Improved fault detection and diagnosis using graph auto encoder and attention-based graph convolution networks
A powerful fault detection and diagnosis (FDD) system plays a pivotal role in achieving operational excellence by maximizing system performance, optimizing maintenance strategies, and ensuring the longevity and resilience of process plants. In the context of FDD for multivariate sensor data, this st...
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| Автори: | , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
Elsevier
2024-06-01
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| Серія: | Digital Chemical Engineering |
| Предмети: | |
| Онлайн доступ: | http://www.sciencedirect.com/science/article/pii/S2772508124000206 |
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