Local–Global Modeling and Distributed Computing Framework for Nonlinear Plant-Wide Process Monitoring With Industrial Big Data

Volume: 32, Issue: 8, Pages: 3355 - 3365
Published: Aug 1, 2021
Abstract
Industrial big data and complex process nonlinearity have introduced new challenges in plant-wide process monitoring. This article proposes a local-global modeling and distributed computing framework to achieve efficient fault detection and isolation for nonlinear plant-wide processes. First, a stacked autoencoder is used to extract dominant representations of each local process unit and establish the local inner monitor. Second, mutual...
Paper Details
Title
Local–Global Modeling and Distributed Computing Framework for Nonlinear Plant-Wide Process Monitoring With Industrial Big Data
Published Date
Aug 1, 2021
Volume
32
Issue
8
Pages
3355 - 3365
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