Gear Fault Detection Based on Ensemble Empirical Mode Decomposition and Hilbert-Huang Transform

被引:8
|
作者
Ai, Shufeng [1 ]
Li, Hui [2 ]
机构
[1] Zhejiang Inst Media & Commun, Dept Commun Technol, Hangzhou, Zhejiang, Peoples R China
[2] Shijiazhuang Inst Railway Technol, Dept Electromech Engn, Shijiazhuang, Hebei Province, Peoples R China
来源
FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 3, PROCEEDINGS | 2008年
基金
中国国家自然科学基金;
关键词
D O I
10.1109/FSKD.2008.64
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A new approach to fault diagnosis of gear crack based on Ensemble Empirical Mode Decomposition (EEMD) and Hilbert-Huang transform (HHT) technique is presented Firstly, the time-domain vibration signal of the gearbox with gear crack fault is measured Then the original vibration signal is separated into intrinsic oscillation modes, using the ensemble empirical mode decomposition. Secondly, Hilbert transform tracks the modulation energy of the Intrinsic Mode Functions (IMTs) and estimates the instantaneous amplitude and instantaneous frequency. Then the HHT spectrum of the vibration signal can be obtained Therefore, the character of the gear crack faults can be recognized according to the HHT spectrum. The experimental results show that EEAM and HHT spectrum can effectively diagnose the faults of the gear crack.
引用
收藏
页码:173 / +
页数:2
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