In-situ non-destructive evaluation method for the degree of aging of a coating based on photoacoustic spectroscopy

Abstract

The application discloses a method for in-situ nondestructive evaluation of aging degree of paint based on photoacoustic spectrum, and relates to the technical field of material detection, which comprises the following steps: collecting multi-source data and performing pretreatment, performing discrete cross-correlation operation on photoacoustic signals and laser intensity to generate a discrete cross-correlation sequence, calculating an autocorrelation sequence of the laser intensity sequence, defining the maximum value of the autocorrelation sequence at zero lag as an autocorrelation peak value, calculating a discrete impulse response based on the cross-correlation sequence and the autocorrelation peak value, performing fast Fourier transform on the discrete impulse response, 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 correction phase by using 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 kinetics process of the coating is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of material detection, in particular to a method for in-situ non-destructive evaluation of aging degree of paint based on photoacoustic spectroscopy. BACKGROUND

[0002] With the development of material science and detection technology, paint has been widely used in the fields of construction, transportation, aerospace and energy equipment, and its service life and performance stability are directly related to the structural safety and use efficiency. The coating material will gradually age under the action of temperature, ultraviolet radiation, humidity and mechanical stress and other environmental factors during long-term use.

[0003] The existing method for in-situ non-destructive evaluation of aging degree of paint based on photoacoustic spectroscopy still has shortcomings. Traditional signal processing often uses single feature extraction method in time domain or frequency domain, which is easily disturbed by environmental noise and difficult to accurately capture the aging-related kinetic characteristics. The existing method often needs to set a threshold to determine the aging degree, which is easily affected by different material systems, environmental conditions and instrument differences, and lacks universality and objectivity. SUMMARY

[0004] In view of the above existing problems, the present application is proposed.

[0005] Therefore, the present application provides a method for in-situ non-destructive evaluation of aging degree of paint based on photoacoustic spectroscopy, which solves the problem that traditional signal processing often uses single feature extraction method in time domain or frequency domain, which is easily disturbed by environmental noise and difficult to accurately capture the aging-related kinetic characteristics. The existing method often needs to set a threshold to determine the aging degree, which is easily affected by different material systems, environmental conditions and instrument differences, and lacks universality and objectivity.

[0006] To solve the above technical problems, the present application provides the following technical solutions:

[0007] In a first aspect, the present application provides a method for in-situ non-destructive evaluation of aging degree of paint based on photoacoustic spectroscopy, which comprises,

[0008] Collecting multi-source data and preprocessing, performing discrete cross-correlation operation on photoacoustic signal and laser intensity, generating discrete cross-correlation sequence, calculating autocorrelation sequence of laser intensity sequence, defining the maximum value of autocorrelation sequence at zero lag as autocorrelation peak value, and calculating discrete impulse response based on cross-correlation sequence and autocorrelation peak value;

[0009] performing fast Fourier transform on the discrete impulse response, calculating normalized frequency response amplitude and normalized frequency response phase, identifying peak frequency of the normalized frequency response amplitude, calculating relaxation time constant based on the peak frequency, generating theoretical phase according to the relaxation time constant, calculating correction phase using linear combination combining the phase and the theoretical phase, calculating correction frequency response using the normalized frequency response amplitude and the correction phase, and converting to angular frequency;

[0010] extracting imaginary part from the correction frequency response, constructing target vector, calculating logarithmic step, calculating relaxation time grid point based on the logarithmic step, calculating kernel matrix using the angular frequency and the relaxation time grid point, constructing linear equation system combining the target vector and the kernel matrix, and generating relaxation time distribution;

[0011] combining the logarithmic step and the relaxation time distribution, calculating aging intensity index, and performing loss evaluation, and constructing visual interface to display the loss evaluation result.

[0012] As a preferred scheme of the in-situ non-destructive evaluation method for the aging degree of the coating based on photoacoustic spectrum, wherein: the maximum value of the autocorrelation sequence at zero lag is defined as the autocorrelation peak, and the discrete impulse response is calculated based on the cross-correlation sequence and the autocorrelation peak, comprising:

[0013] sequencing the photoacoustic signal and the laser intensity according to time sequence to generate photoacoustic signal sequence and laser intensity sequence, and performing discrete cross-correlation operation using fast convolution algorithm to generate cross-correlation sequence;

[0014] calculating the autocorrelation sequence of the laser intensity sequence, and using peak extraction to define the maximum value of the autocorrelation sequence at zero lag as the autocorrelation peak;

[0015] calculating the discrete impulse response based on the cross-correlation sequence and the autocorrelation peak.

[0016] As a preferred scheme of the in-situ non-destructive evaluation method for the aging degree of the coating based on photoacoustic spectrum, wherein: the identification of the peak frequency of the normalized frequency response amplitude comprises:

[0017] performing fast Fourier transform on the discrete impulse response to generate complex frequency response, and performing normalization processing to generate normalized frequency response;

[0018] respectively calculating normalized frequency response amplitude and normalized frequency response phase;

[0019] setting the frequency range of photoacoustic spectrum detection, and identifying the peak frequency of the normalized frequency response amplitude by maximum value search method.

[0020] As a preferred scheme of the in-situ non-destructive evaluation method for the aging degree of the coating based on the photoacoustic spectrum, wherein: the corrected phase is calculated by using a linear combination of the combined phase and the theoretical phase, the corrected frequency response is calculated by using the normalized frequency response amplitude and the corrected phase, and the angular frequency is converted, comprising:

[0021] Based on the peak frequency, the relaxation time constant is calculated;

[0022] According to the relaxation time constant, the theoretical phase is generated using the arctangent function;

[0023] The corrected phase is calculated by using a linear combination of the combined phase and the theoretical phase;

[0024] The corrected frequency response is calculated by using the normalized frequency response amplitude and the corrected phase;

[0025] The frequency point is extracted from the corrected frequency response using the discrete frequency extraction method, and the angular frequency is converted to generate the corrected frequency response of the frequency.

[0026] As a preferred scheme of the in-situ non-destructive evaluation method for the aging degree of the coating based on the photoacoustic spectrum, wherein: the corrected phase is calculated by using a linear combination of the combined phase and the theoretical phase, the corrected frequency response is calculated by using the normalized frequency response amplitude and the corrected phase, and the angular frequency is converted, comprising:

[0027] Based on the angular frequency, the imaginary part is extracted from the corrected frequency response of the frequency to construct the target vector;

[0028] According to the frequency range of the photoacoustic spectrum detection, the minimum and maximum values of the relaxation time are set, the logarithmic time grid is generated by logarithmic transformation, and the step size of the logarithmic time grid is calculated;

[0029] Based on the step size of the logarithmic time grid, the relaxation time grid point is calculated;

[0030] The kernel matrix is calculated using the angular frequency and the relaxation time grid point;

[0031] The linear equation set is constructed by combining the target vector and the kernel matrix;

[0032] The linear equation set is solved using the non-negative least square method to generate the relaxation time distribution.

[0033] As a preferred scheme of the in-situ non-destructive evaluation method for the aging degree of the coating based on the photoacoustic spectrum, wherein: the corrected phase is calculated by using a linear combination of the combined phase and the theoretical phase, the corrected frequency response is calculated by using the normalized frequency response amplitude and the corrected phase, and the angular frequency is converted, comprising:

[0034] The aging intensity index is calculated by combining the logarithmic step size and the relaxation time distribution;

[0035] The aging intensity index is compared with the classification threshold value by using an experience threshold method, and when the aging intensity index is less than the classification threshold value, it is determined as a non-damage state, otherwise it is determined as a damage state.

[0036] As a preferred scheme of the in-situ non-destructive evaluation method for the aging degree of paint based on photoacoustic spectrum, the visual interface is constructed to display the loss evaluation result, including:

[0037] The visual interface is constructed using the visualization tool Matplotlib to display the loss evaluation result in real time.

[0038] The user is allowed to check through real-name verification.

[0039] As a preferred scheme of the in-situ non-destructive evaluation method for the aging degree of paint based on photoacoustic spectrum, the multi-source data is collected and preprocessed, including:

[0040] The multi-source data is collected by a sensor and is subjected to denoising and normalization processing.

[0041] The sensor includes a microphone and a photodiode sensor.

[0042] The multi-source data includes photoacoustic signals and laser intensity data.

[0043] In a second aspect, the present application provides a computer device, including a memory and a processor, and the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the in-situ non-destructive evaluation method for the aging degree of paint based on photoacoustic spectrum according to the first aspect of the present application is realized.

[0044] In a third aspect, the present application provides a computer-readable storage medium, which stores a computer program, wherein: when the computer program is executed by the processor, any step of the in-situ non-destructive evaluation method for the aging degree of paint based on photoacoustic spectrum according to the first aspect of the present application is realized.

[0045] The present application has the following beneficial effects: the present application enhances the sensitivity of aging degree recognition by cross-correlation of photoacoustic signals and laser intensity and self-correlation peak value of laser intensity, and improves the revealing ability of multi-scale aging kinetics process of the coating by combining the imaginary part of the corrected frequency response with the logarithmic step and the relaxation time grid point. BRIEF DESCRIPTION OF DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0047] Figure 1 Flow chart for the method of in-situ non-destructive evaluation of the aging degree of coatings based on photoacoustic spectroscopy in Example 1.

[0048] Figure 2 Flow chart for the relaxation time distribution analysis in Example 1. DETAILED DESCRIPTION

[0049] In order to make the above-mentioned purposes, features and advantages of the present application more apparent and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings.

[0050] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application. However, the present application can be practiced in other ways different from those described herein without departing from the scope of the present application, and those skilled in the art can make similar extensions without departing from the scope of the present application, so the present application is not limited to the specific embodiments disclosed below.

[0051] Secondly, the "one embodiment" or "embodiment" referred to herein means that the specific features, structures or characteristics can be included in at least one implementation of the present application. "In one embodiment" appearing in different places in the specification does not mean the same embodiment, nor is it an independent or alternative embodiment that excludes other embodiments.

[0052] Example 1, the first embodiment of the present application, provides a method for in-situ non-destructive evaluation of the aging degree of coatings based on photoacoustic spectroscopy, comprising the following steps:

[0053] Collecting multi-source data and pre-processing;

[0054] Specifically, collecting multi-source data and pre-processing includes:

[0055] Collecting multi-source data through sensors and performing denoising and normalization processing;

[0056] The sensors include a microphone (such as Panasonic, used to capture photoacoustic signals in the audible frequency range) and a photodiode sensor (such as a photodiode, Photodetector, used to measure the intensity of laser light);

[0057] The multi-source data includes photoacoustic signals and laser intensity data.

[0058] The photoacoustic signal is usually generated by the photoacoustic effect, that is, after the sample is irradiated by laser, the sample absorbs light energy and produces thermal expansion, thereby triggering a sound wave;

[0059] By multi-source sensor acquisition, not only the photoacoustic signal directly related to the change of the molecular structure of the coating is obtained, but also the excitation source intensity and the environmental conditions are combined, which helps to eliminate the deviation caused by a single signal, and the denoising and normalization method can weaken the influence of external electromagnetic interference and system noise, and at the same time eliminate the problem of inconsistent amplitude caused by the difference in sensor sensitivity.

[0060] Embodiment 2, refer to Figure 1 and Figure 2 , the second embodiment of the present application provides a method for in-situ non-destructive evaluation of the aging degree of the coating based on photoacoustic spectroscopy, comprising the following steps:

[0061] Discrete cross-correlation operation 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, the maximum value of the autocorrelation sequence at zero lag is defined as the autocorrelation peak value, and the discrete impulse response is calculated based on the cross-correlation sequence and the autocorrelation peak value;

[0062] Specifically, the maximum value of the autocorrelation sequence at zero lag is defined as the autocorrelation peak value, and the discrete impulse response is calculated based on the cross-correlation sequence and the autocorrelation peak value, including:

[0063] The photoacoustic signal and the laser intensity are sorted in time sequence to generate a photoacoustic signal sequence and a laser intensity sequence, and a fast convolution algorithm is used for discrete cross-correlation operation to generate a cross-correlation sequence, and the formula is:

[0064] ,

[0065] Wherein is the discrete cross-correlation sequence, indicating the correlation of the photoacoustic signal and the laser intensity at lag o, o is the lag index, and N is the sequence length, is the photoacoustic signal sequence, n is the sampling point index, is the laser intensity sequence;

[0066] The autocorrelation sequence of the laser intensity sequence is calculated, and the formula is:

[0067] ,

[0068] Wherein is the autocorrelation sequence, indicating the autocorrelation value of the laser intensity sequence at lag o;

[0069] The maximum value of the autocorrelation sequence at zero lag is defined as the autocorrelation peak value by using peak value extraction;

[0070] Based on the cross-correlation sequence and the autocorrelation peak, the discrete impulse response is calculated, and the formula is:

[0071] ,

[0072] Wherein is the discrete impulse response, indicating the response of the coating to a unit excitation, is the autocorrelation peak.

[0073] Through cross-correlation, the response characteristics of the photoacoustic signal to the laser excitation can be revealed, avoiding the ambiguity that may occur when simply observing the time waveform. By combining with the cross-correlation result, systematic deviation caused by unstable excitation source can be eliminated. The autocorrelation peak as a normalization factor makes the calculation of the discrete impulse response not dependent on the absolute value of the laser intensity, but relative to the intensity of the excitation source, thereby improving the comparability of the results under different experimental conditions. Through the impulse response, the characteristics of the excitation source and the transfer characteristics of the material itself can be distinguished, so as to obtain a physical quantity directly related to the aging state of the coating. The impulse response can be further converted into frequency domain information through Fourier transform, so as to reveal the response characteristics of the coating at different frequencies.

[0074] Performing fast Fourier transform on the discrete impulse response, calculating the normalized frequency response amplitude and the normalized frequency response phase, identifying the peak frequency of the normalized frequency response amplitude, based on the peak frequency, calculating the relaxation time constant, generating a theoretical phase according to the relaxation time constant, combining the phase and the theoretical phase, using 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;

[0075] Specifically, identifying the peak frequency of the normalized frequency response amplitude includes:

[0076] Performing fast Fourier transform on the discrete impulse response to generate a complex frequency response representing the response characteristics of the coating in the frequency domain, and the formula is:

[0077] ,

[0078] Wherein is the complex frequency response, indicating the frequency domain representation of the impulse response, including amplitude and phase, and f is the frequency, is the sampling frequency, and j is the imaginary unit;

[0079] And performing normalization processing to generate a normalized frequency response, and the formula is:

[0080] ,

[0081] Wherein is the normalized complex frequency response, is the reference frequency response, which is set using statistical analysis method;

[0082] The normalized frequency response amplitude and the normalized frequency response phase are calculated respectively, and the formula is:

[0083] ,

[0084] ,

[0085] wherein is the normalized frequency response amplitude, is the normalized frequency response phase;

[0086] The frequency range of the photoacoustic spectrum detection is set, and the peak frequency of the normalized frequency response amplitude is identified by the maximum value search method, and the formula is:

[0087] ,

[0088] wherein is the peak frequency, and are the lower limit of the frequency range and the upper limit of the frequency range respectively.

[0089] The time domain signal is often difficult to directly reflect the microstructure characteristics of the coating material, and the frequency 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 is helpful to separate environmental noise and material inherent characteristics. Different experiments may have differences in laser power, sensor sensitivity or environmental background, and normalization processing can eliminate these differences and improve the comparability of cross-experimental data. The peak frequency corresponds to the main energy concentration point of the material structure under external excitation, which can be used as a sensitive index of coating aging.

[0090] Further, the corrected phase is calculated using linear combination combined with the phase and the theoretical phase, and the corrected frequency response is calculated using the normalized frequency response amplitude and the corrected phase, and is converted into an angular frequency, including:

[0091] Based on the peak frequency, the relaxation time constant is calculated, and the formula is:

[0092] ,

[0093] wherein is the relaxation time constant;

[0094] According to the relaxation time constant, the inverse tangent function is used to generate the theoretical phase, which represents the ideal phase characteristics of the coating thermal-elastic response, and provides a reference for phase correction, and the formula is:

[0095] ,

[0096] wherein theoretical phase;

[0097] Combining the phase and the theoretical phase, the correction phase is calculated using linear combination, and the formula is:

[0098] ,

[0099] wherein is the correction phase, and are the weight of the normalized frequency response phase and the weight of the theoretical phase, respectively;

[0100] Using the normalized frequency response amplitude and the correction phase, the correction frequency response of the amplitude is calculated, and the formula is:

[0101] ,

[0102] wherein is the correction frequency response of the amplitude;

[0103] Using the discrete frequency extraction method to extract the frequency points from the correction frequency response and converting them into angular frequencies, the correction frequency response of the frequency is generated, and the formula is:

[0104] ,

[0105] ,

[0106] wherein is the correction frequency response of the frequency, is the kth angular frequency, k is the frequency index, is the frequency point in the kth correction frequency response.

[0107] The difference between the theoretical phase and the actual phase can reveal the deviation of the material response from the ideal model, providing a basis for analyzing the aging mechanism. The corrected frequency response can more truly reflect the inherent response characteristics of the coating material, avoiding data distortion caused by non-ideal factors of the detection system. By expressing in angular frequency, error accumulation caused by limited frequency resolution in part of the numerical calculation can be avoided.

[0108] The imaginary part is extracted from the corrected frequency response to construct a target vector, the logarithmic step is calculated, the relaxation time grid points are calculated based on the logarithmic step, the kernel matrix is calculated using the angular frequency and the relaxation time grid points, and the relaxation time distribution is generated by constructing a linear equation system combining the target vector and the kernel matrix;

[0109] Specifically, the kernel matrix is calculated using the angular frequency and the relaxation time grid points, and the relaxation time distribution is generated by constructing a linear equation system combining the target vector and the kernel matrix, including:

[0110] The imaginary part is extracted from the corrected frequency response of the frequency to construct a target vector, and the formula is:

[0111] ,

[0112] ,

[0113] wherein is the imaginary part value of the kth frequency point, is the imaginary part operation, a is the target vector, and T is the transpose operation;

[0114] According to the frequency range of photoacoustic spectrum detection, the minimum and maximum values of the relaxation time are set, the logarithmic time grid is generated by logarithmic transformation, and the step size of the logarithmic time grid is calculated, and the formula is:

[0115] , ,

[0117] ,

[0118] wherein is the step size of the logarithmic time grid, M is the total number of grid points, and are the lower and upper limits of the relaxation time, respectively;

[0119] Based on the step size of the logarithmic time grid, the relaxation time grid points are calculated, and the formula is:

[0120] ,

[0121] wherein is the i th relaxation time grid point, and i is the time index;

[0122] Using the angular frequency and the relaxation time grid point, the kernel matrix is calculated, and the formula is:

[0123] ,

[0124] wherein is an element of the kernel matrix, indicating the imaginary part response contribution of the kth frequency point and the i th time point;

[0125] Combined with the target vector and the kernel matrix, a linear equation is constructed, indicating the mapping relationship from the frequency domain to the time domain, and the formula is:

[0126] ,

[0127] ,

[0128] wherein A is the kernel matrix, a is the target vector, g is the relaxation time distribution vector, is the distribution value at the Mth relaxation time.

[0129] The non-negative least squares method is used to solve the linear equation set, and a relaxation time distribution is generated.

[0130] 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 full range from short relaxation to long relaxation, so that the multi-stage kinetic process in the aging process can be analyzed, the kernel matrix serves as a bridge to link the frequency domain imaginary part obtained by the experiment and the potential relaxation time distribution, the complex integral relationship is expressed in the form of a matrix, which simplifies the calculation structure and facilitates subsequent numerical solution, the complex physical inversion problem is converted into a linear algebra problem, which is convenient for solving by using mature numerical methods, the relaxation time distribution represents the probability density or energy distribution, which is necessarily non-negative, and the NNLS method naturally meets this requirement.

[0131] In combination with the logarithmic step length and the relaxation time distribution, the aging intensity index is calculated, and loss evaluation is performed, and a visual interface is constructed to display the loss evaluation result;

[0132] Specifically, in combination with the logarithmic step length and the relaxation time distribution, the aging intensity index is calculated, and loss evaluation is performed, including:

[0133] In combination with the logarithmic step length and the relaxation time distribution, the aging intensity index is calculated, and the formula is:

[0134] ,

[0135] Wherein is the aging intensity index, is the baseline relaxation time distribution, is the relaxation time distribution of the test sample, is a non-negative function, and a positive difference value is reserved to reflect the aging increment;

[0136] An empirical threshold method is used to set a classification threshold, and the aging intensity index is compared with the classification threshold, when the aging intensity index is less than the classification threshold, it is determined that the state is lossless, otherwise it is determined that the state is damaged.

[0137] The index is derived from the change of the relaxation time distribution, and can truly reflect the evolution of the molecular kinematics and energy dissipation mechanism with aging, and through the non-negative function processing, it is guaranteed that the index only reflects the aging enhancement effect, and is not affected by random fluctuations or measurement errors, the empirical threshold provides a demarcation point for qualitative judgment, and in combination with the aging intensity index, the threshold control is introduced, so that the misjudgment caused by slight fluctuations is avoided, and the system reliability is improved.

[0138] Embodiment 3 is a third embodiment of the application, which provides a coating aging degree in-situ nondestructive evaluation method based on photoacoustic spectrum, comprising the following steps:

[0139] Specifically, the visual interface is constructed to display the loss evaluation result, including:

[0140] The visual interface is constructed using the visualization tool Matplotlib to display the loss evaluation result in real time.

[0141] The user who passes the real-name verification is allowed to check.

[0142] The aging intensity index, the relaxation time distribution comparison curve and the damage classification result are displayed in a graphical manner, so that the complex data is clear at a glance, and the user can log in the system according to the permission to browse the aging evaluation data of different materials or structures, and the data security and controllability are ensured.

[0143] Embodiment 4 is a fourth embodiment of the present application, which provides a photoacoustic spectrum-based in-situ nondestructive evaluation method for aging degree of paint, including the following steps:

[0144] The embodiment also provides a computer device suitable for the photoacoustic spectrum-based in-situ nondestructive evaluation method for aging degree of paint, 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 photoacoustic spectrum-based in-situ nondestructive evaluation method for aging degree of paint provided in the above embodiment.

[0145] The computer device can be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner. The wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the computer device. In addition, the input device can be an external keyboard, touchpad or mouse, etc.

[0146] The embodiment also provides a storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method for in-situ nondestructive evaluation of coating aging degree based on photoacoustic spectrum proposed in the above embodiment; the storage medium can be implemented by any type of volatile or nonvolatile storage device or combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0147] In summary, the present application enhances the sensitivity of aging degree identification by cross-correlation of photoacoustic signal and laser intensity and self-correlation peak of laser intensity, and improves the revealing ability of multi-scale aging kinetic process of coating by combining the imaginary part of frequency response with logarithmic step and relaxation time grid points.

[0148] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not limit the present application, and although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application, and all of them should be covered in the scope of the claims of the present application.

Claims

1. A method for in-situ non-destructive evaluation of the degree of ageing of a coating based on photoacoustic spectroscopy, characterised in that: comprising, collecting multi-source data and preprocessing, performing discrete cross-correlation operation on photoacoustic signals and laser intensity, generating discrete cross-correlation sequence, calculating autocorrelation sequence of laser intensity sequence, defining maximum value of autocorrelation sequence at zero lag as autocorrelation peak value, calculating discrete impulse response based on cross-correlation sequence and autocorrelation peak value; performing fast Fourier transform on discrete impulse response, calculating normalized frequency response amplitude and normalized frequency response phase, identifying peak frequency of normalized frequency response amplitude, calculating relaxation time constant based on peak frequency, generating theoretical phase according to relaxation time constant, calculating correction phase using linear combination combined with phase and theoretical phase, calculating correction frequency response using normalized frequency response amplitude and correction phase, and converting to angular frequency; extracting imaginary part from correction frequency response, constructing target vector, calculating logarithmic step, calculating relaxation time grid point based on logarithmic step, calculating kernel matrix using angular frequency and relaxation time grid point, constructing linear equation system combined with target vector and kernel matrix, and generating relaxation time distribution; combining logarithmic step and relaxation time distribution, calculating aging intensity index, and performing loss evaluation, constructing visual interface to display loss evaluation result; combining logarithmic step and relaxation time distribution, calculating aging intensity index, and performing loss evaluation, comprising: combining logarithmic step and relaxation time distribution, calculating aging intensity index, formula is: ， wherein is the aging intensity index, is the baseline relaxation time distribution, is the relaxation time distribution of the test sample, is a non-negative function, preserving positive differences to reflect aging increments, is the step size of the logarithmic time grid, M is the total number of grid points; using empirical threshold method to set classification threshold, comparing aging intensity index with classification threshold, when aging intensity index is less than classification threshold, determining as lossless state, otherwise determining as damage state.

2. The method for in-situ non-destructive evaluation of the degree of paint weathering based on optoacoustic spectroscopy according to claim 1, characterized in that: the maximum value of the autocorrelation sequence at zero lag is defined as the autocorrelation peak value, and the discrete impulse response is calculated based on the cross-correlation sequence and the autocorrelation peak value, comprising: sorting photoacoustic signals and laser intensity in time sequence to generate photoacoustic signal sequence and laser intensity sequence, and using fast convolution algorithm to perform discrete cross-correlation operation to generate cross-correlation sequence; calculating the autocorrelation sequence of the laser intensity sequence, and using peak extraction to define the maximum value of the autocorrelation sequence at zero lag as the autocorrelation peak value; calculating the discrete impulse response based on the cross-correlation sequence and the autocorrelation peak value.

3. The method for in-situ non-destructive evaluation of the degree of paint weathering based on opto-acoustic spectroscopy according to claim 2, characterized in that: the peak frequency of the normalized frequency response amplitude, comprising: performing fast Fourier transform on the discrete impulse response to generate complex frequency response, and performing normalization processing to generate normalized frequency response; respectively calculating normalized frequency response amplitude and normalized frequency response phase; setting the frequency range of photoacoustic spectrum detection, and identifying the peak frequency of the normalized frequency response amplitude by maximum value search method.

4. The method for in-situ non-destructive evaluation of the degree of paint weathering based on optoacoustic spectroscopy according to claim 3, characterized in that: the correction phase is calculated using linear combination combined with phase and theoretical phase, and the correction frequency response is calculated using normalized frequency response amplitude and correction phase, and converted to angular frequency, comprising: calculating the relaxation time constant based on the peak frequency; generating the theoretical phase using arctangent function according to the relaxation time constant; calculating the correction phase using linear combination combined with phase and theoretical phase; calculating the correction frequency response using normalized frequency response amplitude and correction phase; using discrete frequency extraction method to extract frequency points from the correction frequency response, and converting to angular frequency to generate correction frequency response of frequency.

5. The method for in-situ non-destructive evaluation of the degree of paint weathering based on opto-acoustic spectroscopy according to claim 4, characterized in that: The steps of calculating the kernel matrix using the angular frequency and the relaxation time grid points, combining the target vector and the kernel matrix, constructing the linear equation system, generating the relaxation time distribution, include: extracting the imaginary part from the corrected frequency response, constructing the target vector; setting the minimum and maximum values of the relaxation time according to the frequency range of the photoacoustic spectrum detection, generating the logarithmic time grid through logarithmic transformation, calculating the step size of the logarithmic time grid; calculating the relaxation time grid points based on the step size of the logarithmic time grid; calculating the kernel matrix using the angular frequency and the relaxation time grid points; combining the target vector and the kernel matrix, constructing the linear equation system; solving the linear equation system using the non-negative least squares method to generate the relaxation time distribution.

6. The method for in-situ non-destructive evaluation of the degree of paint weathering based on opto-acoustic spectroscopy according to claim 5, characterized in that: The steps of combining the logarithmic step size and the relaxation time distribution, calculating the aging intensity index, and performing loss evaluation, include: combining the logarithmic step size and the relaxation time distribution, calculating the aging intensity index; using the empirical threshold method to set the classification threshold, comparing the aging intensity index with the classification threshold, and determining the lossless state when the aging intensity index is less than the classification threshold, otherwise determining the damage state.

7. The method for in-situ non-destructive evaluation of the degree of paint weathering based on opto-acoustic spectroscopy according to claim 6, characterized in that: The steps of constructing a visual interface to display the loss evaluation results, include: using the visualization tool Matplotlib to construct a visual interface to display the loss evaluation results in real time; allowing users to check through real-name verification.

8. The method for in-situ non-destructive evaluation of the degree of paint weathering based on opto-acoustic spectroscopy according to claim 1, characterized in that: The steps of collecting multi-source data and preprocessing, include: collecting multi-source data through sensors and performing denoising and normalization processing; The sensors include microphones and photodiode sensors; 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, and the computer device is characterized in that: The processor executes the computer program to realize the steps of the photoacoustic spectrum-based in-situ non-destructive evaluation method of the aging degree of paint according to any one of claims 1-8.

10. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program is executed by the processor to realize the steps of the photoacoustic spectrum-based in-situ non-destructive evaluation method of the aging degree of paint according to any one of claims 1-8.

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