43 / 2017-07-03 09:58:58
Fault Classify of Rolling Bearing Based on Time-frequency Generalized Dimension of Vibration Signal and ANFIS
全文录用
芳 李 / 大连交通大学
Research shows that multi-fractal can not only exhibit the singular probability distribution form of the fractal signal completely, but also increase the fine level of signal geometrical characteristics and local scaling behavior. Based on multi fractal dimension calculation of time frequency matrix of vibration signal of rolling bearing in this paper, energy distribution characteristics of time-frequency domain of vibration signal could be extracted, then adaptive fuzzy neural network(ANFIS)was used in signal classification. Experiments showed that this method can realize fault classify of rolling bearing effectively, it is feasible in engineering application.
重要日期
  • 会议日期

    10月03日

    2017

    10月05日

    2017

  • 06月25日 2017

    初稿截稿日期

  • 07月05日 2017

    初稿录用通知日期

  • 07月15日 2017

    终稿截稿日期

  • 10月05日 2017

    注册截止日期

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