Fault-Attention Generative Probabilistic Adversarial Autoencoder for Machine Anomaly Detection

Anomaly detection is one of the most fundamental and indispensable components in predictive maintenance. In this article, anomaly detection is modeled as a one-class classification problem. Based on the scenario that the training data only include healthy state data, a fault-attention generative pro...

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Bibliographic Details

Published in:	IEEE transactions on industrial informatics Vol. 16; no. 12; pp. 7479 - 7488
Main Authors:	Wu, Jingyao, Zhao, Zhibin, Sun, Chuang, Yan, Ruqiang, Chen, Xuefeng
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.12.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Anomalies Anomaly detection artificial neural networks Classification condition monitoring Datasets Decoding Failure Feature extraction Generators Manifolds one-class classification Predictive maintenance Probabilistic logic Statistical analysis
ISSN:	1551-3203, 1941-0050
Online Access:	Get full text
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