AI RESEARCH

An Accurate and Interpretable Framework for Trustworthy Process Monitoring

arXiv CS.AI

ArXi:2302.10426v3 Announce Type: replace Trustworthy process monitoring seeks to build an accurate and interpretable monitoring framework, which is critical for ensuring the safety of energy conversion plant (ECP) that operates under extreme working conditions such as high pressure and temperature. Contemporary self-attentive models, however, fall short in this domain for two main reasons. First, they rely on step-wise correlations that fail to involve physically meaningful semantics in ECP logs, resulting in suboptimal accuracy and interpretability.