CN117390869B - Pulping process dynamics model taking reducing sugar content as parameter - Google Patents
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- 238000004537 pulping Methods 0.000 title claims abstract description 59
- 238000004540 process dynamic Methods 0.000 title description 3
- 238000000034 method Methods 0.000 claims abstract description 51
- 239000010902 straw Substances 0.000 claims abstract description 45
- 108090000790 Enzymes Proteins 0.000 claims abstract description 44
- 102000004190 Enzymes Human genes 0.000 claims abstract description 44
- 241000209140 Triticum Species 0.000 claims abstract description 40
- 235000021307 Triticum Nutrition 0.000 claims abstract description 40
- 238000010009 beating Methods 0.000 claims abstract description 24
- 229940088598 enzyme Drugs 0.000 claims description 44
- 239000002002 slurry Substances 0.000 claims description 35
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 33
- 108010059892 Cellulase Proteins 0.000 claims description 20
- 101710121765 Endo-1,4-beta-xylanase Proteins 0.000 claims description 20
- 229940106157 cellulase Drugs 0.000 claims description 19
- 238000012216 screening Methods 0.000 claims description 15
- 238000005096 rolling process Methods 0.000 claims description 14
- 230000029087 digestion Effects 0.000 claims description 11
- 206010006514 bruxism Diseases 0.000 claims description 10
- HEMHJVSKTPXQMS-UHFFFAOYSA-M Sodium hydroxide Chemical compound [OH-].[Na+] HEMHJVSKTPXQMS-UHFFFAOYSA-M 0.000 claims description 9
- 238000012360 testing method Methods 0.000 claims description 9
- 238000001816 cooling Methods 0.000 claims description 5
- 239000000706 filtrate Substances 0.000 claims description 5
- 238000001914 filtration Methods 0.000 claims description 5
- 238000000227 grinding Methods 0.000 claims description 5
- 239000012535 impurity Substances 0.000 claims description 5
- 238000004898 kneading Methods 0.000 claims description 5
- 238000002156 mixing Methods 0.000 claims description 5
- 239000013049 sediment Substances 0.000 claims description 5
- 238000002791 soaking Methods 0.000 claims description 5
- 238000007619 statistical method Methods 0.000 claims description 5
- 238000005406 washing Methods 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000013461 design Methods 0.000 claims description 4
- 238000007865 diluting Methods 0.000 claims description 4
- 238000011835 investigation Methods 0.000 claims description 4
- 238000010025 steaming Methods 0.000 claims description 4
- 239000008367 deionised water Substances 0.000 claims description 3
- 229910021641 deionized water Inorganic materials 0.000 claims description 3
- 239000012153 distilled water Substances 0.000 claims description 3
- 238000011156 evaluation Methods 0.000 claims description 3
- 238000004255 ion exchange chromatography Methods 0.000 claims description 3
- 238000002386 leaching Methods 0.000 claims description 3
- 238000010993 response surface methodology Methods 0.000 claims description 3
- QAOWNCQODCNURD-UHFFFAOYSA-N sulfuric acid Substances OS(O)(=O)=O QAOWNCQODCNURD-UHFFFAOYSA-N 0.000 claims description 3
- 239000006228 supernatant Substances 0.000 claims description 3
- 230000001681 protective effect Effects 0.000 claims description 2
- 239000002351 wastewater Substances 0.000 abstract description 4
- 239000003513 alkali Substances 0.000 abstract description 3
- 238000001514 detection method Methods 0.000 abstract description 2
- 230000000694 effects Effects 0.000 description 12
- 108010059820 Polygalacturonase Proteins 0.000 description 8
- 108010093305 exopolygalacturonase Proteins 0.000 description 8
- 238000002474 experimental method Methods 0.000 description 5
- 239000002994 raw material Substances 0.000 description 4
- 239000000835 fiber Substances 0.000 description 3
- 238000005265 energy consumption Methods 0.000 description 2
- 244000005700 microbiome Species 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000000540 analysis of variance Methods 0.000 description 1
- 239000003153 chemical reaction reagent Substances 0.000 description 1
- 238000010494 dissociation reaction Methods 0.000 description 1
- 230000005593 dissociations Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 238000005470 impregnation Methods 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000004513 sizing Methods 0.000 description 1
- 230000001954 sterilising effect Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000003911 water pollution Methods 0.000 description 1
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Abstract
The invention discloses a dynamic model of a pulping process taking reducing sugar content as a parameter, and belongs to the technical field of pulping. The dynamic model of the pulping process with the content of the reducing sugar as a parameter, which is provided by the invention, has the advantages that P less than 0.05, the remarkable degree is achieved, the fitting condition is good, and the response value detection can be carried out; r of model 2 0.9922, the standard error is 0.044, the variation coefficient is 1.19%, the signal to noise ratio is 41.729 & gt4, the prediction result is reliable, and the method can be used for predicting the beating degree result after the wheat straw pulping is finished, and the prediction result is comprehensive and accurate; the use of biological enzyme with optimal ratio can greatly reduce the dosage of alkali liquor, thereby effectively reducing the outflow of papermaking black liquor and relieving the treatment pressure of papermaking wastewater.
Description
Technical Field
The invention relates to the technical field of pulping, in particular to a dynamic model of a pulping process taking reducing sugar content as a parameter.
Background
The disclosure of this background section is only intended to increase the understanding of the general background of the invention and is not necessarily to be construed as an admission or any form of suggestion that this information forms the prior art already known to those of ordinary skill in the art.
The biomechanical pulping refers to the pretreatment of raw materials by using microorganisms or enzymes instead of chemicals before mechanical pulping, so that not only can the waste water pollution be reduced, but also the pulping energy consumption can be reduced, and the pulp strength can be improved. The principle is that microorganisms or enzymes are used for acting on raw materials to selectively degrade non-fiber components in the raw materials, so that the fiber can be swelled and softened, fiber damage in the pulping process can be reduced, the physical strength of pulp can be improved, the pulping energy consumption can be reduced, pollution can be reduced, and the method has a wide application prospect.
In the traditional pulping process, pulp monitoring can only be detected after pulping is finished, and the final beating degree and other results cannot be accurately predicted. Therefore, a set of biochemical mechanical pulping system taking wheat straw as raw material is established, and the pulping degree result is predicted after the pulping is finished, so that the method has great significance to pulping and papermaking industries.
Disclosure of Invention
The invention aims to provide a dynamic model of pulping process taking reducing sugar content as a parameter so as to accurately predict the beating degree result after the wheat straw pulping is finished before pulping.
In order to achieve the above object, the present invention provides a dynamic model of pulping process using reducing sugar content as a parameter, the dynamic model is:
f(y)＝24.3110-18.7668×cos(5.8988×y)-0.0594×sin(5.8988×y)-28.7679×cos(5.8988×y×2)-7.8964×sin(5.8988×y×2)-30.6935×cos(5.8988×y×3)-26.9005×sin(5.8988×y×3)-25.9513×cos(5.8988×y×4)-36.2999×sin(5.8988×y×4)-16.7352×cos(5.8988×y×5)-24.8478×sin(5.8988×y×5)-5.9280×cos(5.8988×y×6)-7.4524×sin(5.8988×y×6)，
y＝3.70-0.18×A-0.36×B-0.19×C+0.0084×AB+0.077×AC-0.11×BC+0.10×A 2 -0.047×B 2 -0.029×C 2
wherein f (y) is pulping beating degree, the unit is DEG SR, y is reducing sugar content, the unit is mg/g, A is xylanase dosage, B is cellulase dosage, C is pectase dosage, and the unit is%.
The method for establishing the dynamic model of the pulping process by taking the content of the reducing sugar as a parameter comprises the following steps:
s1, selecting the biological enzyme dosage in the pulping process flow as an investigation factor, and optimally screening by taking the beating degree and the reducing sugar content after pulping as evaluation indexes;
s2, inputting the optimized screening data obtained in the step S1 into Design-expert 8.0 software to carry out Box-Behnken Design-Response Surface Methodology test Design, and fitting the beating degree and the reducing sugar content serving as response values;
s3, performing variance analysis on the obtained correlation model of the reducing sugar content and the biological enzyme dosage;
and S4, carrying out fitting statistical analysis on fitting data of a meaningful reducing sugar content and biological enzyme consumption correlation model, and obtaining a fitting equation of the relation between different beating degrees and reducing sugar content expressed by coding factors by using MATLAB R2023a software.
Preferably, the amount of the biological enzyme in the step S1 includes 3 investigation factors, i.e. xylanase amount, cellulase amount, and pectase amount, and each factor is set to 2 levels: xylanase in an amount of 0.2% and 0.4%, cellulase in an amount of 0.1% and 0.3%, and pectase in an amount of 0.2% and 0.4%.
Preferably, the optimization screening in the step S1 adopts a Box-Behnken response surface method; the fitting statistical analysis of the fitting data in step S4 is implemented by MATLAB R2023a software.
Preferably, the beating degree obtaining method comprises the following steps:
s1-1, washing wheat straw to remove sediment and other non-fibrous impurities;
s1-2, soaking the washed wheat straw in hot water to fully swell the straw;
s1-3, adopting wheat straw immersed in hot water to carry out thread rolling, wherein the distance between grinding teeth is 1mm, and the thread rolling is carried out twice;
s1-4, putting the wheat straw after thread rolling into Gao Wentong, adding a certain amount of alkaline hot water at 100 ℃, fully kneading and uniformly mixing, and steaming at 100 ℃ for 40min;
s1-5, carrying out two-stage pulping on wheat straw immersed in alkaline hot water, wherein the distance between grinding teeth is 0.5mm and 0.15mm respectively;
s1-6, placing the pulp after pulp grinding into warm water at 60 ℃ to be degerming for 10min;
s1-7, cooling the slurry after the digestion to room temperature, adjusting the pH to the optimal pH of the biological enzyme, adding the biological enzyme accounting for 0.2% of the mass of the wheat straw, and preserving the heat for 4 hours;
s1-8, filtering the slurry treated by the biological enzyme by using a slurry bag, screening the obtained coarse slurry by using a slurry screening machine to obtain good slurry, preparing the good slurry into absolute dry slurry, diluting, and reading an DEG SR value by using a beating degree tester.
Preferably, the method for obtaining the content of the reducing sugar comprises the following steps:
s1.1, washing wheat straw to remove sediment and other non-fibrous impurities;
s1.2, soaking the washed wheat straw in hot water to fully swell the straw;
s1.3, adopting wheat straw immersed in hot water to carry out thread rolling, wherein the distance between grinding teeth is 1mm, and the thread rolling is carried out twice;
s1.4, putting the wheat straw after thread rolling into Gao Wentong, adding a certain amount of alkaline hot water at 100 ℃, fully kneading and uniformly mixing, and steaming at 100 ℃ for 40min;
s1.5, carrying out two-stage pulping on wheat straw immersed in alkaline hot water, wherein the distance between grinding teeth is 0.5mm and 0.15mm respectively;
s1.6, placing the pulp after pulp grinding into warm water at 60 ℃ to be degerming for 10min;
s1.7, cooling the slurry after the digestion to room temperature, adjusting the pH to the optimal pH of the biological enzyme, adding the biological enzyme accounting for 0.2% of the mass of the wheat straw, and preserving the heat for 4 hours;
s1.8, filtering the slurry treated by biological enzymes by using a slurry bag, placing the filtrate into a digestion tube, adding concentrated sulfuric acid, adding deionized water, placing the digestion tube into an autoclave, preserving heat at 121 ℃ for 60min, centrifuging 12000r/min for 5min, taking supernatant, adopting ICS-5000 ion chromatography, using carboPacPA20 as an analytical column, using carboPacPA20 as a protective column, adopting 250mmol/L NaOH and distilled water as mobile phases at a column temperature of 30 ℃, carrying out gradient leaching at a flow rate of 0.4mL/min, and reading and calculating the reducing sugar content value.
The application of the dynamic model of pulping process taking the content of reducing sugar as a parameter in predicting the result of pulping freeness of wheat straw.
Therefore, the pulping process dynamics model taking the reducing sugar content as a parameter has the following specific technical effects:
(1) The P of the dynamic model of the pulping process taking the reducing sugar content as a parameter is less than 0.05, the remarkable degree is achieved, the fitting condition is good, and the response value can be detected;
(2) The R of the dynamic model of the pulping process taking the content of reducing sugar as the parameter 2 0.9922, the standard error is 0.044, the variation coefficient is 1.19%, the signal to noise ratio is 41.729 & gt4, and the prediction result is reliable and can be used for predicting the beating degree result after the wheat straw pulping is finished;
(3) The wheat straw pulping process flow provided by the invention is the optimal parameter suitable for wheat straw pulping, can obtain higher beating degree, and can greatly reduce the dosage of alkali liquor by using biological enzyme with optimal ratio, thereby effectively reducing the outflow of papermaking black liquor and relieving the treatment pressure of papermaking wastewater;
(4) The method for establishing the dynamic model of the pulping process taking the content of the reducing sugar as the parameter is simple and effective, and the Design-Expert 8.0 software and the MATLAB R2023a software are used for carrying out equation Design by taking the content of the reducing sugar measured after pulping as an index, so that the prediction result is comprehensive and accurate.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments of the present invention will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of obtaining a freeness value in embodiment one;
FIG. 2 is the effect of varying amounts of xylanase on freeness in example one;
FIG. 3 is the effect of varying amounts of cellulase on freeness in example one;
FIG. 4 is the effect of varying amounts of pectase on the sizing degree in example one;
FIG. 5 is a graph showing the effect of varying amounts of xylanase on reducing sugar content in example one;
FIG. 6 is a graph showing the effect of varying amounts of cellulase on reducing sugar content in example one;
FIG. 7 is the effect of varying amounts of pectase on reducing sugar content in example one.
Detailed Description
The technical scheme of the invention is further described below through the attached drawings and the embodiments.
In order to make the objects, technical solutions and advantages of the present application more clear, thorough and complete, the technical solutions of the present invention will be clearly and completely described below through the accompanying drawings and examples. The following detailed description is of embodiments, and is intended to provide further details of the invention. Unless defined otherwise, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
The reagents, instrumentation, and so forth used in the examples were all commercially available from Norwestine (China) Biotechnology Inc. with xylanase, pectinase, and cellulase enzymes.
Example 1
Pre-experiments were performed to determine 2 levels of bio-enzyme usage by the following method:
s1-1, washing 18 parts of 100g wheat straw with water to remove sediment and other non-fibrous impurities.
S1-2, adding 400mL of 55 ℃ hot water into the washed wheat straw for soaking, so that the straw is fully swelled for 10min.
S1-3, adopting a high-concentration continuous disc mill to thread the wheat straw after hot water impregnation, wherein the distance between grinding teeth is 1mm, and the thread rolling is carried out twice.
S1-4, placing the wheat straw after thread rolling into Gao Wentong, adding a solution prepared by dissolving 5.6g of KOH (the addition amount is 5.6% of the mass of the wheat straw) into 800mL of water (the solid-liquid ratio is 1:8), heating the system to 100 ℃, fully kneading and uniformly mixing, and placing the mixture into a sterilizing pot at 100 ℃ for 40min.
S1-5, carrying out two-stage pulping on the wheat straw immersed by alkaline hot water by adopting a high-concentration continuous disc mill, wherein the grinding tooth spacing is 0.5mm and 0.15mm respectively.
S1-6, placing the pulp after pulp grinding into warm water at 60 ℃ for 10min of de-submerging.
S1-7, cooling the slurry after the digestion to room temperature, detecting the pH of the slurry by using a pH meter and using 1M H 3 PO 4 Regulating pH to 5.5, adding xylanase, cellulase and pectase which are 0.1-0.5% of the mass of the wheat straw respectively, placing in a water bath kettle at 55 ℃, and preserving heat for 4h.
S1-8, filtering the slurry after biological enzyme treatment by using a slurry bag, screening the obtained crude slurry by using a slurry screening machine to obtain good slurry, taking a slurry sample of 2.00g absolute dry slurry, diluting to 1000mL, and transferring the slurry into a dissociator for dissociation, wherein the flow chart is shown in figure 1. The slurry is transferred to a Shober-Ruiger filter chamber, the filtrate passing through the filter layer on the filter screen enters two different graduated cylinders below the beating degree measuring instrument, the graduations in the lateral graduated cylinders are observed, and the SR value is read, and the result is shown in figures 2-4.
S1-9, taking 1mL of the filtrate filtered by the slurry bag in the step S1-8, placing the filtrate in a digestion tube, and adding 45 mu L of 98% concentrated sulfuric acid and 955 mu L of deionized water. The digestion tube was placed in an autoclave and incubated at 121℃for 60min. Centrifuging at 12000r/min for 5min, taking supernatant, diluting for 10 times, adopting ICS-5000 ion chromatography, taking carboPacPA20 (3 mm multiplied by 150 mm) as an analysis column, taking carboPacPA20 (3 mm multiplied by 30 mm) as a protection column, sampling for 25 mu L at a column temperature of 30 ℃, adopting 250mmol/L NaOH and distilled water as mobile phases, carrying out gradient leaching at a flow rate of 0.4mL/min, and reading and calculating the reducing sugar content value. The results are shown in FIGS. 5-7.
From FIGS. 2-7 it can be seen that the effects of different amounts of xylanase, cellulase and pectinase on the pulping degree and the reducing sugar content are different, wherein the optimum levels are 0.3% of xylanase, 0.2% of cellulase and 0.3% of pectinase, and therefore 2 levels of the amount of biological enzyme are determined as the values in Table 1.
TABLE 1Box-Behnken response surface test factors and levels
Example two
The evaluation index values of the freeness and the reducing sugar content were obtained exactly as in example one, except that the amounts of the biological enzymes added in steps S1 to S7 were changed to the factor level ranges in Table 1, i.e., 0.2 to 0.4% xylanase, 0.1 to 0.3% cellulase, and 0.2 to 0.4% pectinase were added, respectively, and the measured freeness values and the calculated reducing sugar content values are shown in Table 2.
TABLE 2Box-Behnken response surface optimization screening results
Example III
A model for correlating the use amount of biological enzyme with the content of reducing sugar is established, and the method comprises the following steps:
s3-1, selecting the amount of the biological enzyme in the pulping process flow: the xylanase dosage, the cellulase dosage and the pectinase dosage are 3 investigation factors, and each factor is respectively provided with 2 levels: xylanase was used in an amount of 0.2% and 0.4%, cellulase was used in an amount of 0.1% and 0.3%, and pectase was used in an amount of 0.2% and 0.4%, the factors and level settings are shown in Table 1.
The results of optimized screening using Box-Behnken response surface method with the beating degree value and reducing sugar content value in Table 2 as response values are shown in Table 2.
S3-2, inputting the optimized screening data obtained in the table 2 into Design-expert 8.0 software to carry out Box-Behnken Design-Response Surface Methodology (BBD-RSM) test Design, and fitting the beating degree and the reducing sugar content in the table 2 as response values to obtain a model of correlating the reducing sugar content with the biological enzyme consumption, wherein the model is as follows:
y＝3.70-0.18×A-0.36×B-0.19×C+0.0084×AB+0.077×AC-0.11×BC+0.10×A 2 -0.047×B 2 -0.029×C 2 ，
wherein y is the content of reducing sugar, the unit is mg/g, A is the xylanase dosage, the unit is the cellulase dosage, and the unit is the pectase dosage, and the unit is the percent.
S3-3, performing variance analysis on the model of correlation between the content of the reducing sugar and the amount of the biological enzyme obtained in the step S3-2, and the results are shown in Table 3.
TABLE 3 analysis of variance of the results of the model test for the correlation of reducing sugar content and amount of biological enzyme
As can be seen from table 3, the p <0.05 of the established model of the relation between the reducing sugar content and the biological enzyme dosage shows that the model of the relation between the reducing sugar content and the biological enzyme dosage reaches a remarkable degree, and the model has good fitting condition and is meaningful, and can detect response values.
Effect example 1
Experiments prove that the prediction effect of the model for correlating the content of the reducing sugar with the dosage of the biological enzyme, which is established in the third embodiment, is as follows:
setting the reducing sugar content to be 3.6mg/g, and inputting the setting value into a model for correlating the reducing sugar content and the biological enzyme dosage in Design-Expert 8.0 software to obtain the biological enzyme dosages in the pulping process, wherein the biological enzyme dosages are respectively as follows: xylanase 0.21%, cellulase 0.28% and pectase 0.29%.
The experiment was performed by the method of example one, except that the amount of the biological enzyme added was changed to 0.29% of xylanase, 0.18% of cellulase and 0.38% of pectinase. The reducing sugar content of the slurry sample was 3.558mg/g as measured by the method described in example one, and the error between the experimental result and the predicted value was 1.18%.
Example IV
A fitting equation of the relation between the reducing sugar content and different freeness is established, and the method is as follows:
s4-1, fitting statistical analysis is carried out on the fitting data of the related model of the reducing sugar content and the biological enzyme dosage, which is obtained in the third embodiment, and the result is shown in Table 4.
Table 4 fit statistics of fit data
| Statistical type | Value of | Statistical type | Value of |
| Std.Dev. | 0.044 | R-Squared | 0.9922 |
| Mean | 3.72 | Adj R-Squared | 0.9822 |
| C.V.％ | 1.19 | Pred R-Squared | 0.945 |
| PRESS | 0.097 | Adeq Precision | 41.729 |
As can be seen from Table 4, R of the model of the relation between the reducing sugar content and the amount of the biological enzyme 2 0.9922, standard error of 0.044, coefficient of variation of 1.19% and signal to noise ratio of 41.729 > 4, indicating that the test result is reliable.
S4-2, performing nonlinear fitting on the freeness (f (y)) and the reducing sugar content (y) by utilizing MATLAB R2023a to obtain a fitting equation which accords with Fourier transform distribution and is expressed by coding factors and is related to the relation between different freeness and reducing sugar content, wherein the fitting equation is as follows:
f(y)＝24.3110-18.7668×cos(5.8988×y)-0.0594×sin(5.8988×y)-28.7679×cos(5.8988×y×2)-7.8964×sin(5.8988×y×2)-30.6935×cos(5.8988×y×3)-26.9005×sin(5.8988×y×3)-25.9513×cos(5.8988×y×4)-36.2999×sin(5.8988×y×4)-16.7352×cos(5.8988×y×5)-24.8478×sin(5.8988×y×5)-5.9280×cos(5.8988×y×6)-7.4524×sin(5.8988×y×6)，
wherein f (y) is pulping beating degree, the unit is DEG SR, y is reducing sugar content, and the unit is mg/g.
The values of the constants in the equation at 95% confidence are given in Table 5.
Table 5 values of constants in the formula at 95% confidence and confidence limits
| Constant (constant) | Value of | Confidence lower limit | Confidence upper limit |
| a 0 | 24.3110 | 8.7542 | 39.8678 |
| a 1 | -18.7668 | -77.7621 | 40.2286 |
| b 1 | -0.0594 | -19.3063 | 19.1874 |
| a 2 | -28.7679 | -135.0536 | 77.5178 |
| b 2 | -7.8964 | -17.1538 | 1.3609 |
| a 3 | -30.6935 | -152.1935 | 90.8064 |
| b 3 | -26.9005 | -80.1645 | 26.3636 |
| a 4 | -25.9513 | -128.8902 | 76.9875 |
| b 4 | -36.2999 | -118.0269 | 45.4271 |
| a 5 | -16.7352 | -80.5112 | 47.0407 |
| b 5 | -24.8478 | -81.2992 | 31.6037 |
| a 6 | -5.9280 | -26.9953 | 15.1392 |
| b 6 | -7.4524 | -23.5492 | 8.6444 |
| w | 5.8988 | 5.8365 | 5.9610 |
The goodness-of-fit test was performed on the fit equation and the results are shown in table 6.
Table 6 goodness-of-fit test of the fit equation
| Goodness of fit | Value of |
| SSE | 0.5991 |
| R 2 | 0.9951 |
| DFE | 3.0000 |
| Adjusting R 2 | 0.9736 |
| RMSE | 0.4469 |
As can be seen from tables 5 and 6, the equation model fits better.
Effect example two
The experiment tests the predictive effect of the fitting equation of the relation between the reducing sugar content and different freeness, which is established in the fourth embodiment, the method is as follows:
setting the reducing sugar content to be 3.5mg/g, calculating the beating degree to be 27.99 DEG SR through a fitting equation established in the fourth embodiment, inputting the reducing sugar content into a fitting equation of the relation between the reducing sugar content in Design-Expert 8.0 software and different beating degrees, and obtaining the biological enzyme dosage in the pulping process respectively as follows: the xylanase addition amount was 0.21%, the cellulase addition amount was 0.23%, and the pectinase addition amount was 0.39%.
Experiments were performed by the method of obtaining the freeness in example one, except that the amount of the biological enzyme added was changed to 0.21% of xylanase, 0.23% of cellulase and 0.39% of pectinase. After the pulping is finished, the freeness is measured to be 29 DEG SR by adopting the freeness measuring method in the first embodiment, and the error between the predicted value and the actual detection value is 3.48%.
And the prediction model has good fitting degree.
Therefore, the dynamic model of the pulping process with the reducing sugar content as a parameter, which is provided by the invention, has the P less than 0.05, achieves the remarkable degree and good fitting condition, and can detect the response value; r of model 2 0.9922, the standard error is 0.044, the variation coefficient is 1.19%, the signal to noise ratio is 41.729 & gt4, the prediction result is reliable, and the method can be used for predicting the beating degree result after the wheat straw pulping is finished, and the prediction result is comprehensive and accurate; the use of biological enzyme with optimal ratio can greatly reduce the dosage of alkali liquor, thereby effectively reducing the outflow of papermaking black liquor and relieving the treatment pressure of papermaking wastewater.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention and not for limiting it, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that: the technical scheme of the invention can be modified or replaced by the same, and the modified technical scheme cannot deviate from the spirit and scope of the technical scheme of the invention.
Claims (5)
1. A method for establishing a dynamic model of a pulping process by taking reducing sugar content as a parameter is characterized by comprising the following steps:
s1, selecting the biological enzyme dosage in the pulping process flow as an investigation factor, and optimally screening by taking the beating degree and the reducing sugar content after pulping as evaluation indexes;
s2, inputting the optimized screening data obtained in the step S1 into Design-expert 8.0 software to carry out Box-Behnken Design-Response Surface Methodology test Design, and fitting the beating degree and the reducing sugar content serving as response values;
s3, performing variance analysis on the obtained correlation model of the reducing sugar content and the biological enzyme dosage;
s4, carrying out fitting statistical analysis on fitting data of a meaningful reducing sugar content and biological enzyme consumption correlation model, and obtaining a fitting equation of the relation between different beating degrees and reducing sugar content expressed by coding factors by using MATLAB R2023a software;
the dynamics model is as follows:
f(y)＝24.3110-18.7668×cos(5.8988×y)-0.0594×sin(5.8988×y)-28.7679×cos(5.8988×y×2)-7.8964×sin(5.8988×y×2)-30.6935×cos(5.8988×y×3)-26.9005×sin(5.8988×y×3)-25.9513×cos(5.8988×y×4)-36.2999×sin(5.8988×y×4)-16.7352×cos(5.8988×y×5)-24.8478×sin(5.8988×y×5)-5.9280×cos(5.8988×y×6)-7.4524×sin(5.8988×y×6)，
y＝3.70-0.18×A-0.36×B-0.19×C+0.0084×AB+0.077×AC-0.11×BC+0.10×A 2 -0.047×B 2 -0.029×C 2
wherein f (y) is pulping beating degree, the unit is DEG SR, y is reducing sugar content, the unit is mg/g, A is xylanase dosage, B is cellulase dosage, C is pectase dosage, and the unit is pectase dosage;
the beating degree obtaining method comprises the following steps:
s1-1, washing wheat straw to remove sediment and other non-fibrous impurities;
s1-2, soaking the washed wheat straw in hot water to fully swell the straw;
s1-3, adopting wheat straw immersed in hot water to carry out thread rolling, wherein the distance between grinding teeth is 1mm, and the thread rolling is carried out twice;
s1-4, putting the wheat straw after thread rolling into Gao Wentong, adding a certain amount of alkaline hot water at 100 ℃, fully kneading and uniformly mixing, and steaming at 100 ℃ for 40min;
s1-5, carrying out two-stage pulping on wheat straw immersed in alkaline hot water, wherein the distance between grinding teeth is 0.5mm and 0.15mm respectively;
s1-6, placing the pulp after pulp grinding into warm water at 60 ℃ to be degerming for 10min;
s1-7, cooling the slurry after the digestion to room temperature, adjusting the pH to the optimal pH of the biological enzyme, adding the biological enzyme accounting for 0.2% of the mass of the wheat straw, and preserving the heat for 4 hours;
s1-8, filtering the slurry treated by the biological enzyme by using a slurry bag, screening the obtained coarse slurry by using a slurry screening machine to obtain good slurry, preparing the good slurry into absolute dry slurry, diluting, and reading an DEG SR value by using a beating degree tester.
2. The method for building a dynamic model of a pulping process according to claim 1, wherein the amount of biological enzyme in step S1 includes 3 factors, i.e. xylanase, cellulase and pectase, respectively, and each factor is set to 2 levels: xylanase in an amount of 0.2% and 0.4%, cellulase in an amount of 0.1% and 0.3%, and pectase in an amount of 0.2% and 0.4%.
3. The method for establishing a dynamic model of a pulping process taking reducing sugar content as a parameter according to claim 1, wherein the method comprises the following steps of: the optimized screening in the step S1 adopts a Box-Behnken response surface method; the fitting statistical analysis of the fitting data in step S4 is implemented by MATLAB R2023a software.
4. The method for establishing a dynamic model of a pulping process by taking the content of reducing sugar as a parameter according to claim 1, wherein the method for acquiring the content of reducing sugar is as follows:
s1.1, washing wheat straw to remove sediment and other non-fibrous impurities;
s1.2, soaking the washed wheat straw in hot water to fully swell the straw;
s1.3, adopting wheat straw immersed in hot water to carry out thread rolling, wherein the distance between grinding teeth is 1mm, and the thread rolling is carried out twice;
s1.4, putting the wheat straw after thread rolling into Gao Wentong, adding a certain amount of alkaline hot water at 100 ℃, fully kneading and uniformly mixing, and steaming at 100 ℃ for 40min;
s1.5, carrying out two-stage pulping on wheat straw immersed in alkaline hot water, wherein the distance between grinding teeth is 0.5mm and 0.15mm respectively;
s1.6, placing the pulp after pulp grinding into warm water at 60 ℃ to be degerming for 10min;
s1.7, cooling the slurry after the digestion to room temperature, adjusting the pH to the optimal pH of the biological enzyme, adding the biological enzyme accounting for 0.2% of the mass of the wheat straw, and preserving the heat for 4 hours;
s1.8, filtering the slurry treated by biological enzymes by using a slurry bag, placing the filtrate into a digestion tube, adding concentrated sulfuric acid, adding deionized water, placing the digestion tube into an autoclave, preserving heat at 121 ℃ for 60min, centrifuging 12000r/min for 5min, taking supernatant, adopting ICS-5000 ion chromatography, using carboPacPA20 as an analytical column, using carboPacPA20 as a protective column, adopting 250mmol/L NaOH and distilled water as mobile phases at a column temperature of 30 ℃, carrying out gradient leaching at a flow rate of 0.4mL/min, and reading and calculating the reducing sugar content value.
5. Use of a method for building a dynamic model of a pulping process according to any of claims 1-4 with reducing sugar content as a parameter for predicting the result of the freeness of wheat straw pulping.
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| WO2020133856A1 (en) * | 2018-12-29 | 2020-07-02 | 齐鲁工业大学 | Method for preparing biomechanical primary color pulp from wheat straw |
| CN113341778A (en) * | 2021-06-11 | 2021-09-03 | 齐鲁工业大学 | Method for performing online control on wheat straw pulping by using fitting equation |
| CN115896210A (en) * | 2022-11-10 | 2023-04-04 | 厦门蓝湾科技有限公司 | Preparation method of high-content chitosan oligosaccharide with helicobacter pylori resistance |
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