Method for measuring defect depth using thermal imaging instantaneous temperature contrast characteristic time

Abstract

The present invention provides a method for measuring defect depth by utilizing thermal imaging instantaneous temperature contrast characteristic time. The method is based on the calculation derivation of one-dimensional heat conduction theory and pulse thermal imaging detection. After extracting the temperature change data of the detection surface, the concept of instantaneous temperature contrast is proposed. The instantaneous temperature contrast change rate between the defective area and the normal area is calculated and obtained. The time corresponding to the peak value of the change rate has a corresponding relationship with the depth position of the internal defect of the material (i.e., the remaining wall thickness after damage). After data processing and analysis, the depth of the internal defect of the material or the remaining wall thickness after structural damage can be obtained.

Description

Technical Field

[0001] The invention belongs to the technical field of nondestructive testing, and in particular relates to a method for measuring defect depth by utilizing instantaneous temperature contrast characteristic time of thermal imaging, which is used for rapid measurement of defect depth / remaining wall thickness inside a material. Background Art

[0002] In the early 19th century, Fourier first proposed the concept of thermal wave in his book "Theory of Heat Conduction in Solids". Thermal wave is a temperature field that changes periodically over time during propagation. However, it was not until 1978 that thermal wave theory began to be truly used in non-destructive testing. Due to the high reflectivity and thermal conductivity of metal materials (such as aluminum and its alloys have very high thermal diffusivity and low surface emissivity), the application of thermal wave technology was limited in early defect / damage detection. However, with the emergence of high-energy flash lamps and high-speed, multi-pixel, high-sensitivity imaging thermal detection equipment and the development of computer digital signal processing technology, the detection of material defect depth has become an important application of thermal imaging non-destructive testing.

[0003] The pulsed thermal (PT) method actively applies controllable pulsed thermal excitation to the object to be inspected, so that the internal defects of the material are manifested in the form of surface temperature changes. The temperature field cloud map sequence of the object surface continuously observed and recorded by the infrared thermal imager is analyzed and processed to realize the detection and quantitative identification of the internal defects of the object. Figure 1 As shown, the location and range of defects can be detected.

[0004] In the field of non-destructive testing, the depth of defects / damage below the surface is called defect depth, and it is regarded as an important part of detection. Various thermal imaging defect depth identification methods have been proposed. The defect depth corresponds to the remaining wall thickness of the structure.

[0005] The defect depth measurement by pulse infrared thermal imaging is mainly based on the theoretical calculation of the one-dimensional heat conduction surface temperature difference. After formula derivation, it can be deduced that the time (peak value) corresponding to the maximum surface temperature difference under pulse thermal excitation is proportional to the square of the remaining wall thickness. This is the basic principle of the most widely used optimal detection time method in pulse thermal wave detection. For isotropic homogeneous materials, in the absence of internal heat sources, the thermal conduction differential equation is approximately a one-dimensional equation, expressed as:

[0006]

[0007] Where α is the thermal diffusivity of the material, m 2 / s, α=λ / (ρC).

[0008] Pulse thermal excitation uses a high-energy flash lamp to apply a pulsed heat flow to the sample surface. The energy of the pulse can be recorded as:

[0009] q=q0δ(x)δ(t) (2)

[0010] Among them, δ(x) and δ(t) are unit pulse functions, also known as Dirac functions, namely:

[0011]

[0012] The boundary conditions for pulse thermal excitation are:

[0013] Initial condition: T(x,0)=T0

[0014] Boundary conditions: Ignore the surface convection heat transfer, that is

[0015] The restrained surface temperature change is derived as:

[0016]

[0017] In order to analyze the principle of thermal wave defect detection, the internal defects or corrosion damage of the material are described as circular, and the cross section of the defect is as follows: Figure 2 As shown. Among them, δ is the material wall thickness, D is the defect diameter, d is the defect depth, and h is the remaining wall thickness (usually in the field of detection technology, h is described as the defect depth, that is, the depth of the defect from the surface).

[0018] The pulsed thermal excitation method is used for heating. For the semi-infinite plate structure, the mathematical model of the defective structure can be simplified to a one-dimensional model (see Figure 2 ), if the heat loss inside the material is not considered, the boundary conditions between the defect / damage and the material interface satisfy the temperature continuity and energy conservation:

[0019] T s =T d =T h (5)

[0020]

[0021] Wherein, the subscripts s and d represent the interface between the normal region and the defect, respectively (s represents the interface of the normal region, and d represents the interface of the defect).

[0022] For areas without defects / damage, the surface temperature change can be expressed by equation (4) based on the analysis of heat conduction of a semi-infinite structure. If there are defects, it can be understood in terms of the concept of heat waves: when the heat wave is transmitted to the defect surface, the heat wave will be affected by the defect surface, and part of the heat wave will be reflected back and continue to propagate in the opposite direction, and then propagate to the material surface and reflect again, and then reflect periodically according to the same propagation law until it decays. Therefore, the surface temperature at the defect includes two parts: one is the temperature decay part of the surface corresponding to the semi-infinite area, and the other is the part that is continuously reflected and accumulated by the defect surface. The two parts constitute the distribution of the surface temperature field at the defect. Here, assuming that the reflection coefficient of the defect interface for the heat wave is r, the reflected heat wave should be the cumulative value of the surface heat wave after decaying at a distance of 2h, 4h, 6h...2nh:

[0023]

[0024] The surface temperature distribution is:

[0025]

[0026] Due to the high attenuation of thermal waves, higher-order attenuation can be ignored, and the reflection coefficient of the defect interface to thermal waves is e1 and e2 represent the thermal emission coefficients of the material and its internal medium respectively. It is known that the reflection coefficient r is a constant, so we can get:

[0027]

[0028] The surface temperature rise is:

[0029]

[0030] To simplify the calculation, the reflection coefficient of the defect to the thermal wave is approximately considered to be a constant 1 (i.e., total reflection), and we can get:

[0031]

[0032] Therefore, the temperature difference between the defective area and the non-defective area is:

[0033]

[0034] Defect depth (i.e., remaining wall thickness) is an important characteristic parameter for characterizing the degree of defects in equipment or materials, and has always been a hot topic in the field of thermal imaging detection. In 1999, Deemer C. et al. found that the first-order differential curve of the surface temperature difference function has a peak value, and the corresponding time has a certain corresponding relationship with the defect depth, and proposed the PST (peak slope time) method. In 2002, JGSun proposed a defect depth calculation method based on least squares fitting and applied for a patent. In 2003, Steven M. Shepard directly took the logarithm of the surface temperature function and then performed the second-order differential on the logarithm of time, and proposed the LPSD (logarithmic peak second-derivative method) method for calculating defect depth. In 2006, JGSun compared and analyzed PCT, PST, LPSD and least squares fitting methods. The results showed that under ideal conditions, various methods have high calculation accuracy. In actual detection, the recognition error of defect depth varies due to the influence of calculation method, defect size and depth. In 2012, Zeng Zhi and others from Capital Normal University transformed the surface temperature function, took the first-order differential of the transformed function to find the extreme value, obtained a characteristic time, and proposed the APST (absolute peak slopetime) method for calculating the defect depth; Huo Yan and others proposed to use the least squares polynomial fitting method to deal with the relationship between the characteristic time and the defect depth of the LPSD method on the basis of the LPSD method, and selected the fitting relationship under the condition of the minimum sum of squares of relative errors as the calibration relationship for defect depth measurement, avoiding the random error that may be caused by single-point calibration measurement depth, and improving the recognition accuracy. The above methods all process the surface temperature data sequence to obtain the characteristic time that has a specific relationship with the defect depth, and realize the quantitative recognition of the defect depth based on the acquisition of the characteristic time. They have been applied in the recognition of different defects in different fields. Several typical pulse thermal imaging defect depth / remaining wall thickness calculation methods are as follows:

[0035] 1) Peak Contrast Time (PCT)

[0036] The PCT method is also called the optimal detection time method. Its characteristic time is the time when the surface temperature difference reaches the maximum, which is proportional to the square of the defect depth:

[0037]

[0038] 2) Peak Slope Time (PST)

[0039] The PST method is to perform the first-order differentiation of the surface temperature difference, that is, to perform the first-order differentiation of equation (11) to obtain the thermal contrast change rate curve, and take the time corresponding to its peak value as the characteristic time:

[0040]

[0041] The solution yields two characteristic times. In order to minimize the impact of three-dimensional heat diffusion on the detection results, the time corresponding to the first extreme point is usually taken as the characteristic time.

[0042] 3) Absolute Peak Slope Time (APST)

[0043] The APST method processes and analyzes the absolute temperature difference between the surface temperature of the material after pulse heating and the initial temperature. First, the absolute temperature difference expression is transformed, and then the extreme value of the transformed function is calculated to obtain a characteristic time. A typical characteristic function of the APST method is:

[0044]

[0045] By taking the first-order differential of the above equation and finding the extreme value, the characteristic time of the APST method can be obtained:

[0046]

[0047] The characteristic time of the APST method is the same as that of the PCT method, but the APST method directly transforms the surface temperature data, reduces the normal area selection and the calculation of the surface temperature difference, avoids the non-uniformity problem to a certain extent, and improves the accuracy of defect identification.

[0048] 4) Logarithmic Peak Second-Derivative Method (LPSD)

[0049] The LPSD method does not require the reference area to be determined in advance. Instead, it directly takes the logarithm of the surface temperature and performs the second-order differential processing on the logarithm of time. The time corresponding to the peak value in the second-order differential logarithmic temperature curve is used as the characteristic time. It is also called the peak method of the second-order differential of logarithmic temperature time (PSDT). Its characteristic time is:

[0050]

[0051] However, in the process of measuring the defect depth (also known as the remaining wall thickness) using the above methods, there are problems such as cumbersome data processing, and the calculation results are easily affected by three-dimensional heat diffusion. In addition, the data interference caused by temperature non-uniformity will affect the accuracy of the calculation results. Especially for the PCT method, the greater the remaining wall thickness, the greater the recognition error of this method.

[0052] In view of the above reasons, it is necessary to explore a new method to measure defect depth / remaining wall thickness. Summary of the invention

[0053] The purpose of the present invention is to solve the existing technical problems and provide a method for measuring defect depth by utilizing the instantaneous temperature contrast characteristic time of thermal imaging.

[0054] In order to achieve the above-mentioned invention object, the specific technical solution provided by the present invention is:

[0055] A method for measuring defect depth by using thermal imaging instantaneous temperature contrast characteristic time, which is special in that it includes the following steps:

[0056] 1) Based on pulse thermal imaging detection, extract the temperature change data of the detection surface;

[0057] 2) According to the temperature change data extracted in step 1), the ratio of the surface temperature difference between the defective area and the normal area to the temperature rise of the normal area is calculated, and the ratio is defined as the instantaneous temperature contrast ratio;

[0058] 3) performing two differential processes on the instantaneous temperature contrast obtained in step 2) with respect to time to obtain the instantaneous temperature contrast change rate;

[0059] 4) Calculate the time corresponding to the maximum value point of the instantaneous temperature contrast change rate in step 3 (also called the instantaneous temperature contrast change rate peak time, or the instantaneous temperature contrast characteristic time), and calculate the defect depth h (h can also be called the remaining wall thickness after structural damage) inside the material according to the following formula:

[0060]

[0061] in, When the surface temperature of the defect area is used as the reference temperature, the time corresponding to the maximum value of the instantaneous temperature contrast change rate;

[0062] α is the thermal diffusivity of the material.

[0063] Further, in step 2), the instantaneous temperature contrast is expressed as follows:

[0064]

[0065] Among them, C P-soundis the instantaneous temperature contrast relative to the normal area, T defect (0,t) and T sound (0, t) are the temperatures of the defect area and the normal area at time t relative to the initial time; q is the pulse energy; c is the specific heat capacity of the material; t is the time; n is a natural integer, indicating the number of reflections of the heat wave; λ is the thermal conductivity coefficient of the material; ρ is the density of the material; e is the base of the natural logarithm; α is the thermal diffusivity of the material; and h is the defect depth inside the material.

[0066] Ignoring the higher-order reflections of heat waves in the material, the instantaneous temperature contrast is simplified to:

[0067]

[0068] Further, step 3) is specifically as follows:

[0069] right Taking the first-order differential, we get:

[0070]

[0071] Differentiating again, we get

[0072]

[0073] Further, step 4) is specifically as follows:

[0074] 4.1) Order The time corresponding to the maximum value of the instantaneous temperature contrast change rate is calculated as:

[0075]

[0076] 4.2) Calculate the defect depth (i.e., remaining wall thickness) according to the following formula:

[0077]

[0078] Principle of the invention:

[0079] The present invention proposes a new defect depth quantitative identification algorithm by transforming and processing the temperature data obtained during the infrared thermal imaging detection process, and creatively proposes the concept of instantaneous temperature contrast, constructs a specific relationship between the instantaneous temperature contrast change rate and the defect depth. The present invention calls this measurement method the instantaneous temperature contrast change rate peak time method (PSTC), which is used to obtain the defect depth.

[0080] Advantages of the present invention:

[0081] 1. The present invention changes the calculation method of temperature data and proposes a temperature contrast calculation method, which helps to eliminate data interference caused by temperature non-uniformity and improves the accuracy of the calculation results. Compared with the PCT method, this calculation method can capture the characteristic time more quickly and avoid the influence of heat diffusion and temperature non-uniformity. Compared with the PST method, when the temperature difference is small and the signal is easily submerged, it is easier to find the characteristic time and observe the peak change, thereby improving the calculation accuracy. Compared with the APST method, the calculation process saves Compared with the LPSD method, the differential calculation process of the term omits the logarithm calculation process, reduces the calculation terms of the t variable, and to a certain extent suppresses the influence of time, diffusion coefficient, and reflection coefficient on the accuracy of the measurement results. At the same time, it reduces the amount of calculation, which can greatly shorten the calculation time and improve the calculation efficiency.

[0082] 2. In the calculation process, the algorithm of the present invention constructs the comparative relationship between the temperature difference between the defect area and the surface of the normal area and the temperature rise of the normal area surface, proposes the concept of transient temperature contrast, and constructs the specific relationship between the peak time of the transient temperature contrast change rate and the defect depth based on the differential processing of the temperature contrast change rate. In the calculation process, a relationship with a time variable is omitted, which reduces the amount of calculation for data differential solution and improves the calculation speed. It is summarized as the Peak Slope Time of Transient Temperature Contrast (PSTC) method for defect depth identification.

[0083] 3. The pulse thermal imaging instantaneous temperature difference change rate peak time method is mainly used to measure the depth of defects in materials or the remaining wall thickness after damage in structures. The present invention is based on the calculation and derivation of one-dimensional heat conduction theory and pulse thermal imaging detection. After extracting the temperature change data of the detection surface, the concept of instantaneous temperature contrast is proposed, and the instantaneous temperature contrast change rate between the defective area and the normal area is calculated. The time corresponding to the peak value of the change rate has a corresponding relationship with the depth position of the internal defects of the material (i.e., the remaining wall thickness after damage). After data processing and analysis, the depth of the internal defects of the material or the remaining wall thickness after structural damage can be obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 This is the principle diagram of pulse infrared thermal imaging detection;

[0085] Figure 2 The principle of thermal imaging detection of internal defects / damages;

[0086] Figure 3 The principle of PSTC deep recognition method, where (a) is C P-soundCurve (b) is C P-sound The first-order differential curve of C P-sound The second-order differential curve of

[0087] Figure 4 The circular pit simulation specimen of steel corrosion, where (a) is the front of the specimen, (b) is the back of the specimen, and (c) is the specimen size diagram, unit: mm;

[0088] Figure 5 The original thermal image sequence of thermal wave detection of circular corrosion pits in steel materials with different depths;

[0089] Figure 6 The curves of the surface temperature and surface temperature difference of the center of the etch pit changing with time after pulse excitation, where (a) is the surface temperature-time curve, and (b) is the surface temperature difference-time curve;

[0090] Figure 7 The instantaneous temperature contrast at the center of the etch pit and its first-order differential curve, where (a) is the instantaneous temperature contrast curve and (b) is the first-order differential curve of the instantaneous temperature contrast. DETAILED DESCRIPTION

[0091] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0092] A method for measuring defect depth / remaining wall thickness using pulse thermal imaging instantaneous temperature contrast change rate peak time comprises the following steps:

[0093] 1) Based on pulse thermal imaging detection, the temperature change data of the detection surface is extracted, which can be obtained using existing methods;

[0094] 2) According to the temperature change data extracted in step 1), the ratio of the surface temperature difference between the defective area and the normal area to the temperature rise of the normal area is calculated, and the ratio is defined as the instantaneous temperature contrast, which is expressed as follows:

[0095]

[0096] Among them, C P-sound is the instantaneous temperature contrast relative to the normal area, T defect (0,t) and T sound (0, t) are the temperatures of the defective area and the normal area at time t relative to the initial time;

[0097] Ignoring the higher-order reflections of heat waves in the material, the instantaneous temperature contrast is simplified to:

[0098]

[0099] 3) Differentiating the instantaneous temperature contrast obtained in step 2) to obtain the instantaneous temperature contrast change rate; specifically:

[0100] right Taking the first-order differential, we get:

[0101]

[0102] Differentiating again, we get

[0103]

[0104] The first-order differential and second-order differential curves are as follows: Figure 3 As shown;

[0105] 4) From Figure 3 It can be seen that the instantaneous temperature contrast increases with time, but the rate of change of the instantaneous temperature contrast (first-order differential curve) increases first and then decreases, with a peak value.

[0106] make The time corresponding to the maximum value of the instantaneous temperature contrast change rate is calculated as:

[0107]

[0108] The depth of internal defects in the material or the remaining wall thickness h after structural damage is calculated according to the following formula:

[0109]

[0110] in,

[0111] When the surface temperature of the defect area is used as the reference temperature, the time corresponding to the maximum value of the instantaneous temperature contrast change rate;

[0112] α is the thermal diffusivity of the material.

[0113] In order to verify the effect of the technical solution of the present invention, the following pulse thermal imaging test of a steel material damage specimen containing a circular defect was performed:

[0114] The corrosion damage of metal materials generally adopts flat-bottom hole specimens. The specimens are made of metal steel and have the dimensions of 280mm×200mm×6mm. There are 4 flat-bottom holes on the back to simulate circular corrosion pits. The diameter of the corrosion pits is 20mm, and the depths are 2mm, 3mm, 4mm, and 5mm respectively. The structural dimensions are as follows: Figure 4 shown.

[0115] In order to facilitate analysis, the pits in the lower half of the steel corrosion simulation specimen were numbered from pit 1 to pit 4 in the order of pit depth from large to small (remaining wall thickness from small to large). The pulsed thermal wave method was used to obtain the following Figure 5 Sequence of infrared heat maps shown.

[0116] from Figure 5 It can be seen that the appearance of the four pits has undergone a change process from dark to bright and then from bright to dark. At about 0.04s, pit 1 first appeared in the form of a hot spot. As time went on, the shallower pits also began to appear, and the hot spots became clearer and clearer. At about 0.40s, the hot spot of pit 4 appeared, but it was difficult to observe it through the thermal map, which was due to the weak signal. Then the bright spot gradually became blurred. After 3s, the hot spot on the thermal map gradually blurred and finally with the lateral propagation of the heat wave, the surface temperature field distribution tended to be uniform, and the corrosion damage on the inner wall of the tank could not be seen. Among them, the bright spot corresponding to the pit with the smallest depth (largest remaining wall thickness) appeared last but disappeared first; the bright spot with the longest duration was the pit with the largest depth (smallest remaining wall thickness), which shows that the smaller the remaining wall thickness, the greater the impact of corrosion on the surface temperature field, and the easier it is to detect. The use of the thermal wave method can timely detect damage and determine the dangerous position.

[0117] The depth of the pit is closely related to the time when the hot spot appears. The deeper the pit, the smaller the remaining wall thickness, and the earlier the corrosion damage is discovered. Therefore, the depth of the pit can be judged according to the time when the pit appears, lasts or disappears. The surface temperature data of the center of the pit after pulse thermal excitation is extracted, and the surface temperature data of the normal area is used as a reference to calculate the surface temperature difference of the pit area. Figure 6 Temperature and temperature difference curves shown.

[0118] from Figure 6 It can be seen from (a) that at the beginning of cooling, the cooling curves at various positions basically overlap, and the temperature drops sharply. Then, the surface temperature drop curves of the pits with different depths begin to separate. The pit with the smallest depth corresponds to the part with the thickest remaining wall thickness, and its surface temperature drops the fastest; the pit with the largest depth corresponds to the part with the thinnest remaining wall thickness, and its surface temperature drops the slowest. As time goes on, the surface temperature field of the specimen tends to be consistent.

[0119] (1) Remaining wall thickness identification based on PCT method

[0120] from Figure 6 It can be seen from (b) that the maximum surface temperature difference occurs at different times at different remaining wall thicknesses. The PCT method is used to quantitatively identify the remaining wall thickness, and the results are shown in Table 1.

[0121] Table 1 Quantitative identification results of the remaining wall thickness at the etch pit by PCT method

[0122]

[0123] It can be seen from Table 1 that the greater the remaining wall thickness, the greater the recognition error of the PCT method. Therefore, the PCT method is suitable for very severe corrosion detection. In this case, the corrosion residual wall thickness is small, and the propagation of heat flow in the tank wall is less affected by three-dimensional heat diffusion. For slight corrosion or early corrosion, the remaining wall thickness of the tank is large, and the measurement result error of the PCT method is large, which cannot meet the measurement requirements.

[0124] (2) Remaining wall thickness identification based on the PSTC method of the present invention

[0125] The extracted surface temperatures of the corroded area and the uncorroded area are calculated according to the above formula to obtain the relationship between the instantaneous temperature contrast and time, as shown in Figure 7 shown.

[0126] contrast Figure 7 Figure (a) and Figure 6 As can be seen from (a), there is no typical moment in the original surface temperature curve that can be used for extraction, and no information related to the remaining wall thickness can be obtained. However, after extracting the instantaneous temperature contrast, the obtained curve has a slope peak, and the corresponding moment has a specific relationship with the remaining wall thickness. After taking the first-order differential of the instantaneous temperature contrast, the instantaneous temperature contrast change rate curve can be obtained, as shown in Figure 7 as shown in (b).

[0127] The peak moments of the instantaneous temperature contrast at different residual wall thicknesses are different. Taking the peak moment of the instantaneous temperature contrast at the thicker residual wall thickness as the benchmark, the remaining wall thicknesses corresponding to the other three pits are calculated based on the peak time method of instantaneous temperature contrast change rate (PSTC), and the corresponding measurement errors are calculated. The results are shown in Table 2.

[0128] Table 2 Quantitative identification results of the remaining wall thickness at the corrosion pit by the PSTC method

[0129]

[0130] It can be seen from Table 2 that, compared with the PCT method, the PSTC method has a smaller measurement error and can be used to calculate the corrosion residual wall thickness. The more severe the corrosion, the smaller the residual wall thickness, and the higher the accuracy of thermal imaging detection in identifying the wall thickness.

[0131] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should be included in the protection scope of the present invention.

Claims

1. A method for measuring defect depth using thermal imaging instantaneous temperature contrast characteristic time, characterized in that: The following steps are involved: 1) Based on pulse thermal imaging detection, extract the temperature change data of the detection surface; 2) According to the temperature change data extracted in step 1), the ratio of the surface temperature difference between the defective area and the normal area to the temperature rise of the normal area is calculated, and the ratio is defined as the instantaneous temperature contrast ratio; The instantaneous temperature contrast is expressed as follows: Among them, C P-sound is the instantaneous temperature contrast relative to the normal area, T defect (0,t) and T sound (0, t) are the temperatures of the defect area and the normal area at time t relative to the initial time; q is the pulse energy; c is the specific heat capacity of the material; t is the time; n is a natural integer, indicating the number of reflections of the heat wave; λ is the thermal conductivity of the material; ρ is the density of the material; e is the base of the natural logarithm; α is the thermal diffusivity of the material; h is the depth of the defect inside the material; Ignoring the higher-order reflections of heat waves in the material, the instantaneous temperature contrast is simplified to: 3) performing two differential processes on the instantaneous temperature contrast obtained in step 2) with respect to time to obtain the instantaneous temperature contrast change rate; right Taking the first-order differential, we get: Differentiating again, we get 4) Calculate the time corresponding to the maximum value of the instantaneous temperature contrast rate of change in step 3) and calculate the defect depth h inside the material according to the following formula: in, When the surface temperature of the defect area is used as the reference temperature, the time corresponding to the maximum value of the instantaneous temperature contrast change rate; α is the thermal diffusivity of the material.

2. The method according to claim 1, characterized in that: Step 4) is specifically as follows: 4.1) Order The time corresponding to the maximum value of the instantaneous temperature contrast change rate is calculated as: 4.2) Calculate the defect depth according to the following formula:

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