Application of frequency family separation method based upon EMD and local Hilbert energy spectrum method to gear fault diagnosis

被引:97
作者
Cheng, Junsheng [1 ]
Yu, Dejie [1 ]
Tang, Jiashi [2 ]
Yang, Yu [1 ]
机构
[1] Hunan Univ, Coll Mech & Automat Engn, Changsha 410082, Hunan, Peoples R China
[2] Hunan Univ, Coll Mech & Aerosp, Changsha 410082, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
empirical mode decomposition (EMD); intrinsic mode functions (IMFs); Hilbert-Huang transform; frequency family; local Hilbert energy spectrum; gear; fault diagnosis;
D O I
10.1016/j.mechmachtheory.2007.05.007
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Targeting the advantages of Hilbert-Huang transform (HHT) and the characteristics of gear fault vibration signals, HHT is introduced into gear fault diagnosis. The concept of local Hilbert energy spectrum is proposed and two gear fault diagnosis approaches, namely, frequency family separation method based on EMD (empirical mode decomposition) and local Hilbert energy spectrum method, are put forward, which are applied to gear fault diagnosis. Considering that the gear fault vibration signal is a multi-component amplitude-demodulated and frequency-demodulated (AM-FM) signal and EMD could exactly decompose the AM-FM signal into a number of intrinsic mode functions (IMFs), each of which can be amplitude-demodulated or frequency-demodulated component, the frequency families could be separated effectively from the gear vibration signal by applying EMD to the gear vibration signal. Furthermore, when faults occur in gear, the energy of the gear vibration signal would change correspondingly, whilst the local Hilbert energy spectrum can exactly provide the energy distribution of the signal in certain frequency with the change of the time and frequency. Thus, the fault information of the gear vibration signal can be extracted effectively from the local Hilbert energy spectrum. The analysis results from the experimental signals show that both frequency family separation method based on EMD and local Hilbert energy spectrum method could extract the characteristics information of the gear fault vibration signal effectively. (C) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:712 / 723
页数:12
相关论文
共 16 条
[1]   Performance and limitations of the Hilbert-Huang transformation (HHT) with an application to irregular water waves [J].
Dätig, M ;
Schlurmann, T .
OCEAN ENGINEERING, 2004, 31 (14-15) :1783-1834
[2]  
[何岭松 He Lingsong], 2002, [振动工程学报, Journal of Vibration Engineering], V15, P119
[3]   A new view of nonlinear water waves: The Hilbert spectrum [J].
Huang, NE ;
Shen, Z ;
Long, SR .
ANNUAL REVIEW OF FLUID MECHANICS, 1999, 31 :417-457
[4]   The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis [J].
Huang, NE ;
Shen, Z ;
Long, SR ;
Wu, MLC ;
Shih, HH ;
Zheng, QN ;
Yen, NC ;
Tung, CC ;
Liu, HH .
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 1998, 454 (1971) :903-995
[5]   A note on analyzing nonlinear and nonstationary ocean wave data. [J].
Hwang, PA ;
Huang, NE ;
Wang, DW .
APPLIED OCEAN RESEARCH, 2003, 25 (04) :187-193
[6]   Wear detection in gear system using Hilbert-Huang transform [J].
Li, Hui ;
Zhang, Yuping ;
Zheng, Haiqi .
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2006, 20 (11) :1781-1789
[7]   Gearbox fault diagnosis using adaptive wavelet filter [J].
Lin, J ;
Zuo, MJ .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2003, 17 (06) :1259-1269
[8]   Gear defect detection through model-based wideband demodulation of vibrations [J].
Ma, J ;
Li, CJ .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 1996, 10 (05) :653-665
[9]   Decomposition of gear vibration signals by the generalised S transform [J].
McFadden, PD ;
Cook, JG ;
Forster, LM .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 1999, 13 (05) :691-707
[10]   Detection of gear faults by decomposition of matched differences of vibration signals [J].
McFadden, PD .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2000, 14 (05) :805-817