An ultrafast and non-destructive detection method for solid cis-trans-butenedioic acid

Abstract

The application discloses a kind of ultrafast and nondestructive detection methods for solid cis-trans-butenedioic acid, it is related to the technical field of testing or analyzing materials by determining the chemical or physical properties of materials, suitable for chemical raw material quality control and organic synthesis process monitoring;Including: taking the mixed powder of cis-isomer and trans-isomer of butenedioic acid;The mixed powder is sequentially ultrasonically mixed, tabletting is formed, and the characteristic peak area ratio of cis-isomer and trans-isomer of butenedioic acid is obtained using Raman spectrum;Establish a prediction model;Based on the prediction model, the mass ratio of cis-isomer and trans-isomer of butenedioic acid in the pretreated powder is predicted.The application realizes the accurate determination of cis-trans-isomer mixture mass fraction by screening control particle size and ultrasonic dry mixing to construct high uniformity sample, while combining the precise control of tabletting process parameters pressure.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of testing or analyzing materials by determining the chemical or physical properties of the materials, in particular to a method for rapid and non-destructive detection of cis-trans butenedioic acid. BACKGROUND

[0002] Cis-butenedioic acid and trans-butenedioic acid, as important dicarboxylic acid isomers, have wide applications in food additives, pharmaceutical synthesis and polymer material industry. The chemical properties and biological activities of the two are significantly different: trans-butenedioic acid is a commonly used food acidity regulator, but cis-butenedioic acid is strictly limited due to potential toxicity. Therefore, rapid and accurate determination of the proportion of the two in the mixture is crucial to ensure product quality, compliance and process optimization.

[0003] Currently, the proportion analysis of cis / trans-butenedioic acid mainly relies on chromatography and mass spectrometry techniques. Chromatography analysis has high precision and mature methods, but the sample components need to be separated before detection, and the sample pretreatment is complex, which is difficult to meet the needs of real-time and in-situ detection; mass spectrometry technique has high sensitivity, but due to the same molecular weight and highly similar fragment ion spectrum of isomers, it must rely on chromatographic pre-separation, and the instrument cost is high. In addition, the ultraviolet spectroscopy method is simple to operate and fast to detect, but due to the serious overlap of the two ultraviolet absorption peaks, it is difficult to decouple the spectrum, and quantitative analysis is difficult. In addition, cis-butenedioic acid and trans-butenedioic acid are both solid powders at room temperature and normal pressure, and their crystal morphology and physical properties (such as density and flowability) are different, which leads to uneven mixing in solid mixtures. This unevenness can significantly affect the representativeness of the detection results of Raman spectroscopy based on point sampling, making it difficult to reflect the true composition ratio of the whole sample.

[0004] Raman spectroscopy technology provides a new path to solve the above problems by virtue of its molecular vibration fingerprint recognition ability. This technology captures the characteristic signals of chemical bond vibration energy level transitions by detecting inelastic scattering light, and has the advantages of non-destructive detection, no need for sample pretreatment, fast detection speed and compatibility with in-situ detection. However, when Raman spectroscopy technology is used to process the above-mentioned solid mixtures, the Raman spectroscopy intensity is easily affected by the surface morphology of the solid, which includes the size and compaction morphology of the solid powder. To eliminate the influence, some existing technologies use Raman spectroscopy intensity and a single multiplier effect parameter to package all physical disturbances (particle size, density, etc.), without explicitly identifying the independent influence mechanism of physical factors, resulting in large estimation errors. Moreover, these technologies directly use original full-spectrum data for modeling, which makes them susceptible to overlapping peak interference and difficult to optimize for isomer-specific characteristic peaks. Due to these shortcomings, existing Raman spectroscopy technologies cannot accurately identify powder solids, making it difficult to distinguish cis / trans-butenedioic acid. SUMMARY

[0005] In order to solve the above problems, the application provides a kind of ultrafast and nondestructive detection method for solid cis-trans fumaric acid.

[0006] An ultrafast and nondestructive detection method for solid cis-trans fumaric acid, comprising the following steps:

[0007] Take the mixed powder of cis-isomer and trans-isomer of fumaric acid, and the particle size range of the mixed powder is 75-150 μm;

[0008] The mixed powder is sequentially subjected to ultrasonic mixing and tabletting to obtain a pretreated powder, and the characteristic peak area ratio of cis-isomer and trans-isomer of fumaric acid in the pretreated powder is obtained based on Raman spectroscopy;

[0009] Based on the prediction model, the mass ratio of cis-isomer and trans-isomer of fumaric acid in the pretreated powder is measured; wherein the input of the prediction model is the characteristic peak area ratio of cis-isomer and trans-isomer of fumaric acid, and the output is the mass ratio of cis-isomer and trans-isomer of fumaric acid.

[0010] Description: The above method can eliminate the interference of inconsistent sample surface morphology by setting the particle size range of the mixed powder and performing pretreatment such as ultrasonic mixing and tabletting, and can ensure the stability of spectral acquisition and improve the accuracy of subsequent determination; at the same time, the method correlates the characteristic peak area ratio with the mass ratio to realize rapid and accurate determination from micro-spectral data to macro-quality ratio, greatly improves the analysis efficiency and accuracy, and provides an efficient and reliable method for in-depth study of fumaric acid isomers.

[0011] Further, the mixed powder is obtained by mechanical vibration screening.

[0012] Description: The above mechanical vibration screening can accurately control the particle size range of the powder, so that the mixed powder has high uniformity and consistency, which is beneficial to the stable performance of subsequent steps such as ultrasonic mixing and tabletting, and improves the accuracy and repeatability of Raman spectroscopy detection.

[0013] Further, the method of ultrasonic mixing of the mixed powder is: placing the mixed powder in a sealed inert container, using an ultrasonic oscillation device for dry mixing, the ultrasonic oscillation frequency is 20-40 kHz, the time is 5-15 min, and the ultrasonic mixing is completed.

[0014] Description: By setting the ultrasonic oscillation frequency and time, the powder can be fully dispersed and uniformly mixed under the action of ultrasonic waves, avoiding local concentration unevenness and preventing the change of powder properties due to excessive processing, thereby providing high-quality and consistent pretreated powder for subsequent tabletting, Raman spectrum detection and other links, and helping to improve the accuracy and reliability of the entire experimental process.

[0015] Further, the tabletting method comprises transferring the mixed powder after ultrasonic mixing to a pressure device for tabletting under pressure P, the tabletting thickness is 1 mm, the tabletting area in the pressure device is fixed and unchanged, and the mass of the mixed powder added into the pressure device each time is the same.

[0016] Description: The above means ensure the consistency and repeatability of tabletting operation, making the physical properties such as density of different batches of tablet samples tend to be consistent, and improving the stability and accuracy of the experiment.

[0017] Further, the method for obtaining the characteristic peak area ratio of the cis-isomer and the trans-isomer of butenedioic acid in the pretreated powder based on the Raman spectrum technology comprises:

[0018] respectively obtaining the standard Raman spectrum of the cis-isomer of butenedioic acid and the standard Raman spectrum of the trans-isomer;

[0019] obtaining the Raman spectrum characteristic peak of the cis-isomer of butenedioic acid and the Raman spectrum characteristic peak of the trans-isomer according to the standard Raman spectrum of the cis-isomer of butenedioic acid and the standard Raman spectrum of the trans-isomer;

[0020] Based on the Raman spectrum characteristic peak of the cis-isomer of butenedioic acid and the Raman spectrum characteristic peak of the trans-isomer, a Gaussian fitting method is used to obtain the characteristic peak area ratio of the cis-isomer and the trans-isomer of butenedioic acid.

[0021] Description: According to the standard spectrum, the characteristic peak can be determined to effectively identify the key information reflecting the characteristics of the isomer, avoiding irrelevant signal interference. The Gaussian fitting method is used to calculate the characteristic peak area ratio, which is mature and can accurately quantify the characteristic peak parameters, greatly improving the accuracy and stability of the ratio acquisition, and providing solid data support for accurately predicting the mass ratio of the cis-isomer and the trans-isomer of butenedioic acid in the pretreated powder.

[0022] Further, the prediction model uses a linear regression model, and the expression of the linear regression model is:

[0023] y = a·x+ b·P + c (1);

[0024] In the formula, a, b, c are fitting coefficients, P is the pressure in tabletting, x is the mass ratio of the cis-isomer and the trans-isomer of butene diacid, and y is the characteristic peak area ratio of the cis-isomer and the trans-isomer of butene diacid.

[0025] Description: The linear regression model can clearly present the linear relationship between variables, use the tabletting pressure and the cis-trans isomer mass ratio as independent variables, and establish a connection with the characteristic peak area ratio, comprehensively consider the key factors affecting the results in the experiment, and make the model more scientific and comprehensive. Through the determination of the fitting coefficients a, b, and c, the quantitative relationship between variables can be accurately fitted based on known data, and then the cis-trans isomer mass ratio of butene diacid in the pretreated powder can be accurately detected.

[0026] Further, the training method of the prediction model comprises:

[0027] Obtaining the characteristic peak area ratio of the cis-isomer and the trans-isomer of butene diacid under multiple mixing ratios and multiple tabletting pressures, to obtain a pressure and characteristic peak area ratio data set;

[0028] Taking the pressure and characteristic peak area ratio data set as input and multiple mixing ratios as output, model simulation training and verification are performed to obtain the trained prediction model.

[0029] Description: The above method forms a comprehensive pressure and characteristic peak area ratio data set by obtaining the characteristic peak area ratio under multiple mixing ratios and tabletting pressures. This data set covers multiple experimental variable combinations and can fully reflect the characteristic changes of butene diacid cis-trans isomers under different conditions, providing an adequate and representative data basis for model training.

[0030] Further, the prediction model adopts a support vector regression model or a random forest model.

[0031] Description: Support vector regression performs well in handling high-dimensional data and nonlinear relationships, and can better capture complex potential patterns in data. The random forest model constructs multiple decision trees and integrates them, has strong anti-overfitting ability, is not sensitive to outliers in data, and can evaluate the importance of each feature.

[0032] Further, the pressure range in tabletting is 10-100 MPa.

[0033] Description: By limiting the pressure range in tabletting, the poor tabletting effect caused by improper pressure setting can be avoided. If the pressure is too small, the powder tabletting may not be tight and the structure may be loose, affecting the accuracy of subsequent Raman spectrum detection. If the pressure is too large, the powder particle structure may be damaged.

[0034] The beneficial effects of the present application are:

[0035] The present application can eliminate the unevenness interference of the sample surface morphology by controlling the particle size range of the mixed powder and carrying out pretreatment such as ultrasonic mixing and tabletting, and can ensure the stability of spectrum acquisition, and further improve the accuracy of subsequent determination results; the method realizes rapid and accurate determination from micro-spectral data to macro-quality ratio by correlating the characteristic peak area ratio with the mass ratio, greatly improves the analysis efficiency and accuracy, and provides an efficient and reliable method for in-depth study of butene diacid isomers; specifically, the present application has the advantages of high selectivity structure identification, non-destructive and rapid in-situ detection, multi-component synchronous detection, high sensitivity quantitative analysis, and improvement of solid powder quantitative accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 is a schematic diagram of the molecular structure of butene diacid cis-trans isomers;

[0037] Figure 2 is a standard Raman spectrum of cis / trans butene diacid in the embodiment of the present application;

[0038] Figure 3 is a standard curve diagram of the ground mixed sample of cis / trans butene diacid in the embodiment of the present application;

[0039] Figure 4 is a Raman spectrum diagram of different point positions when the grinding mass ratio of cis / trans butene diacid is 2:8 in the embodiment of the present application;

[0040] Figure 5 is a Raman spectrum diagram between cis butene diacid and trans butene diacid after process optimization in the embodiment of the present application;

[0041] Figure 6 is a standard curve diagram between cis butene diacid and trans butene diacid after process optimization in the embodiment of the present application;

[0042] Figure 7 is a sample Raman spectrum data diagram of an isomer mixture with unknown mass fraction in the embodiment of the present application;

[0043] Figure 8 is a Raman spectrum diagram of a cis / trans butene diacid mixture with a mass ratio of 5:5 after tabletting under different pressures in the embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to further illustrate the manner of implementing the present application and the effects achieved, the technical solutions of the present application will be described in detail below with reference to experiments.

[0045] In view of the uniformity challenge faced by the solid mixture mentioned in the background art, the present application is based on Raman spectroscopy technology, and by designing reasonable particle size screening, ultrasonic dry mixing and pressure control strategies, combined with characteristic peak extraction and Gaussian function fitting analysis algorithm, the influence of local non-uniformity can be effectively overcome, and reliable identification of cis-trans isomers of butenedioic acid and accurate quantitative analysis of the mass fraction of its mixture can be realized. This method breaks through the time efficiency and complexity bottleneck of traditional detection, and provides an efficient solution for food quality inspection, pharmaceutical raw material monitoring and chemical reaction process. The specific scheme is as follows:

[0046] Embodiment 1: A kind of solid cis-trans butenedioic acid for ultrafast and non-destructive detection method, comprising the following steps:

[0047] S1, take the mixed powder of cis-isomer and trans-isomer of butenedioic acid, the particle size range of mixed powder is 75~150 μm;

[0048] The above mixed powder is obtained by mechanical vibration screening; specifically including: butenedioic acid cis-isomer and trans-isomer powder are respectively ground, and then particle size screening is carried out using double sieve; The double sieve includes upper and lower standard metal sieve, the upper sieve aperture is 150 μm, and the lower sieve aperture is 75 μm; The target powder with particle size range of 75~150 μm is collected in the upper layer of the lower sieve; The molecular structural formula of cis-trans butenedioic acid is as shown in Figure 1 ;

[0049] S2, sequentially ultrasonic mixing, tabletting of the above mixed powder, to obtain pretreated powder, and based on Raman spectroscopy technology, the characteristic peak area ratio of cis-isomer and trans-isomer of butenedioic acid in the pretreated powder is obtained;

[0050] The method for ultrasonic mixing of mixed powder is: placing the mixed powder in a sealed inert container, using ultrasonic oscillation equipment for dry mixing, the ultrasonic oscillation frequency is 20~40 kHz, the time is 5~15 min, and the ultrasonic mixing is completed; To realize the uniform dispersion of powder in microscale;

[0051] The method for tabletting of the above includes: transferring the mixed powder after ultrasonic mixing to a pressure equipment for tabletting under pressure P, the tablet thickness is 1 mm, and the tablet area in the pressure equipment is fixed, which is 1 / 2 inch mold, and the mass of mixed powder added into the pressure equipment each time is the same, which is 0.1 g, and the pressure range in the above tabletting is 10~100 MPa;

[0052] The method for obtaining the characteristic peak area ratio of cis-isomer and trans-isomer of butenedioic acid in the pretreated powder based on Raman spectroscopy technology includes:

[0053] S2-1, respectively, obtain the standard Raman spectrum of the cis isomer of butene diacid and the standard Raman spectrum of the trans isomer; specifically comprising: placing a single-component pure sample piece on the sample table of the Raman spectrometer, using a laser with a wavelength of 532 nm for excitation, a laser power of 10 mW, and collecting a wave number range of 150~2000cm -1 , using a 1200 lines / mm grating, an integration time of 30 s, scanning 3 times, and obtaining a standard Raman spectrum as shown in Figure 2 ;

[0054] S2-2, according to the standard Raman spectrum of the cis isomer of butene diacid and the standard Raman spectrum of the trans isomer, obtain the standard Raman spectrum characteristic peak of the cis isomer of butene diacid and the Raman spectrum characteristic peak of the trans isomer;

[0055] Specifically, the characteristic peaks obtained include 863 cm -1 (cis-butene diacid) and 693 cm -1 (trans-butene diacid), and the ratio of the peak area of 863 cm -1 to the total peak area of 693 cm -1 is calculated as a quantitative analysis variable;

[0056] S2-3, based on the Raman spectrum characteristic peak of the cis isomer of butene diacid and the Raman spectrum characteristic peak of the trans isomer, a Gaussian fitting method is used to obtain the characteristic peak area ratio of the cis isomer and the trans isomer of butene diacid;

[0057] S3, based on the prediction model, the mass ratio of the cis isomer and the trans isomer of butene diacid in the pretreated powder is measured; wherein the input of the prediction model is the characteristic peak area ratio of the cis isomer and the trans isomer of butene diacid, and the output is the mass ratio of the cis isomer and the trans isomer of butene diacid;

[0058] The above prediction model uses a linear regression model, and the method for training the prediction model comprises:

[0059] S3-1, obtain the characteristic peak area ratio of the cis isomer and the trans isomer of butene diacid under a plurality of mixing ratios and a plurality of tabletting forming pressures, to obtain a pressure and characteristic peak area ratio data set;

[0060] Specifically, 10-90% cis / trans isomer mixture samples are obtained: a plurality of mixed proportions, i.e., mass fractions of 10-90% cis / trans isomer mixture samples, are collected to obtain Raman spectra according to the above steps, and the characteristic peak area ratio is extracted by Gaussian fitting; for example, the specific implementation process of a plurality of mass ratios is as follows: the mass ratio of cis-butenedioic acid to trans-butenedioic acid in the mixed powder is 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%, and the Raman spectrum of each mass ratio sample is obtained by determining according to step (1) in the above content, as shown in FIGS. Figure 2 、 Figure 5 The extracted characteristic peaks 863 cm -1 (cis-butenedioic acid) and 693 cm -1 (trans-butenedioic acid) are Gaussian fitted to calculate the peak area, and the results are shown in Table 1.

[0061] Table 1: Peak area calculation results under a plurality of mass ratios

[0062]

[0063] S3-2, a plurality of batches of samples are generated by pressing tablets under different pressures (5 MPa, 10 MPa, 15 MPa, and 50 MPa) for each sample ratio; for each sample: record the pressure P of tablet forming; and extract the cis / trans characteristic peak area ratio y from the Raman spectrum;

[0064] S3-3, the pressure and characteristic peak area ratio data set is used as input, and a plurality of mixed proportions are used as output to perform model simulation training and verification, and a trained prediction model is obtained.

[0065] Model training and verification: input variables: peak area ratio y, pressure P; output variable: cis / trans isomer mass ratio x.

[0066] A multiple linear regression algorithm is used to solve the fitting coefficients a, b, and c by minimizing the prediction error; then the model equation is output; and the model is verified and optimized, and the determination coefficient R 2 is used to evaluate the prediction accuracy, and R 2 closer to 1 represents higher prediction accuracy.

[0067] Preferably, in some other embodiments or cis / trans isomers of other substances, before forming a linear regression model, it is judged whether P affects linearity, if it does, the expression in formula (1) is used, if not, the P 2 term is introduced for model calculation, and the method is the same as the method of the present scheme, which is not described here.

[0068] The expression of the above linear regression model is:

[0069] y = a·x+ b·P+c (1);

[0070] Wherein, a, b, c are fitting coefficients, P is the pressure during tableting, x is the mass ratio of the cis isomer to the trans isomer of butenedioic acid, and y is the characteristic peak area ratio of the cis isomer to the trans isomer of butenedioic acid; the Raman spectrum is shown in FIG. Figure 5 As shown;

[0071] Specifically, based on Figure 7 The Raman spectrum data of the sample of the isomer mixture with unknown mass fraction is used for prediction. The pressure and characteristic peak area ratio in the sample Raman spectrum data are used as input. The mass ratio of the cis-isomer to the trans-isomer of butenedioic acid in the pretreated powder can be obtained by solving the prediction model.

[0072] For example, in this scheme, after simulation, it is found that the accuracy is better when the pressure P=50 MPa, so this value can be used to carry out this experiment, such as Figure 6 As shown, the standard curve is simplified to: y = k·x + c′, where c′ =b·50 + c is a constant term, which is suitable for rapid detection scenarios; at the same time, a complete function form can be established through multi-pressure experiments to achieve more accurate quantitative analysis; in addition, as Figure 8 As shown, it can be proved that the performance of Raman spectra under various pressure compression is different. Therefore, it is necessary to introduce pressure variables for simulation in the method of the present invention.

[0073] Example 2: The prediction model adopts support vector regression or random forest model, and the model training method is the same as the model training method in the prior art.

[0074] Comparative Example 1: The difference from Example 1 is that the mixed powder was not ground and screened, and the particle size range of the mixed powder was not controlled, resulting in a large fluctuation range;

[0075] Comparative Example 2: The difference from Example 1 is that the mixed powder is not tableted or the tableting pressure is different;

[0076] Comparative Example 3: The difference from Example 1 is that the tableting pressure parameter P is not introduced, and only the characteristic peak area ratio is used to construct a univariate linear standard curve for mass fraction prediction;

[0077] like Figure 4 As shown in Table 2, in Comparative Example 2, the peak areas and ratios of the samples of the same mass fraction obtained after tableting at different pressures are unstable.Figure 3 As shown, the pressure parameter is not introduced, and the standard curve fitting condition established by the sample without screening treatment is poor, and the fitting degree R 2 Generally lower than 0.90; while after adopting the particle size control and dry mixing process of embodiment 1 and embodiment 2 of the present application, the standard curve R 2 Can be stably improved to more than 0.98, significantly improving the quantitative accuracy and model reliability, in addition, through the increase of the pressure parameter in the linear regression model, the adaptability of the model to the change of the physical state of the sample can be significantly improved, the influence of the spectral response fluctuation caused by the different tabletting pressures on the prediction result is reduced, thereby improving the accuracy, stability and reproducibility of quantitative analysis.

[0078] Table 2 Test results under different pressures

[0079]

[0080] In summary, the present application can perform high selectivity structure identification, in isomer analysis difficult to distinguish by mass spectrum, the high selectivity of Raman spectrum based on molecular vibration information can provide unique structure fingerprint peak, realize accurate molecular identification; It can also be non-destructive, rapid in-situ detection, compared with the traditional detection method, Raman spectrum technology can directly analyze the sample, without complex pretreatment steps, thereby realizing ultra-fast, non-destructive in-situ detection; A single wavelength laser can excite the Raman spectral characteristic peaks of different components, thereby realizing real-time co-detection of multiple components; In the quantitative analysis of mixtures, Raman spectrum shows high sensitivity, the characteristic peak intensity and mass fraction show good linear relationship (R 2 >0.98), ensuring the accuracy and reliability of quantitative analysis; it can also improve the quantitative accuracy of solid powder, the standardized sample preparation process ensures the consistency of particle size and the uniformity of tabletting, improves the peak stability, the experimental results show that R 2 from <0.9 to >0.98.

Claims

1. A method for ultrafast and non-destructive detection of solid cis-trans butenedioic acid, characterized in that, The method comprises the following steps: The mixed powder of cis-isomer and trans-isomer of butene diacid is taken, and the particle size of the mixed powder is 75-150 μm; The mixed powder is sequentially subjected to ultrasonic mixing and tablet compression to obtain a pretreated powder, and a ratio of a peak area of the cis-isomer of butene diacid to a total peak area of the cis-isomer of butene diacid and the trans-isomer of butene diacid in the pretreated powder is obtained based on a Raman spectrum technology; A mass ratio of the cis-isomer and the trans-isomer of butene diacid in the pretreated powder is measured based on a prediction model, wherein an input of the prediction model is the ratio of the peak area of the cis-isomer of butene diacid to the total peak area of the cis-isomer of butene diacid and the trans-isomer of butene diacid, and an output of the prediction model is the mass ratio of the cis-isomer and the trans-isomer of butene diacid.

2. A method for the ultrafast and non-destructive detection of solid cis- trans-butenedioic acid according to claim 1, characterized in that, The mixed powder is screened by a mechanical vibration screening method.

3. A method for the ultrafast and non-destructive detection of solid cis- trans-butenedioic acid according to claim 1, characterized in that, The method for ultrasonic mixing of the mixed powder comprises the following steps: the mixed powder is placed in a sealed inert container, and dry mixing is performed by using an ultrasonic oscillation device, the ultrasonic oscillation frequency is 20-40 kHz, and the ultrasonic mixing time is 5-15 min.

4. A method for the ultrafast and non-destructive detection of solid cis- trans-butenedioic acid according to claim 1, characterized in that, The method for tablet compression comprises the following steps: the mixed powder after ultrasonic mixing is transferred to a pressure device for tablet compression, the tablet thickness is 1 mm, the tablet area in the pressure device is fixed, and the mass of the mixed powder added into the pressure device each time is the same.

5. A method for the ultrafast and non-destructive detection of solid cis- trans-butenedioic acid according to claim 1, characterized in that, The method for obtaining the ratio of the peak area of the cis-isomer of butene diacid to the total peak area of the cis-isomer of butene diacid and the trans-isomer of butene diacid in the pretreated powder based on the Raman spectrum technology comprises the following steps: Standard Raman spectra of the cis-isomer and the trans-isomer of butene diacid are obtained respectively; Raman spectrum characteristic peaks of the cis-isomer and the trans-isomer of butene diacid are obtained according to the standard Raman spectra of the cis-isomer and the trans-isomer of butene diacid; The ratio of the peak area of the cis-isomer of butene diacid to the total peak area of the cis-isomer of butene diacid and the trans-isomer of butene diacid is obtained by using a Gaussian fitting method based on the Raman spectrum characteristic peaks of the cis-isomer and the trans-isomer of butene diacid.

6. A method for the ultrafast and non-destructive detection of solid cis- trans-butenedioic acid according to claim 1, characterized in that, The prediction model adopts a linear regression model, and an expression of the linear regression model is y = a·x + b·P + c (1); In the formula, a, b and c are fitting coefficients, P is the pressure in tablet compression, x is the mass ratio of the cis-isomer and the trans-isomer of butene diacid, and y is the ratio of the peak area of the cis-isomer of butene diacid to the total peak area of the cis-isomer of butene diacid and the trans-isomer of butene diacid.

7. A method for the ultrafast and non-destructive detection of solid cis- trans-butenedioic acid according to claim 1 or 6, characterized in that, The training method of the prediction model comprises the following steps: The ratio of the peak area of the cis-isomer of butene diacid to the total peak area of the cis-isomer of butene diacid and the trans-isomer of butene diacid under multiple tablet compression pressures and multiple mixing ratios is obtained to obtain a pressure and characteristic peak area ratio data set; The pressure and characteristic peak area ratio data set is taken as an input, and the multiple mixing ratios are taken as an output to perform model simulation training and verification, and a trained prediction model is obtained.

8. A method for ultrafast and non-destructive detection of solid cis-trans butenedioic acid as claimed in claim 1, wherein, The prediction model adopts a support vector regression model or a random forest model.

9. A method for the ultrafast and non-destructive detection of solid cis- trans-butenedioic acid according to claim 1, characterized in that, The pressure range in the tablet compression is 10-100 MPa.

Images