O. P. Gaona, D. González-González, Marco A. Fuentes-Huerta, R. Praga-Alejo
{"title":"Maximum entropy model applied to Reliability Centered Maintenance scheme for replaceable systems.","authors":"O. P. Gaona, D. González-González, Marco A. Fuentes-Huerta, R. Praga-Alejo","doi":"10.1109/ICMEAE.2019.00033","DOIUrl":null,"url":null,"abstract":"Based on methodologies of variational calculus and differential entropy, we propose in this work a non-parametric model that provides a robust estimation of reliability to be used in a RCM scheme. A Weibull analysis is presented first in a case study within the usual RCM schemes. If the sample of data is severly reduced the weibull analysis lost preciscion, impacting in the RCM scheme. To solve this limitation, a maximum entropy aproach is propoused.Differential entropy has been shown as a solid tool to model the response of a random variable when reduced sample size information is available. We take advantage of the formalism of the variational calculus to express a functional that obeys the Euler-Lagrange equations and supported by the Kolmogorov axioms, we extract a generalized non-parametric probability density. By subjecting this density to appropriate boundary conditions in terms of the first moments of the generalized probability density.","PeriodicalId":422872,"journal":{"name":"2019 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)","volume":"26 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMEAE.2019.00033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Based on methodologies of variational calculus and differential entropy, we propose in this work a non-parametric model that provides a robust estimation of reliability to be used in a RCM scheme. A Weibull analysis is presented first in a case study within the usual RCM schemes. If the sample of data is severly reduced the weibull analysis lost preciscion, impacting in the RCM scheme. To solve this limitation, a maximum entropy aproach is propoused.Differential entropy has been shown as a solid tool to model the response of a random variable when reduced sample size information is available. We take advantage of the formalism of the variational calculus to express a functional that obeys the Euler-Lagrange equations and supported by the Kolmogorov axioms, we extract a generalized non-parametric probability density. By subjecting this density to appropriate boundary conditions in terms of the first moments of the generalized probability density.