基于DPHP测量数据提取热导率参数的方法研究

Methodology for extracting the thermal conductivity parameter from Dual-Probe Heat-Pulse data

基于DPHP实测数据研究了提取热导率参数的两种方法:极值法和拟合法.极值法利用温度曲线的峰值及对应时间计算热导率,测量过程中的采样间隔是影响计算结果的关键因素,热导率相对误差同采样间隔与峰值时间的比值有关,当比值小于0.02时,相对误差不超过±1%.采用抛物线拟合采样最大温度值相邻的数据计算峰值温度能够在一定程度上弥补采样率过大的问题.但对于过大的采样间隔获得的数据应使用非线性拟合法.非线性拟合法要求拟合模型对实测数据有良好反映,但理论模型与实际探针模型的差异导致实测数据只是在最大温度前后吻合较好,因此需要对拟合数据窗口进行选择.基本原则是数据区间内应当包含温升最大值,而且上升段的数据量应少于衰减段的数据量.

The two methods to extract the thermal conductivity parameter are studied based on DPHP （Dual-Probe Heat Pulse） measurement data. The first method, named Peak Point Method （PPM）, is based on the peak point of the temperature response curve to pulsed heating. For this method, the sampling interval is the key factor to affect the accuracy of thermal conductivity calculation. The ratio of sampling interval to peak time less than 0. 02 is necessary to ensure the relative error within q-10~. For the sparse data, a parabola fitting approach is suggested to calculate peak temperature and its corresponding peak time, which can make up the disadvantage of too large sampling interval. The second method, called Nonlinear Model Fitting （NMF）, is better for sparser data than PPM. For this method, the model used for fitting should reflect the distribution of the measured data, but the discrepancy between the theoretical model and the probe structure makes the temperature record some different from the theoretical temperature-time curve. In order to geta more acceptable thermal conductivity parameter, an appropriate fitting region including the part of data to join to fitting should be chosen according the following roles, that is （1） the peak temperature record should be included in the fitting window, （2） the region should contain more data of temperature decaying section than that of temperature rising section.