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Triplet Loss Guided Adversarial Domain Adaptation for Bearing Fault Diagnosis
Recently, deep learning methods are becomingincreasingly popular in the field of fault diagnosis and achieve great success. However, since the rotation speeds and load conditions of rotating machines are subject to change during operations, the distribution of labeled training dataset for intelligen...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6983071/ https://www.ncbi.nlm.nih.gov/pubmed/31935949 http://dx.doi.org/10.3390/s20010320 |