During the calibration of an aerodynamic probe, the correlation between the present representative flow quantities of the fluid and the measurand is determined. Thus, a large number, sometimes several thousands, of different calibration points are set and measured, making this a very time-consuming process. The differences in the calibration data of similar constructed probes are very small. With the help of statistical methods, more precisely Gaussian process regressions, this similarity is exploited in order to use existing calibration data of different probes reducing the calibration time with sufficient reconstruction accuracy. Data from single-wire hot-wire probes and from five-hole probes are tested and show a very high reconstruction accuracy compared to the full calibration data set. The number of calibration points in the five-hole probe case is reduced by at least one order of magnitude with comparable reconstruction accuracy.

中文翻译：

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使用高斯过程回归的空气动力学探头校准

在空气动力学探针的校准期间，确定流体的当前代表性流量与被测量物之间的相关性。因此，设置并测量了大量（有时是数千个）不同的校准点，这是一个非常耗时的过程。相似构造的探头的校准数据差异很小。借助统计方法（更准确地说是高斯过程回归），可以利用这种相似性来使用不同探针的现有校准数据，从而以足够的重构精度减少校准时间。测试了来自单线热线探针和五孔探针的数据，与完整的校准数据集相比，它们显示出很高的重构精度。