Data-Driven Health Assessment in a Flight Control System under Uncertain Conditions

PHM technology plays an increasingly significant role in modern aviation condition-based maintenance. As an important part of prognostics and health management (PHM), a health assessment can effectively estimate the health status of a system and provide support for maintenance decision making. Howev...

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Autores principales:	Jie Chen, Yuyang Zhao, Xiaofeng Xue, Runfeng Chen, Yingjian Wu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	aircraft system characteristic parameters fuzzy comprehensive assessment uncertainty qualification λ-PDF probability density maximum entropy Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/79a0d4d998a94782ac2cb472f2649eea
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spelling	oai:doaj.org-article:79a0d4d998a94782ac2cb472f2649eea2021-11-11T15:10:23ZData-Driven Health Assessment in a Flight Control System under Uncertain Conditions10.3390/app1121101072076-3417https://doaj.org/article/79a0d4d998a94782ac2cb472f2649eea2021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10107https://doaj.org/toc/2076-3417PHM technology plays an increasingly significant role in modern aviation condition-based maintenance. As an important part of prognostics and health management (PHM), a health assessment can effectively estimate the health status of a system and provide support for maintenance decision making. However, in actual conditions, various uncertain factors will amplify assessment errors and cause large fluctuations in assessment results. In this paper, uncertain factors are incorporated into flight control system health assessment modeling. First, four uncertain factors of health assessment characteristic parameters are quantified and described by the extended λ-PDF method to acquire their probability distribution function. Secondly, a Monte Carlo simulation (MCS) is used to simulate a flight control system health assessment process with uncertain factors. Thirdly, the probability distribution of the output health index is solved by the maximum entropy principle. Finally, the proposed model was verified with actual flight data. The comparison between assessment results with and without uncertain factors shows that a health assessment conducted under uncertain conditions can reduce the impact of the uncertainty of outliers on the assessment results and make the assessment results more stable; therefore, the false alarm rate can be reduced.Jie ChenYuyang ZhaoXiaofeng XueRunfeng ChenYingjian WuMDPI AGarticleaircraft systemcharacteristic parametersfuzzy comprehensive assessmentuncertainty qualificationλ-PDF probability densitymaximum entropyTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10107, p 10107 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	aircraft system characteristic parameters fuzzy comprehensive assessment uncertainty qualification λ-PDF probability density maximum entropy Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	aircraft system characteristic parameters fuzzy comprehensive assessment uncertainty qualification λ-PDF probability density maximum entropy Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Jie Chen Yuyang Zhao Xiaofeng Xue Runfeng Chen Yingjian Wu Data-Driven Health Assessment in a Flight Control System under Uncertain Conditions
description	PHM technology plays an increasingly significant role in modern aviation condition-based maintenance. As an important part of prognostics and health management (PHM), a health assessment can effectively estimate the health status of a system and provide support for maintenance decision making. However, in actual conditions, various uncertain factors will amplify assessment errors and cause large fluctuations in assessment results. In this paper, uncertain factors are incorporated into flight control system health assessment modeling. First, four uncertain factors of health assessment characteristic parameters are quantified and described by the extended λ-PDF method to acquire their probability distribution function. Secondly, a Monte Carlo simulation (MCS) is used to simulate a flight control system health assessment process with uncertain factors. Thirdly, the probability distribution of the output health index is solved by the maximum entropy principle. Finally, the proposed model was verified with actual flight data. The comparison between assessment results with and without uncertain factors shows that a health assessment conducted under uncertain conditions can reduce the impact of the uncertainty of outliers on the assessment results and make the assessment results more stable; therefore, the false alarm rate can be reduced.
format	article
author	Jie Chen Yuyang Zhao Xiaofeng Xue Runfeng Chen Yingjian Wu
author_facet	Jie Chen Yuyang Zhao Xiaofeng Xue Runfeng Chen Yingjian Wu
author_sort	Jie Chen
title	Data-Driven Health Assessment in a Flight Control System under Uncertain Conditions
title_short	Data-Driven Health Assessment in a Flight Control System under Uncertain Conditions
title_full	Data-Driven Health Assessment in a Flight Control System under Uncertain Conditions
title_fullStr	Data-Driven Health Assessment in a Flight Control System under Uncertain Conditions
title_full_unstemmed	Data-Driven Health Assessment in a Flight Control System under Uncertain Conditions
title_sort	data-driven health assessment in a flight control system under uncertain conditions
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/79a0d4d998a94782ac2cb472f2649eea
work_keys_str_mv	AT jiechen datadrivenhealthassessmentinaflightcontrolsystemunderuncertainconditions AT yuyangzhao datadrivenhealthassessmentinaflightcontrolsystemunderuncertainconditions AT xiaofengxue datadrivenhealthassessmentinaflightcontrolsystemunderuncertainconditions AT runfengchen datadrivenhealthassessmentinaflightcontrolsystemunderuncertainconditions AT yingjianwu datadrivenhealthassessmentinaflightcontrolsystemunderuncertainconditions
_version_	1718437151395282944

Data-Driven Health Assessment in a Flight Control System under Uncertain Conditions

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