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Compact Convolutional Transformer for Bearing Remaining Useful Life Prediction
An accurate prediction of bearing remaining useful life (RUL) has become increasingly important for equipment maintenance with the development of...
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LSTM-based deep learning approach for remaining useful life prediction of rolling bearing using proposed C-MMPE feature
Prognostic health management (PHM) is essential for the predictive maintenance of industrial systems, aiming to predict the remaining useful life...
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Tool remaining useful life prediction and parameters optimization in milling 508III steel
Tool remaining useful life prediction (RUL) and parameters optimization are very important for the normal operation of the machining system, the full...
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Remaining Useful Life Prediction of the Li-Ion Batteries
Many different prediction methods have been developed in recent years and data-driven methods are often used. The aim of this paper is to present the...
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Wind Turbine Remaining Useful Life Prediction Using Small Dataset and Machine Learning Techniques
Recently, there has been a global shift toward clean energy sources, and wind turbines (WT) play a crucial role as one of the most popular renewable...
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Vibration-based anomaly pattern mining for remaining useful life (RUL) prediction in bearings
Predicting the remaining useful life (RUL) of bearings is critical in ensuring rotating machinery’s reliability and maintenance efficiency. Most of...
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Remaining useful life prediction of circuit breaker operating mechanisms based on wavelet-enhanced dual-tree residual networks
The remaining useful life prediction of circuit breaker operating mechanisms is crucial for the condition-based maintenance of national power grids....
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Remaining Useful Life Prediction Method for Multi-Component System Considering Maintenance: Subsea Christmas Tree System as A Case Study
Maintenance is an important technical measure to maintain and restore the performance status of equipment and ensure the safety of the production...
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A new approach for remaining useful life prediction of bearings using 1D-ternary patterns with LSTM
Bearings frequently experience malfunctions in mechanical systems, directly impacting system performance. Accurate prediction of bearing failures is...
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Prediction of remaining useful life of metro traction motor bearings based on DCCNN-GRU and multi-information fusion
A single type of sensor is susceptible to interference and limited degradation information can be extracted. Therefore, a multi-information...
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Advanced ML for predictive maintenance: a case study on remaining useful life prediction and reliability enhancement
In order to achieve an optimal system performance, decision makers are continually faced with the responsibility of making choices that will enhance...
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Enhanced wear prediction of tunnel boring machine disc cutters for accurate remaining useful life estimation using a hybrid model
In tunnel construction with tunnel boring machines (TBMs), accurate prediction of the remaining useful life (RUL) of disc cutters is critical for...
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Prediction of the remaining useful life of rolling bearings by LSTM based on multidomain characteristics and a dual-attention mechanism
This study proposes a framework for bearing remaining useful life (RUL) prediction that uses multidomain features and a dual-attention mechanism...
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Tool remaining useful life prediction using bidirectional recurrent neural networks (BRNN)
Nowadays, new challenges around increasing production quality and productivity, and decreasing energy consumption, are growing in the manufacturing...
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The Prediction of Remaining Useful Life of Aluminum Reduction Cells Based on Improved Hidden Semi-Markov Model
An improved prediction algorithm of the hidden semi-markov model (HSMM) is proposed to predict the remaining useful life (RUL) of aluminum reduction...
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Remaining Useful Life Prediction of Super-Capacitors in Electric Vehicles Using Neural Networks
Batteries for electric vehicles (EVs) have a capacity decay issue as they age. As a result, the use of lithium-ion is becoming more popular with...
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An online unscented Kalman filter remaining useful life prediction method applied to second-life lithium-ion batteries
In electric vehicles (EVs), because of the high current demand, lithium-ion batteries (LiBs) degradation makes the EVs suffer from limitations in...
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Prediction of Remaining useful life of Rolling Bearing using Hybrid DCNN-BiGRU Model
BackgroundRolling bearings are an essential equipment component, and evaluating its remaining useful life (RUL) is vital in guaranteeing safety and...
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Remaining Useful Life Prediction of High-Speed Railroad Contact Network Based on Stacking Integrated Attention-LSTM-CNN Deep Learning
Accurate prediction of the remaining useful life (RUL) of high-speed railroad contact networks can guide the scientific development of maintenance...
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Remaining Useful Life Prediction Based on Bayesian Inference Long and Short-Term Memory Networks
Remaining useful life prediction using deep learning methods has been widely studied, however most deep learning methods ignore the widespread...