Method for suppressing lift-off effect in ferromagnetic and non-ferromagnetic materials in pulsed eddy current testing

Abstract

The application provides a method for inhibiting the lift-off effect of ferromagnetic and non-ferromagnetic materials in pulsed eddy current detection. Step 1: obtaining the preprocessed signals of the same thickness test piece at different lift-off distances, and recording as a group of preprocessed signal curves; step 2: changing the thickness of the test piece detection area, repeating step 1 to obtain the preprocessed signal curves at different thicknesses, and obtaining the corresponding characteristic quantity; step 3: repeating steps 1 and 2 on the standard test piece with a known thickness, obtaining the corresponding characteristic quantity, and fitting to obtain the fitting curve and equation of each characteristic quantity and the thickness of the test piece; step 4: placing the probe on the same device to be detected as the standard test piece material to perform pulsed eddy current detection, obtaining the characteristic quantity, and bringing it into the corresponding fitting curve obtained in step 3 to calculate the thickness of the device to be detected and infer the defect information. The method overcomes the influence of the lift-off effect on the detection results of ferromagnetic and non-ferromagnetic materials, and improves the detection accuracy of the pulsed eddy current.

Description

Technical Field

[0001] This invention belongs to the field of pulsed eddy current nondestructive testing technology, specifically relating to a method for suppressing the lift-off effect of ferromagnetic and non-ferromagnetic materials in pulsed eddy current testing. Background Technology

[0002] Pipeline transportation is widely used as an efficient and economical mode of transport. Among these, pressure-bearing pipelines, as crucial components, are susceptible to corrosion, erosion, and fatigue during service, making them prone to defects such as thick-walled corrosion and thinning. When these defects develop to a certain extent, they can lead to pipeline ruptures and leaks, causing significant economic losses and casualties to the pipeline industry. Therefore, regularly inspecting the health of pressure-bearing thick-walled pipelines is of paramount importance for ensuring effective equipment operation and safeguarding social production safety.

[0003] Pulsed eddy current testing is an effective method for detecting defects in conductive structures, offering advantages such as high efficiency, high precision, non-contact operation, no need for coupling agent, low cost, and simple operation. However, in actual testing, the distance between the probe and the test piece inevitably changes. This change in distance alters the magnetic field lines passing through the conductor; specifically, a shorter distance results in a higher eddy current density and more effective information, while a longer distance results in a lower eddy current density and less effective information. This disturbance to the signal caused by the change in probe-test-piece distance is called the lift-off effect. The lift-off effect affects the detection precision and accuracy; therefore, it is necessary to suppress it.

[0004] To address this issue, researchers proposed the liftoff point of intersection (LOI) as a characteristic quantity. This refers to the fact that when the liftoff distance changes, the differential signals from pulsed eddy current detection in non-ferromagnetic materials always intersect at a single point. This point serves as a signal characteristic for immunity to the liftoff effect and plays a guiding role in suppressing it. However, LOI only applies to non-ferromagnetic materials and not to ferromagnetic materials, thus failing to solve the liftoff effect problem in ferromagnetic materials. Therefore, it is crucial to research a characteristic quantity applicable to both ferromagnetic and non-ferromagnetic materials that is independent of liftoff. Patent CN115825219A proposes that for both ferromagnetic and non-ferromagnetic materials, the detection signals from TR probes with different coil spacings intersect at a single point; this intersection point is independent of liftoff. Patent CN 112505138A indicates that for ferromagnetic materials, obtaining the difference between the detection signal and the air signal, and then differentiating it with the standard deviation of the obtained signal, yields a signal intersection point independent of liftoff. It is evident that the lift-off crossover point of ferromagnetic materials has been a hot topic in eddy current testing in recent years. Based on this, this patent will continue to research methods for suppressing the lift-off effect that are applicable to both ferromagnetic and non-ferromagnetic materials.

[0005] This patent aims to propose a signal characteristic quantity that is applicable to both ferromagnetic and non-ferromagnetic materials and immune to the lift-off effect, and to study its variation law and influencing factors, so as to further enhance the application value and significance of pulsed eddy current technology detection, and provide new ideas and methods for solving the lift-off effect in pulsed eddy current detection. Summary of the Invention

[0006] The purpose of this invention is to provide a characteristic quantity for eliminating the lift-off effect that is applicable to both ferromagnetic and non-ferromagnetic materials, and to use it for the quantitative evaluation of material defects.

[0007] To achieve the above objectives, the present invention employs the following solution: A method for suppressing the lift-off effect of ferromagnetic and non-ferromagnetic materials in pulsed eddy current testing includes the following steps: Step 1: Signal Preprocessing The pre-processed signals of specimens of the same thickness at different lift-off distances were obtained and recorded as a set of pre-processed signal curves. Step 2, Feature Extraction By varying the thickness of the test area of ​​the specimen and repeating step 1, preprocessed signal curves were obtained for different thicknesses, with each thickness corresponding to a set of preprocessed signal curves. Comparing all the preprocessed signal curves, the following conclusions were drawn: 1) For ferromagnetic materials, the pre-processed signal curves of each group completely overlap, that is, the pre-processed signal curves of different thicknesses completely overlap; the peak value and peak time of the pre-processed signal curves corresponding to different thicknesses are different, and the peak value tends to decrease with the increase of specimen thickness, while the peak time tends to increase with the increase of specimen thickness; therefore, the peak value and peak time are both used as characteristic quantities for the defect assessment of ferromagnetic materials. 2) For non-ferromagnetic materials, the preprocessing signal curves at the same thickness have two intersection points besides the starting point, denoted as the first intersection point and the second intersection point, respectively. The positions of the first and second intersection points do not change with the lift-off. The amplitude and time of the first intersection point and the amplitude and time of the second intersection point increase with the increase of the thickness of the non-ferromagnetic specimen. Therefore, the amplitude and time of the first intersection point and the amplitude and time of the second intersection point can both be used as characteristic quantities for defect evaluation of non-ferromagnetic specimens. Step 3: Fitting the curve For a standard specimen with a known thickness, repeat steps 1 and 2 to obtain the corresponding characteristic quantities. Fit these quantities with a first-order polynomial to obtain the fitting curve and equation between each characteristic quantity and the specimen thickness. Step 4: Defect Assessment The probe is placed on the test device with the same material as the standard test piece to perform pulsed eddy current testing, and the characteristic quantities of the test signal of the test device are obtained. The characteristic quantities are then substituted into the corresponding fitting curve obtained in step 3 to calculate the thickness of the test device and infer its defect information.

[0008] Further optimization, step 1 specifically includes the following steps: Step 1.1: Mark a certain area of ​​the specimen as the reference area, perform pulsed eddy current detection on it, and obtain the signal as the reference signal; Step 1.2: Mark other areas of the specimen as the detection area, perform pulsed eddy current detection on them, and acquire the signal as the detection signal; Step 1.3: Perform a differential operation between the reference signal obtained in Step 1.1 and the detection signal obtained in Step 1.2 to obtain the differential signal; Step 1.4: Differentiate the differential signal obtained in Step 1.3 to obtain the differential signal; Step 1.5: Divide the differential signal in Step 1.4 by the integral of the difference signal in Step 1.3 to obtain the preprocessed signal, which is denoted as the preprocessed signal; Step 1.6: Change the lift-off distance between the probe and the specimen surface, while keeping the lift-off distance of the probe in the reference area and the detection area the same. Repeat steps 1.1-1.5 to obtain the pre-processed signals under different lift-off conditions, and record them as a set of pre-processed signal curves.

[0009] Further optimization, step 3 specifically includes the following steps: Step 3.1: Perform pulsed eddy current testing on the reference area of ​​a standard specimen of known thickness to obtain a reference signal; Step 3.2: Perform pulsed eddy current testing on other areas of the standard specimen with known thickness to obtain the detection signal; Step 3.3: Perform a differential operation between the reference signal obtained in Step 3.1 and the detection signal obtained in Step 3.2 to obtain the differential signal; Step 3.4: Differentiate the differential signal obtained in Step 3.3 to obtain the differential signal; Step 3.5: Divide the differential signal from Step 3.4 by the integral of the difference signal from Step 3.3 to obtain the preprocessed signal; Step 3.6: Change the lift-off distance between the probe and the specimen surface, while keeping the lift-off distance of the probe in the reference area and the detection area the same. Repeat steps 3.1-3.5 to obtain the pre-processed signals under different lift-off conditions, and record them as a set of pre-processed signals. Step 3.7: Fitting 1) For ferromagnetic materials, extract the peak value and peak time of the preprocessed signal curves with different thicknesses, and fit them with a first-order polynomial to obtain the fitting curves and equations of the peak value and the specimen thickness and the peak time and the specimen thickness, respectively. 2) For non-ferromagnetic materials, extract the amplitude of the first crossover point, the time of the first crossover point, the amplitude of the second crossover point, and the time of the second crossover point of the preprocessed signal curves with different thicknesses, and fit them with a first-order polynomial to obtain the fitting curve and equation of each of the above feature quantities with the specimen thickness.

[0010] Compared with the prior art, the present invention has the following beneficial effects: The method described in this invention is applicable to defect detection of ferromagnetic and non-ferromagnetic materials and equipment, and has high detection accuracy. It further enhances the application value and significance of pulsed eddy current nondestructive testing, and provides new ideas and methods for solving the lift-off effect in pulsed eddy current testing. Attached Figure Description

[0011] Figure 1 The above are signal curves of the 10.00mm carbon steel specimen in Example 1 after pretreatment under different lift-off conditions. Figure 2 The image shows the preprocessing signal curves for three carbon steel specimens of different thicknesses in Example 1. Figure 3 The curve showing the fitted relationship between the specimen thickness and the signal peak value in Example 1; Figure 4 The curve showing the fitted relationship between specimen thickness and peak time in Example 1; Figure 5 The above are signal curves of the 10.00mm aluminum plate specimen in Example 2 after pretreatment under different lifting conditions. Figure 6 This is a graph showing the preprocessing signal curves of three aluminum plate specimens with different thicknesses in Example 2; Figure 7 This is the first intersection point in the preprocessing signal curves of the aluminum plate specimen. Figure 8 This is the second intersection point in the pretreatment signal curve of the aluminum plate specimen. Figure 9 This is the fitting curve of the specimen thickness and the amplitude of the first intersection point in Example 2; Figure 10 The curve showing the fitting relationship between the specimen thickness and the time at the first intersection point in Example 2; Figure 11 This is the fitting curve of the specimen thickness and the amplitude of the second intersection point in Example 2; Figure 12 The curve showing the fitting relationship between the specimen thickness and the time at the second intersection point in Example 2 is shown. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example 1:

[0013] For ferromagnetic materials, a method for suppressing the lift-off effect of ferromagnetic and non-ferromagnetic materials in pulsed eddy current detection includes the following steps: Step 1: Signal Preprocessing Step 1.1: Mark the area of ​​the carbon steel specimen with a thickness of 20.00 mm as the reference area, perform pulsed eddy current testing on it, and obtain the signal as the reference signal; Step 1.2: Mark the area of ​​the carbon steel specimen with a thickness of 10.00 mm as the detection area, perform pulsed eddy current detection on it, and obtain the signal as the detection signal; Step 1.3: Perform a differential operation between the reference signal obtained in Step 1.1 and the detection signal obtained in Step 1.2 to obtain the differential signal; Step 1.4: Differentiate the differential signal obtained in Step 1.3 to obtain the differential signal; Step 1.5: Divide the differential signal in Step 1.4 by the integral of the difference signal in Step 1.3 to obtain the preprocessed signal, which is denoted as the preprocessed signal; Step 1.6: Set the lift-off distance between the probe and the specimen surface to 0mm, 2mm, and 4mm respectively, while keeping the lift-off distance between the probe in the reference area and the detection area constant. Repeat steps 1.1-1.5 to obtain the pre-processed signals under different lift-off conditions, and record them as a set of pre-processed signals, such as... Figure 1 As shown; Step 2, Feature Extraction By changing the thickness of the detection area, repeat steps 1.1-1.6 to obtain preprocessed signal curves for detection area thicknesses of 10.00 mm, 12.00 mm, and 14.00 mm. Each thickness corresponds to a set of preprocessed signal curves, such as... Figure 2 As shown. Comparison Figure 2 The preprocessed signal curves shown show that: 1) the preprocessed signal curves of each group are completely overlapping, that is, the thickness is the same and the curves with different extraction points are completely overlapping. 2) The peak value and peak time of the preprocessed signal curves differ for different thicknesses. The peak value decreases with increasing specimen thickness, while the peak time increases with increasing specimen thickness. Therefore, both the peak value and peak time are used as characteristic quantities for defect assessment of ferromagnetic materials.

[0014] Step 3: Curve Fitting The thickness of the detection area was set to 10.00 mm, 12.00 mm, 14.00 mm, 16.00 mm, and 18.00 mm. Steps 1 and 2 were repeated to obtain the preprocessed signal curves. The peak value and peak time of the curves with different thicknesses were extracted, and the results are shown in Tables 1 and 2, respectively. Table 1. Peak values ​​of preprocessed signal curves for different carbon steel thicknesses

[0015] Table 2 Peak time of preprocessed signal curves for different carbon steel thicknesses

[0016]

[0017] As shown in Tables 1 and 2, the peak value and peak time of the preprocessed signal curves differ for different thicknesses. The peak value decreases with increasing specimen thickness, while the peak time increases with increasing specimen thickness. A first-order polynomial is used to fit the relationship between the peak value and the specimen thickness; the fitting equation is shown in equation (1), and the fitted curve is shown in... Figure 3 Similarly, the relationship between peak time and specimen thickness is fitted using a first-order polynomial, and the fitting equation is shown in equation (2). The fitting curve is shown in equation (2). Figure 4 .Depend on Figure 3 and Figure 4 It can be seen that both peak value and peak time are characteristic quantities for evaluating defects in ferromagnetic materials, and peak time has better linearity with specimen thickness.

[0018] f ( h ) = -3.242 * 10 -6 * h +6.562*10 -5 (1) f ( h )=0.005 * h -0.02615 (2) In the formula, h Indicates the thickness of the specimen.

[0019] Step 4: Verification The probe was placed on a 17.00 mm thick specimen to verify the accuracy of the characteristic quantity in assessing the specimen thickness. First, the detection signal was acquired. Then, step 3 was repeated to acquire the characteristic quantity of the detection signal from the device under test, where the peak value was 1.1685*10. -5The peak time was 0.00425 s. Substituting the peak time into equation (1), the calculated specimen thickness was 16.64 mm, with a thickness assessment error of 2.11%. Substituting the peak time into equation (2), the calculated specimen thickness was 17.03 mm, with a thickness assessment error of 0.17%. All of the above errors are within the allowable range, indicating that both characteristic quantities can be used for quantitative assessment of defects in ferromagnetic materials, and the peak time has higher quantitative accuracy.

[0020] Example 2: For nonferromagnetic materials, a method for suppressing the lift-off effect of ferromagnetic and nonferromagnetic materials in pulsed eddy current detection includes the following steps: Step 1: Signal Preprocessing Step 1.1: Mark the area of ​​the 20.00mm thick aluminum plate specimen as the reference area, perform pulsed eddy current testing on it, and obtain the signal as the reference signal; Step 1.2: Mark the 10.00mm thick aluminum plate specimen area as the detection area, perform pulsed eddy current detection on it, and acquire the signal as the detection signal; Step 1.3: Perform a differential operation between the reference signal obtained in Step 1.1 and the detection signal obtained in Step 1.2 to obtain the differential signal; Step 1.4: Differentiate the differential signal obtained in Step 1.3 to obtain the differential signal; Step 1.5: Divide the differential signal in Step 1.4 by the integral of the difference signal in Step 1.3 to obtain the preprocessed signal, which is referred to as the preprocessed signal in this patent. Step 1.6: Set the lift-off distance between the probe and the specimen surface to 0mm, 2mm, and 4mm respectively, while keeping the lift-off distance between the probe in the reference area and the detection area constant. Repeat steps 1.1-1.5 to obtain the pre-processed signals under different lift-off conditions, and record them as a set of pre-processed signals, such as... Figure 5 As shown; Step 2, Feature Extraction By changing the thickness of the detection area, repeat steps 1.1-1.6 to obtain preprocessed signal curves for detection area thicknesses of 10.00 mm, 12.00 mm, and 14.00 mm. Each thickness corresponds to a set of preprocessed signal curves, such as... Figure 6 As shown. Analysis Figure 6 The preprocessed signal curve shown reveals the following: 1) Preprocessed signals at the same thickness have two intersection points besides the starting point, denoted as the first intersection point and the second intersection point, respectively. Figure 7 and Figure 8 As shown, the first and second intersection points do not change with the lift-off. 2) The amplitude and time of the first crossover point of the preprocessed signal curves differ from those of the second crossover point for different thicknesses. The amplitude and time of both the first and second crossover points increase with increasing thickness of the non-ferromagnetic specimen. Therefore, the amplitude and time of both the first and second crossover points can be used for defect assessment of non-ferromagnetic specimens. Step 3: Curve Fitting The thicknesses of the detection areas were set to 10.00 mm, 12.00 mm, 14.00 mm, 16.00 mm, and 18.00 mm. Steps 1 and 2 were repeated to obtain the preprocessed signal curves. The amplitude and amplitude-time of the first crossover point, and the amplitude and amplitude-time of the second crossover point, for curves of different thicknesses were extracted. The results are shown in Tables 3, 4, 5, and 6, respectively. Table 3. Amplitude of the first crossover point of the preprocessed signal curves under different aluminum plate thicknesses.

[0021] Table 4. Time of the first crossover point of the preprocessed signal curves under different aluminum plate thicknesses.

[0022] Table 5. Amplitude of the second crossover point of the preprocessed signal curves under different aluminum plate thicknesses.

[0023] Table 6. Second crossover time of preprocessed signal curves under different aluminum plate thicknesses

[0024] Tables 3, 4, 5, and 6 show that the amplitude and time of the first and second crossover points increase with increasing specimen thickness. A linear polynomial is used to fit the relationship between the amplitude of the first crossover point and the specimen thickness; the fitting equation is shown in equation (3), and the fitting curve is shown in... Figure 9 The relationship between the time at the first intersection point and the specimen thickness was fitted using a first-order polynomial. The fitting equation is shown in equation (4), and the fitting curve is shown in equation (5). Figure 10 Similarly, the relationship between the amplitude of the second cross point and the specimen thickness is fitted using a first-order polynomial. The fitting equation is shown in equation (5), and the fitting curve is shown in equation (6). Figure 11 The relationship between the time at the second intersection point and the specimen thickness was fitted using a first-order polynomial. The fitting equation is shown in equation (6), and the fitting curve is shown in equation (7). Figure 12 .Depend on Figure 9 As shown in -12, the amplitude and time of the first crossover point and the amplitude and time of the second crossover point can both be used as characteristic quantities for the assessment of defects in non-magnetic materials, and the linearity between the time of the second crossover point and the thickness of the specimen is better.

[0025] f (h = 3.86 * 10 -6 * h -7.304*10 -5 (3) f ( h ) = 0.0002125 * h + 0.001925 (4) f ( h ) = 0.01712*10 -5 * h -0.3502*10 -5 (5) f ( h ) = 0.0006 * h +0.0093 (6) Step 4: Verification The probe was placed on an aluminum specimen with a thickness of 17.00 mm to verify the accuracy of the characteristic quantity in assessing the specimen thickness. First, the detection signal was acquired. Then, step 3.1 was repeated to acquire the characteristic quantity of the detection signal from the device under test, where the amplitude at the first crossover point was -0.7944*10. -5 The time of the first crossover point is 0.0055s, and the amplitude of the second crossover point is -0.0607*10. -5 The second crossover time is 0.0195s. Substituting the amplitude of the first crossover point into equation (3), the calculated specimen thickness is 16.82mm, with a thickness assessment error of 1.06%; substituting the time of the first crossover point into equation (4), the calculated specimen thickness is 16.86mm, with a thickness assessment error of 0.82%. Substituting the amplitude of the second crossover point into equation (5), the calculated specimen thickness is 16.91mm, with a thickness assessment error of 0.53%; substituting the time of the second crossover point into equation (6), the calculated specimen thickness is 17.00mm, with a thickness assessment error of 0.00%. This shows that all four characteristic quantities can be used for quantitative assessment of defects in non-ferromagnetic materials, and the quantitative accuracy of the second crossover time is higher.

[0026] In summary, the method described in this invention is applicable to defect detection in equipment made of both ferromagnetic and non-ferromagnetic materials, and offers high detection accuracy. Based on the above-described preferred embodiments of this invention, and through the foregoing description, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification but must be determined according to the scope of the claims.

Claims

1. A method for suppressing the lift-off effect of ferromagnetic and non-ferromagnetic materials in pulsed eddy current detection, characterized in that, Includes the following steps: Step 1: Signal Preprocessing The pre-processed signals of specimens of the same thickness at different lift-off distances were obtained and recorded as a set of pre-processed signal curves. Step 2, Feature Extraction By varying the thickness of the test area of ​​the specimen and repeating step 1, preprocessed signal curves were obtained for different thicknesses, with each thickness corresponding to a set of preprocessed signal curves. Comparing all the preprocessed signal curves, the following conclusions were drawn: 1) For ferromagnetic materials, the pre-processing signal curves of each group completely overlap, that is, the pre-processing signal curves with the same thickness and different extractions completely overlap; the peak value and peak time of the pre-processing signal curves corresponding to different thicknesses are different, and the peak value tends to decrease with the increase of specimen thickness, while the peak time tends to increase with the increase of specimen thickness; therefore, the peak value and peak time are both used as characteristic quantities for defect assessment of ferromagnetic materials; for non-ferromagnetic materials, the pre-processing signal curves at the same thickness have two intersection points in addition to the starting point, which are denoted as the first intersection point and the second intersection point, respectively. The positions of the first intersection point and the second intersection point do not change with the change of extraction. 2) The amplitude and time of the first crossover point and the amplitude and time of the second crossover point increase with the increase of the thickness of the non-ferromagnetic specimen; therefore, the amplitude and time of the first crossover point and the amplitude and time of the second crossover point can both be used as characteristic quantities for defect evaluation of non-ferromagnetic specimens. Step 3: Fitting the curve For a standard specimen with a known thickness, repeat steps 1 and 2 to obtain the corresponding characteristic quantities. Fit these quantities using a first-order polynomial to obtain the fitting curve and equation for each characteristic quantity versus the specimen thickness. Specifically, this includes the following steps: Step 3.1: Perform pulsed eddy current testing on the reference area of ​​a standard specimen of known thickness to obtain a reference signal; Step 3.2: Perform pulsed eddy current testing on other areas of the standard specimen with known thickness to obtain the detection signal; Step 3.3: Perform a differential operation between the reference signal obtained in Step 3.1 and the detection signal obtained in Step 3.2 to obtain the differential signal; Step 3.4: Differentiate the differential signal obtained in Step 3.3 to obtain the differential signal; Step 3.5: Divide the differential signal from Step 3.4 by the integral of the difference signal from Step 3.3 to obtain the preprocessed signal; Step 3.6: Change the lift-off distance between the probe and the specimen surface, while keeping the lift-off distance of the probe in the reference area and the detection area the same. Repeat steps 3.1-3.5 to obtain the pre-processed signals under different lift-off conditions, and record them as a set of pre-processed signals. Step 3.7: Fitting 1) For ferromagnetic materials, extract the peak value and peak time of the preprocessed signal curves with different thicknesses, and fit them with a first-order polynomial to obtain the fitting curves and equations of the peak value and the specimen thickness and the peak time and the specimen thickness, respectively. 2) For non-ferromagnetic materials, extract the amplitude of the first crossover point, the time of the first crossover point, the amplitude of the second crossover point, and the time of the second crossover point of the preprocessed signal curves with different thicknesses, and fit them with a first-order polynomial to obtain the fitting curve and equation of each of the above feature quantities with the specimen thickness. Step 4: Defect Assessment The probe is placed on the test device with the same material as the standard test piece to perform pulsed eddy current testing, and the characteristic quantities of the test device's detection signal are obtained. The characteristic quantities are then substituted into the corresponding fitting curve obtained in step 3 to calculate the thickness of the test device and infer its defect information.

2. The method for suppressing the lift-off effect of ferromagnetic and non-ferromagnetic materials in pulsed eddy current detection according to claim 1, characterized in that: Step 1 specifically includes the following steps: Step 1.1: Mark a certain area of ​​the specimen as the reference area, perform pulsed eddy current detection on it, and obtain the signal as the reference signal; Step 1.2: Mark other areas of the specimen as the detection area, perform pulsed eddy current detection on them, and acquire the signal as the detection signal; Step 1.3: Perform a differential operation between the reference signal obtained in Step 1.1 and the detection signal obtained in Step 1.2 to obtain the differential signal; Step 1.4: Differentiate the differential signal obtained in Step 1.3 to obtain the differential signal; Step 1.5: Divide the differential signal in Step 1.4 by the integral of the difference signal in Step 1.3 to obtain the preprocessed signal, which is denoted as the preprocessed signal; Step 1.6: Change the lift-off distance between the probe and the specimen surface, while keeping the lift-off distance of the probe in the reference area and the detection area the same. Repeat steps 1.1-1.5 to obtain the pre-processed signals under different lift-off conditions, and record them as a set of pre-processed signal curves.

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