Volume 36 Issue 10
Oct.  2021
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WANG Shan, NIU Pingjuan, GUO Yongfeng, WANG Fuzhong, MA Xueru, HAN Lili, WANG Yan. Bearing fault diagnosis based on adaptive piecewise hybrid system[J]. Journal of Aerospace Power, 2021, 36(10): 2090-2100. doi: 10.13224/j.cnki.jasp.20200381
Citation: WANG Shan, NIU Pingjuan, GUO Yongfeng, WANG Fuzhong, MA Xueru, HAN Lili, WANG Yan. Bearing fault diagnosis based on adaptive piecewise hybrid system[J]. Journal of Aerospace Power, 2021, 36(10): 2090-2100. doi: 10.13224/j.cnki.jasp.20200381
shu

Bearing fault diagnosis based on adaptive piecewise hybrid system

doi: 10.13224/j.cnki.jasp.20200381
  • 1.

    School of Mechanical Engineering，Tiangong University，Tianjin 300387，China

  • 2.

    School of Electrical and Electronic Engineering，Tiangong University，Tianjin 300387，China

  • 3.

    School of Mathematical Sciences，Tiangong University，Tianjin 300387，China

  • 4.

    School of Physical Science and Technology，Tiangong University，Tianjin 300387，China

  • 5.

    School of Economics and Management，Tianjin Chengjian University，Tianjin 300384，China

  • Received Date: 2020-09-11
  • Publish Date: 2021-10-28
    Abstract
  • An view of the problem of early bearing fault diagnosis under high level of background noise，an adaptive hybrid piecewise stochastic resonance （APHSR） based on unsaturated stochastic resonance was proposed.According to this method，empirical mode decomposition （EMD） was used to preprocess the signal，while energy density method and correlation coefficient method were adopted to reduce high and low frequency noises respectively，obtaining the optimal intrinsic mode functions；and the model of the unsaturated stochastic resonance system was input after scale transformation，then the optimal parameters were obtained automatically and the fault signal was extracted.The engineering test data showed that the spectrum amplitude of bearing fault characteristic frequency，the difference between characteristic frequency amplitude and surrounding maximum noise，and the system output SNR （signal to noise ratio） were higher than those of EMD denoising and classical bistable stochastic resonance methods.Among them，the output SNR of gearbox fault bearing increased by 9.579 dB and 7.473 dB，respectively，the output SNR of rotor fault bearing increased by 8.597 dB and 5.695 dB，respectively，and the output SNR of outer ring bearing fault of Case Western Reserve University increased by 3.369 dB and 17.043 dB，respectively.The data showed that the APHSR method had high efficiency and strong applicability in bearing fault detection.

     

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