Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/34220
Title: Extraction and processing of real time strain of embedded FBG sensors using a fixed filter FBG circuit and an artificial neural network
Authors: Kahandawa, GC
Epaarachchi, J
Wang, H
Canning, J
Lau, KT 
Keywords: Composite structures
FBG sensors
Structural health monitoring
Issue Date: 2013
Publisher: Elsevier
Source: Measurement : journal of the international measurement confederation, 2013, v. 46, no. 10, p. 4045-4051 How to cite?
Journal: Measurement : journal of the international measurement confederation 
Abstract: Fibre Bragg Grating (FBG) sensors have been used in the development of structural health monitoring (SHM) and damage detection systems for advanced composite structures over several decades. Unfortunately, to date only a handful of appropriate configurations and algorithm sare available for using in SHM systems have been developed. This paper reveals a novel configuration of FBG sensors to acquire strain reading and an integrated statistical approach to analyse data in real time. The proposed configuration has proven its capability to overcome practical constraints and the engineering challenges associated with FBG-based SHM systems. A fixed filter decoding system and an integrated artificial neural network algorithm for extracting strain from embedded FBG sensor were proposed and experimentally proved. Furthermore, the laboratory level experimental data was used to verify the accuracy of the system and it was found that the error levels were less than 0.3% in predictions. The developed SMH system using this technology has been submitted to US patent office and will be available for use of aerospace applications in due course.
URI: http://hdl.handle.net/10397/34220
ISSN: 0263-2241
DOI: 10.1016/j.measurement.2013.07.029
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