Gear Fault Diagnosis Based on Empirical Mode Decomposition and 1.5 Dimension Spectrum
Joint Authors
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-01-11
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Aiming at the nonlinear and nonstationary feature of mechanical fault vibration signal, a new fault diagnosis method, which is based on a combination of empirical mode decomposition (EMD) and 1.5 dimension spectrum, is proposed.
Firstly, the vibration signal is decomposed by EMD and the correlation coefficient between each intrinsic mode function and original signal is calculated.
Then these intrinsic mode function components, which have a big correlation coefficient, are selected to estimate its 1.5 dimension spectrum.
And this method uses 1.5 dimension spectrum of each intrinsic mode function to reconstruct its power spectrum.
And these power spectrums are summed to obtain the primary power spectrum of gear fault signal.
Finally, the information feature of fault is extracted from the reconstructed 1.5 dimension spectrum.
A model to reconstruct 1.5 dimension spectrum is established, and the principle and steps of the method are presented.
Some simulated and measured gear fault signals have been processed to demonstrate the effectiveness of new method.
The result shows that this method can greatly inhibit the interference of Gauss noise to raise the SNR and recognize the secondary phase coupling feature of the signal.
The proposed method has a good real-time performance and provides an effective method to determine the early crack fault of gear root.
American Psychological Association (APA)
Cai, Jianhua& Li, Xiaoqin. 2016. Gear Fault Diagnosis Based on Empirical Mode Decomposition and 1.5 Dimension Spectrum. Shock and Vibration،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1119399
Modern Language Association (MLA)
Cai, Jianhua& Li, Xiaoqin. Gear Fault Diagnosis Based on Empirical Mode Decomposition and 1.5 Dimension Spectrum. Shock and Vibration No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1119399
American Medical Association (AMA)
Cai, Jianhua& Li, Xiaoqin. Gear Fault Diagnosis Based on Empirical Mode Decomposition and 1.5 Dimension Spectrum. Shock and Vibration. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1119399
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1119399