Online assessment of the structural health of aircrafts is crucial both in military and civilian settings. In this paper, Artificial Neural Networks (ANNs) are exploited to obtain a reliable system performing two tasks: diagnosis and prognosis. Diagnosis is devoted to (a) detect a crack, (b) identify the component of the panel involved (bay or stringer) and (c) estimate crack centre and size. Prognosis aims at estimating the evolution of the crack and the Remaining Useful Life (RUL). Training of the ANNs is performed on data sets built through finite elements simulation. Two different ANN hierarchies are presented for diagnosis. Crack evolution is performed for cracks on bay and stringer, separately. Two ANNs are used to estimate the parameters of a crack propagation model (NASGRO equation) for RUL prediction. Copyright © 2013 Inderscience Enterprises Ltd.

Candelieri, A., Sormani, R., Arosio, G., Giordani, I., Archetti, F. (2013). Assessing structural health of helicopter fuselage panels through artificial neural networks hierarchies. INTERNATIONAL JOURNAL OF RELIABILITY AND SAFETY, 7(3), 216-234 [10.1504/IJRS.2013.057091].

Assessing structural health of helicopter fuselage panels through artificial neural networks hierarchies

CANDELIERI, ANTONIO
;
SORMANI, RAUL
Secondo
;
GIORDANI, ILARIA
Penultimo
;
ARCHETTI, FRANCESCO ANTONIO
Ultimo
2013

Abstract

Online assessment of the structural health of aircrafts is crucial both in military and civilian settings. In this paper, Artificial Neural Networks (ANNs) are exploited to obtain a reliable system performing two tasks: diagnosis and prognosis. Diagnosis is devoted to (a) detect a crack, (b) identify the component of the panel involved (bay or stringer) and (c) estimate crack centre and size. Prognosis aims at estimating the evolution of the crack and the Remaining Useful Life (RUL). Training of the ANNs is performed on data sets built through finite elements simulation. Two different ANN hierarchies are presented for diagnosis. Crack evolution is performed for cracks on bay and stringer, separately. Two ANNs are used to estimate the parameters of a crack propagation model (NASGRO equation) for RUL prediction. Copyright © 2013 Inderscience Enterprises Ltd.
Articolo in rivista - Articolo scientifico
Artificial neural network; Hierarchies of classifiers; Structural health monitoring system; Safety, Risk, Reliability and Quality
English
2013
7
3
216
234
reserved
Candelieri, A., Sormani, R., Arosio, G., Giordani, I., Archetti, F. (2013). Assessing structural health of helicopter fuselage panels through artificial neural networks hierarchies. INTERNATIONAL JOURNAL OF RELIABILITY AND SAFETY, 7(3), 216-234 [10.1504/IJRS.2013.057091].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/59164
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