Results 161 to 170 of about 1,643,808 (218)
A Semisupervised Deep Hybrid Multitask Model for RUL Prediction
IEEE Transactions on Instrumentation and Measurement, 2023 Deep learning (DL) methods can be used to construct health indicators (HIs) for remaining useful life (RUL) prediction. The existing DL methods consider previous and current sensor signals and utilize labeled data, which are limited in practice. To leverage unlabeled data for extracting HIs, semisupervised methods, especially hybrid methods, can be ...
Lin, Yan-Hui +3 more
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RUL prediction based on two‐phase wiener process
Quality and Reliability Engineering International, 2022AbstractThe degradation model and the remaining useful life (RUL) prediction are two key metrics for machine health prognostics. However, the precision of RUL prediction highly depends on the validity of the degradation model. Consequently, the uncertainty of RUL prediction based on the two‐phase degradation process may cause the estimated product ...
Kai Liu 0042 +3 more
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Sequential Information Bottleneck Network for RUL Prediction
2019 IEEE Symposium Series on Computational Intelligence (SSCI), 2019This work studies the problem of predicting remaining useful life in complex systems. We propose a generic algorithm framework, sequential information bottleneck network(SIBN), which leverages the information criterion to preserve the most relevant information in the learning process.
Yuxuan Zhang +4 more
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Prediction of antidepressant response in both 2.25×threshold RUL and fixed high dose RUL ECT
Journal of Affective Disorders, 2009Some forms of electroconvulsive therapy (ECT) can result in generalized seizures that lack efficacy, therefore physiological markers of treatment adequacy would be helpful. EEG measures of seizure quality, such as EEG regularity and post-ictal suppression, have largely supplanted seizure duration as a marker for seizure adequacy, yet no predictive ...
James N, Kimball +3 more
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A data-driven approach to RUL prediction of tools
Advances in Manufacturing, 2023An effective and reliable prediction of the remaining useful life (RUL) of a tool is important to a metal forming process because it can significantly reduce unexpected maintenance, avoid machine shutdowns and increase system stability. This study proposes a new data-driven approach to the RUL prediction for metal forming processes under multiple ...
Wei Li +5 more
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RUL prediction for IMA based on deep regression method
2017 IEEE 10th International Workshop on Computational Intelligence and Applications (IWCIA), 2017Integrated modular avionics (IMA) is one of the most significant systems which can affect the performance of civil aircraft. The structure of IMA is an open standard platform, on which amount of functionalities are hosted. This structure makes avionics more flexible and more powerful, while it makes avionics more complexity and more critical.
Zehai Gao, Cunbao Ma, Yige Luo
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Joint Online RUL Prediction for Multivariate Deteriorating Systems
IEEE Transactions on Industrial Informatics, 2019Stochastic processes and filtering methods are popular tools for degradation modeling and online remaining useful life (RUL) prediction. However, most models are for one-dimensional degradation and various filtering methods can only handle observations from a single system.
Weiwen Peng +2 more
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A novel soft computing method for engine RUL prediction
Multimedia Tools and Applications, 2017Prognostics is an engineering discipline focused on predicting the Remaining Useful Life (RUL) of a system or a component using raw multimedia (sensor) data. This paper presents a novel machine learning model for this task, which includes a smart ensemble of gradient boosted trees (GBT) and feed-forward neural networks.
Sandip Kumar Singh +2 more
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RUL Prediction of Reaction Wheel Motor in Satellites
PHM Society European Conference, 2018For advanced agile attitude control of the satellite, reaction wheels are used actuated by motor. In order to ensure reliable operation, fault detection and prediction of remaining useful life (RUL) of the motor is of great importance. In this study, multi-scale Extended Kalman Filter (EKF) is employed for this purpose using the data of input current ...
Yuri Yun +3 more
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RUL Prediction Based on Sparse Denoising LSTM
2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (SAFEPROCESS), 2021Funa Zhou, Zhiqiang Zhang, Po Hu
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