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Contrastive Learning for Fault Detection and Diagnostics in the Context of Changing Operating Conditions and Novel Fault Types
Reliable fault detection and diagnostics are crucial in order to ensure efficient operations in industrial assets. Data-driven solutions have shown great potential in various fields but pose many challenges in Prognostics and Health Management (PHM) applications: Changing external in-service factors...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8161334/ https://www.ncbi.nlm.nih.gov/pubmed/34065164 http://dx.doi.org/10.3390/s21103550 |