[HTML][HTML] Remaining Useful Life prediction and challenges: A literature review on the use of Machine Learning Methods
C Ferreira, G Gonçalves - Journal of Manufacturing Systems, 2022 - Elsevier
Abstract Approaches such as Cyber-Physical Systems (CPS), Internet of Things (IoT),
Internet of Services (IoS), and Data Analytics have built a new paradigm called Industry 4.0 …
Internet of Services (IoS), and Data Analytics have built a new paradigm called Industry 4.0 …
Recent advances and trends of predictive maintenance from data-driven machine prognostics perspective
In the Engineering discipline, prognostics play an essential role in improving system safety,
reliability and enabling predictive maintenance decision-making. Due to the adoption of …
reliability and enabling predictive maintenance decision-making. Due to the adoption of …
A prognostic driven predictive maintenance framework based on Bayesian deep learning
Recent years have witnessed prominent advances in predictive maintenance (PdM) for
complex industrial systems. However, the existing PdM literature predominately separates …
complex industrial systems. However, the existing PdM literature predominately separates …
Aircraft engine remaining useful life estimation via a double attention-based data-driven architecture
L Liu, X Song, Z Zhou - Reliability Engineering & System Safety, 2022 - Elsevier
Remaining useful life (RUL) estimation has been intensively studied, given its important role
in prognostics and health management (PHM) of industry. Recently, data-driven structures …
in prognostics and health management (PHM) of industry. Recently, data-driven structures …
Health status assessment and remaining useful life prediction of aero-engine based on BiGRU and MMoE
Prognostics and health management (PHM) is a critical work to ensure the reliable operation
of industrial equipment, in which health status (HS) assessment and remaining useful life …
of industrial equipment, in which health status (HS) assessment and remaining useful life …
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 …
ChatGPT-like large-scale foundation models for prognostics and health management: A survey and roadmaps
PHM technology is vital in industrial production and maintenance, identifying and predicting
potential equipment failures and damages. This enables proactive maintenance measures …
potential equipment failures and damages. This enables proactive maintenance measures …
Remaining useful life prediction of bearings by a new reinforced memory GRU network
The remaining useful life (RUL) prediction of bearings has great significance in the
predictive maintenance of mechanical equipment. Owing to the difficulty of collecting …
predictive maintenance of mechanical equipment. Owing to the difficulty of collecting …
[HTML][HTML] Variational encoding approach for interpretable assessment of remaining useful life estimation
A new method for evaluating aircraft engine monitoring data is proposed. Commonly,
prognostics and health management systems use knowledge of the degradation processes …
prognostics and health management systems use knowledge of the degradation processes …
A gated graph convolutional network with multi-sensor signals for remaining useful life prediction
With the advent of industry 4.0, multi-sensors are utilized to monitor the degradation process
of machinery. When machinery operating, multi-sensor signals have potential relation with …
of machinery. When machinery operating, multi-sensor signals have potential relation with …