One-Dimensional Convolutional Auto-Encoder for Predicting Furnace Blowback Events from Multivariate Time Series Process Data—A Case Study

One-Dimensional Convolutional Auto-Encoder for Predicting Furnace Blowback Events from Multivariate Time Series Process Data—A Case Study

Modern industrial mining and mineral processing applications are characterized by large volumes of historical process data. Hazardous events occurring in these processes compromise process safety and therefore overall viability. These events are recorded in historical data and are often preceded by...

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Bibliographic Details
Main Authors: Carl Daniel Theunissen, Steven Martin Bradshaw, Lidia Auret, Tobias Muller Louw
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Minerals
Subjects:
process monitoring
failure prediction
semi-supervised model
one-dimensional convolutional network
reconstruction-based model
Online Access:https://www.mdpi.com/2075-163X/11/10/1106

Internet

https://www.mdpi.com/2075-163X/11/10/1106

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