Thermal wave imaging coating thickness detection method

Abstract

The invention relates to a thermal wave coating thickness detection method based on step excitation, and belongs to the technical field of infrared nondestructive testing. The method comprises the following steps: continuously heating the surface of a test piece by adopting a thermal excitation source with constant power, and recording the change data of the surface temperature along with time through a radiation detector to obtain a surface temperature rise curve delta T; the method comprises the following steps of: introducing a time offset tau, performing division operation on delta T and a time square root # imgabs0 # with the offset, constructing a new thermal response function curve # imgabs1 #, and realizing accurate and rapid measurement of the coating thickness by constructing a linear or monotonous relation model between a square root at a peak moment of an f (t) curve and the coating thickness. According to the method, the dependence of a traditional method on a reference curve and complex differential calculation is avoided, the calculation process is simplified, the anti-interference capability is enhanced, and the method is suitable for measuring the thickness of a single-layer or multi-layer coating. In addition, the method can be extensively applied to detection of thermal properties, mechanical parameters and bonding quality of a coating and a substrate and depth detection of internal defects of a material, and has a wide application prospect.

Description

Technical Field

[0001] The invention relates to a thermal wave imaging coating thickness detection method based on step heating, and belongs to the technical field of infrared non-destructive testing. Background Art

[0002] With the rapid development of modern engineering technology, coatings and thin film materials, with their unique composite performance advantages, have become core technology carriers in industries such as aerospace, precision semiconductors, high-end equipment manufacturing, and new energy vehicles. By constructing a functional interface layer on the surface of the substrate, these materials impart special functions such as excellent wear resistance, corrosion resistance, thermal barrier properties, electromagnetic shielding, or optical regulation to the surface while maintaining the performance of the substrate. The indicators of these special functions show a significant correlation with the thickness of the coating. Therefore, large-area, non-contact, high-precision, and high-efficiency film thickness detection technology has become a key requirement for ensuring the quality of coating processes and has important engineering value for improving the reliability and service life of industrial products.

[0003] Traditional coating thickness detection technologies mainly include eddy current method, ultrasonic method, X-ray method and mechanical probe method, but they all have certain limitations when facing modern industrial scenarios. The eddy current method is limited by the conductive properties of the material being tested and cannot be applied to non-metallic substrate coatings; ultrasonic testing requires the use of coupling agents to achieve sound wave conduction, which poses a risk of contact contamination and has detection blind spots, and the detection resolution of thin coatings is insufficient; the X-ray method needs to meet the detection conditions of double-sided transmission of the sample, which has radiation protection safety risks and is difficult to adapt to the needs of online rapid detection; the mechanical probe method may cause damage to the coating surface due to contact measurement, and cannot meet the non-destructive testing requirements of high-value precision devices. Overall, the existing technology has inherent deficiencies in detection efficiency, applicable scenarios and operational safety, which restricts the large-scale industrial application of functional coatings. Therefore, it is urgent to develop a new generation of non-contact non-destructive testing technology.

[0004] In recent years, with the advancement of thermal physics analysis technology, thermal wave detection technology, as a new type of non-contact non-destructive testing method, has gradually become a research hotspot. This technology is based on the theory of heat conduction. It triggers the thermal response of the coating-substrate system through active thermal excitation, and combines the spatiotemporal evolution characteristics of the surface temperature field to establish a quantitative correlation model between the thermal diffusion process and the coating thickness. Compared with traditional detection methods, thermal wave technology has very special advantages: first, it uses non-contact detection to avoid physical interference with the surface being tested; second, it supports large-area rapid scanning imaging, significantly improving detection efficiency; third, it has no special requirements for the electrical properties of the material and has strong universality; fourth, through time domain and frequency domain signal analysis, multi-dimensional information such as coating thickness, interface bonding state and thermal physical parameters can be simultaneously obtained, providing strong data support for the comprehensive evaluation of coating performance.

[0005] There are three main thermal excitation methods for thermal wave technology: pulse excitation, modulation excitation, and step excitation. Pulse excitation inverts the coating thickness based on the dynamic cooling process of the specimen surface. It has the advantages of fast detection speed and intuitive physical model, but the total excitation energy is limited, the detection depth is small, and the equipment is relatively bulky and costly. Modulation excitation, also known as phase-locked excitation, obtains the coating thickness based on the phase information of the periodic temperature field on the specimen surface. It has strong anti-interference ability, but the phase and coating thickness models are non-monotonic. For a wide thickness range, multiple frequencies must be used for detection, which is complex to calibrate and difficult to ensure consistency of results. Step excitation, also known as continuous excitation, uses a constant power thermal excitation source. During thermal excitation, a radiation detector is used to record the temperature rise data on the specimen surface. Coating thickness measurement is achieved by analyzing the separation moments of the surface temperature rise curve. Compared with pulse and phase-locked excitation, step excitation has the advantages of low cost, ease of implementation, and high speed, and has a very good application prospect.

[0006] Existing methods for extracting the separation moment of the temperature rise curve using step-excitation thermal wave technology mainly include the temperature contrast method and the double logarithmic differentiation method. The temperature contrast method differs the surface temperature rise signal from the specimen and a reference signal to obtain a temperature contrast signal. The temperature contrast signal of coatings of varying thickness exhibits peak values of varying amplitudes, and the peak moments are linearly related to the coating thickness, enabling coating thickness measurement. The main drawbacks of this method are that the selection of the reference signal is affected by multiple factors, including sample state, test conditions, and human experience. This leads to complexity in implementation, poor anti-interference capabilities, and difficulty ensuring consistency. The double logarithmic differentiation method performs double logarithmic processing on the surface temperature rise and time, followed by polynomial fitting and first-order differentiation. For a semi-infinite model, the double logarithmic curve is a straight line with a slope of 1 / 2, and after first-order differentiation, it becomes a straight line with a slope of zero. For coating structures, the initial behavior of the double logarithmic curve is the same as for the semi-infinite model (a straight line with a slope of 1 / 2). As heat conduction proceeds, the curve gradually separates from the straight line with a slope of 1 / 2, influenced by the interface between the coating and the substrate. After reaching thermal equilibrium, the curves reunite. During the entire process, the first-order differential curve first rises and then falls, and the peak moment is in a linear relationship with the coating thickness, which can be used for coating thickness detection. Compared with the temperature contrast method, this method is a self-reference method, does not require an additional reference signal, the implementation process is relatively simple, and consistency is easy to ensure. However, differential processing is sensitive to noise, and detection precision and accuracy are difficult to guarantee. In addition, polynomial fitting generally requires a higher order (above 6 orders). The differential algorithm will introduce multiple peaks, requiring additional processing or manual intervention to determine which peak is truly correct. This not only increases the detection steps, but also reduces the reliability of the results. Summary of the Invention

[0007] In response to the shortcomings of the existing technology, the purpose of the present invention is to propose a thermal wave coating thickness detection method based on step excitation. By actively introducing a time offset, a new thermal response function is constructed. The new function curve has a unique and obvious peak, and the square root of the peak time is linearly mapped to the coating thickness, which can realize fast and accurate measurement of coating thickness.

[0008] The technical solutions of the present invention are as follows:

[0009] First, a simplified thermal wave coating thickness detection system is Figure 1 As shown in FIG, the thermal excitation controller 11 drives the thermal excitation source 12 to generate a rapid step heating on the surface of the specimen 14. The generated surface temperature rise signal is received by the radiation detector 13 and sent to the signal processing system 15 for data processing to obtain the coating thickness information. The thermal excitation process uses constant power continuous heating, and the radiation detector can be an array sensor or a single point detector. The thermal excitation signal, surface temperature rise curve and collected image are shown in FIG. Figure 2 shown.

[0010] Figure 3 Shown are the surface temperature rise curves produced by different coating thicknesses. Although these curves obviously vary with coating thickness, it is difficult to directly correlate these curves with thickness.

[0011] By introducing a time offset, the recorded surface temperature rise data of the specimen is divided by the square root of the time with the time offset to obtain a new thermal response function, such as Figure 4 The new thermal response function curve has a unique and obvious peak, and the square root of the peak time is linearly related to the coating thickness, as shown in Figure 5 As shown in Figure 2, based on this linear relationship, accurate and rapid measurement of coating thickness can be achieved.

[0012] The selection of the time offset is related to the coating thickness range and the thermal properties of the material, and can be optimized through theoretical calculation or experiment.

[0013] The main advantages of the present invention are:

[0014] The calculation is simple and fast, the characteristic signal is obvious and easy to extract, and the anti-interference ability is good;

[0015] No reference signal required, easy to implement and fast;

[0016] It can be extended to the detection of coating thermal properties, mechanical parameters and bonding quality;

[0017] It can be extended to deep detection of material defects. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1Schematic diagram of thermal wave coating thickness detection system

[0019] Figure 2 Schematic diagram of the excitation signal and sample surface temperature change of the step excitation thermal wave technology;

[0020] Figure 3 This is a graph showing the change in surface temperature rise versus time for different coating thicknesses using the step-excitation thermal wave technology.

[0021] Figure 4 This is a graph showing the relationship between the new thermal response function of different coating thicknesses according to an embodiment of the present invention and time;

[0022] Figure 5 is a graph showing the relationship between the square root of the peak time of the new thermal response function for different coating thicknesses and the coating thickness according to an embodiment of the present invention;

[0023] Figure 6 is a graph showing the relationship between the square root of the peak time of the new thermal response function and the coating thickness at different time offsets according to an embodiment of the present invention;

[0024] Figure 7 This is a flowchart of the implementation of the present invention for optimizing the time offset based on experimental data. DETAILED DESCRIPTION

[0025] The present invention will be further described below with reference to the accompanying drawings and related theoretical models.

[0026] In step-excitation thermal wave technology, a constant thermal excitation source is used to continuously heat the specimen surface. The thermal wave propagates from the specimen surface toward the interior. When it encounters the interface between the coating and the substrate, a portion of the thermal wave is reflected back to the surface, affecting the surface temperature rise trend. If the thermal conductivity of the substrate is greater than that of the coating, the reflected thermal wave slows the surface temperature rise; conversely, it accelerates the surface temperature rise. The time it takes for the reflected thermal wave to reach the coating surface is related to the coating thickness and the thermal properties of the material. It can be characterized by the separation point from the surface temperature rise curve of the semi-infinite thickness structure. The thinner the coating thickness, the earlier the separation moment, and vice versa.

[0027] Normally, the coating thickness is much smaller than the substrate thickness, and the substrate can be regarded as a semi-infinite thickness structure. Under step thermal excitation, the relationship between the coating surface temperature rise ΔT and time is shown in formula (1):

[0028]

[0029] Where Γ is the coating thickness, Q is the surface absorbed energy, ρ0, k0, c0, and α0 are the coating density, thermal conductivity, heat capacity, and thermal diffusivity, respectively. Γ is the thermal reflectivity, which depends on the thermal parameters of the coating and substrate materials. In this embodiment, 0 < Γ < 1 is satisfied. Figure 3The figure below shows the surface temperature rise ΔT of coating specimens with different coating thicknesses during step excitation as a function of time. In the early stages, the heat wave propagates only within the coating, and the surface temperature rise curves for different coating thicknesses overlap. As time goes by, the reflected heat wave at the interface is transmitted to the surface, causing the curves to separate. The separation moment is related to the coating thickness: the thinner the coating, the earlier the separation. Therefore, as long as the separation moment is accurately obtained, the coating thickness can be measured. However, in actual testing, accurate extraction of the separation moment is very difficult due to the influence of multiple factors such as the sampling accuracy of the surface temperature field, sampling speed, signal-to-noise ratio, and separation moment determination conditions.

[0030] To solve the above difficulties, the present invention introduces a time offset τ and constructs a new thermal response function, which is expressed as follows:

[0031]

[0032] Where τ is a positive real number. To facilitate subsequent analysis, the above formula can be further written as:

[0033]

[0034] Where S(t) is the series term in formula (1). When t approaches 0, S(t) also approaches 0, so f(t,τ) approaches 0. When t approaches +∞, S(t) converges to a constant, so f(t,τ) also approaches a constant. When t is between 0 and +∞, as t increases from 0, In the early stage, it shows an upward trend. As time t increases, The growth rate slows down and gradually approaches a constant 1. However, the continuous convergence of S(t) causes f(t,τ) to decrease, thus forming a peak. The position of the peak is related to the coating thickness and only appears once. Figure 4 The f(t, τ) function curves for coating thicknesses of 50 μm, 100 μm, 150 μm, 200 μm, 250 μm, and 300 μm, respectively, are shown in the examples of the present invention. As shown, all function curves have a unique, distinct peak, and the square root of the peak time shows a monotonic relationship with the coating thickness. Figure 5 for Figure 4 The middle curve shows the relationship between the square root of the peak time and the coating thickness. It can be seen that there is a good linear relationship between the square root of the peak time and the coating thickness. Therefore, based on this linear relationship model, a fast and accurate measurement of the coating thickness can be achieved.

[0035] The above calculation process neither relies on a reference signal nor involves differential processing, is simple, fast, easy to implement, insensitive to noise, and has strong anti-interference ability.

[0036] The influence of τ value on the linear relationship between peak time and coating thickness is further explained based on numerical calculations.

[0037] Set τ = 0.01, 0.05, 0.2, and 0.5 respectively to calculate f(t, τ). Figure 6 : The relationship curve between the square root of the peak time of the f(t, τ) function curve and the coating thickness for different τ values in the embodiment of the present invention. Figure 6 As shown in Figure 1, as τ increases, the thin coating curve deviates from the linear relationship first. This is because the duration of the unsteady heat conduction stage of the thin coating is shorter, so a smaller τ value should be set. Therefore, to ensure a better linear model, the thinner the coating, the smaller the τ value should be. It seems that a smaller τ value can be applied to a wider range of coating thickness, but from Figure 6 It can be seen that the larger the τ value, the steeper the slope, which means the higher the detection sensitivity. Therefore, when meeting the requirements of the detection range, it is hoped that the τ value is as large as possible.

[0038] In actual testing, in most cases it is impossible to accurately obtain the thermal parameters of the coating and substrate materials. Therefore, it is necessary to optimize the τ value based on the test data of the standard specimen and obtain the linear inversion model of the coating thickness.

[0039] The following is a further explanation of the optimization steps for the τ value in the experiment.

[0040] Prepare a series of standard coating specimens with varying coating thicknesses within the coating thickness range to be tested. The specimen coating thicknesses typically include the minimum and maximum values within the test range, along with two thickness values between them. Test the standard coating specimens using the same or similar test conditions, including but not limited to thermal excitation power, thermal excitation time, radiation detector parameters, and detection time.

[0041] Randomly select a smaller τ value as the initial value, calculate the new thermal response function f(t,τ) of all standard specimens based on formula (2), extract the peak time of the function curve and obtain the relationship curve between the square root of the peak time and the coating thickness. Continuously adjust τ until the relationship curve has good linearity. The above steps are as follows: Figure 7 As shown, specifically including:

[0042] Step S01: Randomly select a smaller τ value greater than zero as an initial value, such as 0.01 or smaller.

[0043] Step S02: Calculate the new thermal response function curve f(t,τ):

[0044] The surface temperature rise data of all standard specimens are calculated based on formula (2) to obtain the corresponding new thermal response function.

[0045] Step S03: Optimize τ value:

[0046] Extract the peak time of the new thermal response function curve of all standard specimens and obtain the relationship curve between the square root of the peak time and the coating thickness of the specimen. Continuously adjust the τ value until the curve has good linearity. In general, the R of the linear fit of the curve is 2 ≥0.9 is sufficient, the larger the R 2 A higher value often means better detection accuracy. In actual detection, due to the influence of noise, a linear relationship may be difficult to achieve. In this case, a smoother monotonic relationship can also meet the requirements.

[0047] Step S04: Determine the τ value and the characteristic time-coating thickness relationship curve:

[0048] The optimized τ value is used as the final value, and the relationship curve between the corresponding peak time square root and the coating thickness is calculated as the coating thickness inversion curve. The coating thickness can be detected using the τ value and the corresponding relationship curve.

[0049] from Figure 6 It can be seen that the applicable τ value has a large range, so for some coating specimens made of familiar materials, the appropriate τ value can also be selected based on experience.

[0050] The present invention is mainly used to measure coating thickness, but based on the same principles and methods, it can also be applied to the detection of other physical properties of the coating, such as the thermal properties and mechanical parameters of the film layer and the substrate, and the adhesion quality of the film layer and the substrate. The present invention can also be used for defect depth detection.

[0051] The above embodiments are only used to more clearly illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention. Those skilled in the art may modify, change and apply equivalent effects to the present invention within the scope of the claims, which all fall within the scope of protection of the present invention.

Claims

1. A coating thickness thermal wave imaging detection method, characterized in that: The following steps are involved: Step 1: Use a constant-power thermal excitation source to continuously heat the specimen surface, and use a radiation detector to record the surface temperature change data to obtain the surface temperature rise curve ΔT; Step 2: Introduce the offset τ and calculate the new thermal response function f(t,τ) according to the following formula: Among them, the offset τ is a positive real number; Step 3: Extract the peak time of the f(t,τ) curve and obtain a relationship curve between the square root value of the peak time and the coating thickness; Step 4: Use the same or similar test conditions to test the coating specimen to be tested, calculate the new thermal response function f(t,τ) and obtain the square root value of the peak time of the new function curve, and then use the relationship curve between the square root value obtained in step 3 and the coating thickness to calculate the corresponding coating thickness.

2. A coating thickness thermal wave imaging detection method according to claim 1, characterized in that: The offset τ value can be optimized through experiments as follows: Step 1: Prepare a series of standard coating specimens of the same or similar materials and different thicknesses to cover the required coating thickness range; Step 2: Use the same or similar test conditions to test the standard specimen to obtain the surface temperature rise curve; Step 3: Continuously adjust the offset τ value and calculate a new thermal response curve based on formula (1) until a good linear or monotonic relationship is shown between the square root value of the peak time of the new thermal response curve and the coating thickness.

3. According to the coating thickness thermal wave imaging detection method of claim 2, the coating thickness contained in the standard test piece should at least include the minimum value, the maximum value and a different value between the minimum and maximum values of the coating thickness range to be tested.

4. A coating thickness thermal wave imaging detection method according to claim 2, characterized in that: The relationship between the square root of the peak time and the coating thickness has a smooth monotonic relationship.

5. The coating thickness thermal wave imaging detection method according to claim 1, characterized in that: The radiation detector is a single-point detector.

6. The coating thickness thermal wave imaging detection method according to claim 1, characterized in that: The radiation detector is an array detector.

7. The coating thickness thermal wave imaging detection method according to claim 1, characterized in that: The constant power thermal excitation source includes a light heat source, a hot air flow, a resistance heat source or an electromagnetic heat source.

8. The coating thickness thermal wave imaging detection method according to claim 1, characterized in that: The method can also be used to detect the thermal properties of the coating and the substrate (such as thermal conductivity, thermal diffusivity) and the adhesion quality of the coating to the substrate.

9. The coating thickness thermal wave imaging detection method according to claim 1, characterized in that: The method can be used for deep detection of internal defects of materials.

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