Study on Feature Extraction of Gearbox Vibration Signal for Wind Turbines

被引:0
|
作者
Guo, Jinang [1 ]
Wu, Guoxin [1 ]
Zhao, Xiwei [1 ]
Huang, Hao [1 ]
Xu, Xiaoli [1 ]
机构
[1] Beijing Informat Sci & Technol Univ, Key Lab Modern Measurement & Control Technol, Minist Educ, Beijing 100912, Peoples R China
关键词
Wind turbine; Fault diagnosis; ICA; EMD;
D O I
10.1007/978-3-030-99075-6_49
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
As a clean energy, the development of wind power has attracted wide attention. In view of the characteristics of non-linear and non-stationary mixed signals in the vibration state of wind turbines, the separation of noise is the key problem of information feature extraction. In this study, sensors are utilized to collect blind source signals and mixed matrix information in order to retrieve source signals and extract features from information. This paper integrates EMD (Empirical Model Decomposition) with ICA (Independent Component Analysis) with the aim of extracting feature signals from the wind turbine generator system (WTGS). By analyzing signals with obvious fault characteristics, this approach considerably increases the accuracy in extracting feature signals from the WTGS transmission system.
引用
收藏
页码:607 / 614
页数:8
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