Results 31 to 40 of about 1,541,566 (221)

A Lightweight Transformer Edge Intelligence Model for RUL Prediction Classification. [PDF]

Sensors (Basel)
Remaining Useful Life (RUL) prediction is a crucial task in predictive maintenance. Currently, gated recurrent networks, hybrid models, and attention-enhanced models used for predictive maintenance face the challenge of balancing prediction accuracy and ...
Wang L, Li Y, Liu H, Liu T.
europepmc   +2 more sources

Remaining useful life prediction of lithium-ion batteries based on Monte Carlo Dropout and gated recurrent unit

Energy Reports, 2021
Lithium-ion batteries have been widely used for energy storage systems and vehicle industries, highly accurate remaining useful life (RUL) prediction of lithium-ion batteries is one of the key technologies on prognostics and health management.
Meng Wei, Hairong Gu, Min Ye, Qiao Wang, Xinxin Xu, Chenguang Wu   +5 more
doaj   +1 more source

Degradation Prediction Model Based on a Neural Network with Dynamic Windows

Sensors, 2015
Tracking degradation of mechanical components is very critical for effective maintenance decision making. Remaining useful life (RUL) estimation is a widely used form of degradation prediction.
Xinghui Zhang, Lei Xiao, Jianshe Kang
doaj   +1 more source

A Remaining Useful Life Prognosis of Turbofan Engine Using Temporal and Spatial Feature Fusion

Sensors, 2021
The prognosis of the remaining useful life (RUL) of turbofan engine provides an important basis for predictive maintenance and remanufacturing, and plays a major role in reducing failure rate and maintenance costs. The main problem of traditional methods
Cheng Peng, Yufeng Chen, Qing Chen, Zhaohui Tang, Lingling Li, Weihua Gui   +5 more
doaj   +1 more source

The Remaining Useful Life Prediction by Using Electrochemical Model in the Particle Filter Framework for Lithium-Ion Batteries

IEEE Access, 2020
The remaining useful life (RUL) prediction is critical for the safe and reliable operation of lithium-ion battery (LIB) systems, which characterizes the aging status of the battery and provides early warning for battery replacement.
Qianqian Liu, Jingyuan Zhang, Ke Li, Chao Lv   +3 more
doaj   +1 more source

A Novel Combination Neural Network Based on ConvLSTM-Transformer for Bearing Remaining Useful Life Prediction

Machines, 2022
A sensible maintenance strategy must take into account the remaining usable life (RUL) estimation to maximize equipment utilization and avoid costly unexpected breakdowns.
Feiyue Deng, Zhe Chen, Yongqiang Liu, Shaopu Yang, Rujiang Hao, Litong Lyu   +5 more
doaj   +1 more source

Controlling the accuracy and uncertainty trade-off in RUL prediction with a surrogate Wiener propagation model

, 2020
In modern industrial systems, sensor data reflecting the system health state are commonly used for the remaining useful lifetime (RUL) prediction, which are increasingly processed by modern deep learning based approaches recently. But these deep learning
Pechenizkiy, Mykola; id_orcid, Bucchianico, Alessandro Di, Pechenizkiy, Mykola, Deng, Yingjun, Bucchianico, Alessandro Di; id_orcid   +4 more
core   +1 more source

Remaining Useful Life Prediction of High-Frequency Swing Self-Lubricating Liner

Shock and Vibration, 2021
The remaining useful life (RUL) prediction of self-lubricating spherical plain bearings is essential for replacement decision-making and the reliability of high-end equipment. The high-frequency swing self-lubricating liner (HSLL) is the key component of
Xiuhong Hao, Shuqiang Wang, Mengfan Chen, Deng Pan   +3 more
doaj   +1 more source

Remaining useful life prediction for lithium-ion battery by combining an improved particle filter with sliding-window gray model

Energy Reports, 2020
Dependable and accurate battery remaining useful life (RUL) prediction is essential for ensuring the safety and reliability of battery systems. To improve the dynamic traceability of the battery degradation process for RUL prediction under different ...
Lin Chen, Jingjing An, Huimin Wang, Mo Zhang, Haihong Pan   +4 more
doaj   +1 more source

Prediction of the Remaining Useful Life of Lithium-Ion Batteries Based on Dempster-Shafer Theory and the Support Vector Regression-Particle Filter

IEEE Access, 2021
Lithium-ion batteries (LIBs) have been widely used in various electronic equipment. The development of an effective method for predicting the remaining useful life (RUL) of LIBs can ensure the normal operation of equipment by providing an appropriate ...
Hancheng Dong
doaj   +1 more source