基于稳健性择优的自卸车驱动桥桥壳优化

Optimization of Driving Axle Housing of Dump Truck based on Robustness Selection

针对重型自卸车驱动桥桥壳进行轻量化研究时,由于桥壳的使用条件及生产条件存在不确定性因素,使得桥壳的可靠性存在难以控制的问题,提出了一种确定性优化与稳健性择优相结合的轻量化研究方法。对原桥壳进行有限元分析,验证了原桥壳存在进一步优化的空间。利用灵敏度分析法选取了优化设计变量,构建kriging响应面模型。通过多目标遗传优化算法(Multi-Objective Genetic Algorithm)对桥壳进行确定性优化,得到3组9个确定性优化尺寸。构建L9(34)正交表,对确定性优化尺寸进行稳健性择优,基于信噪比η,得到了稳健性较好的优化尺寸。结果表明,在现桥壳的质量比原桥壳降低16.7%的情况下,通过稳健性择优方法,提高了最大应力稳健性和1阶固有频率的稳健性,增加了桥壳的可靠性。该方法能够保证轻量化桥壳在各种不确定性因素干扰下,仍然能够发挥出正常性能,一定程度上弥补了现有稳健性优化方法的不足,为桥壳的稳健性优化提出了一种新的思路。

In lightweight research of driving axle housing of heavy dump trucks,the reliability of the axle housing is difficult to be controlled due to the uncertainty factors in the use and production conditions of the axle housing,so a lightweight research method combining deterministic optimization and robustness selection is proposed.The finite element analysis is carried out on the axle housing,it is verified that there is room for further optimization of the original axle housing.The sensitivity analysis method is used to select the optimization design variables and after that construct the Kriging response surface model.Three groups of 9 optimization sizes are obtained Through the deterministic optimization by multi-objective Genetic Algorithm.The L9(34)orthogonal table is constructed,the robust selection of deterministic optimal size is carried out,the optimal size of good robust performance is obtained based on signal-to-noise ratioη.The results show that under the condition that the mass of the present axle housing is 16.7%lower than that of the original one,the robustness selection method improves the maximum stress robustness and the first-order natural frequency robustness,and increases the reliability of the axle housing.This method can ensure the normal performance of light weight axle housing under the interference of various uncertain factors,and partly make up for the deficiency of the existing robust optimization methods,a new way of thinking is proposed for the robust optimization of axle housing.