One-dimensional decoupled convolutional autoencoder with sparse self-attention mechanism for process monitoring

Industrial processes are constantly disturbed by environmental and human factors during operation. Undifferentiated alarming of these disturbances will bring serious alarm disaster problems.Effectively distinguishing the disturbances that have different effects on the process operation state can hel...

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Bibliographic Details

Published in:	Process safety and environmental protection Vol. 199; p. 107156
Main Authors:	Yang, Yuguo, Shi, Hongbo, Song, Bing, Tao, Yang, Guo, Lei
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.07.2025
Subjects:	Convolutional autoencoder Data distribution alignment Process knowledge embedding Process monitoring Variable-level feature extraction and interaction Process monitoring Process knowledge embedding Data distribution alignment Convolutional autoencoder Variable-level feature extraction and interaction
ISSN:	0957-5820
Online Access:	Get full text
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