Determining the reliability function of the thermal power system in power plant "Nikola Tesla, Block B1"

Representation of probabilistic technique for evaluation of thermal power system reliability is the main subject of this paper. The system of thermal power plant under study consists of three subsystems and the reliability assessment is based on a sixteen-year failure database. By applying...

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Main Authors: Kalaba Dragan V., Đorđević Milan Lj., Kirin Snežana D.
Format: Article
Language:English
Published: VINCA Institute of Nuclear Sciences 2015-01-01
Series:Thermal Science
Subjects:
Online Access:http://www.doiserbia.nb.rs/img/doi/0354-9836/2015/0354-98361400144K.pdf
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spelling doaj-006fafaa743847ecbb3b6d93d50e63622021-01-02T00:34:38ZengVINCA Institute of Nuclear SciencesThermal Science0354-98362334-71632015-01-0119379380010.2298/TSCI140610144K0354-98361400144KDetermining the reliability function of the thermal power system in power plant "Nikola Tesla, Block B1"Kalaba Dragan V.0Đorđević Milan Lj.1Kirin Snežana D.2Faculty of Technical Sciences, Kosovska MitrovicaFaculty of Technical Sciences, Kosovska MitrovicaFaculty of Mechanical Engineering, Innovation Center, BelgradeRepresentation of probabilistic technique for evaluation of thermal power system reliability is the main subject of this paper. The system of thermal power plant under study consists of three subsystems and the reliability assessment is based on a sixteen-year failure database. By applying the mathematical theory of reliability to exploitation research data and using complex two-parameter Weibull distribution, the theoretical reliability functions of specified system have been determined. Obtained probabilistic laws of failure occurrence have confirmed a hypothesis that the distribution of the observed random variable fully describes behaviour of such a system in terms of reliability. Shown results make possible to acquire a better knowledge of current state of the system, as well as a more accurate estimation of its behavior during future exploitation. Final benefit is opportunity for potential improvement of complex system maintenance policies aimed at the reduction of unexpected failure occurrences.http://www.doiserbia.nb.rs/img/doi/0354-9836/2015/0354-98361400144K.pdfThermal power systemreliabilityWeibull distribution
collection DOAJ
language English
format Article
sources DOAJ
author Kalaba Dragan V.
Đorđević Milan Lj.
Kirin Snežana D.
spellingShingle Kalaba Dragan V.
Đorđević Milan Lj.
Kirin Snežana D.
Determining the reliability function of the thermal power system in power plant "Nikola Tesla, Block B1"
Thermal Science
Thermal power system
reliability
Weibull distribution
author_facet Kalaba Dragan V.
Đorđević Milan Lj.
Kirin Snežana D.
author_sort Kalaba Dragan V.
title Determining the reliability function of the thermal power system in power plant "Nikola Tesla, Block B1"
title_short Determining the reliability function of the thermal power system in power plant "Nikola Tesla, Block B1"
title_full Determining the reliability function of the thermal power system in power plant "Nikola Tesla, Block B1"
title_fullStr Determining the reliability function of the thermal power system in power plant "Nikola Tesla, Block B1"
title_full_unstemmed Determining the reliability function of the thermal power system in power plant "Nikola Tesla, Block B1"
title_sort determining the reliability function of the thermal power system in power plant "nikola tesla, block b1"
publisher VINCA Institute of Nuclear Sciences
series Thermal Science
issn 0354-9836
2334-7163
publishDate 2015-01-01
description Representation of probabilistic technique for evaluation of thermal power system reliability is the main subject of this paper. The system of thermal power plant under study consists of three subsystems and the reliability assessment is based on a sixteen-year failure database. By applying the mathematical theory of reliability to exploitation research data and using complex two-parameter Weibull distribution, the theoretical reliability functions of specified system have been determined. Obtained probabilistic laws of failure occurrence have confirmed a hypothesis that the distribution of the observed random variable fully describes behaviour of such a system in terms of reliability. Shown results make possible to acquire a better knowledge of current state of the system, as well as a more accurate estimation of its behavior during future exploitation. Final benefit is opportunity for potential improvement of complex system maintenance policies aimed at the reduction of unexpected failure occurrences.
topic Thermal power system
reliability
Weibull distribution
url http://www.doiserbia.nb.rs/img/doi/0354-9836/2015/0354-98361400144K.pdf
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