An Online Remaining Useful Life Prediction Method With Adaptive Degradation Model Calibration
Author:
Affiliation:
1. Zhijian Laboratory, Rocket Force University of Engineering, Xi’an, 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/ielx7/7361/10336249/10275804.pdf?arnumber=10275804
Reference53 articles.
1. Review of Machine Learning Based Remaining Useful Life Prediction Methods for Equipment
2. Optimal Design for Step-Stress Accelerated Degradation Tests
3. Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
4. A robust hybrid predictive model of mixed oil length with deep integration of mechanism and data
5. An ensemble model for predicting the remaining useful performance of lithium-ion batteries
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