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Predicting the Remaining Lifetime of Distribution Transformers using Machine Learning [PDF]
American Journal of Engineering and Applied Sciences, 2020 Distribution Transformer is a crucial element in deciding the power flow in large power systems. Their better performance implies high power system efficiency and enhanced power transfer capability. However, various Distribution Transformer failures in the recent past lead to power supply disturbance and have acquired much attention from the electrical
Ntiminity Abontakoyah Enoch +2 more
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Meteorologische Zeitschrift, 2023 Due to technical progress in sensor technology and computer power, observation and model data are operationally available today with a high spatial and temporal resolution, suitable for thunderstorm detection and prediction.
Isabella Zöbisch +2 more
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Energy and AI, 2023 The health management of batteries is a key enabler for the adoption of Electric Vertical Take-off and Landing vehicles (eVTOLs). Currently, few studies consider the health management of eVTOL batteries.
Mihaela Mitici +3 more
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Remaining Useful Lifetime (RUL): Probabilistic Predictive Model
International Journal of Prognostics and Health Management, 2021 Reliability evaluations and assurances cannot be delayed until the device (system) is fabricated and put into operation. Reliability of an electronic product should be conceived at the early stages of its design; implemented during manufacturing; evaluated (considering customer requirements and the existing specifications), by electrical, optical ...
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IEEE Access, 2022 According to the United States environmental protection agency (EPA), every burned gallon of gasoline generates 8.87 Kg of CO2. The pollution created by vehicles’ fuel consumption has been one of the primary sources of environmental contamination ...
Mohamed Elmahallawy +3 more
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IEEE Open Journal of Instrumentation and Measurement, 2022 With the rapid development of information and sensor technology, the data-driven remaining useful lifetime (RUL) prediction methods have been acquired a successful development. Nowadays, the data-driven RUL methods are focused on estimating the RUL value.
Ming Zhang +3 more
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IEEE Access, 2020 Focusing on the fact that the existing research on optimal maintenance decision for remaining useful lifetime (RUL) prediction and imperfect maintenance has low accuracy of RUL prediction and rationality of decision results, an optimal maintenance ...
Yunxiang Chen, Zezhou Wang, Zhongyi Cai
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Comparing Single and Hybrid methods of Deep Learning for Remaining Useful Life Prediction of Lithium-ion Batteries [PDF]
E3S Web of Conferences, 2021 The prediction lifetime of a Lithium-ion battery is able to be utilized as an early warning system to prevent the battery’s failure that makes it very significant for assuring safety and reliability.
Zraibi Brahim +2 more
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Metals, 2020 Due to the uncertainties originating from the underlying physical model, material properties and the measurement data in fatigue crack growth (FCG) processing, the prediction of fatigue crack growth lifetime is still challenging.
Hesheng Tang, Xueyuan Guo, Songtao Xue
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Machines, 2023 An aircraft engine is expected to have a high-reliability system as a safety-critical asset. A scheduled maintenance strategy based on statistical calculation has been employed as the current practice to achieve the reliability requirement.
Faisal Maulana +2 more
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