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Shock and Vibration
Volume 2015, Article ID 737213, 10 pages
Research Article

Uncertainty Reduced Novelty Detection Approach Applied to Rotating Machinery for Condition Monitoring

1College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nan Jing 210016, China
2Faculty of Engineering and the Environment, University of Southampton, Southampton S016 7QF, UK

Received 7 May 2015; Revised 25 July 2015; Accepted 27 July 2015

Academic Editor: Mickaël Lallart

Copyright © 2015 S. Ma 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.

  • David N. Coelho, Guilherme A. Barreto, and Claudio M. S. Medeiros, “Detection of short circuit faults in 3-phase converter-fed induction motors using kernel SOMs,” 2017 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM), pp. 1–7, . View at Publisher · View at Google Scholar
  • Jesus Adolfo Cariño-Corrales, Juan Jose Saucedo-Dorantes, Daniel Zurita-Millán, Miguel Delgado-Prieto, Juan Antonio Ortega-Redondo, Roque Alfredo Osornio-Rios, and Rene De Jesus Romero-Troncoso, “Vibration-Based Adaptive Novelty Detection Method for Monitoring Faults in a Kinematic Chain,” Shock and Vibration, vol. 2016, 2016. View at Publisher · View at Google Scholar