DocumentCode :
497344
Title :
Gear Fault Diagnosis Based on EMD and AR Spectrum Analysis
Author :
Ai, Shufeng ; Li, Hui ; Fu, Lihui
Author_Institution :
Dept. of Commun. Technol., Zhejiang Univ. of Media & Commun., Hangzhou, China
Volume :
1
fYear :
2009
fDate :
11-12 April 2009
Firstpage :
673
Lastpage :
676
Abstract :
A novel method to fault diagnosis of gear crack based on empirical mode decomposition (EMD) and autoregressive (AR) spectrum is presented. This method can carry out empirical mode decomposition and extract feature information of different machine parts in condition monitoring and fault diagnosis of machinery. The main objective of empirical mode decomposition is to separate the time series data into components with different time scale. Then the AR model estimation is applied to each intrinsic mode function and the AR spectrum is obtained. As an example, the vibration signal of a gearbox is analyzed. The experimental results show that this method based on empirical mode decomposition and autoregressive spectrum can effectively diagnose the crack faults of gear.
Keywords :
autoregressive processes; condition monitoring; fault diagnosis; feature extraction; gears; spectral analysis; time series; vibrations; AR spectrum analysis; autoregressive spectrum; condition monitoring; empirical mode decomposition analysis; fault diagnosis; feature extraction; gears; machine parts; time series data; vibration signal; Cepstral analysis; Data analysis; Fault detection; Fault diagnosis; Fourier transforms; Gears; Machinery; Signal analysis; Time frequency analysis; Wavelet analysis; AR Spectrum; Vibration; empirical mode decomposition; fault diagnosis; gear;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
Conference_Location :
Zhangjiajie, Hunan
Print_ISBN :
978-0-7695-3583-8
Type :
conf
DOI :
10.1109/ICMTMA.2009.430
Filename :
5203062
Link To Document :
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