A Multimodal Framework for Vibration Signals via Knowledge-Guided Preprocessing (O-XSTFT) and Reconstruction-Contrastive Tokenization (ReCoFormer)
This study formulates vibration-based multimodal diagnosis as a physically grounded signal-to-token interface problem and proposes an integrated framework that transforms rotating-machinery vibration signals into fixed-length tokens for large language model (LLM)-based diagnosis. The proposed method...
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| Главные авторы: | , , , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
IEEE
2026-01-01
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| Серии: | IEEE Access |
| Предметы: | |
| Online-ссылка: | https://ieeexplore.ieee.org/document/11570120/ |
| Метки: |
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