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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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/ |
work_keys_str_mv |
AT junwang anadaptivereliabilitypredictionmethodfortheintelligentsatellitepowerdistributionsystem AT yubintian anadaptivereliabilitypredictionmethodfortheintelligentsatellitepowerdistributionsystem AT junwang adaptivereliabilitypredictionmethodfortheintelligentsatellitepowerdistributionsystem AT yubintian adaptivereliabilitypredictionmethodfortheintelligentsatellitepowerdistributionsystem |
_version_ |
1724192454879477760 |