A process monitoring and fault isolation framework based on variational autoencoders and branch and bound method

DOI10.1016/j.jfranklin.2021.11.016zbMath1481.93099OpenAlexW3217688506MaRDI QIDQ2071230

Kaixiang Peng, Ruihua Jiao, Peng Tang

Publication date: 25 January 2022

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2021.11.016

zbMATH Keywords

branch and boundprocess monitoringfault isolationvariational autoencodermissing value estimation

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Application models in control theory (93C95)

Related Items (2)

Fault detectability analysis for linear systems within a set-based framework ⋮ Fault detection and isolation of multi-variate time series data using spectral weighted graph auto-encoders

Cites Work

• Reconstruction-based contribution for process monitoring

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