Fault Diagnosis Based on Digital Twin Modeling of Bearings
Author:
Affiliation:
1. Xinjiang University,School of Mechanical Engineering,Urumqi,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10667475/10667476/10667568.pdf?arnumber=10667568
Reference13 articles.
1. Development and Prospects of Fault Diagnosis and Remaining Life Prediction for High-Speed Train Bearings [J];Song;Bearing,2020
2. Opportunities and Challenges of Machinery Intelligent Fault Diagnosis in Big Data Era
3. Failure modes, mechanisms and causes of shafts in mechanical equipment [J];Nan;Engineering Failure Analysis,2022
4. Bearing remaining useful life prediction using support vector machine and hybrid degradation tracking model
5. Industrial Big Data Analytics and Cyber-physical Systems for Future Maintenance & Service Innovation
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