Paper Titles
Design of the Intrinsic Safety CO Monitor with Low Power Consumption
p.886
Development of Key Reliability Tester
p.890
Multi-Channel Simultaneous Data Acquisition System with Variable Sampling Rate
p.896
Somatosensory Application Study Based on Kinect Skeletal Tracking
p.901
Vibration Signal of Generator Features and its Fault Diagnosis Application
p.906
The Fault Diagnosis Method of Diesel Based on Wavelet Pocket and BP Neural Network
p.910
Study on Inversion Surface Parameters of Remote-Sensing Information Serving Vegetation-Surface
p.914
Transmission Method Based on Small Relay Core for Achieve Dynamic Measurement of the Flatness
p.918
Multiple Leakage Detection and Localization Method Based on Bayesian Theory and Genetic Algorithm
p.924

Vibration Signal of Generator Features and its Fault Diagnosis Application

Article Preview

Abstract:

This paper study the wind turbine bearing vibration signal characterization and nonlinear transient characteristics, the transient signal characteristics were established based on Wigner-Ville spectrum entropy and support vector machine (SVM) extraction and fault diagnosis model and quantitative description of nonlinear characteristics of multi-scale method based on LMD sort of entropy, and the effectiveness of dynamic signal feature extraction and fault diagnosis method of the study, a typical experiment platform bearing bearing fault diagnosis experiment verified.

You might also be interested in these eBooks
Advanced Design and Manufacturing Technology IV View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 635-637)

Pages:

906-909

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.635-637.906

Citation:

Cite this paper

Online since:

September 2014

Authors:

Hui Yu Wang*

Keywords:

Fault Diagnosis, Mechanical Failure, Signal Acquisition, Signal Processing, Vibration Signal

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

References

[1] V. Muralidharan, V. Sugumaran: Feature extraction using wavelets and classification through decision tree algorithm for fault diagnosis of mono-block centrifugal pump, Measurement, Vol. 46 (2013), pp.353-359.

DOI: 10.1016/j.measurement.2012.07.007

Google Scholar

[2] G. K. Singh, S. A. K. S. Ahmed: Vibration signal analysis using wavelet transform for isolation and identification of electrical faults in induction machine, Electric Power Systems Research, Vol. 68 (2004), pp.119-136.

DOI: 10.1016/s0378-7796(03)00154-8

Google Scholar

[3] J. Arroyo: Diagnostic method based on the analysis of the vibration and acoustic emission energy for emergency diesel generators in nuclear plants, Applied Acoustics, Vol. 74 (2013), pp.502-508.

DOI: 10.1016/j.apacoust.2012.09.010

Google Scholar

[4] C. Kar: Vibration and current transient monitoring for gearbox fault detection using multiresolution Fourier transform, Journal of Sound and Vibration, Vol. 311 (2008), pp.109-132.

DOI: 10.1016/j.jsv.2007.08.023

Google Scholar

[5] H. X. Chen, Patrick S.K. Chua, G.H. Lim: Fault degradation assessment of water hydraulic motor by impulse vibration signal with Wavelet Packet Analysis and Kolmogorov–Smirnov Test, Mechanical Systems and Signal Processing, Vol. 22 (2008).

DOI: 10.1016/j.ymssp.2008.01.009

Google Scholar

[6] Z. Feng, M. Liang: Complex signal analysis for wind turbine planetary gearbox fault diagnosis via iterative atomic decomposition thresholding, Journal of Sound and Vibration, Vol. 333 (2014), pp.5196-5211.

DOI: 10.1016/j.jsv.2014.05.029

Google Scholar

[7] Q. Gao, C. Duan, H. Fan, Q. Meng: Rotating machine fault diagnosis using empirical mode decomposition, Mechanical Systems and Signal Processing, Vol. 22 (2008), pp.1072-1081.

DOI: 10.1016/j.ymssp.2007.10.003

Google Scholar