Deep Learning System with Data Augmentation for Electric Machinery Fault Diagnosis from Vibration Signals
Author:
Affiliation:
1. Faculty of Sirindhorn International Institute of Technology Thammasat University,Pathum Thani,Thailand
2. National Electronics and Computer Technology Center,Pathum Thani,Thailand
Funder
Technology Development
Tokyo Institute of Technology
Thammasat University
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9982721/9982797/09983447.pdf?arnumber=9983447
Reference10 articles.
1. A Novel Deep Learning System with Data Augmentation for Machine Fault Diagnosis from Vibration Signals
2. Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization
3. Unsupervised representation learning with deep convolutional generative adversarial networks;radford,2016
4. Machine Learning Based Bearing Fault Diagnosis Using the Case Western Reserve University Data: A Review
5. Generative adversarial nets;goodfellow;Advances in neural information processing systems,2014
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1. A fault diagnosis method based on multi-agent reinforcement learning for small sample data;Fourth International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology (MEMAT 2023);2024-04-01
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