Remaining Useful Life Prediction of Bearings via Semi-Supervised Transfer Learning Based on an Anti-Self-Healing Health Indicator. [PDF]
Kim JW, Park KS.
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A deep learning approach to optimize remaining useful life prediction for Li-ion batteries. [PDF]
Iftikhar M +6 more
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A Probabilistic Framework for Remaining Useful Life Prediction of Bearings
IEEE Transactions on Instrumentation and Measurement, 2021This article presents a probabilistic framework for remaining useful life (RUL) prediction of bearings. This framework comprises two phases: 1) early fault detection, i.e., modeling the vibration signal as a series of graphs and then conducting graph spectrum analysis to detect the topological change of graph for early fault detection and 2) RUL ...
Teng Wang 0002 +2 more
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Remaining useful life Prediction of air spring
2019 IEEE International Conference on Prognostics and Health Management (ICPHM), 2019The remaining useful life estimation is an important function of an efficient prognostics and health management (PHM) system and can be used preventively to replace the component with the aim of avoiding a breakdown. The prediction of remaining life time of the air spring as one of the critical component of truck is the main goal of this research.
Farzaneh Ahmadzadeh +2 more
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Problems of Predicting the Remaining Useful Life
2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), 2020As the title implies the article, describes some difficulties that appear during the usage process of any technical equipment. It is spoken in detail about the remaining useful life. Different common ways to estimate are described in short. The author attempt made to analyze the Turbofan Engine Degradation Simulation data set.
Alena A. Rozhkovskaya, Igor O. Sychev
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Probabilistic Analysis for Remaining Useful Life Prediction and Reliability Assessment
IEEE Transactions on Reliability, 2022Although the importance of remaining useful life (RUL) prediction is widely recognized in industries, its implementation in real scenarios is highly restricted by the complexity of the degradation mechanism, uncertainty of machinery, and insufficiency of prior knowledge.
Teng Wang 0002 +4 more
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High Performance Remaining Useful Life Prediction for Gearbox
2018 IEEE International Conference on Prognostics and Health Management (ICPHM), 2018Gearbox failure prediction is important for many applications. We present four approaches for predicting the remaining useful life of gearboxes. The first one is rule-based and the second one is a combination of damage curve approach and rule-based approach.
Bulent Ayhan +2 more
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Bidirectional handshaking LSTM for remaining useful life prediction
Neurocomputing, 2019Abstract Unpredictable failures and unscheduled maintenance of physical systems increases production resources, produces more harmful waste for the environment, and increases system life cycle costs. Efficient remaining useful life (RUL) estimation can alleviate such an issue.
Ahmed Elsheikh +2 more
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Adaptive Remaining Useful Life Prediction Algorithm for Bearings
2018 IEEE International Conference on Prognostics and Health Management (ICPHM), 2018It is well known that the lifetime of bearings varies a lot even if the bearings are manufactured in the same assembly line. This is because the exposed operating conditions may be very different for each bearing. As a result, an adaptive remaining lifetime prediction algorithm is a more natural choice and is expected to be more accurate than the non ...
Bulent Ayhan +2 more
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Methodologies for system-level remaining useful life prediction
Reliability Engineering & System Safety, 2016Abstract While most prognostics approaches focus on accurate computation of the degradation rate and the remaining useful life (RUL) of individual components, it is the rate at which the performance of subsystems and systems degrade that is of greater interest to the operators and maintenance personnel of these systems.
Hamed Khorasgani +2 more
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