Results 11 to 20 of about 11,323,207 (336)
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
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Bayesian Approach for Remaining Useful Life Prediction
Chemical Engineering Transactions, 2013 Prediction of the remaining useful life (RUL) of critical components is a non-trivial task for industrial applications. RUL can differ for similar components operating under the same conditions.
A. Mosallam, K. Medjaher, N. Zerhouni
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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
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Digital Twin and Data-Driven Remaining Useful Life Prediction of Gearbox
IEEE AccessTraditional approaches for predicting the remaining useful life (RUL) of gearboxes often face challenges in integrating physical and virtual data, leading to reduced prediction accuracy and an increased risk of system failure.
Quanbo Lu, Mei Li, Xiaojuan Huang
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Remaining Useful Life Prediction Based on Deep Learning: A Survey
SensorsRemaining useful life (RUL) is a metric of health state for essential equipment. It plays a significant role in health management. However, RUL is often random and unknown.
Fuhui Wu +3 more
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Remaining Useful Life Prediction for Rolling Bearings Based on TCN-Transformer Networks Using Vibration Signals. [PDF]
Sensors (Basel)Remaining useful life (RUL) prediction plays a core role in industrial prognostics and health management (PHM), requiring data-driven models with higher predictive capability for accurate long time series prediction.
Jin X +6 more
europepmc +2 more sources
Remaining Useful Life Prediction of Rolling Bearings Based on CBAM-CNN-LSTM
SensorsPredicting the Remaining Useful Life (RUL) is vital for ensuring the reliability and safety of equipment and components. This study introduces a novel method for predicting RUL that utilizes the Convolutional Block Attention Module (CBAM) to address the ...
Bo Sun +4 more
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A failure-efficient prediction of remaining useful life
Machine Learning. EngineeringPredicting the remaining useful life (RUL) is crucial for effective condition-based maintenance, enhancing cost-effectiveness, productivity, and safety by enabling timely maintenance interventions. A fundamental challenge in data-driven RUL prediction is
Sang Bin Moon +3 more
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Predictive maintenance programs for aircraft engines based on remaining useful life prediction. [PDF]
Sci RepAbstract The remaining useful life (RUL) and utilization strategy of an aero-engine are related to the flight safety of an aircraft, which directly affects the flight itself and the safety of the occupants. Aiming at the complexity of aero-engine condition monitoring data, an aero-engine predictive maintenance planning framework based ...
Xue F, Jin G, Tan L, Zhang C, Yu Y.
europepmc +4 more sources
Review of rail remaining useful life prediction
Transportation Safety and EnvironmentRail is one of the most basic components of railway tracks. Accurate prediction of rail remaining useful life is important for ensuring operational safety, optimizing maintenance resource allocation, and reducing operational costs.
Cao Yuan +4 more
semanticscholar +2 more sources