University of Hertfordshire

By the same authors

A methodology using health and usage monitoring system data for payload life prediction

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Original languageEnglish
Title of host publicationProceedings of ISMA2018 International Conference on Noise and Vibration Engineering
EditorsW Desmet, B Pluymers, D Moens, W Rottiers
PublisherKU Leuven
ChapterStructural health monitoring
Pages3711-3722
Number of pages12
Publication statusPublished - 17 Sep 2018

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 of
this 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 in
export 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.

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