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Shock and Vibration
Volume 2014 (2014), Article ID 283750, 11 pages
http://dx.doi.org/10.1155/2014/283750
Research Article

Kernel Local Linear Discriminate Method for Dimensionality Reduction and Its Application in Machinery Fault Diagnosis

1School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China
2School of Mechanical and Electronic Engineering, Chuzhou University, Chuzhou 239000, China

Received 7 September 2013; Accepted 13 January 2014; Published 27 February 2014

Academic Editor: Gyuhae Park

Copyright © 2014 Kunju Shi 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.

Citations to this Article [2 citations]

The following is the list of published articles that have cited the current article.

  • Quansheng Jiang, Qixin Zhu, Bangfu Wang, and Lihua Guo, “Nonlinear machine fault detection by semi-supervised Laplacian Eigenmaps,” Journal of Mechanical Science and Technology, vol. 31, no. 8, pp. 3697–3703, 2017. View at Publisher · View at Google Scholar
  • Yun Zhang, Yan-Gang Si, Dong Yang, and Xu-Meng Fang, “Aero-Engine Vibration Fault Diagnosis Based on Supervised Manifold Learning,” Tuijin Jishu/Journal of Propulsion Technology, vol. 38, no. 5, pp. 1147–1154, 2017. View at Publisher · View at Google Scholar