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为了促进热障涂层红外无损检测的定量检测研究,建立了轴对称圆柱坐标下的热障涂层脉冲相位检测模型,针对研究模型,采用有限体积法求解出脉冲热激励下的温度场,将温度进行FFT变化得到相位分布,分析了不同因素对检测表面相位差分布的影响。在此基础上,采用LM算法研究了轴对称圆柱坐标下对热障涂层厚度的大小和脱粘缺陷的位置进行定量化检测的方法,分析了不同因素对检测结果的影响。研究结果表明:当不存在测温误差时,不同的初始假设、采样窗口时间下都能得到很高的识别精度,其对定量识别的影响不大,当测温仅存在均匀误差时,涂层厚度和脱粘缺陷位置识别精度都很高,均匀误差对识别无影响,识别结果的精度会随测温随机误差的增大而降低,但在较大的随机误差下仍有较高的识别精度。
In order to promote the quantitative detection of infrared non-destructive testing of thermal barrier coatings, a pulse phase detection model of thermal barrier coating under axial symmetry cylindrical coordinates was established. For the research model, the finite volume method was used to solve the temperature field under pulse thermal excitation. The temperature was changed by FFT to get the phase distribution, and the influence of different factors on the phase difference distribution of the test surface was analyzed. On this basis, LM method was used to study the method of quantitatively detecting the thickness of thermal barrier coatings and the location of debonding defects under the axisymmetric cylindrical coordinates, and the influence of different factors on the test results was analyzed. The results show that when there is no error in temperature measurement, different initial assumption and sampling window time can obtain high recognition accuracy, which has little effect on quantitative identification. When there is only a uniform error in temperature measurement, the coating The recognition accuracy of the thickness and debonding defect location are very high. The uniform error has no effect on the recognition. The accuracy of the recognition result decreases with the increase of the random error of the temperature measurement. However, there is still a high recognition accuracy under the large random error .