Anticipating Future Behavior of an Industrial Press Using LSTM Networks

Predictive maintenance is very important in industrial plants to support decisions aiming to maximize maintenance investments and equipment’s availability. This paper presents predictive models based on long short-term memory neural networks, applied to a dataset of sensor readings. The aim is to fo...

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Bibliographic Details
Main Author: Mateus, Balduíno César (author)
Other Authors: Mendes, Mateus (author), Farinha, José Torres (author), Cardoso, António Marques (author)
Format: article
Language:eng
Published: 2021
Subjects:
time series prediction
LSTM prediction
deep learning prediction
predictive maintenance
Online Access:http://hdl.handle.net/10316/100622
Country:Portugal
Oai:oai:estudogeral.sib.uc.pt:10316/100622

Internet

http://hdl.handle.net/10316/100622

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