航空发动机多级装配转子双侧不平衡预测模型

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Lingling Song, Yue Chen
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引用次数: 0

摘要

在航空发动机等多级装配转子的旋转机械中,当旋转转子的装配阶段时,存在的任何不平衡在每个阶段都会发生未知的变化。通常需要反复拆卸和调整,才能满足转子的残余不平衡规范要求。因此,为多级装配转子建立一个双侧不平衡的预测模型,对于提高首次装配合格率和装配效率至关重要。本文提出了一种航空发动机多级装配转子两侧不平衡的预测模型。首先,提出了将各级转子的质量特征参数统一到几何测量坐标系中的方法,实现了多级转子装配过程中几何参数和质量特征参数的同步传递。在此基础上,建立了多级转子实际旋转轴的线性参数方程。在此基础上,计算出转子每一级的质量偏心误差,从而进一步准确预测多级转子的两侧不平衡及其作用阶段。实验结果表明,使用该模型时,四级转子的两侧不平衡及其作用阶段的最大预测误差分别为 9.6% 和 2.5%,与现有模型相比,分别减少了 53.0% 和 38.1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Prediction Model of Two-Sided Unbalance in the Multi-Stage Assembled Rotor of an Aero Engine
In rotating machinery with a multi-stage assembled rotor, such as is found in aero engines, any unbalance present will undergo unknown changes at each stage when rotating the assembly phases of the rotor. Repeated disassembly and adjustments are often required to meet the rotor’s residual unbalance specifications. Therefore, developing a prediction model of this two-sided unbalance for a multi-stage assembled rotor is crucial for improving the first-time assembly pass rate and assembly efficiency. In this paper, we propose a prediction model of the two-sided unbalance seen in the multi-stage assembled rotor of an aero engine. Firstly, a method was proposed to unify the mass feature parameters of each stage’s rotor into a geometric measurement coordinate system, achieving the synchronous transmission of geometric and mass feature parameters during the assembly process of the multi-stage rotor. Building upon this, a linear parameter equation of the actual rotation axis of the multi-stage rotor was established. Based on this axis, the mass eccentricity errors of the rotor were calculated at each stage, further enabling the accurate prediction of two-sided unbalance and its action phase in a multi-stage rotor. The experimental results indicate that the maximum prediction errors of the two-sided unbalance and its action phase for a four-stage rotor are 9.6% and 2.5%, respectively, when using this model, which is a reduction of 53.0% and 38.1% compared to the existing model.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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