Works matching DE "REMAINING useful life"
Results: 688
A novel transfer learning approach based on deep degradation feature adaptive alignment for remaining useful life prediction with multi-condition data.
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- Journal of Intelligent Manufacturing, 2025, v. 36, n. 1, p. 619, doi. 10.1007/s10845-023-02264-4
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Remaining useful lifetime prediction for milling blades using a fused data prediction model (FDPM).
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- Journal of Intelligent Manufacturing, 2024, v. 35, n. 8, p. 4035, doi. 10.1007/s10845-024-02398-z
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Label synchronization for Hybrid Federated Learning in manufacturing and predictive maintenance.
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- Journal of Intelligent Manufacturing, 2024, v. 35, n. 8, p. 4015, doi. 10.1007/s10845-023-02298-8
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Towards prognostic generalization: a domain conditional invariance and specificity disentanglement network for remaining useful life prediction.
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- Journal of Intelligent Manufacturing, 2024, v. 35, n. 7, p. 3459, doi. 10.1007/s10845-023-02215-z
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Development of a cyber physical production system framework for smart tool health management.
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- Journal of Intelligent Manufacturing, 2024, v. 35, n. 7, p. 3037, doi. 10.1007/s10845-023-02192-3
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A pre-trained model selection for transfer learning of remaining useful life prediction of grinding wheel.
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- Journal of Intelligent Manufacturing, 2024, v. 35, n. 5, p. 2295, doi. 10.1007/s10845-023-02154-9
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Prognostics and health management for induction machines: a comprehensive review.
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- Journal of Intelligent Manufacturing, 2024, v. 35, n. 3, p. 937, doi. 10.1007/s10845-023-02103-6
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Experience from implementing digital twins for maintenance in industrial processes.
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- Journal of Intelligent Manufacturing, 2024, v. 35, n. 2, p. 875, doi. 10.1007/s10845-023-02078-4
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Predicting maintenance through an attention long short-term memory projected model.
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- Journal of Intelligent Manufacturing, 2024, v. 35, n. 2, p. 807, doi. 10.1007/s10845-023-02077-5
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Dynamic spatial–temporal graph-driven machine remaining useful life prediction method using graph data augmentation.
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- Journal of Intelligent Manufacturing, 2024, v. 35, n. 1, p. 355, doi. 10.1007/s10845-022-02052-6
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A novel feature-fusion-based end-to-end approach for remaining useful life prediction.
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- Journal of Intelligent Manufacturing, 2023, v. 34, n. 8, p. 3495, doi. 10.1007/s10845-022-02015-x
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Few-shot RUL estimation based on model-agnostic meta-learning.
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- Journal of Intelligent Manufacturing, 2023, v. 34, n. 5, p. 2359, doi. 10.1007/s10845-022-01929-w
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A dynamic mode decomposition based deep learning technique for prognostics.
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- Journal of Intelligent Manufacturing, 2023, v. 34, n. 5, p. 2207, doi. 10.1007/s10845-022-01916-1
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基于特征融合与HPO-RVM的滚动轴承剩余寿命预测.
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- Machine Tool & Hydraulics, 2023, v. 51, n. 17, p. 209, doi. 10.3969/j.issn.1001-3881.2023.17.034
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基于时域和谱峭度特征融合及指数模型的滚动轴承 RUL 预测.
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- Machine Tool & Hydraulics, 2023, v. 51, n. 10, p. 203, doi. 10.3969/j.issn.1001-3881.2023.10.035
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Zur Novellierung der erbschaft- und schenkungsteuerlichen Grundbesitzbewertung durch das JStG 2022.
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- FinanzRundschau, 2023, v. 105, n. 4, p. 153, doi. 10.9785/fr-2023-1050404
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JStG 2022: Geplante Abschaffung der Gebäudeabschreibung nach der kürzeren tatsächlichen Nutzungsdauer ab VZ 2023 – Was wären die Auswirkungen?
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- FinanzRundschau, 2022, v. 104, n. 21, p. 965, doi. 10.9785/fr-2022-1042102
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Design of electrical power telemetering system using microcontroller device via GSM.
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- Journal of Engineering Sciences & Innovation (JESI), 2023, v. 8, n. 4, p. 447
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Dependable Cyber-Physical Systems: concepts, challenges, and case studies.
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- Journal of Engineering Sciences & Innovation (JESI), 2023, v. 8, n. 4, p. 433
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Fault Precognition System for Remaining Useful Life Estimation in Bearing Systems Using Autoencoder-LSTM and Clustering Techniques.
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- Journal Européen des Systèmes Automatisés, 2024, v. 57, n. 6, p. 1721, doi. 10.18280/jesa.570620
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Advancing Predictive Maintenance: Median-Based Particle Filtering in MOSFET Prognostics.
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- Journal Européen des Systèmes Automatisés, 2024, v. 57, n. 4, p. 1103, doi. 10.18280/jesa.570417
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A Novel End-to-End Provenance System for Predictive Maintenance: A Case Study for Industrial Machinery Predictive Maintenance.
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- Computers (2073-431X), 2024, v. 13, n. 12, p. 325, doi. 10.3390/computers13120325
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Predicting the RUL of Li-Ion Batteries in UAVs Using Machine Learning Techniques.
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- Computers (2073-431X), 2024, v. 13, n. 3, p. 64, doi. 10.3390/computers13030064
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A CNN-GRU Approach to the Accurate Prediction of Batteries' Remaining Useful Life from Charging Profiles.
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- Computers (2073-431X), 2023, v. 12, n. 11, p. 219, doi. 10.3390/computers12110219
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Wear volume estimation for a journal bearing dataset.
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- Technisches Messen, 2022, v. 89, n. 7/8, p. 534, doi. 10.1515/teme-2022-0002
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PREDICTION OF REMAINING USEFUL LIFE WITH HELP OF DEEP LEARNING MODELS WITH REGULARIZATION.
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- International Journal on Information Technologies & Security, 2024, v. 16, n. 3, p. 3
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Assessing the Remaining Useful Life of Hydraulic Pumps: A Review.
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- Hidraulica, 2024, n. 3, p. 7
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Experimental and statistical analysis of wear on gear material.
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- Lubrication Science, 2023, v. 35, n. 6, p. 438, doi. 10.1002/ls.1650
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Optimal predictive selective maintenance for fleets of mission-oriented systems.
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- International Journal of Production Research, 2024, v. 62, n. 24, p. 8790, doi. 10.1080/00207543.2024.2349257
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Capability-based remaining useful life prediction of machining tools considering non-geometry and tolerancing features with a hybrid model.
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- International Journal of Production Research, 2023, v. 61, n. 21, p. 7540, doi. 10.1080/00207543.2022.2152126
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Adaptive Framework for Maintenance Scheduling Based on Dynamic Preventive Intervals and Remaining Useful Life Estimation.
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- Future Internet, 2024, v. 16, n. 6, p. 214, doi. 10.3390/fi16060214
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Artificial Intelligence for Corrosion Detection on Marine Structures.
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- Journal of Ocean Technology, 2024, v. 19, n. 2, p. 19
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An integrated method for the leakage fault mode diagnosis and life prediction of the reactor coolant pump.
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- PLoS ONE, 2024, v. 19, n. 6, p. 1, doi. 10.1371/journal.pone.0304652
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A prediction model for complex equipment remaining useful life using gated recurrent unit complex networks.
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- Enterprise Information Systems, 2023, v. 17, n. 5, p. 1, doi. 10.1080/17517575.2021.2008515
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A MODELLING APPROACH FOR ASSET DEGRADATION: ADVANCING DIGITAL TWIN IN MAINTENANCE.
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- International Journal of Simulation Modelling (IJSIMM), 2025, v. 24, n. 1, p. 76, doi. 10.2507/IJSIMM24-1-715
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Make Refineries Safer with Predictive Maintenance Programs.
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- Chemical Engineering, 2024, v. 131, n. 5, p. 51
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- Article
Evaluating eXplainable artificial intelligence tools for hard disk drive predictive maintenance.
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- Artificial Intelligence Review, 2023, v. 56, n. 7, p. 7279, doi. 10.1007/s10462-022-10354-7
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A survey of transfer learning for machinery diagnostics and prognostics.
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- Artificial Intelligence Review, 2023, v. 56, n. 4, p. 2871, doi. 10.1007/s10462-022-10230-4
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Dynamic predictive maintenance strategy for multi‐component system based on LSTM and hierarchical clustering.
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- Quality & Reliability Engineering International, 2025, v. 41, n. 1, p. 30, doi. 10.1002/qre.3656
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Combined improved tuna swarm optimization with graph convolutional neural network for remaining useful life of engine.
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- Quality & Reliability Engineering International, 2025, v. 41, n. 1, p. 174, doi. 10.1002/qre.3651
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A novel equipment remaining useful life prediction approach considering dynamic maintenance threshold.
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- Quality & Reliability Engineering International, 2024, v. 40, n. 7, p. 4088, doi. 10.1002/qre.3623
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Degradation index‐based prediction for remaining useful life using multivariate sensor data.
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- Quality & Reliability Engineering International, 2024, v. 40, n. 7, p. 3709, doi. 10.1002/qre.3615
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Advanced reliability and safety methodologies and novel applications (Selected papers of the international conference of QR2MSE2023).
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- Quality & Reliability Engineering International, 2024, v. 40, n. 7, p. 3643, doi. 10.1002/qre.3611
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Reliability and maintainability estimation of a multi‐failure‐cause system under imperfect maintenance.
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- Quality & Reliability Engineering International, 2024, v. 40, n. 6, p. 3487, doi. 10.1002/qre.3595
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Remaining useful life prediction method for rolling bearings based on hybrid dilated convolution transfer.
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- Quality & Reliability Engineering International, 2024, v. 40, n. 6, p. 3018, doi. 10.1002/qre.3563
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A dual‐channel transferable RUL prediction method integrated with Bayesian deep learning and domain adaptation for rolling bearings.
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- Quality & Reliability Engineering International, 2024, v. 40, n. 5, p. 2348, doi. 10.1002/qre.3539
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Reliability modeling of systems with random failure threshold subjected to cumulative shocks using machine learning method.
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- Quality & Reliability Engineering International, 2024, v. 40, n. 5, p. 2547, doi. 10.1002/qre.3525
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Multifeature‐based online remaining useful life prediction of lithium‐ion batteries in stages using cascaded data‐driven algorithm.
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- Quality & Reliability Engineering International, 2024, v. 40, n. 5, p. 2527, doi. 10.1002/qre.3524
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Fault prognosis for linear stochastic systems with intermittent fault and strong noise via health indicator extraction approach.
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- Quality & Reliability Engineering International, 2024, v. 40, n. 5, p. 2456, doi. 10.1002/qre.3519
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Degradation trajectory prediction of lithium‐ion batteries based on charging‐discharging health features extraction and integrated data‐driven models.
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- Quality & Reliability Engineering International, 2024, v. 40, n. 4, p. 1833, doi. 10.1002/qre.3496
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