Volume 34 Issue 10
Oct.  2019
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DAI Shaowu, CHEN Qiangqiang, NIE Zijian. Rolling bearing fault diagnosis based on smoothness priors approach and fuzzy entropy[J]. Journal of Aerospace Power, 2019, 34(10): 2218-2226. doi: 10.13224/j.cnki.jasp.2019.10.015
Citation: DAI Shaowu, CHEN Qiangqiang, NIE Zijian. Rolling bearing fault diagnosis based on smoothness priors approach and fuzzy entropy[J]. Journal of Aerospace Power, 2019, 34(10): 2218-2226. doi: 10.13224/j.cnki.jasp.2019.10.015

Rolling bearing fault diagnosis based on smoothness priors approach and fuzzy entropy

doi: 10.13224/j.cnki.jasp.2019.10.015
  • Received Date: 2019-03-31
  • Publish Date: 2019-10-28
  • Due to the complexity of mechanical systems, the randomicity of the vibration signal on different scales, it’s necessary to analyze the vibration signal with fuzzy entropy (FE) in a multi-scale way. Based on multi-scale fuzzy entropy analysis of vibration signals, a method of rolling bearing fault diagnosis based on FE and the smoothness priors approach (SPA) was put forward. The SPA algorithm was used to decompose the vibration signal, and the trend with de-trend was obtained. Secondly, the FE of the trend and de-trend was calculated. The FE entropies were accordingly seen as the characteristic vectors, then inputed to the optimized support vector machine (OSVM). Finally, the proposed method was applied to the experimental data. The analysis results showthat the proposed approach can achieve 100% fault diagnosis accuracy when only two component features are extracted, so it can effectively achieve fault diagnosis of rolling bearings.

     

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