Accurate control method and system for dissolution of eucalyptus wood components pretreated by sodium hydroxide

Abstract

The invention belongs to the technical field of pulping and papermaking control, and provides a method and a system for accurately controlling dissolution of components of eucalyptus wood pretreated by sodium hydroxide, and the method comprises the following steps: performing sodium hydroxide reaction on the eucalyptus wood under different pretreatment conditions; after the reaction is finished, obtaining and filtering a pretreatment solution, constructing a relation model between independent variables and response values by taking the lignin component in the pretreatment solution as the response values and taking the reaction temperature, the heating time and the sodium hydroxide addition amount as the independent variables, and performing fitting to obtain a prediction model; and determining the optimal reaction temperature, heating time and sodium hydroxide addition amount by using the prediction model according to the dissolution requirement of the target eucalyptus wood component, and performing accurate control according to the determined result. According to the method, by constructing the prediction model, the dissolution condition of the lignin in the eucalyptus wood pretreated by the sodium hydroxide under different conditions is accurately controlled, and the utilization efficiency is improved.

Description

Technical Field

[0001] This invention belongs to the field of pulp and paper control technology, specifically relating to a method and system for precise control of the leaching of eucalyptus components in sodium hydroxide pretreatment. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Lignocellulose biomass can be divided into four categories: hardwood, softwood, agricultural and forestry waste, and grass. It is mainly composed of cellulose, hemicellulose, lignin, ash, and extractives. Hemicellulose and lignin together form a natural anti-degradation barrier for biomass, providing rigidity to plant cell walls while resisting external corrosion. However, they also hinder the conversion of biomass resources into fuel and other economically valuable biochemical products. Alkaline pretreatment can remove a large amount of lignin and some hemicellulose, causing less sugar degradation compared to acid hydrolysis. Alkaline hydrothermal pretreatment is the most common in practical production applications. It uses alkaline reagents such as NaOH, KOH, Ca(OH)2, and Na2CO3 to break the chemical bonds in the three major components of biomass. Sodium hydroxide pretreatment, due to its mild reaction conditions and high lignin removal rate, has been widely used in biochemical conversion (producing fuel ethanol, biohydrogen, and biomethane, etc.). Alkaline peroxide is a relatively green chemical reagent. Alkaline hydrogen peroxide pretreatment has shown good delignification effects in several biomass substrates. Hydrogen peroxide is commonly used in pulping and bleaching processes. Under alkaline conditions with a pH close to 11.5, H2O2 dissociates to produce hydroperoxide anions (HOO-). These anions continue to react with H2O2 to generate highly reactive hydroxyl radicals (HO·) and superoxide anion radicals (O2·). - These agents selectively oxidize lignin into low molecular weight compounds through several reaction pathways. Current research on alkaline hydrothermal pretreatment of lignocellulosic biomass lacks a systematic and complete explanation of the changes in the components, extracts, and microstructure of eucalyptus, a commonly used raw material. Furthermore, for commonly used reaction parameters in practical production applications, such as alkali dosage, reaction temperature, and heating time, there is a lack of simple and easily implemented technical solutions to achieve efficient and precise separation of lignocellulosic fibers. Summary of the Invention

[0004] To address the aforementioned problems, this invention proposes a method and system for precise control of leaching of eucalyptus components pretreated with sodium hydroxide. By constructing a predictive model, this invention achieves precise control over the leaching of lignin from eucalyptus pretreated with sodium hydroxide under different conditions, thereby improving utilization efficiency.

[0005] According to some embodiments, the present invention adopts the following technical solution: A method for precise control of leaching of eucalyptus components after sodium hydroxide pretreatment includes the following steps: Eucalyptus wood was subjected to sodium hydroxide reaction under different pretreatment conditions; After the reaction, the pretreated solution was obtained and filtered. The lignin component in the pretreated solution was used as the response value, and the reaction temperature, heating time and sodium hydroxide addition amount were used as independent variables. A relationship model between the independent variables and the response value was constructed and fitted to obtain a prediction model. Based on the leaching requirements of the target eucalyptus components, the optimal reaction temperature, heating time, and sodium hydroxide addition amount are determined using a predictive model, and then precisely controlled according to the determined results.

[0006] As an alternative implementation, before the eucalyptus wood undergoes a sodium hydroxide reaction under different pretreatment conditions, it is pre-selected to remove impurities and rotten or discolored wood chips, and then cut into predetermined sizes. As an alternative implementation method, the sodium hydroxide reaction is carried out in a reaction vessel.

[0007] As an alternative implementation, the process of carrying out the sodium hydroxide reaction under different pretreatment conditions is as follows: under different pretreatment conditions, at least one of the reaction temperature, heating time and sodium hydroxide addition amount is different from the other pretreatment conditions, and the reaction temperature, heating time and sodium hydroxide addition amount are all adjusted within a predetermined range.

[0008] As a further defined implementation, under different pretreatment conditions, the reaction temperature was adjusted between 105℃ and 175℃, the heating time was adjusted between 30 min and 150 min, and the amount of sodium hydroxide added was adjusted between 0% and 8%.

[0009] As an alternative implementation method, the Levenberg-Marquardt method is used to construct a relationship model between the independent variables and the response values, and to determine the coefficient parameters of the relationship model.

[0010] As an alternative implementation method, after determining the coefficient parameters of the relational model, parameter significance testing and model fitting are performed.

[0011] As an alternative implementation method, the relational model is as follows: In some embodiments, the model function is obtained as follows: ; Where Y is the amount of lignin dissolved, in g / kg; The reaction temperature is in °C. Heating time, in minutes; The amount of alkali used is %. ∈[105,175], ∈[30,150], ∈[0,8].

[0012] As an alternative implementation method, after the reaction is completed, the reaction vessel is vented and cooled, the pretreated liquid is filtered and collected and stored at a predetermined temperature for testing, and the solid residue is washed until neutral and then air-dried for testing.

[0013] A precise control system for the leaching of eucalyptus components after sodium hydroxide pretreatment includes: The sample data acquisition module is used to react eucalyptus wood with sodium hydroxide under different pretreatment conditions; The prediction model building module is used to obtain and filter the pretreatment liquid after the reaction. The lignin component in the pretreatment liquid is used as the response value, and the reaction temperature, heating time and sodium hydroxide addition amount are used as independent variables. The relationship model between the independent variables and the response value is constructed and fitted to obtain the prediction model. The precision control module is used to determine the optimal reaction temperature, heating time, and sodium hydroxide addition amount based on the leaching requirements of the target eucalyptus components using a predictive model, and then performs precise control according to the determined results.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: To elucidate the mechanism of anti-degradation barrier deconstruction in eucalyptus wood fibers under different pretreatment intensities, this invention employs the Levenberg-Marquardt method to find the most suitable model parameters, thereby establishing an optimal component dissolution prediction model. During the alkali-thermal pretreatment of eucalyptus, the relationship between alkali dosage, reaction temperature, heating time, and component dissolution is non-linear, enabling precise control.

[0015] This invention analyzes the results of parameter significance tests. The model obtained also exhibits good performance on the training dataset. While most of the parameter estimates for the independent variables are not significant, possibly due to multicollinearity or other issues affecting the explanatory power of the independent variables on the dependent variable, R² = 0.9507 indicates a high degree of model fit, meaning the independent variables can explain 95.07% of the variance in the dependent variable. The adjusted R² = 0.9435, after considering the number of independent variables and sample size, still shows a good goodness of fit, indicating that the model can generally describe the relationships between variables well. F = 134.9122, with degrees of freedom (10, 70), and P < 0.05, means that overall, the regression model is significant, meaning at least one independent variable has a significant impact on the dependent variable.

[0016] This invention combines the overall model fit analysis with residual analysis plots in regression analysis to assess the rationality of the regression model and whether the assumptions are met. The residual vs. fitted value plot shows that the point distribution is relatively random, but further detailed observation is needed to observe whether there are potential trends. The residual distribution histogram shows that the residual distribution roughly presents a shape that is high in the middle and low at both ends, initially conforming to the characteristics of a normal distribution, but requiring a more rigorous normality test. If the residuals follow a normal distribution, the points in the residual normality test plot should be roughly distributed along the diagonal. Most points in the plot are close to the diagonal, indicating that the residuals conform to the normality assumption to a certain extent, but some points still deviate, which can be used to assist in numerical testing to determine normality. In the residual sequence plot, the residuals fluctuate randomly near the 0 line without obvious periodicity or trend, suggesting that the model may not have autocorrelation problems. Overall, these graphical results provide intuitive clues for model evaluation, showing that the model performs reasonably well in some basic assumptions. This invention provides a powerful tool for evaluating the effect of alkali-heat pretreatment and accurately controlling process parameters, and provides a theoretical basis and technical support for the high-value utilization of all components of eucalyptus.

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0018] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0019] Figure 1 This is a three-dimensional surface diagram of the lignin dissolution model of eucalyptus wood pretreated with sodium hydroxide according to an embodiment of the present invention. Figure 2 Residual analysis diagrams of the lignin dissolution model of sodium hydroxide pretreated eucalyptus wood in this embodiment of the invention: residuals vs. fitted values, residual distribution, normality QQ plot and residual sequence plot. Figure 3 The effects of reaction temperature and holding time on the concentrations of arabinose, galactose, glucose, and mannose (a), xylose (b), and lignin (c) in the sodium hydroxide pretreatment solution are shown in this embodiment of the invention. The effects of holding time and alkali dosage on the concentrations of arabinose, galactose, glucose, and mannose (d), xylose (e), and lignin (f) in the sodium hydroxide pretreatment solution are also shown.

[0020] Figure 4 The effect of different reaction temperatures on the lignin concentration in the sodium hydroxide pretreatment solution is shown in this embodiment of the invention.

[0021] Figure 5The effects of reaction temperature and hydrogen peroxide dosage on the concentrations of arabinose, galactose, glucose, mannose, xylose (a, g), lignin (bf, hl) and pH in the alkaline hydrogen peroxide pretreatment solution are presented in this embodiment of the invention.

[0022] Figure 6 The images show SEM images of eucalyptus wood surfaces before and after sodium hydroxide pretreatment with alkaline hydrogen peroxide, according to an embodiment of the present invention.

[0023] Figure 7 The images show XRD patterns of eucalyptus wood before and after pretreatment with sodium hydroxide at different alkali dosages (a), pretreatment with alkaline hydrogen peroxide at different reaction temperatures (b), and before and after pretreatment (c) according to embodiments of the present invention.

[0024] Note: HT and t in the figure represent reaction time (min); T represents reaction temperature (°C); S represents sodium hydroxide dosage (%); P represents hydrogen peroxide dosage (%); SHP represents sodium hydroxide pretreatment, and AHPP represents alkaline hydrogen peroxide pretreatment. Detailed Implementation

[0025] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0026] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0027] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0028] Where there is no conflict, the embodiments and features described in this application may be combined with each other.

[0029] Example 1 First, conduct the experiment, which includes the following steps: 1. The amount of alkali used in the sodium hydroxide solution is 0%, 2%, 4%, 6%, and 8%.

[0030] 2. Place the selected eucalyptus chips in a sealed bag to equilibrate the moisture for 48 hours. Weigh a certain amount of chips and place them in a 105℃ oven for 4 hours to measure their moisture content.

[0031] 3. Using the moisture content obtained in step 2, weigh 50g of oven-dried eucalyptus wood chips, add the prepared sodium hydroxide solution, mix well, and place in a vertical rotary reactor (1L×4).

[0032] 4. The reaction temperatures in the reactor were set to 105℃, 115℃, 125℃, 135℃, 145℃, 155℃, 165℃, and 175℃, with holding times of 30 min, 60 min, 90 min, 120 min, and 150 min, respectively. After the reaction, the gases were released, the mixture was cooled, and the solid and liquid were separated. The liquid was placed in a 4℃ refrigerator for testing, and the solid was washed and freeze-dried.

[0033] 5. The contents of arabinose, galactose, glucose, xylose and mannose in the pre-hydrolysate were determined using a two-step acid hydrolysis method.

[0034] 6. Dilute the supernatant obtained from the two acid hydrolysis steps in step 5 by 200-800 times, filter it into a sample vial using a 0.22µm syringe filter, and measure the changes in the content of five monosaccharides using an ICS-6000+ ion chromatograph.

[0035] 7. Prepare sugar standards at concentrations of 0.5, 1, 2, 5, and 10 ppm and plot standard curves, ensuring R² > 0.99. The mobile phase consists of 50 mM and 250 mM sodium hydroxide, 1 mM sodium acetate, and deionized water.

[0036] 8. The absorbance of the supernatant after centrifugation at 205 nm was measured using a UV-Vis spectrophotometer (Beijing Purkinje General Instrument Co., Ltd. (Jinan)). The acid-soluble lignin content was calculated using formula (1). The precipitate obtained after centrifugation following the first step of acid hydrolysis is Klason lignin. After freeze-drying, the precipitate is weighed, which is the amount of Klason lignin dissolved. .

[0037] 9. Concentration of acid-soluble lignin According to formula (1): (1) In formula (1), A is the absorbance of lignin at a wavelength of 205 nm; 110 is the absorption coefficient, L·g -1 ·cm -1 D represents the dilution factor.

[0038] (2) In formula (2), This refers to the total lignin concentration in the pre-hydrolyzed solution. The concentration of Klason lignin in the pre-hydrolyzed solution.

[0039] The next step is model building, including the following steps: 1. In the alkali-thermal pretreatment of eucalyptus, the relationship between the amount of alkali used, reaction temperature, heating time, and component dissolution is non-linear. Taking lignin dissolution as an example:

[0040] Where Y is the amount of lignin dissolved, in g / kg; The reaction temperature is in °C. Heating time, in minutes; The amount of alkali used is %. ∈[105,175], ∈[30,150], ∈[0,8]. These are coefficients to be determined.

[0041] 2. Based on the principle of minimizing the sum of squared errors →Min; By using the Levenberg-Marquardt method to solve for the undetermined coefficients, the model function can finally be obtained as follows:

[0042] 3. The results of the parameter significance test and the overall model fit analysis show that the model also exhibits good performance on the training dataset. The adjusted R² = 0.9435, after considering the number of independent variables and the sample size, still shows that the model has a good fit, indicating that the model can generally describe the relationship between variables well. F = 134.9122, with degrees of freedom of (10, 70), and P < 0.05, which means that the regression model is significant overall, indicating that it is feasible to use the Levenberg-Marquardt method to study the component dissolution law during alkali-thermal pretreatment of eucalyptus wood.

[0043] Finally, precise control is achieved based on the model, including the following steps: 1. The optimal conditions for sodium hydroxide pretreatment of eucalyptus were obtained during the model construction process. Hydrogen peroxide was then added to investigate the dissolution of eucalyptus components and changes in microstructure under alkaline hydrogen peroxide pretreatment.

[0044] 2. During the model construction process, the optimal sodium hydroxide dosage was 6% and the reaction time was 90 min.

[0045] 3. The solid-liquid ratio of the reaction is 1:4, the reaction temperature is 105℃, 125℃, 145℃, 165℃ and 175℃, and the amount of hydrogen peroxide added is 1%-4%.

[0046] 4. Through steps 2, 3 and 4 in the experimental process, alkaline hydrogen peroxide pre-hydrolyzed solution and treated wood chips were obtained.

[0047] 5. The microstructure of the eucalyptus wood chips before and after treatment was observed using a TM4000P scanning electron microscope (Hitachi Scientific Instruments (Beijing) Co., Ltd.) at an accelerating voltage of 15KV. The samples were pre-treated with gold sputtering to ensure conductivity during testing. The wood chips, before and after treatment, were ground into powder and spread evenly on a glass sample plate. X-ray diffractometer (Rigaku Smartlab SE, Japan) was used for scanning, with a scanning range of 5-50°, a scanning step of 0.05°, and a scanning speed of 20° / min.

[0048] 6. Molecular weight analysis of lignin before and after pretreatment was performed. The molecular weight of lignin was determined using gel permeation chromatography (GPC). Pure lignin samples obtained in different pretreatment solutions were acetylated by mixing the lignin sample with pyridine / acetic anhydride (1:1) and stirring in the dark at room temperature for 48 hours. After the reaction, the mixture was washed 2-3 times with hydrochloric acid and then freeze-dried to obtain acetylated lignin. A gel permeation chromatograph (Waters 2695) was used, equipped with a series of PLgel MIXED-E columns and a UV detector (254 nm). A series of polystyrene columns in the range of 2-100 kDa were used for column calibration, and tetrahydrofuran (THF) was used as the mobile phase. The flow rate was set to 0.6 mL / min.

[0049] Table 1. Comparison of lignin molecular weight before and after alkaline hydrogen peroxide pretreatment of eucalyptus in the Examples and Comparative Examples

[0050] Table 2. Results of Parameter Significance Test

[0051] To further elucidate the decomposition mechanism of the anti-degradation barrier under different pretreatment intensities of eucalyptus wood fibers, this invention uses the Levenberg-Marquardt method to find the most suitable model parameters, thereby establishing the optimal component dissolution prediction model.

[0052] like Figures 1-7 As shown, the relationship between alkali dosage, reaction temperature, heating time, and component dissolution during alkali-thermal pretreatment of eucalyptus is non-linear. Therefore, extensive preliminary experiments were conducted to obtain data on reaction conditions and corresponding lignin dissolution amounts. Using alkali dosage, reaction temperature, and reaction time as the X and Y axes, respectively, and the fitted value of lignin dissolution from the model species as the response variable, a three-dimensional surface plot of lignin dissolution in NaOH-pretreated eucalyptus was plotted. It can be seen that the lignin dissolution amount from eucalyptus fibers increases more significantly with increasing alkali dosage and reaction temperature, while remaining relatively unchanged with prolonged heating time.

[0053] Analysis of the parameter significance test results shows that the model also exhibits good performance on the training dataset. Most of the parameter estimates for the independent variables are not significant, possibly due to multicollinearity or other issues affecting the explanatory power of the independent variables on the dependent variable. However, R² = 0.9507 indicates a high degree of model fit, meaning the independent variables can explain 95.07% of the variance in the dependent variable. The adjusted R² = 0.9435, even after considering the number of independent variables and sample size, still shows a good good fit, indicating that the model can generally describe the relationships between variables well. F = 134.9122, degrees of freedom (10, 70), and P < 0.05, meaning that overall, the regression model is significant, i.e., at least one independent variable has a significant impact on the dependent variable.

[0054] Analysis of the overall model fit shows that the residual analysis plot in regression analysis is used to evaluate the rationality of the regression model and whether the assumptions are met. The residual vs. fitted value plot indicates that the point distribution is relatively random, but further detailed observation is needed to observe whether there are potential trends. The residual distribution histogram shows that the residual distribution roughly follows a pattern of high in the middle and low at both ends, initially conforming to the characteristics of a normal distribution, but requiring a more rigorous normality test. If the residuals follow a normal distribution, the points in the residual normality test QQ plot should be roughly distributed along the diagonal. Most points in the plot are close to the diagonal, indicating that the residuals conform to the normality assumption to a certain extent, but some points still deviate, which can be used to assist in numerical testing to determine normality. The residual series plot shows that the residuals fluctuate randomly around the 0 line without obvious periodicity or trend, suggesting that the model may not have autocorrelation problems. Overall, these graphical results provide intuitive clues for model evaluation, showing that the model performs reasonably well in some basic assumptions.

[0055] In summary, this embodiment provides a powerful tool for evaluating the effect of alkali-heat pretreatment and for precisely controlling process parameters, and provides a theoretical basis and technical support for the high-value utilization of all components of eucalyptus.

[0056] Example 2 A method for precise control of leaching of eucalyptus components after sodium hydroxide pretreatment includes the following steps: Eucalyptus chips were pretreated with sodium hydroxide under different process conditions. After the reaction, the content of monosaccharides and lignin in the pretreated solution was measured. A statistical regression equation for lignin dissolution under sodium hydroxide pretreatment was established. The Levenberg-Marquardt method was used for analysis and calculation. By minimizing the sum of squared errors, the optimal coefficient parameters were determined, and the model function was obtained. The model function was fitted to the lignin content in the pretreated solution to accurately predict the amount of lignin dissolution under different treatment conditions.

[0057] After the eucalyptus wood is selected, impurities and rotten or discolored wood chips are removed, and the larger wood chips are cut into similar sizes. In this embodiment, the amount of NaOH used is 0%-8%, and a sodium hydroxide solution is prepared. The solid-liquid ratio of eucalyptus chips to sodium hydroxide solution is 1:4 (mass ratio).

[0058] In this embodiment, the alkaline heat pretreatment temperature is 105℃-175℃, and the reaction time is 30min-150min.

[0059] In this embodiment, the model construction function is:

[0060] Where Y is the amount of lignin dissolved, in g / kg; The reaction temperature is in °C. Heating time, in minutes; The amount of alkali used is %. ∈[105,175], ∈[30,150], ∈[0,8].

[0061] In some embodiments, as preferred alkaline conditions, the amount of sodium hydroxide used is 6% and 10%, and the reaction time is 90 min.

[0062] In some embodiments, as a preferred method, eucalyptus wood is pretreated with alkaline hydrogen peroxide, with the amount of hydrogen peroxide being 1%-4% and the reaction temperature being 105℃-175℃.

[0063] After the reaction was completed, solid-liquid separation was performed, and the sugar components and lignin in the pre-hydrolyzed solution were qualitatively and quantitatively analyzed.

[0064] Example 3 A precise control system for the leaching of eucalyptus components after sodium hydroxide pretreatment includes: The sample data acquisition module is used to react eucalyptus wood with sodium hydroxide under different pretreatment conditions; The prediction model building module is used to obtain and filter the pretreatment liquid after the reaction. The lignin component in the pretreatment liquid is used as the response value, and the reaction temperature, heating time and sodium hydroxide addition amount are used as independent variables. The relationship model between the independent variables and the response value is constructed and fitted to obtain the prediction model. The precision control module is used to determine the optimal reaction temperature, heating time, and sodium hydroxide addition amount based on the leaching requirements of the target eucalyptus components using a predictive model, and then performs precise control according to the determined results.

[0065] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made by those skilled in the art without creative effort within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for precise control of leaching of eucalyptus components pretreated with sodium hydroxide, characterized in that, Includes the following steps: Eucalyptus wood was subjected to sodium hydroxide reaction under different pretreatment conditions; After the reaction, the pretreated solution was obtained and filtered. The lignin component in the pretreated solution was used as the response value, and the reaction temperature, heating time and sodium hydroxide addition amount were used as independent variables. A relationship model between the independent variables and the response value was constructed and fitted to obtain a prediction model. Based on the leaching requirements of the target eucalyptus components, the optimal reaction temperature, heating time, and sodium hydroxide addition amount are determined using a predictive model, and then precisely controlled according to the determined results.

2. The method for precise control of leaching of eucalyptus components pretreated with sodium hydroxide as described in claim 1, characterized in that, Before the eucalyptus wood undergoes a sodium hydroxide reaction under different pretreatment conditions, it is pre-selected to remove impurities and rotten or discolored wood chips, and then cut into predetermined sizes.

3. The method for precise control of leaching of eucalyptus components pretreated with sodium hydroxide as described in claim 1, characterized in that, The sodium hydroxide reaction is carried out in a reaction vessel.

4. The method for precise control of leaching of eucalyptus components pretreated with sodium hydroxide as described in claim 1, characterized in that, The process of carrying out sodium hydroxide reaction under different pretreatment conditions is as follows: under different pretreatment conditions, at least one of the reaction temperature, heating time and sodium hydroxide addition amount is different from the other pretreatment conditions, and the reaction temperature, heating time and sodium hydroxide addition amount are all adjusted within a predetermined range.

5. The method for precise control of leaching of eucalyptus components pretreated with sodium hydroxide as described in claim 4, characterized in that, Under different pretreatment conditions, the reaction temperature was adjusted between 105℃ and 175℃, the heating time was adjusted between 30 min and 150 min, and the sodium hydroxide addition was adjusted between 0% and 8%.

6. The method for precise control of leaching of eucalyptus components pretreated with sodium hydroxide as described in claim 1, characterized in that, The Levenberg-Marquardt method was used to construct a relationship model between independent variables and response values, and the coefficient parameters of the relationship model were determined.

7. The method for precise control of leaching of eucalyptus components pretreated with sodium hydroxide as described in claim 1, characterized in that, After determining the coefficient parameters of the relational model, the significance of the parameters and the model fitting are performed.

8. The method for precise control of leaching of eucalyptus components pretreated with sodium hydroxide as described in claim 1, characterized in that, The relational model is as follows: ； Where Y is the amount of lignin dissolved, in g / kg; The reaction temperature is in °C. Heating time, in minutes; The amount of alkali used is %. ∈[105,175], ∈[30,150], ∈[0,8].

9. The method for precise control of leaching of eucalyptus components pretreated with sodium hydroxide as described in claim 1, characterized in that, After the reaction is completed, the reactor is vented and cooled, the pretreated liquid is filtered and collected and stored at a predetermined temperature for testing, and the solid residue is washed until neutral and then air-dried for testing.

10. A precise control system for the leaching of eucalyptus components pretreated with sodium hydroxide, characterized in that, include: The sample data acquisition module is used to react eucalyptus wood with sodium hydroxide under different pretreatment conditions; The prediction model building module is used to obtain and filter the pretreatment liquid after the reaction. The lignin component in the pretreatment liquid is used as the response value, and the reaction temperature, heating time and sodium hydroxide addition amount are used as independent variables. The relationship model between the independent variables and the response value is constructed and fitted to obtain the prediction model. The precision control module is used to determine the optimal reaction temperature, heating time, and sodium hydroxide addition amount based on the leaching requirements of the target eucalyptus components using a predictive model, and then performs precise control according to the determined results.

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