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Rolling Bearing Feature Extraction Method Based on Improved Intrinsic Time-Scale Decomposition and Mathematical Morphological Analysis
| Content Provider | MDPI |
|---|---|
| Author | Ma, Jianpeng Chen, Guodong Li, Chengwei Zhan, Liwei Zhang, Guang-Zhu |
| Copyright Year | 2021 |
| Description | To overcome the difficulty of extracting the feature frequency of early bearing faults, this paper proposes an adaptive feature extraction scheme. First, the improved intrinsic time-scale decomposition, proposed in this paper, is used as a noise reduction method. Then, we use the adaptive composite quantum morphology analysis method, also proposed in this paper, to perform an adaptive demodulation analysis on the signal, and finally, extract the fault characteristics in the envelope spectrum. The experimental results show that the scheme performs well in the early fault feature extraction of rolling bearings. |
| Starting Page | 2719 |
| e-ISSN | 20763417 |
| DOI | 10.3390/app11062719 |
| Journal | Applied Sciences |
| Issue Number | 6 |
| Volume Number | 11 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-03-18 |
| Access Restriction | Open |
| Subject Keyword | Applied Sciences Industrial Engineering Intrinsic Time-scale Decomposition Mathematical Morphological Analysis Feature Extraction Rolling Bearing Fault Diagnosis |
| Content Type | Text |
| Resource Type | Article |
