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dc.contributor.authorLewis, Andrew
dc.contributor.authorNalliah, Philip
dc.contributor.authorLomax, Colin
dc.contributor.authorHawkins, Chris
dc.contributor.editorDesmet, W
dc.contributor.editorPluymers, B
dc.contributor.editorMoens, D
dc.contributor.editorRottiers, W
dc.date.accessioned2020-05-03T00:01:29Z
dc.date.available2020-05-03T00:01:29Z
dc.date.issued2018-09-17
dc.identifier.citationLewis , A , Nalliah , P , Lomax , C & Hawkins , C 2018 , A methodology using health and usage monitoring system data for payload life prediction . in W Desmet , B Pluymers , D Moens & W Rottiers (eds) , Proceedings of ISMA 2018 International Conference on Noise and Vibration Engineering . KU Leuven , pp. 3837-3848 . < http://past.isma-isaac.be/downloads/isma2018/proceedings/Contribution_570_proceeding_3.pdf >
dc.identifier.otherPURE: 15566215
dc.identifier.otherPURE UUID: 1aa838a1-8572-45f8-812f-1899670ed209
dc.identifier.otherScopus: 85060376430
dc.identifier.urihttp://hdl.handle.net/2299/22646
dc.description© 2018 The Author(s).
dc.description.abstractThis paper presents a methodology to monitor the fatigue life of aerospace structures and hence the remaining allowable fatigue life. In fatigue clearance, conservative load assumptions are made. However, in reality, a structure may see much lower loads and so would be usable for much longer. An example ofthis is air carried guided missiles. In the UK, missiles must be decommissioned after a period of carriage. The implementation of a system that can monitor the usage of a missile during its time in service is advantageous to the military customer and provides a competitive advantage for the missile manufacture inexport markets where reduced through-life costs, longer in-service lives and increased safety are desired. The proposed methodology provides a means to monitor the service life of a missile. This paper describes how machine learning algorithms can be used with accelerometers to determine loads on a missile structure which would then be used to predict how long the missile has left in service.en
dc.format.extent12
dc.language.isoeng
dc.publisherKU Leuven
dc.relation.ispartofProceedings of ISMA 2018 International Conference on Noise and Vibration Engineering
dc.titleA methodology using health and usage monitoring system data for payload life predictionen
dc.contributor.institutionSchool of Engineering and Technology
dc.contributor.institutionCentre for Engineering Research
dc.contributor.institutionMaterials and Structures
dc.identifier.urlhttp://past.isma-isaac.be/downloads/isma2018/proceedings/Contribution_570_proceeding_3.pdf
rioxxterms.versionAM
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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