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Shock and Vibration
Volume 2016, Article ID 1212457, 14 pages
Research Article

Multisensor Fused Fault Diagnosis for Rotation Machinery Based on Supervised Second-Order Tensor Locality Preserving Projection and Weighted -Nearest Neighbor Classifier under Assembled Matrix Distance Metric

1School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China
2Department of Mechanical and Dynamic Engineering, Harbin University of Science and Technology, Harbin 150080, China

Received 15 June 2016; Revised 21 October 2016; Accepted 24 October 2016

Academic Editor: Fiorenzo A. Fazzolari

Copyright © 2016 Fen Wei 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 [4 citations]

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

  • Hamidreza Seiti, and Ashkan Hafezalkotob, “Developing pessimistic-optimistic risk-based methods for multi-sensor fusion: An interval-valued evidence theory approach,” Applied Soft Computing, 2018. View at Publisher · View at Google Scholar
  • Petr Baron, Marek Kočiško, and Jozef Dobránsky, “The dynamic parameters correlation assessment of the textile machine high-speed bearings in changed technological conditions,” Measurement, vol. 116, pp. 575–585, 2018. View at Publisher · View at Google Scholar
  • Fen Wei, Jiang-Hua Ge, Qi Liu, Ya-Ping Wang, and Di Xu, “Fault diagnosis method of gearbox supporting tension machine and KNN-AMDM decision fusion,” Zhendong Gongcheng Xuebao/Journal of Vibration Engineering, vol. 31, no. 6, pp. 1093–1101, 2018. View at Publisher · View at Google Scholar
  • Jingchao Li, Dongyuan Bi, Yulong Ying, Kai Wei, and Bin Zhang, “An Improved Algorithm for Extracting Subtle Features of Radiation Source Individual Signals,” Electronics, vol. 8, no. 2, pp. 246, 2019. View at Publisher · View at Google Scholar