基于光谱奇偶函数分解的光纤布拉格光栅峰值检测

Peak Detection of Fiber Bragg Grating Spectra Using Even-Odd Function for Spectral Decomposition

提出一种采用光谱奇偶函数分解的光纤布拉格光栅(FBG)光谱峰值检测算法,并进行了实验验证。FBG光谱是波长λ和光强P(λ)的函数,沿λ轴逐点移动光谱,使光谱与P(λ)轴相交;并将每个移动点下光谱分解的奇函数的最大值作为特征值。上述特征值的最小值所对应的λ即为FBG光谱的中心波长。采用非对称高斯函数叠加高斯白噪声建立FBG光谱理论模型;对FBG传感器依次施加线性递增的轴向拉力。然后使用所提算法计算理论模型和实验FBG光谱的中心波长,结果表明,与传统算法相比,该算法能够更快、更准确地检测出FBG光谱的中心波长。

In this study, a peak detection algorithm based on an even-odd function to decompose fiber Bragg grating(FBG) spectra is proposed and experimentally demonstrated. An FBG spectrum is a function of wavelength λ and light intensity P(λ), which is moved along the λ axis point-by-point and intersected with the P(λ) axis. The maximum value of the odd function used for the FBG spectral decomposition under each moving point is defined as a characteristic value. The λ value corresponding to the minimum characteristic value is used as the central wavelength of the FBG spectrum. A theoretical model of the FBG spectrum is established using an asymmetric Gaussian model and additive white Gaussian noise superposition. Linearly increasing axial strain is imposed on an FBG sensor in turn. The central wavelengths of the theoretical model and experimental FBG spectra are calculated using the proposed algorithm. The results show that using proposed algorithm, the central wavelength of the FBG spectrum can be obtained more quickly and accurately than conventional algorithms.