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Feature Extraction of Brillouin Scattering Spectrum Based on Half- interval Search Frequency Sweep Method

机译:基于半间隔搜索扫频方法的布里渊散射谱特征提取

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In order to improve the real-time performance of Brillouin optical time-domain analysis (BOTDA) distributed optical fiber sensing system, this paper proposes an extraction method of Brillouin scattering spectrum based on half-interval search frequency sweep. This method shortens measurement time by reducing the frequency sweep range, and provides a simplified Brillouin gain spectrum. Cross-correlation of this spectrum with a standard Lorentz curve, then the ideal Lorentz line type near the peak of the convolution result is used for frequency shift feature extraction. And the estimated value of Brillouin frequency shift (BFS) can be calculated by the result of frequency shift feature extraction. A 15km Rayleigh BOTDA temperature sensing experiment is designed to verify the reliability of the method. The results show that this method avoids extension of measuring time caused by the complex iterative process, and reduces frequency sweep time. It has better real-time performance and measurement accuracy than traditional Lorenz curve fitting (LCF) which based on the Levenberg-Marquardt (LM) algorithm.
机译:为了提高布里渊光时域分析(BOTDA)分布式光纤传感系统的实时性能,提出了一种基于半间隔搜索扫频的布里渊散射谱提取方法。该方法通过减小扫频范围来缩短测量时间,并提供简化的布里渊增益频谱。该频谱与标准洛伦兹曲线互相关,然后将卷积结果的峰值附近的理想洛伦兹线类型用于频移特征提取。通过频移特征提取的结果可以计算出布里渊频移(BFS)的估计值。设计了一个15公里的Rayleigh BOTDA温度感测实验,以验证该方法的可靠性。结果表明,该方法避免了复杂的迭代过程导致的测量时间延长,并减少了扫频时间。与基于Levenberg-Marquardt(LM)算法的传统Lorenz曲线拟合(LCF)相比,它具有更好的实时性能和测量精度。

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