dc.contributor.author | Lewis, Andrew | |
dc.contributor.author | Nalliah, Philip | |
dc.contributor.author | Lomax, Colin | |
dc.contributor.author | Hawkins, Chris | |
dc.contributor.editor | Desmet, W | |
dc.contributor.editor | Pluymers, B | |
dc.contributor.editor | Moens, D | |
dc.contributor.editor | Rottiers, W | |
dc.date.accessioned | 2020-05-03T00:01:29Z | |
dc.date.available | 2020-05-03T00:01:29Z | |
dc.date.issued | 2018-09-17 | |
dc.identifier.citation | Lewis , 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.uri | http://hdl.handle.net/2299/22646 | |
dc.description | © 2018 The Author(s). | |
dc.description.abstract | This 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.extent | 12 | |
dc.format.extent | 1447778 | |
dc.language.iso | eng | |
dc.publisher | KU Leuven | |
dc.relation.ispartof | Proceedings of ISMA 2018 International Conference on Noise and Vibration Engineering | |
dc.title | A methodology using health and usage monitoring system data for payload life prediction | en |
dc.contributor.institution | School of Engineering and Technology | |
dc.contributor.institution | Centre for Engineering Research | |
dc.contributor.institution | Materials and Structures | |
dc.identifier.url | http://past.isma-isaac.be/downloads/isma2018/proceedings/Contribution_570_proceeding_3.pdf | |
rioxxterms.type | Other | |
herts.preservation.rarelyaccessed | true | |