Multi-parameter fiber optic sensors based on fiber random grating

Yanping Xu; Mingjiang Zhang; Ping Lu; Stephen Mihailov; Xiaoyi Bao

doi:10.1117/12.2257795

23 April 2017 Multi-parameter fiber optic sensors based on fiber random grating

Yanping Xu, Mingjiang Zhang, Ping Lu, Stephen Mihailov, Xiaoyi Bao

Proceedings Volume 10323, 25th International Conference on Optical Fiber Sensors; 1032308 (2017) https://doi.org/10.1117/12.2257795
Event: 25th International Conference on Optical Fiber Sensors, 2017, Jeju, Korea, Republic of

Abstract

Two novel configurations of multi-parameter fiber-optic sensing systems based on the fiber random grating are reported. The fiber random grating is fabricated through femtosecond laser induced refractive index modification over a 10cm standard telecom single mode fiber. In one configuration, the reflective spectrum of the fiber random grating is directly detected and a wavelength-division spectral cross-correlation algorithm is adopted to extract the spectral shifts for simultaneous measurement of temperature, axial strain, and surrounding refractive index. In the other configuration, a random fiber ring laser is constructed by incorporating the random feedback from the random grating. Numerous polarization-dependent spectral filters are formed along the random grating and superimposed to provide multiple lasing lines with high signal-to-noise ratio up to 40dB, which enables a high-fidelity multi-parameter sensing scheme by monitoring the spectral shifts of the lasing lines. Without the need of phase mask for fabrication and with the high physical strength, the random grating based sensors are much simpler and more compact, which could be potentially an excellent alternative for liquid medical sample sensing in biomedical and biochemical applications.

Citation Download Citation

Yanping Xu, Mingjiang Zhang, Ping Lu, Stephen Mihailov, and Xiaoyi Bao "Multi-parameter fiber optic sensors based on fiber random grating", Proc. SPIE 10323, 25th International Conference on Optical Fiber Sensors, 1032308 (23 April 2017); https://doi.org/10.1117/12.2257795

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