A novel vibration based non-destructive testing for predicting glass fibre/matrix volume fraction in composites using a neural network model

Composite Structures

Volumn 144, Issue , 2016, Pages 96-107

  Farhana, N I E ^a   Abdul Majid, M S ^a   Paulraj, M P ^a   Ahmadhilmi, E ^b   Fakhzan, M N ^a   Gibson, A G ^c  

^a UNIVERSITY MALAYSIA PERLIS   (Malaysia)

^b Advanced Materials Research Centre AMREC   (Malaysia)

^c NEWCASTLE UNIVERSITY   (United Kingdom)

Author keywords

Composites material; Neural network model; Non destructive testing; Vibration signal; Volume fraction

Indexed keywords

BRIDGE DECKS; DAMAGE DETECTION; FEATURE EXTRACTION; FIBERS; GLASS; GLASS FIBERS; VIBRATION ANALYSIS; VOLUME FRACTION;

CLASSIFICATION PERFORMANCE; CLASSIFICATION RESULTS; COMPOSITES MATERIAL; EXPERIMENTAL PROTOCOLS; NEURAL NETWORK MODEL; NON DESTRUCTIVE TESTING; NON-DESTRUCTIVE TECHNIQUE; VIBRATION SIGNAL;

NONDESTRUCTIVE EXAMINATION;

EID: 84959319532     PISSN: 02638223     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compstruct.2016.02.066     Document Type: Article

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