Double-alkali dynamic collaborative analysis method, device, equipment and medium in chlor-alkali industry

Abstract

The invention relates to a double-alkali dynamic collaborative analysis method, device, equipment and medium in the chlor-alkali industry, and belongs to the field of titration reaction. The method comprises the steps that a sample is pretreated, titration volumes are obtained through dynamic temperature titration, the titration volumes comprise a first end point titration volume and a second end point titration volume, and the pretreatment executes a carbon dioxide removal kinetics protocol; pH parameters and conductivity signals are synchronously collected in the titration process, a multi-modal fusion model is constructed, the dual-alkali concentration is obtained through the multi-modal fusion model based on the titration volume, and the dual-alkali concentration comprises the sodium hydroxide concentration and the sodium carbonate concentration; and recording a potential attenuation curve after a titration end point, obtaining an organic amine interference compensation factor based on the potential attenuation curve by using an organic amine interference compensation model, and automatically compensating the dual-alkali concentration through the organic amine interference compensation factor. According to the invention, electrochemical degassing, dynamic temperature titration, multi-mode sensing, neural network compensation and other means are fused, and dual-alkali dynamic collaborative analysis is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of titration reaction, and in particular relates to a double-alkali dynamic collaborative analysis method, device, equipment and medium in the chlor-alkali industry. Background Art

[0002] The chlor-alkali industry produces sodium hydroxide, chlorine, and hydrogen through the electrolysis of saturated brine, a core process in basic chemical engineering. Real-time and accurate monitoring of alkali concentration is directly related to chlor-alkali production. First, excessive free alkali during the production of sodium hypochlorite can cause highly toxic chlorine to overflow, while insufficient free alkali concentration leads to product decomposition, directly impacting production and personnel safety. Second, ion-exchange membrane electrolyzers must maintain a constant alkali concentration. Concentration fluctuations increase energy consumption and waste resources. Finally, sodium carbonate accumulation can clog pipelines, and insufficient sodium hydroxide purity reduces the qualified rate of downstream products, leading to reduced product quality. In summary, real-time dual-alkali analysis is essential in the chlor-alkali industry.

[0003] Existing dual-alkali (NaOH / Na2CO3) concentration monitoring technologies primarily include offline acid-base titration, online analytical instruments, and spectroscopy. These methods suffer from numerous limitations, including: high-ionic-strength solutions (such as concentrated alkali) weakening the pH jump, leading to endpoint errors; reactions between organic amines and hydrogen ions leading to premature endpoint detection; high equipment costs; and the dissolution of CO2 in the air to form carbonates, which obscure the initial endpoint and cause endpoint deviation. A dynamic, collaborative dual-alkali analysis method suitable for the chlor-alkali industry that overcomes these limitations is urgently needed. Summary of the Invention

[0004] In order to solve the above problems existing in the prior art, the present invention provides a dual-alkali dynamic collaborative analysis method, device, equipment and medium for the chlor-alkali industry.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A dual-alkali dynamic collaborative analysis method for the chlor-alkali industry, wherein the implementation of the dual-alkali dynamic collaborative analysis method for the chlor-alkali industry comprises the following steps: S1: Pre-treating the sample to obtain a titration volume by dynamic temperature titration, wherein the titration volume includes a first endpoint titration volume and a second endpoint titration volume, and the pre-treatment performs a carbon dioxide removal kinetic protocol; S2: During the titration process, pH parameters and conductivity signals are synchronously collected and a multimodal fusion model is constructed. Based on the titration volume, a dual alkali concentration is obtained through the multimodal fusion model, where the dual alkali concentration includes a sodium hydroxide concentration and a sodium carbonate concentration. S3: After the titration endpoint, a potential decay curve is recorded, and an organic amine interference compensation factor is obtained based on the potential decay curve using an organic amine interference compensation model, and the double base concentration is automatically compensated by the organic amine interference compensation factor.

[0006] Preferably, the pre-processing method in step S1 is: The sample is automatically injected, the carbon dioxide removal time is determined according to the carbon dioxide removal kinetic protocol, and the sample is stirred under the coordinated control of temperature and electric field. After the stirring is completed, the sample is allowed to stand.

[0007] Preferably, the carbon dioxide removal kinetic protocol in step S1 is specifically: Obtain liquid phase carbon dioxide concentration, absolute temperature, and applied current; Calibrate thermal desorption rate constant, electromigration rate constant, and carbon dioxide desorption activation energy; The carbon dioxide removal time is obtained by the carbon dioxide removal kinetic equation, and the mathematical description of the carbon dioxide removal kinetic equation is: , where [CO2] is the concentration of liquid carbon dioxide, t is the time for carbon dioxide removal, K T is the thermal desorption rate constant, E a is the activation energy of carbon dioxide desorption, R is the gas constant, T is the absolute temperature, S is the gas-liquid contact area, V is the sample volume, K E is the electromigration rate constant, I app To apply current.

[0008] Preferably, the step S2 specifically includes: S201: synchronously collecting the pH parameter and the conductivity signal and performing feature extraction to obtain a pH jump slope and a conductivity curvature, wherein the pH jump slope includes a first endpoint pH jump slope and a second endpoint pH jump slope; S202: Calibrate the coefficient matrix and obtain the concentration feature vector based on the titration volume, the pH jump slope and the conductivity curvature, and construct the multimodal fusion model based on the coefficient matrix and the concentration feature vector, which is mathematically described as ,in, is the concentration feature matrix, C NaOH is the concentration of sodium hydroxide, is the concentration of sodium carbonate, C d is the titrant concentration, V ref is the reference volume, V is the sample volume, M is the molecular weight matrix, K is the coefficient matrix, and F is the concentration feature matrix.

[0009] Preferably, the concentration feature vector in step S202 is obtained as follows: The total thermal power during the titration process is obtained, and the concentration characteristic vector is obtained according to the titration volume, the pH jump slope, the total thermal power and the conductivity curvature, which is mathematically described as follows: , where V1 is the first endpoint titration volume, V2 is the second endpoint titration volume, and E p1 is the pH jump slope of the first endpoint, E p2 is the pH jump slope of the second endpoint, w c is the conductivity curvature, G0 is the initial conductivity, Q t is the total thermal power during the titration process, is the reference reaction enthalpy, C d is the titrant concentration, and V is the sample volume.

[0010] Preferably, the calibration of the coefficient matrix in step S202 is specifically as follows: Prepare N groups of standard samples, wherein the standard samples include a standard sodium hydroxide sample and a standard sodium carbonate sample, and a preset concentration gradient, wherein the concentrations of the standard samples increase gradually according to the concentration gradient; Each group of standard samples is titrated separately, and the concentration characteristic vector of each group of standard samples is synchronously collected during the titration process, and the coefficient matrix is ​​calibrated based on the concentration characteristic vector.

[0011] Preferably, the step S3 specifically includes: After titrating to the second endpoint, the electrode potential is continuously recorded according to the preset sampling frequency and sampling time to obtain the potential decay curve; Extracting the decay characteristics of the potential decay curve, wherein the decay characteristics include a decay time constant, an integral area, and a maximum recovery slope; Pre-training the organic amine interference compensation model, inputting the attenuation feature into the trained organic amine interference compensation model, and outputting the organic amine interference compensation factor, wherein the organic amine interference compensation factor includes a sodium hydroxide interference compensation factor and a sodium carbonate interference compensation factor; The double base concentration is compensated by the organic amine interference compensation factor.

[0012] A dual-alkali dynamic collaborative analysis device for the chlor-alkali industry, used to perform the dual-alkali dynamic collaborative analysis method for the chlor-alkali industry described above, comprising a dynamic temperature titration module, a dual-alkali concentration acquisition module, and an organic amine compensation module; The dynamic temperature titration module includes pre-treating the sample to obtain a titration volume by dynamic temperature titration, wherein the titration volume includes a first endpoint titration volume and a second endpoint titration volume, and the pre-treating performs a carbon dioxide removal kinetic protocol; The dual-alkali concentration acquisition module includes synchronously collecting pH parameters and conductivity signals during the titration process and constructing a multimodal fusion model, and obtaining the dual-alkali concentration based on the titration volume through the multimodal fusion model, wherein the dual-alkali concentration includes the sodium hydroxide concentration and the sodium carbonate concentration; The organic amine compensation module includes recording a potential decay curve after the titration endpoint, obtaining an organic amine interference compensation factor based on the potential decay curve using an organic amine interference compensation model, and automatically compensating the dual base concentration using the organic amine interference compensation factor.

[0013] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the dual-alkali dynamic collaborative analysis method for the chlor-alkali industry described above is implemented.

[0014] A storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the above-mentioned dual-alkali dynamic collaborative analysis method for the chlor-alkali industry.

[0015] The beneficial effects of the present invention are: (1) The carbon dioxide removal time is determined by the carbon dioxide removal kinetics protocol, the solubility of carbon dioxide is reduced by heating and stirring, and its escape from the liquid phase is accelerated. By applying a positive voltage, hydrogen ions migrate to the cathode, significantly reducing the influence of carbon dioxide on the identification of the titration endpoint; (2) Constructing concentration feature vectors by synchronously utilizing pH jump slope, conductivity curvature, and thermal power to resist interference from high ionic strength; (3) The organic amine interference compensation factor is obtained through the potential decay curve and the double base concentration is automatically compensated to get rid of the interference of organic amine on endpoint identification and further improve the accuracy of double base concentration analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0017] Figure 1 The present invention is a flowchart of the steps of a dual-alkali dynamic collaborative analysis method for the chlor-alkali industry. DETAILED DESCRIPTION

[0018] In order to better understand the present invention, various aspects of the present invention will be described in more detail with reference to the accompanying drawings. It should be understood that these detailed descriptions are only descriptions of exemplary embodiments of the present invention and are not intended to limit the scope of the present invention in any way. Throughout the specification, the expression "and / or" includes any and all combinations of one or more of the associated listed items. As used herein, the terms "roughly", "approximately" and similar terms are used as terms to indicate approximate values, rather than as terms to indicate degree, and are intended to illustrate inherent deviations in measurements or calculated values ​​that will be recognized by those of ordinary skill in the art. In addition, in the present invention, the order in which the steps are described does not necessarily represent the order in which these processes occur in actual operation, unless otherwise specified or can be derived from the context.

[0019] It should also be understood that expressions such as "comprises," "including," "having," "includes," and / or "comprising" are open rather than closed expressions in this specification, indicating the presence of the stated features, elements, and / or components, but do not exclude the presence of one or more other features, elements, components, and / or combinations thereof. In addition, when expressions such as "at least one of..." appear after a list of listed features, they modify the entire list of features rather than just the individual elements in the list. In addition, when describing embodiments of the present invention, "may" is used to mean "one or more embodiments of the present invention." And, the term "exemplary" is intended to refer to an example or illustration.

[0020] Unless otherwise defined, all terms used herein (including engineering and scientific terms) have the same meaning as commonly understood by those skilled in the art to which this invention pertains. It should also be understood that, unless otherwise expressly stated herein, words defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art, and should not be interpreted in an idealized or overly formal sense.

[0021] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0022] Example 1: See also Figure 1 , a dual-alkali dynamic collaborative analysis method for the chlor-alkali industry, comprising: S1: Pre-treating the sample and obtaining a titration volume by dynamic temperature titration, wherein the titration volume includes a first endpoint titration volume and a second endpoint titration volume, and the pre-treatment performs a CO2 removal kinetic protocol; S2: During the titration process, pH parameters and conductivity signals are synchronously collected and a multimodal fusion model is constructed. Based on the titration volume, the multimodal fusion model is used to obtain the dual-alkali concentration, which includes the sodium hydroxide concentration and the sodium carbonate concentration. Traditional methods rely solely on the titration volume to calculate the dual-alkali concentration and cannot handle the nonlinear effect under high ionic strength. Therefore, the pH parameters and conductivity signals are synchronously collected during the titration process to construct a multimodal fusion model to obtain the dual-alkali concentration. S3: Organic amines (such as methylamine) that may exist in the sample will react with hydrogen ions, causing the titration endpoint to be advanced and resulting in a positive deviation. Therefore, the potential decay curve is recorded after the titration endpoint, and the pre-trained organic amine interference compensation model is used to obtain the organic amine interference compensation factor and automatically compensate for the double base concentration.

[0023] In this embodiment, the pre-processing process in step S1 is specifically as follows: Automatic sampling was performed, and the CO2 removal time was determined according to the CO2 removal kinetic protocol. The sample was stirred (stirring time was the CO2 removal time) under the coordinated regulation of temperature and electric field (temperature condition was 40-50°C, electric field condition was 200mV polarization voltage) to drive out carbon dioxide. After stirring, the sample was allowed to stand for bubbles to float.

[0024] In this embodiment, the principle of the CO2 removal kinetics protocol in step S1 is: reduce the solubility of CO2 by increasing the temperature to accelerate its escape from the liquid phase, and apply a positive voltage to make H ＋ Migrate to the cathode to promote the reaction Move to the left. The CO2 removal kinetics protocol specifically includes: obtaining the liquid phase CO2 concentration (which can be directly measured by installing an infrared CO2 sensor in the sample cell bypass), absolute temperature, and applied current; calibrating the thermal desorption rate constant, electromigration rate constant, and CO2 desorption activation energy (i.e., the sum of the chemical adsorption heat and the adsorption activation energy); and obtaining the CO2 removal time using the CO2 removal kinetics equation, which is mathematically described as: , where [CO2] is the liquid phase CO2 concentration (mol / m 3 ), t is the CO2 removal time (s), K T is the thermal desorption rate constant (m / s), E a is the activation energy of CO2 desorption (J / mol), R is the gas constant, which is 8.314 J / (mol·K), T is the absolute temperature (K), and S is the gas-liquid contact area (m 2 ), V is the sample volume (m 3 ), K E is the electromigration rate constant (mol / C), I appis the applied current (A). The calibration process of the electromigration rate constant is as follows: fix the temperature and turn off the stirring (to avoid bubble interference); apply a gradient current and measure the CO2 decrease rate under different currents; fit the CO2 decrease rate and current to obtain r=a+K E I app , r is the CO2 decline rate, K E is the electromigration rate constant, I app is the current, and a is a constant.

[0025] In this embodiment, the titration volume is obtained in step S1 as follows: Traditional titration is performed at a constant temperature, but the solubility of carbon dioxide in the sample varies with temperature. Even if most of the carbon dioxide has been removed by pretreatment in the early stage, it will still lead to endpoint recognition errors. Therefore, the temperature is dynamically changed during the titration process, and the effect of temperature on carbon dioxide solubility and reaction kinetics is utilized to optimize endpoint recognition. Specifically, it is divided into three stages: Initial stage: The titration temperature is set to 40 degrees Celsius. At this temperature, the solubility of CO2 is low, which can reduce the interference of CO2 on the first endpoint (pH 8.3); First endpoint stage: When the pH is close to 8.3 (e.g. pH 9.0 to 8.0), the temperature is reduced to 25°C. At low temperatures, the pH electrode response is more stable and the endpoint jump is more obvious. Second endpoint stage: During the titration to pH 4.3, maintain 25°C to ensure endpoint accuracy.

[0026] In this embodiment, the acquisition of the double alkali concentration can be specifically implemented by the following steps: S201: synchronously collecting the pH parameter and the conductivity signal and performing feature extraction to obtain a pH jump slope and a conductivity curvature, wherein the pH jump slope includes a first endpoint pH jump slope and a second endpoint pH jump slope, which are respectively calculated as the derivative of the pH parameter with respect to the sample volume near the first endpoint (pH 8.3) and the second endpoint (pH 4.3), and the conductivity curvature is the second-order derivative of the conductivity calculated near the lowest conductivity point, which can reflect the interaction between ions; S202: Calibrate the coefficient matrix and obtain the concentration feature vector based on the titration volume, the pH jump slope and the conductivity curvature, and construct the multimodal fusion model based on the coefficient matrix and the concentration feature vector, which is mathematically described as ,in, is the concentration characteristic matrix (g / L), C NaOH is the concentration of sodium hydroxide, is the concentration of sodium carbonate, C d is the titrant concentration (mol / L), V refis the reference volume, generally 1 mL, V is the sample volume (L), M is the molecular weight matrix (g / mol), , K is the coefficient matrix, F is the concentration feature matrix, the multimodal fusion model introduces the pH jump slope ratio to characterize the difference in buffering capacity between hydroxide and bicarbonate, and this ratio is sensitive to NaOH concentration; the conductivity curvature is introduced to correct the Na under high ionic strength. ＋ Changes in mobility, a parameter that is sensitive to Na2CO3 concentration.

[0027] In this embodiment, the concentration feature vector is obtained in step S202 as follows: The total thermal power during the titration process is obtained, and the concentration characteristic vector is obtained according to the titration volume, the pH jump slope, the total thermal power and the conductivity curvature, which is mathematically described as follows: , where V1 is the first endpoint titration volume (ml), V2 is the second endpoint titration volume (ml), and E p1 is the pH jump slope of the first endpoint, E p2 is the pH jump slope of the second endpoint, w c is the conductivity curvature (μS / cm 1 mL 2 ), G0 is the initial conductivity (μS / cm), Q t is the total thermal power during the titration process (J), is the reference reaction enthalpy (kJ / mol), C d is the titrant concentration (mol / L), and V is the sample volume (L).

[0028] In this embodiment, the calibration of the coefficient matrix in step S202 is specifically as follows: Prepare N groups of standard samples, including standard sodium hydroxide samples and standard sodium carbonate samples, with a preset concentration gradient. The concentrations of the standard samples increase according to the concentration gradient, as shown in Table 1: Table 1:

[0029] Each set of standard samples is titrated separately. The concentration characteristic vector of each set of standard samples is collected synchronously during the titration process. The coefficient matrix is ​​calibrated based on the concentration characteristic vector. The calibration equation is: , where K is the coefficient matrix (dimension is 2×4), V is the sample volume (L), and C d is the titrant concentration (mol / L), M is the molecular weight matrix (g / mol), , V ref is the reference volume vector, , C is the standard sample concentration feature matrix (dimension is 2×1, the same as the above concentration feature matrix), F is the concentration feature vector, is element-wise division, is element-wise multiplication.

[0030] In this embodiment, the automatic compensation of the dual-alkali concentration can be implemented by the following steps: S301: After titrating to the second endpoint (pH 4.3), the electrode potential is continuously recorded according to the preset sampling frequency and sampling time to obtain a potential decay curve; S302: extracting attenuation characteristics of the potential attenuation curve, wherein the attenuation characteristics include a decay time constant, an integral area, and a maximum recovery slope; S303: pre-training the organic amine interference compensation model, inputting the attenuation feature into the trained organic amine interference compensation model, and outputting the organic amine interference compensation factor, wherein the organic amine interference compensation factor includes a sodium hydroxide interference compensation factor and a sodium carbonate interference compensation factor; S304: Compensating the double base concentration by the organic amine interference compensation factor, mathematically described as , where C NaOH-J is the concentration of sodium hydroxide after compensation, is the concentration of sodium carbonate after compensation, is the sodium hydroxide interference compensation factor, is the sodium carbonate interference compensation factor.

[0031] In this embodiment, the pre-training process of the organic amine interference compensation model in step S303 is: S303-1: Prepare M groups of mixed solutions of sodium hydroxide, sodium carbonate, and trimethylamine according to the preset concentration gradient, and divide them into training and test sets at an 8:2 ratio; S303-2: Perform double-base titration to the second endpoint (pH 4.3), then continuously record the electrode potential according to the preset sampling frequency and sampling time to obtain the potential decay curve; S303-3: Extract the decay characteristics of the potential decay curve. The decay time constant is used to fit the decay segment data. , where E(t) is the electrode potential at time t, E0 is the initial potential (i.e. the potential at the moment after titration to the second endpoint), is the steady-state potential (the potential at the end of recording the electrode potential), is the decay time constant; the integral area is , where A is the integral area; the maximum recovery slope is , where S max is the maximum recovery slope, E i+1is the electrode potential of the i+1th sampling point, E i is the electrode potential of the i-th sampling point, is the sampling time interval; S303-4: Z-score normalizes the attenuation feature and constructs a 3-layer fully connected neural network (3 nodes in the input layer, 8 nodes in the hidden layer, and 1 node in the output layer). The organic amine interference compensation model is pre-trained using a training set and a test set to obtain a trained organic amine interference compensation model.

[0032] Example 2: A dual-alkali dynamic collaborative analysis device for the chlor-alkali industry, comprising a dynamic temperature titration module, a dual-alkali concentration acquisition module, and an organic amine compensation module; The dynamic temperature titration module includes pre-treating the sample to obtain a titration volume by dynamic temperature titration, wherein the titration volume includes a first endpoint titration volume and a second endpoint titration volume, and the pre-treating performs a carbon dioxide removal kinetic protocol; The dual-alkali concentration acquisition module includes synchronously collecting pH parameters and conductivity signals during the titration process and constructing a multimodal fusion model, and obtaining the dual-alkali concentration based on the titration volume through the multimodal fusion model, wherein the dual-alkali concentration includes the sodium hydroxide concentration and the sodium carbonate concentration; The organic amine compensation module includes recording a potential decay curve after the titration endpoint, obtaining an organic amine interference compensation factor based on the potential decay curve using an organic amine interference compensation model, and automatically compensating the dual base concentration using the organic amine interference compensation factor.

[0033] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as a preferred embodiment as above, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to equivalent embodiments using the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A dual-alkali dynamic collaborative analysis method for the chlor-alkali industry, characterized in that: The following steps are involved: S1: Pre-treating the sample to obtain a titration volume by dynamic temperature titration, wherein the titration volume includes a first endpoint titration volume and a second endpoint titration volume, and the pre-treatment performs a carbon dioxide removal kinetic protocol; S2: During the titration process, pH parameters and conductivity signals are synchronously collected and a multimodal fusion model is constructed. Based on the titration volume, a dual alkali concentration is obtained through the multimodal fusion model, where the dual alkali concentration includes a sodium hydroxide concentration and a sodium carbonate concentration. S3: After the titration endpoint, a potential decay curve is recorded, and an organic amine interference compensation factor is obtained based on the potential decay curve using an organic amine interference compensation model, and the double base concentration is automatically compensated by the organic amine interference compensation factor.

2. The dual-alkali dynamic collaborative analysis method for the chlor-alkali industry according to claim 1, characterized in that: The pre-processing method in step S1 is: The sample is automatically injected, the carbon dioxide removal time is determined according to the carbon dioxide removal kinetic protocol, and the sample is stirred under the coordinated control of temperature and electric field. After the stirring is completed, the sample is allowed to stand.

3. The dual-alkali dynamic collaborative analysis method for the chlor-alkali industry according to claim 2, characterized in that: The carbon dioxide removal kinetic protocol in step S1 is specifically as follows: Obtain liquid phase carbon dioxide concentration, absolute temperature, and applied current; Calibrate thermal desorption rate constant, electromigration rate constant, and carbon dioxide desorption activation energy; The carbon dioxide removal time is obtained by the carbon dioxide removal kinetic equation, and the mathematical description of the carbon dioxide removal kinetic equation is: , where [CO2] is the concentration of liquid carbon dioxide, t is the time for carbon dioxide removal, K T is the thermal desorption rate constant, E a is the activation energy of carbon dioxide desorption, R is the gas constant, T is the absolute temperature, S is the gas-liquid contact area, V is the sample volume, K E is the electromigration rate constant, I app To apply current.

4. The dual-alkali dynamic collaborative analysis method for the chlor-alkali industry according to claim 1, characterized in that: The step S2 specifically includes: S201: synchronously collecting the pH parameter and the conductivity signal and performing feature extraction to obtain a pH jump slope and a conductivity curvature, wherein the pH jump slope includes a first endpoint pH jump slope and a second endpoint pH jump slope; S202: Calibrate the coefficient matrix and obtain the concentration feature vector based on the titration volume, the pH jump slope and the conductivity curvature, and construct the multimodal fusion model based on the coefficient matrix and the concentration feature vector, which is mathematically described as ,in, is the concentration feature matrix, C NaOH is the concentration of sodium hydroxide, is the concentration of sodium carbonate, C d is the titrant concentration, V ref is the reference volume, V is the sample volume, M is the molecular weight matrix, K is the coefficient matrix, and F is the concentration feature matrix.

5. The dual-alkali dynamic collaborative analysis method for the chlor-alkali industry according to claim 4, characterized in that: The acquisition of the concentration feature vector in step S202 is specifically as follows: The total thermal power during the titration process is obtained, and the concentration characteristic vector is obtained according to the titration volume, the pH jump slope, the total thermal power and the conductivity curvature, which is mathematically described as follows: , where V1 is the first endpoint titration volume, V2 is the second endpoint titration volume, and E p1 is the pH jump slope of the first endpoint, E p2 is the pH jump slope of the second endpoint, w c is the conductivity curvature, G0 is the initial conductivity, Q t is the total thermal power during the titration process, is the reference reaction enthalpy, C d is the titrant concentration, and V is the sample volume.

6. The dual-alkali dynamic collaborative analysis method for the chlor-alkali industry according to claim 5, characterized in that: The calibration of the coefficient matrix in step S202 is specifically as follows: Prepare N groups of standard samples, wherein the standard samples include a standard sodium hydroxide sample and a standard sodium carbonate sample, and a preset concentration gradient, wherein the concentrations of the standard samples increase gradually according to the concentration gradient; Each group of standard samples is titrated separately, and the concentration characteristic vector of each group of standard samples is synchronously collected during the titration process, and the coefficient matrix is ​​calibrated based on the concentration characteristic vector.

7. The dual-alkali dynamic collaborative analysis method for the chlor-alkali industry according to claim 1, characterized in that: The step S3 specifically includes: After titrating to the second endpoint, the electrode potential is continuously recorded according to the preset sampling frequency and sampling time to obtain the potential decay curve; Extracting the decay characteristics of the potential decay curve, wherein the decay characteristics include a decay time constant, an integral area, and a maximum recovery slope; Pre-training the organic amine interference compensation model, inputting the attenuation feature into the trained organic amine interference compensation model, and outputting the organic amine interference compensation factor, wherein the organic amine interference compensation factor includes a sodium hydroxide interference compensation factor and a sodium carbonate interference compensation factor; The double base concentration is compensated by the organic amine interference compensation factor.

8. A dual-alkali dynamic collaborative analysis device for the chlor-alkali industry, characterized in that: The device is applied to the dual-alkali dynamic collaborative analysis method in the chlor-alkali industry as described in any one of claims 1 to 7, comprising a dynamic temperature titration module, a dual-alkali concentration acquisition module, and an organic amine compensation module; The dynamic temperature titration module includes pre-treating the sample to obtain a titration volume by dynamic temperature titration, wherein the titration volume includes a first endpoint titration volume and a second endpoint titration volume, and the pre-treating performs a carbon dioxide removal kinetic protocol; The dual-alkali concentration acquisition module includes synchronously collecting pH parameters and conductivity signals during the titration process and constructing a multimodal fusion model, and obtaining the dual-alkali concentration based on the titration volume through the multimodal fusion model, wherein the dual-alkali concentration includes the sodium hydroxide concentration and the sodium carbonate concentration; The organic amine compensation module includes recording a potential decay curve after the titration endpoint, obtaining an organic amine interference compensation factor based on the potential decay curve using an organic amine interference compensation model, and automatically compensating the dual base concentration using the organic amine interference compensation factor.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the dual-alkali dynamic collaborative analysis method for the chlor-alkali industry as described in any one of claims 1-7 is implemented.

10. A storage medium containing computer-executable instructions, characterized in that: When the computer executable instructions are executed by a computer processor, they are used to execute the dual-alkali dynamic collaborative analysis method for the chlor-alkali industry as described in any one of claims 1 to 7.

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