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

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 rob...

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Bibliographic Details
Main Authors: Ronghui Lin, Peng Zhou
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2021-06-01
Series:Jixie chuandong
Subjects:
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2021.06.010
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Summary: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 L<sup>9</sup> (3<sup>4</sup>) 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 ratio <italic>η</italic>. 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.
ISSN:1004-2539