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All issues Volume 227 (2018) MATEC Web Conf., 227 (2018) 02007 References
Open Access
Issue
MATEC Web Conf.
Volume 227, 2018
2018 4th International Conference on Communication Technology (ICCT 2018)
Article Number 02007
Number of page(s) 6
Section Communication Technology and Information Engineering
DOI https://doi.org/10.1051/matecconf/201822702007
Published online 14 November 2018
  1. Wang F, Chen X, Liu C, et al. Reliability Evaluation and Life Prediction of Rolling bearing based on KPCA and WPHM [J]. Vibration. Testing and Diagnostics, vol. 37,no. 3, pp.476-483, Jun. 2017. [Google Scholar]
  2. Wang X, Yan W. Fault diagnosis of Rolling bearing based on variational Mode decomposition and SVM[J]. Vibration and Shock, vol. 36, no. 18, pp.252-256, Sep. 2017. [Google Scholar]
  3. Qin B, Sun G, Ge J, et al. Research on Rolling bearing Fault diagnosis based on Hilbert envelope singular value and IPSO-SVM [J]. Mechanical Transmission, vol. 47, no. 3, pp.166-181, Mar. 2017. [Google Scholar]
  4. Zhou Si, Liao J, Shi X. RBF-SVM kernel parameter selection method and its application in fault diagnosis[J]. Journal of Electronic Measurement and Instruments, vol. 28, no. 3, pp.240-246, Mar. 2014. [Google Scholar]
  5. Samanta, B, Nataraj, C. Use of particle swarm optimization for machinery fault detection[J]. Engineering Applications of Artificial Intelligence, vol. 22, pp.308-316, Oct. 2009. [CrossRef] [Google Scholar]
  6. Li, R, Sopon, P, He, D. Fault features extraction for bearing prognostics. Journal of Intelligent Manufacturing[J]. vol. 23, pp.313-321, Apr. 2012. [CrossRef] [Google Scholar]
  7. Mei H, Yin L, Liu D, et al. Improved Particle Swarm Optimization for Fault diagnosis of SVM Analog Circuits [J]. Journal of Electronic Measurement and Instrumentation, vol. 31,no. 8, pp.1239-1246, Aug. 2017. [Google Scholar]
  8. Fu D, Zhai Y, Yu Q. Research on Rolling bearing Fault diagnosis based on EMD and support Vector Machine[J]. Machine Tools and Hydraulic Pressure, vol. 45,no. 11, pp.184-187, Jun. 2017. [Google Scholar]
  9. Bian B. Rolling bearing Fault diagnosis method based on LCD noise reduction and LS-SVM[J]. Modular Machine Tools and Automatic Machining Technology, vol. 2, pp.:119-122, Feb. 2017. [Google Scholar]
  10. Song G, Wang H, Liu H, et al. Analog circuit fault diagnosis using lifting wavelet transform and SVM[J]. Journal of Electronic Measurement and Instrument vol. 24, no. 1, pp.:17-22, Jan. 2010 [CrossRef] [Google Scholar]

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