Results 181 to 190 of about 20,775 (227)

A Novel Robust Dual Unscented Particle Filter Method for Remaining Useful Life Prediction of Rolling Bearings

IEEE Transactions on Instrumentation and Measurement
It is still challenging to accurately predict the remaining useful life (RUL) of bearings with fluctuating degradation processes. To address this issue, this article proposes a novel robust dual unscented particle filter (DUPF) method for RUL prediction.
Lingli Cui, Wenjie Li, Dongdong Liu, Huaqing Wang   +3 more
semanticscholar   +1 more source

Remaining useful life (RUL) prediction for FDIA on IoT sensor data using CNN and GRU

2021 International Conference on Advances in Technology, Management & Education (ICATME), 2021
Shipra Singh, Kaptan Singh, Amit Saxena
openaire   +1 more source

An Optimal-Subdomain Generalization Method for Remaining Useful Life Prediction of Machinery Under Time-Varying Operation Conditions

IEEE Transactions on Industrial Informatics
Machinery often operates under time-varying conditions, which can lead to distribution discrepancies in degradation samples. However, most existing domain generalization-based methods for predicting remaining useful life (RUL) are applied to constant ...
Xiao-Feng Liu, Yaguo Lei, Naipeng Li, Xiang Li, Bin Yang   +4 more
semanticscholar   +1 more source

Multivariate Phase Space Warping-Based Degradation Tracking and Remaining Useful Life Prediction of Rolling Bearings

IEEE Transactions on Reliability
Effective utilization of signals collected by distributed sensor networks is crucial for tracking degradation and forecasting the remaining useful life (RUL) of rolling bearings.
Hengyu Liu, Rui Yuan, Yong Lv, Xingkai Yang, Hewenxuan Li, E. D. Gedikli   +5 more
semanticscholar   +1 more source

Spatio-temporal Attention-based Hidden Physics-informed Neural Network for Remaining Useful Life Prediction

Advanced Engineering Informatics
Predicting the Remaining Useful Life (RUL) is essential in Prognostic Health Management (PHM) for industrial systems. Although deep learning approaches have achieved considerable success in predicting RUL, challenges such as low prediction accuracy and ...
Feilong Jiang, Xiaonan Hou, Min Xia
semanticscholar   +1 more source

Remaining Useful Life Prediction of Lithium-Ion Batteries With Limited Degradation History Using Random Forest

IEEE Transactions on Transportation Electrification
Predicting the remaining useful life (RUL) of a lithium-ion battery with its limited degradation history is critical as it ensures timely maintenance of electric vehicles (EVs) and efficient reuse of second-life batteries.
Niankai Yang, H. Hofmann, Jing Sun, Ziyou Song   +3 more
semanticscholar   +1 more source

Early Uncertainty Quantification Prediction of Lithium-Ion Battery Remaining Useful Life With Transformer Ensemble Model

IEEE Transactions on Transportation Electrification
Early prediction of the remaining useful life (RUL) of lithium-ion batteries remains challenging due to the weak degradation information available in early-stage data.
Jijuan Hu, Lifeng Wu
semanticscholar   +1 more source

Prediction of Remaining Useful Life (RUL) of Bearing Using Exponential Degradation Model

2022
Keval Bhavsar, Vinay Vakharia
openaire   +1 more source

An Adaptive and Dynamical Neural Network for Machine Remaining Useful Life Prediction

IEEE Transactions on Industrial Informatics
Recently, many neural networks have been proposed for machine remaining useful life (RUL) prediction. However, most network architectures of the existing approaches are fixed.
Ruibing Jin, Duo Zhou, Min Wu, Xiaoli Li, Zhenghua Chen   +4 more
semanticscholar   +1 more source

Machine Remaining Useful Life (RUL) Prediction Based on Particle Swarm Optimization (PSO)

2021
Mohd Najmi Tahir, Abd Kadir Mahamad, Sharifah Saon, Saravanaraj Sathasivam, Hussein Ali Ameen   +4 more
openaire   +1 more source