A prognostic approach to improve system reliability for aircraft system

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dc.contributor.authorFu, Shuai
dc.contributor.authorAvdelidis, Nicolas P.
dc.contributor.authorJennions, Ian K.
dc.date.accessioned2024-02-05T11:37:12Z
dc.date.available2024-02-05T11:37:12Z
dc.date.issued2023-01-08
dc.description.abstractThe primary aims of prognostics encompass the timely detection of potential failures, mitigation or elimination of unscheduled maintenance, prediction of the most suitable timing for preventive maintenance replacement, optimization of maintenance cycles and operational readiness, and enhancement of system reliability by improving design and logistical support for existing systems. In order to facilitate the progress of these approaches, currently available datasets provide a unique and reliable compilation of flight-to-failure trajectories linked to small aircraft engines that have been observed in actual flight conditions. Furthermore, the paper offered an improved neural network that utilized the TanH hyperbolic tangent function. This neural network was enhanced later by integrating it with the TanH, linear, and Gaussian functions. Additionally, a random holdback validation approach was employed in the paper. The results suggest that the NN TanH technique, when implemented, has the potential to significantly enhance the reliability of an aircraft component. This is achieved through accurate estimates of the remaining useful life (RUL) and a proactive understanding of the failure system.en_UK
dc.description.sponsorshipEuropean Commission: Grant Number 955681en_UK
dc.identifier.citationFu S, Avdelidis NP, Jennions IK. (2023) A prognostic approach to improve system reliability for aircraft system. In: 7th International Conference on System Reliability and Safety (ICSRS), 22-24 November 2023, Bologna, Italy, pp. 259-264en_UK
dc.identifier.eisbn979-8-3503-0605-7
dc.identifier.isbn979-8-3503-0606-4
dc.identifier.urihttps://doi.org/10.1109/ICSRS59833.2023.10381117
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/20742
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectprognosticsen_UK
dc.subjecthealth managementen_UK
dc.subjectremaining useful lifeen_UK
dc.subjectaircraft engineen_UK
dc.subjectneural networken_UK
dc.titleA prognostic approach to improve system reliability for aircraft systemen_UK
dc.typeConference paperen_UK
dcterms.dateAccepted2023-09-05

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