Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.695437
Title: Impact detection techniques using fibre-optic sensors for aerospace & defence
Author: John, Ryan Nichols
ISNI:       0000 0004 5989 1928
Awarding Body: Heriot-Watt University
Current Institution: Heriot-Watt University
Date of Award: 2015
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Abstract:
Impact detection techniques are developed for application in the aerospace and defence industries. Optical fibre sensors hold great promise for structural health monitoring systems and methods of interrogating fibre Bragg gratings (FBG) are investigated given the need for dynamic strain capture and multiplexed sensors. An arrayed waveguide grating based interrogator is developed. The relationships between key performance indicators, such as strain range and linearity of response, and parameters such as the FBG length and spectral width are determined. It was found that the inclusion of a semiconductor optical amplifier could increase the signal-to-noise ratio by ~300% as the system moves to its least sensitive. An alternative interrogator is investigated utilising two wave mixing in erbium-doped fibre in order to create an adaptive system insensitive to quasistatic strain and temperature drifts. Dynamic strain sensing was demonstrated at 200 Hz which remained functional while undergoing a temperature shift of 8.5 °C. In addition, software techniques are investigated for locating impact events on a curved composite structure using both time-of-flight triangulation and neural networks. A feature characteristic of composite damage creation is identified in dynamic signals captured during impact. An algorithm is developed which successfully distinguishes between signals characteristic of a non-damaging impact with those from a damaging impact with a classification accuracy of 93 – 96%. Finally, a demonstrator system is produced to exhibit some of the techniques developed in this thesis.
Supervisor: MacPherson, William Sponsor: Not available
Qualification Name: Thesis (Eng.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.695437  DOI: Not available
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