Research and process optimization of crankshaft grinding parameters based on Gaussian heat source model

In the grinding process of crankshafts, the grinding parameters were improperly selected, which easily caused the high temperature in the grinding zone and led to burns on the crankshaft journal surface. To address this issue, referencing previous studies, the suitability of the Gaussian heat source model was verified by comparing it with three different heat source models. The Gaussian heat source model was applied to predict the temperature on the surface of the crankshaft connecting rod journal. Transient thermal analysis and investigation of material phase transformation were employed to explore the mechanism of grinding burns. The interaction effects among grinding parameters were analyzed using the Box-Behnken design, and a multiple linear regression equation was established for response surface optimization. The results demonstrated that applying the Gaussian heat source model and response surface optimization yielded the optimal solution, with a maximum deviation of 1.37% between the simulation and optimization results. By selecting a grinding depth (a_p) of 0.40 mm, wheel speed (v_s) of 40.00 m/s, and feed rate (v_x) of 0.036 mm/s as the processing parameters, the temperature in the grinding zone was reduced to 659.37 °C, effectively mitigating grinding burns.