Coating aging degree in-situ nondestructive evaluation method based on photoacoustic spectroscopy

Abstract

The invention discloses a coating aging degree in-situ nondestructive evaluation method based on photoacoustic spectroscopy, which relates to the technical field of material detection, and comprises the following steps: collecting and preprocessing multi-source data, carrying out discrete cross-correlation operation on photoacoustic signals and laser intensity, generating a discrete cross-correlation sequence, and calculating an autocorrelation sequence of a laser intensity sequence. Defining the maximum value of the self-correlation sequence at the zero lag as a self-correlation peak value, and calculating discrete pulse response based on the cross-correlation sequence and the self-correlation peak value; performing fast Fourier transform on the discrete pulse response, and calculating a normalized frequency response amplitude and a normalized frequency response phase, identifying a peak frequency of the normalized frequency response amplitude, calculating a relaxation time constant based on the peak frequency, generating a theoretical phase according to the relaxation time constant, and calculating a corrected phase using a linear combination in combination with the phase and the theoretical phase. The sensitivity of aging degree identification is enhanced, and the revealing ability of the multi-scale aging dynamics process of the coating is improved.

Description

Technical Field

[0001] This invention relates to the field of materials testing technology, and in particular to an in-situ non-destructive assessment method for the aging degree of coatings based on photoacoustic spectroscopy. Background Technology

[0002] With the development of materials science and testing technology, coatings have been widely used in fields such as construction, transportation, aerospace and energy equipment. Their service life and performance stability are directly related to structural safety and efficiency. During long-term use, coating materials are subject to various environmental factors such as temperature, ultraviolet radiation, humidity and mechanical stress, which gradually lead to aging.

[0003] Existing in-situ non-destructive assessment methods for coating aging based on photoacoustic spectroscopy still have shortcomings. Traditional signal processing often uses single feature extraction methods in the time or frequency domains, which are easily affected by environmental noise and make it difficult to accurately capture aging-related dynamic characteristics. Existing methods often require manually setting thresholds to determine the degree of aging. This method, which relies on empirical parameters, is easily affected by different material systems, environmental conditions, and instrument differences, and lacks universality and objectivity. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides an in-situ non-destructive assessment method for the aging degree of coatings based on photoacoustic spectroscopy. This method solves the problems of traditional signal processing methods that often use single feature extraction in the time or frequency domains, which are easily affected by environmental noise and are difficult to accurately capture aging-related dynamic features. Existing methods often require manually setting thresholds to determine the aging degree. This method, which relies on empirical parameters, is easily affected by different material systems, environmental conditions, and instrument differences, and lacks universality and objectivity.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides an in-situ non-destructive assessment method for the aging degree of coatings based on photoacoustic spectroscopy, comprising, Collect and preprocess multi-source data, perform discrete cross-correlation operation on photoacoustic signal and laser intensity to generate discrete cross-correlation sequence, calculate autocorrelation sequence of laser intensity sequence, define the maximum value of autocorrelation sequence at zero hysteresis as autocorrelation peak value, and calculate discrete impulse response based on cross-correlation sequence and autocorrelation peak value. Perform a Fast Fourier Transform on the discrete impulse response and calculate the normalized frequency response amplitude and phase. Identify the peak frequency of the normalized frequency response amplitude. Based on the peak frequency, calculate the relaxation time constant. Generate the theoretical phase based on the relaxation time constant. Combine the phase and the theoretical phase and use a linear combination to calculate the corrected phase. Use the normalized frequency response amplitude and the corrected phase to calculate the corrected frequency response and convert it to angular frequency. The imaginary part is extracted from the corrected frequency response, the target vector is constructed, the logarithmic step size is calculated, the relaxation time grid points are calculated based on the logarithmic step size, the kernel matrix is ​​calculated using the angular frequency and the relaxation time grid points, and a system of linear equations is constructed by combining the target vector and the kernel matrix to generate the relaxation time distribution. By combining the logarithmic step size and relaxation time distribution, the aging intensity index is calculated, and the loss is assessed. A visual interface is then constructed to display the loss assessment results.

[0007] As a preferred embodiment of the in-situ non-destructive evaluation method for coating aging degree based on photoacoustic spectroscopy described in this invention, the step of defining the maximum value of the autocorrelation sequence at zero hysteresis as the autocorrelation peak value, and calculating the discrete impulse response based on the cross-correlation sequence and the autocorrelation peak value, includes: The photoacoustic signal and laser intensity are sorted in chronological order to generate photoacoustic signal sequence and laser intensity sequence, and then a fast convolution algorithm is used to perform discrete cross-correlation operation to generate cross-correlation sequence; Calculate the autocorrelation sequence of the laser intensity sequence, and use peak extraction to define the maximum value of the autocorrelation sequence at zero hysteresis as the autocorrelation peak. The discrete impulse response is calculated based on the cross-correlation sequence and autocorrelation peak value.

[0008] As a preferred embodiment of the in-situ non-destructive assessment method for coating aging degree based on photoacoustic spectroscopy described in this invention, wherein: identifying the peak frequency of the normalized frequency response amplitude includes: Perform a Fast Fourier Transform on the discrete impulse response to generate a complex frequency response, and then normalize it to generate a normalized frequency response. Calculate the normalized frequency response amplitude and normalized frequency response phase respectively; The frequency range for photoacoustic spectroscopy detection is set, and the peak frequency of the normalized frequency response amplitude is identified by the maximum value search method.

[0009] As a preferred embodiment of the in-situ non-destructive evaluation method for coating aging degree based on photoacoustic spectroscopy described in this invention, the method includes: combining the phase and theoretical phase, using a linear combination to calculate the corrected phase, using the normalized frequency response amplitude and the corrected phase to calculate the corrected frequency response, and converting it into angular frequency, including: Calculate the relaxation time constant based on the peak frequency; The theoretical phase is generated using the arctangent function based on the relaxation time constant; The corrected phase is calculated using a linear combination method by combining the phase and the theoretical phase. The corrected frequency response is calculated using the normalized frequency response amplitude and the corrected phase. The discrete frequency extraction method is used to extract frequency points from the corrected frequency response and convert them into angular frequencies to generate the corrected frequency response.

[0010] As a preferred embodiment of the in-situ non-destructive evaluation method for coating aging degree based on photoacoustic spectroscopy described in this invention, the method includes: calculating the kernel matrix using angular frequency and relaxation time grid points, and constructing a system of linear equations by combining the target vector and the kernel matrix to generate the relaxation time distribution, including: Based on angular frequency, the imaginary part is extracted from the corrected frequency response to construct the target vector; Based on the frequency range of photoacoustic spectroscopy detection, the minimum and maximum values ​​of relaxation time are set, a logarithmic time grid is generated through logarithmic transformation, and the step size of the logarithmic time grid is calculated. The relaxation time grid points are calculated based on the step size of the logarithmic time grid. The kernel matrix is ​​calculated using angular frequency and relaxation time grid points; By combining the target vector and the kernel matrix, a system of linear equations is constructed; The nonnegative least squares method is used to solve the linear equation system and generate the relaxation time distribution.

[0011] As a preferred embodiment of the in-situ non-destructive assessment method for coating aging degree based on photoacoustic spectroscopy described in this invention, the step of calculating the aging intensity index and performing loss assessment by combining logarithmic step size and relaxation time distribution includes: The aging intensity index is calculated by combining the logarithmic step size and relaxation time distribution; The classification threshold is set using the empirical threshold method. The aging intensity index is compared with the classification threshold. When the aging intensity index is less than the classification threshold, it is judged as an undamaged state; otherwise, it is judged as a damaged state.

[0012] As a preferred embodiment of the in-situ non-destructive assessment method for coating aging based on photoacoustic spectroscopy described in this invention, wherein: the construction of a visual interface to display the loss assessment results includes: Use the visualization tool Matplotlib to build a visualization interface to display the loss assessment results in real time; Users who have passed real-name verification are allowed to view it.

[0013] As a preferred embodiment of the in-situ non-destructive evaluation method for coating aging degree based on photoacoustic spectroscopy described in this invention, the step of collecting multi-source data and performing preprocessing includes: Data from multiple sources is collected through sensors and then denoised and normalized. The sensor includes a microphone and a photodiode sensor; The multi-source data includes photoacoustic signals and laser intensity data.

[0014] In a second aspect, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, it implements any step of the in-situ non-destructive evaluation method for coating aging degree based on photoacoustic spectroscopy as described in the first aspect of the present invention.

[0015] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the in-situ non-destructive evaluation method for the degree of aging of coatings based on photoacoustic spectroscopy as described in the first aspect of the present invention.

[0016] The beneficial effects of this invention are as follows: This invention enhances the sensitivity of aging degree identification by combining the cross-correlation between photoacoustic signals and laser intensity with the autocorrelation peak value of laser intensity, and improves the ability to reveal the multi-scale aging dynamics of coatings by correcting the imaginary part of the frequency response and combining the logarithmic step size and relaxation time grid points. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of the in-situ non-destructive assessment method for coating aging based on photoacoustic spectroscopy in Example 1.

[0019] Figure 2 This is a flowchart of the relaxation time distribution analysis in Example 1. Detailed Implementation

[0020] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0021] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0023] Example 1, the first embodiment of the present invention, provides an in-situ non-destructive assessment method for the aging degree of coatings based on photoacoustic spectroscopy, including the following steps: Collect and preprocess data from multiple sources; Specifically, this involves collecting and preprocessing multi-source data, including: Data from multiple sources is collected through sensors and then denoised and normalized. The sensor includes a microphone (e.g., Panasonic, for capturing photoacoustic signals in the audible frequency range) and a photodiode sensor (e.g., a photodetector for measuring the intensity of a laser). The multi-source data includes photoacoustic signals and laser intensity data.

[0024] Photoacoustic signals are usually generated by the photoacoustic effect, that is, after a laser irradiates a sample, the sample absorbs light energy and generates thermal expansion, thereby triggering sound waves; By acquiring data from multiple sources of sensors, not only are photoacoustic signals directly related to changes in the molecular structure of the coating obtained, but the intensity of the excitation source and environmental conditions are also combined, which helps to eliminate the bias caused by a single signal. The denoising and normalization methods can weaken the influence of external electromagnetic interference and system noise, while eliminating the problem of amplitude inconsistency caused by differences in sensor sensitivity.

[0025] Example 2, refer to Figure 1 and Figure 2 This is the second embodiment of the present invention, which provides an in-situ non-destructive assessment method for the aging degree of coatings based on photoacoustic spectroscopy, including the following steps: Discrete cross-correlation is performed on the photoacoustic signal and the laser intensity to generate a discrete cross-correlation sequence. The autocorrelation sequence of the laser intensity sequence is calculated, and the maximum value of the autocorrelation sequence at zero hysteresis is defined as the autocorrelation peak value. Based on the cross-correlation sequence and the autocorrelation peak value, the discrete impulse response is calculated. Specifically, the maximum value of the autocorrelation sequence at zero hysteresis is defined as the autocorrelation peak. Based on the cross-correlation sequence and the autocorrelation peak, the discrete impulse response is calculated, including: The photoacoustic signal and laser intensity are sorted in chronological order to generate photoacoustic signal sequences and laser intensity sequences, respectively. A fast convolution algorithm is then used to perform discrete cross-correlation calculations to generate a cross-correlation sequence, as shown in the formula: , in This is a discrete cross-correlation sequence, representing the correlation between the photoacoustic signal and the laser intensity under hysteresis o, where o is the hysteresis index and N is the sequence length. Here is a photoacoustic signal sequence, where n is the sampling point index. Laser intensity sequence; The formula for calculating the autocorrelation sequence of a laser intensity sequence is: , in The autocorrelation sequence represents the autocorrelation value of the laser intensity sequence under hysteresis o; Peak extraction is used to define the maximum value of the autocorrelation sequence at zero hysteresis as the autocorrelation peak. Based on the cross-correlation sequence and autocorrelation peak, the discrete impulse response is calculated using the following formula: , in The discrete impulse response represents the coating's response to a unit excitation. This represents the peak value of the autocorrelation.

[0026] Cross-correlation can reveal the response characteristics of photoacoustic signals to laser excitation, avoiding ambiguities that may occur when simply observing time waveforms. By combining the results with cross-correlation, systematic biases caused by instability of the excitation source can be eliminated. The autocorrelation peak, as a normalization factor, makes the calculation of discrete impulse response independent of the absolute value of laser intensity, but rather evaluated relative to the intensity of the excitation source, thereby improving the comparability of results under different experimental conditions. Through impulse response, the characteristics of the excitation source can be distinguished from the transmission characteristics of the material itself, thus obtaining physical quantities directly related to the aging state of the coating. The impulse response can be further converted into frequency domain information through Fourier transform, thereby revealing the response characteristics of the coating at different frequencies.

[0027] Perform a Fast Fourier Transform on the discrete impulse response and calculate the normalized frequency response amplitude and phase. Identify the peak frequency of the normalized frequency response amplitude. Based on the peak frequency, calculate the relaxation time constant. Generate the theoretical phase based on the relaxation time constant. Combine the phase and the theoretical phase and use a linear combination to calculate the corrected phase. Use the normalized frequency response amplitude and the corrected phase to calculate the corrected frequency response and convert it to angular frequency. Specifically, identifying the peak frequency of the normalized frequency response amplitude includes: Performing a Fast Fourier Transform on the discrete impulse response generates a complex frequency response, representing the coating's response characteristics in the frequency domain. The formula is as follows: , in The complex frequency response is the frequency domain representation of the impulse response, which includes amplitude and phase, where f is the frequency. Where j is the sampling frequency, and j is the imaginary unit; Then, normalization is performed to generate a normalized frequency response, the formula of which is: , in For normalized complex frequency response, The frequency response was set using statistical analysis. The normalized frequency response amplitude and normalized frequency response phase are calculated separately using the following formulas: , , in To normalize the frequency response amplitude, The phase of the normalized frequency response; The frequency range for photoacoustic spectroscopy detection is defined, and the peak frequency of the normalized frequency response amplitude is identified using a maximum value search method, with the following formula: , in Peak frequency, and These are the lower limit and upper limit of the frequency range, respectively.

[0028] Time-domain signals often fail to intuitively reflect the microstructural characteristics of coating materials. However, the spectrum obtained by FFT can directly show the energy distribution and phase delay of the coating at different frequencies. Frequency domain analysis can distinguish different frequency components superimposed in the time domain, which helps to separate environmental noise from the inherent characteristics of the material. Different experiments may have differences in laser power, sensor sensitivity, or environmental background. Normalization can eliminate these differences and improve the comparability of cross-experiment data. The peak frequency corresponds to the main energy concentration point of the material structure under external excitation and can be used as a sensitive indicator of coating aging.

[0029] Furthermore, combining the phase and the theoretical phase, a linear combination is used to calculate the corrected phase. Using the normalized frequency response amplitude and the corrected phase, the corrected frequency response is calculated and converted to angular frequency, including: The relaxation time constant is calculated based on the peak frequency using the following formula: , in The relaxation time constant; Based on the relaxation time constant, the arctangent function is used to generate the theoretical phase, representing the ideal phase characteristics of the coating's thermo-elastic response, providing a reference for phase correction. The formula is as follows: , in Theoretical phase; Combining the phase and the theoretical phase, the corrected phase is calculated using a linear combination, as shown in the formula: , in To correct the phase, and These are the weights for the normalized frequency response phase and the theoretical phase, respectively. The corrected frequency response of the amplitude is calculated using the normalized frequency response amplitude and the corrected phase, using the following formula: , in The frequency response is a correction for the amplitude; The discrete frequency extraction method is used to extract frequency points from the corrected frequency response and convert them into angular frequencies to generate the corrected frequency response. The formula is as follows: , , in For frequency correction, Let k be the k-th angular frequency, and k be the frequency index. This represents the frequency point in the k-th corrected frequency response.

[0030] The difference between the theoretical phase and the actual phase can reveal the degree of deviation between the material response and the ideal model, providing a basis for analyzing the aging mechanism. The corrected frequency response can more realistically reflect the inherent response characteristics of the coating material, avoiding data distortion caused by non-ideal factors of the detection system. By using angular frequency representation, the accumulation of errors caused by limited frequency resolution in some numerical calculations can be avoided.

[0031] The imaginary part is extracted from the corrected frequency response, the target vector is constructed, the logarithmic step size is calculated, the relaxation time grid points are calculated based on the logarithmic step size, the kernel matrix is ​​calculated using the angular frequency and the relaxation time grid points, and a system of linear equations is constructed by combining the target vector and the kernel matrix to generate the relaxation time distribution. Specifically, using angular frequency and relaxation time grid points, the kernel matrix is ​​calculated. Combining the target vector and the kernel matrix, a system of linear equations is constructed to generate the relaxation time distribution, including: The imaginary part is extracted from the corrected frequency response to construct the target vector, as shown in the formula: , , in Let be the imaginary part of the k-th frequency point. For the imaginary part extraction operation, 'a' is the target vector. This is a transpose operation; Based on the frequency range of photoacoustic spectroscopy detection, the minimum and maximum values ​​of the relaxation time are set. A logarithmic time grid is generated through logarithmic transformation, and the step size of the logarithmic time grid is calculated using the following formula: , , , in The step size is the logarithmic time grid, and M is the total number of grid points. and These are the lower and upper limits of the relaxation time, respectively; The relaxation time grid points are calculated based on the step size of the logarithmic time grid, using the following formula: , in Let i be the i-th relaxation time grid point, where i is the time index; The kernel matrix is ​​calculated using the angular frequency and relaxation time grid points, as follows: , in The elements of the kernel matrix represent the imaginary part response contributions at the k-th frequency point and the i-th time point; Combining the target vector and the kernel matrix, a system of linear equations is constructed to represent the mapping relationship from the frequency domain to the time domain. The formula is as follows: , , Where A is the kernel matrix, a is the target vector, and g is the relaxation time distribution vector. This represents the distribution value at the Mth relaxation time; The nonnegative least squares method is used to solve the linear equation system and generate the relaxation time distribution.

[0032] The imaginary part of the frequency response is directly related to the energy dissipation of the system and can reflect the viscoelastic loss characteristics of the coating under external excitation. The grid point distribution covers the entire range from short-time relaxation to long-time relaxation, so that the multi-stage dynamic process during aging can be analyzed. The kernel matrix is ​​like a bridge, connecting the experimentally obtained imaginary part of the frequency domain with the potential relaxation time distribution. The complex integral relationship is expressed in matrix form, which simplifies the calculation structure and facilitates subsequent numerical solutions. The complex physical inversion problem is transformed into a linear algebra problem, which is easy to solve using mature numerical methods. The relaxation time distribution represents the probability density or energy distribution and must be non-negative. The NNLS method naturally satisfies this requirement.

[0033] By combining the logarithmic step size and relaxation time distribution, the aging intensity index is calculated, and the loss is assessed. A visual interface is then constructed to display the loss assessment results. Specifically, by combining the logarithmic step size and relaxation time distribution, the aging intensity index is calculated, and a loss assessment is performed, including: The aging intensity index is calculated by combining the logarithmic step size and relaxation time distribution, using the following formula: , in The aging strength index, The baseline relaxation time distribution, To test the relaxation time distribution of the sample, It is a non-negative function, retaining positive differences to reflect aging increments; The classification threshold is set using the empirical threshold method. The aging intensity index is compared with the classification threshold. When the aging intensity index is less than the classification threshold, it is judged as an undamaged state; otherwise, it is judged as a damaged state.

[0034] The index originates from the change in relaxation time distribution and can truly reflect the evolution of molecular kinematics and energy dissipation mechanisms with aging. Through non-negative function processing, it is ensured that the index only reflects the aging enhancement effect and is not affected by random fluctuations or measurement errors. The empirical threshold provides the dividing point for qualitative judgment. Combined with the quantitative parameter of aging intensity index, the introduction of threshold control avoids misjudgment caused by slight fluctuations and improves the reliability of the system.

[0035] Example 3, the third embodiment of the present invention, provides an in-situ non-destructive assessment method for the aging degree of coatings based on photoacoustic spectroscopy, including the following steps: Specifically, a visual interface will be built to display the loss assessment results, including: Use the visualization tool Matplotlib to build a visualization interface to display the loss assessment results in real time; Users who have passed real-name verification are allowed to view it.

[0036] The system uses graphical representations to display aging strength indices, relaxation time distribution curves, and damage classification results, making complex data readily understandable. Users can log in to the system according to their permissions to browse aging assessment data for different materials or structures, ensuring data security and controllability.

[0037] Example 4, the fourth embodiment of the present invention, provides an in-situ non-destructive assessment method for the aging degree of coatings based on photoacoustic spectroscopy, including the following steps: This embodiment also provides a computer device applicable to the in-situ non-destructive evaluation method of coating aging degree based on photoacoustic spectroscopy, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the in-situ non-destructive evaluation method of coating aging degree based on photoacoustic spectroscopy as proposed in the above embodiment.

[0038] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0039] This embodiment also provides a storage medium storing a computer program. When executed by a processor, the program implements the in-situ non-destructive evaluation method for coating aging based on photoacoustic spectroscopy as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0040] In summary, this invention enhances the sensitivity of aging degree identification by combining the cross-correlation between photoacoustic signals and laser intensity with the autocorrelation peak value of laser intensity, and improves the ability to reveal the multi-scale aging dynamics of coatings by correcting the imaginary part of the frequency response combined with the logarithmic step size and relaxation time grid points.

[0041] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A non-destructive in-situ assessment method for coating aging based on photoacoustic spectroscopy, characterized in that: include, Collect and preprocess multi-source data, perform discrete cross-correlation operation on photoacoustic signal and laser intensity to generate discrete cross-correlation sequence, calculate autocorrelation sequence of laser intensity sequence, define the maximum value of autocorrelation sequence at zero hysteresis as autocorrelation peak value, and calculate discrete impulse response based on cross-correlation sequence and autocorrelation peak value. Perform a Fast Fourier Transform on the discrete impulse response and calculate the normalized frequency response amplitude and phase. Identify the peak frequency of the normalized frequency response amplitude. Based on the peak frequency, calculate the relaxation time constant. Generate the theoretical phase based on the relaxation time constant. Combine the phase and the theoretical phase and use a linear combination to calculate the corrected phase. Use the normalized frequency response amplitude and the corrected phase to calculate the corrected frequency response and convert it to angular frequency. The imaginary part is extracted from the corrected frequency response, the target vector is constructed, the logarithmic step size is calculated, the relaxation time grid points are calculated based on the logarithmic step size, the kernel matrix is ​​calculated using the angular frequency and the relaxation time grid points, and a system of linear equations is constructed by combining the target vector and the kernel matrix to generate the relaxation time distribution. By combining the logarithmic step size and relaxation time distribution, the aging intensity index is calculated, and the loss is assessed. A visual interface is then constructed to display the loss assessment results.

2. The in-situ non-destructive assessment method for coating aging degree based on photoacoustic spectroscopy as described in claim 1, characterized in that: The step of defining the maximum value of the autocorrelation sequence at zero hysteresis as the autocorrelation peak, and calculating the discrete impulse response based on the cross-correlation sequence and the autocorrelation peak, includes: The photoacoustic signal and laser intensity are sorted in chronological order to generate photoacoustic signal sequence and laser intensity sequence, and then a fast convolution algorithm is used to perform discrete cross-correlation operation to generate cross-correlation sequence; Calculate the autocorrelation sequence of the laser intensity sequence, and use peak extraction to define the maximum value of the autocorrelation sequence at zero hysteresis as the autocorrelation peak. The discrete impulse response is calculated based on the cross-correlation sequence and autocorrelation peak value.

3. The in-situ non-destructive assessment method for coating aging degree based on photoacoustic spectroscopy as described in claim 2, characterized in that: The peak frequency of the identified normalized frequency response amplitude includes: Perform a Fast Fourier Transform on the discrete impulse response to generate a complex frequency response, and then normalize it to generate a normalized frequency response. Calculate the normalized frequency response amplitude and normalized frequency response phase respectively; The frequency range for photoacoustic spectroscopy detection is set, and the peak frequency of the normalized frequency response amplitude is identified by the maximum value search method.

4. The in-situ non-destructive assessment method for coating aging degree based on photoacoustic spectroscopy as described in claim 3, characterized in that: The process involves combining the theoretical phase and the corrected phase, calculating the corrected phase using a linear combination, calculating the corrected frequency response using the normalized frequency response amplitude and the corrected phase, and converting it to an angular frequency, including: Calculate the relaxation time constant based on the peak frequency; The theoretical phase is generated using the arctangent function based on the relaxation time constant; The corrected phase is calculated using a linear combination method by combining the phase and the theoretical phase. The corrected frequency response is calculated using the normalized frequency response amplitude and the corrected phase. The discrete frequency extraction method is used to extract frequency points from the corrected frequency response and convert them into angular frequencies to generate the corrected frequency response.

5. The in-situ non-destructive assessment method for coating aging degree based on photoacoustic spectroscopy as described in claim 4, characterized in that: The process involves using angular frequency and relaxation time grid points to calculate the kernel matrix, combining the target vector and the kernel matrix to construct a system of linear equations, and generating the relaxation time distribution, including: Extract the imaginary part from the corrected frequency response and construct the target vector; Based on the frequency range of photoacoustic spectroscopy detection, the minimum and maximum values ​​of relaxation time are set, a logarithmic time grid is generated through logarithmic transformation, and the step size of the logarithmic time grid is calculated. The relaxation time grid points are calculated based on the step size of the logarithmic time grid. The kernel matrix is ​​calculated using angular frequency and relaxation time grid points; By combining the target vector and the kernel matrix, a system of linear equations is constructed; The nonnegative least squares method is used to solve the linear equation system and generate the relaxation time distribution.

6. The in-situ non-destructive assessment method for coating aging degree based on photoacoustic spectroscopy as described in claim 5, characterized in that: The calculation of the aging intensity index and loss assessment, combining the logarithmic step size and relaxation time distribution, includes: The aging intensity index is calculated by combining the logarithmic step size and relaxation time distribution; The classification threshold is set using the empirical threshold method. The aging intensity index is compared with the classification threshold. When the aging intensity index is less than the classification threshold, it is judged as an undamaged state; otherwise, it is judged as a damaged state.

7. The in-situ non-destructive assessment method for coating aging degree based on photoacoustic spectroscopy as described in claim 6, characterized in that: The construction of a visual interface to display the loss assessment results includes: Use the visualization tool Matplotlib to build a visualization interface to display the loss assessment results in real time; Users who have passed real-name verification are allowed to view it.

8. The in-situ non-destructive assessment method for coating aging degree based on photoacoustic spectroscopy as described in claim 1, characterized in that: The collection and preprocessing of multi-source data includes: Data from multiple sources is collected through sensors and then denoised and normalized. The sensor includes a microphone and a photodiode sensor; The multi-source data includes photoacoustic signals and laser intensity data.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the in-situ non-destructive evaluation method for coating aging degree based on photoacoustic spectroscopy as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the in-situ non-destructive evaluation method for coating aging degree based on photoacoustic spectroscopy as described in any one of claims 1 to 8.

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