Oversampled Modal Approach of a Turbocharger Rotor from the Experimental Lateral Vibrations

IF 0.8 4区工程技术 Q4 ACOUSTICS

International Journal of Acoustics and Vibration Pub Date : 2019-12-31 DOI:10.20855/ijav.2019.24.41484

L. A. Montoya, E. E. Rodriguez, H. J. Zúñiga, I. Mejía

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引用次数: 0

Abstract

The elements of rotors have inherent characteristics as geometry and material composition, which causes natural vibrations at frequencies that, due to the rotor unbalance, may coincide with the harmonics of the shaft speed, increasing stress and the probability of fractures even in transient conditions. Therefore, in this work, a theoreticalexperimental hybrid method for calculating the natural frequencies and the mode shapes, at rest and non-supported conditions, of a turbocharger rotor is proposed. Firstly, a discrete model of low number of degrees of freedom is considered, and from an oversampled modal approach (OSMA) based on the axial oversampling, sectioning and coupling of the rotor, it is possible to use the oversampled mode shapes to increase the degrees of freedom of the system without major complications in the model. This spatial oversampling criterion is based on the NyquistShannon theorem, and it is used to reduce the error in the estimates of the natural frequencies and to get a first approximation of the mode shapes. The natural frequencies were estimated by the transfer matrix method (TMM) and finite element method (FEM) in order to compare the proposed model results with well-founded numerical methods.

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涡轮增压器转子横向振动的过采样模态方法

转子的元件具有固有的几何特性和材料组成，这导致频率上的自然振动，由于转子不平衡，可能与轴转速的谐波相吻合，增加应力和即使在瞬态条件下断裂的可能性。因此，在这项工作中，提出了一种计算涡轮增压器转子在静止和无支撑条件下的固有频率和模态振型的理论和实验混合方法。首先，考虑了一个低自由度的离散模型，并从基于转子轴向过采样，切片和耦合的过采样模态方法(OSMA)中，可以使用过采样模态振型来增加系统的自由度，而不会在模型中产生重大复杂性。该空间过采样准则基于nyquist - shannon定理，用于减小固有频率估计的误差并得到模态振型的第一近似。利用传递矩阵法(TMM)和有限元法(FEM)估算了固有频率，并与已有的数值方法进行了比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Acoustics and Vibration ACOUSTICS-ENGINEERING, MECHANICAL

CiteScore

1.60

自引率

10.00%

发文量

审稿时长

12 months

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