Intelligent detection system for siloxane polyurethane preparation

Abstract

The invention relates to the technical field of siloxane polyurethane production quality control, in particular to an intelligent detection system for siloxane polyurethane preparation, which comprises a vacuum dehydration module, a prepolymerization precursor preparation module, a reduced pressure distillation module, a siloxane polyurethane preparation module, a detection module, an optimization module and an execution module, the detection module monitors the crosslinking density of siloxane polyurethane and the temperature change in the preparation process in real time, and provides accurate data for quality control; the optimization module judges the product quality based on the data, quickly locates the cause of the problem when the product is unqualified, and sends out a correction instruction; and the execution module accurately controls execution of each module according to the instruction, so that automation and intelligentization of the preparation process are realized. The intelligent detection system provided by the invention effectively solves the problems of lack of control in the existing preparation process and difficulty in quick positioning and correction when the product goes wrong, and remarkably improves the quality stability and consistency of the siloxane polyurethane finished product.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of quality control of siloxane polyurethane production, and specifically relates to an intelligent detection system for siloxane polyurethane preparation. BACKGROUND

[0002] Siloxane polyurethane is a composite material formed by introducing polysiloxane segments into the polyurethane network. Since siloxane polyurethane is composed of hard segments (usually crosslinking points formed by polyisocyanate and chain extender) and soft segments (usually polyether or polyester polyol), by controlling the ratio of soft and hard segments and crosslinking density, siloxane polyurethane exhibits various forms from liquid, gel, elastomer to solid, and also has wide application in various fields such as coatings, adhesives, biomedical devices, etc. In the current industrial application of preparing siloxane polyurethane, a two-step method is usually used to synthesize siloxane polyurethane. This preparation method is relatively complex, and the reaction conditions of each step need to be accurately controlled. Any problem in detail may cause a chain reaction, seriously affecting the performance of siloxane polyurethane products. At the same time, when the quality of the finished product is problematic, this complex production method lacking precise detection and control will make it difficult to trace the cause affecting the product performance, and also lack a fast and effective automatic correction means, thereby seriously affecting the quality stability and consistency of siloxane polyurethane products. SUMMARY

[0003] The present application provides an intelligent detection system for siloxane polyurethane preparation to overcome the problem of lack of control in the existing siloxane polyurethane preparation process, and difficulty in quickly locating and correcting when the product is problematic.

[0004] To this end, the present application provides an intelligent detection system for siloxane polyurethane preparation, comprising a vacuum dehydration module for vacuum removing water in polyol; a prepolymer precursor preparation module connected with the vacuum dehydration module for preparing a polyurethane prepolymer precursor; a reduced pressure distillation module connected with the prepolymer precursor preparation module for removing solvent in the polyurethane prepolymer precursor to obtain a polyurethane prepolymer; a siloxane polyurethane preparation module connected with the reduced pressure distillation module for preparing siloxane polyurethane; a detection module comprising a plurality of sensors, a tensile testing machine, a potentiometric titrator and a thermogravimetric analyzer for detecting the crosslinking density of each point in the siloxane polyurethane and the temperature change during the preparation of siloxane polyurethane; an optimization module connected with the detection module to determine whether the quality of the siloxane polyurethane is qualified based on the variance of crosslinking density at each point in the siloxane polyurethane, and to determine the unqualified reason based on the isocyanate group content in the polyurethane prepolymer when the quality is unqualified, and to issue instructions to correct the vacuum dehydration parameters, the prepolymer precursor preparation parameters and the siloxane polyurethane preparation parameters based on the unqualified reason; an execution module connected with the optimization module, the vacuum dehydration module, the prepolymer precursor preparation module and the siloxane polyurethane preparation module to control the corresponding modules to execute based on the instructions.

[0005] Further, the optimization module is used to determine the variance of crosslinking density based on the variance of crosslinking density at each point in the siloxane polyurethane, and to determine whether the quality of the siloxane polyurethane is qualified based on the variance of crosslinking density, and to maintain the system parameters when the quality is qualified, or to determine the unqualified reason based on the isocyanate group content in the polyurethane prepolymer when the quality is unqualified.

[0006] Further, the optimization module is also used to determine the unqualified reason based on the isocyanate group content in the polyurethane prepolymer, and to determine the unqualified reason based on the average value of carbon dioxide concentration in the exhaust gas periodically collected during the preparation of the polyurethane prepolymer precursor when the preparation of the polyurethane prepolymer precursor is unqualified, or to determine the unqualified reason based on the variance of the second derivative of the differential thermal gravity curve at different temperatures when the preparation of the siloxane polyurethane is unqualified.

[0007] Further, the optimization module is also used to determine the average value of carbon dioxide concentration based on the average value of carbon dioxide concentration in the exhaust gas periodically collected during the preparation of the polyurethane prepolymer precursor, and to determine the unqualified reason based on the average value of carbon dioxide concentration, and to correct the holding time of the prepolymer precursor preparation module based on the ratio of the preset isocyanate group content to the isocyanate group content in the polyurethane prepolymer precursor when the stopping of the stopping agent is not timely, or to correct the vacuum degree when removing the water in the polyol in the vacuum dehydration module based on the difference between the average value of carbon dioxide concentration and the preset average value of carbon dioxide concentration when the water removal effect of the polyol does not meet the standard.

[0008] Further, the optimization module is also used to determine the isocyanate group ratio based on the ratio of the preset isocyanate group content to the isocyanate group content in the polyurethane prepolymer precursor, and to shorten the holding time of the prepolymer precursor preparation module based on the isocyanate group ratio, and the shortening range of the holding time is proportional to the isocyanate group ratio.

[0009] Further, the optimization module is further configured to determine a difference value of the holding time based on the difference between the holding time of the prepolymer precursor before and after the correction, and to reduce the cooling rate of the prepolymer precursor preparation module in the preparation of the prepolymer precursor based on the difference value of the holding time, and the reduction amplitude of the cooling rate is proportional to the difference value of the holding time.

[0010] Further, the optimization module is further configured to determine a difference value of the carbon dioxide concentration based on the difference between the average value of the carbon dioxide concentration and the set preset average value of the carbon dioxide concentration, and to increase the vacuum degree of the vacuum dehydration module in the removal of the water in the polyol based on the difference value of the carbon dioxide concentration, and the increase amplitude of the vacuum degree is proportional to the difference value of the carbon dioxide concentration.

[0011] Further, the optimization module is further configured to determine a variance of the second derivative of the differential thermal gravity curve at different temperatures based on the variance of the second derivative of the differential thermal gravity curve at different temperatures, and to determine the cause of the unqualified quality based on the variance of the second derivative of the differential thermal gravity curve, and to correct the curing time of the polyurethane prepolymer and the organofunctional silane of the silicone polyurethane preparation module based on the difference between the minimum temperature and the maximum temperature of the silicone polyurethane precursor during curing when the curing temperature of the siloxane polyurethane is determined to be uneven, or to correct the amount of solvent added by the silicone polyurethane preparation module based on the ratio between the viscosity of the polyurethane prepolymer and the organofunctional silane mixture and the set preset viscosity when the mixing of the polyurethane prepolymer and the organofunctional silane is determined to be uneven.

[0012] Further, the optimization module is further configured to determine a difference value of the curing temperature based on the difference between the minimum temperature and the maximum temperature of the silicone polyurethane precursor during curing, and to extend the curing time of the polyurethane prepolymer and the organofunctional silane of the silicone polyurethane preparation module based on the difference value of the curing temperature, and the extension amplitude of the curing time is proportional to the difference value of the curing temperature.

[0013] Further, the optimization module is further configured to determine a viscosity ratio based on the ratio between the viscosity of the polyurethane prepolymer and the organofunctional silane mixture and the set preset viscosity, and to increase the amount of solvent added by the silicone polyurethane preparation module based on the viscosity ratio, and the increase amplitude of the amount of solvent added is proportional to the viscosity ratio.

[0014] Compared with the prior art, the beneficial effects of the present application are that the intelligent detection system for the preparation of siloxane polyurethane is provided, which comprises a vacuum dehydration module, a prepolymer precursor preparation module, a reduced pressure distillation module, a siloxane polyurethane preparation module, a detection module, an optimization module and an execution module, wherein the detection module utilizes various sensors and detection equipment to monitor the key parameters in the preparation process in real time, ensures the overall controllability of the preparation process, and provides accurate data for subsequent optimization; the optimization module judges the product quality based on the detection data through quantitative indicators such as crosslinking density variance, analyzes the causes of the problem, and automatically issues correction instructions to adjust the preparation parameters, and avoids quality problems caused by improper parameter settings through a real-time feedback mechanism; the execution module accurately controls the operation of each preparation module according to the instructions of the optimization module, ensures that the preparation process is executed according to the optimized parameters, and this systematic control method realizes the automation and intelligent management of the preparation process, improves the consistency and stability of the product quality, significantly shortens the problem positioning and correction time, and effectively solves the problems of lack of control and difficulty in rapid correction in the existing preparation process.

[0015] Further, the crosslinking density variance is used as a quantitative indicator, which can objectively reflect the control effect of mixing uniformity, reaction degree, curing process and other links in the preparation process. By comparing the crosslinking density variance with the preset value, it can be accurately judged whether the product quality is qualified, which provides a clear basis for subsequent parameter adjustment, enhances the system's control ability of product quality, makes the quality judgment more scientific and accurate, and further improves the quality control level of the preparation process of siloxane polyurethane, and ensures the high performance and high quality of the product.

[0016] Further, by monitoring the isocyanate group content in the polyurethane prepolymer, the judgment of unqualified reasons is further refined. The isocyanate group content is a key indicator for measuring the reaction degree and performance of the prepolymer, and its content change reflects the sufficiency of the reaction. When the isocyanate group content is low, by monitoring the average value of carbon dioxide concentration in the tail gas, it can be distinguished whether the terminating agent terminates in time or the water removal effect of the polyol does not meet the standard. The increase of carbon dioxide concentration is a direct sign of excessive water content, which leads to abnormal consumption of isocyanate groups. Through this refined judgment method, the system can more accurately locate the problem, provide a specific direction for subsequent targeted correction, improve the efficiency and accuracy of problem solving, and further optimize the quality control of the preparation process.

[0017] Further, by monitoring the average value of carbon dioxide concentration in the tail gas, it can be accurately judged whether the polyol water removal effect meets the standard. The difference between the average value of carbon dioxide concentration and the preset value directly reflects the completeness of water removal. When the average value of carbon dioxide concentration is higher than the preset value, it means that the water removal is not complete, and the system will automatically adjust the vacuum degree to improve the dehydration efficiency. This dynamic correction method based on actual detection data can timely adjust the process parameters to ensure the smooth progress of the reaction process, avoid quality problems caused by improper parameter setting, and further improve the stability of the preparation process and the reliability of the product quality.

[0018] Further, by introducing the isocyanate group ratio, the present application can dynamically adjust the holding time of the prepolymer precursor. The isocyanate group ratio reflects the deviation of the actual reaction from the expected reaction. When the ratio is greater than 1, it means that the prepolymerization reaction is overdone, and the isocyanate group is consumed too much, which may lead to the decline of the properties of the prepolymer. At this time, the system will use different holding time correction thresholds according to the size of the ratio to shorten the holding time, so that the reaction can be stopped in time by the terminator, and the occurrence of side reactions can be reduced. This dynamic adjustment method based on the actual reaction degree can effectively prevent over-reaction or under-reaction, improve product quality and efficiency, and at the same time improve the sensitivity and accuracy of the intelligent control system, realizing closed-loop control.

[0019] Further, by monitoring the holding time difference, the present application dynamically adjusts the cooling rate during the preparation of the prepolymer precursor. The holding time difference reflects the amount of remaining reactants in the reaction process. When the holding time is shortened, rapid cooling may lead to incomplete reaction or uneven structure. Therefore, the system will use different cooling rate correction thresholds according to the size of the holding time difference to reduce the cooling rate, ensure that the reaction system remains at a lower temperature for a longer period of time, and promote the complete reaction of the remaining reactants. This dynamic optimization of the cooling rate adjustment method can improve the completeness of the reaction, alleviate the internal stress and unevenness that may be caused by rapid cooling, further optimize the preparation process, and improve the stability and consistency of the product quality.

[0020] Further, by monitoring the carbon dioxide concentration difference, the present application can dynamically adjust the vacuum degree during the removal of water in polyols. The carbon dioxide concentration difference reflects the amount of residual water in polyols. When the carbon dioxide concentration difference is large, it means that the water removal is not complete, and the system will automatically increase the vacuum degree to enhance the water evaporation capacity. This dynamic adjustment method based on actual detection data can ensure that the water in polyols is effectively removed, avoid the interference of water on subsequent reactions, and improve the stability and consistency of product quality. At the same time, this adjustment method can flexibly adjust the vacuum degree according to actual needs, avoid the increase of energy consumption and equipment burden caused by excessive vacuum, and realize efficient and energy-saving dehydration control.

[0021] Further, by monitoring the variance of the second derivative of the differential thermal gravimetric curve at different temperatures, the present application can determine the cause of quality defects in the curing process of silicone polyurethane. The variance of the second derivative of the differential thermal gravimetric curve reflects the uniformity of the curing process. When the variance is large, it indicates that there is a problem of temperature non-uniformity or mixing non-uniformity in the curing process. The system will determine whether the curing temperature is non-uniform or the mixing is non-uniform according to the size of the variance, and take appropriate corrective measures. This quality determination and correction method based on thermal gravimetric analysis data can effectively reflect the quality non-uniformity and defect problems in the preparation process, provide accurate feedback information for the intelligent optimization system, guide the dynamic adjustment of process parameters, and further improve the product consistency and performance stability.

[0022] Further, by monitoring the difference between the lowest temperature and the highest temperature of the silicone polyurethane precursor during curing, the present application can dynamically adjust the curing time of the polyurethane prepolymer and organofunctional silane. The difference in curing temperature reflects the temperature uniformity of the curing process. When the difference is large, it indicates that there is a significant temperature gradient inside the system, leading to non-uniform curing. The system will use different curing time correction thresholds according to the size of the curing temperature difference to extend the curing time and ensure the overall curing quality. This extension strategy proportional to the curing temperature difference can achieve dynamic adjustment of the curing time, avoid energy consumption and cost waste caused by excessive curing time, and prevent incomplete curing, further optimizing the quality control of the curing process and improving the finished product yield and mechanical property stability.

[0023] Further, by monitoring the viscosity ratio of the polyurethane prepolymer and organofunctional silane mixture to the preset viscosity, the present application can dynamically adjust the amount of solvent added during the preparation of silicone polyurethane. The viscosity ratio reflects the flowability and uniformity of the mixture. When the viscosity ratio is large, it indicates that the viscosity of the mixture is too high and the mixing is not uniform. The system will use different solvent correction thresholds according to the size of the viscosity ratio to increase the amount of solvent and improve the mixing uniformity. This proportional adjustment method can accurately control the amount of solvent, avoid insufficient or excessive solvent, improve the adjustment efficiency, and avoid other process and performance problems caused by excessive one-time adjustment. Through this dynamically optimized solvent addition amount adjustment method, the quality control of the preparation process can be further optimized, and the performance stability and consistency of the product can be improved. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 Module diagram of the intelligent detection system for silicone polyurethane preparation in the embodiments of the present application; Figure 2 Workflow diagram of the intelligent detection system for silicone polyurethane preparation in the embodiments of the present application; Figure 3A flow chart for judging the unqualified reason based on the isocyanate group content in the polyurethane prepolymer in the embodiment of the present application; Figure 4 A flow chart for reducing the cooling rate during the preparation of the prepolymer precursor based on the difference of the holding time in the embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to make the objects and advantages of the present application clearer, the present application will be further described below in conjunction with embodiments. It should be understood that the specific embodiments described herein merely serve the purpose of explaining the present application and are not intended to limit the present application.

[0026] The preferred embodiments of the present application will be described below with reference to the drawings. It should be understood by those skilled in the art that the embodiments merely serve the purpose of explaining the technical principles of the present application and are not intended to limit the protection scope of the present application.

[0027] Please refer to Figure 1 As shown in the figure, it is a module diagram of the intelligent detection system for the preparation of siloxane polyurethane in the embodiment of the present application. The intelligent detection system for the preparation of siloxane polyurethane in the embodiment of the present application comprises a vacuum dehydration module, a prepolymer precursor preparation module, a reduced pressure distillation module, a siloxane polyurethane preparation module, a detection module, an optimization module and an execution module, wherein, The vacuum dehydration module is used to remove the water in the polyol. The prepolymer precursor preparation module is connected with the vacuum dehydration module and is used to prepare the polyurethane prepolymer precursor. The reduced pressure distillation module is connected with the prepolymer precursor preparation module and is used to remove the solvent in the polyurethane prepolymer precursor to obtain the polyurethane prepolymer. The siloxane polyurethane preparation module is connected with the reduced pressure distillation module and is used to prepare the siloxane polyurethane. The detection module comprises a plurality of sensors, a tensile testing machine, a potentiometric titrator and a thermogravimetric analyzer and is used to detect the quality parameters of the siloxane polyurethane and the temperature change during the preparation of the siloxane polyurethane. The optimization module is connected with the detection module and is used to judge whether the quality of the siloxane polyurethane is qualified based on the variance of the crosslinking density at each point in the siloxane polyurethane, to judge the unqualified reason based on the isocyanate group content in the polyurethane prepolymer when it is unqualified, and to issue the instruction for correcting the vacuum dehydration parameters, the prepolymer precursor preparation parameters and the siloxane polyurethane preparation parameters based on the unqualified reason. The execution module is connected with the optimization module, the vacuum dehydration module, the prepolymer precursor preparation module and the siloxane polyurethane preparation module and is used to control the corresponding modules to execute based on the instruction.

[0028] The crosslinking density test method in the detection module is not limited in principle, and a skilled person can select different test methods according to the morphology of the siloxane polyurethane, for example, the siloxane polyurethane in solid state is tested by stress-strain method, and the siloxane polyurethane in liquid or colloidal state is tested by equilibrium swelling method.

[0029] Please refer to Figure 2 As shown in the working flowchart of the intelligent detection system for preparing siloxane polyurethane in the embodiment of the present application, the working flow of the intelligent detection system for preparing siloxane polyurethane in the embodiment of the present application is as follows: S1: The vacuum dehydration module removes water in the polyol in a vacuum high-temperature environment; S2: The prepolymer precursor preparation module heats the mixed polyisocyanate and polyol to a certain temperature under nitrogen protection to react, and after the reaction is completed, a terminator is added to terminate the reaction to obtain a polyurethane prepolymer precursor; S3: The reduced pressure distillation module removes the solvent in the polyurethane prepolymer precursor to obtain a polyurethane prepolymer; S4: The siloxane polyurethane preparation module mixes and cures the fully mixed organofunctional silane and the polyurethane prepolymer precursor at a certain temperature to prepare a siloxane polyurethane; S5: The detection module detects the quality parameters of the siloxane polyurethane and the temperature change in the process of preparing the siloxane polyurethane; S6: The optimization module determines the quality of the siloxane polyurethane based on the crosslinking density variance of each point in the siloxane polyurethane, and determines the unqualified reason based on the isocyanate group content in the polyurethane prepolymer when the quality is unqualified, and issues instructions for correcting the vacuum dehydration parameters, the prepolymer precursor preparation parameters and the siloxane polyurethane preparation parameters; S7: The execution module controls the corresponding module to execute based on the instructions.

[0030] Further, the optimization module is used to determine the crosslinking density variance based on the variance of the crosslinking density of each point in the siloxane polyurethane, and determine whether the quality of the siloxane polyurethane is qualified based on the crosslinking density variance, and maintain the system parameters when the quality is qualified, or determine the unqualified reason based on the isocyanate group content in the polyurethane prepolymer when the quality is unqualified.

[0031] Crosslinking density is a physical quantity that measures the number of crosslinking points per unit volume in a polymer network, which directly affects the mechanical properties, thermal stability, chemical resistance and other key performance indicators of siloxane polyurethane. Crosslinking density variance refers to the variance of crosslinking density at different points in the siloxane polyurethane. The crosslinking density variance reflects the difference in crosslinking density between different points. A small crosslinking density variance indicates that the crosslinking density at different points is uniform and consistent, and the structure of the siloxane polyurethane is uniform and stable and reliable. A large variance indicates that the crosslinking density is not uniform in space distribution, and there are local low-crosslinking regions or structural defects, which may result in substandard mechanical properties and reduced durability. According to the principles of material science and polymer processing, a uniform crosslinking network is necessary for high-performance siloxane polyurethane. Therefore, as a quantitative indicator, the crosslinking density variance can objectively reflect the control effect of mixing uniformity, reaction degree, curing process and other links in the preparation process. Using it as a quality judgment standard is a scientific and practical approach.

[0032] Specifically, the process of determining whether the quality of the siloxane polyurethane is qualified based on the crosslinking density variance by the optimization module includes: The optimization module determines the crosslinking density variance A based on the variance of the crosslinking density at different points in the siloxane polyurethane, and compares the crosslinking density variance A with a preset crosslinking density variance A M 1. 1. 液体 1∈[9×10 -11 , 9×10 -10 ], A 胶体 1∈[1.5×10 -8 , 9×10 -6 ], A 弹性体 1∈[1.5×10 -9 , 1.5×10 -6 ], the siloxane polyurethane in liquid, gel and elastomer forms each has its general reference range of crosslinking density and quality judgment standard. The crosslinking density of liquid siloxane polyurethane is very low or almost no crosslinking, usually less than 10 -6 mol / cm³, which is mainly a linear or low-crosslinking polymer that maintains good flowability; if the crosslinking density is significantly higher than this range (such as greater than 10 -5 mol / cm³), it may result in decreased flowability, gel formation and unqualified quality; the crosslinking density of gel siloxane polyurethane is about 10 -5 to 10 -4 mol / cm³, which exhibits a partially crosslinked, high-viscoelastic gel state; if it is lower than 10 -5 mol / cm³, the crosslinking is insufficient and the gel performance is poor; if it is higher than 10 -4 mol / cm³, the crosslinking is excessive and the gel performance is poor.A crosslinking density of mol / cm³ may indicate a solid or elastomer-like structure, leading to substandard quality in colloidal products. The crosslinking density of the elastomer siloxane polyurethane is approximately 10. -4 Up to 10 -3 mol / cm³, high cross-linking gives it good elasticity and mechanical properties; if it is below 10 -4 A concentration of mol / cm³ may result in insufficient mechanical strength and elasticity of the elastomer, leading to substandard quality; if it exceeds approximately 2 × 10⁻⁶ mol / cm³, it may cause the elastomer to fail to meet quality standards. -3 If the crosslinking density variance is too high (e.g., mol / cm³), the material may become excessively rigid and brittle, affecting its performance and manufacturing process, and the quality will be considered substandard. Therefore, the preset crosslinking density variance range is set to A. 液体 1∈[9×10 -11 9×10 -10 A 胶体 1∈[1.5×10 -8 9×10 -6 A 弹性体 1∈[1.5×10 -9 1.5×10 -6 ]; If the crosslinking density variance A is less than or equal to the preset crosslinking density variance A1, the optimization module determines that the quality of the siloxane polyurethane is qualified and maintains the system parameters. If the crosslinking density variance A is greater than the preset crosslinking density variance A1, the optimization module determines that the quality of the siloxane polyurethane is unqualified, and the optimization module determines the reason for the unqualification based on the isocyanate group content in the polyurethane prepolymer.

[0033] Furthermore, the optimization module is also used to determine the reason for non-compliance based on the isocyanate group content in the polyurethane prepolymer, and, when the preparation of the polyurethane prepolymer precursor is determined to be unqualified, to determine the reason for non-compliance based on the average carbon dioxide concentration in the tail gas periodically collected during the preparation of the polyurethane prepolymer precursor, or, when the preparation of the siloxane polyurethane is determined to be unqualified, to determine the reason for non-compliance based on the variance of the second derivative of the differential thermogravimetric curve at different temperatures.

[0034] During the polymerization reaction, NCO groups (isocyanate groups) react with hydroxyl groups in polyols to form polyurethane prepolymers. Therefore, changes in their content reflect the sufficiency of the reaction. Low NCO content usually indicates over-reaction or excessive moisture content leading to NCO being consumed by water, which are process abnormalities. By monitoring the NCO content in the prepolymer, abnormalities in the preparation process of siloxane polyurethane can be identified, abnormal steps in the preparation process of siloxane polyurethane can be quickly located, and targeted corrective measures can be taken to ensure the preparation quality of siloxane polyurethane.

[0035] Please see Figure 3As shown, it is a flow chart for judging the unqualified reason based on the isocyanate group content in the polyurethane prepolymer in the embodiment of the application. The process of the optimization module for judging the unqualified reason based on the isocyanate group content in the polyurethane prepolymer includes: The optimization module acquires the isocyanate group content B in the polyurethane prepolymer, and compares the isocyanate group content B in the polyurethane prepolymer with the preset prepolymer isocyanate group content B M 1. Comparison, M is liquid, colloid, elastomer, wherein the preset prepolymer isocyanate group content B is set 液体 1∈[0.5, 2wt%], B 胶体 1∈[2, 4wt%], B 弹性体 1∈[3, 6wt%], in the silicone polyurethane prepolymer, the isocyanate group (-NCO) content is a key indicator for measuring the reaction degree and performance of the prepolymer, and the content varies with the form (liquid, colloidal, elastomer) of the prepolymer. The NCO content of the liquid prepolymer is usually between 0.5% and 2.0 wt% to maintain a low molecular weight and good flowability, facilitating subsequent reactions and film formation; the NCO content of the colloidal prepolymer is between 2.0% and 4.0 wt%, with a certain degree of crosslinking and a higher molecular weight, forming a colloidal structure; the NCO content of the elastomer prepolymer is between 3.0% and 6.0 wt% to ensure sufficient crosslinking and high crosslinking density, thereby obtaining excellent mechanical properties and elasticity.

[0036] If the isocyanate group content B in the polyurethane prepolymer is less than or equal to the preset prepolymer isocyanate group content B M 1, the optimization module judges that the preparation of the polyurethane prepolymer precursor is unqualified. The optimization module judges the unqualified reason based on the average value of the carbon dioxide concentration in the tail gas periodically collected during the preparation process of the polyurethane prepolymer precursor; If the isocyanate group content B in the polyurethane prepolymer is greater than the preset prepolymer isocyanate group content B M 1, the optimization module judges that the preparation of the silicone polyurethane is unqualified, and the optimization module judges the unqualified reason based on the variance of the second derivative of the differential thermal gravimetric curve at different temperatures.

[0037] Further, the optimization module is further configured to determine an average carbon dioxide concentration based on the periodically collected average carbon dioxide concentration in the exhaust gas during the preparation of the polyurethane prepolymer precursor, determine the cause of failure based on the average carbon dioxide concentration, and correct the holding time of the polyurethane prepolymer precursor preparation module based on the preset prepolymer isocyanate group content and the isocyanate group content ratio set in the polyurethane prepolymer when it is determined that the termination of the termination agent is not timely, or correct the vacuum degree of the polyol water removal in the vacuum dehydration module based on the difference between the average carbon dioxide concentration and the preset average carbon dioxide concentration when it is determined that the polyol water removal effect does not meet the standard.

[0038] When the abnormal step is located to the prepolymer precursor preparation stage, the reasons for the low NCO content may include two kinds, one is that the reaction is excessive, causing the NCO to be excessively consumed, affecting the subsequent reaction, and the other is that the polyol dehydration stage is not sufficient, causing the residual water in the polyol to react with the NCO, thereby causing the consumption of NCO; In the preparation process of the polyurethane prepolymer, the residual water in the polyol reacts with the polyisocyanate (-NCO) to generate carbon dioxide, therefore, the increase of the carbon dioxide concentration in the exhaust gas is a direct sign of the abnormal consumption of NCO due to the excessive water content, when the dehydration treatment is insufficient, the average carbon dioxide concentration in the exhaust gas will be significantly higher than the preset standard value, indicating that the water removal effect is not ideal; When the termination agent cannot terminate the reaction in time (at this time, the abnormal consumption of NCO is due to excessive reaction, not water consumption, therefore, no carbon dioxide is generated), the carbon dioxide in the exhaust gas will not be affected, therefore, by combining the changes of carbon dioxide concentration and NCO content, the present application can accurately determine the abnormal reason of the polyurethane prepolymer preparation stage, thereby realizing the rapid positioning of the fault and the precise control of the preparation process, and ensuring the product consistency and quality.

[0039] Specifically, the process of determining the cause of failure based on the average carbon dioxide concentration by the optimization module includes: The optimization module determines the average carbon dioxide concentration C based on the periodically collected average carbon dioxide concentration in the exhaust gas during the preparation of the polyurethane prepolymer precursor, and compares the average carbon dioxide concentration C with the preset average carbon dioxide concentration C1, wherein the preset average carbon dioxide concentration C1 ∈ [0, 5 ppm], in the operation of strict water-free, airtight and pure, theoretically, carbon dioxide is not generated, but in the actual preparation process, trace impurities in some solvents or ingredients may cause trace background CO2 to be detected during detection, therefore, the preset average carbon dioxide concentration C1 ∈ [0, 5 ppm] is set.

[0040] If the average carbon dioxide concentration C is less than or equal to the preset average carbon dioxide concentration C1, the optimization module determines that the stopping agent does not stop in time, and the optimization module corrects the holding time of the prepolymer precursor preparation module based on the preset ratio of the preset isocyanate group content to the isocyanate group content in the polyurethane prepolymer precursor. If the average carbon dioxide concentration C is greater than the preset average carbon dioxide concentration C1, the optimization module determines that the polyol water removal effect does not meet the standard, and the optimization module corrects the vacuum degree when the polyol water is removed by the vacuum dehydration module based on the difference between the average carbon dioxide concentration and the preset average carbon dioxide concentration.

[0041] Further, the optimization module is also used to determine the isocyanate group ratio based on the ratio of the preset isocyanate group content to the isocyanate group content in the polyurethane prepolymer precursor, and shorten the holding time of the prepolymer precursor preparation module based on the isocyanate group ratio, and the shortening range of the holding time is directly proportional to the isocyanate group ratio.

[0042] The isocyanate group content is a very important active group in the polyurethane prepolymer reaction, and its content directly reflects the reaction progress and the remaining reaction activity. The preset isocyanate group content is usually a reference value corresponding to the ideal reaction degree, representing the target conversion degree of the prepolymer reaction. The isocyanate group ratio refers to the ratio of the preset isocyanate group content to the isocyanate group content in the polyurethane prepolymer precursor, which reflects the deviation degree of the actual reaction from the expected reaction. When the actually measured isocyanate group content is lower than the preset value, it means that the prepolymer reaction has proceeded excessively, and the NCO group has been consumed too much, which may lead to the degradation of the properties of the prepolymer. At this time, shortening the holding time can help the stopping agent to stop the reaction in time to avoid excessive reaction and reduce the occurrence of side reactions, thereby improving the product quality. Secondly, by making the shortening range of the holding time directly proportional to the isocyanate group ratio, flexible adjustment based on actual deviation can be achieved, precise control can be achieved, and the intelligentization and automation level of the reaction process can be improved. In this way, experience-based fixed time adjustment is avoided, and production efficiency and product consistency are improved. In summary, this dynamic adjustment method based on the actual reaction degree can effectively prevent excessive or insufficient reaction, improve product quality and efficiency, and at the same time improve the sensitivity and accuracy of the intelligent control system, realizing closed-loop control.

[0043] Specifically, the process of shortening the holding time of the prepolymer precursor by the optimization module based on the isocyanate group ratio includes: The optimization module determines an isocyanate group ratio D based on a ratio of the preset isocyanate group content to the isocyanate group content in the polyurethane prepolymer precursor, and compares the isocyanate group ratio D with a set first preset isocyanate group ratio D1 and a second preset isocyanate group ratio D2, wherein the first preset isocyanate group ratio D1 is set to be in a range of 1.05 to 1.15, and the second preset isocyanate group ratio D2 is set to be in a range of 1.15 to 1.25. Most polyurethane production processes allow a fluctuation of NCO content within a range of about 5%, and the corresponding ratio of 1.05 is a reasonable sensitive early warning threshold. The Polyurethane Industrial Production Process Guide (industry general reference material) indicates that when the NCO deviates from the target by 5%-10%, the process parameters need to be corrected, and some polyurethane production enterprises in the European Union and the United States mention that when the NCO content error reaches 15%-25%, a larger amplitude of correction of preparation parameters is needed to avoid the impact on the subsequent process; If the isocyanate group ratio D is less than or equal to the first preset isocyanate group ratio D1, the optimization module corrects the prepolymer precursor holding time by using a first holding time correction threshold a1, and the corrected prepolymer precursor holding time T' = T x a1, wherein the first holding time correction threshold a1 is set to be 0.95. If the isocyanate group ratio D is greater than the first preset isocyanate group ratio D1 and less than or equal to the second preset isocyanate group ratio D2, the optimization module corrects the prepolymer precursor holding time by using a second holding time correction threshold a2, and the corrected prepolymer precursor holding time T' = T x a2, wherein the second holding time correction threshold a2 is set to be 0.89. If the isocyanate group ratio D is greater than the second preset isocyanate group ratio D2, the optimization module corrects the prepolymer precursor holding time by using a third holding time correction threshold a3, and the corrected prepolymer precursor holding time T' = T x a3, wherein the third holding time correction threshold a3 is set to be 0.8.

[0044] Further, the optimization module is also used to determine a holding time difference based on the difference between the holding time before and after correction, and to reduce the prepolymer precursor preparation module cooling rate when preparing the prepolymer precursor based on the holding time difference, and the reduction amplitude of the cooling rate is proportional to the holding time difference.

[0045] The holding time is a key parameter of the polyurethane prepolymer reaction. Although shortening the holding time can help the terminator to terminate the reaction in time, there may still be some reactants in the incomplete or slow stage of reaction. If the temperature is rapidly reduced at this time, the molecular movement and reaction rate of the reaction system will sharply decrease, which may lead to uneven structure or incomplete termination of the polyurethane prepolymer reaction, affecting the uniformity and quality of the polyurethane prepolymer. Therefore, reducing the cooling rate can allow the reaction system to remain at a lower temperature for a longer period of time, promote the slow and sufficient crosslinking reaction between the remaining isocyanate groups and hydroxyl groups, improve the completeness of the reaction, and alleviate the internal stress and unevenness that may be caused by rapid cooling, promote the further rearrangement of molecular chains and structure optimization, and thus obtain a more uniform and stable prepolymer. In addition, the reduction amplitude of the cooling rate is proportional to the difference between the holding times, because the greater the difference between the holding times, the more obvious the influence on the reaction completeness, and a greater reduction amplitude of the cooling rate is needed to compensate for the deficiency caused by the shortening of the holding time to avoid structural defects. Conversely, the difference between the holding times is small, and the reaction is basically close to the expected degree, so only a slight reduction in the cooling rate is needed to achieve reaction compensation and performance stability. This design ensures the dynamic optimization of process parameters and the reliability of the performance of the reaction system, which helps the intelligent system to automatically adjust the process according to the real-time detection results, improves the preparation efficiency and product quality.

[0046] Please refer to Figure 4 The process of the optimization module for reducing the cooling rate during the preparation of the prepolymer precursor based on the difference between the holding times is shown in the flowchart of FIG. 1. The process of the optimization module for reducing the cooling rate during the preparation of the prepolymer precursor based on the difference between the holding times includes the following steps: The optimization module determines the holding time difference E based on the difference between the holding times of the prepolymer precursor before and after correction, and compares the holding time difference E with the set first preset holding time difference E1 and second preset holding time difference E2, wherein the first preset holding time difference E1 is set to be in the range of [0.05, 0.4h), and the second preset holding time difference E2 is set to be in the range of [0.4, 0.8h]. The holding time of the polyurethane prepolymer mainly depends on factors such as the formula of the reaction system, the reaction temperature, the molar ratio of isocyanate to polyol, the type and amount of catalyst, etc. Generally, the holding time of the polyurethane prepolymer is about 1 to 4 hours, so the value range of the first preset holding time difference E1 is 0.05-0.4h, and the value range of the second preset holding time difference E2 is 0.4-0.8h. If the holding time difference E is less than or equal to the first preset holding time difference E1, the optimization module corrects the cooling rate V during the preparation of the prepolymer precursor by using the first cooling rate correction threshold β1, and the corrected cooling rate V' = V x β1, wherein the first cooling rate correction threshold β1 is set to be 0.98. If the holding time difference E is greater than the first preset holding time difference E1 and less than or equal to the second preset holding time difference E2, the optimization module corrects the cooling rate V during the preparation of the prepolymer precursor by using a second cooling rate correction threshold β2, and the corrected cooling rate V' = V x β2, wherein the second cooling rate correction threshold β2 is set to 0.95; If the holding time difference E is greater than the second preset holding time difference E2, the optimization module corrects the cooling rate V during the preparation of the prepolymer precursor by using a third cooling rate correction threshold β3, and the corrected cooling rate V' = V x β3, wherein the third cooling rate correction threshold β3 is set to 0.9.

[0047] Further, the optimization module is also used to determine the carbon dioxide concentration difference based on the difference between the average carbon dioxide concentration and the preset average carbon dioxide concentration, and increase the vacuum degree of the vacuum dehydration module when removing the water in the polyol based on the carbon dioxide concentration difference, and the increase in the vacuum degree is proportional to the carbon dioxide concentration difference.

[0048] The water in the polyol is extremely critical in the preparation of polyurethane, and the residual water will affect the reaction of isocyanate, produce carbon dioxide and other byproducts, and cause incomplete reaction or performance degradation of the product. By periodically collecting the carbon dioxide concentration in the tail gas, the amount of residual water in the polyol can be indirectly reflected. If the carbon dioxide concentration is detected to be higher than the preset standard, it indicates that the water removal is not complete, and the vacuum degree of the vacuum dehydration module must be increased (i.e. the system pressure is reduced) to enhance the water evaporation capacity and accelerate the removal of water from the polyol. The higher the vacuum degree, the lower the boiling point of water, which is beneficial to the removal of water at a lower temperature, prevents thermal damage to the material, and improves the dehydration rate and efficiency. In addition, the greater the carbon dioxide concentration difference, the more residual water, the more serious the problem of insufficient dehydration, and the greater the increase in the vacuum degree is needed to enhance the dehydration intensity to ensure that the water can be effectively removed, thereby reducing the generation of carbon dioxide in the tail gas. Conversely, a smaller concentration difference means that the dehydration is close to the ideal state, and the adjustment amplitude can be appropriately reduced to avoid unnecessary energy consumption or equipment burden. This linear adjustment relationship ensures the flexibility of the dehydration process and the precision of the automatic adjustment, achieving efficient and energy-saving dehydration control. In summary, this design uses carbon dioxide concentration as an intelligent feedback indicator for the residual water in the polyol, dynamically and flexibly adjusts the vacuum dehydration conditions based on the feedback results, improves the dehydration quality and efficiency, realizes automatic and precise control of the system, avoids human errors, ensures the stability of the silicone polyurethane preparation process and the consistency of the product performance, and fully embodies the linkage of intelligent detection and optimization module to promote the intelligent upgrading of the production process.

[0049] Specifically, the process of increasing the vacuum degree of the vacuum dehydration module based on the carbon dioxide concentration difference to remove the water in the polyol includes: The optimization module is further configured to determine a carbon dioxide concentration difference F based on a difference between the average value of the carbon dioxide concentration and a preset average value of the carbon dioxide concentration, and compare the carbon dioxide concentration difference F with a first preset carbon dioxide concentration difference F1 and a second preset carbon dioxide concentration difference F2, wherein the first preset carbon dioxide concentration difference F1 is set to be in a range of [1, 5ppm), and the second preset carbon dioxide concentration difference F2 is set to be in a range of [5, 15ppm]. Some studies have shown that when the carbon dioxide concentration is found to be between 5 and 10 ppm, the water removal effect is slightly insufficient, and the vacuum degree can be appropriately increased to correct it. When the carbon dioxide concentration is between 10 and 20 ppm, the water removal effect is poor, and a greater adjustment is needed.

[0050] If the carbon dioxide concentration difference F is less than or equal to the preset carbon dioxide concentration difference F1, the optimization module corrects the vacuum degree X for removing water in the polyol by using a first vacuum correction threshold θ1, and the corrected vacuum degree X' = X x θ1, wherein the first vacuum correction threshold θ1 is set to be 1.03. If the carbon dioxide concentration difference F is greater than the preset carbon dioxide concentration difference F1 and less than or equal to the second preset carbon dioxide concentration difference F2, the optimization module corrects the vacuum degree X for removing water in the polyol by using a second vacuum correction threshold θ2, and the corrected vacuum degree X' = X x θ2, wherein the second vacuum correction threshold θ2 is set to be 1.07. If the carbon dioxide concentration difference F is greater than the second preset carbon dioxide concentration difference F2, the optimization module corrects the vacuum degree X for removing water in the polyol by using a third vacuum correction threshold θ3, and the corrected vacuum degree X' = X x θ3, wherein the third vacuum correction threshold θ3 is set to be 1.12.

[0051] Further, the optimization module is further configured to determine a variance of the second derivative of the differential thermal gravimetric curve based on the variance of the second derivative of the differential thermal gravimetric curve at different temperatures, and determine the cause of the unqualified quality based on the variance of the second derivative of the differential thermal gravimetric curve. When it is determined that the curing temperature of the siloxane polyurethane is not uniform, the curing time of the polyurethane prepolymer and the organofunctional silane in the siloxane polyurethane preparation module is corrected based on the difference between the minimum temperature and the maximum temperature of the siloxane polyurethane precursor during curing. When it is determined that the polyurethane prepolymer and the organofunctional silane are not mixed uniformly, the amount of solvent added in the siloxane polyurethane preparation process in the siloxane polyurethane preparation module is corrected based on the ratio between the viscosity of the polyurethane prepolymer and the organofunctional silane mixture and the preset viscosity.

[0052] Thermogravimetric analysis (TGA) provides information on thermal stability, decomposition process and reaction of materials by detecting the change of mass with temperature increasing. The differential thermogravimetric curve (DTG) as the first derivative of the thermogravimetric curve can clearly show the decomposition temperature and decomposition stage, and its second derivative has higher sensitivity to capture subtle reaction transitions and stage characteristics in the curing process. If the internal structure of the siloxane polyurethane is uniform and the crosslinking density is consistent, the second derivative curve of the DTG in the same temperature range is relatively stable, and the variance is small; otherwise, if the sample has uneven curing, uneven component distribution or incomplete reaction, the variance will increase. As a statistical dispersion index, the variance can quantify the uniformity of the reaction or decomposition behavior and provide quantitative judgment basis for quality abnormalities. This method is non-destructive, fast and can identify quality defects caused by the process. When the curing temperature is determined to be uneven, the quality can be improved by adjusting the curing time; when the mixing is determined to be uneven, the mixing uniformity can be improved by adjusting the amount of solvent. In summary, using the second derivative variance of the differential thermogravimetric curve as a quality judgment index can effectively reflect the quality unevenness and defect problems in the preparation of siloxane polyurethane, provide accurate feedback information for the intelligent optimization system, guide the dynamic adjustment of process parameters, and improve the product consistency and performance stability.

[0053] Specifically, the process of determining the reason for quality failure based on the second derivative variance of the differential curve by the optimization module includes: The optimization module is also used to determine the second derivative variance H of the differential curve based on the variance of the second derivative of the differential thermogravimetric curve at different temperatures, and compare the second derivative variance H of the differential curve with the preset second derivative variance H1 of the differential curve, wherein the preset second derivative variance H1 of the differential curve is not limited in principle and can be derived according to the actual situation and the law of historical data. If the second derivative variance H of the differential curve is less than or equal to the preset second derivative variance H1 of the differential curve, the optimization module determines that the curing temperature of the siloxane polyurethane is uneven, and the optimization module corrects the curing time of the polyurethane prepolymer and the organofunctional silane based on the difference between the lowest temperature and the highest temperature of the siloxane polyurethane precursor during curing. If the second derivative variance H of the differential curve is greater than the preset second derivative variance H1 of the differential curve, the optimization module determines that the mixing of the polyurethane prepolymer and the organofunctional silane is uneven, and the optimization module corrects the amount of solvent added in the preparation process of the siloxane polyurethane based on the difference between the viscosity of the polyurethane prepolymer and the organofunctional silane mixture and the preset preset viscosity.

[0054] Further, the optimization module is further configured to determine a curing temperature difference based on a difference between a lowest temperature and a highest temperature of the siloxane polyurethane precursor during curing, and extend a curing time of the polyurethane prepolymer and the organofunctional silane by the siloxane polyurethane preparation module based on the curing temperature difference, and the extension of the curing time is proportional to the curing temperature difference.

[0055] The curing temperature difference refers to a difference between a lowest temperature and a highest temperature of the siloxane polyurethane precursor during curing, and the curing temperature difference reflects a temperature uniformity of the curing process, and a larger difference means that there is a significant temperature gradient in the system, resulting in uneven curing, affecting crosslinking density and mechanical properties. Secondly, extending the curing time helps to complete the curing reaction in the low temperature area, ensuring the overall curing quality. The larger the curing temperature difference, the greater the difference in reaction rate, and the longer the curing time needed to compensate. This extension strategy proportional to the curing temperature difference realizes the dynamic adjustment of the curing time, which not only avoids the waste of energy and cost caused by too long curing time, but also prevents incomplete curing. Through the combination of intelligent detection and control modules, this strategy guarantees the integrity and consistency of the curing in the preparation process of the siloxane polyurethane, effectively avoids structural defects and performance fluctuations caused by uneven temperature, and improves the qualified rate of finished products and the stability of mechanical properties.

[0056] Specifically, the process of extending the curing time of the polyurethane prepolymer and the organofunctional silane based on the curing temperature difference by the optimization module includes: The optimization module determines a curing temperature difference G based on a difference between a lowest temperature and a highest temperature of the siloxane polyurethane precursor during curing, and compares the curing temperature difference G with a first preset curing temperature difference G1 and a second preset curing temperature difference G2, wherein the first preset curing temperature difference G1 ∈ (3, 5) and the second preset curing temperature difference G2 ∈ [5, 7], and the temperature uniformity of the polymer curing system is usually recommended to be controlled within ±3℃ to ensure uniform crosslinking; when the temperature difference exceeds 5℃, the curing quality may be affected, and when the temperature difference is greater than 7℃, there is usually obvious uneven performance or defects, so the value range of the first preset curing temperature difference is set to 3-5℃, and the value range of the second preset curing temperature difference is set to 5-7℃. If the curing temperature difference G is less than or equal to the first preset curing temperature difference G1, the optimization module adopts a first curing time correction threshold The curing time K of the polyurethane prepolymer and the organofunctional silane is corrected, and the corrected curing time K' of the polyurethane prepolymer and the organofunctional silane is K'=K× , wherein the first curing time correction threshold is set to 1.05. If the curing temperature difference G is greater than the first preset curing temperature difference G1 and less than or equal to the second preset curing temperature difference G2, the optimization module adopts a second curing time correction threshold corrects the curing time K of the polyurethane prepolymer and organofunctional silane, and the corrected curing time K' of the polyurethane prepolymer and organofunctional silane is K'=K x , wherein the second curing time correction threshold =1.11 is set. If the curing temperature difference G is greater than the second preset curing temperature difference G2, the optimization module adopts a third curing time correction threshold corrects the curing time K of the polyurethane prepolymer and organofunctional silane, and the corrected curing time K' of the polyurethane prepolymer and organofunctional silane is K'=K x , wherein the third curing time correction threshold =1.2 is set.

[0057] Further, the optimization module is also used to determine a viscosity ratio based on the ratio between the viscosity of the polyurethane prepolymer and organofunctional silane mixture and the set preset viscosity, and to increase the amount of solvent added in the silicone polyurethane preparation module based on the viscosity ratio, and the increase in the amount of solvent added is directly proportional to the viscosity ratio.

[0058] The viscosity ratio refers to the difference between the viscosity of the polyurethane prepolymer and organofunctional silane mixture and the set preset viscosity, which reflects the difference in flowability and component uniformity of the polyurethane prepolymer and organofunctional silane mixture compared to the ideal polyurethane prepolymer and organofunctional silane mixture. Proportional increase in solvent amount can achieve precise control, avoid insufficient or excessive solvent, and linear adjustment strategy can improve adjustment efficiency and avoid excessive adjustment at one time, which may cause other process and performance problems. This proportional adjustment ensures the precision and flexibility of intelligent control of the system, improves the stability of the overall production and the consistency of product quality, and reasonable increase in solvent amount helps to reduce the local viscosity of the mixture, improve the mixing uniformity, reduce the local crosslinking density difference, and further promote the product performance stability. This design reflects the high synergy of intelligent detection and feedback control system, and through precise and dynamic process parameter adjustment, the ideal viscosity and uniformity of the silicone polyurethane mixing system are realized, which ensures the stability of the subsequent curing and product performance, thereby improving the production efficiency and product quality.

[0059] Specifically, the process of increasing the amount of solvent added in the silicone polyurethane preparation process based on the viscosity ratio includes: The optimization module is also used to determine a viscosity ratio P based on a difference between the viscosity of the polyurethane prepolymer and the organofunctional silane mixture and a set preset viscosity, and compare the viscosity ratio P with a set first preset viscosity ratio P1 and a second preset viscosity ratio P2, wherein the first preset viscosity ratio P1 is set to be in [1.05, 1.1], and the second preset viscosity ratio P2 is set to be in [1.1, 1.15]. In actual silicone polyurethane production, it is found that a 5%-10% increase in the viscosity of the polyurethane prepolymer and the organofunctional silane mixture usually belongs to the process fluctuation allowable range, but has begun to affect the mixing uniformity, and a moderate adjustment of the solvent can be made. When the viscosity increases by more than 15%, it usually indicates a more serious mixing abnormality, and a larger adjustment effort is required. Therefore, in the present scheme, the first preset viscosity ratio P1 is set to be in [1.05, 1.1], and the second preset viscosity ratio P2 is set to be in [1.1, 1.15].

[0060] If the viscosity ratio P is less than or equal to the first preset viscosity ratio P1, the optimization module corrects the solvent addition amount R in the silicone polyurethane preparation process by using a first solvent correction threshold λ1, and the corrected solvent addition amount R' = R x λ1, wherein the first solvent correction threshold λ1 is set to be 1.1. If the viscosity ratio P is greater than the first preset viscosity ratio P1 and less than or equal to the second preset viscosity ratio P2, the optimization module corrects the solvent addition amount R in the silicone polyurethane preparation process by using a first solvent correction threshold λ2, and the corrected solvent addition amount R' = R x λ2, wherein the first solvent correction threshold λ2 is set to be 1.22. If the viscosity ratio P is greater than the second preset viscosity ratio P2, the optimization module corrects the solvent addition amount R in the silicone polyurethane preparation process by using a third solvent correction threshold λ3, and the corrected solvent addition amount R' = R x λ3, wherein the third solvent correction threshold λ3 is set to be 1.35.

[0061] The application provides a kind of intelligent detection system for siloxane polyurethane preparation, by setting multiple modules work cooperatively, realized the comprehensive detection and optimization control of siloxane polyurethane preparation process.Vacuum dehydration module can effectively remove water in polyol, avoid the influence of water on subsequent reaction;Prepolymer precursor preparation module, vacuum distillation module and siloxane polyurethane preparation module are connected in sequence, ensure the continuity and stability of preparation process;Detection module can detect the crosslinking density of siloxane polyurethane and the temperature change of preparation process and other key parameters in real time, provide accurate basis for quality control;Optimization module judges product quality based on detection results, and quickly locates the cause when unqualified, issues correction instruction;Execution module then accurately controls each module according to the instruction, realizes the automation and intelligent control of preparation process, effectively solves the problem of lack of control in existing preparation process, and it is difficult to quickly locate and correct when product problem occurs, improves the quality stability and consistency of siloxane polyurethane finished product, reduces production cost, improves production efficiency.

[0062] So far, the technical scheme of the application has been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to related technical features without departing from the principles of the application, and the technical scheme after the changes or replacements will fall within the protection scope of the application.

Claims

1. A smart detection system for silicone polyurethane preparation, characterized by, The system comprises: a vacuum dehydration module for removing water from the polyol; a prepolymer precursor preparation module connected to the vacuum dehydration module for preparing a polyurethane prepolymer precursor; a vacuum distillation module connected to the prepolymer precursor preparation module for removing solvent from the polyurethane prepolymer precursor to obtain a polyurethane prepolymer; a siloxane polyurethane preparation module connected to the vacuum distillation module for preparing a siloxane polyurethane; a detection module comprising a plurality of sensors, a tensile testing machine, a potentiometric titrator and a thermogravimetric analyzer for detecting crosslinking density at each point in the siloxane polyurethane and temperature change during preparation of the siloxane polyurethane; an optimization module connected to the detection module for determining whether the quality of the siloxane polyurethane is qualified based on variance of crosslinking density at each point in the siloxane polyurethane, and, when the quality is not qualified, determining the cause of unqualification based on isocyanate group content in the polyurethane prepolymer, and issuing an instruction to correct vacuum dehydration parameters, prepolymer precursor preparation parameters and siloxane polyurethane preparation parameters based on the cause of unqualification; an execution module connected to the optimization module, the vacuum dehydration module, the prepolymer precursor preparation module and the siloxane polyurethane preparation module for controlling the corresponding modules to execute based on the instruction.

2. The intelligent detection system of claim 1, wherein, The optimization module is configured to determine crosslinking density variance based on variance of crosslinking density at each point in the siloxane polyurethane, and determine whether the quality of the siloxane polyurethane is qualified based on the crosslinking density variance, and, when the quality is qualified, maintain system parameters, or, when the quality is not qualified, determine the cause of unqualification based on isocyanate group content in the polyurethane prepolymer.

3. The intelligent detection system of claim 2, wherein, The optimization module is further configured to determine the cause of unqualification based on isocyanate group content in the polyurethane prepolymer, and, when the preparation of the polyurethane prepolymer precursor is not qualified, determine the cause of unqualification based on average value of carbon dioxide concentration in exhaust gas periodically collected during preparation of the polyurethane prepolymer precursor, or, when the preparation of the siloxane polyurethane is not qualified, determine the cause of unqualification based on variance of second derivative of differential thermogravimetric curve at different temperatures.

4. The intelligent detection system of claim 3, wherein, The optimization module is further configured to determine average value of carbon dioxide concentration based on average value of carbon dioxide concentration in exhaust gas periodically collected during preparation of the polyurethane prepolymer precursor, and determine the cause of unqualification based on the average value of carbon dioxide concentration, and, when the blocking agent does not block in time, correct holding time of the prepolymer precursor preparation module based on a ratio of preset isocyanate group content in the polyurethane prepolymer precursor to isocyanate group content, or, when the effect of water removal from the polyol does not meet the standard, correct vacuum degree during water removal from the polyol by the vacuum dehydration module based on a difference between the average value of carbon dioxide concentration and a preset average value of carbon dioxide concentration.

5. The intelligent detection system of claim 4, wherein, The optimization module is further configured to determine an isocyanate group ratio based on a ratio of the preset isocyanate group content to an isocyanate group content in the polyurethane prepolymer precursor, and shorten a holding time of the prepolymer precursor preparation module based on the isocyanate group ratio, and a shortening range of the holding time is proportional to the isocyanate group ratio.

6. The intelligent detection system of claim 5, wherein, The optimization module is further configured to determine a holding time difference based on a difference between the holding time of the prepolymer precursor before and after the correction, and reduce a cooling rate of the prepolymer precursor preparation module during preparation of the prepolymer precursor based on the holding time difference, and a reduction range of the cooling rate is proportional to the holding time difference.

7. The intelligent detection system of claim 4, wherein, The optimization module is further configured to determine a carbon dioxide concentration difference based on a difference between the average carbon dioxide concentration and a preset average carbon dioxide concentration, and increase a vacuum degree of the vacuum dehydration module during removal of water in the polyol based on the carbon dioxide concentration difference, and an increase range of the vacuum degree is proportional to the carbon dioxide concentration difference.

8. The intelligent detection system of claim 3, wherein, The optimization module is further configured to determine a second derivative variance of the differential thermal gravimetric curve based on a variance of the second derivative of the differential thermal gravimetric curve at different temperatures, and determine a cause of unqualified quality based on the second derivative variance of the differential thermal gravimetric curve, and correct a curing time of the polyurethane prepolymer and the organofunctional silane of the silicone polyurethane preparation module based on a difference between a minimum temperature and a maximum temperature of the silicone polyurethane precursor during curing when the curing temperature of the siloxane polyurethane is determined to be non-uniform, or correct an amount of solvent added by the silicone polyurethane preparation module based on a ratio between a viscosity of the mixture of the polyurethane prepolymer and the organofunctional silane and a preset preset viscosity when the mixing of the polyurethane prepolymer and the organofunctional silane is determined to be non-uniform.

9. The intelligent detection system of claim 8, wherein, The optimization module is further configured to determine a curing temperature difference based on a difference between a minimum temperature and a maximum temperature of the silicone polyurethane precursor during curing, and extend a curing time of the polyurethane prepolymer and the organofunctional silane of the silicone polyurethane preparation module based on the curing temperature difference, and an extension range of the curing time is proportional to the curing temperature difference.

10. The intelligent detection system of claim 8, wherein, The optimization module is further configured to determine a viscosity ratio based on a ratio between a viscosity of the mixture of the polyurethane prepolymer and the organofunctional silane and a preset preset viscosity, and increase an amount of solvent added by the silicone polyurethane preparation module based on the viscosity ratio, and an increase range of the amount of solvent added is proportional to the viscosity ratio.

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