TFFC-RNN:A New RNN Based Approach for Bearing and Misalignment Compound Fault
Author:
Affiliation:
1. Harbin Institute of Technology,Institute of Power Electronics & Electric Drives,Harbin,China
2. Institute of Power Electronics & Electric Drives, Harbin Institute of Technology,Harbin,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9806820/9806821/09807095.pdf?arnumber=9807095
Reference18 articles.
1. RNN-based Method for Fault Diagnosis of Grinding System
2. APPLICATION OF THE ENVELOPE AND WAVELET TRANSFORM ANALYSES FOR THE DIAGNOSIS OF INCIPIENT FAULTS IN BALL BEARINGS
3. Classification of unbalance and misalignment faults in rotor using multi-axis time domain features
4. Motor Fault Detection and Feature Extraction Using RNN-Based Variational Autoencoder
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1. A Comprehensive Study of Fast Fourier Transform for Bearing Fault Diagnosis with Long Short-Term Memory Networks;2023 3rd International Conference on Electrical Engineering and Mechatronics Technology (ICEEMT);2023-07-21
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