Fault Feature Extraction of Gearboxes Using Ensemble Empirical Mode Decomposition

被引：0
|
作者：
Lin, Jinshan [1 ]
机构：
[1] Weifang Univ, Sch Mech & Elect Engn, Weifang, Shandong, Peoples R China
来源：
APPLIED INFORMATICS AND COMMUNICATION, PT I | 2011年 / 224卷
关键词：
feature extraction; gearbox; emsemble empirical mode decomposition(EEMD); intrinsic mode function(IMF);
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper employs ensemble empirical mode decomposition (EEMD) to extract the fault information from the signal collected from a defective gearbox. In view of the shortcoming of the mode mixing which empirical mode decomposition (EMD) fails to overcome, the EEMD method is used to decompose the signal captured from the defective gearbox and successfully separate the different components from high frequency to low frequency. Then, the first four intrinsic mode functions (IMFs), containing the most energy of the signal, are extracted; by analyzing the spectrum of the first four components, we succeed in uncovering the reason causing the fault of the gearbox. The results show that the EEMD method could be feasible to diagnose the fault of the gearbox.
引用
下载
收藏
页码：478 / 483
页数：6
相关论文
共 50 条
  • [1] Fault Feature Extraction of Gearboxes Using Ensemble Empirical Mode Decomposition
    Lin, Jinshan
    2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL I, 2010, : 271 - 274
  • [2] Fault Feature Extraction for Gearboxes Using Empirical Mode Decomposition
    Dou, Chunhong
    MANUFACTURING SCIENCE AND TECHNOLOGY, PTS 1-8, 2012, 383-390 : 1376 - 1380
  • [3] Fault Detection of Planetary Gearboxes Based on an Adaptive Ensemble Empirical Mode Decomposition
    Lei, Yaguo
    Li, Naipeng
    Lin, Jing
    ENGINEERING ASSET MANAGEMENT - SYSTEMS, PROFESSIONAL PRACTICES AND CERTIFICATION, 2015, : 837 - 848
  • [4] FEATURE EXTRACTION OF ROLLING BEARING FAULT BASED ON ENSEMBLE EMPIRICAL MODE DECOMPOSITION AND CORRELATION DIMENSION
    Zhao, Lei
    Zhou, Zude
    Yin, Yang
    Chen, Rong
    Liu, Quan
    Wei, Qin
    PROCEEDINGS OF THE ASME 9TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, 2014, VOL 2, 2014,
  • [5] Feature Signal Extraction Based on Ensemble Empirical Mode Decomposition for Multi-fault Bearings
    Guo, W.
    Wang, K. S.
    Wang, D.
    Tse, P. W.
    ENGINEERING ASSET MANAGEMENT - SYSTEMS, PROFESSIONAL PRACTICES AND CERTIFICATION, 2015, : 1337 - 1347
  • [6] Bearing fault feature extraction method based on complete ensemble empirical mode decomposition with adaptive noise
    Xiao, Maohua
    Zhang, Cunyi
    Wen, Kai
    Xiong, Longfei
    Geng, Guosheng
    Wu, Dan
    JOURNAL OF VIBROENGINEERING, 2018, 20 (07) : 2622 - 2631
  • [7] Rolling bearing fault feature extraction method based on ensemble empirical mode decomposition and kurtosis criterion
    Hu, Aijun
    Ma, Wanli
    Tang, Guiji
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2012, 32 (11): : 106 - 111
  • [8] An adaptive denoising fault feature extraction method based on ensemble empirical mode decomposition and the correlation coefficient
    Yang, Huixiang
    Ning, Tengfei
    Zhang, Bangcheng
    Yin, Xiaojing
    Gao, Zhi
    ADVANCES IN MECHANICAL ENGINEERING, 2017, 9 (04) : 1 - 9
  • [9] Fault Feature Extraction Method for Rolling Bearings Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Variational Mode Decomposition
    Wang, Lijing
    Li, Hongjiang
    Xi, Tao
    Wei, Shichun
    SENSORS, 2023, 23 (23)
  • [10] Blade fault diagnosis using empirical mode decomposition based feature extraction method
    Tan, C. Y.
    Ngui, W. K.
    Leong, M. S.
    Lim, M. H.
    ENGINEERING APPLICATION OF ARTIFICIAL INTELLIGENCE CONFERENCE 2018 (EAAIC 2018), 2019, 255
12345