Abstract
This paper proposed a Rolling bearing health state assessment based on ITD-GMM method to fully dig the favorable information of the vibration signal from the rolling bearing with decline trend. By data analytic, the six components of vibration signal were calculated, and each component has three feature vectors. Finally, the performance of rolling bearing was quantified, and the curve of performance was acquired. The experimental results indicate that the method is feasible and effective for the assessment of rolling bearing.
| Original language | English |
|---|---|
| Pages (from-to) | 46-50 |
| Number of pages | 5 |
| Journal | Vibroengineering Procedia |
| Volume | 16 |
| DOIs | |
| State | Published - 1 Dec 2017 |
| Externally published | Yes |
| Event | 30th International Conference on Vibroengineering - Phuket, Thailand Duration: 16 Dec 2017 → 17 Dec 2017 |
Keywords
- Gaussian mixture model
- Health state assessment
- Intrinsic time-scale decomposition
- Rolling bearing
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