基于NSGA-Ⅱ算法的航天产品装配公差多目标优化

Multi-objective Optimization Based on NSGA-Ⅱ Algorithm for Assembly Tolerance of Aerospace Products

针对航天产品装配公差优化设计问题,提出一种引入装配成本的多目标优化方案。在考虑航天产品装配过程中成功率低、成本高问题的基础上,建立基于产品成本及质量损失的装配公差的多目标优化数学模型,利用带精英策略的非支配排序遗传算法(NSGA-Ⅱ),以装配功能要求和加工能力为约束条件,对装配公差进行优化求解,得到Pareto最优解集。以某空间站某型号组件为例,验证了该优化方法的有效性。通过建立归一化权重目标函数,获得优化的各组成环装配公差,利用该公差进行组件加工装配,提高了装配成功率,降低了产品加工成本及质量损失。

In order to solve the problem of assembly tolerance optimization for aerospace products,a multiobjective optimization scheme with assembly cost is proposed.Based on the consideration of low success rate and high cost in the assembly process of aerospace products,a multi-objective optimization mathematical model based on the assembly tolerances of product cost and quality loss is established.Then,a fast and elitist multi-objective genetic algorithm(NSGA-Ⅱ)is adopted to optimize the assembly tolerance under the constraints of assembly function requirements and machining capacity,and a set of Pareto optimal solutions is obtained.The effectiveness of the optimization method is verified by taking a component of a space station as an example.By constructing a normalized weight objective function,the desired optimal assembly tolerance is obtained.Then,the obtained tolerance is used to machine and assemble the component.It is shown that the proposed optimization method improves the assembly success rate and reduces the machining cost and quality loss of the product.