Volume 36 Issue 8
Aug.  2010
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Hong Jie, Han Lei, Miao Xuewen, et al. Assessment based on support vector machine for rolling bearing grade-life[J]. Journal of Beijing University of Aeronautics and Astronautics, 2010, 36(8): 896-899. (in Chinese)
Citation: Hong Jie, Han Lei, Miao Xuewen, et al. Assessment based on support vector machine for rolling bearing grade-life[J]. Journal of Beijing University of Aeronautics and Astronautics, 2010, 36(8): 896-899. (in Chinese)

Assessment based on support vector machine for rolling bearing grade-life

  • Received Date: 29 Jun 2009
  • Publish Date: 30 Aug 2010
  • Grade-life was used to describe rolling bearing-s service life, and an assessment model was presented for bearing-s Grade-life. Signal feature extraction and pattern recognition algorithm were keys to construct the model. Vibration signals of the rolling bearing were analyzed, and the wavelet packet analysis theory was adopted to extract the grade-life characteristics. Through signal reconfiguration with wavelet package to extract energy feature of various frequency bands acting as the life feature vector was input into support vector machine (SVM) to realize the mapping between the grade-life vector and the grade-life of rolling bearing, and the model in establishing the identification by using bearing test stand run-to-failure data. The validity and creditability of model has been demonstrated by bearing test stand dates.

     

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