Results 11 to 20 of about 10,541,846 (196)
Remaining Useful Life Prediction for Lithium-Ion Battery: A Deep Learning Approach
IEEE Access, 2018 Accurate prediction of remaining useful life (RUL) of lithium-ion battery plays an increasingly crucial role in the intelligent battery health management systems. The advances in deep learning introduce new data-driven approaches to this problem.
Lei Ren +5 more
doaj +2 more sources
Prognostics for electronics components of avionics - NASA IGBT accelerated ageing case study [PDF]
, 2013 Insulate gate bipolar transistors (IGBTs) are widely used in electric vehicles, railway locomotive and new generation aircrafts, due to the IGBTs have advantages in small conduction resistance and small drive current.
Xie, Yuan'an
core +7 more sources
Prediction of Remaining Useful Life (RUL) of Lithium ion (Li-ion) Batteries [PDF]
, 2020 In recent time Li-ion battery gained popularity because of their high charge density, portability and longer life span. It compliments the human quest for green energy. As many of the green energy applications like Electrical Vehicle, Wind Energy and Solar Energy use Li-ion battery as their energy storage device.
Shukla, Rashmikant T.
core +5 more sources
Remaining Useful Life Prediction of Fracturing Truck Valve Bodies Based on the CB2-RUL Algorithm
ComputationThe triplex reciprocating drilling pump is a critical piece of equipment in drilling platforms, and the operational condition of its core component—the valve body—directly affects the pump’s performance and the stability of the entire system. Therefore, accurate prediction of the valve body’s Remaining Useful Life (RUL) is of great significance for ...
Xinyue Chen +5 more
openaire +3 more sources
Sensors, 2022 Tool condition monitoring can be employed to ensure safe and full utilization of the cutting tool. Hence, remaining useful life (RUL) prediction of a cutting tool is an important issue for an effective high-speed milling process-monitoring system ...
Weichao Liu, Wen-An Yang, Youpeng You
doaj +1 more source
Demonstration of a Response Time Based Remaining Useful Life (RUL) Prediction for Software Systems
CoRR, 2023 Prognostic and Health Management (PHM) has been widely applied to hardware systems in the electronics and non-electronics domains but has not been explored for software. While software does not decay over time, it can degrade over release cycles. Software health management is confined to diagnostic assessments that identify problems, whereas prognostic
Ray Islam, Peter Sandborn
openaire +3 more sources
Heliyon, 2022 RUL (remaining useful life) shapelets were recently developed to overcome the shortcomings of similarity-based RUL prediction methods, such as high sensitivity to parameters.
Gilseung Ahn +3 more
doaj +1 more source
Sensors, 2022 Prediction of remaining useful life (RUL) is greatly significant for improving the safety and reliability of manufacturing equipment. However, in real industry, it is difficult for RUL prediction models trained on a small sample of faults to obtain ...
Lixiong Wang +5 more
doaj +1 more source
IEEE Access, 2020 To achieve efficient and accurate remaining life prediction and effectively express the uncertainty of prediction results, this paper proposes a remaining life prediction method based on fuzzy evaluation-Gaussian process regression (FE-GPR).
Weijie Kang +5 more
doaj +1 more source
jiaxiang-cheng/cnn-pytorch-remaining-useful-life-prediction: RUL Prediction with CNN
, 2021 Inspired by Babu, G. S., Zhao, P., & Li, X. L. (2016, April). Deep convolutional neural network-based regression approach for estimation of remaining useful life. In International conference on database systems for advanced applications (pp.
Jia-Xiang Cheng
core +1 more source