Analysis of Crosstalk in Fiber Grating Sensor Array Caused by Fiber-End Reflection

Zili, 张自丽 Zhang; Xiaojun, 陈小军 Chen; Bo, 叶博 Ye; Huiliang, 葛辉良 Ge

doi:10.3788/lop53.120604

Cited by 1 publication

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“…When noise from the fiber-end reflection overlaps the sensing signal, the peak wavelength of the ultra-weak FBG cannot be demodulated correctly. Some studies have also shown that additional noises caused by the interaction of fiberend reflection and multiple crosstalk can reduce the peaking wavelength accuracy of ultra-weak FBGs and even lead to a misjudgment of the number of ultra-weak FBGs [10]. Hence, reducing the reflectivity of the fiber-end surface and increasing the return loss (RL) for fiber-end reflection are effective methods to reduce noise in ultra-weak FBG arrays.…”

Section: Introductionmentioning

confidence: 99%

Fiber-end antireflection method for ultra-weak fiber Bragg grating sensing systems

Zhi-Quan

Zhang

Cheng

et al. 2021

Meas. Sci. Technol.

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A novel fiber-end antireflection method for reducing the reflection noise in ultra-weak fiber Bragg grating (FBG) sensing systems is proposed in this study. The principle of fiber-end antireflection is analyzed and simulated theoretically, and then an antireflection structure is designed and fabricated. In this method, the fiber end is cut into an inclined surface and covered directly with an ellipsoid photosensitive ultraviolet (UV) glue drop, whose refractive index is similar to that of the fiber core. Under the online monitoring of the fiber-end reflection with the ultra-weak FBG interrogator, the refractive index of the glue drop is adjusted by controlling the UV curing time to achieve optimal reflection suppression. Results show that this method can reduce fiber-end reflection to less than −60 dB and effectively eliminate the influence of fiber-end reflection noise on the last sensor. The proposed method thus provides an excellent solution for the fiber-end processing of ultra-weak FBG sensing systems.

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Section: Introductionmentioning

confidence: 99%