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基于倾斜光纤布拉格光栅和表面等离子体共振的包层模拟合辅助自动折射率解调光纤传感探头

Cladding Mode Fitting-Assisted Automatic Refractive Index Demodulation Optical Fiber Sensor Probe Based on Tilted Fiber Bragg Grating and SPR.

作者信息

Lin Wenwei, Huang Weiying, Liu Yingying, Chen Xiaoyong, Qu Hang, Hu Xuehao

机构信息

Research Center for Advanced Optics and Photoelectronics, Department of Physics, College of Science, Shantou University, Shantou 515063, China.

Key Laboratory of Intelligent Manufacturing Technology of MOE, Shantou University, Shantou 515063, China.

出版信息

Sensors (Basel). 2022 Apr 15;22(8):3032. doi: 10.3390/s22083032.

DOI:10.3390/s22083032
PMID:35459016
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9032900/
Abstract

In the paper based on surface plasmon resonance (SPR) in a tilted fiber Bragg grating (TFBG), a novel algorithm is proposed, which facilitates demodulation of surrounding refractive index (SRI) via cladding mode interrogation and accelerates calibration and measurement of SRI. Refractive indices with a tiny index step of 2.2 × 10 are prepared by the dilution of glucose aqueous solution for the test and the calibration of this fiber sensor probe. To accelerate the calibration process, automatic selection of the most sensitive cladding mode is demonstrated. First, peaks of transmitted spectrum are identified and numbered. Then, sensitivities of several potentially sensitive cladding modes in amplitude adjacent to the left of the SPR area are calculated and compared. After that, we focus on the amplitudes of the cladding modes as a function of a SRI, and the highest sensitivity of -6887 dB/RIU (refractive index unit) is obtained with a scanning time of 15.77 s in the range from 1520 nm to 1620 nm. To accelerate the scanning speed of the optical spectrum analyzer (OSA), the wavelength resolution is reduced from 0.028 nm to 0.07 nm, 0.14 nm, and 0.28 nm, and consequently the scanning time is shortened to 6.31 s, 3.15 s, and 1.58 s, respectively. However, compared to 0.028 nm, the SRI sensitivity for 0.07 nm, 0.14 nm, and 0.28 nm is reduced to -5685 dB/RIU (17.5% less), -5415 dB/RIU (21.4% less), and -4359 dB/RIU (36.7% less), respectively. Thanks to the calculation of parabolic equation and weighted Gauss fitting based on the original data, the sensitivity is improved to -6332 dB/RIU and -6721 dB/RIU, respectively, for 0.07 nm, and the sensitivity is increased to -5850 dB/RIU and -6228 dB/RIU, respectively, for 0.14 nm.

摘要

在基于倾斜光纤布拉格光栅(TFBG)表面等离子体共振(SPR)的论文中,提出了一种新算法,该算法通过包层模式询问促进周围折射率(SRI)的解调,并加速SRI的校准和测量。通过稀释葡萄糖水溶液制备具有2.2×10微小折射率步长的折射率,用于该光纤传感器探头的测试和校准。为了加速校准过程,展示了自动选择最敏感包层模式的方法。首先,识别并标记透射光谱的峰值。然后,计算并比较SPR区域左侧相邻幅度处几种潜在敏感包层模式的灵敏度。之后,我们关注包层模式的幅度作为SRI的函数,在1520nm至1620nm范围内扫描时间为15.77s时,获得了-6887dB/RIU(折射率单位)的最高灵敏度。为了加速光谱分析仪(OSA)的扫描速度,将波长分辨率从0.028nm降低到0.07nm、0.14nm和0.28nm,因此扫描时间分别缩短到6.31s、3.15s和1.58s。然而,与0.028nm相比,0.07nm、0.14nm和0.28nm的SRI灵敏度分别降低到-5685dB/RIU(降低17.5%)、-5415dB/RIU(降低21.4%)和-4359dB/RIU(降低36.7%)。由于基于原始数据进行抛物线方程计算和加权高斯拟合,对于0.07nm,灵敏度分别提高到-6332dB/RIU和-6721dB/RIU,对于0.14nm,灵敏度分别提高到-5850dB/RIU和-6228dB/RIU。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/6567676f40b3/sensors-22-03032-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/0a621c208ae9/sensors-22-03032-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/8e5a96038ceb/sensors-22-03032-g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/6340ca7a6cd0/sensors-22-03032-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/782f277b46de/sensors-22-03032-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/66e09d172c81/sensors-22-03032-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/77705a45f989/sensors-22-03032-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/b2db4f4425e2/sensors-22-03032-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/87c19e2b993a/sensors-22-03032-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/3dc055a6e870/sensors-22-03032-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/5c7038e12f46/sensors-22-03032-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/6567676f40b3/sensors-22-03032-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/0a621c208ae9/sensors-22-03032-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/8e5a96038ceb/sensors-22-03032-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/e9bf5eade0d3/sensors-22-03032-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/6b990c4ef8f8/sensors-22-03032-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/6340ca7a6cd0/sensors-22-03032-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/782f277b46de/sensors-22-03032-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/66e09d172c81/sensors-22-03032-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/77705a45f989/sensors-22-03032-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/b2db4f4425e2/sensors-22-03032-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/87c19e2b993a/sensors-22-03032-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/3dc055a6e870/sensors-22-03032-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/5c7038e12f46/sensors-22-03032-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b3/9032900/6567676f40b3/sensors-22-03032-g013.jpg

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