Verification system in photoinitiator preparation process and preparation process thereof

Abstract

The invention provides a verification system in a photoinitiator preparation process and a preparation process thereof, and relates to the technical field of photoinitiator evaluation and verification, the verification system in the photoinitiator preparation process comprises a sample analysis unit, an index acquisition unit, a purity evaluation unit and a standard comparison unit, the sample analysis unit, the index acquisition unit, the purity evaluation unit and the standard comparison unit are connected in sequence. According to the method, the purity of the photoinitiator can be scientifically and objectively evaluated, the evaluation result is compared with the preset evaluation standard, the objectivity and consistency of the verification result are ensured through the standardized comparison mode, whether the photoinitiator meets the preparation requirement or not can be determined through comparison, and the accuracy of the photoinitiator is improved. And a reliable basis is provided for subsequent production and use.

Description

Technical Field

[0001] The present invention relates to the technical field of photoinitiator evaluation and verification, and in particular to a verification system and a preparation process thereof in a photoinitiator preparation process. Background Art

[0002] Photoinitiators are a special class of chemicals that can absorb light energy within a specific wavelength range (usually in the ultraviolet or visible light region) and initiate chemical reactions. These substances play a vital role in photocuring technology. Their main function is to generate free radicals or cations under light conditions, thereby stimulating the polymerization reaction of monomers or prepolymers. This process allows the material to quickly transform from a liquid or semi-solid state to a solid state and achieve curing. The selection and application of photoinitiators are crucial to the performance of photocuring systems because their efficiency and spectral absorption characteristics directly affect the speed and quality of material curing. For example, during the manufacturing process, the use of photoinitiators can accurately control the curing process, which has significant industrial application value for the production of high-performance optoelectronic devices, coatings, adhesives and 3D printing materials.

[0003] In addition, when selecting and applying photoinitiators, environmental stability, toxicity and mobility are key factors that must be considered. By optimizing the chemical structure and functional properties of these substances, safer and more efficient photoinitiator systems can be developed to meet the stringent requirements of modern industry and science and technology. Therefore, purity verification is particularly important during the preparation of photoinitiators. However, existing purity verification methods often only focus on single indicators, such as purity, impurity content, etc., and lack a comprehensive evaluation of the overall performance of photoinitiators. This may lead to the neglect of certain key performance indicators, thereby affecting the actual application effect of the product.

[0004] Currently, no effective solution has been proposed for the problems in the related technologies. Summary of the invention

[0005] In view of this, in order to solve the problems in the related art, the present invention provides a verification system and a preparation process of a photoinitiator to solve the problem that the existing purity verification methods mentioned above often only focus on a single indicator.

[0006] In order to solve the above problems, the specific technical solutions adopted by the present invention are as follows: According to one aspect of the present invention, a verification system in a photoinitiator preparation process is provided, the verification system in a photoinitiator preparation process comprises: a sample analysis unit, an index acquisition unit, a purity evaluation unit and a standard comparison unit, and the sample analysis unit, the index acquisition unit, the purity evaluation unit and the standard comparison unit are connected in sequence; A sample analysis unit, used for obtaining a photoinitiator sample and obtaining chromatographic data of the photoinitiator sample by using a chromatographic analysis method; An index acquisition unit, used for extracting purity index data of the photoinitiator by wavelet transform method according to the obtained chromatographic data; A purity evaluation unit, used to evaluate and verify the purity of the photoinitiator based on the purity index data of the photoinitiator and based on the target decision evaluation method; A standard comparison unit is used to compare the obtained evaluation results with the pre-set evaluation standards and determine whether the photoinitiator meets the preparation requirements; The purity evaluation unit includes: a judgment matrix construction module, an optimal weight determination module, a superiority matrix construction module, an evaluation value calculation module and a comprehensive evaluation calculation module, and the judgment matrix construction module, the optimal weight determination module, the superiority matrix construction module, the evaluation value calculation module and the comprehensive evaluation calculation module are connected in sequence; A judgment matrix construction module is used to compare the purity index data of the photoinitiator in pairs based on the interval analytic hierarchy process, and to construct an interval importance judgment matrix according to the comparison results; The optimal weight determination module is used to establish a weight target optimization model based on the interval importance judgment matrix and determine the optimal weight value of each purity index through an improved radial movement algorithm; A superiority matrix construction module is used to determine the relative degree of membership of each purity index based on the degree of membership method, and to construct a relative superiority matrix of each purity index; An evaluation value calculation module is used to calculate the evaluation value of each purity index according to the optimal weight value and relative superiority matrix of each purity index; The comprehensive evaluation calculation module is used to comprehensively evaluate the purity of the photoinitiator according to the evaluation values ​​of each purity index to obtain a comprehensive evaluation value.

[0007] Preferably, the sample analysis unit comprises: a sample injection module, a chromatographic analysis module and a signal acquisition storage module, and the sample injection module, the chromatographic analysis module and the signal acquisition storage module are connected in sequence; A sample injection module is used to dissolve and dilute the sample obtained from the photoinitiator, and inject the dissolved and diluted sample into a pre-set chromatographic instrument; A chromatography analysis module, used for performing chromatography analysis on the dissolved and diluted sample by a chromatography instrument based on a thin layer chromatography analysis method; The signal acquisition storage module is used to acquire the detection signals of each component of the photoinitiator sample through a mass spectrometer detector and store them.

[0008] Preferably, the index acquisition unit includes: a preprocessing module, a signal decomposition module and a purity index determination module, and the preprocessing module, the signal decomposition module and the purity index determination module are connected in sequence; A preprocessing module is used to perform baseline correction and noise filtering on the obtained chromatographic data; A signal decomposition module is used to perform scale analysis on the processed chromatographic data through wavelet transform and extract wavelet coefficients at each scale; The purity index determination module is used to extract features of the peaks at each scale based on the extracted wavelet coefficients to determine the purity index of the photoinitiator.

[0009] Preferably, based on the extracted wavelet coefficients, feature extraction is performed on the peaks at each scale to determine the purity index of the photoinitiator including: According to the extracted wavelet coefficients, the peaks in the chromatographic data are identified and their starting points, peak apex and end points are located; Determine characteristic parameters of peaks in the chromatographic data according to the recognition results; The purity index of the photoinitiator is determined by using the extracted characteristic parameters combined with prior knowledge.

[0010] Preferably, based on the interval importance judgment matrix, establishing a target optimization model and determining the optimal weight value of each purity index data by an improved radial movement algorithm include: For the interval numbers in the interval importance judgment matrix, the separation degree between each interval number is calculated by the separation degree theory; The objective function is to minimize the sum of the degrees of separation of the interval importance judgment matrix, and the target optimization model is established with the sum of the weight values ​​of each purity index data being 1 and the value range of the weight value as constraints; The objective function is taken as the fitness function, and the target optimization model is solved by improving the radial movement algorithm to obtain the optimal weight value of each purity index data.

[0011] Preferably, the calculation formula for calculating the separation degree between each interval number by separation degree theory is: ; In the formula, G ( B ij , K ij ) represents the number of intervals B ij and K ij The separation degree; K ij Indicates i Purity index data and jThe pairwise judgment range of purity index data when comparing their importance; ( x ij , y ij ) represents the number of intervals B ij The range of the interval; n Indicates the number of purity indicators.

[0012] Preferably, the objective function is used as the fitness function, and the target optimization model is solved by an improved radial movement algorithm to obtain the optimal weight value of each purity index data, including: Initialize the parameters of the improved radial movement algorithm and randomly generate a population of weighted solutions; Use the objective function as the fitness function and calculate the fitness function value of each weight solution; Calculate the fitness function value for each weight solution and update the weight solution; The fitness evaluation and weight solution update are repeated through the iterative optimization method until the preset number of iterations is reached, and the optimal weight value of each purity index data is output.

[0013] Preferably, the calculation formula of the fitness function is: ; In the formula, f represents the fitness function; G ( B ij , K ij ) represents the number of intervals B ij and K ij The separation degree; K ij Indicates i Purity index data and j The pairwise judgment range of purity index data when comparing their importance; ( x ij , y ij ) represents the number of intervals B ij The range of the interval; n Indicates the number of purity indicators; w i Indicates i The optimal weight value of each purity index data; w j Indicates j The optimal weight value of the purity index data.

[0014] Preferably, determining the relative membership of each purity index based on the membership method and constructing a relative superiority matrix of each purity index includes: An evaluation scale is set for each purity index, and the membership of each purity index on each evaluation scale is calculated through the membership function; Compare the membership of each purity index on the same evaluation scale, and determine the membership of each index relative to other indexes to obtain the relative membership; According to the relative membership value of each purity index relative to other indicators, the relative superiority matrix of each purity index is constructed.

[0015] According to another aspect of the present invention, a photoinitiator preparation process is provided, the photoinitiator preparation process comprising the following steps: S1, subjecting the acyl chloride, aluminum chloride and solvent to a Friedel-Crafts reaction with benzene, and sending the resulting Friedel-Crafts reaction product to a gas-liquid separation tank to separate hydrogen chloride gas and a first reaction liquid; S2, quenching the first reaction solution with hydrochloric acid, and standing for phase separation after quenching, adding the organic phase to a thin film evaporator to separate the solvent, and obtaining a Friedel-Crafts reaction intermediate; S3, mixing the Friedel-Crafts reaction intermediate with chlorine gas to perform a chlorination reaction, and separating the gas and the second reaction liquid from the chlorination reaction product; S4, mixing the sodium hydroxide solution and the phase transfer catalyst evenly, and subjecting the mixed product to a hydrolysis reaction with the second reaction solution, and sequentially passing the hydrolysis reaction product into a buffer tank and a phase separation tank to obtain a crude product organic phase, and purifying the crude product organic phase to obtain a photoinitiator; S5, obtaining a photoinitiator sample, and obtaining chromatographic data of the photoinitiator sample by using a chromatographic analysis method; S6. Extracting purity index data of the photoinitiator by wavelet transform method according to the obtained chromatographic data; S7. Based on the purity index data of the photoinitiator, the purity of the photoinitiator is evaluated and verified based on the target decision evaluation method; S8. Compare the obtained evaluation results with the pre-set evaluation criteria, and determine whether the photoinitiator meets the preparation requirements.

[0016] Compared with the prior art, the present invention provides a verification system and a preparation process of a photoinitiator, which has the following beneficial effects: (1) The present invention forms an automated process by sequentially connecting a sample analysis unit, an index acquisition unit, a purity evaluation unit, and a standard comparison unit, which not only improves the efficiency of verification, but also reduces the error of human operation, thereby ensuring the accuracy of the verification result. The purity of the photoinitiator is evaluated and verified based on the target decision evaluation method. This evaluation method combines professional knowledge and practical experience, and can scientifically and objectively evaluate the purity of the photoinitiator. The evaluation result is compared with the pre-set evaluation standard. This standardized comparison method ensures the objectivity and consistency of the verification result. Through comparison, it can be determined whether the photoinitiator meets the preparation requirements, thereby providing a reliable basis for subsequent production and use.

[0017] (2) The present invention performs baseline correction and noise filtering on the chromatographic data, effectively improving the signal-to-noise ratio of the data and enhancing the reliability and accuracy of the data. The processed chromatographic data are subjected to scale analysis through wavelet transform, and the wavelet coefficients at each scale are extracted. This multi-scale analysis method can capture the characteristics of different frequency components in the chromatographic data, thereby achieving more refined feature extraction.

[0018] (3) The present invention takes minimizing the sum of the degrees of separation of the interval importance judgment matrix as the objective function, which can ensure that the weight distribution is more reasonable, reduce the deviation caused by subjective judgment, and help improve the accuracy and reliability of purity evaluation. By solving the target optimization model through the improved radial movement algorithm, the optimal weight value of each purity index data can be efficiently found. It combines randomness and deterministic search strategies, has a faster convergence speed and better global search ability, and determines the relative superiority of each purity index based on the membership method. It can clearly reflect the performance of each purity index on the evaluation scale. By calculating the degrees of separation and membership between interval numbers, the relationship and difference between purity indicators can be deeply understood, which provides rich information for purity evaluation, helps to explain the evaluation results and guide subsequent optimization work. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings: Figure 1 is a principle block diagram of a verification system in a photoinitiator preparation process according to an embodiment of the present invention; Figure 2 4 is a flow chart of a process for preparing a photoinitiator according to an embodiment of the present invention.

[0020] In the figure: 1. Sample analysis unit; 2. Index acquisition unit; 3. Purity assessment unit; 4. Standard comparison unit. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0022] According to an embodiment of the present invention, a verification system and a preparation process of a photoinitiator are provided.

[0023] The present invention is further described with reference to the accompanying drawings and specific embodiments. Figure 1 As shown, according to the verification system and preparation process of the photoinitiator preparation process according to the embodiment of the present invention, the verification system in the photoinitiator preparation process includes: a sample analysis unit 1, an index acquisition unit 2, a purity evaluation unit 3 and a standard comparison unit 4, and the sample analysis unit 1, the index acquisition unit 2, the purity evaluation unit 3 and the standard comparison unit 4 are connected in sequence; The sample analysis unit 1 is used to obtain a photoinitiator sample and obtain chromatographic data of the photoinitiator sample by using a chromatographic analysis method; As a preferred embodiment, the sample analysis unit 1 comprises: a sample injection module, a chromatographic analysis module and a signal acquisition storage module, and the sample injection module, the chromatographic analysis module and the signal acquisition storage module are connected in sequence; A sample injection module is used to dissolve and dilute the sample obtained from the photoinitiator, and inject the dissolved and diluted sample into a pre-set chromatographic instrument; It should be noted that a suitable solvent is selected according to the chemical properties of the photoinitiator. Commonly used solvents include methanol, acetonitrile, water or a mixed solvent thereof. According to the analysis requirements, the dissolved sample needs to be further diluted to reach a concentration range suitable for chromatographic analysis. The diluted sample needs to be fully mixed to ensure the uniformity of the sample.

[0024] A chromatography analysis module, used for performing chromatography analysis on the dissolved and diluted sample by a chromatography instrument based on a thin layer chromatography analysis method; It should be noted that thin layer chromatography is a commonly used chromatographic technique that is particularly suitable for separating and identifying compounds in complex mixtures. In thin layer chromatography, samples are separated on a thin layer plate coated with a stationary phase.

[0025] The signal acquisition storage module is used to acquire the detection signals of each component of the photoinitiator sample through a mass spectrometer detector and store them.

[0026] It should be noted that the mass spectrometer detector converts the photoinitiator sample molecules into ions. This is usually achieved through an ionization source, such as electron bombardment ionization, chemical ionization, etc. During the ionization process, the sample molecules lose or gain electrons to form charged ions, and the ionized ions are introduced into the analyzer of the mass spectrometer detector. The main function of the analyzer is to separate the ions according to their mass and charge for subsequent detection; in the analyzer, the ions are deflected or separated by an electric or magnetic field. Ions of different masses are subjected to different forces in the electric or magnetic field, so that they move in different paths to achieve mass separation. The separated ions enter the detector. The detector measures the relative abundance of the ions (that is, the number of ions) and generates a corresponding signal.

[0027] An index acquisition unit 2 is used to extract the purity index data of the photoinitiator by wavelet transform method according to the obtained chromatographic data; As a preferred embodiment, the index acquisition unit 2 includes: a preprocessing module, a signal decomposition module and a purity index determination module, and the preprocessing module, the signal decomposition module and the purity index determination module are connected in sequence; A preprocessing module is used to perform baseline correction and noise filtering on the obtained chromatographic data; It should be noted that the purpose of baseline correction is to eliminate the influence of the instrument's own offset and noise on the actual sample signal. Common baseline correction methods include zero point correction, reference material method and linear model method.

[0028] Noise filtering is to reduce random errors and interference signals in chromatographic data and improve the signal-to-noise ratio of the data. Common noise filtering methods include data smoothing and Fourier filtering.

[0029] A signal decomposition module is used to perform scale analysis on the processed chromatographic data through wavelet transform and extract wavelet coefficients at each scale; Specifically, performing scale analysis on the processed chromatographic data by wavelet transform and extracting wavelet coefficients at each scale includes the following steps: The processed chromatographic data are subjected to wavelet transform using wavelet basis functions; wavelet transform decomposes the original signal into a series of wavelet coefficients, which describe the characteristics of the signal at different time-frequency scales; After obtaining the wavelet coefficients, scale analysis can be performed. Scale analysis refers to studying the characteristics of signals at different scales. For chromatographic data, we can observe the wavelet coefficients at different scales; According to the results of scale analysis, wavelet coefficients at various scales can be extracted, and these coefficients contain detailed information of the signal at different scales; The purity index determination module is used to extract features of the peaks at each scale based on the extracted wavelet coefficients to determine the purity index of the photoinitiator.

[0030] As a preferred embodiment, based on the extracted wavelet coefficients, feature extraction is performed on the peaks at each scale to determine the purity index of the photoinitiator including: According to the extracted wavelet coefficients, the peaks in the chromatographic data are identified and their starting points, peak apex and end points are located; It should be noted that by analyzing the extracted wavelet coefficients, the chromatographic peaks are identified, which are usually manifested as local maxima or minima of the wavelet coefficients, and the starting point, highest point (peak) and end point of each peak are determined. This usually involves finding the turning point in the coefficients, that is, the point where it changes from positive to negative or from negative to positive.

[0031] Determine characteristic parameters of peaks in the chromatographic data according to the recognition results; It should be noted that according to the position of each peak, characteristic parameters such as peak height (amplitude of peak coefficient), peak width (distance between the starting and ending points) and peak area (total area under the peak, which can be obtained by integration coefficient) are extracted.

[0032] The purity index of the photoinitiator is determined by using the extracted characteristic parameters combined with prior knowledge.

[0033] It should be noted that the characteristic parameters of the chromatographic peaks identified and located by wavelet transform (such as starting point, peak apex, end point, peak height, peak width and peak area) are sorted out. The importance of each parameter in determining the purity index is evaluated. For example, the peak area is usually directly related to the concentration of the component, while the peak shape and width can provide information about the sample purity and component separation.

[0034] Combined with prior knowledge, the most relevant indicators are selected from the characteristic parameters taking into account the chemical properties of the photoinitiator. For example: If purity and concentration are of concern, peak area and height are likely to be the primary parameters of concern.

[0035] If identification of components is of concern, retention time and peak shape parameters such as tail factor or symmetry factor become more important.

[0036] Quantitative chemical analysis methods such as external standard method or internal standard method are used to calculate the absolute or relative content of each component.

[0037] A purity evaluation unit 3, used for evaluating and verifying the purity of the photoinitiator based on the purity index data of the photoinitiator and based on the target decision evaluation method; As a preferred embodiment, the purity evaluation unit 3 includes: a judgment matrix construction module, an optimal weight determination module, a superiority matrix construction module, an evaluation value calculation module and a comprehensive evaluation calculation module, and the judgment matrix construction module, the optimal weight determination module, the superiority matrix construction module, the evaluation value calculation module and the comprehensive evaluation calculation module are connected in sequence; A judgment matrix construction module is used to compare the purity index data of the photoinitiator in pairs based on the interval analytic hierarchy process, and to construct an interval importance judgment matrix according to the comparison results; Specifically, based on the interval analytic hierarchy process, the purity index data of the photoinitiator are compared pairwise, and the interval importance judgment matrix is ​​constructed according to the comparison results, including the following steps: For each purity indicator, a pairwise comparison is required to determine their relative importance. This comparison is usually based on expert opinion or historical data; the result of the pairwise comparison is no longer a definite value (such as a 1-9 scale), but an interval value. For example, if indicator A is considered slightly more important than indicator B, then an interval such as [1.2, 1.5] is given instead of a definite number such as 1.3; The results of the pairwise comparisons are combined into a matrix, namely the interval importance judgment matrix. Each row of this matrix represents an indicator, and each column also represents an indicator. The elements in the matrix represent the interval importance of the row indicator relative to the column indicator.

[0038] Assuming there are three purity indicators A, B, and C, the results of pairwise comparison are as follows: A is slightly more important than B: [1.2,1.5]; A is significantly more important than C: [2.0, 2.5]; And B is slightly less important than A (that is, the inverse of A’s slight importance relative to B): [1 / 1.5, 1 / 1.2] = [0.67, 0.83]; The importance of B relative to C is between A and C: [1.5, 2.0] (hypothesis); The importance of C relative to A is the reciprocal of the importance of A relative to C: [1 / 2.5, 1 / 2.0] = [0.4, 0.5]; The importance of C relative to B and the importance of B relative to C are reciprocals of each other: [1 / 2.0,1 / 1.5]=[0.5,0.67].

[0039] The optimal weight determination module is used to establish a weight target optimization model based on the interval importance judgment matrix and determine the optimal weight value of each purity index through an improved radial movement algorithm; As a preferred implementation, based on the interval importance judgment matrix, a target optimization model is established and the optimal weight value of each purity index data is determined by an improved radial movement algorithm, including: For the interval numbers in the interval importance judgment matrix, the separation degree between each interval number is calculated by the separation degree theory; Specifically, the calculation formula for calculating the separation degree between each interval number through the separation degree theory is: ; In the formula, G ( B ij , K ij ) represents the number of intervals B ij and K ij The separation degree; K ij Indicates i Purity index data and j The pairwise judgment range of purity index data when comparing their importance; ( x ij , y ij ) represents the number of intervals B ij The range of the interval; n Indicates the number of purity indicators.

[0040] The objective function is to minimize the sum of the degrees of separation of the interval importance judgment matrix, and the target optimization model is established with the sum of the weight values ​​of each purity index data being 1 and the value range of the weight value as constraints; The objective function is taken as the fitness function, and the target optimization model is solved by improving the radial movement algorithm to obtain the optimal weight value of each purity index data.

[0041] As a preferred implementation, the objective function is used as a fitness function, and the target optimization model is solved by an improved radial movement algorithm to obtain the optimal weight values ​​of each purity index data, including: Initialize the parameters of the improved radial movement algorithm and randomly generate a population of weighted solutions; It should be noted that the parameters for initializing the improved radial movement algorithm include population size, number of iterations, mutation rate, etc., and a population of weighted solutions is randomly generated. Each weighted solution represents a possible weight combination, where the weight value should satisfy the normalization condition (the sum of the weights is 1).

[0042] Use the objective function as the fitness function and calculate the fitness function value of each weight solution; Specifically, the calculation formula of the fitness function is: ; In the formula, f represents the fitness function; G ( B ij , K ij ) represents the number of intervals B ij and K ij The separation degree; K ij Indicates i Purity index data and j The pairwise judgment range of purity index data when comparing their importance; ( x ij , y ij ) represents the number of intervals B ij The range of the interval; n Indicates the number of purity indicators; w i Indicates i The optimal weight value of each purity index data; w j Indicates j The optimal weight value of each purity index data; When i Purity index data and j When all purity index data are optimally weighted, ( B ij , w i / w j ) indicates a point w i / w j To the interval number B ij The degree of separation.

[0043] Calculate the fitness function value for each weight solution and update the weight solution; Specifically, based on the size of the fitness function value, you can evaluate the pros and cons of each weight solution. A smaller fitness function value usually indicates a better solution. Based on the evaluation results, you can use different strategies to update the weight solution. This usually involves the following steps: Selection: Select some "excellent" weight solutions from the current population, which will be used to generate new weight solutions; the selection strategy can be based on the ranking of fitness function values ​​(such as roulette selection) or other more complex selection methods.

[0044] Crossover (or recombination): Pair the selected weight solutions and exchange their information in some way (such as crossover operation) to generate a new weight solution.

[0045] Mutation: Make small random modifications to the new weight solution (such as changing a weight value) to increase the diversity of the population and explore new search spaces. Mutation operations also help prevent the algorithm from converging to a local optimal solution too early.

[0046] The newly generated weight solutions (possibly including some unmodified "excellent" weight solutions) are added to the population, and some weight solutions with lower fitness may be removed to keep the population size unchanged.

[0047] The fitness evaluation and weight solution update are repeated through the iterative optimization method until the preset number of iterations is reached, and the optimal weight value of each purity index data is output.

[0048] A superiority matrix construction module is used to determine the relative degree of membership of each purity index based on the degree of membership method, and to construct a relative superiority matrix of each purity index; As a preferred implementation, the relative membership of each purity index is determined based on the membership method, and the relative superiority matrix of each purity index is constructed, including: An evaluation scale is set for each purity index, and the membership of each purity index on each evaluation scale is calculated through the membership function; It should be noted that one or more evaluation scales are set for each purity indicator, such as very high, high, medium, low and very low, and these scales will be used in subsequent membership calculations.

[0049] For each evaluation scale, determine its central value (i.e., the most typical purity index value under this scale) and standard deviation. The central value usually corresponds to the midpoint or representative value of the evaluation scale, while the standard deviation is determined according to your requirements for the degree of dispersion of the membership function. For each purity index value and each evaluation scale, use the Gaussian membership function to calculate its membership.

[0050] Compare the membership of each purity index on the same evaluation scale, and determine the membership of each index relative to other indexes to obtain the relative membership; It should be noted that for each evaluation scale, the membership values ​​of each indicator are compared. For example, for the evaluation scale "high", the membership values ​​of all indicators on this scale are collected.

[0051] For each indicator, the ratio of its membership on each evaluation scale to the membership of all other indicators on the same scale is calculated to obtain the relative membership.

[0052] According to the relative membership value of each purity index relative to other indicators, the relative superiority matrix of each purity index is constructed.

[0053] An evaluation value calculation module is used to calculate the evaluation value of each purity index according to the optimal weight value and relative superiority matrix of each purity index; It should be noted that the optimal weight value of each purity index is multiplied by the relative superiority matrix to obtain the evaluation value of each purity index.

[0054] The comprehensive evaluation calculation module is used to comprehensively evaluate the purity of the photoinitiator according to the evaluation values ​​of each purity index to obtain a comprehensive evaluation value.

[0055] It should be noted that the purity of the photoinitiator is comprehensively evaluated based on the evaluation values ​​of each purity index and a comprehensive evaluation value is obtained by calculating the weighted average of these evaluation values.

[0056] A standard comparison unit 4 is used to compare the obtained evaluation result with a preset evaluation standard and determine whether the photoinitiator meets the preparation requirements; Specifically, comparing the obtained evaluation results with the pre-set evaluation criteria and judging whether the photoinitiator meets the preparation requirements includes the following steps: Determine the evaluation criteria based on previous research, industry standards, or specific application requirements; for example, the comprehensive evaluation value of the photoinitiator may need to be 0.75 or above to be considered to meet the preparation requirements; The calculated comprehensive evaluation value of the photoinitiator is compared with the preset standard.

[0057] Based on the comparison results, determine whether the photoinitiator meets the preparation requirements. If the evaluation value is lower than the standard, the production process or formulation may need to be adjusted to meet the requirements.

[0058] If the photoinitiator does not meet the requirements, analyze which purity indicators are insufficient and explore possible improvement measures. This may include changing the proportion of certain chemical components, adjusting processing conditions, etc. After implementing improvements, re-evaluate the purity to ensure that the new results meet the preset standards.

[0059] like Figure 2 According to another embodiment of the present invention, a photoinitiator preparation process is provided, and the photoinitiator preparation process comprises the following steps: S1, subjecting the acyl chloride, aluminum chloride and solvent to a Friedel-Crafts reaction with benzene, and sending the resulting Friedel-Crafts reaction product to a gas-liquid separation tank to separate hydrogen chloride gas and a first reaction liquid; S2, quenching the first reaction solution with hydrochloric acid, and standing for phase separation after quenching, adding the organic phase to a thin film evaporator to separate the solvent, and obtaining a Friedel-Crafts reaction intermediate; S3, mixing the Friedel-Crafts reaction intermediate with chlorine gas to perform a chlorination reaction, and separating the gas and the second reaction liquid from the chlorination reaction product; S4, mixing the sodium hydroxide solution and the phase transfer catalyst evenly, and subjecting the mixed product to a hydrolysis reaction with the second reaction solution, and sequentially passing the hydrolysis reaction product into a buffer tank and a phase separation tank to obtain a crude product organic phase, and purifying the crude product organic phase to obtain a photoinitiator; S5, obtaining a photoinitiator sample, and obtaining chromatographic data of the photoinitiator sample by using a chromatographic analysis method; S6. Extracting purity index data of the photoinitiator by wavelet transform method according to the obtained chromatographic data; S7. Based on the purity index data of the photoinitiator, the purity of the photoinitiator is evaluated and verified based on the target decision evaluation method; S8. Compare the obtained evaluation results with the pre-set evaluation criteria, and determine whether the photoinitiator meets the preparation requirements.

[0060] In summary, with the aid of the above-mentioned technical scheme of the present invention, the present invention forms an automated process by sequentially connecting the sample analysis unit 1, the index acquisition unit 2, the purity evaluation unit 3 and the standard comparison unit 4, which not only improves the efficiency of verification, but also reduces the error of manual operation, and ensures the accuracy of the verification result. The purity of the photoinitiator is evaluated and verified based on the target decision evaluation method. This evaluation method combines professional knowledge and practical experience, and can scientifically and objectively evaluate the purity of the photoinitiator, and compare the evaluation result with the pre-set evaluation standard. This standardized comparison method ensures the objectivity and consistency of the verification result. Through comparison, it can be clarified whether the photoinitiator meets the preparation requirements, and provides a reliable basis for subsequent production and use. The present invention performs baseline correction and noise filtering on the chromatographic data, effectively improves the signal-to-noise ratio of the data, improves the reliability and accuracy of the data, and performs scale analysis on the processed chromatographic data through wavelet transform. The invention adopts the multi-scale analysis method to capture the characteristics of different frequency components in the chromatographic data, thereby realizing more refined feature extraction. The objective function of the invention is to minimize the sum of the degrees of separation of the interval importance judgment matrix, which can ensure that the weight distribution is more reasonable, reduce the deviation caused by subjective judgment, and help improve the accuracy and reliability of purity evaluation. The target optimization model is solved by improving the radial movement algorithm, and the optimal weight value of each purity index data can be efficiently found. The invention combines the randomness and deterministic search strategies, has a faster convergence speed and better global search ability, and determines the relative superiority of each purity index based on the membership method, which can clearly reflect the performance of each purity index on the evaluation scale. By calculating the degrees of separation and membership between interval numbers, the relationship and difference between purity indicators can be deeply understood, which provides rich information for purity evaluation, helps to explain the evaluation results and guide the subsequent optimization work.

[0061] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, optical storage, etc.) containing computer-usable program code.

[0062] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A verification system in the process of preparing a photoinitiator, characterized in that: The verification system in the photoinitiator preparation process comprises: a sample analysis unit, an index acquisition unit, a purity evaluation unit and a standard comparison unit, and the sample analysis unit, the index acquisition unit, the purity evaluation unit and the standard comparison unit are connected in sequence; The sample analysis unit is used to obtain a photoinitiator sample and obtain chromatographic data of the photoinitiator sample by using a chromatographic analysis method; The index acquisition unit is used to extract the purity index data of the photoinitiator by wavelet transform method according to the obtained chromatographic data; The purity evaluation unit is used to evaluate and verify the purity of the photoinitiator based on the purity index data of the photoinitiator and based on the target decision evaluation method; The standard comparison unit is used to compare the obtained evaluation result with the preset evaluation standard and determine whether the photoinitiator meets the preparation requirements; The purity evaluation unit includes: a judgment matrix construction module, an optimal weight determination module, a superiority matrix construction module, an evaluation value calculation module and a comprehensive evaluation calculation module, and the judgment matrix construction module, the optimal weight determination module, the superiority matrix construction module, the evaluation value calculation module and the comprehensive evaluation calculation module are connected in sequence; The judgment matrix construction module is used to compare the purity index data of the photoinitiator in pairs based on the interval analytic hierarchy process, and to construct an interval importance judgment matrix according to the comparison results; The optimal weight determination module is used to establish a weight target optimization model based on the interval importance judgment matrix and determine the optimal weight value of each purity index through an improved radial movement algorithm; The superiority matrix construction module is used to determine the relative membership of each purity index based on the membership method, and to construct the relative superiority matrix of each purity index; The evaluation value calculation module is used to calculate the evaluation value of each purity index according to the optimal weight value of each purity index and the relative superiority matrix; The comprehensive evaluation calculation module is used to comprehensively evaluate the purity of the photoinitiator according to the evaluation values ​​of each purity index to obtain a comprehensive evaluation value.

2. The verification system in the photoinitiator preparation process according to claim 1, characterized in that: The sample analysis unit comprises: a sample injection module, a chromatographic analysis module and a signal acquisition storage module, and the sample injection module, the chromatographic analysis module and the signal acquisition storage module are connected in sequence; The sample injection module is used to dissolve and dilute the sample obtained from the photoinitiator, and inject the dissolved and diluted sample into a pre-set chromatographic instrument; The chromatography analysis module is used to perform chromatography analysis on the dissolved and diluted sample through a chromatography instrument based on thin layer chromatography analysis; The signal acquisition and storage module is used to acquire and store the detection signals of each component of the photoinitiator sample through a mass spectrometer detector.

3. The verification system in the photoinitiator preparation process according to claim 1, characterized in that: The index acquisition unit includes: a preprocessing module, a signal decomposition module and a purity index determination module, and the preprocessing module, the signal decomposition module and the purity index determination module are connected in sequence; The preprocessing module is used to perform baseline correction and noise filtering on the obtained chromatographic data; The signal decomposition module is used to perform scale analysis on the processed chromatographic data through wavelet transform and extract wavelet coefficients at each scale; The purity index determination module is used to perform feature extraction on the peaks at each scale based on the extracted wavelet coefficients to determine the purity index of the photoinitiator.

4. The verification system in the photoinitiator preparation process according to claim 3, characterized in that: Based on the extracted wavelet coefficients, the peaks at each scale are subjected to feature extraction to determine the purity index of the photoinitiator, including: According to the extracted wavelet coefficients, the peaks in the chromatographic data are identified and their starting points, peak apex and end points are located; Determine characteristic parameters of peaks in the chromatographic data according to the recognition results; The purity index of the photoinitiator is determined by using the extracted characteristic parameters combined with prior knowledge.

5. The verification system in the photoinitiator preparation process according to claim 1, characterized in that: The method of establishing a target optimization model based on the interval importance judgment matrix and determining the optimal weight value of each purity index data by using an improved radial movement algorithm includes: For the interval numbers in the interval importance judgment matrix, the separation degree between each interval number is calculated by the separation degree theory; The objective function is to minimize the sum of the degrees of separation of the interval importance judgment matrix, and the target optimization model is established with the sum of the weight values ​​of each purity index data being 1 and the value range of the weight value as constraints; The objective function is taken as the fitness function, and the target optimization model is solved by improving the radial movement algorithm to obtain the optimal weight value of each purity index data.

6. The verification system in the photoinitiator preparation process according to claim 5, characterized in that: The calculation formula for calculating the separation degree between each interval number by the separation degree theory is: ； In the formula, G ( B ij , K ij ) represents the number of intervals B ij and K ij The separation degree; K ij Indicates i Purity index data and j The pairwise judgment range of purity index data when comparing their importance; ( x ij , y ij ) represents the number of intervals B ij The range of the interval; n Indicates the number of purity indicators.

7. The verification system in the photoinitiator preparation process according to claim 5, characterized in that: The objective function is used as the fitness function, and the target optimization model is solved by improving the radial movement algorithm to obtain the optimal weight value of each purity index data, including: Initialize the parameters of the improved radial movement algorithm and randomly generate a population of weighted solutions; Use the objective function as the fitness function and calculate the fitness function value of each weight solution; Calculate the fitness function value for each weight solution and update the weight solution; The fitness evaluation and weight solution update are repeated through the iterative optimization method until the preset number of iterations is reached, and the optimal weight value of each purity index data is output.

8. The verification system in the photoinitiator preparation process according to claim 7, characterized in that: The calculation formula of the fitness function is: ； In the formula, f represents the fitness function; G ( B ij , K ij ) represents the number of intervals B ij and K ij The separation degree; K ij Indicates i Purity index data and j The pairwise judgment range of purity index data when comparing their importance; ( x ij , y ij ) represents the number of intervals B ij The range of the interval; n Indicates the number of purity indicators; w i Indicates i The optimal weight value of each purity index data; w j Indicates j The optimal weight value of the purity index data.

9. A verification system in a photoinitiator preparation process according to claim 8, characterized in that: The method of determining the relative membership of each purity index based on the membership method and constructing the relative superiority matrix of each purity index includes: An evaluation scale is set for each purity index, and the membership of each purity index on each evaluation scale is calculated through the membership function; Compare the membership of each purity index on the same evaluation scale, and determine the membership of each index relative to other indexes to obtain the relative membership; According to the relative membership value of each purity index relative to other indicators, the relative superiority matrix of each purity index is constructed.

10. A process for preparing a photoinitiator, for preparing the photoinitiator according to any one of claims 1 to 9, characterized in that: The photoinitiator preparation process comprises the following steps: S1, subjecting the acyl chloride, aluminum chloride and solvent to a Friedel-Crafts reaction with benzene, and sending the resulting Friedel-Crafts reaction product to a gas-liquid separation tank to separate hydrogen chloride gas and a first reaction liquid; S2, quenching the first reaction solution with hydrochloric acid, and standing for phase separation after quenching, adding the organic phase to a thin film evaporator to separate the solvent, and obtaining a Friedel-Crafts reaction intermediate; S3, mixing the Friedel-Crafts reaction intermediate with chlorine gas to perform a chlorination reaction, and separating the gas and the second reaction liquid from the chlorination reaction product; S4, mixing the sodium hydroxide solution and the phase transfer catalyst evenly, and subjecting the mixed product to a hydrolysis reaction with the second reaction solution, and sequentially passing the hydrolysis reaction product into a buffer tank and a phase separation tank to obtain a crude product organic phase, and purifying the crude product organic phase to obtain a photoinitiator; S5, obtaining a photoinitiator sample, and obtaining chromatographic data of the photoinitiator sample by using a chromatographic analysis method; S6. Extracting purity index data of the photoinitiator by wavelet transform method according to the obtained chromatographic data; S7. Based on the purity index data of the photoinitiator, the purity of the photoinitiator is evaluated and verified based on the target decision evaluation method; S8. Compare the obtained evaluation results with the pre-set evaluation criteria, and determine whether the photoinitiator meets the preparation requirements.

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