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Документ Statistical analysis of thermal nondestructive testing data(Національний технічний університет "Харківський політехнічний інститут", 2019) Galagan, R.; Momot, A.The features of processing of active thermal nondestructive testing results are considered. Proved the necessity of search and introduction of new informative parameters in evaluation ofthermograms in order to improve the reliability of control. Task of detecting and estimating the relationships between defect parameters and optimal testingtime and the maximum value of temperature signal is set. Computer simulation of active thermal testingof two samples with artificial defects with known characteristics was performed. Also obtainedthe sequences of thermogramsand formed the sets of initial data during simulationfor correlation, regression and dispersion analysis of testingresults. The method of dynamic thermal tomography was used to determine the levels of maximum differential temperature signal and optimal testing time. The estimates of correlation coefficient for various informational parameters of thermal control obtained. There is a high level of relations between the optimal control time and depth of defects. A high correlation also observed between the maximum value of temperature signal and depth of defects. The nature of relationships between various informative parameters of active thermal control establishedby the regression analysis. A one-factor dispersion analysis of the influence of defect parameters on optimal testing time and maximum value of the temperature signal was performed. High degree of mutual influence of all informative parameters is established. The conclusion made on the necessity ofdeveloping new modern methods for analysis thedata of thermal testing. Revealed patterns in relationships between data show low efficiency of traditional statistical methods in tasksof active thermal testing. Alternatively, proposed to use theartificial intelligence technologies, in particular, neural networks.