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微弯型光纤传感报警器的原理结构如图1所示。当光纤发生弯曲时,由于其全反射条件被破坏,纤芯中传播的某些模式光束进入包层,造成光纤中的能量损耗,光功率减小,阻值增大,此时电路1中电流减小,电磁继电器磁力减小,引发衔铁回弹,电路2接通触发报警器报警。
近似将光纤看成是正旋微弯,其弯曲函数[14]为:
$$ f(z) = \left\{ \begin{gathered} A\sin \omega \cdot Z\quad (0 \leqslant Z \leqslant L) \\ 0\quad \quad \quad \quad (Z \lt 0,Z \gt L) \end{gathered} \right. $$ (1) 光纤由于弯曲产生的光能损耗系数为:
$$ \begin{gathered} \alpha = \frac{{{A^2}L}}{4}\left\{ { \frac{{\sin [(\omega - {\omega _c})L/2]}}{{(\omega - {\omega _c})L/2}}+\frac{{\sin [(\omega + {\omega _c})L/2]}}{{(\omega + {\omega _c})L/2}}} \right\} \end{gathered} $$ (2) 式中:
$ {\omega _c} $ 称为谐振频率。$$ {\omega _c} = \frac{{2\pi }}{{{A_c}}} = \beta - \beta ' = \Delta \beta $$ (3) 式中:Ac为谐振波长;β和β ′为纤芯中两个模式的传播常数。当ω=ωc时,这两个模式的光功率耦合特别紧,因而损耗也增大[15]。如果选择相邻的两个模式,对光纤折射率为平方律分布的多模光纤可得:
$$ \Delta \beta = \sqrt {2\mathit\Delta } /r $$ (4) 式中:r为光纤半径;Δ为纤芯与包层之间的相对折射率差。由公式(3)和(4)可得:
$$ {A_c} = 2{\text{π}} r/\sqrt {2\mathit\Delta } $$ (5) -
微弯测试光路如图3所示,包含四个部分:光源(功率2.5 mW,波长650 nm)、功率计、微弯光纤(光纤纤芯9.0 μm)、微弯光纤架。两光纤端头分别接光源和功率计,光源电流67.5 mA,功率计档位调制20.0 mW。将85 mm的光纤固定在微弯光纤架上,固定好之后光纤可以自由活动。实验中观察功率计示数和纵向丝杆的读数,从而获得不同入侵程度的响应。
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光纤弯曲功率随位移变化关系如图4所示,当光纤没有发生弯曲时输出功率为1.0 mW。随着光纤弯曲程度加大,光功率变化趋势明显。
从图4可以看出,在位移调制范围0~3 mm内,光纤微弯的损耗基本呈线性规律, 由于实验误差也会存在个别测试点位偏离的现象。 实现了对光功率的线性调制,进而即可达到智能化入侵报警、系统联动等功能。依据实验数据进行曲线拟合,可得拟合方程为:
$$ {y} = 1.006\;1x + 0.005\;6 $$ (6) 式中:x为位移;y为光功率。 由实验结果可知采用光纤微弯传感方式可以制作高灵敏报警系统,实验结果满足设计要求。
对于非线性区域部分,可以采用建立校样数据表的方式,因为当位移量超过0.5 mm时就属于较大唯一偏差的状态,这时的系统响应明显,所以不需要通过写入细致变化量进行分析,从而采用阈值判断方式时效性更好。
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为了对比采用滤波前后的回波信号,分析算法对非信号频率噪声的抑制能力,给出了原始信号在干扰抑制算法解调前后的波形,如图5所示。
由图5(a)和(b)对比可知,经过滤波后,在有效信号窗以外的噪声被大幅抑制,信号变得清晰可见,同时,信号振幅基本没有太大的衰减。其中振幅最大值为63.4,最小值为−47.3,主波脉宽约42.2 ms,主次峰间距56.1 ms。由此可见,该干扰抑制算法具有很好的噪声抑制能力。
虽然大幅噪声可以通过频率窗进行抑制,但是滤波后仍会存在一些小幅的噪声,分析认为由于噪声频率是分布于所有频段上的,所以采用频率窗滤波同样会有部分噪声保留,但是这个噪声并不影响系统获取信号,因为该噪声振幅相比信号小很多,可以通过阈值滤波的方式消除。
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为了提高预警准确度,首先需要对干扰项进行分析,入侵测试中最容易产生误判的四种情况是:(1)情况a,附近存在施工机械,机械对地面有敲击、挖掘等动作,从而使光纤传感网络产生振动,实验采用5 m远位置;(2)情况b,人员经过警戒区域附近,虽没有进入预警区域,但振动幅度导致系统响应,实验采用2 m远位置;(3)情况c,有车辆从预警区域外围附近经过,实验采用5 m远位置;(4)情况d,有小动物进入预警区域,结果如图6所示。
由图6(a)可知,虽然响应信号明显,但相比人入侵的波形图5(b)而言,其波形结构为一个频率较大的主波构成,主峰脉宽21.3 ms,基本没有连续的旁瓣波;由图6(b)看出,其波形分布也是明显具有旁瓣波,与人入侵的波形分布非常相似,但是其振幅均值明显偏小,振幅最大值为38.9,最小值为−28.7,在数据分析过程中只需要采用阈值滤波的方式就能排除该种误识别的情况(振幅是探测信号和本振信号的比值与标定系数的乘积,通过比例值抑制绝对值分析时粗大噪声对真实信号的影响。由图6(c)可见,虽然响应信号较大,超过测试阈值,但是高于阈值信号的信号时长远大于人入侵条件下的时长,持续时长148 ms,由此采用阈值时间作为分离依据的方式就能够将其排除;由图6(d),无论振幅强度和分布特性均与人入侵有所不同,采用振幅阈值和时间阈值均能够有效抑制该类噪声。综上所述,采用该系统可以快速有效地对入侵状态进行判断与识别,从而做出正确的预警。
Design and development of an intelligent security alarm system based on optical fiber sensing
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摘要: 针对现有安防传感系统高能耗、易受电磁干扰、成本高和铺设困难等缺陷,提出了一种低能耗、高灵敏度、不受电磁干扰的智能光纤传感安防报警系统。系统传感器采用微弯型阶跃光纤结构,在分析微弯光纤传感器光能损耗与谐振频率相对折射率差函数关系的基础上,优化了传感单元的结构参数。实验首先对干扰抑制算法进行测试,从波形分布看出,采用本算法后噪声得到了大幅抑制。在此基础上,又采用系统对不同伪目标干扰进行了测试。选用功率为2.5 mW的650.0 nm激光器、光纤功率计、微弯光纤架和纤芯9 μm的微弯光纤传感器搭建了光纤微弯传感实验,对4种不同安防状态的光电响应特征进行了分析。结果表明,针对不同干扰类型只要采用相应的信号分析手段就能有效降低系统误识别的概率。由此可见,光纤微弯传感系统具有高灵敏、低能耗、抗干扰等优势,满足设计要求,在智能安防领域具有很好的应用前景。Abstract: Aiming at the defects of high energy consumption, susceptibility to electromagnetic interference, high cost and difficulty in laying of existing security sensor systems, a smart optical fiber sensor security alarm system with low energy consumption, high sensitivity and no electromagnetic interference is proposed. The system sensor adopts a microbent-type step fiber structure. Based on the analysis of the relationship between the optical energy loss of the microbent fiber sensor and the relative refractive index difference function of the resonant frequency, the structural parameters of the sensing unit are optimized. The experiment first tested the interference suppression algorithm. From the waveform distribution, it can be seen that the noise is greatly suppressed after using this algorithm. On this basis, the system was used to test the interference of different pseudotargets. A 650.0 nm laser with a power of 2.5 mW, a fiber power meter, a microbend fiber holder and a microbend fiber sensor with a core of 9 μm were selected to build a fiber microbend sensing experiment, and the photoelectric response characteristics of 4 different security states were determined. analyse. The results show that as long as the corresponding signal analysis methods are adopted for different interference types, the probability of system misrecognition can be effectively reduced. It can be seen that the optical fiber microbend sensing system has the advantages of high sensitivity, low energy consumption, anti-interference, etc., and meets the design requirements. It has good application prospects in the field of intelligent security.
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