Results 31 to 40 of about 1,643,808 (218)
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 +2 more
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A Remaining Useful Life Prognosis of Turbofan Engine Using Temporal and Spatial Feature Fusion
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 +5 more
doaj +1 more source
Segmental Degradation RUL Prediction of IGBT Based on Combinatorial Prediction Algorithms
Aiming at the segmentation nonlinear degradation characteristics of IGBT, the traditional single remaining useful lifetime (RUL) method has low accuracy. This paper proposes a method combining gray prediction and particle filter algorithm. The gray prediction model is used for slow degradation trends prediction in the early stage.
Linghui Meng 0002 +2 more
openaire +2 more sources
Degradation Prediction Model Based on a Neural Network with Dynamic Windows
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
Remaining Useful Life Prediction of High-Frequency Swing Self-Lubricating Liner
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 +3 more
doaj +1 more source
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 +5 more
doaj +1 more source
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 +3 more
doaj +1 more source
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
Research on Remaining Useful Life Prediction of Equipment Based on Digital Twins
Remaining Useful Life (RUL) prediction is a key factor in fault diagnosis, prediction, and health management (PHM) during equipment operation and service.
Jiaju Wu +5 more
doaj +1 more source
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 +4 more
doaj +1 more source

