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Abstract
In the context of Structural Health Monitoring, the Acoustic Emission Technique may be efficiently used to detect damage on aerospace structures. This study focuses on the development of a source identification algorithm to distinguish different acoustic emission events in aluminium sheets, which have been collected during experimental tests. The future goal will be the design of a Holistic Structural Health Monitoring System which will make the complete aircraft an intelligent structure able to diagnose its own structural damage based on the condition of the structure while maintaining safety.
Abstract
In the context of Structural Health Monitoring, the Acoustic Emission Technique may be efficiently used to detect damage on aerospace structures. This study focuses on the development of a source identification algorithm to distinguish different acoustic emission events in aluminium sheets, which have been collected during experimental tests. The future goal will be the design of a Holistic Structural Health Monitoring System which will make the complete aircraft an intelligent structure able to diagnose its own structural damage based on the condition of the structure while maintaining safety.
Tipologia del documento
Tesi di laurea
(Laurea magistrale)
Autore della tesi
Facciotto, Nicolò
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
Acoustic emissions, structural health monitoring, pattern recognition
Data di discussione della Tesi
16 Marzo 2017
URI
Altri metadati
Tipologia del documento
Tesi di laurea
(NON SPECIFICATO)
Autore della tesi
Facciotto, Nicolò
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
Acoustic emissions, structural health monitoring, pattern recognition
Data di discussione della Tesi
16 Marzo 2017
URI
Gestione del documento: