An Adaptive Reliability Prediction Method for the Intelligent Satellite Power Distribution System

The accurate prediction of reliability for long-time running intelligent satellite power distribution systems is crucial in engineering. In this paper, an adaptive method is proposed to achieve this goal. Based on lifetime and degradation data, an estimator of the reliability for the system is deriv...

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Main Authors: Jun Wang, Yubin Tian
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8488357/
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spelling doaj-b35ea42edaaa464a833bde065b8b90402021-03-29T21:41:03ZengIEEEIEEE Access2169-35362018-01-016587195872710.1109/ACCESS.2018.28751178488357An Adaptive Reliability Prediction Method for the Intelligent Satellite Power Distribution SystemJun Wang0https://orcid.org/0000-0002-3162-5738Yubin Tian1https://orcid.org/0000-0002-3162-5738School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, ChinaSchool of Mathematics and Statistics, Beijing Institute of Technology, Beijing, ChinaThe accurate prediction of reliability for long-time running intelligent satellite power distribution systems is crucial in engineering. In this paper, an adaptive method is proposed to achieve this goal. Based on lifetime and degradation data, an estimator of the reliability for the system is derived by mainly using an additive degradation model of combined Poisson and Gaussian processes. A locally c-optimal approach to choosing effective data from the real-time data flow is given. Associated with the sequence of observed lifetime and degradation data, a robust criterion is proposed to determine an appropriate data subset for reliability prediction. A simulation study shows that the proposed method gives superior performance over the traditional method. Benefiting from adaptive and optimal strategies, the reliability predictions for 16 to 20 years obtained from the proposed method are convincing even if the initial models fitted by the ground test data have deviations from the true models.https://ieeexplore.ieee.org/document/8488357/Satelliteintelligent power distribution systemreliability predictionadaptive estimationrecursive maximum likelihood
collection DOAJ
language English
format Article
sources DOAJ
author Jun Wang
Yubin Tian
spellingShingle Jun Wang
Yubin Tian
An Adaptive Reliability Prediction Method for the Intelligent Satellite Power Distribution System
IEEE Access
Satellite
intelligent power distribution system
reliability prediction
adaptive estimation
recursive maximum likelihood
author_facet Jun Wang
Yubin Tian
author_sort Jun Wang
title An Adaptive Reliability Prediction Method for the Intelligent Satellite Power Distribution System
title_short An Adaptive Reliability Prediction Method for the Intelligent Satellite Power Distribution System
title_full An Adaptive Reliability Prediction Method for the Intelligent Satellite Power Distribution System
title_fullStr An Adaptive Reliability Prediction Method for the Intelligent Satellite Power Distribution System
title_full_unstemmed An Adaptive Reliability Prediction Method for the Intelligent Satellite Power Distribution System
title_sort adaptive reliability prediction method for the intelligent satellite power distribution system
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2018-01-01
description The accurate prediction of reliability for long-time running intelligent satellite power distribution systems is crucial in engineering. In this paper, an adaptive method is proposed to achieve this goal. Based on lifetime and degradation data, an estimator of the reliability for the system is derived by mainly using an additive degradation model of combined Poisson and Gaussian processes. A locally c-optimal approach to choosing effective data from the real-time data flow is given. Associated with the sequence of observed lifetime and degradation data, a robust criterion is proposed to determine an appropriate data subset for reliability prediction. A simulation study shows that the proposed method gives superior performance over the traditional method. Benefiting from adaptive and optimal strategies, the reliability predictions for 16 to 20 years obtained from the proposed method are convincing even if the initial models fitted by the ground test data have deviations from the true models.
topic Satellite
intelligent power distribution system
reliability prediction
adaptive estimation
recursive maximum likelihood
url https://ieeexplore.ieee.org/document/8488357/
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