Auxiliary-model-based domain adaptation for reciprocating compressor diagnosis under variable conditions
Author:
Affiliation:
1. School of Mechanical and Transportation Engineering, China University of Petroleum (Beijing), Changping, Beijing, China
Publisher
IOS Press
Subject
Artificial Intelligence,General Engineering,Statistics and Probability
Reference13 articles.
1. Rolling bearing fault diagnosis under variable conditions using LMD-SVD and extreme learning machine;Tian;Mechanism and Machine Theory,2015
2. Fault diagnosis network design for vehicle on-board equipments of high-speed railway: A deep learning approach;Yin;Engineering Applications of Artificial Intelligence,2016
3. A novel deep autoencoder feature learning method for rotating machinery fault diagnosis;Shao;Mechanical Systems and Signal Processing,2017
4. Domain adaptation for statistical classifiers;Daume;Artificial Intelligence Research,2006
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