A Method of Rolling Bearing Fault Diagnose Based on Double Sparse Dictionary and Deep Belief Network
Feature extraction is the key technology in the data-driven intelligent fault diagnosis methods of rolling bearing. However, the acquired features by the traditional methods, which mainly based on time-frequency domain, sometimes cannot well represent the characteristics of the signal and are diffic...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9121996/ |