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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Autors principals:	Hoe Jun Jeong, Dong Hyun Seo, Sang Hyeon Lee, Seung Ha Kim, Jang Woo Kwon
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2026-01-01
Col·lecció:	IEEE Access
Matèries:	Fault diagnosis multimodal large language model O-XSTFT ReCoFormer rotating machinery vibration signal
Accés en línia:	https://ieeexplore.ieee.org/document/11570120/
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