Deep Domain Adaptation Model for Bearing Fault Diagnosis with Riemann Metric Correlation Alignment
In many real-world fault diagnosis applications, due to the frequent changes in working conditions, the distribution of labeled training data (source domain) is different from the distribution of the unlabeled test data (target domain), which leads to performance degradation. In order to solve this...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2020-01-01
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| Series: | Mathematical Problems in Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/4302184 |