An Imbalanced Data Augmentation and Assessment Method for Industrial Process Fault Classification With Application in Air Compressors
Author:
Affiliation:
1. College of Information Science and Technology (CIST), Beijing University of Chemical Technology (BUCT), Beijing, China
2. School of Business, Sichuan University, Chengdu, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/19/10012124/10167817.pdf?arnumber=10167817
Reference34 articles.
1. Novel Regularization Double Preserving Integrated With Neighborhood Locality Projections for Fault Diagnosis
2. Imbalanced Learning for Fault Diagnosis Problem of Rotating Machinery Based on Generative Adversarial Networks
3. Intelligent Condition Based Monitoring Using Acoustic Signals for Air Compressors
4. High-Dimensional Time Series Feature Extraction for Low-Cost Machine Olfaction
5. Deep convolutional neural network model based chemical process fault diagnosis
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