Induction Machine Fault Detection and Classification Using Non-Parametric, Statistical-Frequency Features and Shallow Neural Networks
Author:
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology
Link
http://xplorestaging.ieee.org/ielx7/60/9438973/09234012.pdf?arnumber=9234012
Cited by 21 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
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2. Convolutional Neural Network-Based Online Stator Inter-Turn Faults Detection for Line-Connected Induction Motors;IEEE Transactions on Industry Applications;2024-05
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4. One-Dimensional LSTM-Regulated Deep Residual Network for Data-Driven Fault Detection in Electric Machines;IEEE Transactions on Industrial Electronics;2024-03
5. A Comparative Classification Study for Broken Rotor Bar Fault and its Severity Analysis using Machine Learning Approaches in Rotating Machines;2023 IEEE International Conference on Energy Technologies for Future Grids (ETFG);2023-12-03
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