Virtual fault simulation for diagnosis of shaft misalignment of rotating machine
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/6949764/6968191/06968225.pdf?arnumber=6968225
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Low-Frequency Adaptation-Deep Neural Network-Based Domain Adaptation Approach for Shaft Imbalance Fault Diagnosis;Journal of Vibration Engineering & Technologies;2023-02-24
2. Misalignment Detection of Rotating Machine Shaft Using Artificial Neural Network and t-Distributed Stochastic Neighbor Embedding Classification Technique;Journal of Control, Automation and Electrical Systems;2022-12-12
3. Application of Spectral and Wavelet Analysis of Stator Current to Detect Angular Misalignment in PMSM Drive Systems;Power Electronics and Drives;2021-01-01
4. Misalignment Detection of Rotor System Based on Adaptive Input-output Model Identification of Motor Speed;2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC2020-ECCE Asia);2020-11-29
5. Instantaneous power factor signature analysis for efficient fault diagnosis in inverter fed three phased induction motors;International Journal of Hydrogen Energy;2017-03
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