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

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• 作者：N.I.E. Farhana^a ; ^{farhanaizwani@ymail.com" class="auth_mail" title="E-mail the corresponding author} ; M.S. Abdul Majid^a ; ^{shukry@unimap.edu.my" class="auth_mail" title="E-mail the corresponding author} ; M.P. Paulraj^a ; ^{paul@unimap.edu.my" class="auth_mail" title="E-mail the corresponding author} ; E. Ahmadhilmi^b ; ^{hilmi@sirim.my" class="auth_mail" title="E-mail the corresponding author} ; M.N. Fakhzan^a ; ^{fakhzan@unimap.edu.my" class="auth_mail" title="E-mail the corresponding author} ; A.G. Gibson^c ; ^{geoff.gibson@ncl.co.uk" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Volume fraction ; Composites material ; Vibration signal ; Non-destructive testing ; Neural network model
• 刊名：Composite Structures
• 出版年：2016
• 出版时间：1 June 2016
• 年：2016
• 卷：144
• 期：Complete
• 页码：96-107
• 全文大小：2534 K

文摘

This study proposes a novel approach to determine the fibre volume fraction in composites using vibration based non-destructive technique with a neural network. Currently, the volume fraction of a glass fibre/matrix based composite material is assessed using destructive techniques. Instead of changing or destroying the structure, a new non-destructive approach based on vibration analysis is proposed. Complete experimental protocols were developed to capture the vibration pattern. An auto-regressive model was developed as a feature extraction tool to classify the fibre volume fractions and as a pole tracking algorithm. The classification performances were within the range of 90–98%. For NDT method to be efficient, the classification results were then compared with destructive burn-out technique. The results of non-destructive test showed good agreement with those obtained through destructive test suggesting that the proposed method is an alternative to ASTM D2584-11 for determining the volume fraction of a glass fibre/matrix composite.