基于NSGA-II算法的内齿轮插齿残余应力加工参数优化

Optimization of machining parameters for residual stress in internal gear shaping based on the NSGA-II algorithm

  • 摘要: 为实现内齿轮插齿加工齿面残余应力的精准调控,建立了基于Abaqus的等效斜角切削热-力耦合有限元模型。通过单行程切削假设,将复杂往复运动等效为连续进给速度,减少了仿真计算成本。以切削速度、进给速度和切削深度为自变量,利用响应曲面法(response surface methodology, RSM)构建了残余压应力S1与残余拉应力S2的预测模型,并通过方差分析验证了模型的高精度与高可靠性。结合 NSGA-II 算法对残余应力进行多目标优化,获取了非支配最优解集。结果显示,预测模型R2>0.96,优化参数组合能显著增大压应力、减小拉应力,仿真与实验的绝对相对误差平均值分别为8.55%与7.43%。

     

    Abstract: To achieve precise control of the tooth surface residual stress in internal gear shaping, a thermo-mechanical coupled finite element model of equivalent oblique cutting is established based on Abaqus. By adopting the single-stroke cutting assumption, the complex reciprocating motion is equivalent to a continuous feed speed, which reduces the computational cost of the simulation. Taking cutting speed, feed speed and cutting depth as independent variables, response surface methodology (RSM) is employed to construct prediction models for residual compressive stress S1 and residual tensile stress S2. The high accuracy and reliability of the models are verified by analysis of variance (ANOVA). By integrating the non-dominated sorting genetic algorithm (NSGA-II), multi-objective optimization is performed for residual stress, thereby obtaining the non-dominated optimal solution set. The results show that the coefficient of determination R2 of the prediction models are greater than 0.96. The optimized parameter combination can significantly increase the compressive stress and reduce the tensile stress. The average absolute relative errors between simulation and experiment are 8.55% and 7.43%, respectively.

     

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