Deep Fault Recognizer: An Integrated Model to Denoise and Extract Features for Fault Diagnosis in Rotating Machinery

Deep Fault Recognizer: An Integrated Model to Denoise and Extract Features for Fault Diagnosis in Rotating Machinery

Fault diagnosis in rotating machinery is significant to avoid serious accidents; thus, an accurate and timely diagnosis method is necessary. With the breakthrough in deep learning algorithm, some intelligent methods, such as deep belief network (DBN) and deep convolution neural network (DCNN), have...

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Bibliographic Details
Main Authors: Xiaojie Guo, Changqing Shen, Liang Chen
Format: Article
Language:English
Published: MDPI AG 2016-12-01
Series:Applied Sciences
Subjects:
fault diagnosis
deep learning
stacked denoising autoencoder
feature extraction
integrated deep fault recognizer
Online Access:http://www.mdpi.com/2076-3417/7/1/41

Internet

http://www.mdpi.com/2076-3417/7/1/41

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