Cross-Domain Remaining Useful Life Prediction Based on Adversarial Training
Machines, 2022 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
Mathematics, 2023 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
Probabilistic Monte-Carlo method for modelling and prediction of electronics component life [PDF]
, 2014 Power electronics are widely used in electric vehicles, railway locomotive and new generation aircrafts. Reliability of these components directly affect the reliability and performance of these vehicular platforms.
Alghassi, Ali +3 more
core +1 more source
Remaining useful life prediction for equipment based on RF-BiLSTM
AIP Advances, 2022 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
A Data-Driven-Based Framework for Battery Remaining Useful Life Prediction
IEEE Access, 2023 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
Remaining useful life estimation in heterogeneous fleets working under variable operating conditions [PDF]
, 2016 The availability of condition monitoring data for large fleets of similar equipment motivates the development of data-driven prognostic approaches that capitalize on the information contained in such data to estimate equipment Remaining Useful Life (RUL).
Al-Dahidi, Sameer +3 more
core +4 more sources
A Novel Deep Learning Approach for Machinery Prognostics Based on Time Windows
Applied Sciences, 2019 Remaining useful life (RUL) prediction is a challenging research task in prognostics and receives extensive attention from academia to industry. This paper proposes a novel deep convolutional neural network (CNN) for RUL prediction.
Hanbo Yang +4 more
doaj +1 more source
A DLSTM-Network-Based Approach for Mechanical Remaining Useful Life Prediction
Sensors, 2022 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
A remaining useful life prediction method based on PSR-former
Scientific Reports, 2022 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
Remaining Useful Life Prediction Based on Multi-Representation Domain Adaptation
Mathematics, 2022 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