A new type of ultra-broadband microstructured fiber sensor based on surface plasmon resonance

Ding Zi-Ping; Liao Jian-Fei; Zeng Ze-Kai

doi:10.7498/aps.70.20201477

Abstract

Microstructured fiber (MF) sensors based on surface plasmon resonance (SPR) have been widely investigated because they have many merits including high sensitivity, label-free and real-time detection and so on, thus they possess extensive applications such as in food safety control, environmental monitoring, biomolecular analytes detection, antibody-antigen interaction, liquid detection and many others. However, most of reported SPR-based MF sensors can only work in the visible or near-infrared wavelength region. Hence, the investigation of high-performance mid-infrared SPR-based MF sensors is a challenge task. In this paper, with the aim of overcoming the above limitation, a new type of high-sensitivity SPR-based MF sensor coated with indium tin oxide (ITO) layer is proposed. The proposed sensor can work in both the near-infrared and mid-infrared wavelength region. Benefitting from its two-core and single analyte channel structure, our proposed sensor can effectively eliminate the interference among neighboring analyte channels, improving its signal-to-noise ratio, and achieving high-sensitivity detection in ultra-broadband wavelength range. By using the full-vector finite method with the PML boundary conditions, the sensing properties of our proposed sensor are numerically studied in detail. The numerical results show that the resonance wavelength of the proposed sensor shifts toward a long wavelength region as the refractive index of analyte increases from 1.423 to 1.513, and a similar phenomenon can be found if the thickness of the ITO layer increases from 40 nm to 60 nm. Nevertheless, the wavelength sensitivity of the proposed sensor decreases with the increase of the diameter of the hole located in the fiber core region. On the other hand, when the refractive index of analyte varies in a large range of 1.423–1.513, the proposed sensor can operate in an ultra-broad wavelength range of 1.548–2.796 μm, and the average wavelength sensitivity is as high as 13964 nm/refractive index unit (RIU). Moreover, the maximum wavelength sensitivity and refractive index resolution increase up to 17900 nm/RIU and 5.59 × 10^–7 RIU, respectively. Hence, our proposed SPR-based MF sensor can be applied to environmental monitoring, biomolecular analyte detection and chemical detection.

Keywords:

PACS:

42.81.-i	(Fiber optics)
42.81.Bm	(Fabrication, cladding, and splicing)
73.20.Mf	(Collective excitations (including excitons, polarons, plasmons and other charge-density excitations))
42.81.Pa	(Sensors, gyros)

Authors and contacts

College of Physics and Electronic Information, Gannan Normal University, Ganzhou 341000, China

Corresponding author: Liao Jian-Fei, jfliao@126.com

Funds: Project supported by the National Natural Science Foundation of China (Grant No. 61765003), the Natural Science Foundation of Jiangxi Province, China (Grant No. 20181BAB202029), and the Graduate Innovation Foundation of Gannan Normal University, China (Grant No. YCX19A043)

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1. 引　言

痕量检测是一种检测物质含量在百万分之一以下的分析检测方法, 它在安全生产、生物医学、环境检测、国防科技等众多领域都有极为重要的应用^[1-3]. 因此, 对高精度、超灵敏的痕量检测技术的研发已变得至关重要, 而基于微结构光纤(microstructured fiber, MF)表面等离子体共振(surface plasmon resonance, SPR)的传感技术, 由于其大动态测量范围、超高灵敏度及适用于各种恶劣环境等优点已成为该领域最具潜力的发展方向之一. 其基本原理是输入光在MF和金属交界面处产生的倏逝波会引发自由电子相干振荡而产生表面等离子体波. 当倏逝波与表面等离子体激元(surface plasmon polaritons, SPP)产生共振时, 能量会从光子转移到表面等离子体中, 这样等离子体波就可以吸收入射光的大部分能量, 从而导致检测到的反射光强会形成一个损耗峰值, 最后通过测量共振波长或损耗峰的位置来检测分析物质的属性. 如今, SPR-MF传感器已成为痕量检测领域内的研究热点^[4].

SPR-MF传感器最先由Hassani和Skorobogatiy在2006年提出^[5], 研究发现该传感器的波长灵敏度与折射率分辨率分别为984 nm/RIU和8 × 10^–5. 随后, 各种结构新颖性能优越的SPR-MF传感器不断被提出. 如早在2010年, Yu等^[6]提出了一种可工作在可见光区域范围内的选择性镀金属层SPR-MF传感器, 该传感器实现了高达5500 nm/RIU的波长灵敏度. 到了2013年, Shuai等^[7]提出了一种双通道近红外SPR-MF传感器. 该传感器在自参考模式下的平均灵敏度为7533 nm/RIU, 而在同时测两种待测样品模式下的最高灵敏度则高达10200 nm/RIU. 在2014年, Otupiri等^[8]提出了一种可用于可见光区域范围内的新型开槽型SPR-MF传感器, 其x偏振模和y偏振模的折射率分辨率分别为5 × 10^–5 RIU、6 × 10^–5 RIU. 2015年, Liu等^[9]提出了一种可工作在可见光区域范围内的多芯多孔银膜SPR-MF传感器. 研究表明该传感器的平均灵敏度为4500 nm/RIU. 2017年, Huang^[10]提出了一种D型近红外SPR-MF传感器. 该传感器可以实现单偏振模传感, 且其平均波长灵敏度高达6000 nm/RIU. 为了能扩大此类传感器的应用范围, Chen等^[11]在2018年设计了一种新型中红外SPR-MF传感器. 该传感器的波长灵敏度最高可达11055 nm/RIU. 到了今年, Li等^[12]提出了一种H型SPR-MF传感器, 其最大灵敏度可达12600 nm/RIU. 综上所述, 现在所报道的SPR-MF传感器通常只能工作在可见光和近红外区域, 很少能工作在中红外区域, 而同时能工作在近红外和中红外区域的SPR-MF传感器至今尚未见报.

为了进一步扩大SPR-MF传感器的应用范围, 本文提出了一种镀氧化铟锡(indium tin oxide, 记为ITO)的双芯单通道SPR-MF传感器. 利用全矢量有限元法, 系统研究了传感器结构参数和待测样品折射率对其传感特性的影响. 研究发现: 该传感器的平均灵敏度、最大灵敏度和折射率分辨率分别高达13964 nm/RIU, 17900 nm/RIU, 5.59 × 10^–7 RIU. 此外, 该传感器还可以同时工作在近红外和中红外区域.

2. 传感器结构设计

我们所设计的SPR-MF传感器的结构如图1所示. 该双芯MF包含3层按正三角形晶格排列的空气孔, 其晶格常数为Λ, 空气孔直径为d₂. 光纤的两个纤芯位于第2层空气孔的相应位置, 并分别标记为1和2. 为了能够更好地调节纤芯基模的模有效折射率, 使传感器能够在更宽的波长范围内进行工作, 我们在纤芯的中心区域引入了2个填充待测样品的小孔, 其直径为d₃. 此外, 为了提高传感器的信噪比和消除样品通道间的串扰, 该光纤的中心区域只有1个直径为d₁, 内表面镀ITO(厚度为t)的大圆形空气孔用来作为待测样品的传感通道. n_a为待测样品的折射率, 其值在1.423—1.513之间; 空气的折射率为1. 光纤的衬底材料为SiO₂, 其折射率由Sellmeier方程计算可得^[13]:

$图 1 SPR-MF传感器的横截面示意图\r\nFig. 1. Cross section of the proposed multi-core PCF sensor based on SPR.$

图 1 SPR-MF传感器的横截面示意图

Fig. 1. Cross section of the proposed multi-core PCF sensor based on SPR.

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$\begin{split} {n}^{2}\left(\lambda \right)=\;&1+\frac{0.6961663{\lambda }^{2}}{{\lambda }^{2}-{\left(0.0684043\right)}^{2}}+\frac{0.4079426{\lambda }^{2}}{{\lambda }^{2}-{\left(0.1162414\right)}^{2}}\\ &+\frac{0.8974794{\lambda }^{2}}{{\lambda }^{2}-{\left(9.896161\right)}^{2}}, \\[-15pt] \end{split}$

(1)

其中: λ为入射光波长. ITO作为等离子体材料, 其相对介电常数ε可以由Drude模型计算获得^[14]:

$\varepsilon ={\varepsilon }_{\infty }- {{{\omega }_{\mathrm{p}}}^{2}}/({{\omega }^{2}+\mathrm{i}\omega \varGamma }),$

(2)

${{\omega }_{\mathrm{p}}}^{2}= {n{e}^{2}}/({{\varepsilon }_{\infty }{m}^{*}}),$

(3)

其中: ε_∞ = 3.9; ω_p为等离子体频率; ω为角频率; Г为电子散射率, Г = 1.8 × 10¹⁴ rad/s; m*为电子的有效质量, m* = 0.35m₀, m₀ = 9.1 × 10^–31 kg为电子质量; n为ITO的载流子浓度, n = 1.8 × 10²¹ cm^–3; e为电子电荷.

3. 仿真结果与讨论

利用全矢量有限元法^[15], 我们首先研究了双芯SPR-MF传感器的模式共振特性, 研究发现X偏振基模无法有效的与SPP模进行耦合共振. 基于此, 本文只研究Y偏振基模与SPP模之间的共振特性, 具体研究结果由图2给出. 其中传感器的损耗 $\alpha$ 计算表达式为^[16]:

$图 2 (a) Y偏振模与SPP模的色散曲线; (b) Y偏振模与SPP模的损耗曲线\r\nFig. 2. (a) The dispersion curve of Y-polarized mode and SPP mode; (b) the loss curve of Y-polarized mode and SPP mode.$

图 2 (a) Y偏振模与SPP模的色散曲线; (b) Y偏振模与SPP模的损耗曲线

Fig. 2. (a) The dispersion curve of Y-polarized mode and SPP mode; (b) the loss curve of Y-polarized mode and SPP mode.

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$\mathrm{\alpha }\left(\mathrm{d}\mathrm{B}/\mathrm{c}\mathrm{m}\right)=8.686\times (2\mathrm{\pi }/\lambda )\mathrm{I}\mathrm{m}\left({n}_{\mathrm{e}\mathrm{f}\mathrm{f}}\right)\times {10}^{4},$

(4)

其中, $\mathrm{I}\mathrm{m}\left({n}_{\mathrm{e}\mathrm{f}\mathrm{f}}\right)$ 为模有效折射率的虚部. 光纤的结构参数为: Λ = 2 μm, d₁ = 2 μm, d₂ = 1 μm, d₃ = 0.5 μm, t = 50 nm, n_a = 1.423. 从图2(a)中可以看出: 在短波长处, SPP模的模有效折射率实部比Y偏振模的要大, 但随着波长的增大, 两模的模有效折射率都会逐渐减小, 并且它们之间的差值也在逐渐减小. 当波长增大到1.548 μm时, SPP模和Y偏振模的模有效折射率相等, 即满足了两模的耦合共振条件. 从该图中的电场分布插图可以清晰的看出SPP模和Y偏振模之间的耦合共振特性. 如在波长1.46 μm处, 由于不满足耦合共振条件, SPP模和Y偏振模的能量分别被限制在芯区和金属层表面. 然而, 随着波长的增大, Y偏振模的能量会逐渐耦合到SPP模中, 并在波长1.548 μm处, 两模实现耦合共振, 此时两模的能量分布几乎一样. 当波长进一步增大到1.66 μm时, Y偏振模的能量又会因为不满足耦合条件而返回纤芯区域. 图2(b)给出了SPP模和Y偏振模的损耗特性. 从此图可以看出: 在整个仿真波长范围内, SPP模的损耗先减小后增大, 而Y偏振模的损耗却先增大后减小, 并且在共振波长1.548 μm处, 两模的损耗会相等, 这也就意味着我们所设计的传感器能满足损耗匹配条件, 实现完全耦合, 使SPP模和Y偏振模之间的耦合达到最佳状态. 此外, 除了耦合共振点, SPP模的损耗都要大于Y偏振模的损耗.

接下来我们研究了待测样品折射率n_a对传感器共振特性的影响, 其仿真结果如图3所示. 光纤的其他结构参数为: Λ = 2 μm, d₁ = 2 μm, d₂ = 1 μm, d₃ = 0.5 μm, t = 50 nm. 从图3(a)可以看出: 当n_a从1.423增大到1.513时, 其耦合波长会产生红移, 对应的共振波长从1.548 μm增加到2.796 μm. 其主要原因是SPP模的模有效折射率会随着n_a的增大而增大, 而Y偏振模的基本不变, 从而导致两模式之间的耦合共振波长产生红移. 此外, 传感器的损耗峰值会随着n_a的增大而减小. 其原因是当n_a增大时, SPP模与Y偏振模之间的能量耦合减弱, 使从Y偏振模转移至SPP模的能量减小, 进而导致Y偏振模的损耗变小. 图3(b)为共振波长与n_a的线性拟合曲线, 其拟合方程为: $\lambda \left({{\text {μ}} }\mathrm{m}\right)=13.964{n}_{\mathrm{a}}-18.384$ . 该方程的斜率就是传感器在该探测范围内的平均灵敏度, 所以其平均灵敏度为13964 nm/RIU. 为了能够更好的研究传感器的灵敏度, 我们还计算了单个波长灵敏度 ${S}_{\lambda }$ . 其计算公式如下^[17,18]:

$图 3 当na从1.423增加到1.513时,　(a) Y偏振模的损耗曲线和共振波长与(b)na的线性拟合曲线\r\nFig. 3. (a) Loss curve of Y-polarized mode and (b) linear fitting line of the resonance wavelength versus na by changing na from 1.423 to 1.523.$

图 3 当n_a从1.423增加到1.513时,　(a) Y偏振模的损耗曲线和共振波长与(b)n_a的线性拟合曲线

Fig. 3. (a) Loss curve of Y-polarized mode and (b) linear fitting line of the resonance wavelength versus n_a by changing n_a from 1.423 to 1.523.

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${S}_{\lambda }\left(\mathrm{n}\mathrm{m}/\mathrm{R}\mathrm{I}\mathrm{U}\right)=\Delta {\lambda }_{\mathrm{p}\mathrm{e}\mathrm{a}\mathrm{k}}\left({n}_{\mathrm{a}}\right)/\Delta {n}_{\mathrm{a}},$

(5)

式中, Δλ_peak为共振波长的变化量, Δn_a为n_a的变化量. 从图3(b)可以看出: 当n_a = 1.503时, 其共振波长为2.617 μm, 而当n_a增大到1.513时, 共振波长变为2.796 μm, 通过(5)式计算可得此时传感器的最大灵敏度为17900 nm/RIU. 该灵敏度远大于其他多芯SPR-MF传感器^[19-21]. 若探测器的波长分辨率为0.01 nm时, 则传感器的折射率分辨率高达5.59 × 10^–7.

最后, 为了进一步分析光纤结构参数对传感器传感性能的影响, 我们重点研究了金属膜厚度t和填充样品小孔直径d₃对传感器损耗特性及波长灵敏度的影响.

图4为不同金属膜厚度下传感器的Y偏振模损耗曲线. 光纤的其他结构参数为: Λ = 2 μm, d₁ = 2 μm, d₂ = 1 μm, d₃ = 0.5 μm, n_a = 1.423. 由此图可以发现: 随着镀膜厚度的增加, 传感器的共振波长向长波长方向移动. 如当ITO的厚度分别为40 nm, 45, 50, 55, 60 nm时, 传感器所对应的共振波长分别为1.423, 1.493, 1.548, 1.599, 1.645 μm. 类似的现象也可以从其他SPR-MF传感器中看到^[22,23]. 其原因是ITO厚度的增大使得SPP模的模有效折射率也增大, 而Y偏振模的模有效折射率却几乎不受影响, 进而导致共振波长发生红移. 此外, 当ITO的厚度从40 nm增大到60 nm时, Y偏振基模的损耗峰值几乎没有变化. 因此, 我们可以通过合理调节ITO的厚度来提高传感器的传感性能.

$图 4 ITO厚度对Y偏振模损耗的影响\r\nFig. 4. Influence of the thickness of ITO film on the loss of Y-polarized mode.$

图 4 ITO厚度对Y偏振模损耗的影响

Fig. 4. Influence of the thickness of ITO film on the loss of Y-polarized mode.

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图5为d₃对Y偏振模损耗的影响. 光纤的其他结构参数为: Λ = 2 μm, d₁ = 2 μm, d₂ = 1 μm, t = 50 nm, n_a = 1.423. 从此图可以看出: 随着小孔直径的变大, Y偏振模的共振波长向长波长移动, 但损耗峰值基本不变. 如当d₃分别为0.3, 0.4, 0.5, 0.6, 0.7 μm时, 传感器所对应的共振波长分别为1.538, 1.542, 1.548, 1.555, 1.563 μm. 这是因为小孔直径的增大只会影响Y偏振基模的模有效折射率, 使其模有效折射率减小, 进而导致耦合波长产生红移.

$图 5 d3对Y偏振模损耗的影响\r\nFig. 5. The influence of d3 on the loss of Y-polarized model.$

图 5 d₃对Y偏振模损耗的影响

Fig. 5. The influence of d₃ on the loss of Y-polarized model.

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为了更好的分析光纤结构参数对传感器传感性能的影响, 我们还研究了t和d₃对传感器灵敏度的影响. 图6(a)给出了t对传感器灵敏度的影响. 光纤的其他结构参数为: Λ = 2 μm, d₁ = 2 μm, d₂ = 1 μm, d₃ = 0.5 μm. 从图6(a)可以发现: 当ITO厚度从40 nm增大到50 nm时, 传感器的波长灵敏度保持不变. 这是因为当ITO厚度在40—50 nm之间变化时, SPP模与Y偏振模之间的耦合效率并不会受其影响^[16]. 然而, 当ITO厚度从50 nm增大到60 nm时, 对应的波长灵敏度会随之从9200 nm/RIU减小到9000 nm/RIU. 这也就意味着SPP模和Y偏振模之间的耦合效率变差了. 从图6(b)中可以看出: 当小孔直径d₃从0.3 μm增大到0.7 μm时, 传感器的灵敏度直接从9600 nm/RIU减小到8600 nm/RIU. 这说明SPP模与Y偏振模之间的耦合效率会随着d₃的增大而减小. 此时光纤的其他结构参数为: Λ = 2 μm, d₁ = 2 μm, d₂ = 1 μm, t = 50 nm.

$图 6 当na由1.423增大到1.433时, 结构参数t和d3对波长灵敏度的影响　(a)结构参数t; (b) d3\r\nFig. 6. The influence of fiber parameters t and d3 on the wavelength sensitivity with na increasing from 1.423 to 1.433: (a) Fiber parameters t; (b) d3.$

图 6 当n_a由1.423增大到1.433时, 结构参数t和d₃对波长灵敏度的影响　(a)结构参数t; (b) d₃

Fig. 6. The influence of fiber parameters t and d₃ on the wavelength sensitivity with n_a increasing from 1.423 to 1.433: (a) Fiber parameters t; (b) d₃.

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4. 结　论

利用MF的多孔结构, 设计了一种可工作在近红外和中红外区域的新型SPR-MF传感器. 采用全矢量有限元法对其传感性能进行了系统的研究, 研究发现: 该传感器只能实现Y偏振模与SPP模之间的耦合共振, 且当待测样品折射率处于1.423—1.513范围内时, 传感器的平均灵敏度、最大灵敏度和折射率分辨率分别高达13964 nm/RIU, 17900 nm/RIU, 5.59 × 10^–7 RIU. 因此, 我们所设计的SPR-MF传感器在安全生产、药物筛选、环境检测等领域都有广泛的应用前景.

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[12]	Li T, Zhu L, Yang X, Lou X, Yu L 2020 Sensor 20 741 Google Scholar
[13]	Rifat A A, Mahdiraji G A, Shee Y G, Shawon M J, Adikan F R M 2016 Procedia Eng. 140 1 Google Scholar
[14]	Yang Z, Xia L, Li C, Chen X, Liu D, 2019 Opt. Commun. 430 195 Google Scholar
[15]	Petracek J, Selleri S 2001 Opt. Quant. Electron. 33 373 Google Scholar
[16]	Zhang Z, Li S, Liu Q, Feng X, Zhang S, Wang Y, Wu J 2018 Opt. Fiber Technol. 43 45 Google Scholar
[17]	Haque E, Hossain M A, Ahmed F, Namihira Y 2018 IEEE Sens. J. 18 8287 Google Scholar
[18]	An G, Li S, Yan X, Zhang X, Yuan Z, Wang H, Zhang Y, Hao X, Shao Y, Han Z 2017 Plasmonics 12 465 Google Scholar
[19]	Rifat A A, Mahdiraji G A, Chow D M, Shee Y G, Ahmed R, Adikan F R M 2015 Sensor 15 11499 Google Scholar
[20]	Tong K, Wang F, Wang M, Dang P, Wang Y 2018 Opt. Fiber Technol. 46 306 Google Scholar
[21]	Shuai B, Xia L, Zhang Y, Liu D 2012 Opt. Express 20 5974 Google Scholar
[22]	Rahman M M, Molla M A, Paul A K, Based M A, Rana M M, Anower M S 2020 Results Phys. 18 103313 Google Scholar
[23]	Abdullah H, Ahmed K, Mitu S A 2020 Results Phys. 17 103151 Google Scholar

Cited By

期刊类型引用(5)

1.	戴峻峰，付丽辉. 群智能优化的动态基线调整在光纤SPR传感器信号处理中的应用. 传感技术学报. 2023(07): 1092-1102 . 百度学术
2.	李建，高云. 基于阶跃函数的光纤传感器超差校准方法仿真. 计算机仿真. 2023(10): 307-311 . 百度学术
3.	李焕贞，皮珣珣. 基于多智能体的光传感器故障诊断系统. 激光杂志. 2023(12): 240-245 . 百度学术
4.	张瑾，常敏，陈楠，刘学静，章曦，杜嘉，丁鑫. 基于D型双芯PCF的近红外宽检测范围SPR折射率传感器. 光学技术. 2022(01): 109-115 . 百度学术
5.	王飞. 基于光纤传感技术的智能矿山无人化巡检系统研究. 煤炭科学技术. 2021(S2): 263-267 . 百度学术

其他类型引用(2)

图 1 SPR-MF传感器的横截面示意图

Figure 1. Cross section of the proposed multi-core PCF sensor based on SPR.

DownLoad: Full-Size Img PowerPoint

图 2 (a) Y偏振模与SPP模的色散曲线; (b) Y偏振模与SPP模的损耗曲线

Figure 2. (a) The dispersion curve of Y-polarized mode and SPP mode; (b) the loss curve of Y-polarized mode and SPP mode.

DownLoad: Full-Size Img PowerPoint

图 3 当n_a从1.423增加到1.513时,　(a) Y偏振模的损耗曲线和共振波长与(b)n_a的线性拟合曲线

Figure 3. (a) Loss curve of Y-polarized mode and (b) linear fitting line of the resonance wavelength versus n_a by changing n_a from 1.423 to 1.523.

DownLoad: Full-Size Img PowerPoint

图 4 ITO厚度对Y偏振模损耗的影响

Figure 4. Influence of the thickness of ITO film on the loss of Y-polarized mode.

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图 5 d₃对Y偏振模损耗的影响

Figure 5. The influence of d₃ on the loss of Y-polarized model.

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图 6 当n_a由1.423增大到1.433时, 结构参数t和d₃对波长灵敏度的影响　(a)结构参数t; (b) d₃

Figure 6. The influence of fiber parameters t and d₃ on the wavelength sensitivity with n_a increasing from 1.423 to 1.433: (a) Fiber parameters t; (b) d₃.

DownLoad: Full-Size Img PowerPoint

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[12]	Li T, Zhu L, Yang X, Lou X, Yu L 2020 Sensor 20 741 Google Scholar
[13]	Rifat A A, Mahdiraji G A, Shee Y G, Shawon M J, Adikan F R M 2016 Procedia Eng. 140 1 Google Scholar
[14]	Yang Z, Xia L, Li C, Chen X, Liu D, 2019 Opt. Commun. 430 195 Google Scholar
[15]	Petracek J, Selleri S 2001 Opt. Quant. Electron. 33 373 Google Scholar
[16]	Zhang Z, Li S, Liu Q, Feng X, Zhang S, Wang Y, Wu J 2018 Opt. Fiber Technol. 43 45 Google Scholar
[17]	Haque E, Hossain M A, Ahmed F, Namihira Y 2018 IEEE Sens. J. 18 8287 Google Scholar
[18]	An G, Li S, Yan X, Zhang X, Yuan Z, Wang H, Zhang Y, Hao X, Shao Y, Han Z 2017 Plasmonics 12 465 Google Scholar
[19]	Rifat A A, Mahdiraji G A, Chow D M, Shee Y G, Ahmed R, Adikan F R M 2015 Sensor 15 11499 Google Scholar
[20]	Tong K, Wang F, Wang M, Dang P, Wang Y 2018 Opt. Fiber Technol. 46 306 Google Scholar
[21]	Shuai B, Xia L, Zhang Y, Liu D 2012 Opt. Express 20 5974 Google Scholar
[22]	Rahman M M, Molla M A, Paul A K, Based M A, Rana M M, Anower M S 2020 Results Phys. 18 103313 Google Scholar
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期刊类型引用(5)

1.	戴峻峰，付丽辉. 群智能优化的动态基线调整在光纤SPR传感器信号处理中的应用. 传感技术学报. 2023(07): 1092-1102 . 百度学术
2.	李建，高云. 基于阶跃函数的光纤传感器超差校准方法仿真. 计算机仿真. 2023(10): 307-311 . 百度学术
3.	李焕贞，皮珣珣. 基于多智能体的光传感器故障诊断系统. 激光杂志. 2023(12): 240-245 . 百度学术
4.	张瑾，常敏，陈楠，刘学静，章曦，杜嘉，丁鑫. 基于D型双芯PCF的近红外宽检测范围SPR折射率传感器. 光学技术. 2022(01): 109-115 . 百度学术
5.	王飞. 基于光纤传感技术的智能矿山无人化巡检系统研究. 煤炭科学技术. 2021(S2): 263-267 . 百度学术

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