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Robustness testing framework for RUL prediction Deep LSTM networks
ISA Transactions, 2021Efficiency and robustness in remaining useful life (RUL) prediction are crucial in system health monitoring. Thus, the internal logic computation of a Deep LSTM model for RUL prediction is mainly shaped and evaluated over a training data-set and its performance examined on a testing data-set.
Mohamed Sayah +2 more
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A Semisupervised Deep Hybrid Multitask Model for RUL Prediction
IEEE Transactions on Instrumentation and Measurement, 2023Deep 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 ...
Yan-Hui Lin +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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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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CRULP: Reliable RUL Estimation Inspired by Conformal Prediction
IEEE Transactions on Instrumentation and MeasurementRuyi Huang, Fugee Tsung
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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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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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