Fault Diagnosis of Rolling Bearings Based on a Residual Dilated Pyramid Network and Full Convolutional Denoising Autoencoder

Intelligent fault diagnosis algorithm for rolling bearings has received increasing attention. However, in actual industrial environments, most rolling bearings work under severe working conditions of variable speed and strong noise, which makes the performance of many intelligent fault diagnosis met...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 20; no. 20; p. 5734
Main Authors:	Shi, Hongmei, Chen, Jingcheng, Si, Jin, Zheng, Changchang
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 09.10.2020 MDPI
Subjects:	Accuracy Algorithms Artificial intelligence Bearings Decomposition Deep learning dilated pyramid network Fault diagnosis fully convolutional denoising autoencoder intelligent fault diagnosis Machine learning Machinery Methods Neural networks Noise noise robustness residual learning Signal processing Support vector machines Wavelet transforms
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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