Anomaly detection for multivariate times series through the multi-scale convolutional recurrent variational autoencoder

To realize the anomaly detection for industrial multi-sensor data, we develop a novel multi-scale convolutional recurrent variational autoencoder (MSCRVAE) model. It is a hybrid of convolutional autoencoder and convolutional long short-term memory with variational autoencoder (ConvLSTM-VAE). The Con...

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Veröffentlicht in:	Expert systems with applications Jg. 231; S. 120725
Hauptverfasser:	Xie, Tianming, Xu, Qifa, Jiang, Cuixia
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 30.11.2023
Schlagworte:	Anomaly detection Inner correlation Multi-scale convolutional recurrent variational autoencoder Multi-sensor data Multivariate time series Variational autoencoder Multi-sensor data Variational autoencoder Inner correlation Multi-scale convolutional recurrent variational autoencoder Multivariate time series Anomaly detection
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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