Intelligent Condition-Based Monitoring of Rotary Machines With Few Samples

Recently, intelligent condition based monitoring systems build on deep learning methods have gained popularity. The success of these methods relies upon the large labeled training datasets, which are crucial to collect in industries. Therefore, building an effective fault diagnosis system becomes ch...

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Veröffentlicht in:	IEEE sensors journal Jg. 20; H. 23; S. 14337 - 14346
Hauptverfasser:	Dixit, Sonal, Verma, Nishchal K.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.12.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Air compressors Centroids Classifiers condition based monitoring Condition monitoring conditional variational autoencoder Datasets Fault diagnosis Intelligent sensors Machine learning Machinery condition monitoring Multilayers Neural networks Rotary machines Rotsting machines Sensor data Support vector machines synthetic data Training
ISSN:	1530-437X, 1558-1748
Online-Zugang:	Volltext
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