Open Access
MATEC Web of Conferences
Volume 55, 2016
2016 Asia Conference on Power and Electrical Engineering (ACPEE 2016)
Article Number 03004
Number of page(s) 6
Section Fault Diagnostic and Fault-Tolerant Power Converters
Published online 25 April 2016
  1. ZHANG Lin, SUN Anquan, WANG Tianyi, et al. Intelligent fault diagnosis of certain missile equipment. Journal of Central South University(Science and Technology), 216-220.(2013) [Google Scholar]
  2. LI Xue-liang, LIU Shi-bin, CHEN dong, QIU Song-song. Denoising of LAPS signal based on wavelet transform. Journal of Optoelectronics • Laser,25(5):835–839. (2014) [Google Scholar]
  3. Gu Wen-cheng; Chai Bao-ren; Teng Yan-ping. Research on Support Vector Machine Based on Particle Swarm Optimization. Transactions of Beijing Institute of Technology, 34(7):705–709. (2014) [Google Scholar]
  4. Lin Zhang, Liu Tao, etc. Research on Fault Diagnosis of Weapon Equipment Based on SVM. 2012 International Conference on Intelligent System and Applied Material GSAM,1242–1245. (2012) [Google Scholar]
  5. ZENG Zuo-qin. Application of Wavelet Transform for Data Processing in Making and Breaking Test. Electrotechnics Electric. 2:42–47.(2012) [Google Scholar]
  6. Hu Liang-mou. Support Vector Machine fault diagnosis and control technology. Beijing: Academic Press. (2011) [Google Scholar]
  7. An-quan Sun, Lin Zhang, Wen-feng Wang, et al. Robust FDI for a Class of Nonlinear Networked Systems with ROQs. Mathematical Problems in Engineering, 1-8. (2014) [Google Scholar]
  8. Wang Chun-lin, Zho Uhao, Li Guo-neng. etc. Combining Support Vector Machine and Genetic Algorithm to Predict Ash Fusion Temperature. Proceedings of the CSEE, 08:11–15. (2007) [Google Scholar]
  9. Lin H T, Lin C J. A study on sigmoid kernels for SVM and the training of non-PSD kernels by SMO-type methods [EB]. http:/ (2003) [Google Scholar]
  10. Zheng Jun, HOU Rui-feng. Selection of Wavelet Base in Denoising of Wavelet Transform. Journal of Shenyang University,21(2):108–110.(2009) [Google Scholar]

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