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改进剥层法实现FBG非均匀应变传感解调
引用本文:沈小燕,张良岳,孙杰,胡佳成,李东升. 改进剥层法实现FBG非均匀应变传感解调[J]. 红外与激光工程, 2015, 44(12): 3734-3739
作者姓名:沈小燕  张良岳  孙杰  胡佳成  李东升
作者单位:1.中国计量学院 计量测试工程学院,浙江 杭州 310018
基金项目:国家自然科学基金(61205082);浙江省自然科学基金(LQ14F050004)
摘    要:剥层法是重构光纤Bragg光栅(FBG)参数的常用方法,利用剥层法可以解调FBG非均匀应变。常规剥层法获得的FBG复耦合系数存在误差,为提高非均匀应变解调精度,提出基于剥层法的复耦合系数幅值修正改进方法。新方法在剥层求解当前层复耦合系数后,保留耦合系数相位,对耦合系数幅值进行修正,构成新的复耦合系数用于下一层反射谱的剥层求解。给出了改进算法求解非均匀应变的详细步骤和过程,并进行了仿真实验研究。利用传输矩阵法模拟仿真无应变、应变线性增大、应变线性减小以及二次曲线应变下的FBG反射谱,分别使用常规方法和改进的方法对各反射谱进行应变解调。结果表明:改进的方法获得的应变结果与理论应变有更高的一致性;不同理论应变下,改进的方法获得应变最大误差均值约为原始方法的1/5,均方根误差的均值约为原始方法的1/7,改进的方法解调误差远小于原始方法。

关 键 词:非均匀应变检测   复耦合系数修正   剥层法   光纤Bragg光栅
收稿时间:2015-04-11

Improved layer peeling algorithm to realize FBG non-uniform strain sense demodulation
Affiliation:1.College of Metrology & Measurement Engineering,China Jiliang University,Hangzhou 310018,China
Abstract:Layer peeling algorithm is a common method of fiber Bragg grating(FBG) parameter reconstruction, which can be used to demodulate the inhomogeneous strain applying on FBG. The study found that conventional layer peeling algorithm cannot figure out the exact value of complex coupling coefficient, to increase the non-uniform strain demodulation precision, a improved layer peeling algorithm called complex coupling coefficient amplitude correction method was proposed. The improved method retained the phase of coupling coefficient, corrected the amplitude of coupling coefficient, and used the modified complex coupling coefficient on layer peeling calculation of the reflection spectrum. The following 4 reflection spectrums of FBG were obtained by the transfer matrix simulating method: without strain, strain increasing linearly, strain decreasing linearly and strain of quadratic curve, the strain results were calculated by both the conventional method and the improved method. The experiment shows that the strain results of the improved method are consistent with the input strain; With different theoretical strains, mean of the largest error of improved method is about 1/5 of conventional method, the mean of root mean square error is about 1/7 of the conventional one, the error is obviously much smaller.
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