An Integrated Distributed Fault Diagnosis Framework for Large-Scale Industrial Processes Based on Spatio-Temporal Causal Analysis

The networked structure of sensors emerges in large-scale industrial processes. Causal graphs can reveal the underlying mechanisms. However, due to the constraints of material and information flows, industrial process data exhibit complex spatio-temporal characteristics. Traditional causal discovery...

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Vydané v:	IEEE transactions on industrial informatics Ročník 21; číslo 8; s. 6537 - 6546
Hlavní autori:	Hua, Dongjie, Dong, Jie, Peng, Kaixiang, Simani, Silvio
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.08.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Convolutional neural networks Correlation Decoding Distributed fault diagnosis Fault detection Fault diagnosis Feature extraction Hot strip mills Information flow large-scale industrial process Redundancy root cause recognition Spatiotemporal data spatio–temporal causal graph (STCG) spatio–temporal characteristics Strip mills Time series analysis Training Vegetation
ISSN:	1551-3203, 1941-0050
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