Methods for determining the water content of polymerization solutions
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-05-28
- Publication Date
- 2026-08-14
Smart Images
Figure CN122567586A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of detection technology for polymer solutions, and more particularly to a method for detecting the water content of polymer solutions. Background Technology
[0002] Against the backdrop of the rapid development of the carbon fiber industry, the performance of carbon fiber products is constantly improving, but the technology for detecting the moisture content of raw materials and intermediates in the production process is relatively lacking.
[0003] In related technologies, Karl Fischer potentiometric titration is commonly used to detect the water content of a solution. However, the operation is complicated, the reagent consumption is large, the detection process introduces large errors, and it can also introduce interfering components, resulting in inaccurate detection of the water content of the solution. Summary of the Invention
[0004] To overcome the problems existing in related technologies, this application provides a method for detecting the water content of a polymerization solution.
[0005] This application provides a method for detecting the water content of a polymerization solution, the method comprising: Prepare the base stock solution; The basic mother liquor is dehydrated to obtain dried mother liquor; The dried mother liquor is divided into several training mother liquors, and the mass of each training mother liquor is recorded and recorded as the first mass. Distilled water was added to each of the training mother liquors to obtain a polymerization solution, and the mass of each polymerization solution was recorded and denoted as the second mass. Each of the polymer solutions is placed in a preset transmission container, each of the polymer solutions is controlled within a preset temperature range, and the absorbance data of each of the polymer solutions is detected within a preset wavenumber range. Based on the second mass of several polymer solutions, the absorbance data, and the first mass of the polymer solution corresponding to the training mother liquor, a target prediction model is established to predict the water content of the solution based on the absorbance data. The solution to be tested is placed in the preset transmission container, the solution to be tested is controlled within the preset temperature range, and the absorbance data of the solution to be tested is detected within the preset wavenumber range. The water content of the solution to be tested is obtained based on the absorbance data of the solution to be tested and the target prediction model.
[0006] In some embodiments of this application, the basic mother liquor is dehydrated to obtain a dried mother liquor, including: The base mother liquor was pre-dehydrated using a molecular sieve that had been dried and activated; The pre-dehydrated base mother liquor is passed through a drying tube filled with a desiccant for deep dehydration to obtain a dried mother liquor.
[0007] In some embodiments of this application, the base mother liquor is pre-dehydrated using a molecular sieve that has been dried and activated, including: The dried and activated molecular sieves are added to the base mother liquor; The basic mother liquor added to the molecular sieve is allowed to stand for a first preset time; The base mother liquor is filtered using a filtration device equipped with an organic filter membrane to obtain the base mother liquor after pre-dehydration treatment.
[0008] In some embodiments of this application, the desiccant in the drying tube is anhydrous magnesium sulfate.
[0009] In some embodiments of this application, the dried mother liquor is divided into several portions of training mother liquor, including: The dried mother liquor was divided into several equal portions of training mother liquor.
[0010] In some embodiments of this application, distilled water is added to each of the training mother liquors to obtain a polymerization solution, including: Different masses of distilled water were added to each of the training mother liquors to obtain polymerization solutions.
[0011] In some embodiments of this application, controlling each of the polymerization solutions within a preset temperature range and detecting the absorbance data of each of the polymerization solutions within a preset wavenumber range includes: The near-infrared spectrometer is used to control each of the polymerization solutions within a preset temperature range, and the near-infrared spectrometer is used to detect the absorbance data of each of the polymerization solutions within a preset wavenumber range.
[0012] In some embodiments of this application, a near-infrared spectroscopy is used to control each of the polymerization solutions within a preset temperature range, including: The temperature of each preset transmission container containing the polymerization solution is detected in real time using the temperature detection module of a near-infrared spectrometer and recorded as the first detection temperature. When the first detected temperature is lower than the minimum value of the preset temperature range, the controller of the near-infrared spectrometer controls the heating device to heat the preset transmission container so that the temperature of the preset transmission container is within the preset temperature range. When the first detected temperature is higher than the maximum value of the preset temperature range, the controller of the near-infrared spectrometer controls the cooling device to cool the preset transmission container so that the temperature of the preset transmission container is within the preset temperature range.
[0013] In some embodiments of this application, a target prediction model for predicting the water content of a solution based on absorbance data is established according to a plurality of samples of the second mass of the polymerization solution, the absorbance data, and the first mass of the polymerization solution corresponding to the training mother liquor, including: Based on the second mass of several polymer solutions, the absorbance data, and the first mass of the polymer solution corresponding to the training mother liquor, a target prediction model for predicting the water content of the solution based on the absorbance data is established using regression analysis.
[0014] In some embodiments of this application, a target prediction model for predicting the water content of a solution based on absorbance data is established using regression analysis, including: A target prediction model for predicting solution water content based on absorbance data was established using multiple linear regression analysis.
[0015] The technical solutions provided by the embodiments of this application may include the following beneficial effects: Based on the second mass and absorbance data of several polymerization solutions, and the first mass of the corresponding training mother liquor, a target prediction model is established to predict the water content of the solution based on the absorbance data. The absorbance data of the test solution is detected within a preset wavenumber range. The water content of the test solution is obtained based on the absorbance data of the test solution and the target prediction model. This method solves the safety problem of ampoule use in Karl Fischer potentiometric titration, reduces reagent consumption, avoids the introduction of interfering components, reduces human error, simplifies operation, and improves detection efficiency and accuracy of water content detection. The molecular interactions between various components in the polymerization solution are very complex. The target preset model only models the water component, avoiding interference from other intermolecular interactions, thereby improving the prediction accuracy of the target preset model.
[0016] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description
[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0018] Figure 1 This is a flowchart illustrating a method for detecting the water content of a polymerization solution according to an exemplary embodiment; Figure 2 This is a flowchart illustrating the dehydration treatment of a base mother liquor according to an exemplary embodiment; Figure 3 This is a partial flow diagram illustrating the dehydration treatment of a base mother liquor according to an exemplary embodiment; Figure 4 This is another flowchart illustrating a method for detecting the water content of a polymerization solution according to an exemplary embodiment; Figure 5 This is a schematic diagram of a partial structure of a near-infrared spectrometer according to an exemplary embodiment.
[0019] Figure label: 1-Light source; 2-Aperture; 31-Beam splitter; 32-Moving mirror; 33-Fixed mirror; 41 - First laser; 42 - Second laser; 5-detector; 6-Sample. Detailed Implementation
[0020] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.
[0021] Against the backdrop of the rapid development of the carbon fiber industry, the performance of carbon fiber products is constantly improving. However, the technology for detecting the moisture content of raw materials and intermediates during the production process is relatively lacking. Among the relevant technologies, Karl Fischer potentiometric titration is usually used to detect the moisture content of the solution. However, the operation process is complicated, the reagent consumption is large, the detection process introduces large errors, and it can introduce interfering components, resulting in inaccurate detection of the moisture content of the solution.
[0022] Based on this, an exemplary embodiment of this disclosure provides a method for detecting the water content of a polymer solution. Based on the second mass and absorbance data of several polymer solutions and the first mass of the corresponding training mother liquor, a target prediction model is established to predict the water content of the solution based on the absorbance data. The absorbance data of the test solution within a preset wavenumber range is detected. The water content of the test solution is obtained based on the absorbance data of the test solution and the target prediction model. This method solves the safety issues related to the use of ampoules in Karl Fischer potentiometric titration, reduces reagent consumption, avoids the introduction of interfering components, reduces human error, lowers operational difficulty, and improves detection efficiency and accuracy of water content detection. Furthermore, the molecular interactions between various components in a polymer solution are highly complex. The target preset model only models the water component, avoiding interference from other intermolecular interactions, thereby improving the prediction accuracy of the target preset model.
[0023] This disclosure provides a method for detecting the water content of a polymerization solution. (See reference...) Figure 1 The method for detecting the water content of the polymerization solution specifically includes the following steps: S100, prepare the basic mother liquor.
[0024] In this step, the base mother liquor can be a polyacrylonitrile solution. The polyacrylonitrile solution is used to prepare polyacrylonitrile precursor fibers, which are then further formed into carbon fibers. The water content of the polyacrylonitrile solution has a certain impact on the performance and stability of the finished carbon fiber product. When preparing the base mother liquor, the solution is thoroughly stirred to ensure that the polyacrylonitrile is completely and uniformly dissolved in the solvent, preventing clumping, and thus obtaining a base mother liquor with uniform composition and properties.
[0025] S200: Dehydrate the base mother liquor to obtain a dried mother liquor.
[0026] In this step, when dehydrating the base mother liquor, organic groups that generate absorption should not be introduced to avoid affecting the absorbance data of subsequent detection, ensuring the accuracy of the target prediction model, and improving the accuracy of the calculation of the water content of the test solution.
[0027] S300. Divide the dried mother liquor into several training mother liquors, record the mass of each training mother liquor and record it as the first mass.
[0028] In this step, the initial mass of each training stock solution is equal, or the initial mass of some training stock solutions is unequal.
[0029] S400. Add distilled water to each training mother liquor to obtain a polymerization solution, record the mass of each polymerization solution and record it as the second mass.
[0030] In this step, the water content of the polymerization solution is obtained based on the second mass of the polymerization solution and the first mass of the corresponding training mother liquor. Water content = ((second mass - first mass) / first mass) × 100%. At least some of the training mother liquor contains different amounts of distilled water.
[0031] S500. Place each polymerization solution into a preset transmission container, control each polymerization solution within a preset temperature range, and detect the absorbance data of each polymerization solution within a preset wavenumber range.
[0032] In this step, the preset transmission container can be a transmission glass tube. The transmission glass tube includes a section with an inner diameter of 5 mm for absorbance data detection. During absorbance data detection, the liquid volume of the polymerization solution inside the transmission glass tube is approximately 2 / 3 of the tube's volume, reducing the amount of polymerization solution used. Each test only requires adding approximately 2 / 3 of the transmission glass tube's volume of polymerization solution, significantly reducing raw material waste and waste disposal costs. During absorbance data detection, the outer wall of the transmission glass tube is kept clean and dry to avoid water on the outer wall causing deviations in the absorbance data. Near-infrared spectroscopy is used to detect the absorbance data of each polymerization solution within a preset wavenumber range, and the data is collected into an absorbance database. The preset wavenumber range is 4000 cm⁻¹. -1 -12800cm -1 The preset temperature range is 29.5℃-30.5℃.
[0033] S600. Based on the second mass and absorbance data of several polymerization solutions and the first mass of the corresponding training mother liquor, establish a target prediction model for predicting the water content of the solution based on the absorbance data.
[0034] In this step, the water content of the polymerization solution can be obtained based on the second mass of the polymerization solution and the first mass of the corresponding training mother liquor. Based on several sets of water content and absorbance data of the polymerization solution, a target prediction model can be established with absorbance data as the independent variable and water content as the dependent variable.
[0035] S700. Place the solution to be tested into a preset transmission container, control the solution to be tested within a preset temperature range, and detect the absorbance data of the solution to be tested within a preset wavenumber range. Based on the absorbance data of the solution to be tested and the target prediction model, obtain the water content of the solution to be tested.
[0036] In this step, the solution to be tested can be a polyacrylonitrile solution. When detecting absorbance data, the preset projection container, preset temperature range, and preset wavenumber range used for both the solution to be tested and the polymerization solution are identical. This avoids introducing variables that could cause the absorbance data of the solution to be tested to mismatch with the target prediction model, ensuring the accuracy of the calculated water content of the solution.
[0037] In this application, a target prediction model is established based on the second mass and absorbance data of several polymerization solutions and the first mass of the corresponding training mother liquor. This model predicts the water content of the solution based on the absorbance data. The absorbance data of the test solution is detected within a preset wavenumber range. The water content of the test solution is obtained based on the absorbance data and the target prediction model. This solves the safety problem of using ampoules in Karl Fischer potentiometric titration, reduces reagent consumption, avoids the introduction of interfering components, reduces human error, reduces operational difficulty, and improves detection efficiency and accuracy of water content detection. The molecular interactions between various components in the polymerization solution are very complex. The target preset model only models the water component, avoiding interference from other intermolecular interactions, thereby improving the prediction accuracy of the target preset model.
[0038] In one embodiment, reference Figure 2 The basic mother liquor is dehydrated to obtain a dried mother liquor, which includes: S210. The base mother liquor is pre-dehydrated using molecular sieves that have been dried and activated.
[0039] In this step, the molecular sieve undergoes drying and activation treatment to maximize its water absorption performance. The molecular sieve can be heated to a first drying temperature range for initial drying, achieving preliminary dehydration. It can then be heated to a second drying temperature range for activation, achieving deep dehydration. The minimum temperature value in the second drying temperature range is greater than the maximum temperature value in the first drying temperature range. The molecular sieve can be a 3A molecular sieve. The molecular sieve is added to the base mother liquor for water absorption treatment, and then the base mother liquor is filtered using a filtration device to remove the molecular sieve from the base mother liquor. This prevents the introduced molecular sieve from affecting the absorbance data of subsequent detections, ensuring the accuracy of the absorbance data and improving the accuracy of the target prediction model and the precision of the water content calculation of the test solution. The filtration device can be a Buchner funnel. Alternatively, molecular sieves can be used to create molecular sieve filter layers, allowing the base mother liquor to dehydrate as it passes through. Or, molecular sieves can be placed in a drying container, through which the base mother liquor flows for pre-dehydration.
[0040] S220. The pre-dehydrated mother liquor is passed through a drying tube filled with desiccant for deep dehydration to obtain dried mother liquor.
[0041] In this step, the pre-dehydrated base mother liquor is extracted by a drive pump and transported to a drying tube filled with desiccant, so that the base mother liquor is further dehydrated using the desiccant to obtain dried mother liquor. The drive pump can be a peristaltic pump.
[0042] In this embodiment, the absorbance data depends on the overtone and combination vibrations of hydrogen-containing groups (such as CH, OH, NH, etc.). After absorbing near-infrared light of a specific wavelength, the hydrogen-containing groups undergo energy level transitions, forming characteristic absorption peaks. The use of molecular sieves for pre-dehydration treatment avoids the introduction of organic groups that generate absorption, thus preventing any impact on the absorbance data, ensuring the accuracy of the target prediction model, and improving the precision of the water content calculation of the solution to be tested.
[0043] In one embodiment, reference Figure 3 The base mother liquor is pre-dehydrated using molecular sieves that have been dried and activated, including: S211. Add the dried and activated molecular sieve to the base mother liquor.
[0044] In this step, molecular sieves are added to the base mother liquor, where they absorb water. Sufficient molecular sieve should be added to the base mother liquor to avoid ineffective pre-dehydration.
[0045] S212. Let the basic mother liquor containing the molecular sieve stand for the first preset time.
[0046] In this step, the first preset time can be 30 minutes. Allowing the basic mother liquor added to the molecular sieve to stand for the first preset time allows the molecular sieve to fully absorb water, which can improve the pre-dehydration effect.
[0047] S213. The base mother liquor is filtered using a filtration device equipped with an organic filter membrane to obtain a base mother liquor that has undergone pre-dehydration treatment.
[0048] In this step, after adding molecular sieves to the basic mother liquor, the mother liquor contains molecular sieves, which can be filtered out using a filtration device. An organic filter membrane is installed on the filtration device to filter the basic mother liquor, removing dust and broken particles introduced by the molecular sieves, thus improving the filtration accuracy. The filtration device can be a Buchner funnel. The organic filter membrane can be attached to the top surface of the Buchner funnel's filter screen, allowing the filter screen and organic filter membrane to filter the basic mother liquor as it passes through, effectively removing dust and broken particles introduced by the molecular sieves, improving the filtration accuracy, and preventing molecular sieve contamination of the Buchner funnel.
[0049] In one embodiment, the desiccant inside the drying tube is anhydrous magnesium sulfate. Absorbance data depends on the overtone and combination vibrations of hydrogen-containing groups (such as CH, OH, NH, etc.). After absorbing near-infrared light of a specific wavelength, these hydrogen-containing groups undergo energy level transitions, forming characteristic absorption peaks. Using anhydrous magnesium sulfate as a desiccant avoids introducing organic groups that generate absorption, thus preventing interference with absorbance data, ensuring the accuracy of the target prediction model, and improving the precision of calculating the water content of the solution being tested.
[0050] In one embodiment, reference Figure 4 The dried mother liquor was divided into several portions of training mother liquor, including: Divide the dried mother liquor into several portions of training mother liquor.
[0051] Setting each training stock solution to be identical eliminates the need to label the initial mass of each training stock solution. Instead, a single initial mass is set and recorded for each batch of training stock solutions. By directly controlling the amount of distilled water added to each training stock solution, gradient samples with different water contents can be formed, effectively reducing calculation steps and operational procedures.
[0052] In one embodiment, reference Figure 4 Distilled water was added to each training mother liquor to obtain a polymerization solution, including: Different masses of distilled water were added to each training mother liquor to obtain polymerization solutions.
[0053] By adding different masses of distilled water to each training mother solution to obtain a polymerization solution, the water content of each training mother solution varies, thus enabling the acquisition of training samples with a wider water content coverage.
[0054] In one embodiment, reference Figure 4 The polymerization solutions are controlled within a preset temperature range, and the absorbance data of each polymerization solution is measured within a preset wavenumber range, including: Near-infrared spectroscopy was used to control each polymerization solution within a preset temperature range, and the absorbance data of each polymerization solution within a preset wavenumber range was detected using near-infrared spectroscopy.
[0055] In this embodiment, a near-infrared spectrometer is used to control each polymerization solution within a preset temperature range. This allows the absorbance detection and temperature control functions of the polymerization solution to be integrated into the same device, avoiding repeated transfer of samples between the temperature control device and the spectrometer and frequent disassembly of the preset transmission container. This reduces operation time and improves experimental efficiency.
[0056] In one embodiment, after the polymerization solution is placed into a preset transmission container, a cap is used to seal the polymerization solution inside the preset transmission container to prevent the solution from evaporating.
[0057] In one embodiment, controlling each polymerization solution within a preset temperature range using a near-infrared spectroscopy includes: The temperature of each preset transmission container containing the polymerization solution is detected in real time using the temperature detection module of a near-infrared spectrometer and recorded as the first detection temperature. When the first detection temperature is lower than the minimum value of the preset temperature range, the controller of the near-infrared spectrometer controls the heating device to heat the preset transmission container so that the temperature of the preset transmission container is within the preset temperature range. When the first detection temperature is higher than the maximum value of the preset temperature range, the controller of the near-infrared spectrometer controls the cooling device to cool the preset transmission container so that the temperature of the preset transmission container is within the preset temperature range.
[0058] refer to Figure 5 The near-infrared spectrometer includes a sample chamber. The sample chamber is used to hold sample 6. Both the preset transmission container containing the polymerization solution and the preset transmission container containing the solution to be tested are samples 6. The near-infrared spectrometer includes a temperature detection module, a controller, a heating device, and a cooling device.
[0059] The temperature detection module is used to detect the temperature of a preset transmission container placed on the sample chamber, in order to obtain the temperature of the polymerization solution inside the preset transmission container. The temperature detection module is electrically connected to the controller.
[0060] The temperature detection module converts temperature signals into electrical signals. The controller receives the electrical signals output by the temperature detection module. The controller converts the received electrical signals into a first detected temperature. The controller compares the first detected temperature with a preset temperature range. Based on the comparison result, the controller determines the output signal according to a PID control algorithm (Proportional-Integral-Derivative Control Algorithm). When the first detected temperature is lower than the minimum value of the preset temperature range, the controller sends a signal to start the heating device. When the first detected temperature is higher than the maximum value of the preset temperature range, the controller sends a signal to start the cooling device. Both the heating and cooling devices operate according to the signals sent by the controller, heating or cooling the preset transmission container to keep its temperature within the preset temperature range. The temperature detection module monitors temperature changes in real time. The controller receives signals from the temperature detection module and continuously adjusts the heating intensity of the heating device or the cooling intensity of the cooling device until the temperature of the preset transmission container is within the preset temperature range.
[0061] In one embodiment, reference Figure 5The near-infrared spectrometer includes a spectral detection module. The spectral detection module includes a light source 1. Light source 1 emits near-infrared light with a wavelength range of 780nm-2500nm, providing the necessary light for the measurement process.
[0062] The spectral detection module includes an interferometer. The spectral detection module includes an aperture 2, which is used to control the size and shape of the light beam entering the interferometer.
[0063] refer to Figure 5 The interferometer includes a beam splitter 31, a moving mirror 32, and a fixed mirror 33. The fixed mirror 33 is stationary. The moving mirror 32 moves within a certain range. The moving and stationary mirrors have a travel distance of 2X, that is, they move between -X and X. The beam splitter 31 splits the light passing through the aperture 2 into two beams. One beam is directed to the moving mirror 32, and the other is directed to the fixed mirror 33. The two beams are reflected by the moving mirror 32 and the fixed mirror 33 respectively, and then merge to form interference light.
[0064] refer to Figure 5 The spectral detection module includes a first laser 41. The first laser 41 is used to detect the displacement of the moving mirror 32. The first laser 41 can be a helium-neon laser. The spectral detection module also includes a second laser 42. The second laser 42 is used to monitor the position of the fixed mirror 33.
[0065] The spectral detection module includes an attenuation wheel. The attenuation wheel filters and attenuates the light emanating from the interferometer. By changing the position and angle of the attenuation wheel, the light intensity can be controlled to adapt to the measurement requirements of different samples 6. The interferometric light, after passing through the attenuation wheel, illuminates sample 6.
[0066] refer to Figure 5 The spectral detection module includes detector 5. Detector 5 is used to receive interference light passing through sample 6 and convert the interference light signal into an electrical signal.
[0067] The spectral detection module includes a data processing unit. The data processing unit acquires the electrical signal generated by detector 5. The data processing unit has built-in software. It performs a Fourier transform algorithm on the electrical signal from detector 5, converting it into a near-infrared spectrum. Processing the near-infrared spectrum yields absorbance data within a preset wavenumber range.
[0068] In one embodiment, based on the second mass and absorbance data of several polymerization solutions and the first mass of the corresponding training mother liquor, a target prediction model for predicting the water content of the solution based on absorbance data is established, including: Based on the second mass and absorbance data of several polymerization solutions, as well as the first mass of the corresponding training mother liquor, a target prediction model for predicting the water content of the solution is established using regression analysis.
[0069] Specifically, based on the second mass and absorbance data of several polymerization solutions and the first mass of the corresponding training mother liquor, a target prediction model for predicting the water content of the solution based on absorbance data is established using regression analysis. Then, based on the absorbance data of the solution to be tested and the target prediction model, the water content of the solution to be tested is calculated.
[0070] In one embodiment, a target prediction model for predicting solution water content based on absorbance data is established using regression analysis, including: S610. Establish a target prediction model for predicting the water content of a solution based on absorbance data using multiple linear regression analysis.
[0071] In this process, based on the second mass and absorbance data of several polymerization solutions and the first mass of the corresponding training mother liquor, a target prediction model for predicting the water content of the solution based on the absorbance data is established using multiple linear regression analysis. Then, based on the absorbance data of the solution to be tested and the target prediction model, the water content of the solution to be tested is calculated.
[0072] The indicators for evaluating the effectiveness of the target prediction model include the coefficient of determination (COD) and the root mean square error (RMSE). The COD represents the proportion of the total variation in the dependent variable that can be explained by the independent variable through the regression model. The COD is usually denoted as R². R² = 1 - SSE / SST. SSE is the sum of squares of the differences between the actual water content of the solution and the predicted value from the initial prediction model. SST is the sum of squares of the differences between the actual water content of the solution and the average of the actual values. The closer the COD is to 1, the stronger the explanatory power of the initial prediction model. The RMSE is usually denoted as Root Mean Square Error (RMSE). The smaller the RMSE, the higher the prediction accuracy of the initial prediction model. Cross-validation can be used to calculate the COD and RMSE. When the COD is greater than 0.999 and the RMSE is less than 0.5%-1%, the initial prediction model shows better detection performance.
[0073] The specific process of establishing a target prediction model is as follows: (1) Sample determination and absorbance data measurement Select m portions of polymerization solution, with at least two portions having different water contents. The water contents of the m portions of polymerization solution are y1 to y2. m For example, select m equal amounts of training mother liquor, add different amounts of water to each training mother liquor, and obtain m polymer solutions with different water contents.
[0074] Absorbance data were measured for each polymerization solution, and absorbance values were selected at n different wavenumbers. The absorbance values of the first polymerization solution at n different wavenumbers are a. 11 to a 1nThe absorbance values of the m-th polymerization solution at n different wavenumbers are respectively a m1 to a mn The same wavenumber was selected for each polymerization solution.
[0075] (2) Determination of regression analysis method A target prediction model is established using multiple linear regression analysis. The formula for multiple linear regression analysis is: Y = Xβ + ε.
[0076] Y is the water content vector of m parts of the polymerization solution. Y = [y1, y2, ..., y...] m ] T .
[0077] X is a matrix of absorbance values of m parts of the polymerization solution at n different wavenumbers. , In the X matrix, the first column is all 1s, the (j+1)th column is the absorbance value of all samples at the j-th wavenumber, and the absorbance values of each polymer solution are in the same row.
[0078] β is the regression coefficient vector, β = [β0, β1, β2, ..., β] n ] T .
[0079] ε is the error vector, ε=[ε1, ε2, ..., ε m ] T .
[0080] During the calculation, all values in ε are set to zero, resulting in β=(X T X) 1 X T Y, the target model is y = [1, a1, a2, ..., a2]. n ]β, the absorbance values of the test solution at n different wavenumbers are a1 to a n The wavenumber selected for the test solution is the same as the wavenumber selected for the polymerization solution when constructing the target model, and y is the water content of the test solution.
[0081] For example, Four polymerization solutions were selected, and the four polymerization solutions had different water contents. The water contents of the four polymerization solutions were y1, y3 and y4, respectively.
[0082] Absorbance data were measured for each polymerization solution, and absorbance values were selected at three different wavenumbers. The absorbance values of the first polymerization solution at the three different wavenumbers were a... 11 a 12 and a 13The absorbance values of the second polymerization solution at three different wavenumbers were a 21 a 22 and a 23 The absorbance values of the third polymerization solution at three different wavenumbers were a 31 a 32 and a 33 .
[0083] Y = [y1, y2, y3, y4] T , , β is the regression coefficient vector, β = [β0, β1, β2, β3] T .
[0084] ε is the error vector, ε=[0,0,0,0] T .
[0085] We get β=(X) T X) 1 X T Y, the target model is y = [1, a1, a2, a3]β, the absorbance values of the test solution at 3 different wavenumbers are a1 to a3 respectively, the wavenumber selected for the test solution is the same as the wavenumber selected for the polymerization solution when constructing the target model, and y is the water content of the test solution.
[0086] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.
[0087] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.
Claims
1. A method for detecting the water content of a polymerization solution, characterized in that, The method for detecting the water content of the polymerization solution includes: Prepare the base stock solution; The basic mother liquor is dehydrated to obtain dried mother liquor; The dried mother liquor is divided into several training mother liquors, and the mass of each training mother liquor is recorded and recorded as the first mass. Distilled water was added to each of the training mother liquors to obtain a polymerization solution, and the mass of each polymerization solution was recorded and denoted as the second mass. Each of the polymer solutions is placed in a preset transmission container, each of the polymer solutions is controlled within a preset temperature range, and the absorbance data of each of the polymer solutions is detected within a preset wavenumber range. Based on the second mass of several polymer solutions, the absorbance data, and the first mass of the polymer solution corresponding to the training mother liquor, a target prediction model is established to predict the water content of the solution based on the absorbance data. The solution to be tested is placed in the preset transmission container, the solution to be tested is controlled within the preset temperature range, and the absorbance data of the solution to be tested is detected within the preset wavenumber range. The water content of the solution to be tested is obtained based on the absorbance data of the solution to be tested and the target prediction model.
2. The method for detecting the water content of a polymerization solution according to claim 1, characterized in that, The basic mother liquor is dehydrated to obtain a dried mother liquor, comprising: The base mother liquor was pre-dehydrated using a molecular sieve that had been dried and activated; The pre-dehydrated base mother liquor is passed through a drying tube filled with a desiccant for deep dehydration to obtain a dried mother liquor.
3. The method for detecting the water content of the polymerization solution according to claim 2, characterized in that, The base mother liquor is pre-dehydrated using a dried and activated molecular sieve, including: The dried and activated molecular sieves are added to the base mother liquor; The basic mother liquor added to the molecular sieve is allowed to stand for a first preset time; The base mother liquor is filtered using a filtration device equipped with an organic filter membrane to obtain the base mother liquor after pre-dehydration treatment.
4. The method for detecting the water content of the polymerization solution according to claim 2, characterized in that, The desiccant inside the drying tube is anhydrous magnesium sulfate.
5. The method for detecting the water content of a polymerization solution according to claim 1, characterized in that, The dried mother liquor is divided into several portions of training mother liquor, including: The dried mother liquor was divided into several equal portions of training mother liquor.
6. The method for detecting the water content of a polymerization solution according to claim 5, characterized in that, Adding distilled water to each of the aforementioned training mother liquors yields a polymerization solution, comprising: Different masses of distilled water were added to each of the training mother liquors to obtain polymerization solutions.
7. The method for detecting the water content of a polymerization solution according to claim 1, characterized in that, Controlling each of the polymerization solutions within a preset temperature range and detecting the absorbance data of each polymerization solution within a preset wavenumber range includes: The near-infrared spectrometer is used to control each of the polymerization solutions within a preset temperature range, and the near-infrared spectrometer is used to detect the absorbance data of each of the polymerization solutions within a preset wavenumber range.
8. The method for detecting the water content of a polymerization solution according to claim 7, characterized in that, Controlling each polymerization solution within a preset temperature range using a near-infrared spectroscopy includes: The temperature of each preset transmission container containing the polymerization solution is detected in real time using the temperature detection module of a near-infrared spectrometer and recorded as the first detection temperature. When the first detected temperature is lower than the minimum value of the preset temperature range, the controller of the near-infrared spectrometer controls the heating device to heat the preset transmission container so that the temperature of the preset transmission container is within the preset temperature range. When the first detected temperature is higher than the maximum value of the preset temperature range, the controller of the near-infrared spectrometer controls the cooling device to cool the preset transmission container so that the temperature of the preset transmission container is within the preset temperature range.
9. The method for detecting the water content of a polymerization solution according to claim 1, characterized in that, Based on the second mass of several polymer solutions, the absorbance data, and the first mass of the polymer solution corresponding to the training mother liquor, a target prediction model for predicting the water content of the solution based on the absorbance data is established, including: Based on the second mass of several polymer solutions, the absorbance data, and the first mass of the polymer solution corresponding to the training mother liquor, a target prediction model for predicting the water content of the solution based on the absorbance data is established using regression analysis.
10. The method for detecting the water content of a polymerization solution according to claim 9, characterized in that, A target prediction model for predicting solution water content based on absorbance data was established using regression analysis, including: A target prediction model for predicting solution water content based on absorbance data was established using multiple linear regression analysis.