Nonlinear dynamic analysis of the central bevel gear transmission system in aero engine subjected to internal and external excitation

Author:

Liu Jiayin12,Zhang Hao3ORCID,Zhai Jingyu12,Han Qingkai12ORCID

Affiliation:

1. School of Mechanical Engineering, Dalian University of Technology, Dalian, Liaoning, PR China

2. Collaborative Innovation Center of Major Machine Manufacturing in Liaoning, Dalian, Liaoning, PR China

3. College of Mechanical Engineering and Automation, Liaoning University of Technology, Jinzhou, Liaoning, PR China

Abstract

The research on the nonlinear dynamic characteristics of the central bevel gear transmission system was carried out for the requirement of the vibration control and fault diagnosis of the central bevel gear transmission system in an aero engine. This paper proposes the dynamic model for the first time in order to investigate nonlinear dynamic behavior of the central bevel gear transmission system, and the internal and external excitations are taken into account by using lumped parameter modeling. Time-varying meshing stiffness, gear backlash, and gear transmission error is included in the internal excitations, and the input power, the speed fluctuation of the driven shaft and the high-pressure rotor unbalance excitation are included in the external excitations. The effects of the external excitations on the complex nonlinear dynamic behavior of the system are studied. The results show that reasonable control of input power, speed fluctuations, and high-pressure rotor mass imbalance can improve engine vibration.

Funder

Natural Science Foundation of Liaoning Province

Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education, Northeastern University

National Natural Science Foundation of China

Publisher

SAGE Publications

Subject

Mechanical Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Comprehensive analysis of aero-engine vibration signals based on wavelet transform method;EURASIP Journal on Advances in Signal Processing;2023-11-15

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