43 / 2017-07-03 09:58:58
Fault Classify of Rolling Bearing Based on Time-frequency Generalized Dimension of Vibration Signal and ANFIS
Draft Accepted
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.
Important Date
  • Conference Date

    Oct 03

    2017

    to

    Oct 05

    2017

  • Jun 25 2017

    Draft paper submission deadline

  • Jul 05 2017

    Draft Paper Acceptance Notification

  • Jul 15 2017

    Final Paper Deadline

  • Oct 05 2017

    Registration deadline

Contact Information
  • Miss 朱老师
  • +86********