Minimizing recalibration using a non-linear regression technique for thermal anemometry
Minimizing recalibration using a non-linear regression technique for thermal anemometry
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DOI：
10.1007/s00348-019-2763-9
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发表时间：
2019-07-01
影响因子：
2.4
通讯作者：
Poole, Robert J.
中科院分区：
文献类型：
--
作者：
Agrawal, Rishav;Whalley, Richard D.;Poole, Robert J.
研究了一种使用非线性回归技术来最小化热风速测量中重新校准的新方法。该方法在长期测量中校正非热校准漂移的情况下以及不可能直接校准热膜/热线或遭受重大不确定性的情况下具有潜在的应用。该技术的基本输入是给定雷诺数的速度或壁剪切应力的前三个或四个时刻的先验知识。在使用该技术作为直接校准的替代方法的情况下，可以从单独的数据库（实验或数值）获得这些数据，或者在校正非热校准漂移时从先前或同时进行的一组实验获得这些数据。使用该输入，可以通过误差最小化过程获得假定的校准函数形式的系数。显示了通道流的说明性结果，其中胶粘热膜探头和热线探头分别用于壁剪切应力和流向速度测量。发现使用回归和先前校准获得的速度和壁剪应力之间有很好的一致性，这通过时间历史和概率密度函数图得到了证实。进行对校准关系形式、矩数和回归所需样本数的敏感性。通过示例可以看出，当使用从数值数据库获得的矩时，该方法在估计数据方面效果良好，并且在校正非热校准漂移方面也效果良好。如果雷诺数接近但不同于测量的雷诺数，则该技术也被证明可以很好地用于估计电压信号的数据。然后讨论与外部流量测量相关的另一种潜在应用场景。[图表]。
A new method to minimize recalibration in thermal anemometry using a non-linear regression technique is investigated. This method finds potential applications in cases of correcting for non-thermal calibration drifts in long measurements and scenarios where direct calibration of the hot films/hot wires is not possible or suffers significant uncertainties. The essential input for this technique is the a priori knowledge of the first three or four moments of velocity or wall-shear stress for a given Reynolds number. These can be obtained from a separate database (experimental or numerical) in cases where this technique is used as an alternative to direct calibration, or from a previous or simultaneous set of experiments when correcting for non-thermal calibration drifts. Using this input, the coefficients for the assumed calibration functional form can be obtained by an error minimization process. Illustrative results are shown for channel flows where glue-on hot-film probes and hot-wire probes are used for wall-shear stress and streamwise velocity measurements, respectively. There is found to be a good agreement between the velocity and wall-shear stress obtained using regression and prior calibration, which is confirmed using both time history and probability density function plots. Sensitivity to the form of calibration relationship, number of moments, and number of samples required for the regression are conducted. Through examples, it is observed that this method works well in estimating the data when moments obtained from a numerical database are used and also works well in correcting for non-thermal calibration drifts. This technique is also shown to work well for the estimation of data from the voltage signals if moments are available for a Reynolds number close to, but not the same as, the measured Reynolds number. One additional potential scenario for application related to the measurement in external flows is then discussed.[GRAPHICS].