Results 11 to 20 of about 9,602,001 (284)
Shapelet-based remaining useful life estimation [PDF]
In the Prognostics and Health Management domain, estimating the remaining useful life (RUL) of critical machinery is a challenging task. Various research topics as data acquisition and processing, fusion, diagnostics, prognostivs and decision are involved in this domain.
Simon Malinowski +2 more
openaire +3 more sources
A DLSTM-Network-Based Approach for Mechanical Remaining Useful Life Prediction
Remaining useful life prediction is one of the essential processes for machine system prognostics and health management. Although there are many new approaches based on deep learning for remaining useful life prediction emerging in recent years, these ...
Yan Liu +5 more
doaj +2 more sources
Prediction of Tool Remaining Useful Life Based on NHPP-WPHM
A tool remaining useful life prediction method based on a non-homogeneous Poisson process and Weibull proportional hazard model (WPHM) is proposed, taking into account the grinding repair of machine tools during operation.
Yingzhi Zhang +4 more
doaj +2 more sources
A Hybrid Prognostic Methodology and its Application to Well-Controlled Engineering Systems [PDF]
This thesis presents a novel hybrid prognostic methodology, integrating physics-based and data-driven prognostic models, to enhance the prognostic accuracy, robustness, and applicability.
Eker, Ă–mer Faruk
core +7 more sources
Prognostics for electronics components of avionics - NASA IGBT accelerated ageing case study [PDF]
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
Interaction models for remaining useful life estimation
submitted to Journal of Industrial Information ...
Dmitry Zhevnenko +2 more
openaire +3 more sources
Remaining Useful Life Prediction Using Temporal Convolution with Attention
Prognostic techniques attempt to predict the Remaining Useful Life (RUL) of a subsystem or a component. Such techniques often use sensor data which are periodically measured and recorded into a time series data set.
Wei Ming Tan, T. Hui Teo
doaj +1 more source
Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo, Y., Wu, Q., Li, X., & Huang, B. (2021).
Jia-Xiang Cheng
core +1 more source
Data-driven remaining useful life prediction based on domain adaptation [PDF]
As an important part of prognostics and health management, remaining useful life (RUL) prediction can provide users and managers with system life information and improve the reliability of maintenance systems.
Bin cheng Wen +5 more
doaj +2 more sources
jiaxiang-cheng/cnn-pytorch-remaining-useful-life-prediction: RUL Prediction with CNN
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

