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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Bibliographic Details
Main Authors:	Zeqing Yang, Wenbo Zhang, Wei Cui, Lingxiao Gao, Yingshu Chen, Qiang Wei, Libing Liu
Format:	Article
Language:	English
Published:	MDPI AG 2022-08-01
Series:	Energies
Subjects:	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
Online Access:	https://www.mdpi.com/1996-1073/15/15/5671

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