Transformer diagnostics generate vast amounts of data, yet legal, commercial, cybersecurity, and architectural barriers keep much of it unavailable for collective learning. This article examines how fragmented datasets, inconsistent metadata, and overconfident models limit AI-assisted dissolved gas analysis. It proposes governed data structures, federated or model-to-data learning, a five-level maturity path and strict human oversight, arguing that shared models should support engineering judgement, never replace it.
Locked Data, Limited Intelligence
This article examines how fragmented datasets, inconsistent metadata, and overconfident models limit AI-assisted dissolved gas analysis.
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