Method for determining hydrogenation efficiency of hydrogenation liquid or oxidation efficiency of oxidation liquid in hydrogen peroxide production process

Abstract

The invention relates to the field of spectrum detection, and discloses a method for determining the hydrogenation efficiency of a hydrogenation solution or the oxidation efficiency of an oxidation solution in the hydrogen peroxide production process, and the method comprises the following steps: 1) collecting a near infrared spectrogram of a standard solution; 2) obtaining a spectral intensity variable I1; 3) a random forest algorithm is adopted, I1 is adopted as an input variable, hydrogenation efficiency or oxidation efficiency is adopted as an output variable, and a prediction model M1 is constructed; 4) amplifying the variable I1 to obtain a variable I2; 5) a random forest algorithm is used, I2 is used as an input variable, and a prediction model M2 is constructed; 6) acquiring spectral intensity variables I1 and I2 of a reaction solution to be detected, and substituting the spectral intensity variables I1 and I2 into the prediction models M1 and M2 to obtain hydrogenation efficiency Q1 and Q2 or oxidation efficiency P1 and P2; 7) averaging Q1 and Q2 to obtain hydrogenation efficiency; and the P1 and the P2 are averaged. The method is simultaneously suitable for determining the hydrogenation efficiency of the hydrogenation liquid and the oxidation efficiency of the oxidation liquid, and is rapid, simple, accurate and stable.

Description

Technical Field

[0001] This invention relates to the field of spectroscopic detection, and more specifically, to a method for determining the hydrogenation efficiency of hydrogenation liquid or the oxidation efficiency of oxidation liquid in the production of hydrogen peroxide. Background Technology

[0002] Hydrogen peroxide is mainly produced using the anthraquinone process, which boasts a high degree of automation, low product cost, and low energy consumption, making it suitable for large-scale production. However, since the raw materials, intermediate products, and final products are almost all flammable, explosive, or combustion-supporting substances, and the production process is relatively complex, accurate and timely monitoring and real-time adjustment of the quality indicators in the hydrogen peroxide production process are extremely important.

[0003] Among them, hydrogen efficiency of hydrogenation liquid and oxygen efficiency of oxidation liquid are two important analytical items in the anthraquinone process for hydrogen peroxide production. They directly affect the yield, quality and production safety of hydrogen peroxide. They are analyzed frequently, generally every 4-8 hours.

[0004] The hydrogenation efficiency of hydrogenation solutions and the oxidation efficiency of oxidation solutions are generally determined by manually adding potassium permanganate titrant. This method is cumbersome and time-consuming, making it difficult to provide accurate results quickly. Furthermore, manual analysis requires highly skilled operators, involves strenuous work, operates in poor environments, and uses reagents that can pollute the environment. Therefore, current manual analysis methods are not advantageous for industrial hydrogen peroxide production. In particular, existing rapid analytical methods analyze hydrogenation and oxidation efficiencies separately, using separate methods for each. This further complicates the process, demands more from operators, and is prone to errors, resulting in low accuracy and poor repeatability.

[0005] Therefore, there is a need to develop methods that can accurately, rapidly, simply, and stably determine hydrogenation efficiency and oxidation efficiency. In particular, it is essential to establish a unified, rapid, stable, and industrially applicable analytical method that can simultaneously determine the hydrogenation efficiency of hydrogenation solutions and the oxidation efficiency of oxidation solutions, thereby further improving analytical efficiency. Summary of the Invention

[0006] The purpose of this invention is to overcome the aforementioned problems in the prior art and provide a method for determining the hydrogenation efficiency of hydrogenation liquid or the oxidation efficiency of oxidation liquid in the hydrogen peroxide production process. This method is suitable for determining both the hydrogenation efficiency of hydrogenation liquid and the oxidation efficiency of oxidation liquid, and can obtain results quickly, simply, accurately and stably. Compared with the prior art, the method provided by this invention has significant advantages in operation, accuracy, repeatability and stability, and is especially suitable for long-term industrial online analysis.

[0007] To achieve the above objectives, the present invention provides a method for determining the hydrogenation efficiency of a hydrogenation liquid or the oxidation efficiency of an oxidation liquid during hydrogen peroxide production, the method comprising:

[0008] (1) Obtain multiple standard hydrogenation solutions with known and different hydrogenation efficiencies and multiple standard oxidation solutions with known and different oxidation efficiencies; collect near-infrared spectra of the above standard solutions respectively;

[0009] (2) Select the characteristic spectral bands of the near-infrared spectrum of the above standard solution to obtain the spectral intensity variable I1 corresponding to the characteristic spectral bands;

[0010] (3) Using the random forest algorithm, the I1 obtained in step (2) is used as the input variable, and the corresponding hydrogenation efficiency or oxidation efficiency obtained in step (1) is used as the output variable to construct a prediction model M1 between the input and output variables.

[0011] (4) The spectral intensity variables of the characteristic spectral bands obtained in step (2) are amplified to obtain the amplified variable I2;

[0012] (5) Using the random forest algorithm, the amplified variable I2 is used as the input variable, and the corresponding hydrogenation efficiency or oxidation efficiency obtained in step (1) is used as the output variable to construct the prediction model M2.

[0013] (6) Obtain the reaction solution to be tested, obtain the spectral intensity variable I1 of the corresponding characteristic spectral band in the manner of step (2), and substitute it into the prediction model M1 to obtain the hydrogenation efficiency Q1 or oxidation efficiency P1; obtain the amplified spectral intensity variable I2 in the manner of step (4), and substitute it into the prediction model M2 to obtain the hydrogenation efficiency Q2 or oxidation efficiency P2.

[0014] (7) The hydrogenation efficiency Q1 and hydrogenation efficiency Q2 are averaged to obtain the final hydrogenation efficiency of the reaction solution to be tested; the oxidation efficiency P1 and oxidation efficiency P2 are averaged to obtain the final oxidation efficiency of the reaction solution to be tested.

[0015] The above technical solution provides a predictive model suitable for simultaneously determining the hydrogenation efficiency of hydrogenation liquids and the oxidation efficiency of oxidation liquids. Therefore, when determining hydrogenation or oxidation efficiency, it is unnecessary to process each object separately; simply substitute the corresponding characteristic spectral bands into the predictive model. This method is more convenient, faster, and simpler, and yields accurate and stable results. Compared to existing technologies, the method provided by this invention avoids complex manual processing, is more efficient, greatly improves the analytical operating environment, and exhibits good accuracy, repeatability, and stability. It is applicable to both offline laboratory analysis and online industrial analysis, and is particularly suitable for long-term online industrial analysis. Attached Figure Description

[0016] Figure 1 This is a correlation diagram of the measured values ​​and calculated values ​​obtained in Embodiment 1 of the present invention. Detailed Implementation

[0017] The endpoints and any values ​​of the ranges disclosed herein are not limited to the precise ranges or values, and these ranges or values ​​should be understood to include values ​​close to these ranges or values. For numerical ranges, the endpoint values ​​of the various ranges, the endpoint values ​​of the various ranges and individual point values, and individual point values ​​can be combined with each other to obtain one or more new numerical ranges, which should be considered as specifically disclosed herein.

[0018] This invention provides a method for determining the hydrogenation efficiency of a hydrogenation liquid or the oxidation efficiency of an oxidation liquid during hydrogen peroxide production. The method includes:

[0019] (1) Obtain multiple standard hydrogenation solutions with known and different hydrogenation efficiencies and multiple standard oxidation solutions with known and different oxidation efficiencies; collect near-infrared spectra of the above standard solutions respectively;

[0020] (2) Select the characteristic spectral bands of the near-infrared spectrum of the above standard solution to obtain the spectral intensity variable I1 corresponding to the characteristic spectral bands;

[0021] (3) Using the random forest algorithm, the I1 obtained in step (2) is used as the input variable, and the corresponding hydrogenation efficiency or oxidation efficiency obtained in step (1) is used as the output variable to construct a prediction model M1 between the input and output variables.

[0022] (4) The spectral intensity variables of the characteristic spectral bands obtained in step (2) are amplified to obtain the amplified variable I2;

[0023] (5) Using the random forest algorithm, the amplified variable I2 is used as the input variable, and the corresponding hydrogenation efficiency or oxidation efficiency obtained in step (1) is used as the output variable to construct the prediction model M2.

[0024] (6) Obtain the reaction solution to be tested, obtain the spectral intensity variable I1 of the corresponding characteristic spectral band in the manner of step (2), and substitute it into the prediction model M1 to obtain the hydrogenation efficiency Q1 or oxidation efficiency P1; obtain the amplified spectral intensity variable I2 in the manner of step (4), and substitute it into the prediction model M2 to obtain the hydrogenation efficiency Q2 or oxidation efficiency P2.

[0025] (7) The hydrogenation efficiency Q1 and hydrogenation efficiency Q2 are averaged to obtain the final hydrogenation efficiency of the reaction solution to be tested; the oxidation efficiency P1 and oxidation efficiency P2 are averaged to obtain the final oxidation efficiency of the reaction solution to be tested.

[0026] The anthraquinone process is the main method for producing hydrogen peroxide. The main reaction liquids involved in the hydrogen peroxide production process generally include hydrogenation liquid, oxidation liquid, and raffinate. The main process of the anthraquinone process includes: preparing a working solution by mixing anthraquinone (generally 2-ethylanthraquinone) with an organic solvent (such as a mixed solvent of C9-C10 heavy aromatics, trioctyl phosphate, and tetrabutylurea). Hydrogenation stage: Under pressure of 0.3 MPa or above, temperature of 40-80℃ and catalyst (such as Pd catalyst), anthraquinone in the working solution is hydrogenated and reduced by H2 to obtain anthraquinone or tetrahydroanthraquinone; Oxidation stage: The material after hydrogenation stage is oxidized with O2 under conditions of 30-60℃ and slight compression, so that anthraquinone and tetrahydroanthraquinone are oxidized to generate H2O2 and anthraquinone; Then, the material after oxidation stage is subjected to extraction (raffinate is the solution remaining after extracting H2O2), regeneration, purification and concentration to obtain a 20-50 wt% H2O2 aqueous solution.

[0027] The inventors of this invention discovered in their research that, for the hydrogenation liquid and oxidation liquid in the anthraquinone process for producing hydrogen peroxide, the above-mentioned method, in particular, involves first obtaining more spectral intensity variable information through amplification, then establishing a calibration model using a nonlinear random forest algorithm, and finally obtaining the final prediction result by averaging the results of the two prediction methods. When used to calculate unknown hydrogenation efficiency and oxidation efficiency, this method ensures that it is fast, convenient, and accurate, while also maintaining the repeatability and long-term stability of the analytical model.

[0028] According to the present invention, preferably, in step (1), the hydrogenation efficiency of the standard hydrogenation solution and the oxidation efficiency of the standard oxidation solution are each independently 4-30 g / L.

[0029] More preferably, the hydrogenation efficiency of the standard hydrogenation solution and the oxidation efficiency of the standard oxidizing solution are each independently 6-20 g / L (for example, 6, 7, 8, 9, 12, 14, 16, 18, 20, or any two of the above values ​​within a range of 6, 7, 8, 9, 12, 14, 16, 18, 20, or any two of the above values). The hydrogenation efficiency of the standard hydrogenation solution and the oxidation efficiency of the standard oxidizing solution are each independently within the above-mentioned range.

[0030] Understandably, when collecting samples, it is generally necessary to ensure that the sample conditions are evenly distributed within the possible range to further guarantee the accuracy of the model obtained from the samples. Therefore, the hydrogenation efficiency of the standard hydrogenation solution and the oxidation efficiency of the standard oxidation solution should also be relatively evenly distributed within the above range. For example, the difference between any two adjacent hydrogenation efficiency values ​​(or oxidation efficiency values) should preferably be between 0.01 and 0.5 g / L.

[0031] According to the present invention, preferably, in step (1), the total number of the standard hydrogenation solution and the standard oxidation solution is not less than 100, more preferably not less than 150 (for example, it can be 150, 180, 200, 220, 240, 260 and any two of the above values ​​forming a range or value within the range).

[0032] It is understood that a larger sample size leads to better accuracy, but considering cost and operational feasibility, the total number of standard hydrogenation solutions and standard oxidation solutions is preferably 100-300. The inventors of this invention have discovered in their research that a more accurate model can be obtained within this range. Furthermore, to ensure good calculation results for both hydrogenation efficiency and oxidation efficiency, the number of standard hydrogenation solutions and standard oxidation solutions should be roughly equal, for example, each accounting for half of the total (or approximately half; for example, the difference between the number of each and half of the total should not exceed 5% of the total).

[0033] In this invention, there are no particular limitations on the specific method for obtaining near-infrared spectra, and it can be carried out in accordance with conventional methods in the art. In a preferred embodiment of this invention, in step (1), the conditions for obtaining the near-infrared spectrum include: a temperature of 12-62 °C (for example, it can be 12, 15, 20, 22, 24, 25, 26, 28, 30, 35, 40, 45, 50, 60, 62, or any two of the above values ​​within a range of 12, 15, 20, 22, 24, 25, 26, 28, 30, 35, 40, 45, 50, 60, 62, or ... any two of the above values); and a wavenumber range of 3500-12000 cm⁻¹. -1 The resolution is 2-16 cm (for example, it can be 2, 4, 6, 7, 8, 9, 10, 12, 14, 16, or any two of the above values). -1 .

[0034] According to the present invention, more preferably, in step (1), the conditions for the near-infrared spectrum include: a temperature of 20-30 °C (for example, it can be 20, 22, 24, 26, 28, 30, or any two of the above values ​​within a range of 30 °C); and a wavenumber range of 3500-12000 cm⁻¹. -1 The resolution is 6-10 cm (for example, it can be a range or value within the range formed by any two of the values ​​6, 7, 8, 9, 10, or above). -1 The number of scans can range from 64 to 128.

[0035] In this invention, the near-infrared spectrum of the reaction solution to be tested can be obtained by either an offline near-infrared spectroscopy method in the laboratory or by an online near-infrared spectroscopy method. The instruments used for acquiring the near-infrared spectrum are not particularly limited and can be conventional choices in the field.

[0036] According to the present invention, preferably, in step (2), the characteristic spectral band range is 4000-8000 cm⁻¹. -1 More preferably, the characteristic spectral band is in the range of 4556-7596 cm⁻¹. -1 The inventors of this invention have discovered that by selecting the aforementioned characteristic spectral bands, information related to hydrogenation efficiency and oxidation efficiency can be more fully reflected.

[0037] According to the present invention, preferably, before performing step (3), the method further includes: preprocessing the characteristic spectral bands to reduce redundant information and / or noise in the spectrum. The inventors of the present invention have discovered that by preprocessing the characteristic spectral bands, it is possible to further extract effective spectral data information and eliminate interference information.

[0038] According to the present invention, preferably, the preprocessing method is selected from second-order derivatives and / or first-order derivatives, more preferably second-order derivatives with a window width of 15-25 (e.g., 15, 17, 19, 21, 23, 25, or any two of the above values ​​within a range). The inventors of the present invention have further discovered that, using the above preprocessing method, whether for hydrogenated liquid samples or oxidized liquid samples, can further ensure the acquisition of more effective information on the corresponding hydrogenation efficiency or oxidation efficiency, which is beneficial to further improving the accuracy of the results obtained by the subsequent prediction model.

[0039] According to the present invention, the Random Forest (RF) algorithm is selected in steps (3) and (5). The Random Forest algorithm is a fusion classification algorithm that includes many decision trees and voting strategies. It belongs to the ensemble algorithm and is a natural nonlinear modeling tool that can be used for classification or regression analysis. The inventors of the present invention have found in their research that, compared with other algorithms, such as partial least squares linear modeling algorithms, the Random Forest algorithm has a good tolerance for outliers and noise and is not prone to overfitting. In particular, the obtained model has a high prediction accuracy in determining both the hydrogenation efficiency of hydrogenated liquid and the oxidation efficiency of oxidized liquid. Regarding the Random Forest algorithm itself, it is a common algorithm, and those skilled in the art are aware of its principle. The above algorithm has been open-sourced and applied. For details, please refer to the description in Fang Kuangnan; Wu Jianbin; Zhu Jianping; Xie Bangchang. A Review of Random Forest Method Research [J]. Statistics and Information Forum, 2011, 26(03):32-38. The above model using the Random Forest algorithm can be constructed in the professional computing software MATLAB.

[0040] According to the present invention, in the random forest algorithm, the parameters ntree (generally the number of times the sampling training is performed) and mtry (generally the number of features selected in each sampling training) can also be controlled. ntree can be set to 200-700, preferably 400-600; mtry can be set to 1 / 4-1 / 2 of the number of input variables.

[0041] According to the present invention, in step (4), the amplification refers to transforming I1 and merging it with the original I1 as a new set of variables. The merging method is to append the transformed variables to I1. According to one embodiment of the present invention, the amplification method is as follows: I1 is appended with k·I1 to form the amplified variable I2, where k is 1 / 20-1 / 5 of the prediction result of model M1 (for calibration set samples, this prediction result is the calibration set prediction result predicted by M1; for unknown samples, this prediction result is the prediction result of M1 for them).

[0042] More specifically, amplification can be performed using MATLAB. The amplification method can be described in MATLAB as follows:

[0043] I = (I1.*(PredictY1. / n)');

[0044] I2 = [I1'I]';

[0045] Where n is an integer between 5 and 20 (inclusive), I1 represents the spectral intensity variable corresponding to the characteristic spectral band obtained in step (2), Y1 represents the M1 prediction result of the corresponding modeling sample or unknown sample, I represents the variable of the amplification segment, and I2 represents the total variable after connection.

[0046] In this invention, variable amplification further increases the amount of spectral information obtained and is organically combined with the random forest algorithm. A prediction model M1 is constructed by directly combining the spectral intensity variables before amplification with a nonlinear regression-based random forest algorithm. A prediction model M2 is constructed again by combining the amplified variables with the random forest algorithm. The final result of this invention is the average of the two established prediction models. The inventors of this invention have found that establishing a dual prediction model can further ensure better accuracy in predicting the hydrogenation efficiency or oxidation efficiency in the test reaction solution, while also possessing good stability and repeatability, making it particularly suitable for long-term stable use scenarios, such as online analysis.

[0047] According to the present invention, preferably, in step (6), the reaction solution to be tested is a hydrogenation solution with unknown hydrogenation efficiency or an oxidation solution with unknown oxidation efficiency.

[0048] The present invention will be described in detail below through embodiments.

[0049] In the following examples, the hydrogenation liquid and oxidation liquid are obtained during the anthraquinone process for producing hydrogen peroxide.

[0050] In step (1) of the following embodiments, the hydrogenation efficiency of the standard hydrogenation solution is determined by first oxidizing with oxygen and then adding potassium permanganate, and the oxidation efficiency of the standard oxidation solution is determined by titration with potassium permanganate. The hydrogenation efficiency and oxidation efficiency obtained in this way are their respective measured values.

[0051] The instrument used to collect near-infrared spectra is a Fourier transform near-infrared spectrometer.

[0052] The operations following spectral acquisition are performed in the professional computing software MATLAB.

[0053] Example 1

[0054] (1) 123 hydrogenation solutions and 117 oxidation solutions were obtained, totaling 240 samples, and their corresponding measured values ​​were obtained. The measured values ​​of hydrogenation efficiency ranged from 8.37 to 13.33 g / L, and the measured values ​​of oxidation efficiency ranged from 7.42 to 9.39 g / L. The difference between any two adjacent hydrogenation efficiency (or any two adjacent oxidation efficiency) values ​​was in the range of 0.01 to 0.5 g / L.

[0055] Samples were injected into the sample cell (optical path length 2 mm) for spectral acquisition. The conditions for acquiring near-infrared spectra included: a temperature of 25℃ and a wavenumber range of 3500-10000 cm⁻¹. -1 The resolution is 8cm. -1 , 128 scans.

[0056] (2) For the near-infrared spectra obtained above, the characteristic spectral band range of 4556-7596 cm⁻¹ was selected. -1 Then, the second derivative of each characteristic spectral band is performed with a window width of 25 to obtain the spectral intensity variable I1 corresponding to the characteristic spectral band.

[0057] (3) For the above 240 samples, the random forest algorithm is used. The spectral intensity variable I1 corresponding to the characteristic spectral band is used as the input variable of the random forest algorithm, and the measured value of hydrogenation efficiency or oxidation efficiency corresponding to each sample is used as the output variable. ntree is set to 500, mtry is set to 253 (1 / 3 of the number of input variables), and the prediction model M1 is constructed.

[0058] (4) The spectral intensity variable I1 of the characteristic spectral band obtained in step (2) is amplified by connecting I1 with k·I1 to form the amplified variable I2, where k is 1 / 10 of the prediction result of model M1.

[0059] (5) For the above 240 samples, the random forest algorithm is used. The variable I2 after amplification of each sample is used as the input variable of the random forest algorithm, and the measured value of hydrogenation efficiency or oxidation efficiency corresponding to each sample is used as the output variable. ntree is set to 600, mtry is set to 507 (1 / 3 of the number of input variables), and the prediction model M2 is constructed.

[0060] (6) Take 46 samples to be tested, including 19 hydrogenation liquids and 27 oxidation liquids. Obtain near-infrared spectra using the method in step (1), and obtain the spectral intensity variable I1 of the corresponding characteristic spectral bands using the method in step (2). Substitute it into the prediction model M1 to obtain the hydrogenation efficiency Q1 or oxidation efficiency P1. Obtain the amplified spectral intensity variable I2 using the method in step (4), and substitute it into the prediction model M2 to obtain the hydrogenation efficiency Q2 or oxidation efficiency P2.

[0061] (7) 46 samples to be tested, wherein the hydrogenation efficiency Q1 and hydrogenation efficiency Q2 of the hydrogenation liquid are averaged to obtain the final hydrogenation efficiency of the test reaction liquid; the oxidation efficiency P1 and oxidation efficiency P2 are averaged to obtain the final oxidation efficiency of the test reaction liquid, and the final calculated value of hydrogenation efficiency or oxidation efficiency of 46 samples to be tested is obtained.

[0062] Furthermore, to verify the accuracy of the prediction model, the measured values ​​of hydrogenation efficiency or oxidation efficiency for each of the 46 samples were obtained.

[0063] Table 1 shows the measured and calculated values ​​of the 46 samples, as well as the deviation between them (calculated value minus measured value). Furthermore, the performance of the prediction model M was evaluated using the root mean square error of prediction (RMSEP) and the correlation coefficient (R).

[0064]

[0065] Where n is 46, y i Let be the measured value of the i-th sample to be tested. This is the calculated value for the i-th sample to be tested.

[0066]

[0067] Where n is 46, y i Let be the measured value of the i-th sample to be tested. Let be the calculated value for the i-th sample to be tested. This is the average of the measured values ​​of 46 samples. The calculated R value is 0.928.

[0068] Table 1

[0069]

[0070]

[0071] Furthermore, a correlation plot was created using the measured values ​​(x-axis) and calculated values ​​(y-axis) of the 46 samples in the validation set. (See attached image.) Figure 1 (where R is the correlation coefficient).

[0072] It is evident that the method provided by this invention can quickly, simply, and accurately predict the hydrogenation efficiency of the hydrogenation liquid and the oxidation efficiency of the oxidation liquid in the hydrogen peroxide production process. Furthermore, the prediction results are quite accurate for various concentrations, demonstrating high accuracy.

[0073] Example 2

[0074] Used to evaluate the repeatability of the method provided by the present invention.

[0075] Take one sample each of the hydrogenated liquid or oxidized liquid to be tested, and repeat the near-infrared spectrum measurement four times for each sample according to step (1) in Example 1. Then process the sample as described in Example 1 to obtain the four results (calculated values) of each sample in the four parallel calculations, as shown in Table 2. The relative standard deviation is calculated as follows:

[0076]

[0077] Where S represents the standard deviation of the calculated value, The x represents the average of the calculated values ​​of the sample, i = 1, 2, ..., n, where n represents the number of samples. i This represents the calculated value of the i-th sample.

[0078] Table 2

[0079] Number of analyses Hydrogenation efficiency of hydrogenated liquid (g / L) Oxidation efficiency of the oxidizing solution (g / L) 1 8.82 8.23 2 8.86 8.30 3 8.85 8.27 4 8.86 8.25 average value 8.85 8.26 Relative standard deviation 0.25％ 0.36％

[0080] As shown in Table 2, the relative standard deviations of the four predicted values ​​of hydrogen efficiency for hydrogenation liquid and oxygen efficiency for oxidation liquid are both low according to the method of the present invention. Therefore, the method provided by the present invention not only has good accuracy for the hydrogenation efficiency of the hydrogenation liquid and the oxidation efficiency of the oxidation liquid to be tested, but also has good repeatability, indicating that the method provided by the present invention has high repeatability.

[0081] Example 3

[0082] Used to evaluate the long-term stability of the method provided by this invention.

[0083] Following step (1) in Example 1, near-infrared online analysis systems for hydrogenation and oxidation liquids in a hydrogen peroxide production plant were continuously sampled for 10 minutes (from 1:29 AM to 1:40 AM on a certain day), obtaining near-infrared spectra of 10 hydrogenation liquid samples and 10 oxidation liquid samples. The obtained near-infrared spectra were processed according to the analytical method established in this invention and substituted into the constructed prediction model to obtain the final calculated values ​​of the hydrogenation efficiency of the hydrogenation liquid samples and the oxidation efficiency of the oxidation liquid samples, as shown in Table 3.

[0084] Table 3

[0085]

[0086] As shown in Table 3, when the method of the present invention is used for online analysis of actual industrial samples, the analysis results can accurately reflect the stability and slight fluctuations of the material properties, and no obvious outliers are found. The results are consistent with the actual working conditions, indicating that the method of the present invention has high stability for continuous use.

[0087] Comparative Example 1

[0088] Following the method in Example 1, except that the random forest algorithm was replaced with a partial least squares algorithm to build the model. The results are shown in Table 4.

[0089] Table 4

[0090]

[0091]

[0092] The results of Example 1 and Comparative Example 1 show that the hydrogenation efficiency and oxidation efficiency predicted by the analytical method established in this invention are closer to the measured values, indicating that the prediction model constructed in this invention is more consistent with actual working conditions and has outstanding effects in accuracy and stability.

[0093] Moreover, although not shown, the inventors of this invention have discovered that averaging is more accurate and stable than using prediction model M1 and prediction model M2 alone.

[0094] The preferred embodiments of the present invention have been described in detail above; however, the present invention is not limited thereto. Within the scope of the inventive concept, various simple modifications can be made to the technical solutions of the present invention, including combinations of various technical features in any other suitable manner. These simple modifications and combinations should also be considered as the content disclosed in the present invention and are all within the protection scope of the present invention.

Claims

1. A method for determining the hydrogenation efficiency of a hydrogenation liquid or the oxidation efficiency of an oxidation liquid in a hydrogen peroxide production process, characterized in that, The method includes: (1) Obtain multiple standard hydrogenation solutions with known and different hydrogenation efficiencies and multiple standard oxidation solutions with known and different oxidation efficiencies; collect near-infrared spectra of the above standard solutions respectively; (2) Select the characteristic spectral bands of the near-infrared spectrum of the above standard solution to obtain the spectral intensity variable I1 corresponding to the characteristic spectral bands; (3) Using the random forest algorithm, the I1 obtained in step (2) is used as the input variable, and the corresponding hydrogenation efficiency or oxidation efficiency obtained in step (1) is used as the output variable to construct a prediction model M1 between the input and output variables. (4) Amplify the spectral intensity variable I1 of the characteristic spectral band obtained in step (2) to obtain the amplified variable I2; (5) Using the random forest algorithm, the amplified variable I2 is used as the input variable, and the corresponding hydrogenation efficiency or oxidation efficiency obtained in step (1) is used as the output variable to construct the prediction model M2. (6) Obtain the reaction solution to be tested, obtain the spectral intensity variable I1 of the corresponding characteristic spectral band in the manner of step (2), and substitute it into the prediction model M1 to obtain the hydrogenation efficiency Q1 or oxidation efficiency P1; obtain the amplified spectral intensity variable I2 in the manner of step (4), and substitute it into the prediction model M2 to obtain the hydrogenation efficiency Q2 or oxidation efficiency P2. (7) The hydrogenation efficiency Q1 and hydrogenation efficiency Q2 are averaged to obtain the final hydrogenation efficiency of the reaction solution to be tested; the oxidation efficiency P1 and oxidation efficiency P2 are averaged to obtain the final oxidation efficiency of the reaction solution to be tested.

2. The method according to claim 1, wherein, In step (1), the hydrogenation efficiency of the standard hydrogenation solution and the oxidation efficiency of the standard oxidation solution are each independently 4-30 g / L; Preferably, the hydrogenation efficiency of the standard hydrogenation solution and the oxidation efficiency of the standard oxidation solution are each independently 6-20 g / L.

3. The method according to claim 1, wherein, In step (1), the total number of standard hydrogenation solution and standard oxidation solution is not less than 100, preferably not less than 150.

4. The method according to claim 1, wherein, In step (1), the testing conditions for the near-infrared spectrum include: a temperature of 12-62℃; and a wavenumber range of 3500-12000 cm⁻¹. -1 Resolution is 2-16cm -1 .

5. The method according to claim 1, wherein, In step (1), the testing conditions for the near-infrared spectrum include: a temperature of 20-30℃; and a resolution of 6-10cm. -1 .

6. The method according to claim 1, wherein, In step (2), the characteristic spectral band range is 4000-8000 cm⁻¹. -1 ; Preferably, the characteristic spectral band is in the range of 4556-7596 cm⁻¹. -1 .

7. The method according to claim 1, wherein, Before performing step (3), the method further includes: preprocessing the characteristic spectral bands to reduce redundant information and / or noise in the spectrum.

8. The method according to claim 7, wherein, The preprocessing method is selected from second-order derivatives and / or first-order derivatives, preferably second-order derivatives with a window width of 15-25.

9. The method according to claim 1, wherein, In step (4), the amplification method is to connect I1 with k·I1 to form the amplified variable I2, where k is 1 / 20-1 / 5 of the prediction result of model M1.

10. The method according to claim 1, wherein, In step (6), the reaction solution to be tested is a hydrogenation solution with unknown hydrogenation efficiency or an oxidation solution with unknown oxidation efficiency.

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