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Application of the joint algorithm of smooth pseudo Wigner-Ville distribution and four-parameter particle swarm optimization to BOTDR
Results in Physics ( IF 5.3 ) Pub Date : 2021-04-28 , DOI: 10.1016/j.rinp.2021.104215
Xuan Li , Lixia Xi , Yang'an Zhang , Xueguang Yuan , Xiaoguang Zhang

Short-time Fourier transform is utilized for the data processing of traditional point-frequency Brillouin optical time-domain reflectometry (BOTDR). This method can improve the measurement speed, but theoretically there is a contradiction between spatial resolution and frequency resolution. To avoid this contradiction, a joint algorithm of smooth pseudo Wigner-Ville distribution (SPWVD) and four-parameter particle swarm optimization (four-parameter PSO) algorithm is proposed to improve spatial resolution, frequency resolution and frequency shift extraction accuracy of Brillouin scattering spectrum. SPWVD can smooth the signal to enhance the frequency resolution by adding a sliding window on time and frequency domain simultaneously when making the quadratic time-frequency transforming. To further improve the fit and the extraction accuracy of the frequency shift, the Brillouin scattering spectra (BSS) processed by SPWVD are fitted to find the Brillouin frequency shift (BFS) using a four-parameter PSO algorithm that takes the gain, BFS, full width at half maximum of the BSS, and linear weight coefficients of Lorentz and Gaussian lines as unknown parameters. According to the experimental results, the BOTDR using SPWVD and four-parameter PSO joint algorithm will cost less operation time since it can get better results with fewer accumulations and it does not need to find proper initial values before curve-fitting operation. Meanwhile, the joint algorithm can improve the spatial resolution and frequency resolution over four and two times simultaneously for BOTDR with 100 ns pump pulse width.



中文翻译:

平滑伪Wigner-Ville分布和四参数粒子群优化联合算法在BOTDR中的应用

短时傅里叶变换用于传统点频布里渊光时域反射仪(BOTDR)的数据处理。这种方法可以提高测量速度,但是在理论上空间分辨率和频率分辨率之间存在矛盾。为了避免这种矛盾,提出了一种平滑伪Wigner-Ville分布(SPWVD)和四参数粒子群优化(四参数PSO)算法的联合算法,以提高布里渊散射频谱的空间分辨率,频率分辨率和频移提取精度。 。当进行二次时频转换时,SPWVD可以通过在时域和频域上同时添加一个滑动窗口来平滑信号,从而提高频率分辨率。为了进一步提高频率偏移的拟合度和提取精度,使用四参数PSO算法对SPWVD处理的布里渊散射频谱(BSS)进行拟合,以找到布里渊频移(BFS),该算法将增益BFS满BSS的一半最大值的宽度,以及洛伦兹和高斯线的线性权重系数作为未知参数。根据实验结果,使用SPWVD和四参数PSO联合算法的BOTDR将花费更少的操作时间,因为它可以得到更好的结果,并且累加更少,并且不需要在曲线拟合操作之前找到合适的初始值。同时,联合算法可以将泵浦脉冲宽度为100 ns的BOTDR的空间分辨率和频率分辨率同时提高4到2倍。使用四参数PSO算法对由SPWVD处理的布里渊散射光谱(BSS)进行拟合,以找到布里渊频移(BFS),该算法采用增益,BFS,BSS的一半最大值的全宽度以及洛伦兹的线性权重系数和高斯线作为未知参数。根据实验结果,使用SPWVD和四参数PSO联合算法的BOTDR将花费更少的操作时间,因为它可以得到更好的结果,并且累加更少,并且不需要在曲线拟合操作之前找到合适的初始值。同时,联合算法可以将泵浦脉冲宽度为100 ns的BOTDR的空间分辨率和频率分辨率同时提高4到2倍。使用四参数PSO算法对由SPWVD处理的布里渊散射光谱(BSS)进行拟合,以找到布里渊频移(BFS),该算法采用增益,BFS,BSS的一半最大值的全宽度以及洛伦兹的线性权重系数和高斯线作为未知参数。根据实验结果,使用SPWVD和四参数PSO联合算法的BOTDR将花费更少的操作时间,因为它可以得到更好的结果,并且累加更少,并且不需要在曲线拟合操作之前找到合适的初始值。同时,联合算法可以将泵浦脉冲宽度为100 ns的BOTDR的空间分辨率和频率分辨率同时提高4到2倍。

更新日期:2021-05-09
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