Data-Driven Bearing Fault Diagnosis of Microgrid Network Power Device Based on a Stacked Denoising Autoencoder in Deep Learning and Clustering by Fast Search without Data Labels

The traditional health indicator (HI) construction method of electric equipment devices in microgrid networks, such as bearings that require different time-frequency domain indicators, needs several models to combine. Therefore, it is necessary to manually select appropriate and sensitive models, su...

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Bibliographic Details
Published in:	Complexity (New York, N.Y.) Vol. 2020; no. 2020; pp. 1 - 29
Main Authors:	Zhang, Xiaodi, Li, Xin, Shu, Xin, Xu, Fan
Format:	Journal Article
Language:	English
Published:	Cairo, Egypt Hindawi Publishing Corporation 02.11.2020 Hindawi John Wiley & Sons, Inc Wiley
Subjects:	Analysis Bearings Clustering Data search Decomposition Deep learning Degradation Distributed generation Electric equipment Electrical equipment and supplies Electrical machinery Electronic devices Entropy (Information theory) Fault diagnosis Frequency domain analysis Indicators Kurtosis Noise Noise reduction Permutations Principal components analysis Time series Wear Prince Edward Island
ISSN:	1076-2787, 1099-0526
Online Access:	Get full text
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