Implementation of a Sequence-to-Sequence Stacked Sparse Long Short-Term Memory Autoencoder for Anomaly Detection on Multivariate Timeseries Data of Industrial Blower Ball Bearing Units

Implementation of a Sequence-to-Sequence Stacked Sparse Long Short-Term Memory Autoencoder for Anomaly Detection on Multivariate Timeseries Data of Industrial Blower Ball Bearing Units

The advent of Industry 4.0 introduced new ways for businesses to evolve by implementing maintenance policies leading to advancements in terms of productivity, efficiency, and financial performance. In line with the growing emphasis on sustainability, industries implement predictive techniques based...

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Bibliographic Details
Main Authors: Elisavet Karapalidou, Nikolaos Alexandris, Efstathios Antoniou, Stavros Vologiannidis, John Kalomiros, Dimitrios Varsamis
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Sensors
Subjects:
anomaly detection
autoencoder
deep learning
industrial data
long short-term memory
predictive maintenance
Online Access:https://www.mdpi.com/1424-8220/23/14/6502

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https://www.mdpi.com/1424-8220/23/14/6502

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