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Free Spectral Range Matched Interrogation Technique for Wavelength Demodulation of Fiber Bragg Grating Sensors

Free Spectral Range Matched Interrogation (FSRMI) technique for wavelength demodulation of fiber Bragg grating sensors.
We designed and tested a new wavelength demodulation system based on free-spectral-range-matched interrogation which employs a tunable fiber Fabry-Perot interferometer (FPI) and a multi-channel bandpass filter. This technique was deployed to test fiber Bragg gratings (FBG), long period gratings (LPG) and tilted fiber Bragg gratings (TFBG).
In the experimental setup, a broadband source launches light into a fiber Bragg grating under test and the reflection/transmission spectrum is fed into a tunable FPI. By tuning an external bias applied to the FPI, the transmission spectrum of FPI scans over a wavelength range. The input optical signal is therefore selectively passed through the FPI and then fed into a four-channel bandpass filter followed by four photodetectors. The optical signal is converted to electrical signal by the photodiodes and is acquired by a data acquisition system. Since a bandpass filter with four channels are used in this interrogation system it can scan four distinguished wavelength ranges simultaneously and thus the scan rate is four time faster.
We used this setup for doing some temperature and strain sensitivity measurements on some fiber gratings. Strain sensitivity measurements were done on FBG, TFBG and LPG and temperature sensitivity measurements were performed on TFBG. The strain and temperature sensitivity coefficients of these fiber Bragg grating sensors were obtained from experimental data. Our results show the potential of the integration of the FSRMI system with fiber Bragg gratings for temperature and strain multiple-sensor arrays with high sampling speed and high accuracy.

Identiferoai:union.ndltd.org:WATERLOO/oai:uwspace.uwaterloo.ca:10012/4232
Date20 January 2009
CreatorsRahimi, Somayyeh
Source SetsUniversity of Waterloo Electronic Theses Repository
LanguageEnglish
Detected LanguageEnglish
TypeThesis or Dissertation

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