Interpreting acoustic emission signals by artificial neural networks to predict the residual strength of pre-fatigued GFRP laminates

Composites Science and Technology

Volumn 66, Issue 2, 2006, Pages 233-239

  Leone, C ^a   Caprino, G ^a   de Iorio, I ^a  

^a UNIVERSITY OF NAPLES FEDERICO II   (Italy)

Author keywords

Acoustic emission D; Artificial neural networks; Fatigue B; Polymer matrix composites A

Indexed keywords

ACOUSTIC EMISSION TESTING; FATIGUE OF MATERIALS; FRACTURE MECHANICS; LAMINATED COMPOSITES; MATHEMATICAL MODELS; NEURAL NETWORKS; NONDESTRUCTIVE EXAMINATION; RESIDUAL STRESSES; STRENGTH OF MATERIALS;

ACOUSTIC EMISSION SIGNALS; POLYMER-MATRIX COMPOSITES; RESIDUAL STRENGTH;

GLASS FIBER REINFORCED PLASTICS;

FATIGUE; FIBER REINFORCED COMPOSITE; GLASS FIBER; NEURAL NETWORK; STRENGTH;

EID: 29244487546     PISSN: 02663538     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compscitech.2005.04.032     Document Type: Article

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