Abstract
This paper applies an Artificial Neural Networks (ANN) method– Wavelet Neural Networks (WNN) on fault diagnosis for a wind turbine gearbox. A gearbox is one of the most important units in a wind turbine drive train. It is significant to study fault diagnosis of gearbox conditions. First this paper presents the principles and advantages of Wavelet Neural Networks. Second this paper specifies the vibration mechanism of the gearbox and the feature parameter group reflecting fault feature, and then the standard fault samples (training samples) and simulation samples (testing samples) are obtained. Third this paper applies the WNN method to perform diagnosing. The accurate diagnostic results have proved the effectiveness of the method for vibration fault diagnosis of gearbox. Finally, the relative advantages of the WNN method are contrasted with those of BPNN method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Cai, N., Hu, K., Li, S., Su, W.: Wavelet neural network and its application. J. Chinese Journal of Stereology and Image Analysis 4, 239–245 (2001)
Zhang, Q., Benveniste, A.T.: Wavelet networks. IEEE Trans. On Neural Networks 3(6), 889–898 (1992)
Xu, Q., Meng, X., Han, X., Meng, S.: Gas turbine fault diagnosis based on wavelet neural network. In: Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, Beijing, China, 2-4, November, pp. 738–741 (2007)
Rui, Z., Xu, L., Feng, R.: Gear faults diagnosis based on wavelet neural network. Journal of Mechanical Transmission 01, 80–83 (2008)
Martin, V., Cormac, H.: Wavelets and filter banks: theory and design. IEEE Trans. On Signal Processing 40, 2207–2231 (1992)
Leonard, J.A., Kramer, M.A.: Radial basis function networks for classifying process faults. IEEE Control Systems, 31–38 (1991)
Dickhaus, H., Kohonen, H.H.: Classifying biosignals with wavelet networks. IEEE Engineering in Medicine and Biology, 103–111 (1996)
Tang, X., Xie, Z., Wang, Z., Wu, J.: Fault diagnosis of gearbox for wind turbine. Noise and Vibration Control 01, 120–124 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Huang, Q., Jiang, D., Hong, L., Ding, Y. (2008). Application of Wavelet Neural Networks on Vibration Fault Diagnosis for Wind Turbine Gearbox. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87734-9_36
Download citation
DOI: https://doi.org/10.1007/978-3-540-87734-9_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87733-2
Online ISBN: 978-3-540-87734-9
eBook Packages: Computer ScienceComputer Science (R0)