A health indicator construction method of rolling bearing based on vibration image features and deep autoencoder network
Author:
Affiliation:
1. Xi’an University of Science and Technology,School of Mechanical Engineering,Xi’an,China
Funder
National Natural Science Foundation of China
China Postdoctoral Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10336048/10336051/10336116.pdf?arnumber=10336116
Reference20 articles.
1. Predictive Monitoring of Incipient Faults in Rotating Machinery: A Systematic Review from Data Acquisition to Artificial Intelligence
2. A novel health indicator for intelligent prediction of rolling bearing remaining useful life based on unsupervised learning model
3. Construction of health indicators for condition monitoring of rotating machinery: A review of the research
4. A novel optimized SVM classification algorithm with multi-domain feature and its application to fault diagnosis of rolling bearing
5. Entropy Measures in Machine Fault Diagnosis: Insights and Applications
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