A synthetic latex polymerization reaction temperature optimization control method

Abstract

The application relates to the field of polymerization reactions. A synthetic latex polymerization reaction temperature optimization control method comprises the following steps: acquiring temperature detection data of a reaction kettle in a synthetic latex polymerization reaction, wherein the temperature detection data comprises real-time distributed temperature of a polymerization reaction zone, reaction kettle temperature distribution data and heat transfer medium flow data; acquiring a thermal stress index value according to the real-time distributed temperature of the polymerization reaction zone, and generating a reaction zone parameter compensation amount according to the thermal stress index value; and acquiring a reaction kettle temperature field uniformity index according to the reaction kettle temperature distribution data. Through real-time collection and coupling analysis of multiple source data such as polymerization reaction zone temperature deviation, in-kettle temperature field uniformity and heat transfer medium flow fluctuation, a multi-dimensional coupling matrix of thermal stress, uniformity and flow fluctuation is constructed, the limitation of traditional single-parameter control is broken through, and comprehensive evaluation of reaction heat state, stirring effect and heat exchange stability is realized.

Description

Technical Field

[0001] This application relates to the field of polymerization reactions, and in particular to a method for optimizing and controlling the temperature of a synthetic latex polymerization reaction. Background Technology

[0002] The polymerization reaction of synthetic latex (such as styrene-butadiene latex, acrylic latex, etc.) is a typical strongly exothermic nonlinear process. Temperature, as a core process parameter, directly affects the polymerization rate, molecular weight distribution, latex stability and product properties.

[0003] In related technologies, the heat release of existing polymerization reactions exhibits phased characteristics (such as significant differences in the heat release rates during the initiation, chain growth, and termination phases), and is also affected by multiple factors such as stirring and mixing effects and the stability of the heat transfer medium. Traditional single-loop PID control relies solely on single-point temperature feedback from the reactor, which cannot handle the coupling effects of reaction thermal stress, temperature field inhomogeneity, and heat transfer medium fluctuations, easily leading to local overheating or incomplete reaction. Summary of the Invention

[0004] This application provides a method for optimizing the temperature control of synthetic latex polymerization reaction to solve the problems of uneven thermal stress distribution, heat transfer medium fluctuation and temperature field uniformity coupling and uncontrolled operation in traditional control.

[0005] In a first aspect, this application provides a method for optimizing and controlling the temperature of a synthetic latex polymerization reaction, applied to a reaction vessel and a flow regulating valve for the heat transfer medium, the method comprising:

[0006] Acquire temperature detection data of the reactor during the latex polymerization reaction, wherein the temperature detection data includes real-time temperature distribution in the polymerization reaction zone, reactor temperature distribution data, and heat transfer medium flow rate data;

[0007] The thermal stress index value is obtained based on the real-time temperature distribution in the polymerization reaction zone, and the reaction zone parameter compensation amount is generated based on the thermal stress index value.

[0008] The uniformity index of the temperature field in the reactor is obtained based on the temperature distribution data of the reactor.

[0009] The dynamic index of heat transfer medium flow rate is obtained based on the heat transfer medium flow rate data.

[0010] A multi-dimensional coupling matrix is ​​constructed based on the compensation amount of the reaction zone parameters, the uniformity index of the temperature field of the reactor, and the dynamic index of the heat transfer medium flow rate.

[0011] The temperature control fluctuation value is obtained based on the multi-dimensional coupling matrix;

[0012] Dynamic adjustment information is obtained based on the temperature control fluctuation value, and the heat transfer medium flow regulating valve is adjusted based on the dynamic adjustment information.

[0013] Optionally, the step of obtaining a thermal stress index value according to the real-time temperature distribution of the polymerization reaction zone, and generating a reaction zone parameter compensation amount according to the thermal stress index value, comprises:

[0014] Obtaining material real-time temperature distribution data according to the real-time temperature distribution of the polymerization reaction zone, wherein the material real-time temperature distribution data comprises a top position material real-time temperature value and a bottom position material real-time temperature value;

[0015] Obtaining a first temperature deviation degree and a second temperature deviation degree according to the top position material real-time temperature value and the bottom position material real-time temperature value;

[0016] Obtaining a first fluctuation rate and a second fluctuation rate corresponding in the polymerization reaction according to the first temperature deviation degree and the second temperature deviation degree;

[0017] Obtaining a temperature fluctuation distortion rate according to the first fluctuation rate and the second fluctuation rate;

[0018] Obtaining a thermal stress index value according to the temperature fluctuation distortion rate;

[0019] Obtaining a preset heat exchange efficiency of an external jacket of the reaction kettle;

[0020] Generating a reaction zone parameter compensation amount according to the thermal stress index value and the preset heat exchange efficiency.

[0021] Optionally, the step of obtaining a reaction kettle temperature field uniformity index according to the reaction kettle temperature distribution data, comprises:

[0022] Obtaining a reaction kettle bottom temperature value, a reaction kettle middle temperature value, and a reaction kettle top temperature value according to the reaction kettle temperature distribution data;

[0023] Obtaining an average temperature value according to the reaction kettle bottom temperature value, the reaction kettle middle temperature value, and the reaction kettle top temperature value, and obtaining a first kettle body temperature deviation value, a second kettle body temperature deviation value, and a third kettle body temperature deviation value corresponding to the reaction kettle bottom temperature value, the reaction kettle middle temperature value, and the reaction kettle top temperature value according to the average temperature value;

[0024] Obtaining a preset kettle body temperature difference threshold value;

[0025] Obtaining a reaction kettle temperature field uniformity index according to the preset kettle body temperature difference threshold value, the first kettle body temperature deviation value, the second kettle body temperature deviation value, and the third kettle body temperature deviation value.

[0026] Optionally, the step of obtaining a heat transfer medium flow dynamic index according to the heat transfer medium flow data, comprises:

[0027] According to the heat transfer medium flow data, the fluctuation frequency and the maximum offset of the heat transfer medium per minute are obtained;

[0028] According to the heat transfer medium flow data, the average flow deviation rate is obtained;

[0029] According to the average flow deviation rate, the fluctuation frequency and the maximum offset, a flow fluctuation factor is generated;

[0030] According to the flow fluctuation factor, a processing flow fluctuation factor is obtained by normalization;

[0031] According to the processing flow fluctuation factor, a heat transfer medium flow dynamic index is obtained.

[0032] Optionally, the step of constructing a multi-dimensional coupling matrix according to the reaction zone parameter compensation amount, the reaction kettle temperature field uniformity index and the heat transfer medium flow dynamic index comprises:

[0033] According to the reaction zone parameter compensation amount and the reaction kettle temperature field uniformity index, a first coupling coefficient is obtained;

[0034] According to the reaction zone parameter compensation amount and the heat transfer medium flow dynamic index, a second coupling coefficient is obtained;

[0035] According to the reaction kettle temperature field uniformity index and the heat transfer medium flow dynamic index, a third coupling coefficient is obtained;

[0036] According to the first coupling coefficient, the second coupling coefficient and the third coupling coefficient, a multi-dimensional coupling matrix is constructed.

[0037] Optionally, the step of obtaining a temperature control fluctuation value according to the multi-dimensional coupling matrix comprises:

[0038] Eigenvalue decomposition is performed on the multi-dimensional coupling matrix to obtain temperature fluctuation eigenvalues and corresponding fluctuation eigenvectors of the multi-dimensional coupling matrix;

[0039] According to the temperature fluctuation eigenvalues and corresponding fluctuation eigenvectors, a principal eigenvector is obtained, and a comprehensive eigenvector is generated by linear combination;

[0040] A preset temperature control vector of the polymerization stage is obtained, and a cosine similarity is obtained according to the preset temperature control vector and the comprehensive eigenvector;

[0041] According to the cosine similarity, a temperature control fluctuation value is obtained.

[0042] Optionally, the step of obtaining dynamic adjustment information according to the temperature control fluctuation value comprises:

[0043] According to the temperature control fluctuation value, a proportional factor adjustment range of the controller is obtained;

[0044] According to the temperature control fluctuation value, a change trend is obtained;

[0045] According to the heat transfer medium flow regulating valve, a delay time is obtained;

[0046] According to the change trend and a proportional factor, a flow proportional regulation amplitude and a regulation time are generated;

[0047] According to the flow proportional regulation amplitude and the regulation time, dynamic adjustment information is obtained.

[0048] The application further discloses a synthetic latex polymerization reaction temperature optimization control system applied to a reaction kettle and a heat transfer medium flow regulating valve, and comprising:

[0049] A data acquisition module is configured to obtain temperature detection data of the reaction kettle in the synthetic latex polymerization reaction, wherein the temperature detection data comprises real-time distribution temperature of a polymerization reaction zone, reaction kettle temperature distribution data and heat transfer medium flow data;

[0050] A thermal stress analysis module is configured to obtain a thermal stress index value according to the real-time distribution temperature of the polymerization reaction zone and generate a reaction zone parameter compensation amount according to the thermal stress index value;

[0051] A uniformity evaluation module is configured to obtain a reaction kettle temperature field uniformity index according to the reaction kettle temperature distribution data;

[0052] A flow dynamic analysis module is configured to obtain a heat transfer medium flow dynamic index according to the heat transfer medium flow data;

[0053] A coupling matrix construction module is configured to construct a multi-dimensional coupling matrix according to the reaction zone parameter compensation amount, the reaction kettle temperature field uniformity index and the heat transfer medium flow dynamic index;

[0054] A fluctuation acquisition module is configured to obtain a temperature control fluctuation value according to the multi-dimensional coupling matrix;

[0055] A valve control module is configured to obtain dynamic adjustment information according to the temperature control fluctuation value and adjust the heat transfer medium flow regulating valve according to the dynamic adjustment information.

[0056] Optionally, the thermal stress analysis module comprises:

[0057] A temperature distribution acquisition unit is configured to obtain material real-time temperature distribution data according to the real-time distribution temperature of the polymerization reaction zone, wherein the material real-time temperature distribution data comprises a material real-time temperature value at an uppermost position and a material real-time temperature value at a lowermost position;

[0058] A temperature deviation calculation unit is configured to obtain a first temperature deviation degree and a second temperature deviation degree according to the topmost position material real-time temperature value and the bottommost position material real-time temperature value;

[0059] A fluctuation rate calculation unit is configured to obtain a first fluctuation rate and a second fluctuation rate in the polymerization reaction according to the first temperature deviation degree and the second temperature deviation degree;

[0060] A distortion rate calculation unit is configured to obtain a temperature fluctuation distortion rate according to the first fluctuation rate and the second fluctuation rate;

[0061] A thermal stress calculation unit is configured to obtain a thermal stress index value according to the temperature fluctuation distortion rate;

[0062] A heat exchange efficiency obtaining unit is configured to obtain a preset heat exchange efficiency of an external jacket of the reaction kettle;

[0063] A compensation generation unit is configured to generate a reaction zone parameter compensation amount according to the thermal stress index value and the preset heat exchange efficiency.

[0064] Optionally, the uniformity evaluation module comprises:

[0065] A kettle body temperature obtaining unit is configured to obtain a reaction kettle bottom temperature value, a reaction kettle middle temperature value, and a reaction kettle top temperature value according to the reaction kettle temperature distribution data;

[0066] A deviation value calculation unit is configured to obtain an average temperature value according to the reaction kettle bottom temperature value, the reaction kettle middle temperature value, and the reaction kettle top temperature value, and obtain a first kettle body temperature deviation value, a second kettle body temperature deviation value, and a third kettle body temperature deviation value corresponding to the reaction kettle bottom temperature value, the reaction kettle middle temperature value, and the reaction kettle top temperature value according to the average temperature value;

[0067] A temperature difference threshold value obtaining unit is configured to obtain a preset kettle body temperature difference threshold value;

[0068] A uniformity calculation unit is configured to obtain a reaction kettle temperature field uniformity index according to the preset kettle body temperature difference threshold value, the first kettle body temperature deviation value, the second kettle body temperature deviation value, and the third kettle body temperature deviation value.

[0069] Compared with the related art, the synthetic latex polymerization reaction temperature optimization control method provided by the present application at least has the following technical effects:

[0070] Through real-time collection and coupling analysis of multi-source data such as temperature deviation of the polymerization reaction zone, uniformity of the temperature field in the kettle, flow fluctuation of the heat transfer medium, a multi-dimensional coupling matrix of thermal stress, uniformity and flow fluctuation is constructed, the limitations of traditional single-parameter control are broken through, the overall evaluation of the reaction heat state, stirring effect and heat exchange stability is realized, the root cause of temperature abnormality is accurately located, the automation decision from temperature abnormality detection to regulation instruction generation is realized, manual intervention is reduced, and production efficiency is improved.

[0071] Details of one or more embodiments of the present application are presented in the following drawings and description to make other features, objects and advantages of the present application more apparent. BRIEF DESCRIPTION OF DRAWINGS

[0072] The drawings described herein are intended to provide further understanding of the present application, and constitute a part of the present application. The illustrative embodiments of the present application and their description serve to explain the present application, and do not constitute an improper limitation on the present application. In the drawings:

[0073] Figure 1 is a flow chart of a synthetic latex polymerization reaction temperature optimization control method according to an exemplary embodiment;

[0074] Figure 2 is a system diagram of a synthetic latex polymerization reaction temperature optimization control method according to an exemplary embodiment. DETAILED DESCRIPTION

[0075] In order to make the purposes, technical solutions and advantages of the present application more apparent, the present application is described and explained below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and do not limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the scope of protection of the present application.

[0076] Obviously, the drawings in the following description are only some examples or embodiments of the present application, and for those of ordinary skill in the art, the present application can be applied to other similar scenarios without making creative efforts based on these drawings. In addition, it can be understood that although the efforts made in this development process can be complex and lengthy, for those of ordinary skill in the art related to the content disclosed in the present application, some design, manufacture or production changes based on the technical content disclosed in the present application are only routine technical means, and should not be understood as insufficient disclosure of the content disclosed in the present application.

[0077] Reference to an "embodiment" in this application means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive of one another. It is expressly understood that that the embodiments described herein are merely examples and are not a limitation as to the scope of use or functionality of the application.

[0078] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The materials, methods, and examples provided herein are illustrative only and not intended to be limiting. Except where otherwise indicated, the terms "plurality" and "a plurality" as used herein mean "two or more." The phrase "and / or," as used herein in the usage of "and / or," indicates there are three meanings: "only A," "only B," and "both A and B." The term "coupled" as used herein, unless otherwise indicated, means there can be a direct connection between entities, or there can be an indirect connection between entities through one or more other entities. The term "comprises" and variations thereof as used herein are intended to cover a non-exclusive inclusion. For example, a process, method, product, or apparatus that comprises a list of steps or components does not necessarily comprise only those steps or components but can include additional steps or components not expressly listed or inherent to such process, method, product, or apparatus. The term "connected" as used herein, unless otherwise indicated, does not necessarily mean there is a direct connection between entities, but can also mean there is an indirect connection between entities through one or more other entities. The term "first," "second," "third," etc. as used herein is merely to distinguish similar objects from one another, and does not necessarily indicate a specific order or sequence.

[0079] Embodiment 1

[0080] The embodiment of the application provides a synthetic latex polymerization reaction temperature optimization control method. Figure 1 is a method flowchart according to an example embodiment. Applied to a reaction kettle and a heat transfer medium flow regulating valve, as shown in Figure 1 , the method comprises:

[0081] In step S101, temperature detection data of the reaction kettle in the synthetic latex polymerization reaction is acquired, wherein the temperature detection data comprises real-time distribution temperature of a polymerization reaction zone, reaction kettle temperature distribution data, and heat transfer medium flow data.

[0082] In step S102, a thermal stress index value is acquired according to the real-time distribution temperature of the polymerization reaction zone, and a reaction zone parameter compensation amount is generated according to the thermal stress index value.

[0083] Step S103, obtaining a reaction kettle temperature field uniformity index according to the reaction kettle temperature distribution data;

[0084] Step S104, obtaining a heat transfer medium flow dynamic index according to the heat transfer medium flow data;

[0085] Step S105, constructing a multi-dimensional coupling matrix according to the reaction zone parameter compensation amount, the reaction kettle temperature field uniformity index and the heat transfer medium flow dynamic index;

[0086] Step S106, obtaining a temperature control fluctuation value according to the multi-dimensional coupling matrix;

[0087] Step S107, obtaining dynamic adjustment information according to the temperature control fluctuation value, and adjusting the heat transfer medium flow regulating valve according to the dynamic adjustment information.

[0088] According to the above, the present application firstly obtains temperature detection data of the reaction kettle in the synthesis latex polymerization reaction, including polymerization reaction zone real-time distribution temperature, reaction kettle temperature distribution data and heat transfer medium flow data. The polymerization reaction zone real-time distribution temperature is collected by thermocouples at different heights of the material layer in the reaction kettle, and is used to reflect the temperature state of the core reaction area; the reaction kettle temperature distribution data is obtained by temperature sensors at the bottom, middle and top of the kettle body, and is used to evaluate the material temperature uniformity and the stirring and mixing effect; the heat transfer medium flow data is monitored by electromagnetic flowmeters on the jacket or coil pipeline, and reflects the flow stability of the heat transfer oil, cooling water and other media, and is directly related to the heat exchange efficiency;

[0089] Then, a heat stress index value is calculated according to the polymerization reaction zone real-time distribution temperature, and a reaction zone parameter compensation amount is generated. The upper and lower material temperature values are extracted from the real-time distribution temperature, the deviation degree from the corresponding stage process set temperature is calculated, and then the deviation degree is converted into a fluctuation rate. The temperature fluctuation distortion rate is obtained by analyzing the difference of the fluctuation rate, and the higher the distortion rate is, the more unstable the reaction heat state is. Combined with the preset heat exchange efficiency of the reaction kettle jacket (determined by the jacket cleanliness, medium flow rate, etc.), the reaction zone parameter compensation amount is generated by algorithm, which is used to adjust the subsequent control parameters to cope with the heat stress.

[0090] Then, a temperature field uniformity index is calculated according to the reaction kettle temperature distribution data. The bottom, middle and top temperature values are extracted, the average value is calculated, and then the deviation values of each position from the average value are obtained. A preset kettle body temperature difference threshold value (set according to the process stage) is introduced, and the uniformity index is calculated by formula. The lower the index is, the more uneven the temperature distribution is, and it needs to be improved by adjusting the stirring speed and the like.

[0091] According to the heat transfer medium flow data, a flow dynamic index is generated. The number of fluctuations and the maximum offset of the flow per minute are counted, the deviation rate of the average flow from the rated flow is calculated, the flow fluctuation factor is generated from the deviation rate, the number of fluctuations and the offset, and the flow dynamic index is obtained after normalization processing, which is used to evaluate the flow stability.

[0092] Then a multi-dimensional coupling matrix is constructed to comprehensively reflect the reaction zone parameter compensation amount, the temperature field uniformity index and the flow dynamic index. The first coupling coefficient of the reaction heat stress and uniformity, the second coupling coefficient of the heat stress and the flow fluctuation, and the third coupling coefficient of the uniformity and the flow fluctuation are calculated, and the three are combined with the unit matrix to form the coupling matrix for analyzing the interaction of multi-dimensional data.

[0093] The temperature control fluctuation value is obtained by eigenvalue decomposition of the coupling matrix. The main eigenvector is extracted and a comprehensive eigenvector is generated. The cosine similarity is calculated with the preset temperature control vector (set according to the aggregation stage), the similarity reflects the difference between the current state and the target state, and the temperature control fluctuation value is obtained accordingly. The greater the fluctuation value, the greater the adjustment amplitude.

[0094] Finally, the dynamic adjustment information is generated according to the temperature control fluctuation value. The controller proportional factor adjustment amplitude is determined according to the fluctuation value, the integral time constant is adjusted according to the fluctuation trend, the flow proportional adjustment amplitude and the adjustment time are generated combined with the response time of the regulating valve, the adjustment information is converted into instruction control of the regulating valve, and the temperature dynamic adjustment is realized.

[0095] In one embodiment, step S102 specifically comprises:

[0096] Step S1021, obtaining material real-time temperature distribution data according to the real-time distribution temperature of the polymerization reaction zone, wherein the material real-time temperature distribution data includes a real-time temperature value of the material at the uppermost position and a real-time temperature value of the material at the lowermost position;

[0097] Step S1022, obtaining a first temperature deviation degree and a second temperature deviation degree according to the real-time temperature value of the material at the uppermost position and the real-time temperature value of the material at the lowermost position;

[0098] Step S1023, obtaining a first fluctuation rate and a second fluctuation rate corresponding in the polymerization reaction according to the first temperature deviation degree and the second temperature deviation degree;

[0099] Step S1024, obtaining a temperature fluctuation distortion rate according to the first fluctuation rate and the second fluctuation rate;

[0100] Step S1025, obtaining a heat stress index value according to the temperature fluctuation distortion rate;

[0101] Step S1026, obtaining a preset heat exchange efficiency of the external jacket of the reaction kettle;

[0102] Step S1027, generating a reaction zone parameter compensation amount according to the thermal stress index value and a preset heat exchange efficiency.

[0103] The present application first obtains material real-time temperature distribution data in the real-time distribution temperature of the polymerization reaction zone through a preset temperature sensor network in the reaction kettle in step S1021. The data specifically includes a real-time temperature value of material at the uppermost position in the reaction kettle and a real-time temperature value of material at the lowermost position, which usually correspond to the area below the liquid surface and close to the kettle bottom respectively, for capturing the temperature distribution characteristics in the vertical direction of the reaction zone, providing a basis for analyzing the thermal state difference between the upper and lower layers.

[0104] In step S1022, the real-time temperature value of material at the uppermost position and the real-time temperature value of material at the lowermost position obtained are compared with the process set temperature of the current polymerization stage respectively, and the difference between the two is calculated to obtain a first temperature deviation degree and a second temperature deviation degree. These two deviation degree indexes are used to measure the absolute degree of deviation of the upper and lower layer material temperature from the process target. For example, if the upper layer temperature is higher than the set temperature, the first deviation degree is positive, and vice versa, and the lower layer is the same. The positive and negative values and the numerical value can directly judge whether the upper and lower layer temperature is overheated or underheated and the deviation amplitude.

[0105] In step S1023, the first temperature deviation degree and the second temperature deviation degree are converted into relative proportion indexes, i.e. a first fluctuation rate and a second fluctuation rate. The specific method is to divide the respective deviation degree by the process set temperature to obtain the fluctuation proportion relative to the set temperature. This conversion makes the deviation under different temperature settings comparable. For example: whether the set temperature is 50℃ or 80℃, the fluctuation rate can reflect the relative fluctuation intensity, which is convenient for unified evaluation of temperature stability in different polymerization stages.

[0106] In step S1024, the temperature fluctuation distortion rate is calculated by analyzing the difference between the first fluctuation rate and the second fluctuation rate, and the preset process temperature value is obtained, wherein the calculation formula is:

[0107] , wherein, represents the temperature fluctuation distortion rate, represents the first fluctuation rate, represents the second fluctuation rate, represents the preset process temperature value. Specifically, the absolute value of the difference between the two is calculated. The larger the value, the more significant the inconsistency of the upper and lower layer material temperature fluctuation, which may mean that there is thermal stratification phenomenon or poor stirring effect in the reaction kettle, resulting in insufficient mixing of the upper and lower layer materials and uneven heat distribution. For example, if the upper layer fluctuation rate is +5% and the lower layer is -3%, the distortion rate is 8%, which indicates that attention should be paid to the stirring system or heat exchange efficiency.

[0108] In step S1025, according to the size of the temperature fluctuation distortion rate, the thermal stress index value is obtained through the pre-established corresponding relationship. Generally, the higher the distortion rate, the larger the thermal stress index value, indicating that the impact of the reaction heat on the system stability is stronger, and more significant control measures are needed to maintain temperature balance. The index value is a key parameter for measuring whether the current reaction heat state is stable, and provides a basis for subsequent compensation calculation.

[0109] In step S1026, the preset heat exchange efficiency of the external jacket of the reaction kettle is obtained. The efficiency value is an inherent parameter reflecting the heat transfer capacity of the jacket, which is affected by factors such as the cleanliness of the jacket, the flow rate of the heat transfer medium, the contact area between the jacket and the material, etc. It can be determined through test data or historical operation data during the equipment debugging stage, and is used to correct the actual effect of thermal stress compensation. For example, the jacket with high heat exchange efficiency requires smaller compensation under the same thermal stress, and vice versa.

[0110] In step S1027, the thermal stress index value is combined with the preset heat exchange efficiency to comprehensively calculate the reaction zone parameter compensation. The specific process is as follows: according to the thermal stress index value, the direction and amplitude of the control parameter to be adjusted are determined, and then multiplied by the heat exchange efficiency coefficient to obtain the final compensation. For example, if the thermal stress index value shows that the cooling capacity needs to be increased, and the heat exchange efficiency is high, then the compensation is relatively small; if the heat exchange efficiency is low, the compensation needs to be increased to overcome the heat transfer deficiency. The compensation will be used to adjust the parameters of the subsequent fuzzy PID controller, such as the proportional factor, the integral time constant, etc., so as to realize the dynamic adjustment of the heat transfer medium flow or the stirring speed to cope with the current thermal state abnormality.

[0111] Continuing to refer to Figure 1 After step S102, step S103 is performed, as follows:

[0112] Step S1031, obtaining a reaction kettle bottom temperature value, a reaction kettle middle temperature value, and a reaction kettle top temperature value according to the reaction kettle temperature distribution data;

[0113] Step S1032, obtaining an average temperature value according to the reaction kettle bottom temperature value, the reaction kettle middle temperature value, and the reaction kettle top temperature value, and obtaining a first kettle body temperature deviation value, a second kettle body temperature deviation value, and a third kettle body temperature deviation value corresponding to the reaction kettle bottom temperature value, the reaction kettle middle temperature value, and the reaction kettle top temperature value according to the average temperature value;

[0114] Step S1033, obtaining a preset kettle body temperature difference threshold value;

[0115] Step S1034, obtaining a reaction kettle temperature field uniformity index according to the preset kettle body temperature difference threshold value, the first kettle body temperature deviation value, the second kettle body temperature deviation value, and the third kettle body temperature deviation value.

[0116] In step S1031, the temperature sensor network pre-arranged in the reaction kettle is used to obtain the bottom temperature value, the middle temperature value and the top temperature value of the reaction kettle. These sensors are usually installed at a certain distance from the bottom surface, the geometric center position of the middle part and the area near the liquid surface below the top part of the kettle body, respectively, to collect material temperature data at different heights in the vertical direction of the reaction kettle in real time, and to provide basic data support for analyzing the temperature distribution uniformity in the kettle.

[0117] In step S1032, the average temperature value is first calculated according to the obtained bottom, middle and top temperature values. The specific method is to add the temperature values of the three positions and take the arithmetic mean. This average temperature value reflects the overall temperature level of the material in the reaction kettle. Then, the temperature value of each position is subtracted from the average temperature value to obtain the corresponding first kettle body temperature deviation value (bottom), second kettle body temperature deviation value (middle) and third kettle body temperature deviation value (top). These deviation values are used to measure the deviation of the temperature at each position from the overall average temperature. A positive deviation indicates that the temperature at that position is higher than the average temperature, and a negative deviation indicates that the temperature is lower than the average temperature. The size and sign of the deviation value can be used to intuitively determine whether there is a local overheating or underheating phenomenon in the kettle.

[0118] In step S1033, the preset kettle body temperature difference threshold value is obtained. This threshold value is pre-set according to the process requirements of different stages of synthetic latex polymerization reaction. For example, in the latex particle generation stage, the preset threshold value may be set to a small value due to the higher requirement for temperature uniformity. In the chain growth stage, the threshold value may be appropriately relaxed according to the reaction characteristics. This threshold value is the basis for judging whether the temperature distribution is uniform, and is used for subsequent calculation and evaluation of the uniformity index.

[0119] In step S1034, the reaction kettle temperature field uniformity index is obtained according to the preset kettle body temperature difference threshold value, the first kettle body temperature deviation value, the second kettle body temperature deviation value and the third kettle body temperature deviation value. The calculation formula of the reaction kettle temperature field uniformity index is: wherein, represents the reaction kettle temperature field uniformity index, represents the i-th kettle body temperature deviation value, represents the preset kettle body temperature difference threshold value. The specific process is as follows: first, the squares of the three kettle body temperature deviation values are calculated, and their sum is obtained to reflect the overall deviation of the temperature at each position from the average temperature. Then, the sum of the squares of the deviations is divided by three times the square of the preset kettle body temperature difference threshold value to obtain a normalized value. Finally, 1 is subtracted from the value to obtain the temperature field uniformity index. The value range of the uniformity index is usually between 0 and 1. The closer the value is to 1, the more uniform the temperature distribution, and vice versa.

[0120] In terms of data synergy, the bottom, middle and top temperature values are basic inputs, the overall temperature reference is determined by calculating the average temperature value, the deviation value of each position reveals the difference between the local temperature and the whole, the preset kettle temperature difference threshold provides a standard for judging whether the difference is reasonable, and the uniformity index is the quantitative evaluation result obtained after comprehensively considering these data. For example, in a certain polymerization reaction stage, if the bottom temperature value is low and the middle and top temperature values are high, the average temperature value calculated may be close to the process set temperature, but the deviation value of each position is large, resulting in a large deviation sum, and then the uniformity index is low, indicating that although the overall temperature meets the requirements, the temperature distribution in the vertical direction is uneven, and there may be problems such as poor stirring effect or uneven distribution of heat transfer medium. At this time, the system can trigger corresponding adjustment measures according to the uniformity index, such as increasing the stirring speed to promote material mixing, or adjusting the heat transfer medium flow to improve local heat exchange, so as to improve the temperature field uniformity index and ensure that the reaction is carried out in a uniform temperature environment.

[0121] With reference to the foregoing Figure 1 Step S104 is performed after step S103, and specifically as follows:

[0122] Step S1041, obtaining the fluctuation frequency and maximum offset of the heat transfer medium per minute according to the heat transfer medium flow data;

[0123] Step S1042, obtaining the average flow deviation rate according to the heat transfer medium flow data;

[0124] Step S1043, generating a flow fluctuation factor according to the average flow deviation rate, the fluctuation frequency and the maximum offset;

[0125] Step S1044, obtaining a processing flow fluctuation factor by normalizing the flow fluctuation factor;

[0126] Step S1045, obtaining a heat transfer medium flow dynamic index according to the processing flow fluctuation factor.

[0127] In the present application, firstly in step S1041, the flow data is collected in real time by the electromagnetic flowmeter installed on the heat transfer medium conveying pipeline, the flow change in unit time is monitored, and the fluctuation frequency and maximum offset per minute are extracted. The fluctuation frequency is based on the frequency of the flow curve crossing the preset reference line, which is usually set as the rated flow value, and each crossing is regarded as a fluctuation; the maximum offset is obtained by comparing the absolute value of the difference between the real-time flow and the rated flow, which reflects the maximum degree of deviation of the flow from the process set value in the fluctuation process, and the two parameters jointly characterize the frequency and amplitude characteristics of the flow fluctuation.

[0128] In step S1042, the average flow rate is calculated based on the flow rate data collected continuously within a period of time, and compared with the rated flow rate. The average flow rate deviation rate is obtained by calculating the proportion of the difference between the two in the rated flow rate. The deviation rate is used to evaluate the overall deviation trend of the flow rate in a long time range. If the deviation rate is positive, it indicates that the average flow rate is higher than the rated value, which may cause excessive heat transfer. If it is negative, it indicates that the average flow rate is insufficient, which may cause delayed cooling or heating. Through this parameter, the overall balance of the flow supply can be preliminarily judged.

[0129] In step S1043, the average flow rate deviation rate, the fluctuation frequency and the maximum deviation are comprehensively processed to generate a flow fluctuation factor. The specific process is as follows. First, the fluctuation frequency and the maximum deviation are standardized respectively, so that they have the same dimension as the average flow rate deviation rate. Then, each parameter is assigned a corresponding weight. The weight is determined according to the sensitivity of different stages of the polymerization reaction to each fluctuation factor. For example, in the initial stage of the reaction, the flow rate deviation is more sensitive, so the weight of the average flow rate deviation rate can be increased. Finally, the weighted sum of each parameter is obtained to obtain the flow fluctuation factor. The factor integrates the multi-dimensional flow fluctuation characteristics and quantifies the comprehensive influence degree of the flow fluctuation.

[0130] In step S1044, the generated flow fluctuation factor is normalized to obtain a processed flow fluctuation factor. The purpose of normalization is to eliminate the dimensional differences of data between different batches of production or different devices, so that the fluctuation factor has comparability. The specific method is as follows. Based on the historical production data, the maximum and minimum values of the flow fluctuation factor are determined. The currently calculated fluctuation factor is converted to the interval of 0 to 1 through linear mapping. The processed flow fluctuation factor after conversion can directly reflect the severity of the current flow fluctuation relative to the historical fluctuation, which is convenient for unified evaluation standard.

[0131] In step S1045, the heat transfer medium flow dynamic index is obtained according to the processed flow fluctuation factor. The index directly reflects the fluctuation state of the heat transfer medium flow, and has a positive correlation with the processed flow fluctuation factor. Generally, the processed flow fluctuation factor can be directly used as the flow dynamic index, or it can be generated through a simple linear transformation. The flow dynamic index is the final evaluation result, which is input into the control system. When the index exceeds the preset threshold, the system will trigger corresponding adjustment measures, such as adjusting the speed of the pump, switching the standby pump group or adjusting the valve opening, to stabilize the flow of the heat transfer medium and ensure that the polymerization reaction is carried out in a stable thermal environment.

[0132] Continuing to refer to Figure 1 After step S104, step S105 is performed, which is as follows.

[0133] In step S1051, the first coupling coefficient is obtained according to the reaction zone parameter compensation amount and the reaction kettle temperature field uniformity index.

[0134] Step S1052, obtaining a second coupling coefficient according to the reaction zone parameter compensation amount and the heat transfer medium flow dynamic index;

[0135] Step S1053, obtaining a third coupling coefficient according to the reaction kettle temperature field uniformity index and the heat transfer medium flow dynamic index;

[0136] Step S1054, constructing a multi-dimensional coupling matrix according to the first coupling coefficient, the second coupling coefficient and the third coupling coefficient.

[0137] The application constructs a multi-dimensional parameter coupling analysis framework in steps S1051 to S1054, and provides a synergistic optimization basis for the system by quantifying the interaction relationship between different control factors. In step S1051, the system analyzes the reaction zone parameter compensation amount and the reaction kettle temperature field uniformity index. The reaction zone parameter compensation amount is derived from the previous thermal stress evaluation result, and reflects the adjustment amount of the control parameter for balancing the reaction heat. The reaction kettle temperature field uniformity index quantifies the balance degree of the temperature distribution in the kettle. By mathematically correlating the two, a first coupling coefficient is obtained, which is used to measure the mutual influence strength between the thermal stress compensation operation and the temperature field uniformity. If the compensation amount increases while the uniformity index decreases, it indicates that the current thermal compensation strategy may exacerbate the temperature distribution unevenness, and the compensation method needs to be re-evaluated.

[0138] In step S1052, the system performs coupling analysis on the reaction zone parameter compensation amount and the heat transfer medium flow dynamic index. The heat transfer medium flow dynamic index reflects the fluctuation state of the heat transfer medium flow. By correlating it with the reaction zone parameter compensation amount, a second coupling coefficient is obtained, which reveals the internal relationship between the thermal stress compensation demand and the heat transfer medium stability. If both increase at the same time, it indicates that the instability of the heat transfer medium flow may affect the thermal compensation effect, and the flow needs to be stabilized to improve the control precision.

[0139] In step S1053, the system focuses on the correlation between the reaction kettle temperature field uniformity index and the heat transfer medium flow dynamic index. By analyzing the interaction relationship between the two, a third coupling coefficient is obtained, which is used to evaluate the coupling degree between the temperature distribution uniformity and the heat transfer medium flow stability. If the flow fluctuation is large and the uniformity index is low, it indicates that the flow instability may lead to local uneven heat exchange, and thus affect the overall temperature distribution.

[0140] In step S1054, the system integrates the first, second and third coupling coefficients to construct a multi-dimensional coupling matrix, which presents the interaction relationship among the three key parameters in a structured manner, the main diagonal elements of the matrix are all set to 1, indicating that the parameters are completely related to themselves, and the non-diagonal elements are the corresponding coupling coefficients, reflecting the correlation strength between different parameters, and by analyzing the numerical value of each element in the matrix, the key coupling relationship that dominates the overall system behavior can be identified.

[0141] In the entire data processing process, first, the reaction zone parameter compensation amount, the reaction kettle temperature field uniformity index and the heat transfer medium flow dynamic index are obtained through the previous steps, then the coupling coefficients between each two of them are calculated, these coefficients not only quantify the correlation degree between parameters, but also represent the correlation direction through positive and negative values, for example, a positive coupling coefficient indicates that the two parameters have consistent change trends, and a negative coupling coefficient indicates that the change trends are opposite, finally, these coefficients are organized into a matrix form, making the complex relationship among multi-dimensional parameters intuitive and easy to analyze.

[0142] Continuing to refer to Figure 1 After step S105, step S106 is performed, which is as follows:

[0143] Step S1061, eigenvalue decomposition is performed on the multi-dimensional coupling matrix to obtain temperature fluctuation eigenvalues and corresponding fluctuation eigenvectors of the multi-dimensional coupling matrix;

[0144] Step S1062, a principal eigenvector is obtained according to the temperature fluctuation eigenvalues and corresponding fluctuation eigenvectors, and a comprehensive eigenvector is generated through linear combination;

[0145] Step S1063, a preset temperature control vector of the aggregation stage is obtained, and a cosine similarity is obtained according to the preset temperature control vector and the comprehensive eigenvector;

[0146] Step S1064, a temperature control fluctuation value is obtained according to the cosine similarity.

[0147] In step S1061, the system performs eigenvalue decomposition on the multi-dimensional coupling matrix from step S1054, which decomposes the matrix into a set of eigenvalues and corresponding eigenvectors, where the eigenvalues represent the energy intensity of each fluctuation mode, and the eigenvectors correspond to specific fluctuation modes. Through this decomposition, the system can extract the potential periodic or abnormal fluctuation source from the complex coupling relationship, providing a basis for subsequent analysis.

[0148] In step S1062, the system obtains the principal eigenvector based on the eigenvalue decomposition result and generates a comprehensive eigenvector, the principal eigenvector is the eigenvector corresponding to the maximum eigenvalue, which represents the dominant fluctuation mode. The system selects the first several principal eigenvectors, calculates the weight coefficients according to the eigenvalue size, and then generates a comprehensive eigenvector through weighted linear combination. This vector integrates the fluctuation information in multiple dimensions and can comprehensively describe the fluctuation characteristics of the system, providing a unified representation form for subsequent comparison with the ideal control mode.

[0149] In step S1063, the system obtains the preset temperature control vector of the aggregation stage and compares it with the comprehensive eigenvector. The preset temperature control vector is set based on the aggregation process standard and represents the ideal temperature fluctuation mode. The system calculates the cosine similarity of the two vectors to measure the matching degree of the actual fluctuation mode and the ideal control mode. The cosine similarity is calculated by vector dot product. The closer the value is to 1, the more consistent the directions of the two vectors, that is, the more the actual fluctuation mode meets the expectation.

[0150] In step S1064, the system obtains the temperature control fluctuation value according to the cosine similarity. This process maps the cosine similarity to an intuitive fluctuation index. By subtracting the cosine similarity from 1, the difference obtained is the temperature control fluctuation value. The smaller the value, the closer the actual fluctuation is to the ideal state, and the better the performance of the control system. Through this mapping, the system converts the abstract vector similarity into a quantitative index that can be directly used for control decision-making.

[0151] In the entire data processing process, first, the multi-dimensional coupled matrix is converted into a series of fluctuation modes with physical meaning through eigenvalue decomposition, each mode is described by eigenvalue and eigenvector, then the complex multi-dimensional fluctuation information is integrated into a single comprehensive eigenvector by selecting the principal eigenvector and weighted combination. This process not only simplifies the data representation, but also retains the most important fluctuation characteristics. Then, through the cosine similarity calculation with the preset temperature control vector, the system can evaluate the matching degree of the current fluctuation mode and the ideal mode. This evaluation method does not depend on the specific amplitude of the fluctuation, but focuses on the mode characteristics of the fluctuation. Finally, through a simple mapping operation, the similarity is converted into an intuitive fluctuation value, providing a clear basis for control system regulation.

[0152] Continuing to refer to Figure 1 After step S106, step S107 is performed, as follows:

[0153] In step S1071, the adjustment amplitude of the proportional factor of the controller is obtained according to the temperature control fluctuation value.

[0154] In step S1072, the change trend is obtained according to the temperature control fluctuation value.

[0155] Step S1073, obtaining a delay time according to the heat transfer medium flow regulating valve;

[0156] Step S1074, adjusting the amplitude and corresponding time according to the change trend and the scale factor to generate a flow scale adjustment amplitude and an adjustment time;

[0157] Step S1075, obtaining dynamic adjustment information according to the flow scale adjustment amplitude and the adjustment time.

[0158] Firstly, in step S1071, the system obtains the scale factor adjustment amplitude of the controller based on the temperature control fluctuation value obtained in step S1064. This process is achieved by establishing a mapping relationship between the fluctuation value and the scale factor adjustment amplitude. The larger the fluctuation value, the larger the corresponding scale factor adjustment amplitude, so as to enhance the response ability of the system to temperature fluctuations, and enable the controller to dynamically adjust the control parameters according to the fluctuation degree.

[0159] In step S1072, the system analyzes the change trend of the temperature control fluctuation value. By collecting the fluctuation values at consecutive time points and calculating the slope, the change trend information is obtained. This information is used to predict the development direction of the fluctuation. If the trend is positive, it indicates that the fluctuation is intensifying, and the system needs to take intervention measures in advance. If the trend is negative, the adjustment intensity can be appropriately slowed down to avoid over-adjustment.

[0160] In step S1073, the system obtains the corresponding time of the heat transfer medium flow regulating valve. This process is based on the historical operation data of the regulating valve, analyzes the relationship between the valve opening change amount and the response time, establishes a response time model, which quantifies the inertia delay characteristics of the regulating valve, and provides a basis for the calculation of the subsequent adjustment time, ensuring that the system can consider the physical limitations of the actuator and avoid over-adjustment or insufficient adjustment caused by response delay.

[0161] In step S1074, the system generates a flow scale adjustment amplitude and an adjustment time by comprehensively considering the scale factor adjustment amplitude, the change trend and the response time of the regulating valve. The calculation of the flow scale adjustment amplitude combines the scale factor adjustment amplitude and the change trend, so that the adjustment amplitude can be dynamically adjusted according to the development trend of the fluctuation. The calculation of the adjustment time is based on the response time model of the regulating valve and considers the influence of the change trend. When the fluctuation intensifies, the adjustment time is appropriately prolonged to balance the response speed and stability.

[0162] In step S1075, the system integrates the flow scale adjustment amplitude and the adjustment time into dynamic adjustment information. This process converts the abstract parameters calculated into directly executable regulating valve control instructions, including valve ID, adjustment amplitude, adjustment time and execution timestamp, etc. A complete regulating valve control scheme is formed to drive the actuator to act and realize precise adjustment of the heat transfer medium flow.

[0163] Embodiment 2

[0164] The embodiment 2 of the present application provides a synthetic latex polymerization reaction temperature optimization control system. Figure 2 is a system block diagram shown according to an exemplary embodiment. As Figure 2 shown, a synthetic latex polymerization reaction temperature optimization control system comprises:

[0165] a data acquisition module 1 configured to acquire temperature detection data of a reaction kettle in a synthetic latex polymerization reaction, wherein the temperature detection data comprises real-time distribution temperature of a polymerization reaction zone, reaction kettle temperature distribution data, and heat transfer medium flow data;

[0166] a thermal stress analysis module 2 configured to acquire a thermal stress index value according to the real-time distribution temperature of the polymerization reaction zone, and generate a reaction zone parameter compensation amount according to the thermal stress index value;

[0167] a uniformity evaluation module 3 configured to acquire a reaction kettle temperature field uniformity index according to the reaction kettle temperature distribution data;

[0168] a flow dynamic analysis module 4 configured to acquire a heat transfer medium flow dynamic index according to the heat transfer medium flow data;

[0169] a coupling matrix construction module 5 configured to construct a multi-dimensional coupling matrix according to the reaction zone parameter compensation amount, the reaction kettle temperature field uniformity index, and the heat transfer medium flow dynamic index;

[0170] a fluctuation acquisition module 6 configured to acquire a temperature control fluctuation value according to the multi-dimensional coupling matrix;

[0171] a valve control module 7 configured to acquire dynamic adjustment information according to the temperature control fluctuation value, and adjust a heat transfer medium flow regulating valve according to the dynamic adjustment information.

[0172] In one embodiment, the thermal stress analysis module 2 comprises:

[0173] a temperature distribution acquisition unit configured to acquire real-time temperature distribution data of a material according to the real-time distribution temperature of the polymerization reaction zone, wherein the real-time temperature distribution data of the material comprises a real-time temperature value of material at an uppermost position and a real-time temperature value of material at a lowermost position;

[0174] a temperature deviation calculation unit configured to acquire a first temperature deviation degree and a second temperature deviation degree according to the real-time temperature value of material at the uppermost position and the real-time temperature value of material at the lowermost position;

[0175] a fluctuation rate calculation unit configured to acquire a first fluctuation rate and a second fluctuation rate corresponding in the polymerization reaction according to the first temperature deviation degree and the second temperature deviation degree;

[0176] a distortion rate calculation unit configured to obtain a temperature fluctuation distortion rate according to the first fluctuation rate and the second fluctuation rate;

[0177] a thermal stress calculation unit configured to obtain a thermal stress index value according to the temperature fluctuation distortion rate;

[0178] a heat exchange efficiency obtaining unit configured to obtain a preset heat exchange efficiency of an external jacket of the reaction kettle;

[0179] a compensation generation unit configured to generate a reaction zone parameter compensation amount according to the thermal stress index value and the preset heat exchange efficiency.

[0180] In one embodiment, the uniformity evaluation module 3 comprises:

[0181] a kettle body temperature obtaining unit configured to obtain a bottom temperature value, a middle temperature value, and a top temperature value of the reaction kettle according to the reaction kettle temperature distribution data;

[0182] a deviation value calculation unit configured to obtain an average temperature value according to the bottom temperature value, the middle temperature value, and the top temperature value of the reaction kettle, and obtain first, second, and third kettle body temperature deviation values corresponding to the bottom temperature value, the middle temperature value, and the top temperature value of the reaction kettle according to the average temperature value;

[0183] a temperature difference threshold value obtaining unit configured to obtain a preset kettle body temperature difference threshold value;

[0184] a uniformity calculation unit configured to obtain a reaction kettle temperature field uniformity index according to the preset kettle body temperature difference threshold value, the first, second, and third kettle body temperature deviation values.

Claims

1. A method for optimizing and controlling the temperature of a synthetic latex polymerization reaction, applied to a reaction vessel and a flow regulating valve for the heat transfer medium, characterized in that, The method includes: Acquire temperature detection data of the reactor during the latex polymerization reaction, wherein the temperature detection data includes real-time temperature distribution in the polymerization reaction zone, reactor temperature distribution data, and heat transfer medium flow rate data; The real-time temperature distribution data of the material is obtained based on the real-time temperature distribution in the polymerization reaction zone, wherein the real-time temperature distribution data of the material includes the real-time temperature value of the material at the uppermost position and the real-time temperature value of the material at the lowermost position. The first temperature deviation and the second temperature deviation are obtained based on the real-time temperature values ​​of the material at the top and bottom positions. The first volatility and the second volatility corresponding to the polymerization reaction are obtained based on the first temperature deviation and the second temperature deviation. The temperature fluctuation distortion rate is obtained based on the first volatility and the second volatility. The thermal stress index value is obtained based on the temperature fluctuation distortion rate. Obtain the preset heat exchange efficiency of the outer jacket of the reactor; The reaction zone parameter compensation amount is generated based on the thermal stress index value and the preset heat exchange efficiency. The temperature values ​​at the bottom, middle, and top of the reactor are obtained based on the reactor temperature distribution data. The average temperature value is obtained based on the temperature values ​​at the bottom, middle, and top of the reactor. The first, second, and third reactor body temperature deviation values ​​corresponding to the bottom, middle, and top temperatures of the reactor are then obtained based on the average temperature value. Obtain the preset temperature difference threshold of the vessel body; The uniformity index of the temperature field of the reactor is obtained based on the preset temperature difference threshold, the temperature deviation value of the first reactor, the temperature deviation value of the second reactor, and the temperature deviation value of the third reactor. The dynamic index of heat transfer medium flow rate is obtained based on the heat transfer medium flow rate data. A multi-dimensional coupling matrix is ​​constructed based on the compensation amount of the reaction zone parameters, the uniformity index of the temperature field of the reactor, and the dynamic index of the heat transfer medium flow rate. The temperature control fluctuation value is obtained based on the multi-dimensional coupling matrix; Dynamic adjustment information is obtained based on the temperature control fluctuation value, and the heat transfer medium flow regulating valve is adjusted based on the dynamic adjustment information.

2. The method for optimizing and controlling the polymerization reaction temperature of synthetic latex according to claim 1, characterized in that, The step of obtaining the dynamic index of heat transfer medium flow rate based on the heat transfer medium flow rate data includes: The number of fluctuations and the maximum deviation of the heat transfer medium per minute are obtained based on the flow rate data of the heat transfer medium. The average flow deviation rate is obtained based on the heat transfer medium flow data. A flow fluctuation factor is generated based on the average flow deviation rate, the number of fluctuations, and the maximum offset. The processed flow fluctuation factor is obtained by normalizing the flow fluctuation factor. The dynamic index of heat transfer medium flow rate is obtained based on the processing flow fluctuation factor.

3. The method for optimizing and controlling the polymerization reaction temperature of synthetic latex according to claim 1, characterized in that, The step of constructing a multi-dimensional coupling matrix based on the reaction zone parameter compensation amount, the reactor temperature field uniformity index, and the heat transfer medium flow dynamic index includes: The first coupling coefficient is obtained based on the compensation amount of the reaction zone parameters and the uniformity index of the temperature field in the reactor. The second coupling coefficient is obtained based on the compensation amount of reaction zone parameters and the dynamic index of heat transfer medium flow rate. The third coupling coefficient is obtained based on the uniformity index of the temperature field in the reactor and the dynamic index of the heat transfer medium flow rate. A multi-dimensional coupling matrix is ​​constructed based on the first coupling coefficient, the second coupling coefficient, and the third coupling coefficient.

4. The method for optimizing and controlling the polymerization reaction temperature of synthetic latex according to claim 1, characterized in that, The step of obtaining the temperature control fluctuation value based on the multi-dimensional coupling matrix includes: Eigenvalue decomposition is performed on the multi-dimensional coupling matrix to obtain the temperature fluctuation eigenvalues ​​and corresponding fluctuation eigenvectors of the multi-dimensional coupling matrix. The main feature vector is obtained based on the temperature fluctuation feature value and the corresponding fluctuation feature vector, and a comprehensive feature vector is generated by linear combination. Obtain the preset temperature control vector for the aggregation stage, and obtain the cosine similarity based on the preset temperature control vector and the comprehensive feature vector; Temperature control fluctuation values ​​are obtained based on cosine similarity.

5. The method for optimizing and controlling the polymerization reaction temperature of synthetic latex according to claim 1, characterized in that, The step of obtaining dynamic adjustment information based on the temperature control fluctuation value includes: The adjustment range of the controller's proportional factor is obtained based on the temperature control fluctuation value; The trend of change is obtained based on the temperature control fluctuation value; The delay time is obtained based on the heat transfer medium flow regulating valve; Based on the changing trend and the adjustment range of the proportional factor, the corresponding time is used to generate the flow ratio adjustment range and adjustment time; Dynamic adjustment information is obtained based on the flow rate adjustment range and adjustment time.

6. A temperature optimization and control system for synthetic latex polymerization reaction, applied to a reactor and a flow regulating valve for the heat transfer medium, characterized in that, include: The data acquisition module is used to acquire temperature detection data of the reactor in the latex polymerization reaction. The temperature detection data includes real-time temperature distribution in the polymerization reaction zone, temperature distribution data of the reactor, and flow rate data of the heat transfer medium. The thermal stress analysis module is used to obtain real-time temperature distribution data of the material based on the real-time temperature distribution in the polymerization reaction zone. The real-time temperature distribution data of the material includes the real-time temperature value of the material at the uppermost position and the real-time temperature value of the material at the lowermost position. The first temperature deviation and the second temperature deviation are obtained based on the real-time temperature values ​​of the material at the top and bottom positions. The first volatility and the second volatility corresponding to the polymerization reaction are obtained based on the first temperature deviation and the second temperature deviation. The temperature fluctuation distortion rate is obtained based on the first volatility and the second volatility. The thermal stress index value is obtained based on the temperature fluctuation distortion rate. Obtain the preset heat exchange efficiency of the outer jacket of the reactor; The reaction zone parameter compensation amount is generated based on the thermal stress index value and the preset heat exchange efficiency. The uniformity assessment module is used to obtain the temperature values ​​at the bottom, middle, and top of the reactor based on the reactor temperature distribution data. The average temperature value is obtained based on the temperature values ​​at the bottom, middle, and top of the reactor. The first, second, and third reactor body temperature deviation values ​​corresponding to the bottom, middle, and top temperatures of the reactor are then obtained based on the average temperature value. Obtain the preset temperature difference threshold of the vessel body; The uniformity index of the temperature field of the reactor is obtained based on the preset temperature difference threshold, the temperature deviation value of the first reactor, the temperature deviation value of the second reactor, and the temperature deviation value of the third reactor. The flow dynamic analysis module is used to obtain the heat transfer medium flow dynamic index based on the heat transfer medium flow data. The coupling matrix construction module is used to construct a multi-dimensional coupling matrix based on the reaction zone parameter compensation amount, the reactor temperature field uniformity index, and the heat transfer medium flow dynamic index. The fluctuation acquisition module is used to acquire temperature control fluctuation values ​​based on the multi-dimensional coupling matrix. The valve control module is used to obtain dynamic adjustment information based on the temperature control fluctuation value, and to adjust the heat transfer medium flow regulating valve according to the dynamic adjustment information.

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