Fault Diagnosis with Imbalanced Datasets for Sucker Rod Pumping System Based on Dynamometer Card
Author:
Affiliation:
1. Nanjing University of Aeronautics and Astronautics,College of Automation Engineering,Nanjing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10295546/10295577/10295930.pdf?arnumber=10295930
Reference27 articles.
1. 5-Year progression prediction of endplate defects: Utilizing the EDPP-Flow convolutional neural network based on unbalanced data
2. Imputation-based Ensemble Techniques for Class Imbalance Learning
3. Comprehensive machine and deep learning analysis of sensor-based human activity recognition
4. Remote Blood Pressure Estimation via the Spatiotemporal Mapping of Facial Videos
5. Automatic Recognition of Sucker-Rod Pumping System Working Conditions Using Dynamometer Cards with Transfer Learning and SVM
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