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Modelling and Simulation in Engineering
Volume 2011, Article ID 696947, 12 pages
Research Article

Type-2 Fuzzy Modeling for Acoustic Emission Signal in Precision Manufacturing

Department of Mechanical Engineering, Ecole Polytechnique de Montreal, CP 6079, Succursale Centre-Ville, Montreal, QC, Canada H3C 3A7

Received 17 March 2011; Revised 6 June 2011; Accepted 20 June 2011

Academic Editor: Andrzej Dzielinski

Copyright © 2011 Qun Ren 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 [5 citations]

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

  • Qun Ren, Luc Baron, and Marek Balazinski, “Fuzzy identification of cutting acoustic emission with extended subtractive cluster analysis,” Nonlinear Dynamics, vol. 67, no. 4, pp. 2599–2608, 2012. View at Publisher · View at Google Scholar
  • Qun Ren, Marek Balazinski, and Luc Baron, “High-order interval type-2 Takagi-Sugeno-Kang fuzzy logic system and its application in acoustic emission signal modeling in turning process,” International Journal Of Advanced Manufacturing Technology, vol. 63, no. 9-12, pp. 1057–1063, 2012. View at Publisher · View at Google Scholar
  • Qun Ren, Marek Balazinski, Luc Baron, Krzysztof Jemielniak, Ruxandra Botez, and Sofiane Achiche, “Type-2 fuzzy tool condition monitoring system based on acoustic emission in micromilling,” Information Sciences, 2013. View at Publisher · View at Google Scholar
  • Raja Ishak Raja Hamzah, Yasir Hassan Ali, and Roslan Abd Rahman, “Acoustic emission signal analysis and artificial intelligence techniques in machine condition monitoring and fault diagnosis: A review,” Jurnal Teknologi (Sciences and Engineering), vol. 69, no. 2, pp. 121–126, 2014. View at Publisher · View at Google Scholar
  • Qun Ren, Luc Baron, Marek Balazinski, Ruxandra Botez, and Pascal Bigras, “Tool wear assessment based on type-2 fuzzy uncertainty estimation on acoustic emission,” Applied Soft Computing, vol. 31, pp. 14–24, 2015. View at Publisher · View at Google Scholar