A Semi-Supervised Approach with Monotonic Constraints for Improved Remaining Useful Life Estimation [PDF]
Sensors, 2022 Remaining useful life is of great value in the industry and is a key component of Prognostics and Health Management (PHM) in the context of the Predictive Maintenance (PdM) strategy.
Diego Nieves Avendano +6 more
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Remaining Useful Life Estimation In the Presence of Given Shocks [PDF]
International Journal of Industrial Engineering and Production Research, 2022 In a system, prediction of remaining useful lifetime (RUL) of servicing before reaching to a specified breakdown threshold is a very important practical issue, and research in this field is still regarded as an appreciated research gap.
Mehrnaz Piroozbakht +3 more
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Deep learning-based anomaly-onset aware remaining useful life estimation of bearings [PDF]
PeerJ Computer Science, 2021 Remaining Useful Life (RUL) estimation of rotating machinery based on their degradation data is vital for machine supervisors. Deep learning models are effective and popular methods for forecasting when rotating machinery such as bearings may malfunction
Pooja Vinayak Kamat +2 more
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Deep Learning-Based Remaining Useful Life Estimation of Bearings with Time-Frequency Information [PDF]
Sensors, 2022 In modern industrial production, the prediction ability of remaining useful life of bearings directly affects the safety and stability of the system. Traditional methods require rigorous physical modeling and perform poorly for complex systems.
Bingguo Liu +4 more
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Cross-condition and cross-platform remaining useful life estimation via adversarial-based domain adaptation [PDF]
Scientific Reports, 2022 Supervised machine learning is a traditionally remaining useful life (RUL) estimation tool, which requires a lot of prior knowledge. For the situation lacking labeled data, supervised methods are invalid for the issue of domain shift in data distribution.
Dongdong Zhao, Feng Liu
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Remaining Useful Life Estimation in Prognostics Using Deep Reinforcement Learning
IEEE Access, 2023 In modern industrial systems, condition-based maintenance (CBM) has been wildly adopted as an efficient maintenance strategy. Prognostics, as a key enabler of CBM, involves the kernel task of estimating the remaining useful life (RUL) for engineered ...
Qiankun Hu +4 more
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On-Line Remaining Useful Life Estimation of Power Connectors Focused on Predictive Maintenance [PDF]
Sensors, 2021 Connections are critical elements in power systems, exhibiting higher failure probability. Power connectors are considered secondary simple devices in power systems despite their key role, since a failure in one such element can lead to major issues ...
Jordi-Roger Riba +3 more
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Remaining Useful Life Estimation for Engineered Systems Operating under Uncertainty with Causal GraphNets [PDF]
Sensors, 2021 In this work, a novel approach, termed GNN-tCNN, is presented for the construction and training of Remaining Useful Life (RUL) models. The method exploits Graph Neural Networks (GNNs) and deals with the problem of efficiently learning from time series ...
Charilaos Mylonas, Eleni Chatzi
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A One-Stage Ensemble Framework Based on Convolutional Autoencoder for Remaining Useful Life Estimation [PDF]
Sensors, 2022 As the legislative pressure to reduce energy consumption is increasing, data analysis of power consumption is critical in the production planning of manufacturing facilities.
Yong-Keun Park +2 more
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Robust HMM-Based Remaining Useful Life Estimation Using a Ridge-Regularized EM Algorithm [PDF]
SensorsEstimating the remaining useful life (RUL) of engineering systems is crucial for maintenance planning and the reliability of complex mechanical units. Accurate RUL predictions support timely interventions and help to prevent unexpected failures.
Halime Beyza Küçükdağ +2 more
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