Minimizing Fatigue Damage in Aircraft Structures

Aircraft structural health monitoring (SHM) refers to a process in which sensors assess the current (and predict the future) state of a structure in terms of its aging and deterioration to assure users or operators of its safety and performance. In addition to preventing failures, SHM extends aircra...

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Veröffentlicht in:IEEE intelligent systems Jg. 31; H. 4; S. 22 - 29
Hauptverfasser: Ruotsalainen, Marja, Jylha, Juha, Visa, Ari
Format: Journal Article
Sprache:Englisch
Veröffentlicht: IEEE 01.07.2016
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ISSN:1541-1672, 1941-1294
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Zusammenfassung:Aircraft structural health monitoring (SHM) refers to a process in which sensors assess the current (and predict the future) state of a structure in terms of its aging and deterioration to assure users or operators of its safety and performance. In addition to preventing failures, SHM extends aircraft life cycles. Consequently, adopting SHM is strongly motivated not only by flight safety but also by economic considerations. This article focuses on the optimization of aircraft usage as a new aspect of SHM and discusses a knowledge discovery approach based on dynamic time warping and genetic programming. In addition, it points out some of the challenges faced in applying artificial intelligence to aircraft SHM. This novel work reveals that AI provides a means to gain valuable knowledge for decision making on cost-efficient future usage of an aircraft fleet.
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content type line 23
ISSN:1541-1672
1941-1294
DOI:10.1109/MIS.2016.23