Multi-Scale Convolutional Recurrent Neural Network for Bearing Fault Detection in Noisy Manufacturing Environments

Multi-Scale Convolutional Recurrent Neural Network for Bearing Fault Detection in Noisy Manufacturing Environments

The failure of a facility to produce a product can have significant impacts on the quality of the product. Most equipment failures occur in rotating equipment, with bearing damage being the biggest cause of failure in rotating equipment. In this paper, we propose a denoising autoencoder (DAE) and mu...

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Bibliographic Details
Main Authors:	Seokju Oh, Seugmin Han, Jongpil Jeong
Format:	Article
Language:	English
Published:	MDPI AG 2021-04-01
Series:	Applied Sciences
Subjects:	deep learning fault detection MS-CRNN denoising autoencoder bearing manufacturing
Online Access:	https://www.mdpi.com/2076-3417/11/9/3963

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