Dynamic Characteristics of Wind Turbine Gearbox with the Chipping Fault

Author(s):  
Xin Wang ◽  
Yuxiu Xu ◽  
Taotao Li
2013 ◽  
Vol 321-324 ◽  
pp. 9-12
Author(s):  
Wen Jun Yang ◽  
Hui Qun Yuan ◽  
Zhi Min Huang ◽  
Li Se Yang

Based on gear transmission system of 1.5MW wind turbine, dynamic characteristics are analyzed under the effect of both external and internal incentives. Using lumped parameter method, the dynamic model involving 6 degrees of freedom for every helical gear is established with taking the time-varying mesh stiffness and error into account. The results show that the transmission system is quasi-periodic under the operating speed, and the vibration direction of gear with a large amplitude is obtained. This study can be referred to the engineering applications.


2017 ◽  
Vol 31 (3) ◽  
pp. 1079-1088 ◽  
Author(s):  
Shuaishuai Wang ◽  
Caichao Zhu ◽  
Chaosheng Song ◽  
Huachao Liu ◽  
Jianjun Tan ◽  
...  

Author(s):  
Aiqiang Zhang ◽  
Jing Wei ◽  
Datong Qin ◽  
Shaoshuai Hou ◽  
Teik C. Lim

Gravity is usually neglected in the dynamic modeling and analysis of the transmission system, especially in some relatively lightweight equipment. The wind turbine gearbox weight up to tens of tons or even hundreds of tons, and the effects of gravity have not been explored and quantified. In order to obtain accurate vibration response predictions to understand the coupled dynamic characteristics of the wind turbine gear transmission system, a comprehensive, fully coupled, dynamic model is established using the node finite element method with gravity considered. Both time-domain and frequency-domain dynamic responses are calculated using the precise integration method with various excitations being taken into account. The results indicate that gravity has a significant impact on the vibration equilibrium position of central floating components, but the changing trends are different. Gravity does not change the composition of the excitation frequency, but will have a certain impact on the distribution ratio of the frequency components. And the high frequency vibrations are hardly affected by gravity. In addition, the load sharing coefficient is greater when gravity is taken into account, both of internal gearing and external gearing system. When the planet gears have a certain position error in accordance with certain rules, the load sharing performance of the system will be better.


2019 ◽  
Vol 33 (1) ◽  
pp. 393-402 ◽  
Author(s):  
Liang Xu ◽  
Caichao Zhu ◽  
Huaiju Liu ◽  
Guo Chen ◽  
Wei Long

Author(s):  
Aiqiang Zhang ◽  
Jing Wei ◽  
Datong Qin ◽  
Shaoshuai Hou ◽  
Teik C. Lim

Gravity is usually neglected in the dynamic modeling and analysis of the transmission system, especially in some relatively lightweight equipment. The weight of wind turbine gearbox is up to tens of tons or even hundreds of tons, and the effects of gravity have not been explored and quantified. In order to obtain accurate vibration response predictions to understand the coupled dynamic characteristics of the wind turbine gear transmission system, a comprehensive, fully coupled, dynamic model is established by the node finite element method with gravity considered. Both time-domain and frequency-domain dynamic responses are calculated using the precise integration method with various excitations being taken into account. The results indicate that gravity has a significant impact on the vibration equilibrium position of central floating components, but the changing trends are different. Gravity does not change the composition of the excitation frequency, but will have a certain impact on the distribution ratio of the frequency components. And the high frequency vibrations are hardly affected by gravity. In addition, the load sharing coefficient is greater when gravity is taken into account, both of internal gearing and of external gearing system. When the planet gears have a certain position error in accordance with certain rules, the load sharing performance of the system will be better.


2014 ◽  
Vol 28 (4) ◽  
pp. 314-323
Author(s):  
Jung-Su Kimg ◽  
No-Gill Park ◽  
Ki-Bong Han ◽  
Hyoung-Woo Lee

2016 ◽  
Vol 103 ◽  
pp. 138-147 ◽  
Author(s):  
Hongfei Zhai ◽  
Caichao Zhu ◽  
Chaosheng Song ◽  
Huaiju Liu ◽  
Houyi Bai

Author(s):  
Jiatang Cheng ◽  
Yan Xiong

Background: The effective diagnosis of wind turbine gearbox fault is an important means to ensure the normal and stable operation and avoid unexpected accidents. Methods: To accurately identify the fault modes of the wind turbine gearbox, an intelligent diagnosis technology based on BP neural network trained by the Improved Quantum Particle Swarm Optimization Algorithm (IQPSOBP) is proposed. In IQPSO approach, the random adjustment scheme of contractionexpansion coefficient and the restarting strategy are employed, and the performance evaluation is executed on a set of benchmark test functions. Subsequently, the fault diagnosis model of the wind turbine gearbox is built by using IQPSO algorithm and BP neural network. Results: According to the evaluation results, IQPSO is superior to PSO and QPSO algorithms. Also, compared with BP network, BP network trained by Particle Swarm Optimization (PSOBP) and BP network trained by Quantum Particle Swarm Optimization (QPSOBP), IQPSOBP has the highest diagnostic accuracy. Conclusion: The presented method provides a new reference for the fault diagnosis of wind turbine gearbox.


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