A variational local weighted deep sub-domain adaptation network for remaining useful life prediction facing cross-domain condition
Most supervised learning-based approaches follow the assumptions that offline data and
online data must obey a similar distribution, which is difficult to satisfy in realistic remaining …
online data must obey a similar distribution, which is difficult to satisfy in realistic remaining …
A parallel hybrid neural network with integration of spatial and temporal features for remaining useful life prediction in prognostics
Prediction of remaining useful life (RUL) is an indispensable part of prognostics health
management (PHM) in complex systems. Considering the parallel integration of the spatial …
management (PHM) in complex systems. Considering the parallel integration of the spatial …
An overview of the state of the art in aircraft prognostic and health management strategies
M Kordestani, ME Orchard… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Aircraft are complex engineering systems composed of many interconnected subsystems
with possible uncertainties in their structure. They often function for a long number of flight …
with possible uncertainties in their structure. They often function for a long number of flight …
Bayesian deep-learning for RUL prediction: An active learning perspective
Deep learning (DL) has been intensively exploited for remaining useful life (RUL) prediction
in the recent decade. Although with high precision and flexibility, DL methods need sufficient …
in the recent decade. Although with high precision and flexibility, DL methods need sufficient …
Explainable predictive maintenance: a survey of current methods, challenges and opportunities
Predictive maintenance is a well studied collection of techniques that aims to prolong the life
of a mechanical system by using artificial intelligence and machine learning to predict the …
of a mechanical system by using artificial intelligence and machine learning to predict the …
Transformer-based hierarchical latent space VAE for interpretable remaining useful life prediction
Data-driven prediction of remaining useful life (RUL) has emerged as one of the most sought-
after research in prognostics and health management (PHM). Nevertheless, most RUL …
after research in prognostics and health management (PHM). Nevertheless, most RUL …
Bayesian gated-transformer model for risk-aware prediction of aero-engine remaining useful life
Abstract Remaining Useful Life (RUL) prediction plays a critical role in the prognostics and
health management (PHM) for aero-engines. A variety of Deep Learning (DL) approaches …
health management (PHM) for aero-engines. A variety of Deep Learning (DL) approaches …
Multitask learning of health state assessment and remaining useful life prediction for sensor-equipped machines
J Yan, Z He, S He - Reliability Engineering & System Safety, 2023 - Elsevier
Prognostics and health management (PHM) uses data collected through sensors to monitor
the states of sensor-equipped machines and provide maintenance decisions. PHM includes …
the states of sensor-equipped machines and provide maintenance decisions. PHM includes …
Automatic multi-differential deep learning and its application to machine remaining useful life prediction
Different levels of characteristic information cannot be mined using various feature extraction
modes in most neural networks, and thus, a novel method called the automatic multi …
modes in most neural networks, and thus, a novel method called the automatic multi …
Research of artificial intelligence operations for wind turbines considering anomaly detection, root cause analysis, and incremental training
C Zhang, D Hu, T Yang - Reliability Engineering & System Safety, 2024 - Elsevier
Artificial intelligence operations (AIOps) is emerging as a novel technology in industrial
automation to improve operation and maintenance (O&M) efficiency through machine …
automation to improve operation and maintenance (O&M) efficiency through machine …