Results 11 to 20 of about 85,181 (261)
Remaining Useful Life Prediction Under Imperfect Prior Degradation Information
The remaining useful life (RUL) prediction is the core of equipment maintenance and decision-making. Accurate RUL prediction can make effective maintenance before the failure occurs to reduce the probability of equipment failure.
Wan Changhao +4 more
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A DLSTM-Network-Based Approach for Mechanical Remaining Useful Life Prediction
Remaining useful life prediction is one of the essential processes for machine system prognostics and health management. Although there are many new approaches based on deep learning for remaining useful life prediction emerging in recent years, these ...
Yan Liu +5 more
doaj +1 more source
Remaining useful life prediction for equipment based on RF-BiLSTM
The prediction technology of remaining useful life has received a lot attention to ensure the reliability and stability of complex mechanical equipment. Due to the large-scale, non-linear, and high-dimensional characteristics of monitoring data, machine ...
Zhiqiang Wu +8 more
doaj +1 more source
Cross-Domain Remaining Useful Life Prediction Based on Adversarial Training
Remaining useful life prediction can assess the time to failure of degradation systems. Currently, numerous neural network-based prediction methods have been proposed by researchers.
Yuhang Duan +3 more
doaj +1 more source
Prediction of Tool Remaining Useful Life Based on NHPP-WPHM
A tool remaining useful life prediction method based on a non-homogeneous Poisson process and Weibull proportional hazard model (WPHM) is proposed, taking into account the grinding repair of machine tools during operation.
Yingzhi Zhang +4 more
doaj +1 more source
A Data-Driven-Based Framework for Battery Remaining Useful Life Prediction
Electric vehicles are expected to dominate the vehicle fleet in the near future due to their zero emissions of pollutants, reduced fossil fuel reserves, comfort, and lightness.
Amal Ezzouhri +3 more
doaj +1 more source
A remaining useful life prediction method based on PSR-former
The non-linear and non-stationary vibration data generated by rotating machines can be used to analyze various fault conditions for predicting the remaining useful life(RUL).
Huang Zhang +6 more
doaj +1 more source
Parametric probabilistic models for predicting creep remaining useful life
The creep phenomenon, associated with a time-dependent progressive deformation of a material under stress and high temperatures, is of great industrial interest since these are typical operating conditions in several industries. Thus, a safe forecast of the life in creep is a critical phase in the design of equipment that operates at high temperatures,
Maudonet, Victor +2 more
openaire +3 more sources
Remaining Useful Life Prediction Based on Multi-Representation Domain Adaptation
All current deep learning-based prediction methods for remaining useful life (RUL) assume that training and testing data have similar distributions, but the existence of various operating conditions, failure modes, and noise lead to insufficient data ...
Yi Lyu +3 more
doaj +1 more source
Aero-Engine Remaining Useful Life Prediction Based on Bi-Discrepancy Network
Most unsupervised domain adaptation (UDA) methods align feature distributions across different domains through adversarial learning. However, many of them require introducing an auxiliary domain alignment model, which incurs additional computational ...
Nachuan Liu +3 more
doaj +1 more source

