Multiscale intelligent fault detection system based on agglomerative hierarchical clustering using stacked denoising autoencoder with temporal information

Deep learning-based process monitoring has achieved remarkable progress. Generally, a deep model is empirically selected before the data features are learned. In this study, the interpretability and suitability of stacked denoising autoencoder (SDAE) in process monitoring territory are theoretically...

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Veröffentlicht in:	Applied soft computing Jg. 95; S. 106525
Hauptverfasser:	Yu, Jianbo, Yan, Xuefeng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.10.2020
Schlagworte:	Multiscale analysis Process monitoring Robust features Stacked denoising autoencoder Temporal information Process monitoring Stacked denoising autoencoder Robust features Multiscale analysis Temporal information
ISSN:	1568-4946
Online-Zugang:	Volltext
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