grinding, a mathematical model is established for the contact line of the target gear and the cross-sectional profile of the grinding wheel. The relationship between GWIA and tooth flank deviation is investigated using a proprietary virtual prototype. A multi-objective artificial bee colony (ABC) optimization algorithm is employed to determine the optimal values of GWIA and CL. For the axial modification curve, this paper introduces a novel three-segment quadratic curve optimization scheme as an improvement over conventional modification methods. To validate the proposed optimization technique, form-grinding experiments are conducted on the L300G gear grinding machine. Simulation outcomes indicate that, pre-optimization, the maximum tooth flank distortion errors primarily occur at the tooth root and tip regions on both ends of the gear. After optimization, the simulated distortion error on the left tooth flank is reduced by 48.5%, while the right flank shows a reduction of 29.4%. These simulation outcomes exhibit a deviation of approximately 10% compared with the experimental results. This study provides valuable insights for enhancing the transmission performance of helical gears.