UV curing control method and system based on real-time spectrum monitoring

Abstract

The invention discloses a UV curing control method and system based on real-time spectrum monitoring, and relates to the field of UV curing control, and the method comprises the steps: firstly obtaining original full spectrum data, analyzing the parameters of a skeleton peak and a reactant characteristic peak, and calculating the microscopic vibration temperature in real time through the Stokes and anti-Stokes integral areas of the skeleton peak; and then, thermally induced drift correction is performed on the reactant characteristic peak based on the temperature data, and interference of temperature fluctuation on a spectral signal is eliminated, so that the accurate curing degree is reconstructed. And then, a double-variable cooperative feedback control model based on the precise curing degree and the microscopic temperature is established, the chemical reaction progress and the thermal safety threshold are comprehensively evaluated, and the power of the UV light source is subjected to self-adaptive dynamic optimization adjustment. Thus, the problem of spectrum misjudgment caused by photo-thermal coupling can be effectively solved, accurate closed-loop control over the chemical reaction and the heat effect in the curing process is achieved, and therefore the stability of the curing process and the product quality are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of UV curing control, and more specifically, to a UV curing control method and system based on real-time spectral monitoring. BACKGROUND

[0002] With the rapid development of advanced manufacturing technology and continuous breakthroughs in material science, ultraviolet (UV) curing technology has been widely penetrated into high-end manufacturing fields such as microelectronic packaging, optical fiber coating, high-precision 3D printing, and functional coating, due to its fast curing speed, high energy utilization rate, and no volatile organic compound emissions. In these high-value-added application scenarios, the curing quality of photosensitive materials directly determines the mechanical strength, optical performance, and weather resistance of the final product. Therefore, in order to overcome the hysteresis and destructiveness of traditional offline detection methods, online monitoring technology based on spectral analysis has gradually become the focus of the industry. This technology aims to capture the spectral signal changes of specific functional groups in the reaction system in real time, analyze the polymerization reaction kinetics process, and thus accurately control the curing degree, which is of great significance to improve the yield rate of automated production lines and reduce production costs.

[0003] However, although existing spectral monitoring methods perform well in ideal laboratory environments, they still face severe challenges when applied in complex industrial online curing scenarios. UV curing is essentially a severe photo-thermal coupling process, and the reaction system not only receives radiant heat from high-power UV light sources, but also releases a large amount of chemical reaction heat itself, resulting in a significant increase in the temperature of the substrate. Most existing UV curing control systems based on spectral monitoring are based on the isothermal assumption, and their control logic often relies solely on the decay of characteristic peak intensity or the change in peak area to infer the curing degree, but they seriously ignore the physical interference of the micro-temperature field on the spectral morphology. From the perspective of molecular spectroscopy, fluctuations in temperature directly change the vibrational energy level distribution of molecules, causing spectral characteristic peaks to shift (i.e., thermal drift) and lines to broaden. Existing control systems lack decoupling and correction mechanisms for this thermal effect, often mistakenly attributing the spectral peak position thermal drift caused by temperature rise to the curing degree change caused by chemical bond conversion. This misjudgment of spectral signals can lead to incorrect feedback adjustment instructions from the control system, not only wasting energy, but also potentially causing quality defects such as product overheating yellowing and internal stress cracking, making it difficult to meet the stringent requirements of high-precision manufacturing for curing processes.

[0004] Therefore, there is an urgent need for an optimized UV curing control method and system based on real-time spectral monitoring. SUMMARY

[0005] To solve the above technical problems, the present application is proposed.

[0006] According to one aspect of this application, a UV curing control method based on real-time spectral monitoring is provided, comprising:

[0007] Obtain the raw full spectrum data;

[0008] Characteristic peak pairs were extracted and parameters were analyzed from the original full spectrum data to obtain the Stokes integral area of ​​the skeleton peak, the anti-Stokes integral area of ​​the skeleton peak, the original peak position of the reactant characteristic peak, and the original integral area of ​​the reactant characteristic peak.

[0009] The micro-temperature of the skeleton peak is calculated in real time by solving the Stokes integral area and the anti-Stokes integral area of ​​the skeleton peak to obtain the real-time micro-vibration temperature.

[0010] The degree of cure is recalculated based on the original peak positions and the original integral areas of the characteristic peaks of the reactants to obtain the accurate degree of cure.

[0011] A dual-variable collaborative feedback control of precise curing degree and real-time micro-vibration temperature is used to obtain the final UV light source power control command.

[0012] According to another aspect of this application, a UV curing control system based on real-time spectral monitoring is provided, comprising:

[0013] The raw full spectrum data acquisition module is used to acquire raw full spectrum data;

[0014] The characteristic peak pair extraction and analysis module is used to extract characteristic peak pairs and analyze parameters from the original full spectrum data to obtain the Stokes integral area of ​​the skeleton peak, the anti-Stokes integral area of ​​the skeleton peak, the original peak position of the reactant characteristic peak, and the original integral area of ​​the reactant characteristic peak.

[0015] The micro-temperature calculation module is used to calculate the micro-temperature in real time from the Stokes integral area and the anti-Stokes integral area of ​​the skeleton peak to obtain the real-time micro-vibration temperature.

[0016] The curing calculation module is used to recalculate the degree of curing based on the original peak positions and the original integral areas of the characteristic peaks of the reactants to obtain the accurate degree of curing.

[0017] The dual-variable collaborative feedback control module is used to perform dual-variable collaborative feedback control on the precise curing degree and real-time micro-vibration temperature to obtain the final UV light source power control command.

[0018] Compared with existing technologies, this application provides a UV curing control method and system based on real-time spectral monitoring. First, it acquires raw full-spectrum data and analyzes the parameters of the framework peaks and reactant characteristic peaks. The micro-vibration temperature is calculated in real-time using the Stokes and anti-Stokes integral areas of the framework peaks. Subsequently, based on this temperature data, thermally induced drift correction is performed on the reactant characteristic peaks to eliminate interference from temperature fluctuations on the spectral signal, thereby reconstructing the accurate degree of curing. Furthermore, a bivariate collaborative feedback control model based on the accurate degree of curing and micro-temperature is established to comprehensively evaluate the chemical reaction progress and thermal safety threshold, and adaptively and dynamically optimize the UV light source power. This effectively overcomes the spectral misjudgment problem caused by photothermal coupling, achieving precise closed-loop control of the chemical reaction and thermal effects during the curing process, thereby improving the stability of the curing process and product quality. Attached Figure Description

[0019] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0020] Figure 1 This is a flowchart of a UV curing control method based on real-time spectral monitoring according to an embodiment of this application.

[0021] Figure 2 This is a data flow diagram of a UV curing control method based on real-time spectral monitoring according to an embodiment of this application.

[0022] Figure 3 This is a flowchart of sub-step S1 of the UV curing control method based on real-time spectral monitoring according to an embodiment of this application.

[0023] Figure 4 This is a flowchart of sub-step S13 of the UV curing control method based on real-time spectral monitoring according to an embodiment of this application.

[0024] Figure 5 This is a flowchart of sub-step S3 of the UV curing control method based on real-time spectral monitoring according to an embodiment of this application.

[0025] Figure 6 This is a flowchart of sub-step S4 of the UV curing control method based on real-time spectral monitoring according to an embodiment of this application.

[0026] Figure 7 This is a block diagram of a UV curing control system based on real-time spectral monitoring according to an embodiment of this application. Detailed Implementation

[0027] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0028] To address the problems mentioned above in the background technology, this application proposes a UV curing control method based on real-time spectral monitoring. Figure 1 This is a flowchart of a UV curing control method based on real-time spectral monitoring according to an embodiment of this application. Figure 2 This is a data flow diagram of a UV curing control method based on real-time spectral monitoring according to an embodiment of this application. Figure 1 and Figure 2 As shown, the UV curing control method based on real-time spectral monitoring includes the following steps: S1, acquiring raw full-spectrum data; S2, extracting characteristic peak pairs and analyzing parameters from the raw full-spectrum data to obtain the Stokes integral area of ​​the skeleton peak, the anti-Stokes integral area of ​​the skeleton peak, the original peak position of the reactant characteristic peak, and the original integral area of ​​the reactant characteristic peak; S3, performing real-time micro-temperature calculation on the Stokes integral area and anti-Stokes integral area of ​​the skeleton peak to obtain the real-time micro-vibration temperature; S4, recalculating the degree of curing based on the original peak position and the original integral area of ​​the reactant characteristic peak to obtain the accurate degree of curing; S5, performing bivariate collaborative feedback control on the accurate degree of curing and the real-time micro-vibration temperature to obtain the final UV light source power control command.

[0029] In the aforementioned UV curing control method based on real-time spectral monitoring, step S1 involves acquiring raw full-spectrum data. It should be understood that because the chemical cross-linking reaction of the material during UV curing is accompanied by continuous changes in its characteristic spectrum, local spectral data cannot fully capture the key information in the reaction process, easily leading to misjudgment of the curing state. Therefore, this application collects complete spectral information covering the characteristic wavebands of the reaction to comprehensively record the spectral evolution of the material during the transition from liquid to solid state, providing a complete basis for the analysis of key parameters such as curing degree and reaction rate. This accurately reflects the real-time state of the curing reaction, avoids control deviations caused by missing data, and ensures the mechanical properties, thermal stability, and dimensional consistency of the final product.

[0030] In particular, in one specific embodiment, Figure 3 This is a flowchart of sub-step S1 of the UV curing control method based on real-time spectral monitoring according to an embodiment of this application. Figure 3As shown, step S1 includes: S11, exciting the material to be cured with a single laser, the single laser having a predetermined excitation wavelength; S12, configuring a spectrometer to cover the Stokes region and anti-Stokes region symmetrically distributed on both sides of the predetermined excitation wavelength; S13, acquiring the original full spectrum data with the spectrometer.

[0031] Specifically, in step S11, the material to be cured is excited by a single laser with a predetermined excitation wavelength. It should be understood that excitation by multiple wavelength sources can cause spectral superposition interference, making it impossible to accurately distinguish between the characteristic scattering signal and stray light signal of the material to be cured, thus increasing the difficulty of spectral analysis. Therefore, this application further employs a single laser with a predetermined excitation wavelength as the excitation source to generate a highly specific and stable Raman scattering signal from the material to be cured, avoiding mutual interference between excitation lights of different wavelengths. This improves the purity and discriminability of the spectral signal, clearly presenting key information such as material molecular vibrations and chemical bond changes, laying the foundation for accurate analysis of subsequent spectral data and ensuring the accuracy of monitoring the curing process.

[0032] Specifically, in one possible embodiment, step S11 is implemented as follows: First, the characteristic absorption band of the material to be cured is determined based on its chemical composition, and then a single laser corresponding to the predetermined excitation wavelength is selected. The laser is then fixed at a preset position on the UV curing device, and the installation angle of the laser is adjusted to ensure that the output beam can perpendicularly irradiate the monitoring area of ​​the material to be cured. Next, the output power of the laser is adjusted to a reasonable range that can both excite an effective scattering signal and not damage the material properties. Simultaneously, the laser beam is focused into a micrometer-sized spot using a focusing lens to ensure the accuracy of the excitation area and the stability of the signal intensity, forming a continuous and stable excitation environment.

[0033] Specifically, in step S12, the spectrometer is configured to cover the Stokes and anti-Stokes regions symmetrically distributed on both sides of the predetermined excitation wavelength. It should be understood that since the Stokes spectrum reflects changes in the molecular structure of the material to be cured, and the anti-Stokes spectrum characterizes temperature changes, acquiring only one region would result in a lack of dimension in characterizing the curing state, failing to comprehensively reflect the reaction process. Therefore, this application further adjusts the spectrometer's acquisition parameters and optical structure to symmetrically cover the two spectral regions on both sides of the predetermined excitation wavelength, thereby simultaneously acquiring dual spectral information related to the evolution of the material's chemical structure and thermal effects. This enables coordinated monitoring of the chemical reaction progress and temperature changes during curing, comprehensively judging the degree of curing and reaction uniformity of the material, and providing multi-dimensional data support for the dynamic adjustment of curing parameters.

[0034] Specifically, in one possible embodiment, step S12 is implemented as follows: First, the wavelength ranges of the Stokes and anti-Stokes regions are calculated based on the predetermined excitation wavelength to determine the total wavelength range to be covered by the spectrometer. Then, a grating with wide-spectrum acquisition capability and a high-sensitivity detector are selected and assembled into the spectrometer body, and the entrance slit width is adjusted to balance resolution and signal intensity. The scattered light transmission channel is precisely aligned with the spectrometer's entrance port using an optical coupling assembly, and the spectrometer's integration time and detection gain are adjusted to ensure that the spectral signals from both regions can be effectively captured. Finally, wavelength calibration is performed, and the symmetry and accuracy of the acquisition range are verified using a standard light source, completing the spectrometer's configuration and debugging.

[0035] Specifically, in step S13, the raw full-spectrum data is acquired using a spectrometer. It should be understood that since the chemical changes and temperature fluctuations of the material during UV curing are synchronously reflected in the continuous evolution of the spectrum, acquiring only local spectra or pre-processed spectral data would result in the loss of detailed features of key reaction stages, leading to deviations in the calculation of the degree of cure and temperature. Therefore, this application further utilizes a spectrometer to continuously acquire complete spectral information during the curing process, thereby fully recording all spectral feature changes during the transformation of the material from a liquid prepolymer to a solid crosslinked body. This provides undistorted basic data for subsequent thermal drift correction and degree of cure recalculation. This ensures that the spectral information relied upon by subsequent analyses covers the key details of the entire reaction cycle, avoiding control command errors due to missing or distorted data, and guaranteeing the stability of the UV curing process and the consistency of the final product's quality.

[0036] In particular, in one specific embodiment, Figure 4 This is a flowchart of sub-step S13 of the UV curing control method based on real-time spectral monitoring according to an embodiment of this application. Figure 4 As shown, step S13 includes: S131, acquiring mixed scattered light using a spectrometer; S132, performing spectral dispersion and filtering on the mixed scattered light to obtain a spectral signal; and S133, digitizing the spectral signal to obtain raw full-spectrum data.

[0037] More specifically, in step S131, mixed scattered light is acquired using a spectrometer. It should be understood that during UV curing, the interaction between the laser and the molecules of the material to be cured generates mixed scattered light, including Rayleigh scattering, Stokes Raman scattering, and anti-Stokes Raman scattering. The Stokes signal reflects changes in chemical structure, while the anti-Stokes signal is associated with molecular vibrational temperature. The absence of any one of these components leads to incomplete analysis of the reaction state. Therefore, this application further captures this mixed scattered light through the optical acquisition link of the spectrometer to obtain all the optical signal components generated by the interaction of material molecules during curing, providing the original optical signal source for subsequent separation of effective spectral information. This ensures that subsequent spectral separation and filtering steps have a complete signal basis, avoiding temperature calculation failures or curing degree judgment errors due to missed key optical signal components, and ensuring the integrity of the data source for the entire monitoring system.

[0038] Specifically, in one possible embodiment, step S131 is implemented as follows: First, an optical system consisting of an incident light path and a collection light path is constructed. The incident light path uses an optical fiber to transmit the laser to a focusing lens, ensuring that the laser is vertically focused on the monitoring area of ​​the material to be cured. The collection light path adopts a confocal design, fixing the spectrometer probe at a 45-degree angle to the incident light, ensuring that the probe's field of view completely covers the point of interaction between the laser and the material. Then, the probe's focal length is adjusted so that the mixed scattered light can be accurately focused onto the spectrometer's entrance slit, while simultaneously checking the light path's sealing to prevent stray light from entering. After starting the UV curing device and the laser, the spectrometer's light signal acquisition function is simultaneously activated. The spectrometer's built-in light signal receiving module continuously captures the mixed scattered light and transmits it to the subsequent beam splitting and filtering modules, ensuring that the light signal intensity is stable and uninterrupted during the acquisition process.

[0039] More specifically, step S132 involves spectral dispersion and filtering of the mixed scattered light to obtain a spectral signal. It should be understood that the mixed scattered light contains extremely high-intensity Rayleigh scattering light, which coincides with the excitation wavelength and has an intensity far exceeding that of Raman scattering light reflecting the material state. If not removed, this would overwhelm the useful signal. Simultaneously, the mixed light also contains stray light from the external environment, which can interfere with the accurate identification of spectral characteristic peaks. Therefore, this application further performs sequential filtering and spectral dispersion on the mixed scattered light to first eliminate the interference from Rayleigh scattering light and stray light, and then separates the remaining light signal according to wavelength into spectral components corresponding to the Stokes and anti-Stokes regions. This yields a pure spectral signal containing only the vibrational characteristics of the material molecules, ensuring the accuracy of subsequent peak extraction and integral area calculation, and providing a reliable spectral basis for microscopic temperature calculation and curing degree correction.

[0040] Specifically, in one possible embodiment, step S132 is implemented as follows: First, a band-stop filter is installed in the optical signal transmission path of the spectrometer. The band-stop wavelength of this filter perfectly matches the predetermined excitation wavelength of the laser, used to accurately filter out Rayleigh scattering light with an intensity exceeding 90%. Simultaneously, a narrow-bandpass filter is installed behind the band-stop filter to further filter stray light from the external environment. Then, the filtered optical signal is introduced into the spectrometer's built-in grating beam splitting module. A diffraction grating adapted to the wavelength range to be collected is selected, and the rotation angle of the grating is adjusted so that the optical signal is spatially expanded in wavelength order, forming spectral bands corresponding to the Stokes and anti-Stokes regions, respectively. Next, the entrance and exit slit widths of the spectrometer are adjusted to ensure that the spectral resolution meets the requirements for characteristic peak identification. Finally, the expanded spectral signal is accurately projected onto the photosensitive area of ​​the detector, forming a spectral signal that can be subsequently processed.

[0041] More specifically, step S133 involves digitizing the spectral signal to obtain the original full-spectrum data. It should be understood that since the spectral signal after dispersion and filtering is still an analog light signal, it cannot be directly stored, calculated, or used for feedback adjustment by the control system. Furthermore, analog signals are susceptible to electromagnetic interference during transmission, leading to distortion and affecting the accuracy of subsequent data processing. Therefore, this application further converts the analog spectral signal into a digital signal through the spectrometer's signal processing module. This converts the intensity information of the light signal into quantifiable digital data and organizes it into a full-spectrum dataset according to wavelength sequence. This transforms the spectral information into a format suitable for computer analysis, facilitating subsequent calculations of peak positions and integral areas, automating the calculation of microscopic temperature and recalculation of curing degree, while ensuring stable data storage and distortion-free transmission, guaranteeing the real-time performance and accuracy of feedback control.

[0042] Specifically, in one possible embodiment, step S133 is implemented as follows: First, the spectral signal after dispersion is projected onto the linear CCD detector built into the spectrometer. The number of pixels in the detector matches the spectral acquisition range, ensuring that each pixel corresponds to a light signal of a specific wavelength. Then, the detector's integration function is activated, and the integration time is set to match the light signal intensity to avoid detector saturation or a weak signal. After integration, the detector converts the light signal intensity received by each pixel into an analog electrical signal, which is then transmitted to the spectrometer's analog-to-digital converter (A / D) module. The A / D module converts the analog electrical signal into a 16-bit or 32-bit digital quantity, sorts the digital quantities in ascending order of wavelength, and forms a two-dimensional data array with wavelength as the horizontal axis and the digital quantity (corresponding light intensity) as the vertical axis. Finally, the data array is stored in a preset format (such as CSV or binary format), and the acquisition timestamp and corresponding UV light source parameters are associated with it. After storage, the digital data is checked for integrity. Once it is confirmed that there are no data misalignments or missing data, the final raw full-spectrum data is formed.

[0043] In the aforementioned UV curing control method based on real-time spectral monitoring, step S2 involves extracting characteristic peak pairs and analyzing parameters from the original full-spectrum data to obtain the Stokes integral area of ​​the framework peak, the anti-Stokes integral area of ​​the framework peak, the original peak position of the reactant characteristic peak, and the original integral area of ​​the reactant characteristic peak. It should be understood that since the original full-spectrum data contains background noise, stray light interference, and redundant wavelength information, and the framework peak signal reflecting material temperature and the reactant characteristic peak signal reflecting chemical reaction are superimposed, directly using the original data for temperature calculation and degree of cure calculation will lead to parameter extraction deviations. Therefore, this application further performs characteristic peak pair identification and key parameter analysis on the original full-spectrum data to separate the Stokes / anti-Stokes signals of the framework peak and the reactant characteristic peak signals, and extracts core parameters such as integral area and peak position, providing accurate input data for subsequent microscopic temperature calculation and thermally induced drift correction. This eliminates invalid interference information in the original data, ensuring that the peak area ratio used for temperature calculation and the peak position and peak area parameters used for curing degree calculation are accurate and reliable. It avoids failure of thermal drift correction or misjudgment of curing degree due to parameter distortion, and ensures the accuracy of the entire UV curing control logic.

[0044] Specifically, in one possible embodiment, step S2 is implemented as follows: First, the original full-spectrum data is preprocessed by using a polynomial fitting algorithm to subtract baseline background noise and eliminate the influence of spectrometer dark current and external stray light on the signal. Then, the preprocessed spectral data is smoothed using the Savitzky-Golay smoothing algorithm to retain the characteristic peak morphology while reducing high-frequency noise interference. Next, the characteristic peak pair localization stage is entered. Based on the molecular structure characteristics of the material to be cured, Stokes peaks and anti-Stokes peak pairs corresponding to the skeleton peaks (such as the C=C skeleton vibration peaks of material molecules) are identified in the spectral data, and the center wavelength positions of the two peaks are determined using a peak vertex detection algorithm. Simultaneously, the characteristic peaks of the reactants (such as the C=C double bond vibration peaks of acrylate materials) are located, and their original peak coordinates are marked. Then, parameter analysis is performed. Gaussian functions are used to fit the Stokes and anti-Stokes peaks of the skeleton peaks, respectively, and the integral areas of the two peaks are calculated. Similarly, Gaussian fitting is used for the characteristic peaks of the reactants to extract their original peak coordinates and integral areas. Finally, the parameters obtained from the analysis are checked for consistency. After confirming that the wavelength shift of the skeleton peak pairs conforms to the Raman scattering law and that the peak shape of the reactant characteristic peaks has no abnormal distortion, the parameters are stored as structured data for subsequent use by the microscopic temperature calculation module and the thermal drift correction module.

[0045] In the aforementioned UV curing control method based on real-time spectral monitoring, step S3 involves real-time calculation of the microscopic temperature of the Stokes integral area and the anti-Stokes integral area of ​​the framework peak to obtain the real-time microscopic vibrational temperature. It should be understood that since the temperature rise of the material during UV curing originates from the exothermic reaction of photopolymerization and the infrared radiation of the UV light source, external temperature measurements (such as thermocouples) can only obtain the macroscopic surface temperature and cannot reflect the molecular vibrational temperature at the spectral detection point. Furthermore, there is a thermal conduction lag, leading to a spatiotemporal mismatch between temperature data and spectral data during thermal drift correction. Therefore, this application further utilizes the physical correlation between the Stokes and anti-Stokes integral areas of the framework peak to perform real-time calculation of the microscopic temperature, thereby converting the molecular vibrational state implicit in the spectral signal into a quantitative temperature value, achieving spatiotemporal synchronization between temperature and spectral data. This provides microscopic temperature data that perfectly matches the spectral detection point for subsequent thermal drift correction, avoiding peak position and peak area correction deviations caused by inaccurate or delayed temperature data, ensuring the accuracy of the curing degree calculation, and thus ensuring the rationality of the UV light source power adjustment command.

[0046] In particular, in one specific embodiment, Figure 5 This is a flowchart of sub-step S3 of the UV curing control method based on real-time spectral monitoring according to an embodiment of this application. Figure 5As shown, step S3 includes: S31, calculating the peak area ratio and frequency correction factor of the Stokes integral area and the anti-Stokes integral area of ​​the skeleton peak based on the absolute value of the Raman shift of the selected skeleton peak and the wavenumber of the excitation light; S32, performing temperature calculation on the peak area ratio and frequency correction factor to obtain the real-time micro-vibration temperature.

[0047] Specifically, in step S31, based on the absolute value of the Raman shift of the selected skeleton peak and the wavenumber of the excitation light, the peak area ratio and frequency correction factor are calculated for the Stokes integral area and the anti-Stokes integral area of ​​the skeleton peak to obtain the peak area ratio and frequency correction factor. It should be understood that since the Raman scattering intensity is proportional to the fourth power of the scattered light frequency, and the scattering cross-sections of the Stokes scattered light (frequency lower than the excitation light) and the anti-Stokes scattered light (frequency higher than the excitation light) differ, directly using the ratio of their integral areas to calculate the temperature would introduce systematic errors. Furthermore, the peak area ratio needs to be stripped of frequency influence to reflect only the population difference of the molecular vibrational energy levels (which is temperature-dependent). Therefore, this application further combines the absolute value of the Raman shift of the skeleton peak and the wavenumber of the excitation light to calculate the peak area ratio and frequency correction factor, thereby first obtaining the original peak area ratio and then eliminating the influence of frequency on the scattering intensity through the correction factor. In this way, we can obtain the corrected peak area ratio that is only related to the molecular vibration temperature, providing accurate input parameters for subsequent temperature calculations, avoiding temperature calculation deviations caused by the failure to eliminate frequency influences, and ensuring the reliability of microscopic temperature data.

[0048] Specifically, in one possible embodiment, step S31 is implemented as follows: First, the preset absolute value of the Raman shift of the selected skeleton peak and the wavenumber of the excitation light are retrieved from the system parameter library to ensure that the two parameters match the laser currently used and the material to be cured. Then, the Stokes integral area and anti-Stokes integral area of ​​the skeleton peak output by the characteristic peak analysis module are read, and the original peak area ratio is obtained through division (i.e., the Stokes integral area of ​​the skeleton peak divided by the anti-Stokes integral area). Next, based on the excitation light wavenumber and the absolute value of the Raman shift of the skeleton peak, the frequency ratio of the Stokes scattered light and the anti-Stokes scattered light is calculated, and then this frequency ratio is raised to the fourth power to obtain the frequency correction factor. After the calculation is completed, the peak area ratio and the correction factor are checked for validity. If the peak area ratio is not zero and the correction factor is within a reasonable range, i.e., it conforms to the Raman scattering frequency characteristics and there are no abnormalities, the two parameters are temporarily stored in the cache for subsequent temperature calculation steps. At the same time, the source of the parameters and the calculation logic during the calculation process are recorded for subsequent traceability and verification.

[0049] Specifically, step S32 involves calculating the peak area ratio and frequency correction factor to obtain the real-time micro-vibrational temperature. It should be understood that since the peak area ratio, after frequency correction, is only related to the population of the molecular vibrational energy levels, and this population follows the Boltzmann distribution law, it has a quantitative mathematical correlation with the molecular vibrational temperature. Without conversion through theoretical formulas, it is impossible to directly obtain the temperature value that can be used for thermally induced drift correction. Therefore, this application further calculates the peak area ratio and frequency correction factor based on Boltzmann distribution theory to convert the corrected peak area ratio into intuitive quantitative data of micro-vibrational temperature, establishing a direct correspondence between spectral parameters and temperature. In a specific example of this application, step S32 includes: calculating the peak area ratio and frequency correction factor to the temperature using the following formula:

[0050]

[0051] in, For frequency correction factor, The ratio of peak areas. Let be Planck's constant. The speed of light in a vacuum. The absolute value of the Raman displacement. Boltzmann's constant, Let e ​​be the base-e logarithmic function. This refers to the real-time microscopic vibration temperature. That is, first through... , , The product of these factors constructs a quantitative benchmark for molecular vibrational energy, which is then used... Correction The deviation introduced by frequency difference in the middle makes ( This only reflects the change in the population of molecular vibrational energy levels. The exponential relationship of the Boltzmann distribution is then linearized using the natural logarithm, and finally... This coefficient bridge converts energy and population information into specific temperature values. This provides precise temperature input to the thermally induced drift correction module, ensuring that peak shift and peak area correction factors are calculated based on actual molecular vibrational temperatures. This avoids curing degree calculation errors caused by inaccurate temperature data, thus guaranteeing the integrity and accuracy of the temperature, correction, and power regulation links in the UV curing control logic.

[0052] In the aforementioned UV curing control method based on real-time spectral monitoring, step S4 involves recalculating the degree of curing based on the original peak positions and the original integrated areas of the reactant characteristic peaks to obtain an accurate degree of curing. It should be understood that during UV curing, the real-time micro-vibration temperature increase causes thermal drift (peak position shift) and physical changes in peak area of ​​the reactant characteristic peaks. The original peak positions and integrated areas simultaneously contain information about temperature interference and chemical changes. Directly using these for degree of curing calculations can confuse the effects of thermal effects and chemical reactions, leading to misjudgments of the degree of curing. Therefore, this application further combines the original parameters of the reactant characteristic peaks with the real-time micro-vibration temperature to perform thermal drift correction and degree of curing recalculation. This removes the physical interference of temperature on spectral parameters, retaining only the peak position and peak area changes caused by chemical reactions, thus obtaining a degree of curing that reflects the true degree of chemical crosslinking. This avoids misjudgments of false curing or under-curing caused by thermal drift, ensuring accurate and reliable degree of curing data. This provides a correct decision-making basis for subsequent UV light source power adjustment, ensuring the stability of the curing process and the compliance of the mechanical and optical properties of the final product.

[0053] In particular, in one specific embodiment, Figure 6 This is a flowchart of sub-step S4 of the UV curing control method based on real-time spectral monitoring according to an embodiment of this application. Figure 6 As shown, step S4 includes: S41, determining the thermally induced peak position drift and thermally induced peak area correction factor based on real-time micro-vibration temperature; S42, performing peak area normalization correction on the original peak position and original integrated area of ​​the reactant characteristic peak based on the thermally induced peak position drift and thermally induced peak area correction factor to obtain the temperature-corrected reactant peak area; S43, calculating the precise degree of curing based on the temperature-corrected reactant peak area and the corrected peak area at the initial time.

[0054] Specifically, step S41 determines the thermally induced peak position shift and the thermally induced peak area correction factor based on the real-time micro-vibration temperature. It should be understood that as the molecular vibrations of the material to be cured intensify with increasing temperature, the characteristic peak position shifts to lower wavenumbers (thermally induced drift). Simultaneously, changes in intermolecular distance alter light scattering efficiency, resulting in a physical increase or decrease in peak area. Both of these changes are quantitatively related to temperature; without quantification, accurate correction of spectral parameters is impossible. Therefore, this application further uses the real-time micro-vibration temperature as the core basis, combined with preset calibration coefficients, to determine the thermally induced peak position shift and the thermally induced peak area correction factor. This transforms the influence of temperature changes on spectral parameters into calculable quantitative parameters, providing a clear basis for subsequent peak position and peak area correction. This ensures that subsequent correction steps have a unified quantitative standard, avoiding correction deviations caused by inaccurate quantification of temperature effects, guaranteeing the authenticity of the corrected spectral parameters, and laying the foundation for accurate curing degree calculation.

[0055] Specifically, in one possible embodiment, step S41 is implemented as follows: First, the initial reference temperature (the microscopic temperature of the material before curing begins), peak position-temperature drift coefficient (calibrated through previous experiments, reflecting the rate of change of a specific characteristic peak position with temperature), and peak area-temperature influence coefficient (also calibrated through experiments, reflecting the proportion of change of peak area with temperature) are retrieved from the system parameter library. Then, the real-time micro-vibration temperature output by the micro-temperature calculation module is read, and the temperature difference between the real-time temperature and the initial reference temperature is calculated. Based on the product of this temperature difference and the peak position-temperature drift coefficient, the thermally induced peak position drift is obtained; based on this temperature difference and the peak area-temperature influence coefficient, the thermally induced peak area correction factor is calculated using a preset linear function (reflecting the correlation between temperature and peak area influence). After the calculation is completed, the drift and correction factor are checked for range. Once it is confirmed that the drift conforms to the temperature sensitivity characteristics of the material's characteristic peak and that the correction factor is not zero and within a reasonable value range, the two parameters are stored in the correction parameter cache for subsequent peak position and peak area correction steps.

[0056] Specifically, in step S42, based on the thermally induced peak position shift and the thermally induced peak area correction factor, the original peak position and the original integrated area of ​​the reactant characteristic peak are normalized to obtain the temperature-corrected reactant peak area. It should be understood that because the original peak position of the reactant characteristic peak may deviate from the preset integration window due to thermal drift, the original integrated area contains false errors caused by peak position shift. Simultaneously, the original peak area contains physical changes caused by temperature. These two errors can overlap and mask the actual chemical reaction process, resulting in a reduction in peak area due to reactant consumption. Therefore, this application further utilizes the thermally induced peak position shift to dynamically shift the integration interval of the reactant characteristic peak, thereby restoring the peak position to the position at the reference temperature (ensuring the accuracy of the integration window). Specifically, the initially set integration center wavenumber is added to the thermally induced peak position shift to obtain the corrected integration center wavenumber, and the current dynamic integration interval is determined accordingly. Simultaneously, the thermally induced peak area correction factor is used to normalize the original integrated area, thereby restoring the peak area to the value at the reference temperature (eliminating physical changes). In a specific example of this application, step S42 includes: performing peak area normalization correction using the following formula:

[0057]

[0058] in, The original integrated area of ​​the characteristic peaks of the reactants. This is the thermally induced peak area correction factor. This represents the temperature-corrected peak area of ​​the reactants. In other words, it represents the peak area of ​​the reactants. The spurious changes in peak area caused by temperature increase (such as fluctuations in scattering efficiency due to changes in intermolecular distance) are addressed by dividing by... The elimination operation essentially calibrates the original peak areas under different temperature conditions to a reference temperature. This eliminates the physical interference of temperature fluctuations on the peak area, ensuring that the corrected reactant peak areas only retain the changes caused by the chemical reaction, i.e., they are only related to the reactant concentration. This provides a pure chemical signal input free from temperature interference for subsequent curing degree calculations.

[0059] Specifically, step S43 calculates the precise degree of cure based on the temperature-corrected peak area of ​​the reactants and the corrected peak area at the initial moment. It should be understood that since the temperature-corrected peak area of ​​the reactants only reflects changes in reactant concentration (chemical information), the corrected peak area at the initial moment (at t=0, when the temperature has not changed, the corrected area is the original area) serves as a benchmark for the initial reactant concentration. The ratio of the two directly reflects the proportion of reactant consumption, which is then converted into the degree of cure. Without an initial benchmark or without using the corrected area, the reaction progress cannot be accurately quantified. Therefore, this application further calculates the precise degree of cure by comparing the temperature-corrected real-time peak area with the corrected peak area at the initial moment, thereby directly converting changes in spectral parameters into a quantitative indicator reflecting the degree of chemical crosslinking, providing a core decision-making basis for feedback control. In a specific example of this application, step S43 includes: calculating the precise degree of cure using the following formula:

[0060]

[0061] in, This represents the corrected peak area at the initial moment. To ensure precise curing degree, that is, first through... and The ratio is used to calculate the remaining proportion of reactants at real time. Then, subtracting this remaining proportion from 1 gives the consumption proportion of reactants. Finally, multiplying by 100% converts it into a percentage of the degree of curing, achieving a direct conversion from the relative change of the spectral signal to a quantitative value of the chemical crosslinking progress. Since the input peak area has been temperature-corrected, the final output degree of curing is not affected by temperature fluctuations and can accurately reflect the true progress of the chemical reaction. This ensures that the subsequent UV light source power adjustment command can accurately match the reaction progress, guaranteeing complete curing without overheating damage.

[0062] In a preferred embodiment, when performing thermally induced drift correction and recalculating the degree of cure based on the original peak positions and original integrated areas of the reactant characteristic peaks to obtain accurate cure degree, a dynamic self-reference normalization method based on an internal standard peak can be used instead of a correction method based on a pre-calibration function. The skeleton peak used for real-time microtemperature calculation is taken as the internal standard peak. That is, instead of calculating an independent peak area correction factor, the ratio of the original integrated area of ​​the reactant characteristic peak at the current moment to the Stokes integrated area of ​​the internal standard peak at the same moment is directly calculated. This allows for dynamic correction of the reactant characteristic peak area using a chemically stable internal standard peak that is only affected by temperature physical effects. Here, the internal standard peak is the skeleton peak used for calculating the Stokes / anti-Stokes ratio temperature measurement, and its Stokes peak area is denoted as... .

[0063] Specifically, step S4 includes: employing a dynamic self-reference normalization method based on an internal standard peak, using the skeleton peak used for real-time micro-temperature calculation as the internal standard peak; calculating the ratio of the original integral area of ​​the reactant characteristic peak at the current moment to the Stokes integral area of ​​the internal standard peak at the same moment to obtain the normalized reactant ratio; and calculating the accurate degree of cure based on the normalized reactant ratio at the current moment and the normalized reactant ratio at the initial moment. That is, when relying on a pre-calibrated function to obtain the thermally induced peak area correction factor from the real-time micro-vibration temperature, since this function (e.g., a simplified linear model) is an approximation of a complex physical process, and the actual peak area-temperature relationship may be non-linear, using a simplified model will introduce systematic model errors. Furthermore, the calibration coefficients may change for different batches of UV adhesives, different substrates, and even small long-term drifts in the spectrometer's optical path, causing the pre-calibrated model to fail, which reduces the robustness and versatility of the method.

[0064] Considering that under the same spectrum and measurement conditions, the physical effect of temperature on the area of ​​any Raman peak (mainly caused by changes in Boltzmann distribution and refractive index, etc.) is homogeneous and proportional, that is, if an increase in temperature causes the area of ​​the reactant peak to decrease by 10% due to physical effects, then the area of ​​the internal standard peak will also decrease by approximately 10% due to physical effects. If we let... For reactants at time The true peak area contribution determined solely by its chemical concentration makes The contribution of the peak area determined by the chemical concentration of the internal standard is a constant because it does not participate in the reaction. Therefore, the actual measured peak area can be expressed as... , ,in, It is an unknown but identical function representing all complex temperature physical effects. Furthermore, by calculating the ratio of the areas of these two peaks, this unknown temperature influence function can be eliminated, that is:

[0065]

[0066] This ratio is directly proportional to the actual chemical concentration of the reactants and is completely unaffected by the physical effects of temperature. Thus, because self-referencing and self-calibration are essentially performed at each time point, it can compensate for common-mode variations affecting the entire spectrum, such as fluctuations in light source power (i.e., if the laser power jitters instantaneously, the areas of the two peaks will change proportionally, and their ratio remains stable), changes in optical path coupling efficiency (i.e., if the sample moves slightly, causing a change in collection efficiency, the areas of the two peaks will also change proportionally, and their ratio remains stable), and batch differences in materials (i.e., even if a new batch of adhesive causes differences in the overall Raman signal intensity, as long as the relative proportions of the internal standard peak and reactant peaks are determined in the initial state, subsequent calculations remain valid).

[0067] Therefore, based on the original integral area of ​​the characteristic peaks of the reactants Stokes integral area of ​​the internal standard peak (i.e., the skeleton peak) Calculate the normalized ratio, that is, at time... The original integral area of ​​the characteristic peaks of the reactants Divided by the Stokes integral area of ​​the internal standard peak at the same time For example, the ratio is denoted as It is a quantity that has eliminated the physical effects of temperature and is directly proportional to the chemical concentration of the reactants.

[0068] Thus, when calculating the precise degree of cure, the normalized reactant ratio at the current moment is used. and the initial time ( Normalized reactant ratio (This needs to be calculated and stored as a baseline value at the start of curing), then the degree of cure. The exact degree of cure is calculated using the following formula, which is equal to the relative decrease in the normalized reactant ratio:

[0069]

[0070] in, To ensure precise curing degree, This represents the normalized reactant ratio at the current moment. This represents the normalized reactant ratio at the initial moment.

[0071] Therefore, by eliminating the model approximation error caused by the pre-calibration function, the accuracy of curing degree calculation can be significantly improved, and it has stronger robustness to light source fluctuations, optical path drift, and material batch differences, making it more suitable for complex industrial production environments. Furthermore, because the tedious and easily failed peak area-temperature function calibration is no longer required, it only needs to be performed before curing begins (…). The initial ratio can be obtained, which greatly simplifies the deployment and maintenance process.

[0072] In the aforementioned UV curing control method based on real-time spectral monitoring, step S5 involves performing dual-variable collaborative feedback control on the precise degree of curing and the real-time micro-vibration temperature to obtain the final UV light source power control command. It should be understood that single-variable control (based solely on degree of curing or solely on temperature) cannot balance the reaction efficiency and thermal safety of UV curing. Adjusting power solely based on degree of curing can easily lead to excessive power increases to accelerate the process, causing material overheating, yellowing, and internal stress cracking. Adjusting power solely based on temperature can easily lead to excessive power reduction due to temperature control, resulting in insufficient curing and affecting product strength. Therefore, this application further constructs a collaborative feedback control logic using precise degree of curing and real-time micro-vibration temperature as dual inputs to simultaneously manage the chemical reaction progress and molecular vibration temperature, achieving dynamic adaptation of UV light source power. This ensures that the degree of curing efficiently approaches the target value while strictly limiting the temperature within the material's safety threshold, avoiding the drawbacks of single control, ensuring stable curing processes, and guaranteeing that the mechanical, optical, and weather-resistant properties of the final product meet design requirements.

[0073] Specifically, in one possible embodiment, step S5 is implemented as follows: First, the hardware linkage debugging of the feedback control module and the UV light source drive unit is completed. Signal simulation testing confirms that the control command transmission delay is less than 10 milliseconds, meeting real-time control requirements. Then, the precise degree of cure output from the thermal drift correction module and the real-time micro-vibration temperature output from the micro-temperature calculation module are retrieved from the data bus. Simultaneously, preset process parameters are retrieved, namely the target degree of cure, the maximum allowable micro-temperature of the material, and the rated power range of the UV light source. After starting the control program, the first step is to construct a dual-loop control logic: the main loop uses the precise degree of cure as the control object, employs a PID algorithm to calculate the degree of cure deviation (the difference between the target value and the real-time value), and outputs a basic UV power command. The secondary loop uses the real-time micro-vibration temperature as the control object. If the temperature is below the maximum value, a power suppression factor of 1 is generated; if the temperature exceeds the limit, a suppression factor in the 0-1 range is generated based on the over-temperature amplitude, with the factor decreasing as the over-temperature amplitude increases. The second step is to multiply the basic power command by the suppression factor to obtain the final UV light source power control command. Finally, the validity of the instruction is verified to ensure that it is within the rated power range of the light source and that the change in power from the previous instruction is less than 5% to avoid sudden power fluctuations. After the verification is passed, the instruction is transmitted to the UV light source drive unit to drive the light source to adjust the output power. At the same time, the instruction generation timestamp and corresponding parameters are recorded in the process log.

[0074] In summary, the UV curing control method based on real-time spectral monitoring, as described in this application, is explained. First, raw full-spectrum data is acquired, and the parameters of the framework peaks and reactant characteristic peaks are analyzed. The micro-vibration temperature is calculated in real-time using the Stokes and anti-Stokes integral areas of the framework peaks. Subsequently, thermally induced drift correction is performed on the reactant characteristic peaks based on this temperature data to eliminate the interference of temperature fluctuations on the spectral signal, thereby reconstructing the accurate degree of curing. Furthermore, a bivariate collaborative feedback control model based on the accurate degree of curing and micro-temperature is established to comprehensively evaluate the chemical reaction progress and thermal safety threshold, and adaptively and dynamically optimize the UV light source power. This effectively overcomes the spectral misjudgment problem caused by photothermal coupling, achieving precise closed-loop control of the chemical reaction and thermal effects during the curing process, thereby improving the stability of the curing process and product quality.

[0075] Figure 7 This is a block diagram of a UV curing control system based on real-time spectral monitoring according to an embodiment of this application. Figure 7As shown, the UV curing control system 100 based on real-time spectral monitoring according to an embodiment of this application includes: a raw full-spectrum data acquisition module 110, used to acquire raw full-spectrum data; a characteristic peak pair extraction and analysis module 120, used to extract characteristic peak pairs and analyze parameters from the raw full-spectrum data to obtain the Stokes integral area of ​​the skeleton peak, the anti-Stokes integral area of ​​the skeleton peak, the original peak position of the reactant characteristic peak, and the original integral area of ​​the reactant characteristic peak; a micro-temperature calculation module 130, used to perform real-time micro-temperature calculation on the Stokes integral area of ​​the skeleton peak and the anti-Stokes integral area of ​​the skeleton peak to obtain the real-time micro-vibration temperature; a curing calculation module 140, used to recalculate the degree of curing based on the original peak position and the original integral area of ​​the reactant characteristic peak to obtain the accurate degree of curing; and a bivariate collaborative feedback control module 150, used to perform bivariate collaborative feedback control on the accurate degree of curing and the real-time micro-vibration temperature to obtain the final UV light source power control command.

[0076] As described above, the UV curing control system 100 based on real-time spectral monitoring according to the embodiments of this application can be implemented in various wireless terminals, such as servers with UV curing control algorithms based on real-time spectral monitoring. In one possible implementation, the UV curing control system 100 based on real-time spectral monitoring according to the embodiments of this application can be integrated into the wireless terminal as a software module and / or a hardware module. For example, the UV curing control system 100 based on real-time spectral monitoring can be a software module in the operating system of the wireless terminal, or it can be an application developed for the wireless terminal; of course, the UV curing control system 100 based on real-time spectral monitoring can also be one of many hardware modules of the wireless terminal.

[0077] Alternatively, in another example, the UV curing control system 100 based on real-time spectral monitoring and the wireless terminal can also be separate devices, and the UV curing control system 100 based on real-time spectral monitoring can be connected to the wireless terminal via wired and / or wireless networks, and transmit interactive information in accordance with an agreed data format.

[0078] Here, those skilled in the art will understand that the specific operations of each step in the UV curing control system based on real-time spectral monitoring described above have been referenced. Figures 1 to 6 The method for controlling UV curing based on real-time spectral monitoring has been described in detail in the previous section, and therefore, its repeated description will be omitted.

Claims

1. A UV curing control method based on real-time spectral monitoring, characterized in that, include: Obtain the raw full spectrum data; Characteristic peak pairs were extracted and parameters were analyzed from the original full spectrum data to obtain the Stokes integral area of ​​the skeleton peak, the anti-Stokes integral area of ​​the skeleton peak, the original peak position of the reactant characteristic peak, and the original integral area of ​​the reactant characteristic peak. The micro-temperature of the skeleton peak is calculated in real time by solving the Stokes integral area and the anti-Stokes integral area of ​​the skeleton peak to obtain the real-time micro-vibration temperature. The degree of cure is recalculated based on the original peak positions and the original integral areas of the characteristic peaks of the reactants to obtain the accurate degree of cure. A dual-variable collaborative feedback control of precise curing degree and real-time micro-vibration temperature is used to obtain the final UV light source power control command.

2. The UV curing control method based on real-time spectral monitoring according to claim 1, characterized in that, Obtain the raw full spectrum data, including: The material to be cured is excited by a single laser, wherein the single laser has a predetermined excitation wavelength; Configure the spectrometer to cover the Stokes region and anti-Stokes region symmetrically distributed on both sides of the predetermined excitation wavelength; The raw full-spectrum data was acquired using a spectrometer.

3. The UV curing control method based on real-time spectral monitoring according to claim 2, characterized in that, The raw full-spectrum data was acquired using a spectrometer, including: Mixed scattered light was collected using a spectrometer; The mixed scattered light is subjected to spectral dispersion and filtering to obtain the spectral signal; The spectral signal is digitized to obtain the raw full-spectrum data.

4. The UV curing control method based on real-time spectral monitoring according to claim 1, characterized in that, The real-time micro-temperature is obtained by calculating the Stokes integral area and the anti-Stokes integral area of ​​the skeleton peaks, including: Based on the absolute value of the Raman shift of the selected skeleton peak and the wavenumber of the excitation light, the peak area ratio and frequency correction factor are calculated for the Stokes integral area and the anti-Stokes integral area of ​​the skeleton peak to obtain the peak area ratio and frequency correction factor. Temperature calculations were performed on the peak area ratio and frequency correction factor to obtain the real-time micro-vibration temperature.

5. The UV curing control method based on real-time spectral monitoring according to claim 1, characterized in that, To obtain the real-time micro-vibration temperature, the peak area ratio and frequency correction factor are calculated for temperature. This includes calculating the peak area ratio and frequency correction factor for temperature using the following formula: in, For frequency correction factor, The ratio of peak areas. Let be Planck's constant. The speed of light in a vacuum. The absolute value of the Raman displacement. Boltzmann's constant, Let e ​​be the base-e logarithmic function. This refers to the real-time microscopic vibration temperature.

6. The UV curing control method based on real-time spectral monitoring according to claim 1, characterized in that, The degree of cure is recalculated based on the original peak positions and original integrated areas of the characteristic peaks of the reactants to obtain the accurate degree of cure, including: Based on real-time micro-vibration temperature, the amount of thermally induced peak position shift and the thermally induced peak area correction factor are determined. Based on the thermally induced peak position shift and the thermally induced peak area correction factor, the original peak position and the original integrated area of ​​the reactant characteristic peak are normalized and corrected to obtain the temperature-corrected reactant peak area. The precise degree of cure is calculated based on the temperature-corrected peak area of ​​the reactants and the corrected peak area at the initial moment.

7. The UV curing control method based on real-time spectral monitoring according to claim 6, characterized in that, Based on the thermally induced peak position shift and the thermally induced peak area correction factor, the original peak position and the original integrated area of ​​the reactant characteristic peak are normalized to obtain the temperature-corrected reactant peak area. This includes performing peak area normalization correction using the following formula: in, The original integrated area of ​​the characteristic peaks of the reactants. This is the thermally induced peak area correction factor. This represents the temperature-corrected peak area of ​​the reactants.

8. The UV curing control method based on real-time spectral monitoring according to claim 6, characterized in that, The precise degree of cure is calculated based on the temperature-corrected peak area of ​​the reactants and the corrected peak area at the initial moment, including: calculating the precise degree of cure using the following formula, wherein the formula is: in, This represents the corrected peak area at the initial moment. For precise curing degree.

9. The UV curing control method based on real-time spectral monitoring according to claim 1, characterized in that, The degree of cure is recalculated based on the original peak positions and original integrated areas of the characteristic peaks of the reactants to obtain the accurate degree of cure, including: A dynamic self-reference normalization method based on internal standard peaks is adopted, and the skeleton peaks used for real-time micro-temperature calculation are used as internal standard peaks. The normalized reactant ratio is obtained by calculating the ratio of the original integral area of ​​the characteristic peak of the reactant at the current moment to the Stokes integral area of ​​the internal standard peak at the same moment. Based on the normalized reactant ratio at the current moment and the normalized reactant ratio at the initial moment, the precise degree of cure is calculated according to the following formula: in, To ensure precise curing degree, This represents the normalized reactant ratio at the current moment. This represents the normalized reactant ratio at the initial moment.

10. A UV curing control system based on real-time spectral monitoring, characterized in that, include: The raw full spectrum data acquisition module is used to acquire raw full spectrum data; The characteristic peak pair extraction and analysis module is used to extract characteristic peak pairs and analyze parameters from the original full spectrum data to obtain the Stokes integral area of ​​the skeleton peak, the anti-Stokes integral area of ​​the skeleton peak, the original peak position of the reactant characteristic peak, and the original integral area of ​​the reactant characteristic peak. The micro-temperature calculation module is used to calculate the micro-temperature in real time from the Stokes integral area and the anti-Stokes integral area of ​​the skeleton peak to obtain the real-time micro-vibration temperature. The curing calculation module is used to recalculate the degree of curing based on the original peak positions and the original integral areas of the characteristic peaks of the reactants to obtain the accurate degree of curing. The dual-variable collaborative feedback control module is used to perform dual-variable collaborative feedback control on the precise curing degree and real-time micro-vibration temperature to obtain the final UV light source power control command.

Images