Predictive maintenance lets you estimate the remaining useful life (RUL) of your machine. RUL prediction gives you insights about when your machine will fail so you can schedule maintenance in advance. You’ll learn about the most common RUL estimator models: similarity, survival...
Remaining Useful Life (RUL) estimation is a fundamental task in the prognostic and health management (PHM) of industrial equipment and systems. To this end, we propose a novel approach for RUL estimation in this paper, based on deep neural architecture due to its great success in sequence ...
RUL estimation based on ISOMAP and SVR The main steps of the proposed contribution are shown in Fig. 2. Feature extraction and reduction and degradation modeling steps will be described in the following of the paper. Description of the experimental platform PRONOSTIA PRONOSTIA is an experimental pla...
Meanwhile, health indicator (HI) construction and remaining useful life (RUL) estimation are two key elements to efficiently perform PHM. In this paper, a health indicator generator (HIG) based on an artificial neural network (ANN) is constructed. The HIG is learned from training data extracted...
RemainingUsefulLifeEstimationin PrognosticsUsingDeepConvolution NeuralNetworks XiangLi a,1 QianDing b Jian-QiaoSun c a CollegeofSciences,NortheasternUniversity,Shenyang110819,China b DepartmentofMechanics,TianjinUniversity,Tianjin300072,China c SchoolofEngineering,UniversityofCalifornia,Merced,CA95343,USA ...
OF剩余ofLIFELife锂离子电池lifeion 系统标签: batterylithiumionremainingpredictionlife Remaining useful life prediction of lithium-ion battery with unscented particle filter technique Qiang Miao a,⇑ , Lei Xie a , Hengjuan Cui a , Wei Liang a , Michael Pecht b a School of Mechanical, Electroni...
[1] X.-S. Si, W. Wang, C.-H. Hu and D.-H. Zhou, “Remaining useful life estimation—A review on the statistical data driven approaches”, Eur. J. Oper. Res., vol. 213, no. 1, pp. 1-14, Aug. 2011. To start the demo, complete the following steps: ...
Remaining useful life estimation is central to the prognostics and health management of systems, particularly for safety-critical systems, and systems that are very expensive. We present a non-linear model to estimate the remaining useful life of a system based on monitored degradation signals. A ...
Remaining useful life (RUL) estimation is an important part of prognostic health management (PHM) technology. Traditional RUL estimation methods need to define thresholds with the help of experience, and the thresholds affect the precision of the test results. In this paper, a hybrid method of co...
A Wiener-process-based degradation model with a recursive filter algorithm for remaining useful life estimation Mech Syst Signal Process (2013) O. Straka et al. Truncation nonlinear filters for state estimation with nonlinear inequality constraints Automatica (2012) E. Zio et al. Particle filtering ...