Dynamic optimization of two-stage reducer considering design and layout parameters

被引：0
|
作者：
Jin P. [1 ]
Zhou J. [1 ]
Qi L. [1 ]
Wang S. [1 ]
Zhou H. [1 ]
Song L. [1 ]
机构：
[1] College of Mechanical Engineering, Xinjiang University, Urumqi
来源：
Zhendong yu Chongji/Journal of Vibration and Shock | 2023年 / 42卷 / 13期
关键词：
Bayesian algorithm; dynamic characteristics; layout parameters; multi-objective optimization; parametric dynamic model;
D O I：
10.13465/j.cnki.jvs.2023.13.031
中图分类号：
学科分类号：
摘要：
Here, to study dynamic performance optimization method of multistage fixed shaft gear train, taking a secondary gear system as the study object, a parametric dynamic model including gear design parameters (tooth number, gear module, tooth width) and system layout parameters (gear installation position, inter-stage phase angle) was established by using the generalized finite element method. Newmark-β time domain integral method was used to solve the dynamic equation under the rated rotating speed, and effects of various parameters on dynamic characteristics of the system were analyzed. Then, a dynamic optimization method for multistage fixed shaft gear system was proposed. Taking design and layout parameters as variables, and transmission ratio of reducer, shaft diameter and width, etc. as constraints, and dynamic load amplitude of the two-stage gear system and the minimum difference between loads of bearings at both shaft sides as the main objectives, a multi-objective mixed discrete optimization model was established, and a code was written based on Bayesian algorithm to solve the model to obtain the optimal design variables. The results showed that after optimization, the reducer's first stage gear meshing force amplitude reduces by 18.9%, its second stage gear meshing force amplitude reduces by 17.2%, and bearing load differences for 3 pairs of bearings at both shaft sides in inter-stage shafting reduce by 36%, 40% and 45%, respectively; the system mass decreases by 8.1%, and boundary box volume decreases by 27%; so, the optimization effect is obvious. © 2023 Chinese Vibration Engineering Society. All rights reserved.
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页码：259 / 268
页数：9
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