AI RESEARCH
LoRM: Learning the Language of Rotating Machinery for Self-Supervised Condition Monitoring
arXiv CS.CL
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ArXi:2604.05863v1 Announce Type: new We present LoRM (Language of Rotating Machinery), a self-supervised framework for multi-modal rotating-machinery signal understanding and real-time condition monitoring. LoRM is built on the idea that rotating-machinery signals can be viewed as a machine language: local signals can be tokenised into discrete symbolic units, and their future evolution can be predicted from observed multi-sensor context.