Abnormal Detection for Running State of Linear Motor Feeding System Based on Deep Neural Networks

Abnormal Detection for Running State of Linear Motor Feeding System Based on Deep Neural Networks

Because the linear motor feeding system always runs in complex working conditions for a long time, its performance and state transition have great randomness. Therefore, abnormal detection is particularly significant for predictive maintenance to promptly discover the running state degradation trend...

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Podrobná bibliografie
Hlavní autoři: Zeqing Yang, Wenbo Zhang, Wei Cui, Lingxiao Gao, Yingshu Chen, Qiang Wei, Libing Liu
Médium: Článek
Jazyk:English
Vydáno: MDPI AG 2022-08-01
Edice:Energies
Témata:
linear motor feeding system
lack of abnormal samples
deep neural network
anomaly detection
semi-supervised anomaly detection generative adversarial network (GANomaly)
long short-term memory (LSTM) network
On-line přístup:https://www.mdpi.com/1996-1073/15/15/5671

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https://www.mdpi.com/1996-1073/15/15/5671

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