Issue 50

A. Kostina et alii, Frattura ed Integrità Strutturale, 50 (2019) 667-683; DOI: 10.3221/IGF-ESIS.50.57 669 been compared to the main well-known and widely used techniques of signal reconstruction (simple moving average method, Gaussian filter, Savitzky-Golay filter and median filter). Values of the temperature contrast evaluated by the numerical simulations in the first part of the paper were used as ideal reference signals and thus, allow us to estimate the efficiency of the proposed approach. N UMERICAL SIMULATION OF PULSED THERMOGRAPHY Mathematical formulation he evolution of the temperature field during heating of the solid is described by the heat transfer equation:           0 T c T t   (1) where  [kg/m 3 ] is the density, c [J/(kg·K)] is the heat capacity, T [K] is the absolute temperature, t [s] is the time,  [W/(m·K)] is the thermal conductivity. The initial condition for Eqn. (1) has the form:     , , , 0 o T x y z t T (2) where o T [K] is the initial temperature of the solid. The following boundary conditions are applied to the heated surface F of the solid:        F o T Q  n (3)           F o T T T   n (4)           4 4 F o T T T   n (5) where n is the unit normal to F , o Q [W/m 2 ] is the heat flux,  [W/(m·K)] is the convective heat transfer coefficient,  [W/(m 2 ·K 4 )] is the Stefan-Boltzmann constant,  is the surface emissivity. The fundamental base of non-destructive techniques is the temperature contrast. The most commonly used definition of this parameter refers to the absolute temperature contrast and states that it is equal to the difference between the mean temperature in the defective area and the mean temperature in the non-defective (sound) area [2]:   d s C T T (6) where C is the value of absolute temperature contrast, d T is the mean temperature in the defective area, s T is the mean temperature in the sound area. This parameter characterizes the visibility of the specific defect but it is susceptible to surface noise [2]. Therefore, an accurate prediction of this value using simple and effective signal processing techniques should be carried out. In this work, model (1)-(5) was applied to the estimation of the “ideal” (without noise) temperature contrast evolution in sample with subsurface defects of various depths and sizes. Validation of the model The verification of the model was based on the simulation of the experiment published in [13]. Pulsed thermography was applied to evaluate of the temperature contrast in rectangular AISI 316 L steel plate containing artificial square defects of various sizes located at various depths from the surface. The plate has a length of 150 mm and a width of 100 mm. The thickness of the sample is 3.5 mm. A schematic representation of the specimen is given in Fig. 1 (a). T