A terahertz wave-based epoxy resin aging detection method and related device

Abstract

This application provides a method and related equipment for epoxy resin aging detection based on terahertz waves, belonging to the field of epoxy resin aging detection technology. On one hand, the method of this embodiment performs aging detection based on the detection results of terahertz pulses transmitted through the epoxy resin to be evaluated, without consuming or damaging the epoxy resin, thus achieving non-destructive aging detection. On the other hand, by inputting the terahertz response parameter data of the epoxy resin to be evaluated into the aging detection model, its aging detection results can be directly obtained, thereby effectively improving the detection efficiency of epoxy resin aging detection. Furthermore, the detection model applied in this application provides a comprehensive method for evaluating the aging state and dielectric properties of epoxy resin by learning the aging behavior and failure mechanism of epoxy resin under multi-stress coupling. Therefore, this application method can achieve non-destructive, efficient, and comprehensive epoxy resin aging detection.

Description

Technical Field

[0001] This application relates to epoxy resin aging assessment technology and non-destructive testing of materials, and in particular to an epoxy resin aging testing method and related equipment based on terahertz waves. Background Technology

[0002] Epoxy resin, due to its excellent electrical insulation, high dielectric strength and excellent arc resistance, has become an essential insulating material and is widely used in electronic components, printed circuit boards and high-voltage electrical equipment, providing indispensable support for the stable operation of modern electrical and electronic industries.

[0003] However, the degradation of epoxy resin over long-term use can lead to a deterioration in insulation performance, affecting the operational stability of equipment. In recent years, epoxy resin has been commonly tested using methods such as deformation testing and metallographic analysis, but these methods suffer from significant drawbacks such as severe sample damage and low efficiency, hindering their practical engineering applications.

[0004] Therefore, there is an urgent need to develop new non-destructive testing methods to achieve efficient non-destructive testing of epoxy resins under aging conditions caused by different factors. Summary of the Invention

[0005] The main objective of this application is to propose a terahertz wave-based epoxy resin aging detection method and related equipment, which aims to perform non-destructive and efficient aging detection on the epoxy resin to be evaluated based on its terahertz response.

[0006] To achieve the above objectives, one aspect of this application proposes a method for detecting the aging of epoxy resin based on terahertz waves, the method comprising: Obtain terahertz response parameter data of the epoxy resin to be evaluated; The terahertz response parameter data of the epoxy resin to be evaluated is input into the trained aging test model for calculation to obtain the evaluation results of the aging state and dielectric properties of the epoxy resin to be evaluated; the aging test model is trained based on the terahertz response parameter data of the sample epoxy resin under different aging conditions and aging cycles. in, The terahertz response parameter data of the epoxy resin to be evaluated were obtained in the following way: The epoxy resin to be evaluated is transmitted through a terahertz pulse in a preset frequency band. The terahertz pulse transmitted through the epoxy resin is detected, and the terahertz response parameter data of the epoxy resin to be evaluated is obtained based on the detection results.

[0007] In some embodiments, the terahertz response parameter data includes several terahertz response parameters of the epoxy resin to be evaluated; the step of inputting the terahertz response parameter data of the epoxy resin to be evaluated into a trained aging detection model for calculation to obtain the evaluation results of the aging state and dielectric properties of the epoxy resin to be evaluated includes: Based on the terahertz response parameter data of the epoxy resin to be evaluated, calculations are performed to obtain the variation curves of several terahertz response parameters of the epoxy resin to be evaluated. Based on the variation curves of several terahertz response parameters of the epoxy resin to be evaluated, the variation trend or peak value of the parameters in the variation curves are analyzed, and the aging state and dielectric properties of the epoxy resin to be evaluated are evaluated based on the analysis results of the variation curves of each terahertz response parameter.

[0008] In some embodiments, the aging detection model is trained in the following manner: Obtain a labeled sample dataset; the sample dataset includes terahertz response parameter data of several sample epoxy resins and their corresponding labels; the labels indicate the aging conditions and aging cycle of the sample epoxy resins; The sample dataset is input into a preset aging test model for calculation to obtain an evaluation result set; the evaluation result set includes the aging conditions and aging cycle evaluation results corresponding to several epoxy resin samples in the sample dataset; The sample dataset and the evaluation result set are analyzed, and the model parameters of the preset aging detection model are adjusted based on the analysis results until the preset requirements are met. The trained aging detection model is obtained based on the adjustment results.

[0009] To achieve the above objectives, another aspect of this application proposes a transmission-type terahertz time-domain spectroscopy testing platform, which is applied to the above-described method; the platform includes a light source, a beam splitter, a terahertz emission unit, a time delay unit, a detection unit, and a data processing unit; wherein, The light source is used to generate laser pulses; The beam splitter is used to split the laser pulse into pump light and probe light; When driven by the pump light, the terahertz emitting unit generates a terahertz pulse for transmitting through the epoxy resin to be evaluated. The time delay unit is used to delay the probe light so that it coincides with the time of the terahertz pulse transmitted through the epoxy resin to be evaluated at the probe unit, so that the probe light scans the terahertz pulse transmitted through the epoxy resin to be evaluated and generates a scanning light signal. The detection unit is used to detect and amplify the scanning light signal to obtain a detection light signal; the detection light signal includes the original acquisition signal and the amplified acquisition signal. The data processing unit is used to process the probe light signal to output the terahertz response parameter data of the epoxy resin to be evaluated.

[0010] In some embodiments, the time delay unit is further configured to change the relative time delay between the probe light and the terahertz pulse transmitted through the epoxy resin to be evaluated point by point, so that the probe unit can detect the terahertz time-domain waveform of the terahertz pulse transmitted through the epoxy resin to be evaluated.

[0011] In some embodiments, the detection unit includes a detector, a low-noise preamplifier, and a lock-in amplifier; wherein, The detector is used to convert the scanning optical signal based on the electro-optic effect or the photoconductive effect to obtain the original acquisition signal; The low-noise preamplifier is used to initially amplify the original acquired signal to obtain a first amplified signal. The lock-in amplifier is used to synchronously demodulate the first amplified signal based on the modulation frequency of the pump light to obtain the amplified acquisition signal.

[0012] To achieve the above objectives, another aspect of this application proposes an epoxy resin aging detection system based on terahertz waves. The system includes a data acquisition module and an evaluation module; wherein... The data acquisition module is used to acquire the terahertz response parameter data of the epoxy resin to be evaluated; The evaluation module is used to input the terahertz response parameter data of the epoxy resin to be evaluated into the trained aging detection model for calculation, so as to obtain the evaluation results of the aging state and dielectric properties of the epoxy resin to be evaluated; the aging detection model is trained based on the terahertz response parameter data of the sample epoxy resin under different aging conditions and aging cycles. The terahertz response parameter data of the epoxy resin to be evaluated were obtained in the following manner: The epoxy resin to be evaluated is transmitted through a terahertz pulse in a preset frequency band. The terahertz pulse transmitted through the epoxy resin is detected, and the terahertz response parameter data of the epoxy resin to be evaluated is obtained based on the detection results.

[0013] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0014] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0015] The embodiments of this application include at least the following beneficial effects: This application provides a terahertz wave-based epoxy resin aging detection method, a corresponding test platform, electronic equipment, and storage medium. This scheme obtains the terahertz response parameter data of the epoxy resin to be evaluated and inputs the terahertz response parameter data of the epoxy resin to be evaluated into a trained aging detection model for calculation, thereby obtaining the evaluation results of the aging state and dielectric properties of the epoxy resin to be evaluated. On the one hand, the terahertz response parameter data of the epoxy resin to be evaluated is calculated based on the detection results of the terahertz pulse transmitted through the epoxy resin to be evaluated, without the need to consume or damage the sample, thus achieving non-destructive aging detection of epoxy resin. On the other hand, the sample is transmitted through a terahertz pulse, and the terahertz pulse after transmission through the sample is analyzed. The detection method can obtain the terahertz response parameter data of the sample in a very short time, which can effectively improve the aging detection efficiency of epoxy resin. Furthermore, by inputting the terahertz response parameter data of the epoxy resin to be evaluated into the trained aging detection model, the aging detection results of the epoxy resin to be evaluated can be obtained directly. In contrast, traditional aging detection methods often require waiting for the sample to react or require a lot of calculations. In comparison, the method of this application can effectively improve the detection efficiency of epoxy resin aging detection. In addition, the detection model used in this application method is trained based on the terahertz response parameter data of the sample epoxy resin under different aging conditions and aging cycles. By learning the aging behavior and failure mechanism of epoxy resin under multi-stress coupling, a comprehensive method is provided for evaluating the aging state and dielectric properties of epoxy resin. Attached Figure Description

[0016] Figure 1 This is a flowchart of an epoxy resin aging detection method based on terahertz waves provided in an embodiment of this application; Figure 2 This is a flowchart of the steps of a sample epoxy resin preparation method provided in the embodiments of this application; Figure 3 This is a comparison of the surface morphology of the epoxy resin samples provided in the embodiments of this application under different aging conditions and aging cycles; Figure 4A This is a graph showing the change in the mass of the epoxy resin sample provided in this application under different aging conditions over time. Figure 4BThis is a graph showing the change in the mass loss rate of epoxy resin samples under different aging conditions over time, provided in the embodiments of this application. Figure 5A This is a curve showing the change of the loss tangent of the epoxy resin under the first aging cycle and different aging factors provided in the embodiments of this application; Figure 5B This is a curve showing the change in refractive index of epoxy resin under the first aging cycle and different aging factors, provided in the embodiments of this application. Figure 5C This is a curve showing the change in the extinction coefficient of the epoxy resin under the first aging cycle and different aging factors provided in the embodiments of this application; Figure 5D This is a curve showing the change in the absorption coefficient of the epoxy resin under the first aging cycle and different aging factors provided in the embodiments of this application; Figure 5E This is a time-domain amplitude variation curve of epoxy resin under the first aging cycle and different aging factors provided in the embodiments of this application; Figure 5F This is a frequency domain amplitude variation curve of epoxy resin under the first aging cycle and different aging factors provided in the embodiments of this application; Figure 5G This is a curve showing the change of the real part of the dielectric constant of the epoxy resin under the first aging cycle and different aging factors provided in the embodiments of this application. Figure 5H This is a curve showing the change of the imaginary part of the dielectric constant of the epoxy resin under the first aging cycle and different aging factors provided in the embodiments of this application. Figure 6A This is a curve showing the change of the loss tangent of the epoxy resin under the third aging cycle and different aging factors provided in the embodiments of this application; Figure 6B This is a curve showing the change in refractive index of the epoxy resin under the third aging cycle and different aging factors, as provided in the embodiments of this application. Figure 6C This is a curve showing the change in extinction coefficient of the epoxy resin provided in the embodiments of this application under the third aging cycle and different aging factors; Figure 6D This is a curve showing the change in the absorption coefficient of the epoxy resin under the third aging cycle and different aging factors provided in the embodiments of this application; Figure 6E This is a time-domain amplitude variation curve of epoxy resin under the third aging cycle and different aging factors provided in the embodiments of this application; Figure 6F This is a frequency domain amplitude variation curve of epoxy resin under the third aging cycle and different aging factors provided in the embodiments of this application; Figure 6GThis is a curve showing the change of the real part of the dielectric constant of the epoxy resin under the third aging cycle and different aging factors, as provided in the embodiments of this application. Figure 6H This is a curve showing the change of the imaginary part of the dielectric constant of epoxy resin under the third aging cycle and different aging factors, as provided in the embodiments of this application. Figure 7 This is a structural diagram of a transmission terahertz time-domain spectroscopy testing platform provided in an embodiment of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0019] Before providing a detailed description of the embodiments of this application, some of the nouns and terms involved in the embodiments of this application will be explained first. The nouns and terms involved in the embodiments of this application are subject to the following interpretations.

[0020] 1) Terahertz pulse: an ultrafast electromagnetic pulse with a frequency between microwave and infrared. It can penetrate most non-polar materials and has low photon energy, making it suitable for non-destructive imaging, material identification and ultrafast process detection.

[0021] 2) Precision moving delay line: A key component that uses high-precision mechanical displacement to change the optical path difference, thereby achieving precise time delay control of femtosecond or picosecond-level optical signals.

[0022] In related technologies, epoxy resin, due to its excellent electrical insulation, high dielectric strength, and excellent arc resistance, has become a crucial insulating material, widely used in electronic components, printed circuit boards, and high-voltage electrical equipment, providing essential support for the stable operation of modern electrical and electronic industries. However, the degradation of epoxy resin under long-term use can lead to a deterioration in its insulation performance, affecting the operational stability of equipment. In recent years, epoxy resin has typically been tested using methods such as deformation testing and metallographic analysis. However, these methods suffer from significant drawbacks, including severe sample damage, limited evaluation dimensions, and low efficiency, hindering their practical engineering applications. Therefore, there is an urgent need to develop new non-destructive testing methods to achieve efficient non-destructive testing of epoxy resin under various aging conditions.

[0023] In view of this, this application provides a terahertz wave-based method for testing the aging of epoxy resin, a corresponding testing platform, electronic equipment, and a storage medium. This method acquires the terahertz response parameter data of the epoxy resin to be evaluated and inputs this data into a trained aging test model for calculation, thereby obtaining the evaluation results of the aging state and dielectric properties of the epoxy resin. On the one hand, the terahertz response parameter data of the epoxy resin to be evaluated is calculated based on the detection results of the terahertz pulse transmitted through the epoxy resin, without requiring the consumption or damage of the sample, thus achieving non-destructive aging testing of the epoxy resin to be evaluated. On the other hand, by transmitting a terahertz pulse through the sample and detecting the terahertz pulse after transmission, it is possible to... This method can obtain the terahertz response parameter data of the sample in a very short time, which can effectively improve the aging detection efficiency of epoxy resin. Furthermore, by inputting the terahertz response parameter data of the epoxy resin to be evaluated into the trained aging detection model, the aging detection results of the epoxy resin to be evaluated can be obtained directly. In contrast, traditional aging detection methods often require waiting for the sample to react or require a large amount of calculation. In comparison, the method of this application can effectively improve the detection efficiency of epoxy resin aging detection. In addition, the detection model used in this application is trained based on the terahertz response parameter data of the sample epoxy resin under different aging conditions and aging cycles. By learning the aging behavior and failure mechanism of epoxy resin under multi-stress coupling, a comprehensive method is provided for evaluating the aging state and dielectric properties of epoxy resin.

[0024] This application provides a terahertz wave-based epoxy resin aging detection method, relating to the field of epoxy resin aging detection technology. The terahertz wave-based epoxy resin aging detection method provided in this application can be applied to a terminal, a server, or software running on a terminal or server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the terahertz wave-based epoxy resin aging detection method, but is not limited to the above forms.

[0025] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0026] Figure 1 This is an optional flowchart of the terahertz wave-based epoxy resin aging detection method provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S102.

[0027] Step S101: Obtain the terahertz response parameter data of the epoxy resin to be evaluated.

[0028] Acquire various terahertz response parameter data of the epoxy resin to be evaluated in the preset terahertz band, as the data basis for subsequent evaluation of the aging state and dielectric properties of the epoxy resin to be evaluated.

[0029] Step S102: Input the terahertz response parameter data of the epoxy resin to be evaluated into the trained aging test model for calculation to obtain the evaluation results of the aging state and dielectric properties of the epoxy resin to be evaluated; the aging test model is trained based on the terahertz response parameter data of the sample epoxy resin under different aging conditions and aging cycles.

[0030] By inputting relevant data into a pre-trained aging test model, the aging test results of the epoxy resin to be evaluated can be directly obtained. The aging test model is trained based on the terahertz response parameters of the epoxy resin under different aging conditions and aging cycles. It learns the relationship between these parameters and the terahertz response of the epoxy resin under different aging conditions and aging cycles, thereby analyzing the aging behavior and failure mechanism of the epoxy resin under multi-stress coupling, and thus enabling a comprehensive assessment of the aging state of the epoxy resin.

[0031] in, The terahertz response parameter data of the epoxy resin to be evaluated were obtained in the following way: A terahertz pulse of a preset frequency band is transmitted through the epoxy resin to be evaluated. The terahertz pulse transmitted through the epoxy resin is detected, and the terahertz response parameter data of the epoxy resin to be evaluated is obtained based on the detection results.

[0032] In this regard, the terahertz response parameter data of the epoxy resin to be evaluated is calculated based on the detection results of the terahertz pulse transmitted through the epoxy resin to be evaluated, without consuming or damaging the sample, thus achieving non-destructive aging detection of epoxy resin. On the other hand, by transmitting the terahertz pulse through the sample and detecting the terahertz pulse after transmission, the terahertz response parameter data of the sample can be obtained in a very short time, which can effectively improve the aging detection efficiency of epoxy resin.

[0033] In some embodiments, the sample epoxy resin in the method of this embodiment is prepared by the following manner: Step S201: Weigh the accelerator dimethylaminomethylphenol, the curing agent methylhexahydrophthalic anhydride, and the epoxy resin according to the preset dosage ratio, and put the weighed substances into a beaker for mixing to prepare the adhesive solution.

[0034] Weigh the relevant substances to prepare the base adhesive.

[0035] Step S202: Place the prepared adhesive solution into a magnetic stirrer and stir at a preset temperature and speed to obtain a uniformly stirred mixture.

[0036] The base adhesive is stirred at a constant temperature and speed to obtain a uniformly mixed solution, which serves as the basis for subsequent mold making.

[0037] Step S203: Pour the mixture into a preset mold, perform gradient heating, demolding and cooling to obtain the sample epoxy resin.

[0038] The process involves molding, heating and solidification, demolding, and cooling to obtain the sample epoxy resin.

[0039] In one embodiment, such as Figure 2 As shown, Figure 2 This is a flowchart illustrating the steps of a sample epoxy resin preparation method provided in this application embodiment; the preparation process includes: (1) Weigh the accelerator dimethylaminomethylphenol, the curing agent methylhexahydrophthalic anhydride and the epoxy resin according to the ratio of 1:85:100, put them into a beaker and mix them to prepare the adhesive solution. Stir the solution on a magnetic stirrer at a constant temperature and speed of 60°C and 1000r / min for 30min.

[0040] (2) Spray the release agent into the mold, then pour the well-stirred mixture into the prepared mold, and use a needle to pick out the air bubbles in the mixture.

[0041] (3) Place the mold in a forced-air drying oven and cure the epoxy resin by gradient heating. Dry it for two hours at 80℃, 100℃ and 120℃ respectively, for a total of six hours. Take it out and let it cool naturally to prepare an epoxy resin sample of 100mm×100mm×1mm.

[0042] In some embodiments, the terahertz response parameter data of the sample epoxy resin under different aging conditions and aging cycles are obtained in the following ways: Aging tests were conducted on the epoxy resin samples under different aging conditions and for different aging cycles. The terahertz response parameters of the epoxy resin samples were obtained during the tests to obtain the terahertz response parameters of the epoxy resin samples under different aging conditions and for different aging cycles. The types of aging conditions included single thermal aging, thermal-electric composite aging, thermal-mechanical composite aging, and thermal-mechanical-electric composite aging.

[0043] In some embodiments, the method of this embodiment builds an epoxy resin aging platform by modifying a traditional aging test chamber and designing a fixing fixture; the platform can apply high pressure, temperature and vibration stress to the epoxy resin to carry out multi-factor aging tests on the epoxy resin.

[0044] The epoxy resin aging platform uses polytetrafluoroethylene (PTFE) as the main insulating support component. The upper electrode has a diameter of 80mm and a thickness of 6mm, while the lower electrode has a diameter of 100mm and a thickness of 6mm. The difference in diameter between the upper and lower electrodes is primarily to prevent short circuits caused by damage to the electrode edges under combined stress. The insulating part consists of a PTFE bottom support and an upper cover. The bottom support measures 450mm × 500mm × 20mm and is designed with a nine-grid slot (for placing the material to be aged). Each slot measures 100mm × 100mm × 13mm, and holes are drilled in the bottom to fix the lower electrode and allow wiring to be led out. The upper cover measures 450mm × 500mm × 10mm and also has holes drilled in the top to fix the upper electrode and allow wiring to be led out.

[0045] Furthermore, the process of conducting epoxy resin aging tests using this epoxy resin aging platform includes: (1) Aging tests with different factors were conducted on multiple epoxy resin samples, including thermal aging, thermo-electric aging, thermo-mechanical aging and thermo-electric-mechanical combined aging, in order to systematically study the aging behavior and failure mechanism of epoxy resin under different stress combinations.

[0046] Optionally, under thermal aging conditions, the heating temperature is 150°C.

[0047] Optionally, under thermo-electric aging conditions, the heating temperature is 150℃, and an external AC electric field of 4kV / mm is applied.

[0048] Optionally, under thermo-mechanical aging conditions, the heating temperature is 150℃ and the applied vibration frequency is 100Hz.

[0049] Optionally, under thermo-electric-mechanical aging conditions, the heating temperature is 150℃, an external 4kV / mm AC electric field is applied, and the vibration frequency is 100Hz.

[0050] Optionally, the aging test cycle for different factors is 5 times, namely 0h, 120h, 288h, 384h, and 480h.

[0051] Optionally, such as Figure 3 As shown, Figure 3 This is a comparison of the surface morphology of the epoxy resin samples provided in the embodiments of this application under different aging conditions and aging cycles.

[0052] (2) The average mass loss rate of epoxy resin under different aging conditions was calculated and statistically analyzed.

[0053] Based on the experimental test results, the average mass loss rate of epoxy resin insulation materials under different aging conditions was calculated and statistically analyzed. A curve showing the change in mass loss rate over time was then plotted. Figure 4A As shown, Figure 4AThis is a graph showing the change in the mass of the epoxy resin sample provided in this application under different aging conditions over time; Figure 4A It can be seen that under thermal aging conditions, the sample mass initially increases slightly, then slowly decreases, and eventually stabilizes. The initial mass increase can be attributed to residual unreacted curing agent molecules or adsorbed moisture in the sample. As aging progresses, the material degrades and produces volatile products, leading to a gradual decrease in mass. Later, as the main volatile components are completely released, the mass change tends to reach equilibrium. The rate of mass loss and the period of significant change show significant differences in the intensity of the effects of different aging conditions, in the following order: thermal-electric aging < thermal-mechanical aging < thermal-electric-mechanical aging, indicating that multi-stress coupling significantly accelerates material degradation. After 480 hours of aging, the mass loss under each condition gradually stabilizes, indicating that the mass loss caused by chemical reactions such as chain breakage and oxidation within the epoxy resin is most significant in the early stages of aging. Figure 4B As shown, Figure 4B This is a graph showing the change in the mass loss rate of epoxy resin samples under different aging conditions over time, provided in the embodiments of this application. Figure 4B The comparison of material mass loss rate under different aging types is further shown, and it can be clearly seen that the destructive effect of multi-factor combined aging on epoxy resin is much greater than that of single aging factor, especially showing a higher mass loss rate in long-term aging.

[0054] In some embodiments, the terahertz response parameter data in the method of this embodiment includes several terahertz response parameters of the epoxy resin to be evaluated; the terahertz response parameter data of the epoxy resin to be evaluated is input into a trained aging detection model for calculation to obtain the evaluation results of the aging state and dielectric properties of the epoxy resin to be evaluated, including: Step S301: Based on the terahertz response parameter data of the epoxy resin to be evaluated, calculations are performed to obtain the variation curves of several terahertz response parameters of the epoxy resin to be evaluated.

[0055] Curves are plotted based on the data corresponding to several terahertz response parameters to obtain the parameter variation curves for each terahertz parameter used in the analysis.

[0056] Step S302: Based on the variation curves of several terahertz response parameters of the epoxy resin to be evaluated, analyze the variation trend or peak value of the parameters in the variation curves, and obtain the evaluation results of the aging state and dielectric properties of the epoxy resin to be evaluated based on the analysis results of the variation curves of each terahertz response parameter.

[0057] The parameter variation curves of each terahertz parameter are analyzed to determine the aging state and dielectric performance of the sample based on the analysis results of the terahertz parameter variation. Finally, the results are summarized to output the aging state and dielectric performance evaluation results of the epoxy resin to be evaluated.

[0058] Specifically, the terahertz response parameters of epoxy resin include a series of terahertz response parameters such as loss tangent, refractive index, extinction coefficient, absorption coefficient, time-domain amplitude, frequency-domain amplitude, and complex permittivity.

[0059] In one embodiment, epoxy resin insulating material was selected for terahertz response testing at 0.1THz to 3THz to obtain the terahertz response of the material under different aging conditions during the first aging cycle; wherein, Figure 5A The loss tangent variation curves of the epoxy resin provided in this application embodiment under the first aging cycle and different aging factors are used to measure the degree of its dielectric loss. From Figure 5A It can be observed that the loss tangent of the aged epoxy resin increases significantly, and the loss tangent during multi-factor coupled aging is significantly higher than that during single-factor aging. This indicates that the multi-factor coupled environment has a significant synergistic amplification effect on the degradation of the material's dielectric properties. Within this frequency band, the loss spectrum shows a trend of first increasing and then decreasing, consistent with typical relaxation polarization response behavior, with a loss peak appearing near the characteristic frequency. Furthermore, the increase in loss tangent caused by thermo-electric aging is consistently greater than that caused by thermo-mechanical aging, indicating that electric field stress has a more severe impact on the epoxy resin polymer chain structure and trapped energy level distribution than mechanical stress. The underlying mechanisms include: intensified carrier migration under the influence of the electric field, enhanced trap-assisted polarization process, molecular chain breakage induced by partial discharge, and increased energy consumption due to dipole orientation. These factors collectively lead to more significant energy dissipation and dielectric property degradation.

[0060] Figure 5B The refractive index variation curve of the epoxy resin under different aging factors provided in the embodiments of this application is from... Figure 5B As can be seen, the refractive index of epoxy resin samples under different aging conditions exhibits a typical dispersion trend, decreasing with frequency, and the refractive index decrease is more severe under multi-factor aging conditions. This is mainly due to the increase in the density of impurity ions and defect states inside the material after aging, which leads to weakened dielectric polarization and reduced polarization relaxation ability.

[0061] Figure 5C This is a curve showing the change in the extinction coefficient of the epoxy resin under the first aging cycle and different aging factors provided in the embodiments of this application; Figure 5D This is a curve showing the change in the absorption coefficient of the epoxy resin under the first aging cycle and different aging factors provided in the embodiments of this application; Figure 5C and Figure 5D The extinction coefficient and absorption coefficient of the epoxy resin samples are presented as a function of frequency. Both coefficients show a trend of first increasing and then decreasing, indicating that there is significant chemical structural damage inside the aged epoxy resin. This phenomenon becomes more pronounced with the increase of aging factors, mainly because multi-factor aging induces material degradation, and its products produce significant characteristic absorption in the terahertz frequency range.

[0062] Figure 5E This is a time-domain amplitude variation curve of the epoxy resin provided in the embodiments of this application under the first aging cycle and different aging factors; from Figure 5E It can be seen that in the terahertz time-domain signal, the time-domain pulse signal of the thermo-electric-mechanical combined aging sample arrives earliest, followed by the thermo-electric and thermo-mechanical aging samples, while the terahertz time-domain signal peak of the unaged sample arrives latest. The results indicate that the terahertz time-domain pulse delay time is significantly correlated with aging factors and can be used as a reliable indicator for assessing the aging state.

[0063] Based on this, performing a Fourier transform on the detected terahertz time-domain pulse signal yields the corresponding frequency-domain spectrum, such as... Figure 5F As shown, Figure 5F This application provides frequency domain amplitude variation curves for epoxy resin under different aging factors during the first aging cycle. Furthermore, in the complex dielectric constant spectrum, the real part of the dielectric constant shows significant decay in the 0.5–1 THz range, indicating that molecular chain breakage and cross-linking structure destruction reduce the contribution of orientation polarization. Figure 5G As shown, Figure 5G This is a curve showing the change of the real part of the dielectric constant of the epoxy resin provided in the embodiments of this application under the first aging cycle and different aging factors. Simultaneously, it can be seen from the imaginary part of the complex dielectric constant that the original loss peak shifts from 1.2 THz to 2.0 THz in the imaginary part, and the loss peak value increases significantly with the increase of aging factors, corresponding to the enhanced polarization process at the Maxwell-Wagner interface caused by the increase of Schottky-type vacancy defects. Figure 5H As shown, Figure 5H This is a curve showing the change of the imaginary part of the dielectric constant of the epoxy resin provided in the embodiments of this application under the first aging cycle and different aging factors.

[0064] In summary, these results demonstrate that terahertz waves can be used for non-destructive testing of epoxy resins under various aging conditions.

[0065] In one embodiment, to further evaluate the performance characteristics of epoxy resin under long-term aging conditions, Figures 6A to 6H The terahertz response of epoxy resin under different aging factors during the third cycle (384 h) is presented within the frequency range of 0.1–3.0 THz. like Figure 6AAs shown, compared with unaged epoxy resin, the dielectric loss tangent of epoxy resin after three aging cycles increased significantly. Under the synergistic effect of multiple aging factors such as thermal stress, electrical stress, and mechanical stress, aging was further accelerated. It can also be seen that electric field stress has a more severe impact on the epoxy resin polymer chain structure and trapped energy level distribution than mechanical stress and thermal stress. Figure 6B The changes in the refractive index of the epoxy resin are shown. It can be observed that the refractive index exhibits typical dispersive characteristics, decreasing with increasing frequency. During the multi-factor composite aging process, the epoxy resin shows the most significant decrease. Both the extinction coefficient and absorption coefficient show a trend of first increasing and then decreasing, such as... Figure 6C and Figure 6D As shown. Furthermore, compared to unaged and single-factor aging, epoxy resins subjected to multi-factor composite aging exhibit significantly improved extinction coefficient and absorption coefficient. Figure 6E and Figure 6F The figures show the time-domain and frequency-domain characteristic curves of epoxy resin, respectively. It can be seen that the time-domain pulse signal arrives earliest in the sample under combined thermo-electrical-mechanical aging. The arrival time of the time-domain pulse signal is directly related to the degree of aging of the sample, while the time-domain pulse signal of the unaged sample arrives latest. Figure 6G As shown, in the complex dielectric constant spectrum, the real part of the dielectric constant decays significantly in the range of 0.5–1 THz, indicating that molecular chain breakage and cross-linking structure disruption reduce the contribution of orientation polarization; as Figure 6H As shown, for the imaginary part of the complex dielectric constant, the original loss peak shifts from 1.2 THz to 2.0 THz, and the peak value increases significantly with the increase of aging factors, indicating that the loss under multi-factor aging conditions is significantly higher than that of the unaged sample and the sample under single aging stress. The results show that the performance of epoxy resin deteriorates significantly during long-term aging, and the multi-factor composite aging environment has a significant accelerating effect on the deterioration of the dielectric properties of epoxy resin.

[0066] In summary, by combining the variation patterns of these parameters, the method in this embodiment deeply analyzes and constructs the aging behavior and failure mechanism of epoxy resin under multi-stress coupling. Through comprehensive analysis of multi-dimensional terahertz response characteristics, it provides a comprehensive and non-destructive method for evaluating the aging state and dielectric properties of epoxy resin.

[0067] In some embodiments, the aging detection model is trained in the following manner: Step S401: Obtain a labeled sample dataset; the sample dataset includes terahertz response parameter data of several sample epoxy resins and their corresponding labels; the labels indicate the aging conditions and aging cycle of the sample epoxy resins.

[0068] Step S402: Input the sample dataset into the preset aging test model for calculation to obtain the evaluation result set; the evaluation result set includes the aging conditions and aging cycle evaluation results of several epoxy resin samples in the sample dataset.

[0069] Step S403: Analyze the sample dataset and evaluation result set, adjust the model parameters of the preset aging detection model based on the analysis results until the preset requirements are met, and obtain the trained aging detection model based on the adjustment results.

[0070] By comparing the model evaluation results with the actual aging state of the sample epoxy resin, and adjusting the preset aging detection model according to the comparison results until it meets the preset requirements, a trained aging detection model is obtained. This model can identify the aging conditions and aging cycle, i.e., the aging state, based on the terahertz response of the sample epoxy resin.

[0071] In summary, the embodiments of this method include, but are not limited to, the following beneficial effects: (1) Achieving non-destructive aging test of epoxy resin: In this embodiment, the terahertz response parameter data of the epoxy resin to be evaluated is calculated based on the detection results of the terahertz pulse transmitted through the epoxy resin to be evaluated. It does not require the sample to be consumed or damaged, thus achieving non-destructive aging test of epoxy resin.

[0072] (2) Achieving efficient aging detection of epoxy resin: By transmitting the sample through a terahertz pulse and detecting the terahertz pulse after the sample is transmitted, the terahertz response parameter data of the sample can be obtained in a very short time, which can effectively improve the aging detection efficiency of epoxy resin. Furthermore, by inputting the terahertz response parameter data of the epoxy resin to be evaluated into the trained aging detection model, the aging detection result of the epoxy resin to be evaluated can be obtained directly. In contrast, traditional aging detection methods often require waiting for the sample to react or require a lot of calculations. Compared with this method, the detection efficiency of epoxy resin aging detection can be effectively improved.

[0073] (3) Achieving comprehensive aging detection of epoxy resin: The detection model used in this application is trained based on the terahertz response parameter data of the sample epoxy resin under different aging conditions and aging cycles. By learning the aging behavior and failure mechanism of epoxy resin under multi-stress coupling, a comprehensive method is provided for evaluating the aging state and dielectric properties of epoxy resin.

[0074] In some embodiments, another aspect of this application provides a transmission-type terahertz time-domain spectroscopy testing platform, which is applied to the above-described method; the platform includes a light source, a beam splitter, a terahertz emission unit, a time delay unit, a detection unit, and a data processing unit; wherein... The light source is used to generate laser pulses; A beam splitter is used to split a laser pulse into a pump beam and a probe beam; When driven by pump light, the terahertz emitting unit generates terahertz pulses for transmitting through the epoxy resin to be evaluated. The time delay unit is used to delay the probe light so that it coincides with the time of the terahertz pulse transmitted through the epoxy resin to be evaluated at the probe unit, so that the probe light scans the terahertz pulse transmitted through the epoxy resin to be evaluated and generates a scanning light signal. The detection unit is used to detect and amplify the scanning light signal to obtain the detection light signal; the detection light signal includes the original acquisition signal and the amplified acquisition signal. The data processing unit is used to process the probe light signal to output the terahertz response parameter data of the epoxy resin to be evaluated.

[0075] In this embodiment, the platform generates terahertz pulses by pump light drive and scans with probe light to detect the terahertz pulses carrying the spectral response information of the epoxy resin to be evaluated. Based on the probe light signal obtained from the scan, a series of processing steps are performed to finally obtain the terahertz response parameter data of the epoxy resin to be evaluated.

[0076] In some embodiments, the time delay unit in the platform described above is further used to change the relative time delay between the probe light and the terahertz pulse transmitted through the epoxy resin to be evaluated point by point, so that the probe unit can detect the terahertz time-domain waveform of the terahertz pulse transmitted through the epoxy resin to be evaluated.

[0077] In this embodiment, the time delay unit in the platform achieves point-by-point scanning in the time domain by changing the relative time delay between the probe light and the terahertz pulse transmitted through the epoxy resin to be evaluated. Ultimately, this enables the probe unit to detect the terahertz time-domain waveform of the terahertz pulse transmitted through the epoxy resin to be evaluated.

[0078] In some embodiments, the detection unit in the platform described above includes a detector, a low-noise preamplifier, and a lock-in amplifier; wherein... The detector is used to convert the scanning optical signal based on the electro-optic effect or the photoconductive effect to obtain the original acquired signal; A low-noise preamplifier is used to initially amplify the original acquired signal to obtain the first amplified signal; A lock-in amplifier is used to synchronously demodulate the first amplified signal based on the modulation frequency of the pump light to obtain the amplified acquisition signal.

[0079] The detector in this embodiment platform amplifies and demodulates the original acquired signal to suppress noise and improve the signal-to-noise ratio, and finally outputs the original and processed acquired signals.

[0080] In one embodiment, a transmission terahertz time-domain spectroscopy testing platform is used to measure the changes in various parameters of epoxy resin insulation material after aging. The testing platform is as follows: Figure 7 As shown, Figure 7 This is a structural diagram of a transmission terahertz time-domain spectroscopy testing platform provided in an embodiment of this application; Figure 7 In this system, (1) is a femtosecond laser, (2) is a beam splitter, (3) is a terahertz emitting device, (4) is a first parabolic mirror, (5) is transparent, (6) is the epoxy resin to be evaluated, (7) is a vector network analyzer, (8) is a low-noise preamplifier, (9) is a lock-in amplifier, (10) is a time delay system including a mechanical optical delay line and a precision moving delay line, and (11) is a second parabolic mirror. This terahertz time-domain spectroscopy system uses a femtosecond laser as the pump-probe source. Its output ultrashort pulse is split into a pump light path with higher intensity and a probe light path with lower intensity by the beam splitter. The pump light is incident on the terahertz emitting device, which excites the generation of a broadband terahertz pulse. After collimation and focusing, the terahertz wave is transmitted through the epoxy resin to be evaluated, carrying the spectral response information of the sample. The probe light path introduces a controllable time delay through a mechanical optical delay line, so that it coincides with the terahertz pulse after interaction with the sample at the probe end. By precisely moving the delay line and gradually changing the relative time delay between the probe light and the terahertz pulse, the time-domain waveform of the terahertz electric field can be scanned and acquired. In the detector, the terahertz electric field is converted into a weak current signal through electro-optic or photoconductive effects. This signal is first amplified by a low-noise preamplifier, then input to a lock-in amplifier for synchronous demodulation using the modulation frequency of the pump light as a reference signal, significantly suppressing noise and improving the signal-to-noise ratio. Finally, the amplified and acquired signal is transmitted to a computer for time-domain-frequency domain transformation, sample parameter inversion, and other processing to obtain the frequency-domain spectral characteristics of the epoxy resin under evaluation in the terahertz band, such as the absorption coefficient and refractive index.

[0081] It is understood that the content of the above method embodiments is applicable to the above platform embodiments. The specific functions implemented by the platform embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0082] In some embodiments, another aspect of this application provides an epoxy resin aging detection system based on terahertz waves; the system includes a data acquisition module and an evaluation module; wherein, The data acquisition module is used to acquire the terahertz response parameter data of the epoxy resin to be evaluated; The evaluation module is used to input the terahertz response parameter data of the epoxy resin to be evaluated into the trained aging test model for calculation, and obtain the evaluation results of the aging state and dielectric properties of the epoxy resin to be evaluated; the aging test model is trained based on the terahertz response parameter data of the sample epoxy resin under different aging conditions and aging cycles. The terahertz response parameter data of the epoxy resin to be evaluated were obtained in the following way: A terahertz pulse of a preset frequency band is transmitted through the epoxy resin to be evaluated. The terahertz pulse transmitted through the epoxy resin is detected, and the terahertz response parameter data of the epoxy resin to be evaluated is obtained based on the detection results.

[0083] It is understood that the content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0084] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0085] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0086] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0087] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0088] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0089] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0090] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0091] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0092] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0093] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0094] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0095] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0096] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0097] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0098] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0099] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0100] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0101] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for detecting the aging of epoxy resin based on terahertz waves, characterized in that, The method includes the following steps: Obtain terahertz response parameter data of the epoxy resin to be evaluated; The terahertz response parameter data of the epoxy resin to be evaluated is input into the trained aging test model for calculation to obtain the evaluation results of the aging state and dielectric properties of the epoxy resin to be evaluated; the aging test model is trained based on the terahertz response parameter data of the sample epoxy resin under different aging conditions and aging cycles. in, The terahertz response parameter data of the epoxy resin to be evaluated were obtained in the following way: The epoxy resin to be evaluated is transmitted through a terahertz pulse in a preset frequency band. The terahertz pulse transmitted through the epoxy resin is detected, and the terahertz response parameter data of the epoxy resin to be evaluated is obtained based on the detection results.

2. The method according to claim 1, characterized in that, The terahertz response parameter data of the epoxy resin samples under different aging conditions and aging cycles were obtained in the following way: Aging tests were conducted on the epoxy resin samples under different aging conditions and for different aging cycles, and the terahertz response parameter data of the epoxy resin samples during the tests were obtained accordingly, so as to obtain the terahertz response parameter data of the epoxy resin samples under different aging conditions and aging cycles; the types of aging conditions include single thermal aging, thermal-electric composite aging, thermal-mechanical composite aging, and thermal-mechanical-electric composite aging.

3. The method according to claim 1, characterized in that, The terahertz response parameter data of the epoxy resin to be evaluated includes several terahertz response parameters of the epoxy resin to be evaluated; the step of inputting the terahertz response parameter data of the epoxy resin to be evaluated into a trained aging detection model for calculation to obtain the evaluation results of the aging state and dielectric properties of the epoxy resin to be evaluated includes: Based on the terahertz response parameter data of the epoxy resin to be evaluated, calculations are performed to obtain the variation curves of several terahertz response parameters of the epoxy resin to be evaluated. Based on the variation curves of several terahertz response parameters of the epoxy resin to be evaluated, the variation trend or peak value of the parameters in the variation curves are analyzed, and the aging state and dielectric properties of the epoxy resin to be evaluated are evaluated based on the analysis results of the variation curves of each terahertz response parameter.

4. The method according to claim 1, characterized in that, The aging detection model is trained in the following way: Obtain a labeled sample dataset; the sample dataset includes terahertz response parameter data of several sample epoxy resins and their corresponding labels; the labels indicate the aging conditions and aging cycle of the sample epoxy resins; The sample dataset is input into a preset aging test model for calculation to obtain an evaluation result set; the evaluation result set includes the aging conditions and aging cycle evaluation results corresponding to several epoxy resin samples in the sample dataset; The sample dataset and the evaluation result set are analyzed, and the model parameters of the preset aging detection model are adjusted based on the analysis results until the preset requirements are met. The trained aging detection model is obtained based on the adjustment results.

5. A transmission-type terahertz time-domain spectroscopy testing platform, characterized in that, The platform is applied to the method of claim 1; the platform includes a light source, a beam splitter, a terahertz emission unit, a time delay unit, a detection unit, and a data processing unit; wherein... The light source is used to generate laser pulses; The beam splitter is used to split the laser pulse into pump light and probe light; When driven by the pump light, the terahertz emitting unit generates a terahertz pulse for transmitting through the epoxy resin to be evaluated. The time delay unit is used to delay the probe light so that it coincides with the time of the terahertz pulse transmitted through the epoxy resin to be evaluated at the probe unit, so that the probe light scans the terahertz pulse transmitted through the epoxy resin to be evaluated and generates a scanning light signal. The detection unit is used to detect and amplify the scanning light signal to obtain a detection light signal; the detection light signal includes the original acquisition signal and the amplified acquisition signal. The data processing unit is used to process the probe light signal to output the terahertz response parameter data of the epoxy resin to be evaluated.

6. The platform according to claim 5, characterized in that, The time delay unit is also used to change the relative time delay between the probe light and the terahertz pulse transmitted through the epoxy resin to be evaluated point by point, so that the probe unit can detect the terahertz time-domain waveform of the terahertz pulse transmitted through the epoxy resin to be evaluated.

7. The platform according to claim 5, characterized in that, The detection unit includes a detector, a low-noise preamplifier, and a lock-in amplifier; wherein... The detector is used to convert the scanning optical signal based on the electro-optic effect or the photoconductive effect to obtain the original acquisition signal; The low-noise preamplifier is used to initially amplify the original acquired signal to obtain a first amplified signal. The lock-in amplifier is used to synchronously demodulate the first amplified signal based on the modulation frequency of the pump light to obtain the amplified acquisition signal.

8. A terahertz wave-based epoxy resin aging detection system, characterized in that, The system includes a data acquisition module and an evaluation module; wherein... The data acquisition module is used to acquire the terahertz response parameter data of the epoxy resin to be evaluated; The evaluation module is used to input the terahertz response parameter data of the epoxy resin to be evaluated into the trained aging detection model for calculation, so as to obtain the evaluation results of the aging state and dielectric properties of the epoxy resin to be evaluated; the aging detection model is trained based on the terahertz response parameter data of the sample epoxy resin under different aging conditions and aging cycles. The terahertz response parameter data of the epoxy resin to be evaluated were obtained in the following manner: The epoxy resin to be evaluated is transmitted through a terahertz pulse in a preset frequency band. The terahertz pulse transmitted through the epoxy resin is detected, and the terahertz response parameter data of the epoxy resin to be evaluated is obtained based on the detection results.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 5.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 5.

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