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Genetic Algorithms Application for the Photoacoustic Signal Temporal Shape Analysis and Energy Density Spatial Distribution Calculation

机译:遗传算法在光声信号时态分析和能量密度空间分布计算中的应用

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摘要

Recently, a few numerical methods based on the photoacoustic (PA) signal temporal shape analysis and energy density spatial distribution calculation, which is directly related to the laser beam spatial profile, have been presented. It has been shown that these methods allow a precise reproduction of the spatial profile and the radius of the laser beam, determining the vibrational-to-translational (V-T) relaxation time with good accuracy. Their applicability has been shown and confirmed for the analysis of an arbitrary symmetric laser beam spatial profile in cylindrical geometry. Here, the application of genetic optimization for solving the problem of a simultaneous laser beam spatial profile and V-T relaxation time determination by pulsed PAs is presented. Real-coded genetic algorithms are used to calculate the mentioned relaxation time by fitting the experimental signal δp(r, t) with the theoretical one. The aim is to find combinations of PA signal parameters, namely, the radius of the laser beam and the V-T relaxation time that provide the best match with the given signal. A calculated PA signal with a known profile is used to simulate an experimental signal, and the sum of the square deviations representing deviations of the given and fitted signals is minimized by means of genetic optimization. In that way, the genetic algorithms are used to simultaneously estimate the radius of the laser beam and the V-T relaxation time efficiently and with high accuracy. Compared to previous methods, the presented method is much simpler and requires less time to compute.
机译:最近,提出了一些基于光声(PA)信号时间形状分析和能量密度空间分布计算的数值方法,这些方法与激光束的空间轮廓直接相关。已经表明,这些方法允许精确再现激光束的空间轮廓和半径,从而以良好的精度确定振动到平移(V-T)的松弛时间。已经证明了它们的适用性,并可以用于分析圆柱几何形状中的任意对称激光束空间轮廓。在这里,提出了遗传优化在解决同时脉冲光束空间轮廓和通过脉冲PA确定V-T弛豫时间的问题中的应用。实编码遗传算法用于通过将实验信号δp(r,t)与理论值拟合来计算上述弛豫时间。目的是找到PA信号参数的组合,即与给定信号最匹配的激光束半径和V-T弛豫时间。计算出的具有已知轮廓的PA信号用于模拟实验信号,并且通过遗传优化将代表给定信号和拟合信号的偏差的平方偏差之和最小化。以此方式,遗传算法被用于同时高效且高精度地估计激光束的半径和V-T弛豫时间。与以前的方法相比,提出的方法简单得多,所需的时间更少。

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