A novel bearing fault diagnosis method based on 2D image representation and transfer learning-convolutional neural network-Reference-Cited by-同舟云学术

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A novel bearing fault diagnosis method based on 2D image representation and transfer learning-convolutional neural network

Published:2019-04-02 Issue:5 Volume:30 Page:055402
ISSN:0957-0233
Container-title:Measurement Science and Technology
language:
Short-container-title:Meas. Sci. Technol.

Author:

Ma Ping,Zhang Hongli^ORCID,Fan Wenhui,Wang Cong,Wen Guangrui,Zhang Xining^ORCID

Funder

The National Science Foundation of China

The Outstanding Doctor Graduate Student Innovation Project ensemble

The Graduate Student Innovation Project of Xinjiang Uygur Autonomous Region

Publisher

IOP Publishing

Subject

Applied Mathematics,Instrumentation,Engineering (miscellaneous)

Link

http://iopscience.iop.org/article/10.1088/1361-6501/ab0793/pdf

Reference35 articles.

1. A review on data-driven fault severity assessment in rolling bearings

2. A data-driven method to enhance vibration signal decomposition for rolling bearing fault analysis

3. Generator bearing fault diagnosis for wind turbine via empirical wavelet transform using measured vibration signals

4. A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

5. Fault Detection of Bearing Systems through EEMD and Optimization Algorithm

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