基于中介轴承润滑效率的流道结构参数反向预测

朱冬磊; 陈国定; 李炎军

doi:10.13224/j.cnki.jasp.2020.02.023

基于中介轴承润滑效率的流道结构参数反向预测

doi: 10.13224/j.cnki.jasp.2020.02.023

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出版历程
- 收稿日期: 2019-09-11
- 刊出日期: 2020-02-28

Inverse prediction of flow-path structure parameters based on intershaft bearing lubrication efficiency

1.
School of Mechanical Engineering,Northwestern Polytechnical University,Xi’an 710072,China
2.
Sichuan Gas Turbine Establishment,Aero Engine Corporation of China,Chengdu 610500,China

摘要

摘要: 为了满足航空发动机中介轴承润滑系统设计需求,即在给出特定轴承润滑效率的前提下,获得与之匹配的合理的轴承润滑流道结构参数,提出了考虑各结构参数取值约束条件的轴承润滑效率——流道结构参数反向预测分析方法。根据轴承润滑效率神经网络模型,构造反映结构参数与润滑效率拟合关系的润滑效率函数;以润滑效率函数值与给定润滑效率误差最小为优化目标,通过考虑各结构参数取值范围的优化分析,获得满足给定润滑效率(误差最小)的流道结构参数。相较于目前已有分析方法,所提出的反向预测分析方法预测精度提高了439%,平均计算时长缩短了175 min,且能同时实现多个参数的预测,为中介轴承润滑系统设计提供了一种思路。
- 中介轴承 /
- 润滑效率 /
- 流道结构 /
- 反向预测 /
- 预测精度
Abstract: An inverse prediction method considering the constraints of flow-path structure parameters was proposed to satisfy the designing requirements of aero-engine intershaft bearing lubrication system while obtaining feasible structure parameters corresponding to the given bearing lubrication efficiency. Lubrication efficiency function was constructed to demonstrate the fitting relation between structure parameters and lubrication efficiency according to the neural network model. By virtue of structure parameters optimization, the distraction between lubrication efficiency function values and the given lubrication efficiency was mininized, the constraints of each parameter were considered to obtain, the flow-path structure parameters satisfying the given lubrication efficiency(minimized distraction). In comparison with the present analytical methods, the proposed inverse prediction method could improve the prediction precision by 439%, shorten the average calculation time by 175 minutes, and predict multiple parameters simultaneously, providing an approach to the design of intershaft bearing lubrication system.
- intershaft bearing /
- lubrication efficiency /
- flow-path structure /
- inverse prediction /
- prediction precision

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