Certification of machine learning algorithms for safe life assessment of landing gear

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dc.contributor.authorEl Mir, Haroun
dc.contributor.authorPerinpanayagam, Suresh
dc.date.accessioned2022-11-29T10:54:59Z
dc.date.available2022-11-29T10:54:59Z
dc.date.issued2022-11-15
dc.description.abstractThis paper provides information on current certification of landing gear available for use in the aerospace industry. Moving forward, machine learning is part of structural health monitoring, which is being used by the aircraft industry. The non-deterministic nature of deep learning algorithms is regarded as a hurdle for certification and verification for use in the highly-regulated aerospace industry. This paper brings forth its regulation requirements and the emergence of standardisation efforts. To be able to validate machine learning for safety critical applications such as landing gear, the safe-life fatigue assessment needs to be certified such that the remaining useful life may be accurately predicted and trusted. A coverage of future certification for the usage of machine learning in safety-critical aerospace systems is provided, taking into consideration both the risk management and explainability for different end user categories involved in the certification process. Additionally, provisional use case scenarios are demonstrated, in which risk assessments and uncertainties are incorporated for the implementation of a proposed certification approach targeting offline machine learning models and their explainable usage for predicting the remaining useful life of landing gear systems based on the safe-life method.en_UK
dc.identifier.citationEl Mir H & Perinpanayagam S (2022) Certification of machine learning algorithms for safe life assessment of landing gear, Frontiers in Astronomy and Space Sciences, Volume 9, November 2022, Article number 896877en_UK
dc.identifier.issn2296-987X
dc.identifier.urihttps://doi.org/10.3389/fspas.2022.896877
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/18751
dc.language.isoenen_UK
dc.publisherFrontiersen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectexplainable AIen_UK
dc.subjectlanding gear systemsen_UK
dc.subjectcertificationen_UK
dc.subjectrisk managementen_UK
dc.subjectsafe-life designen_UK
dc.titleCertification of machine learning algorithms for safe life assessment of landing gearen_UK
dc.typeArticleen_UK

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