Table of Contents Author Guidelines Submit a Manuscript
Shock and Vibration
Volume 2016, Article ID 5468716, 10 pages
http://dx.doi.org/10.1155/2016/5468716
Research Article

A Novel Clustering Method Combining ART with Yu’s Norm for Fault Diagnosis of Bearings

1School of Mechanic and Automation, Wuhan University of Science and Technology, Wuhan, Hubei 430073, China
2School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430081, China

Received 8 December 2015; Revised 4 April 2016; Accepted 18 April 2016

Academic Editor: Mariano Artés

Copyright © 2016 Zengbing Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. M. Polycarpou and A. J. Helmicki, “Automated fault detection and accommodation: a learning system approach,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 25, no. 11, pp. 1447–1458, 1995. View at Publisher · View at Google Scholar
  2. S. Grossberg, “Adaptive resonance theory: how a brain learns to consciously attend, learn, and recognize a changing world,” Neural Networks, vol. 37, pp. 1–47, 2013. View at Publisher · View at Google Scholar · View at Scopus
  3. G. A. Carpenter, S. Grossberg, N. Markuzon, J. H. Reynolds, and D. B. Rosen, “Fuzzy ARTMAP: a neural network architecture for incremental supervised learning of analog multidimensional maps,” IEEE Transactions on Neural Networks, vol. 3, no. 5, pp. 698–713, 1992. View at Publisher · View at Google Scholar · View at Scopus
  4. G. A. Carpenter, S. Grossberg, and D. B. Rosen, “Fuzzy ART: fast stable learning and categorization of analog patterns by an adaptive resonance system,” Neural Networks, vol. 4, no. 6, pp. 759–771, 1991. View at Publisher · View at Google Scholar · View at Scopus
  5. G. A. Carpenter and S. Grossberg, “ART 2: self-organization of stable category recognition codes for analog input patterns,” Applied Optics, vol. 26, no. 30, pp. 4919–4930, 1987. View at Publisher · View at Google Scholar
  6. I. Dagher, M. Georgiopoulos, G. L. Heileman, and G. Bebis, “An ordering algorithm for pattern presentation in fuzzy ARTMAP that tends to improve generalization performance,” IEEE Transactions on Neural Networks, vol. 10, no. 4, pp. 768–778, 1999. View at Publisher · View at Google Scholar · View at Scopus
  7. T.-C. Lin and P.-T. Yu, “Centroid neural network adaptive resonance theory for vector quantization,” Signal Processing, vol. 83, no. 3, pp. 649–654, 2003. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  8. B. S. Yang, T. Han, and J. L. An, “ART-KOHONEN neural network for fault diagnosis of rotating machinery,” Mechanical Systems and Signal Processing, vol. 18, no. 3, pp. 645–657, 2004. View at Publisher · View at Google Scholar · View at Scopus
  9. T. Wakahara and Y. Yamashita, “k-NN classification of handwritten characters via accelerated GAT correlation,” Pattern Recognition, vol. 47, no. 3, pp. 994–1001, 2014. View at Publisher · View at Google Scholar · View at Scopus
  10. D. H. Pandya, S. H. Upadhyay, and S. P. Harsha, “Fault diagnosis of rolling element bearing with intrinsic mode function of acoustic emission data using APF-KNN,” Expert Systems with Applications, vol. 40, no. 10, pp. 4137–4145, 2013. View at Publisher · View at Google Scholar · View at Scopus
  11. L. Szilágyi and S. M. Szilágyi, “Generalization rules for the suppressed fuzzy c-means clustering algorithm,” Neurocomputing, vol. 139, pp. 298–309, 2014. View at Publisher · View at Google Scholar · View at Scopus
  12. P. Luukka, “Similarity classifier using similarity measure derived from Yu's norms in classification of medical data sets,” Computers in Biology and Medicine, vol. 37, no. 8, pp. 1133–1140, 2007. View at Publisher · View at Google Scholar · View at Scopus
  13. L. Silva, R. Moura, A. M. P. Canuto, R. H. N. Santiago, and B. Bedregal, “An interval-based framework for fuzzy clustering applications,” IEEE Transactions on Fuzzy Systems, vol. 23, no. 6, pp. 2174–2187, 2015. View at Publisher · View at Google Scholar
  14. H. J. Zimmermann, Fuzzy Set Theory—And Its Applications, Kluwer Academic, New York, NY, USA, 2001.
  15. K. A. Loparo, Bearings Vibration Data Set, Case Western Reserve University, Cleveland, Ohio, USA, 2003.
  16. Y. Shuzi, W. Ya, and X. Jianping, Time Series Analysis in Engineering Application, Huazhong University of Science and Technology Press, 2007.
  17. J. N. Liang, S. Yang, and A. Winstanley, “Invariant optimal feature selection: a distance discriminant and feature ranking based solution,” Pattern Recognition, vol. 41, no. 5, pp. 1429–1439, 2008. View at Publisher · View at Google Scholar · View at Scopus
  18. B. Efron, “Bootstrap methods: another look at the jackknife,” The Annals of Statistics, vol. 7, no. 1, pp. 1–26, 1979. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet