Use of fixed wavelength Fibre-Bragg Grating (FBG) filters to capture time domain data from the distorted spectrum of an embedded FBG sensor to estimate strain with an artificial neural network

Kahandawa, G. C. and Epaarachchi, J. A. and Wang, H. and Followell, D. and Birt, P. (2013) Use of fixed wavelength Fibre-Bragg Grating (FBG) filters to capture time domain data from the distorted spectrum of an embedded FBG sensor to estimate strain with an artificial neural network. Sensors and Actuators A: Physical, 194. pp. 1-7. ISSN 0924-4247

Abstract

It is well known that an FBG sensor spectrum is distorted, thus making it difficult to estimate strain in monitored structures by simply tracking the peak point of the spectrum. Due to this issue, the traditional data acquired in the wavelength domain from optical spectrum analysers (OSA) needs significant processing to decode it into a useable form as an input to an Artificial Neural Network (ANN), a potential candidate for post-processing irregular data sets. This paper describes a successful application of an FBG filter system using three fixed wavelength FBG filters to capture real-time data from an embedded FBG sensor in the time domain. The time domain FBG data was post-processed using power-time area integration to account for the distortion before it was input into an ANN. The strain estimated by the ANN correlates well with the empirical results.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2012 Elsevier B.V. Published version made not accessible.
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Mechanical and Mechatronic Engineering
Date Deposited: 11 Apr 2013 23:58
Last Modified: 11 Feb 2015 05:40
Uncontrolled Keywords: structural health monitoring; FBG sensors; composite materials;
Fields of Research : 09 Engineering > 0901 Aerospace Engineering > 090103 Aerospace Structures
09 Engineering > 0912 Materials Engineering > 091202 Composite and Hybrid Materials
09 Engineering > 0906 Electrical and Electronic Engineering > 090605 Photodetectors, Optical Sensors and Solar Cells
09 Engineering > 0901 Aerospace Engineering > 090102 Aerospace Materials
Socio-Economic Objective: B Economic Development > 86 Manufacturing > 8613 Transport Equipment > 861301 Aerospace Equipment
Identification Number or DOI: 10.1016/j.sna.2012.12.028
URI: http://eprints.usq.edu.au/id/eprint/23171

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