Reliability Synthesis and Prediction for Complex Electromechanical System: A Case Study

The life test of a complex electromechanical system (CEMS) is restricted by many factors, such as test time, test cost, test environment, test site, and test conditions. It is difficult to realize system reliability synthesis and prediction of a CEMS which consists of units with different life distr...
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Autor*in:	Chunyu Yu [verfasserIn] Yuanlin Guan [verfasserIn] Xixin Yang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Monte Carlo simulation computer simulation system reliability prediction system reliability synthesis complex electromechanical system

Übergeordnetes Werk:	In: Frontiers in Energy Research - Frontiers Media S.A., 2014, 10(2022)
Übergeordnetes Werk:	volume:10 ; year:2022

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fenrg.2022.865252

Katalog-ID:	DOAJ006559719

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allfields	10.3389/fenrg.2022.865252 doi (DE-627)DOAJ006559719 (DE-599)DOAJ9669f30bb5544482bc6cdc59034f339d DE-627 ger DE-627 rakwb eng Chunyu Yu verfasserin aut Reliability Synthesis and Prediction for Complex Electromechanical System: A Case Study 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The life test of a complex electromechanical system (CEMS) is restricted by many factors, such as test time, test cost, test environment, test site, and test conditions. It is difficult to realize system reliability synthesis and prediction of a CEMS which consists of units with different life distributions. Aiming at the problems, a numerical analysis method based on the computer simulation and the Monte Carlo (MC) method is proposed. First, the unit’s life simulation values are simulated using the MC method with the given each unit’s life distribution and its distribution parameter point estimation. Next, using the unit’s life simulation values, the CEMS life simulation value can be obtained based on the CEMS reliability model. A simulation test is realized instead of the life test of the CEMS when there are enough simulation values of the CEMS life. Then, simulation data are analyzed, and the distribution of the CEMS life is deduced. The goodness-of-fit test, point estimation and confidence interval of the parameters, and reliability measure are estimated. Finally, as a test example of the wind turbine, the practicability and effectiveness of the method proposed in this paper are verified. Monte Carlo simulation computer simulation system reliability prediction system reliability synthesis complex electromechanical system General Works A Chunyu Yu verfasserin aut Yuanlin Guan verfasserin aut Yuanlin Guan verfasserin aut Xixin Yang verfasserin aut In Frontiers in Energy Research Frontiers Media S.A., 2014 10(2022) (DE-627)768576768 (DE-600)2733788-1 2296598X nnns volume:10 year:2022 https://doi.org/10.3389/fenrg.2022.865252 kostenfrei https://doaj.org/article/9669f30bb5544482bc6cdc59034f339d kostenfrei https://www.frontiersin.org/articles/10.3389/fenrg.2022.865252/full kostenfrei https://doaj.org/toc/2296-598X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022
spelling	10.3389/fenrg.2022.865252 doi (DE-627)DOAJ006559719 (DE-599)DOAJ9669f30bb5544482bc6cdc59034f339d DE-627 ger DE-627 rakwb eng Chunyu Yu verfasserin aut Reliability Synthesis and Prediction for Complex Electromechanical System: A Case Study 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The life test of a complex electromechanical system (CEMS) is restricted by many factors, such as test time, test cost, test environment, test site, and test conditions. It is difficult to realize system reliability synthesis and prediction of a CEMS which consists of units with different life distributions. Aiming at the problems, a numerical analysis method based on the computer simulation and the Monte Carlo (MC) method is proposed. First, the unit’s life simulation values are simulated using the MC method with the given each unit’s life distribution and its distribution parameter point estimation. Next, using the unit’s life simulation values, the CEMS life simulation value can be obtained based on the CEMS reliability model. A simulation test is realized instead of the life test of the CEMS when there are enough simulation values of the CEMS life. Then, simulation data are analyzed, and the distribution of the CEMS life is deduced. The goodness-of-fit test, point estimation and confidence interval of the parameters, and reliability measure are estimated. Finally, as a test example of the wind turbine, the practicability and effectiveness of the method proposed in this paper are verified. Monte Carlo simulation computer simulation system reliability prediction system reliability synthesis complex electromechanical system General Works A Chunyu Yu verfasserin aut Yuanlin Guan verfasserin aut Yuanlin Guan verfasserin aut Xixin Yang verfasserin aut In Frontiers in Energy Research Frontiers Media S.A., 2014 10(2022) (DE-627)768576768 (DE-600)2733788-1 2296598X nnns volume:10 year:2022 https://doi.org/10.3389/fenrg.2022.865252 kostenfrei https://doaj.org/article/9669f30bb5544482bc6cdc59034f339d kostenfrei https://www.frontiersin.org/articles/10.3389/fenrg.2022.865252/full kostenfrei https://doaj.org/toc/2296-598X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022
allfields_unstemmed	10.3389/fenrg.2022.865252 doi (DE-627)DOAJ006559719 (DE-599)DOAJ9669f30bb5544482bc6cdc59034f339d DE-627 ger DE-627 rakwb eng Chunyu Yu verfasserin aut Reliability Synthesis and Prediction for Complex Electromechanical System: A Case Study 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The life test of a complex electromechanical system (CEMS) is restricted by many factors, such as test time, test cost, test environment, test site, and test conditions. It is difficult to realize system reliability synthesis and prediction of a CEMS which consists of units with different life distributions. Aiming at the problems, a numerical analysis method based on the computer simulation and the Monte Carlo (MC) method is proposed. First, the unit’s life simulation values are simulated using the MC method with the given each unit’s life distribution and its distribution parameter point estimation. Next, using the unit’s life simulation values, the CEMS life simulation value can be obtained based on the CEMS reliability model. A simulation test is realized instead of the life test of the CEMS when there are enough simulation values of the CEMS life. Then, simulation data are analyzed, and the distribution of the CEMS life is deduced. The goodness-of-fit test, point estimation and confidence interval of the parameters, and reliability measure are estimated. Finally, as a test example of the wind turbine, the practicability and effectiveness of the method proposed in this paper are verified. Monte Carlo simulation computer simulation system reliability prediction system reliability synthesis complex electromechanical system General Works A Chunyu Yu verfasserin aut Yuanlin Guan verfasserin aut Yuanlin Guan verfasserin aut Xixin Yang verfasserin aut In Frontiers in Energy Research Frontiers Media S.A., 2014 10(2022) (DE-627)768576768 (DE-600)2733788-1 2296598X nnns volume:10 year:2022 https://doi.org/10.3389/fenrg.2022.865252 kostenfrei https://doaj.org/article/9669f30bb5544482bc6cdc59034f339d kostenfrei https://www.frontiersin.org/articles/10.3389/fenrg.2022.865252/full kostenfrei https://doaj.org/toc/2296-598X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022
allfieldsGer	10.3389/fenrg.2022.865252 doi (DE-627)DOAJ006559719 (DE-599)DOAJ9669f30bb5544482bc6cdc59034f339d DE-627 ger DE-627 rakwb eng Chunyu Yu verfasserin aut Reliability Synthesis and Prediction for Complex Electromechanical System: A Case Study 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The life test of a complex electromechanical system (CEMS) is restricted by many factors, such as test time, test cost, test environment, test site, and test conditions. It is difficult to realize system reliability synthesis and prediction of a CEMS which consists of units with different life distributions. Aiming at the problems, a numerical analysis method based on the computer simulation and the Monte Carlo (MC) method is proposed. First, the unit’s life simulation values are simulated using the MC method with the given each unit’s life distribution and its distribution parameter point estimation. Next, using the unit’s life simulation values, the CEMS life simulation value can be obtained based on the CEMS reliability model. A simulation test is realized instead of the life test of the CEMS when there are enough simulation values of the CEMS life. Then, simulation data are analyzed, and the distribution of the CEMS life is deduced. The goodness-of-fit test, point estimation and confidence interval of the parameters, and reliability measure are estimated. Finally, as a test example of the wind turbine, the practicability and effectiveness of the method proposed in this paper are verified. Monte Carlo simulation computer simulation system reliability prediction system reliability synthesis complex electromechanical system General Works A Chunyu Yu verfasserin aut Yuanlin Guan verfasserin aut Yuanlin Guan verfasserin aut Xixin Yang verfasserin aut In Frontiers in Energy Research Frontiers Media S.A., 2014 10(2022) (DE-627)768576768 (DE-600)2733788-1 2296598X nnns volume:10 year:2022 https://doi.org/10.3389/fenrg.2022.865252 kostenfrei https://doaj.org/article/9669f30bb5544482bc6cdc59034f339d kostenfrei https://www.frontiersin.org/articles/10.3389/fenrg.2022.865252/full kostenfrei https://doaj.org/toc/2296-598X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022
allfieldsSound	10.3389/fenrg.2022.865252 doi (DE-627)DOAJ006559719 (DE-599)DOAJ9669f30bb5544482bc6cdc59034f339d DE-627 ger DE-627 rakwb eng Chunyu Yu verfasserin aut Reliability Synthesis and Prediction for Complex Electromechanical System: A Case Study 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The life test of a complex electromechanical system (CEMS) is restricted by many factors, such as test time, test cost, test environment, test site, and test conditions. It is difficult to realize system reliability synthesis and prediction of a CEMS which consists of units with different life distributions. Aiming at the problems, a numerical analysis method based on the computer simulation and the Monte Carlo (MC) method is proposed. First, the unit’s life simulation values are simulated using the MC method with the given each unit’s life distribution and its distribution parameter point estimation. Next, using the unit’s life simulation values, the CEMS life simulation value can be obtained based on the CEMS reliability model. A simulation test is realized instead of the life test of the CEMS when there are enough simulation values of the CEMS life. Then, simulation data are analyzed, and the distribution of the CEMS life is deduced. The goodness-of-fit test, point estimation and confidence interval of the parameters, and reliability measure are estimated. Finally, as a test example of the wind turbine, the practicability and effectiveness of the method proposed in this paper are verified. Monte Carlo simulation computer simulation system reliability prediction system reliability synthesis complex electromechanical system General Works A Chunyu Yu verfasserin aut Yuanlin Guan verfasserin aut Yuanlin Guan verfasserin aut Xixin Yang verfasserin aut In Frontiers in Energy Research Frontiers Media S.A., 2014 10(2022) (DE-627)768576768 (DE-600)2733788-1 2296598X nnns volume:10 year:2022 https://doi.org/10.3389/fenrg.2022.865252 kostenfrei https://doaj.org/article/9669f30bb5544482bc6cdc59034f339d kostenfrei https://www.frontiersin.org/articles/10.3389/fenrg.2022.865252/full kostenfrei https://doaj.org/toc/2296-598X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022
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author	Chunyu Yu
spellingShingle	Chunyu Yu misc Monte Carlo simulation misc computer simulation misc system reliability prediction misc system reliability synthesis misc complex electromechanical system misc General Works misc A Reliability Synthesis and Prediction for Complex Electromechanical System: A Case Study
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topic_title	Reliability Synthesis and Prediction for Complex Electromechanical System: A Case Study Monte Carlo simulation computer simulation system reliability prediction system reliability synthesis complex electromechanical system
topic	misc Monte Carlo simulation misc computer simulation misc system reliability prediction misc system reliability synthesis misc complex electromechanical system misc General Works misc A
topic_unstemmed	misc Monte Carlo simulation misc computer simulation misc system reliability prediction misc system reliability synthesis misc complex electromechanical system misc General Works misc A
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title	Reliability Synthesis and Prediction for Complex Electromechanical System: A Case Study
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title_full	Reliability Synthesis and Prediction for Complex Electromechanical System: A Case Study
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title_sort	reliability synthesis and prediction for complex electromechanical system: a case study
title_auth	Reliability Synthesis and Prediction for Complex Electromechanical System: A Case Study
abstract	The life test of a complex electromechanical system (CEMS) is restricted by many factors, such as test time, test cost, test environment, test site, and test conditions. It is difficult to realize system reliability synthesis and prediction of a CEMS which consists of units with different life distributions. Aiming at the problems, a numerical analysis method based on the computer simulation and the Monte Carlo (MC) method is proposed. First, the unit’s life simulation values are simulated using the MC method with the given each unit’s life distribution and its distribution parameter point estimation. Next, using the unit’s life simulation values, the CEMS life simulation value can be obtained based on the CEMS reliability model. A simulation test is realized instead of the life test of the CEMS when there are enough simulation values of the CEMS life. Then, simulation data are analyzed, and the distribution of the CEMS life is deduced. The goodness-of-fit test, point estimation and confidence interval of the parameters, and reliability measure are estimated. Finally, as a test example of the wind turbine, the practicability and effectiveness of the method proposed in this paper are verified.
abstractGer	The life test of a complex electromechanical system (CEMS) is restricted by many factors, such as test time, test cost, test environment, test site, and test conditions. It is difficult to realize system reliability synthesis and prediction of a CEMS which consists of units with different life distributions. Aiming at the problems, a numerical analysis method based on the computer simulation and the Monte Carlo (MC) method is proposed. First, the unit’s life simulation values are simulated using the MC method with the given each unit’s life distribution and its distribution parameter point estimation. Next, using the unit’s life simulation values, the CEMS life simulation value can be obtained based on the CEMS reliability model. A simulation test is realized instead of the life test of the CEMS when there are enough simulation values of the CEMS life. Then, simulation data are analyzed, and the distribution of the CEMS life is deduced. The goodness-of-fit test, point estimation and confidence interval of the parameters, and reliability measure are estimated. Finally, as a test example of the wind turbine, the practicability and effectiveness of the method proposed in this paper are verified.
abstract_unstemmed	The life test of a complex electromechanical system (CEMS) is restricted by many factors, such as test time, test cost, test environment, test site, and test conditions. It is difficult to realize system reliability synthesis and prediction of a CEMS which consists of units with different life distributions. Aiming at the problems, a numerical analysis method based on the computer simulation and the Monte Carlo (MC) method is proposed. First, the unit’s life simulation values are simulated using the MC method with the given each unit’s life distribution and its distribution parameter point estimation. Next, using the unit’s life simulation values, the CEMS life simulation value can be obtained based on the CEMS reliability model. A simulation test is realized instead of the life test of the CEMS when there are enough simulation values of the CEMS life. Then, simulation data are analyzed, and the distribution of the CEMS life is deduced. The goodness-of-fit test, point estimation and confidence interval of the parameters, and reliability measure are estimated. Finally, as a test example of the wind turbine, the practicability and effectiveness of the method proposed in this paper are verified.
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title_short	Reliability Synthesis and Prediction for Complex Electromechanical System: A Case Study
url	https://doi.org/10.3389/fenrg.2022.865252 https://doaj.org/article/9669f30bb5544482bc6cdc59034f339d https://www.frontiersin.org/articles/10.3389/fenrg.2022.865252/full https://doaj.org/toc/2296-598X
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up_date	2024-07-03T21:38:45.335Z
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