A New Intelligent Fault Recognition Method for Gearbox

Abstract:

In this paper, a novel method to recognize gear fault pattern was approached based on multi-scale morphological undecimated wavelet decomposition, sample entropy and grey incidence. Firstly, multi-scale morphological undecimated wavelet decomposition was developed based on the characteristic of impulse feature extraction in difference morphological filter. And it was used to process different gear fault signals in five levels. Secondly, the sample entropy of each level was calculated. Finally, the sample entropy was served as the feature vectors and the grey incidence of different gear vibration signals was calculated to identify the fault pattern and condition. Practical example shows the efficiency of the proposed recognition method. It is suitable for on-line monitoring and fault diagnosis of gear.

• Periodical: Advanced Materials Research (Volume 684)
• Pages: 369-372
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.684.369
• Online since: April 2013
• Authors: Wen Bin Zhang, Yan Ping Su, Yan Jie Zhou, Ya Song Pu
• Keywords: Fault Recognition, Gear, Grey Incidence, Multi-Scale Morphological Undecimated Wavelet Decomposition, Sample Entropy

References

[1] J. Goutsias and H. J. A. M. Heijmans. Nonlinear multiresoultion signal decomposition schemes-Part I: morphological pyramids, edited by IEEE Transactions on Image Processing, Vol. 9 (2000), pp.1862-1876.

DOI: 10.1109/83.877209

[2] H. J. A. M. Heijmans and J. Goutsias. Nonlinear multiresolution signal decomposition schemes-Part II: morphological wavelets, edited by IEEE Transaction on Image Processing, Vol. 9 (2000), p.1897-(1913).

DOI: 10.1109/83.877211

[3] J. F. Zhang, J. S. Smith and Q. H. Wu. Morphological undecimated wavelet decomposition for fault location on power transmission lines, edited by IEEE Transactions on circuits and systems, Vol. 53 (2006), pp.1395-1402.

DOI: 10.1109/tcsi.2006.875172

[4] R. Alcaraz and J. J. Rieta. Review on sample entropy applications for the non-invasive analysis of atria fibrillation electrocardiograms, edited by Biomedical Signal Processing and Control, Vol. 5 (2010), pp.1-14.

DOI: 10.1016/j.bspc.2009.11.001

[5] W. B. Zhang, L. Shen, J. S. Li, Q. Cai and H. J. Wang. Morphological undecimated wavelet decomposition for fault feature extraction of rolling element bearing, edited by Proceedings of the 2009 2nd International Congress on Image and Signal Processing, pp.4252-4258. (2009).

DOI: 10.1109/cisp.2009.5303712

[6] L. Shen, X. J. Zhou, W. B. Zhang and Z. G. Zhang. Fault diagnosis of rolling element bearing based on morphological filter and grey incidence, edited by Journal of Vibration and Shock, Vol. 28(2009), pp.17-20.