High-elasticity chemically-crosslinked polyethylene foam material and preparation process thereof

Abstract

The invention relates to a high-elasticity chemical cross-linked polyethylene foam material and a preparation process thereof, belonging to the technical field of preparation of polymer cross-linked foam materials. The problems of low crosslinking degree control precision, lack of multi-parameter cooperative control and contradiction between crosslinking density increase and gas diffusion resistance increase are solved. A 4 * 4 matrix temperature sensor, a near-infrared spectrometer crosslinking degree detection device and a gas concentration sensor are adopted to form a multi-point monitoring system; establishing a cross-linked foaming digital twinborn model containing coupling solution of a radial heat conduction equation, a reaction kinetic equation and a modified diffusion resistance equation; executing a predictive control algorithm based on sequential quadratic programming; a space-time decoupling regulation and control technology is implemented, a surface layer cross-linking strengthening area and an inner layer foaming optimization area are divided according to the boundary distance of 30 + / -5 mm, a radial concentration gradient is established through layered synchronous feeding, and when the cross-linking degree reaches 0.70 + / -0.05, a cross-linking reaction dominant period is switched to a foaming reaction dominant period. The cross-linking degree control precision is + / -5%, and the product percent of pass is increased to 92% or above.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of polymer cross-linking foaming material preparation, in particular to a high-elasticity chemical cross-linking polyethylene foaming material based on a multi-physical field coupling digital twin model and a preparation process thereof. BACKGROUND

[0002] Polyethylene foaming material is widely used in automotive interiors, sports equipment, building insulation and other fields due to its excellent cushioning performance, lightweight characteristics and good chemical stability. Chemical cross-linking is an important means to improve the elasticity and strength of polyethylene foaming material, and a chemical bond is formed between the polymer molecular chains through a cross-linking agent to construct a three-dimensional network structure.

[0003] Existing polyethylene cross-linking foaming technology mainly uses traditional temperature control methods. For example, CN205517763U discloses a polyethylene cross-linking preparation system that uses an electromagnetic heating coil in combination with a temperature sensor for temperature control, which improves thermal efficiency but only enables simple feedback control of a single parameter. CN111286311A discloses a multiple cross-linking polymer gel profile control agent that uses a multiple cross-linking system to improve cross-linking performance, but this technology is mainly directed to oil field profile control applications and does not address the complex control problems in the foaming material preparation process. CN117225332A discloses a cross-linking agent production equipment and its control system, which realizes dynamic control through multiple temperature detectors and control modules, but the control algorithm is relatively simple and lacks prediction function.

[0004] The existing technology has the following disadvantages: low control precision, cross-linking degree control precision is usually ±15%, temperature control precision is ±5℃, it is difficult to meet the requirements of high-quality products; lack of multi-parameter collaborative control ability, unable to handle the space-time coupling problem of cross-linking reaction and foaming reaction; relying on operator experience, poor product quality consistency, the qualified rate is only about 85%; lack of predictive control ability, unable to predict the process change trend in advance and make feedforward adjustment; the contradiction between cross-linking density improvement and gas diffusion resistance increase is difficult to solve, affecting the comprehensive performance of the material. SUMMARY

[0005] TECHNICAL PROBLEM

[0006] The technical problem to be solved by the present application is how to realize accurate control of the polyethylene cross-linking foaming process, solve the contradiction between cross-linking density improvement and gas diffusion resistance increase, and improve product quality consistency and production efficiency.

[0007] TECHNICAL SCHEME

[0008] To solve the above technical problems, the present application provides a preparation method of a high-elasticity chemical cross-linking polyethylene foaming material, which comprises the steps of raw material preparation, cross-linking reaction and foaming molding:

[0009] The raw material preparation step includes mixing polyethylene matrix with peroxide crosslinking agent at a mass ratio of 1.4wt%, adding auxiliary crosslinking agent triallyl isocyanurate 0.3wt%, adding foaming agent azodicarbonamide 1.0wt%, and melt mixing at 120-140℃ for 15-25 minutes.

[0010] The crosslinking reaction step includes crosslinking reaction at a reaction temperature of 170-180℃ and a reaction pressure of 0.5-2.0MPa, with a total reaction time of 60-120 minutes. The decomposition rate of peroxide crosslinking agent is relatively stable in this temperature range, which is convenient for accurate control.

[0011] The foaming forming step includes three-stage pressure reduction control in the later stage of crosslinking reaction: the first stage reduces from 1.5MPa to 1.0MPa at a rate of 0.08MPa / min, the second stage reduces to 0.5MPa at a rate of 0.04MPa / min, and the third stage reduces to 0.2±0.05MPa at a rate of 0.02MPa / min. Temperature compensation control based on Sanchez-Lacombe equation of state is used during pressure reduction process to establish the temperature-pressure relationship: , wherein is the target temperature after compensation, is the initial set temperature, is the temperature compensation amount; Temperature compensation amount: , wherein is the pressure value before pressure reduction, is the pressure value after pressure reduction, is the temperature compensation coefficient; Compensation coefficient: , wherein is the current foaming temperature, is the crosslinking degree of polymer, and the compensation coefficient is determined by combining the thermal expansion coefficient of polymer melt, the change of gas solubility, and the constraint effect of crosslinking network on molecular motion. The coefficient is obtained by fitting PVT experimental data at different temperatures and crosslinking degrees, with a correlation coefficient R²>0.95. The compensation of pressure reduction cooling effect is achieved by increasing the heating power, ensuring that the foaming temperature is maintained at 170±3℃.

[0012] The key feature is the inclusion of multi-point parameter monitoring steps. Temperature sensors are evenly arranged in a 4×4 matrix on the inner wall of the reaction vessel; a crosslinking degree detection device detects changes in the intensity of the CH bond stretching vibration peak; and a gas concentration sensor monitors the gas generation rate, allowing for real-time acquisition of temperature distribution, crosslinking degree, and gas concentration data. The temperature sensors are K-type thermocouples, with an adjacent sensor spacing of 50mm in the 4×4 matrix arrangement. The temperature detection accuracy is ±0.2℃, the response time is less than 1.0s, and the data acquisition frequency is 1.0Hz. A 5-point moving average filtering algorithm is used to process the temperature data to improve the signal-to-noise ratio, ensuring that the sensors have reached a steady-state response at each acquisition time and filtering out high-frequency noise. The crosslinking degree detection device employs a high-temperature near-infrared spectrometer equipped with a sapphire optical window and an active temperature compensation system. Baseline drift correction is performed by real-time monitoring of a reference wavelength of 1800 cm⁻¹. The detection accuracy, experimentally verified under high temperature and high pressure conditions, is ±8%. A 45s signal integration time and a 60s detection frequency matching control cycle are used to simultaneously monitor three characteristic peaks at 2920 cm⁻¹, 2850 cm⁻¹, and 1465 cm⁻¹. A crosslinking degree prediction model is established using multi-wavelength cross-validation and partial least squares regression algorithms. The model's prediction correlation coefficient R² = 0.92. The device is equipped with a temperature compensation module and a pressure-sealed window. The crosslinking degree calculation employs a dual temperature and pressure compensation algorithm. , in Crosslinking degree (%) The reaction temperature is ℃. The reaction pressure is (MPa). The initial light intensity, Real-time light intensity, and These are the coefficients of the first-order term and the constant term related to temperature and pressure, respectively, and the specific calculation formulas are as follows: , , 175℃ and 1.0MPa are the standard calibration temperature and pressure conditions, respectively. Offline sample verification and calibration are performed every 30 minutes to ensure long-term stability.

[0013] A cross-linked foamed coupled digital twin model was established, and a two-dimensional axisymmetric simplified model was adopted to reduce computational complexity. This model includes the radial heat conduction equation: , in For density, For specific heat capacity, For temperature, For time, Thermal conductivity, For the enthalpy of reaction, It is a function of the reaction rate. (conversion rate) Reaction kinetic equation: , in Pre-exponential factor, For activation energy, The gas constant is The reaction order is [number]. Modified diffusion resistance equation: , in For concentration, For the effective diffusion coefficient, The reaction terms are related to concentration, temperature, and conversion rate; the numerical simulation of the cross-linking foaming process is achieved by solving the above three equations in a coupled manner.

[0014] A fast-response simplified model is established using model reduction techniques for real-time control, where the effective diffusion coefficient is based on free volume theory. , in The effective diffusion coefficient (m² / s) and the initial diffusion coefficient are given. m² / s was determined by pulsed field gradient nuclear magnetic resonance (PFG-NMR), and the diffusion activation energy was... kJ / mol is determined based on the diffusion theory of gases in polymers. The universal gas constant is 8.314 J / (mol·K) Absolute temperature (K), porosity and tortuosity Determined by mercury porosimetry The degree of crosslinking (dimensionless) and its hindering effect on diffusion, denoted by 2.3, were calibrated through gas permeation experiments on samples with different degrees of crosslinking. The standard Arrhenius equation form was used, and the frequency factor... ,activation energy The kJ / mol value was determined by differential scanning calorimetry (DSC) under nitrogen protection to measure the decomposition reaction of the peroxide. This value is consistent with the theoretical activation energy of dicumyl peroxide decomposition. The reaction order n=1.0 conforms to the first-order kinetics of free radical-initiated crosslinking reaction. When the temperature exceeds 175℃, the influence of side reactions is considered, and a correction factor is introduced. Correct the reaction rate constant.

[0015] Based on the aforementioned cross-linking foaming coupled digital twin model, a polymer reaction prediction and control algorithm is executed. Based on the cross-linking reaction time constant τ=180s identified by the system, and according to model predictive control theory, the prediction time domain is set to... Step (corresponding to 540s, approximately 3 times the time constant to ensure 95% dynamic response coverage), control time domain The step (corresponding to 180s, approximately 1 time constant to balance control performance and computational load), the control cycle of 60s is determined based on sensor response time and actuator action time. The predictive control algorithm adopts a decreasing weight strategy, with weight coefficients adjusted according to... To mitigate the impact of long-term forecast uncertainty, the model parameters are updated every 20 minutes, employing a rolling time-domain optimization strategy. The objective function is... , in The objective function value, for Time prediction Cross-linking degree at any time For the target degree of crosslinking, for Temperature control increment at any time, The state weight matrix is... To control the weight matrix and achieve coordinated optimization control of crosslinking degree and temperature, a sequential quadratic programming approach is used, with the constraint that 170℃ ≤ ≤180℃, 0.6≤ ≤0.9. Weight matrix and Determined through optimization using a multi-objective genetic algorithm: The diagonal elements of the matrix [100, 50, 20] correspond to the importance of controlling the degree of crosslinking, temperature, and pressure, respectively. The diagonal elements [10,5] of the matrix balance control accuracy and control stability.

[0016] A spatiotemporal decoupling control technology for crosslinking and foaming was implemented. Spatially, the reaction area was divided into a surface crosslinking enhancement zone and an inner foaming optimization zone using multiple concentric circles with a boundary distance of 30±5mm. A radial concentration gradient was established through layered synchronous feeding technology. Based on Fick's diffusion law, the minimum stable concentration gradient that could be maintained at 175℃ was 0.008wt% / mm. 1.6wt% crosslinking agent solution was continuously added through the surface annular feed port (5mm from the wall), and 1 wt% was added through the inner central feed port. A 0.2 wt% crosslinking agent solution, with a feed rate ratio of 1.2:1 to 1.5:1, combined with a zoned stirring strategy (15 rpm for the surface layer and 35 rpm for the inner layer) and temperature gradient control (175℃ for the surface layer and 172℃ for the inner layer), can establish and maintain a radial concentration gradient ≥0.008 wt% / mm within the first 5 minutes of the reaction. Subsequently, the gradient gradually decreases to a uniform distribution under natural diffusion. Temporally, when the degree of crosslinking reaches 0.70±0.05, the reaction switches from the crosslinking-dominant phase to the foaming-dominant phase. The peroxide crosslinking agent concentration in the surface crosslinking enhancement zone is 1.6 wt%, and the co-crosslinking agent concentration is 0.4 wt%. The peroxide crosslinking agent concentration in the inner foaming optimization zone is 1.2 wt%, and the co-crosslinking agent concentration is 0.2 wt%. The temperature during the dominant phase of the crosslinking reaction is controlled at 175±2℃. When the degree of crosslinking reaches 0.70±0.05, the temperature is gradually reduced to 170±2℃ to enter the dominant phase of the foaming reaction, ensuring that the ratio of the crosslinking reaction rate to the foaming reaction rate is adjusted from 5:1 to 1:3, achieving a smooth switch in reaction dominance. A layered synchronous feeding technology is adopted: the surface region is continuously supplied with a high-concentration crosslinking agent solution through an annular feed inlet, while the inner region is supplied with a low-concentration crosslinking agent solution through a central feed inlet, with the feed rate ratio adjusted within the range of 1.2:1 to 1.5:1. The entire reactor employs a zoned stirring strategy, maintaining a radial concentration gradient ≥0.008wt% / mm by controlling the feed time difference (30s earlier for the surface layer) and the feed concentration difference, with a gradient maintenance time of 5 minutes. The 30±5mm boundary distance is determined by establishing a heat and mass transfer coupling model for a cylindrical reactor: calculating the radial temperature gradient and concentration diffusion rate to ensure that the surface crosslinking rate is 30±5% higher than that of the inner layer.

[0017] This invention also provides an intelligent control system for implementing the above-described preparation method. The intelligent control system includes: a multi-point parameter monitoring unit, comprising a temperature sensor, a crosslinking degree detection device, and a gas concentration sensor, for real-time acquisition of reaction process parameters; a crosslinking foaming coupled digital twin model unit, comprising a model building module, a parameter identification module, and a model updating module, for establishing and maintaining a multi-physics field coupled simulation model; a polymer reaction prediction and control unit, which executes a sequential quadratic programming algorithm based on the digital twin model to output optimal temperature and pressure control commands; a zoned execution control unit, comprising a surface heating control module, an inner layer heating control module, a stirring control module, and a layered feeding control module, for executing spatiotemporal decoupling control commands; and a safety protection unit, comprising a multi-level temperature alarm system, a pressure relief valve, a peroxide safety monitoring system, an inert gas protection system, and an emergency quenching system. The parameter identification module employs a recursive least squares method with a forgetting factor. Initial value of covariance matrix ,in The model is an identity matrix; the model update frequency is once every 20 minutes; the safety protection unit is equipped with a multi-level temperature alarm system: Level 1 alarm 185℃, Level 2 alarm 188℃, emergency shutdown 190℃, pressure relief valve opening pressure 2.2MPa, the peroxide safety monitoring system adopts a fixed threshold strategy: when the concentration of unreacted peroxides exceeds 1.0wt% during the entire reaction process, Level 1 response is activated; when it exceeds 1.5wt%, Level 2 response is activated and automatic cooling is performed; when the concentration of abnormal decomposition products (phenol, acetone, etc.) exceeds 10ppm, the emergency quenching system is immediately activated; an activated carbon adsorption device is equipped to treat volatile organic compounds; an inert gas protection system maintains an oxygen content of <1%; the emergency quenching system reduces the temperature to below 120℃ within 30s by injecting low-temperature nitrogen; all safety systems use hardware interlocking to ensure fault safety.

[0018] Beneficial effects The present invention has the following advantages over the prior art: Significantly improved control accuracy: Through multi-point sensor fusion and predictive control algorithms, the cross-linking degree control accuracy is ±5%, and the temperature control accuracy is ±3℃. By adopting a spatial averaging control strategy with 16 temperature sensors, the control accuracy of the surface area is ±2℃, and the control accuracy of the inner area is ±4℃. The overall system control performance is improved by more than 50% compared with traditional methods.

[0019] Product quality consistency has been significantly improved: the coefficient of variation of density distribution uniformity is less than 3.0%, which is 40% higher than the 5% of the existing technology; the product qualification rate has increased from 85% to over 92%.

[0020] Improved production efficiency and economic benefits: Through predictive control and multi-parameter collaborative optimization, production efficiency is increased by 7% and energy consumption is reduced by 10%.

[0021] The technical challenge of crosslinking-foaming coupling control has been solved: through spatiotemporal decoupling control technology, the fundamental contradiction between increased crosslinking density and increased gas diffusion resistance has been successfully resolved, achieving a balance between high crosslinking degree and good foaming performance. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the overall architecture of the multi-physics field coupled intelligent control system according to an embodiment of the present invention; Figure 2 This is a flowchart of the spatiotemporal decoupling control technology for crosslinking foaming according to an embodiment of the present invention; Figure 3 This is a schematic diagram of a multi-sensor data fusion system according to an embodiment of the present invention. Detailed Implementation

[0023] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0024] Example 1: The purpose of this example is to verify the control effect of the polymer reaction prediction and control algorithm based on the multi-physics field coupled digital twin model in the polyethylene crosslinking and foaming process, and to demonstrate the complete preparation process.

[0025] like Figure 1 As shown, the multi-physics coupled intelligent control system includes a multi-point parameter monitoring unit, a cross-linking foaming coupled digital twin model unit, a polymer reaction prediction and control unit, a zoned execution control unit, and a safety protection unit.

[0026] Raw material preparation steps: Linear low-density polyethylene (LLDPE) was selected as the matrix material, with a melt flow index of 2.0 g / 10 min and a density of 0.918 g / cm³. The raw materials were formulated according to the following ratio: 100 parts polyethylene matrix, 1.4 parts peroxide crosslinking agent, 0.3 parts triallyl isocyanurate co-crosslinking agent, and 1.0 part azodicarbonamide foaming agent. The mixture was melt-mixed in a twin-screw extruder at 130°C for 20 minutes with a screw speed of 60 rpm to obtain a homogeneous premix.

[0027] Multi-point parameter monitoring system configuration: like Figure 3 As shown, 16 K-type thermocouples are arranged in a 4×4 matrix on the inner wall of the reaction vessel, with an adjacent sensor spacing of 50 mm, a temperature detection accuracy of ±0.2℃, a response time of 1.0 s, and a data acquisition frequency of 1.0 Hz. Figure 3As shown, the multi-sensor data fusion system ensures data accuracy and reliability through weighted averaging and outlier detection algorithms, providing high-quality input data for predictive control algorithms. A high-temperature near-infrared spectrometer equipped with a sapphire optical window and an active temperature compensation system is used. Baseline drift correction is performed by real-time monitoring of the reference wavelength of 1800 cm⁻¹. The detection accuracy, experimentally verified under high temperature and high pressure conditions, is ±8%. A 45s signal integration time and a 60s detection frequency matching control cycle are used to simultaneously monitor three characteristic peaks at 2920 cm⁻¹, 2850 cm⁻¹, and 1465 cm⁻¹. A cross-linking degree prediction model is established through multi-wavelength cross-validation and partial least squares regression algorithms. The model's prediction correlation coefficient R² = 0.92. A temperature compensation module and a pressure-sealed window are also included. , in Crosslinking degree (%) The reaction temperature is ℃. The reaction pressure is (MPa). The initial light intensity, Real-time light intensity, and These are the coefficients of the first-order term and the constant term related to temperature and pressure, respectively, and the specific calculation formulas are as follows: , , 175℃ and 1.0MPa were used as the standard calibration temperature and pressure conditions, respectively. Offline sample verification and calibration were performed every 30 minutes to ensure long-term stability. A CO2 concentration sensor was configured to monitor the gas generation rate, with a measurement range of 0-20% and a response time of less than 1.5s. The CO2 concentration changes during the reaction were as follows: Initial stage (0-15 minutes): CO2 concentration slowly increased from 0.1% to 0.8%, with a concentration change rate of 0.05% / min; Crosslinking-dominant period (15-45 minutes): CO2 concentration increased from 0.8% to 4.2%, with a concentration change rate of 0.11% / min; Crosslinking-foaming transition period (45-60 minutes): CO2 concentration increased from 4.2% to 8.5%, with a concentration change rate of 0.29% / min; Foaming-dominant period (60-90 minutes): CO2 concentration increased from 8.5% to 15.2%, with a concentration change rate of 0.22% / min.

[0028] Establishment of a cross-linked foaming coupled digital twin model: Establish a coupled set of equations that include heat conduction, reaction kinetics, and mass transfer: Heat conduction equation: , in For density, For specific heat capacity, For temperature, For time, Thermal conductivity, For the enthalpy of reaction, It is a function of the reaction rate. (conversion rate) Reaction kinetic equation: , in Pre-exponential factor, For activation energy, The gas constant is The reaction order is [number]. Modified diffusion resistance equation: , in For concentration, For the effective diffusion coefficient, These are reaction terms related to concentration, temperature, and conversion rate.

[0029] Model parameters were determined through experimental calibration: They were implemented using the standard Arrhenius equation form, with frequency factors... ,activation energy The kJ / mol value was determined by differential scanning calorimetry (DSC) under nitrogen protection to measure the decomposition reaction of the peroxide. This value is consistent with the theoretical activation energy of dicumyl peroxide decomposition. The reaction order n=1.0 conforms to the first-order kinetics of free radical-initiated crosslinking reaction. When the temperature exceeds 175℃, the influence of side reactions is considered, and a correction factor is introduced. The modified reaction rate constant and effective diffusion coefficient are established based on free volume theory. , in The effective diffusion coefficient (m² / s) and the initial diffusion coefficient are given. m² / s was determined by pulsed field gradient nuclear magnetic resonance (PFG-NMR), and the diffusion activation energy was... kJ / mol is determined based on the diffusion theory of gases in polymers. The universal gas constant is 8.314 J / (mol·K) Absolute temperature (K), porosity and tortuosity The crosslinking degree's inhibition effect coefficient on diffusion was determined by mercury porosimetry and calibrated by gas permeation experiments on samples with different crosslinking degrees.

[0030] Execution of polymer reaction prediction and control algorithm: The model predictive control algorithm is adopted. Based on the crosslinking reaction time constant τ=180s obtained by system identification, and according to model predictive control theory, the prediction time domain is set as... Step (corresponding to 540s), control the time domain Step (corresponding to 180s), control cycle 60s, predictive control algorithm adopts decreasing weight strategy, weight coefficient according to To mitigate the impact of long-term forecast uncertainty, the model parameters are updated every 20 minutes, employing a rolling time-domain optimization strategy. The objective function is: , in The objective function value, for Time prediction Cross-linking degree at any time For the target degree of crosslinking, for Temperature control increment at any time, The state weight matrix is... To control the weight matrix. Weight matrix The diagonal elements of the matrix are set to [100, 50, 20], and the weight matrix is... The diagonal elements of the matrix are set to [10, 5]. Constraint: 170℃ ≤ ≤180℃, 0.6≤ ≤0.9, 0.5MPa≤ ≤2.0MPa. The optimal control sequence is solved using a sequential quadratic programming algorithm, with a computation time of <30s.

[0031] Implementation of cross-linking foaming spatiotemporal decoupling control technology: like Figure 2As shown, the flow chart of the spatiotemporal decoupling control technology for crosslinking and foaming details the complete process flow and control logic, starting from raw material preparation, through spatial partitioning (dividing the surface crosslinking enhancement zone and the inner foaming optimization zone with a 30±5mm boundary distance), layered feeding control (1.6wt% crosslinking agent concentration in the surface layer and 1.2wt% in the inner layer), crosslinking degree monitoring (real-time detection of crosslinking degree changes), reaction dominance period switching judgment (switching when the crosslinking degree reaches 0.70±0.05), foaming dominance period control, until the final product is formed. This includes the temporal relationship and control logic of key steps such as determining the boundary distance, setting the concentration gradient, and switching the reaction dominance period. By establishing a heat and mass transfer coupling model of a cylindrical reactor, the radial temperature gradient and concentration diffusion rate were calculated, and 30±5mm was determined as the optimal boundary distance, making the surface crosslinking rate 30±5% higher than the inner layer. The peroxide crosslinking agent concentration in the surface region was set to 1.6wt%, and the co-crosslinking agent concentration was 0.4wt%; the peroxide crosslinking agent concentration in the inner layer region was set to 1.2wt%, and the co-crosslinking agent concentration was 0.2wt%. A radial concentration gradient is established using a layered synchronous feeding technique. Based on Fick's diffusion law, the minimum stable concentration gradient that can be maintained at 175℃ is 0.008wt% / mm. A crosslinking agent solution of 1.6wt% is continuously added through the surface annular feed port (5mm from the wall) and a crosslinking agent solution of 1.2wt% is added through the inner central feed port. The feed rate ratio is 1.2:1 to 1.5:1. Combined with a zoned stirring strategy (15rpm for the surface layer and 35rpm for the inner layer) and temperature gradient control (175℃ for the surface layer and 172℃ for the inner layer), a radial concentration gradient of ≥0.008wt% / mm can be established and maintained within 5 minutes of the initial reaction.

[0032] Dynamically allocate the dominant period of the response in time: Crosslinking reaction dominance period: temperature controlled at 175±2℃, pressure maintained at 1.5±0.1MPa, crosslinking rate 0.08min⁻¹; During the foaming reaction dominance period: when the degree of crosslinking reaches 0.70±0.05, the temperature is gradually reduced to 170±2℃, and the pressure is controlled by a three-stage pressure reduction to 0.2±0.05MPa, with a foaming rate of 0.12min⁻¹. Safety protection measures: The system is equipped with a multi-level temperature alarm system: Level 1 alarm at 185℃, Level 2 alarm at 188℃, and emergency shutdown at 190℃; a pressure relief valve with an opening pressure of 2.2MPa; and a peroxide safety monitoring system employing a fixed threshold strategy: Level 1 response is activated when the concentration of unreacted peroxides exceeds 1.0wt% throughout the reaction process, Level 2 response is activated and automatic cooling is performed when it exceeds 1.5wt%, and an emergency quenching system is immediately activated when the concentration of abnormal decomposition products (phenol, acetone, etc.) exceeds 10ppm. An activated carbon adsorption device is also included to treat volatile organic compounds. An inert gas protection system maintains an oxygen content of <1%, and the emergency quenching system lowers the temperature to below 120℃ within 30 seconds by injecting low-temperature nitrogen. All safety systems are hardware-interlocked to ensure fault safety, ensuring that the storage temperature of the peroxide crosslinking agent is <25℃, and multiple safety protections are implemented during the reaction process.

[0033] Preparation process: Add 500g of premix to the reaction vessel and start the multiphysics coupled intelligent control system. The system automatically executes the following control sequence, with a baseline production cycle of 90 minutes: 1. Heating stage: Increase the temperature to 175℃ at a rate of 2℃ / min, while simultaneously pressurizing to 1.5MPa; 2. Crosslinking-dominant period: Maintain 175±2℃ and 1.5±0.1MPa, and monitor changes in the degree of crosslinking; 3. Foaming-dominant stage: When the degree of crosslinking reaches 0.70±0.05, the temperature is gradually reduced to 170±2℃, and the pressure is reduced to 0.2±0.05MPa in three stages to complete the foaming process; 4. Cooling and curing: Allow to cool naturally to room temperature, then demold and remove the product. Test results:

[0034] The prepared polyethylene foam material had a density of 0.118±0.003 g / cm³, a resilience of 87±3%, a compressive strength of 0.82±0.08 MPa, and a tensile strength of 2.25±0.15 MPa. The degree of crosslinking was 77±5%, and the coefficient of variation for density distribution uniformity was 2.5%. The gradient crosslinking structure achieved through spatiotemporal decoupling control technology was key to its high performance: the highly crosslinked surface region (85±3%) provided structural strength, the moderately crosslinked inner region (65±5%) ensured elastic recovery, and the uniform pore structure with an average pore size of 110±15 μm ensured excellent cushioning performance. Microstructural analysis showed that the surface crosslinking density was 8.7×10⁻⁶. 18 The cross-linking density of the inner layer is 6.0 × 10⁻⁶ cells / cm³. 18The density is 1.8 kWh / cm³, and the porosity is 87±2%. The energy consumption per unit product is 2.8 kWh / kg, calculated based on a total power consumption of 14.0 kWh divided by the product weight of 5.0 kg. The batch-to-batch coefficient of variation is: density 1.8%, resilience 2.1%, and degree of crosslinking 3.5%.

[0035] This embodiment verifies that the multi-physics coupled digital twin model can accurately predict the cross-linking foaming process, the predictive control algorithm achieves a control accuracy of ±5% in cross-linking degree, and the spatiotemporal decoupling control technology successfully solves the cross-linking-foaming coupling contradiction, proving the effectiveness of the technical solution of this invention.

[0036] Example 2: The purpose of this example is to verify the adaptability of the multi-physics coupled intelligent control system under different combinations of process parameters and to demonstrate the system's adaptive adjustment capability.

[0037] Using the same equipment configuration and control system as in Example 1, the process parameters are adjusted as follows: The concentration of the peroxide crosslinking agent was adjusted to 1.2 wt%. The reaction temperature was adjusted to 172℃; The target degree of crosslinking is set to 0.82; Adaptive parameter adjustment process: The system automatically adjusts model parameters and control strategies based on the target degree of crosslinking. The recursive least squares parameter identification module updates reaction kinetic parameters in real time. Upon detecting a slow crosslinking rate, the system automatically extends the crosslinking dominance period to 720 s and fine-tunes the temperature to 172℃. (Weight matrix) The parameters were automatically adjusted to [120, 60, 25] to improve the accuracy of crosslinking control. CO2 concentration monitoring showed that under the adjusted process conditions, the gas generation rate was 0.06% / min during the crosslinking-dominant period and 0.22% / min during the foaming-dominant period, with a final concentration of 14.8%.

[0038] Preparation results: The final product had a density of 0.125±0.004 g / cm³, a resilience of 84±4%, a compressive strength of 0.78±0.06 MPa, a tensile strength of 2.15±0.12 MPa, and a crosslinking degree of 81±4%, achieving the preset targets. The crosslinking degree prediction error was maintained within ±8% during the control process, and the temperature control accuracy was ±2.3℃. The product had a uniform microstructure with an average pore size of 108±6 μm. The unit product energy consumption was 2.9 kWh / kg, calculated based on a total power consumption of 14.5 kWh divided by the product weight of 5.0 kg. The batch-to-batch coefficient of variation was 2.0% for density, 2.5% for resilience, and 3.8% for crosslinking degree.

[0039] This embodiment verifies that the multiphysics coupled intelligent control system has good parameter adaptability and self-learning ability, and can automatically adjust the control strategy according to different process requirements, demonstrating the robustness and practicality of the system.

[0040] Example 3: The purpose of this example is to verify the stability and consistency of the system under continuous production conditions and to simulate an industrial production environment.

[0041] The system continuously produces 30 batches, each weighing 5 kg, with a production cycle of 90 minutes. Key parameters and product performance indicators for each batch are automatically recorded.

[0042] Statistics on continuous production results: Establish a regression model between process parameters and product performance: density rebound rate ,in Crosslinking agent concentration (wt%) The foaming temperature (°C) is the temperature at which the foaming begins. The degree of crosslinking is represented. Model prediction accuracy: density ±0.003 g / cm³, rebound rate ±2%. CO2 concentration monitoring data shows that the gas generation behavior in 30 batches of production was highly consistent, with an average final concentration of 15.0 ± 0.8% and a coefficient of variation of only 5.3%.

[0043] The average density of the 30 batches of products was 0.121±0.008 g / cm³, the average resilience was 85.5±4.2%, the average compressive strength was 0.80±0.12 MPa, the average tensile strength was 2.2±0.18 MPa, and the average degree of crosslinking was 76±5%. The coefficients of variation between batches were 2.1% for density, 2.8% for resilience, and 3.2% for degree of crosslinking, all of which meet the requirements for industrial production.

[0044] System operational stability: The control system operated continuously for 45 hours without failure, with a sensor data acquisition success rate of 99.8% and a control command execution success rate of 99.9%. Energy consumption monitoring showed that the average energy consumption per unit product was 2.8 kWh / kg, which is 10% lower than that of traditional processes. The calculation is based on the total power consumption of 420 kWh for 30 batches divided by the total product weight of 150 kg.

[0045] This embodiment verifies the stability and reliability of the multiphysics coupled intelligent control system under continuous production conditions. The product quality consistency is significantly better than that of traditional control methods, demonstrating the industrial application value of the system.

[0046] Example 4: The purpose of this example is to specifically verify the effect of the crosslinking foaming spatiotemporal decoupling control technology and highlight its role in resolving the crosslinking-foaming contradiction.

[0047] Using the same basic configuration as in Example 1, the focus is on optimizing the spatiotemporal decoupling control parameters: The dividing distance is precisely controlled at 30±2mm; The concentration gradient of the surface crosslinking agent was optimized to 1.6 wt%. The concentration gradient of the inner layer crosslinking agent was optimized to 1.2 wt%. The switching timing is precisely controlled when the degree of crosslinking is 0.70 ± 0.05; Verification of spatiotemporal decoupling effect: Radial sampling analysis showed that the crosslinking degree in the surface region reached 0.85±0.03, and the crosslinking degree in the inner region was 0.68±0.04, achieving the expected gradient distribution. Gas diffusion tests showed that the surface diffusion resistance was reduced by 15% compared to the uniform distribution scheme, while the foaming uniformity of the inner layer was improved by 20%. CO2 concentration distribution tests indicated that the final CO2 concentration in the surface region was 12.8%, and in the inner region it was 16.5%, forming a concentration gradient conducive to foaming.

[0048] Preparation results: The product density is 0.119±0.002 g / cm³, resilience is 86±2%, compressive strength is 0.83±0.05 MPa, tensile strength is 2.28±0.08 MPa, and the coefficient of variation for density distribution uniformity is 1.8%. Microstructural analysis shows that the pore size distribution is more uniform, with the standard deviation decreasing from ±12 μm to ±6 μm. Batch-to-batch coefficient of variation: density 1.5%, resilience 1.8%, degree of crosslinking 2.9%.

[0049] This embodiment specifically verifies that the spatiotemporal decoupling control technology can effectively resolve the contradiction between increased crosslinking density and increased gas diffusion resistance, achieving a balance between high crosslinking degree and excellent foaming performance, thus demonstrating the core value of this technology.

[0050] Comparative Example 1 The purpose of this comparative study is to verify the impact of the lack of a multi-sensor fusion monitoring system on product quality control, and a traditional single-point temperature control method is used for comparison.

[0051] Using the same raw material ratio and basic process flow, but only a single temperature sensor is used for temperature control, without configuring a near-infrared spectrometer and a gas concentration sensor, and a traditional PID control algorithm is used instead of a predictive control algorithm.

[0052] Comparison of preparation processes: A single-point temperature sensor was used to monitor the center temperature of the reaction vessel, and a PID controller was used to adjust the heating power. Due to the lack of real-time monitoring of the degree of crosslinking, spatiotemporal decoupling control was not possible, so a fixed temperature-time program control was used: heating to 180℃, holding for 60 minutes, and then cooling to 170℃ for foaming for 30 minutes.

[0053] Comparison results: The prepared product had a density of 0.132±0.015 g / cm³, a resilience of 78±7%, a compressive strength of 0.75±0.12 MPa, a tensile strength of 2.0±0.18 MPa, and a crosslinking degree of 71±8%. The coefficient of variation for density distribution uniformity was 4.8%, and the temperature control accuracy was ±4.2℃. The performance of the 30 batches of product showed significant fluctuations: a density coefficient of variation of 13.4%, a resilience coefficient of variation of 8.4%, and a crosslinking degree coefficient of variation of 11.3%. The energy consumption per unit product was 3.0 kWh / kg, calculated based on a total power consumption of 450 kWh divided by the total product weight of 150 kg for the 30 batches. CO2 concentration monitoring data showed that due to a lack of precise control, gas generation behavior was unstable, with a final concentration of 13.2±2.1% and a coefficient of variation reaching 15.9%.

[0054] The comparison shows that the lack of multi-sensor fusion monitoring leads to a significant decrease in control accuracy and poor product quality consistency, which proves the necessity and superiority of the multi-sensor fusion monitoring system of this invention.

[0055] Comparative Example 2 The purpose of this comparative study is to verify the impact of the lack of digital twin model predictive control on system performance, and to compare it with traditional empirical control methods.

[0056] The same sensor configuration is used, but no digital twin model is established, no predictive control algorithm is used, and fixed process parameters are set only based on operator experience.

[0057] Comparison of preparation processes: Based on experience, fixed process parameters were set: heating rate 3℃ / min, crosslinking temperature 180℃, crosslinking time 60 minutes, foaming temperature 170℃, and foaming time 30 minutes. No dynamic adjustments or optimizations were made throughout the process; only simple temperature feedback control was implemented. The production cycle was 97 minutes, 7.8% longer than the 90 minutes in Example 1.

[0058] Comparison results: The product density was 0.128±0.012 g / cm³, the resilience was 81±6%, the compressive strength was 0.77±0.10 MPa, and the tensile strength was 2.1±0.15 MPa. However, the energy consumption was 10.7% higher than that of Example 1, with a unit product energy consumption of 3.1 kWh / kg. The calculation was based on the total power consumption of 465 kWh for 30 batches divided by the total product weight of 150 kg. Due to the lack of predictive control, two temperature overshoots occurred, affecting product quality. The crosslinking degree control accuracy was only ±12%, far lower than the ±5% of the present invention. The coefficient of variation among 30 batches was: density 11.1%, resilience 7.0%, and crosslinking degree 12.0%. CO2 concentration monitoring showed that the gas generation rate was 0.08% / min during the crosslinking-dominant period and 0.18% / min during the foaming-dominant period, with a final concentration of 14.1±1.5% and a coefficient of variation of 10.6%.

[0059] The comparison shows that the lack of a digital twin model for predictive control leads to increased energy consumption, reduced efficiency, and the inability to achieve process optimization, thus proving the superiority of the predictive control algorithm of this invention.

[0060] Comparative Example 3 The purpose of this comparative study is to verify the impact of the lack of spatiotemporal decoupling control technology on resolving the crosslinking-foaming contradiction. A uniform crosslinking agent distribution scheme is used for comparison.

[0061] The same multiphysics coupled intelligent control system was used, but spatiotemporal decoupling control was not implemented. The crosslinking agent was uniformly distributed throughout the reaction region at a concentration of 1.4 wt%. Due to the lack of stratified control, the internal temperature distribution of the reactor was uneven, resulting in differences between the baseline data and Example 1.

[0062] Comparison of preparation processes: The crosslinking agent is uniformly distributed without stratification control. Other control strategies are the same as in Example 1, including multi-sensor monitoring and predictive control algorithms.

[0063] Comparison results: The overall cross-linking degree of the product was 75±6%, but uneven cross-linking was observed internally. Excessive cross-linking on the surface hindered gas diffusion, while insufficient cross-linking in the inner layer affected strength. The final product had a resilience of only 80±6%, a compressive strength of 0.73±0.08 MPa, a tensile strength of 2.0±0.12 MPa, and a density distribution variation coefficient of 2.9%. Microstructural analysis showed that the surface pore size was too small, the inner pore size was too large, and the pore size distribution was uneven, with a standard deviation of ±12 μm. The variation coefficients among 30 batches were: density 2.7%, resilience 7.1%, and cross-linking degree 8.0%. CO2 concentration monitoring showed that due to the lack of stratification control, gas generation and distribution were uneven, with the final CO2 concentration in the surface area being 10.5% and in the inner area being 17.8%, and the excessive concentration gradient affecting product quality.

[0064] The comparison shows that the lack of spatiotemporal decoupling control technology cannot effectively resolve the contradiction between crosslinking density and gas diffusion, leading to a decline in product performance. This proves the necessity and effectiveness of the spatiotemporal decoupling control technology of this invention.

[0065] Based on the above embodiments and comparative examples, the core innovation of this invention lies in establishing a cross-linking foaming coupled digital twin model, realizing multi-parameter collaborative predictive control, and solving the fundamental contradiction between increased cross-linking density and increased gas diffusion resistance through spatiotemporal decoupling control technology. Compared with the prior art, this invention achieves a significant improvement in control accuracy, a substantial improvement in product quality consistency, and an effective increase in production efficiency, possessing significant technical value and application prospects.

Claims

1. A method for preparing a highly elastic chemically cross-linked polyethylene foam material, comprising raw material preparation, cross-linking reaction, and foaming molding steps, characterized in that: Step 1: Raw material preparation. Mix polyethylene matrix and peroxide crosslinking agent at a mass ratio of 1.4 wt%, add 0.3 wt% triallyl isocyanurate as a co-crosslinking agent, and add 1.0 wt% azodicarbonamide as a foaming agent. Melt mix at 120-140℃ for 15-25 minutes. Step 2: Crosslinking reaction. The crosslinking reaction is carried out at a reaction temperature of 170-180℃ and a reaction pressure of 0.5-2.0MPa, with a total reaction time of 60-120 minutes. Step 3: Foaming and molding, with three-stage pressure reduction control and temperature compensation control based on the Sanchez-Lacombe equation of state used in the later stage of the crosslinking reaction; Step 4: Multi-point parameter monitoring, real-time acquisition of reaction process parameters through temperature sensors, crosslinking degree detection devices, and gas concentration sensors; Step 5: Establish a cross-linked foaming coupled digital twin model; Step Six: Execute the polymer reaction prediction and control algorithm based on the cross-linking foaming coupled digital twin model; Step 7: Implement the spatiotemporal decoupling control technology for cross-linking foaming. Spatially, the reaction area is divided into a surface cross-linking enhancement zone and an inner foaming optimization zone. Temporally, when the degree of cross-linking reaches 0.70±0.05, the process switches from the cross-linking reaction dominance period to the foaming reaction dominance period.

2. The preparation method according to claim 1, characterized in that, In the foaming molding process, the three-stage pressure reduction control includes: a first stage reducing the pressure from 1.5 MPa to 1.0 MPa at a rate of 0.08 MPa / min; a second stage reducing the pressure to 0.5 MPa at a rate of 0.04 MPa / min; and a third stage reducing the pressure to 0.2 ± 0.05 MPa at a rate of 0.02 MPa / min. Temperature compensation control establishes the temperature-pressure relationship. ， in The target temperature after compensation, To set the initial temperature, This is the temperature compensation amount; Temperature compensation amount: ， in The pressure value before pressure reduction. This is the pressure value after depressurization. This is the temperature compensation coefficient; Compensation coefficient: ， in The current foaming temperature, The degree of crosslinking of the polymer is determined by combining the thermal expansion coefficient of the polymer melt, the change in gas solubility, and the constraint effect of the crosslinking network on molecular motion. The foaming temperature is maintained at 170±3℃ by increasing the heating power to compensate for the pressure drop cooling effect.

3. The preparation method according to claim 1, characterized in that, In the multi-point parameter monitoring step, temperature sensors are uniformly arranged in a 4×4 matrix on the inner wall of the reaction vessel, a crosslinking degree detection device detects the intensity change of the CH bond stretching vibration peak, and a gas concentration sensor monitors the gas generation rate. Temperature distribution, crosslinking degree, and gas concentration data are collected in real time. The temperature sensors are K-type thermocouples, with an adjacent sensor spacing of 50 mm in the 4×4 matrix arrangement. The temperature detection accuracy is ±0.2℃, the response time is less than 1.0s, the data acquisition frequency is 1.0Hz, and a 5-point moving average filtering algorithm is used to process the temperature data to improve the signal-to-noise ratio.

4. The preparation method according to claim 3, characterized in that, The crosslinking degree detection device employs a high-temperature near-infrared spectrometer equipped with a sapphire optical window and an active temperature compensation system. Baseline drift correction is performed by real-time monitoring of a reference wavelength of 1800 cm⁻¹. The detection accuracy, experimentally verified under high temperature and high pressure conditions, is ±8%. A 45s signal integration time and a 60s detection frequency matching control cycle are used to simultaneously monitor three characteristic peaks at 2920 cm⁻¹, 2850 cm⁻¹, and 1465 cm⁻¹. A crosslinking degree prediction model is established using multi-wavelength cross-validation and partial least squares regression algorithms. The model's prediction correlation coefficient R² = 0.

92. A temperature and pressure dual compensation model is also established. ， in Crosslinking degree (%) The reaction temperature is ℃. The reaction pressure is (MPa). The initial light intensity, Real-time light intensity, and These are the coefficients of the first-order term and the constant term related to temperature and pressure, respectively, and the specific calculation formulas are as follows: ， ， 175℃ and 1.0MPa are the standard calibration temperature and pressure conditions, respectively. Offline sample verification and calibration are performed every 30 minutes to ensure long-term stability.

5. The preparation method according to claim 1, characterized in that, The cross-linked foaming coupled digital twin model employs a two-dimensional axisymmetric simplified model to reduce computational complexity. This model involves the coupled solution of radial heat conduction equations, reaction kinetic equations, and modified diffusion resistance equations. A fast-response simplified model is established using model order reduction techniques for real-time control. The model adopts the standard Arrhenius equation form, with a frequency factor... ,activation energy The kJ / mol value was determined by differential scanning calorimetry under nitrogen protection for the peroxide decomposition reaction. The reaction order n=1.0 conforms to the first-order kinetics of free radical-initiated crosslinking reactions. When the temperature exceeds 175℃, the influence of side reactions is considered, and a correction factor is introduced. The reaction rate constant is corrected, where T is the reaction temperature (°C), and the effective diffusion coefficient is established based on the free volume theory: ， in The effective diffusion coefficient (m² / s) and the initial diffusion coefficient are given. m² / s was determined by pulsed field gradient nuclear magnetic resonance (PFG-NMR), and the diffusion activation energy was... kJ / mol is determined based on the diffusion theory of gases in polymers. The universal gas constant is 8.314 J / (mol·K) Absolute temperature (K), porosity and tortuosity Determined by mercury porosimetry The degree of crosslinking (dimensionless) is the barrier effect coefficient of crosslinking degree on diffusion. 2.3 is calibrated by gas permeation experiments on samples with different degrees of crosslinking.

6. The preparation method according to claim 1, characterized in that, The polymer reaction predictive control algorithm is based on the crosslinking reaction time constant τ=180s obtained by the system identification, and according to model predictive control theory, the prediction time domain is set to... The step corresponds to approximately three times the time constant of 540 seconds to ensure coverage of 95% of the dynamic response and control the time domain. The step corresponds to approximately 1 time constant (180s) to balance control performance and computational load. The control cycle of 60s is determined based on sensor response time and actuator action time. The predictive control algorithm employs a decreasing weight strategy, with weight coefficients adjusted according to... To reduce the impact of uncertainty in long-term forecasts, the model parameters are updated every 20 minutes, and a rolling time-domain optimization strategy is adopted to achieve coordinated optimization control of crosslinking degree and temperature.

7. The preparation method according to claim 1, characterized in that, In the aforementioned crosslinking and foaming spatiotemporal decoupling control technology, the reaction area is spatially divided into a surface crosslinking enhancement zone and an inner foaming optimization zone using a multi-layer concentric circle method with a boundary distance of 30±5mm. A radial concentration gradient is established through layered synchronous feeding technology. Based on Fick's diffusion law, the minimum stable concentration gradient that can be maintained at 175℃ is 0.008wt% / mm. 1.6wt% crosslinking agent solution is continuously replenished through the surface annular feed port 5mm from the wall, and 1.2wt% crosslinking agent solution is replenished through the inner central feed port, with a feed rate ratio of 1.2:1 to 1.5:

1. Combined with a zoned stirring strategy of 15rpm for the surface layer and 35rpm for the inner layer, and temperature gradient control of 175℃ for the surface layer and 172℃ for the inner layer, a radial concentration gradient ≥0.008wt% / mm can be established and maintained within the first 5 minutes of the reaction. Subsequently, the gradient gradually decreases to a uniform distribution under natural diffusion. Temporally, when the degree of crosslinking reaches 0.70±0.05, the reaction switches from the crosslinking reaction dominance period to the foaming reaction dominance period.

8. The preparation method according to claim 7, characterized in that, The peroxide crosslinking agent concentration in the surface crosslinking reinforcement zone is 1.6 wt%, and the co-crosslinking agent concentration is 0.4 wt%. The peroxide crosslinking agent concentration in the inner foaming optimization zone is 1.2 wt%, and the co-crosslinking agent concentration is 0.2 wt%. The temperature during the dominant crosslinking reaction period is controlled at 175±2℃. When the degree of crosslinking reaches 0.70±0.05, the temperature is gradually reduced to 170±2℃ to enter the dominant foaming reaction period. A layered synchronous feeding technology is adopted: the surface area is continuously replenished with a high-concentration crosslinking agent solution through an annular feed port 5 mm away from the wall, and the inner area is replenished with a low-concentration crosslinking agent solution through a central feed port. The surface area is fed 30 seconds earlier, and the feeding rate ratio is adjusted within the range of 1.2:1 to 1.5:

1. Combined with temperature gradient control, the surface area is 175℃ and the inner area is 172℃. By controlling the feeding time difference and feeding concentration difference, a radial concentration gradient ≥0.008 wt% / mm is maintained.

9. An intelligent control system for implementing the preparation method of claim 1, characterized in that, include: The multi-point parameter monitoring unit includes a temperature sensor, a crosslinking degree detection device, and a gas concentration sensor, which are used to collect reaction process parameters in real time. The cross-linked foamed coupled digital twin model unit includes a model building module, a parameter identification module, and a model updating module, which are used to establish and maintain multiphysics coupled simulation models. The polymer reaction prediction and control unit executes a sequence quadratic programming algorithm based on the digital twin model and outputs optimal temperature and pressure control commands. The partitioned execution control unit includes a surface heating control module, an inner heating control module, a stirring control module, and a layered feeding control module, which are used to execute spatiotemporal decoupling control commands; The safety protection unit includes a multi-level temperature alarm system, a pressure relief valve, a peroxide safety monitoring system, an inert gas protection system, and an emergency quenching system; The parameter identification module employs recursive least squares method and a forgetting factor. Initial value of covariance matrix ,in The model is an identity matrix; the model update frequency is once every 20 minutes; the safety protection unit is equipped with a multi-level temperature alarm system: Level 1 alarm 185℃, Level 2 alarm 188℃, emergency shutdown 190℃, the pressure relief valve opening pressure is 2.2MPa, the peroxide safety monitoring system adopts a fixed threshold strategy: when the concentration of unreacted peroxides exceeds 1.0wt% during the entire reaction process, Level 1 response is activated; when it exceeds 1.5wt%, Level 2 response is activated and the temperature is automatically reduced; when the concentration of abnormal decomposition products exceeds 10ppm, the emergency quenching system is immediately activated; an activated carbon adsorption device is equipped to treat volatile organic compounds; an inert gas protection system maintains an oxygen content of <1%; the emergency quenching system reduces the temperature to below 120℃ within 30s by injecting low-temperature nitrogen; all safety systems use hardware interlocking to ensure fault safety.

10. The highly elastic chemically cross-linked polyethylene foam material prepared according to claim 1, characterized in that, The material has a density of 0.12±0.02 g / cm³, a resilience of 85±5%, a compressive strength of 0.8±0.2 MPa, a coefficient of variation of density distribution uniformity of less than 3.0%, a degree of crosslinking of 75±8%, and a tensile strength of 2.2±0.3 MPa.

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