@inproceedings{2535d0c8fbaa4103997009d1f5540c0e,
title = "Classification of composite damage from FBG load monitoring signals",
abstract = "This paper describes a new method for the classification and identification of two major types of defects in composites, namely delamination and matrix cracks, by classification of the spectral features of fibre Bragg grating (FBG) signals. In aeronautical applications of composites, after a damage is detected, it is very useful to know the type of damage prior to determining the treatment method of the area or perhaps replacing the part. This was achieved by embedding FBG sensors inside a glass-fibre composite, and analysing the output signal from the sensors. The glass-fibre coupons were subjected to mode-I loading under tension-compression and static tests, in order to induce matrix cracks and delamination damages respectively. Afterwards, using wavelet features extracted from spectral measurements of the FBG sensors, classification of the damage type was carried out by means of support vector machines as a general classification tool with a quadratic kernel.",
keywords = "classification, delamination, Fibre Bragg grating (FBG), load monitoring, matrix crack, support vector machines (SVM), wavelet features",
author = "Aydin Rajabzadehdizaji and Hendriks, {Richard C.} and Richard Heusdens and Groves, {Roger M.}",
year = "2017",
doi = "10.1117/12.2257660",
language = "English",
series = "Proceedings of SPIE",
publisher = "SPIE",
pages = "1--8",
booktitle = "Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017",
address = "United States",
note = "Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017 ; Conference date: 26-03-2017 Through 29-03-2017",
}