Estimation of system reliability using a semiparametric model

Published

Conference Paper

An important problem in reliability engineering is to predict the failure rate, that is, the frequency with which an engineered system or component fails. This paper presents a new method of estimating failure rate using a semiparametric model with Gaussian process smoothing. The method is able to provide accurate estimation based on historical data and it does not make strong a priori assumptions of failure rate pattern (e.g., constant or monotonic). Our experiments of applying this method in power system failure data compared with other models show its efficacy and accuracy. This method can be used in estimating reliability for many other systems, such as software systems or components. © 2011 IEEE.

Full Text

Duke Authors

Cited Authors

  • Wu, L; Teravainen, T; Kaiser, G; Anderson, R; Boulanger, A; Rudin, C

Published Date

  • August 17, 2011

Published In

  • Ieee 2011 Energytech, Energytech 2011

International Standard Book Number 13 (ISBN-13)

  • 9781457707773

Digital Object Identifier (DOI)

  • 10.1109/EnergyTech.2011.5948537

Citation Source

  • Scopus