TPU supercritical foaming material and preparation process thereof

Abstract

The invention relates to the technical field of high polymer material preparation, in particular to a TPU (thermoplastic polyurethane) supercritical foaming material and a preparation process thereof, and the process comprises the following steps: preparing materials, blending and granulating, extruding small blanks and performing supercritical physical foaming to prepare the TPU supercritical foaming material. The foaming temperature change in the kettle is analyzed in the supercritical physical foaming process to control and adjust the foaming temperature; cutting the TPU foamed board subjected to supercritical physical foaming through a cutting machine, and laminating cloth or an adhesive film through a laminating machine, so as to obtain a foamed finished product. The invention aims at avoiding the situation that the foaming temperature in the foaming kettle is too high or too low, and the TPU foaming effect in the supercritical physical foaming process is improved.

Description

Technical Field

[0001] The present application relates to the technical field of polymer material preparation, and in particular to a TPU supercritical foaming material and a preparation process thereof. Background Art

[0002] TPU foam is a polymer compound. Due to its excellent wear resistance, corrosion resistance, and high resilience, it is widely used in applications such as shoe soles, pillows, and sheet materials. Currently, the existing preparation process for TPU foam involves introducing a mixture of supercritical nitrogen and carbon dioxide in a certain proportion, using supercritical foaming technology for purely physical foaming. This improves the foaming effect and efficiency during the foaming process. Furthermore, because supercritical nitrogen and carbon dioxide are relatively eco-friendly, supercritical foaming technology can avoid causing environmental pollution. Therefore, supercritical foaming technology has important application value in the existing preparation process for TPU foam.

[0003] During the supercritical physical foaming process, an inappropriate foaming temperature can have a serious adverse effect on foam expansion, so it is necessary to control the foaming temperature during the foaming process. Existing technologies mostly use PID controllers to control and adjust the foaming temperature to avoid the foaming temperature being too high or too low, thereby ensuring the foaming effect during the foaming process. However, due to the nonlinear random fluctuations in temperature during the supercritical physical foaming process, existing technologies do not fully consider nonlinear random fluctuations to accurately control and adjust the foaming temperature, which can easily lead to thermal runaway during the supercritical physical foaming process, making it impossible to ensure the foaming effect during the foaming process, and ultimately affecting the performance of the TPU foamed product. Summary of the Invention

[0004] In order to solve the above technical problems, the present application provides a TPU supercritical foaming material and a preparation process thereof to solve the existing problems.

[0005] The present invention discloses a TPU supercritical foaming material and its preparation process using the following technical solutions: One embodiment of the present application provides a preparation process of a TPU supercritical foaming material, which comprises the following steps: (1) Ingredients: by weight, weigh 70-90 parts of TPU particles, 10-25 parts of ammonium polyphosphate, 1-5 parts of nano hydroxide, 1-3 parts of cross-linking agent, 0.1-3 parts of anti-dripping agent, and 0.5-3 parts of anti-hydrolysis agent; (2) Blending and granulation: All ingredients are melt-blended and granulated through an extruder to obtain micro-modified particles; (3) Extrusion of small embryos: The micro-modified particles are formed into sheets through an extruder; (4) Supercritical physical foaming: Place the sheet into a supercritical foaming reactor, introduce a mixture of carbon dioxide and nitrogen, and perform supercritical physical foaming for 2-3 hours after heating and pressurizing. After expansion, a TPU foam sheet is obtained; Among them, during the supercritical physical foaming process, the foaming temperature of several temperature measuring points in the kettle is collected; The high-frequency subsequence is constructed by using the difference between the foaming temperature data of each temperature measurement point in any historical period and the smoothed data. In any historical time period, the high-frequency variation coefficient of any temperature measurement point is determined based on the difference distance between any temperature measurement point and the high-frequency subsequence of all temperature measurement points and the degree of disorder of the high-frequency subsequence of any temperature measurement point; and the nonlinear evaluation parameter of the foaming temperature in any historical time period is determined by combining the residual characteristics of the foaming temperature data of each temperature measurement point; The nonlinear evaluation parameters of all historical time periods before each collection moment are weighted and summed using the collection time interval between the historical time period and the collection moment to obtain the random disturbance characteristic value at each collection moment. The difference between the random disturbance characteristic values ​​at adjacent collection moments is used to feedback-regulate the actual foaming temperature. The foaming temperature in the foaming kettle is controlled and adjusted using a PID controller based on the feedback foaming temperature and the actual foaming temperature. The TPU foamed sheet after supercritical physical foaming is sliced ​​by a slicing machine and laminated with fabric or film by a laminating machine to obtain a foamed finished product.

[0006] Preferably, the cross-linking aid is one of dicumyl peroxide or di-(tert-butylperoxyisopropyl)benzene.

[0007] Preferably, the temperature of the plasticizing section of the extruder is set to 170-190°C, and the temperature of the rear metering section is set to 150-170°C.

[0008] Preferably, the mixed gas is carbon dioxide and nitrogen in a ratio of 10:90.

[0009] Preferably, the method for constructing the high-frequency subsequence is: The smoothed sequence of foaming temperature data of each temperature measurement point in any historical time period is recorded as a low-frequency subsequence; The sequence formed by subtracting the corresponding elements between the sequence composed of the foaming temperature data of each temperature measuring point in any historical time period and the low-frequency subsequence is recorded as the high-frequency subsequence of each temperature measuring point in any historical time period.

[0010] Preferably, the method for determining the high-frequency variation coefficient of any temperature measuring point is: Where, is the high-frequency variation parameter of the i-th temperature measurement point, is the approximate entropy of the high-frequency subsequence of the i-th temperature measurement point, is the number of temperature measuring points in the supercritical foaming reactor, is the difference distance of the high-frequency subsequence between the i-th temperature measurement point and the j-th temperature measurement point.

[0011] Preferably, the method for determining the nonlinear evaluation parameter of the foaming temperature in any historical time period is: Where, is the nonlinear evaluation parameter of the foaming temperature in the kth historical time period, is the residual feature of the i-th temperature measurement point in the k-th historical time period, is the high-frequency change parameter of the i-th temperature measuring point in the k-th historical time period; wherein, the method for obtaining the residual feature is: extracting the residual sequence of the foaming temperature data of the i-th temperature measuring point in the k-th historical time period; normalizing the range of the product of the range and the standard deviation in the residual sequence, and recording it as the residual feature of the i-th temperature measuring point in the k-th historical time period.

[0012] Preferably, the method for obtaining the random disturbance characteristic value at each acquisition moment is: Where, is the random disturbance eigenvalue at the tth acquisition moment, is the hyperbolic tangent function, is the number of elements in the nonlinear evaluation parameter sequence at the tth acquisition moment, is the bit number of the element in the nonlinear evaluation parameter sequence at the tth acquisition moment, is the sth element in the nonlinear evaluation parameter sequence at the tth acquisition moment; wherein, the nonlinear evaluation parameter sequence at the tth acquisition moment is obtained by sorting the nonlinear evaluation parameters of all historical time periods before the tth acquisition moment in chronological order.

[0013] Preferably, the method for obtaining the feedback foaming temperature at the current collection moment is: Where, is the feedback foaming temperature at the current collection moment, is the actual foaming temperature at the current collection moment, which is calculated by taking the average foaming temperature of all temperature measurement points at the current collection moment. and They are the minimum foaming temperature and maximum foaming temperature preset in the TPU supercritical physical foaming process, and are the random disturbance eigenvalues ​​of the current acquisition moment and the previous acquisition moment, is the absolute difference between the random perturbation eigenvalues ​​at the current acquisition moment and the previous acquisition moment.

[0014] The second embodiment of the present application provides a TPU supercritical foaming material, which is prepared by the preparation process described above.

[0015] In the above scheme, the beneficial effects are: (1) This application combines the high-frequency characteristics and residual characteristics of the foaming temperature change to more accurately measure the nonlinear random fluctuations of the foaming temperature in the supercritical foaming reactor during the historical period, which is conducive to the subsequent timely downward adjustment of the foaming temperature in the supercritical foaming reactor, thereby avoiding the phenomenon of foaming thermal runaway caused by rapid temperature increase during the nonlinear random fluctuation process.

[0016] (2) The present application constructs a random feature sequence through the nonlinear random fluctuation of the foaming temperature, and sets different weights for the elements in the random feature sequence, so as to accurately and timely respond to the random disturbance characteristics of the foaming temperature at each acquisition moment, which is conducive to more accurate control and adjustment of the foaming temperature in the supercritical foaming reactor in the future.

[0017] (3) The present application performs feedback regulation on the foaming temperature during the supercritical physical foaming process of TPU by changing the characteristic value of random disturbance, and effectively ensures that the foaming temperature after feedback regulation is within a reasonable range, thereby avoiding the foaming temperature being too high or too low, and improving the TPU foaming effect during the supercritical physical foaming process. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 A flowchart of a process for preparing a TPU supercritical foaming material according to one embodiment of the present application; Figure 2 A flow chart of the steps for controlling and regulating the foaming temperature in a supercritical physical foaming process provided in one embodiment of the present application. DETAILED DESCRIPTION

[0020] To further illustrate the technical means and effectiveness of this application's objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, details the TPU supercritical foaming material and its preparation process, including its specific implementation, structure, features, and effectiveness. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0021] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0022] The following describes in detail a TPU supercritical foaming material and a specific solution for its preparation process provided by the present application in conjunction with the accompanying drawings.

[0023] An embodiment of the present application provides a preparation process of a TPU supercritical foaming material. Please refer to the preparation flow chart. Figure 1 , the specific preparation process is as follows: (1) Ingredients: by weight, weigh 70-90 parts of TPU particles, 10-25 parts of ammonium polyphosphate, 1-5 parts of nano hydroxide, 1-3 parts of cross-linking aid, 0.1-3 parts of anti-dripping aid, and 0.5-3 parts of anti-hydrolysis aid. The cross-linking aid can be diisopropylbenzene peroxide (DCP) or di-(tert-butylperoxyisopropyl)benzene (BIBP), the anti-dripping aid is polytetrafluoroethylene, and the anti-hydrolysis aid is a carbodiimide compound.

[0024] In this embodiment, the composition includes 80 parts of TPU particles, 10 parts of ammonium polyphosphate, 4 parts of nano-hydroxide, 2 parts of a cross-linking agent, 2 parts of an anti-dripping agent, and 2 parts of an anti-hydrolysis agent, wherein the cross-linking agent is dicumyl peroxide (DCP).

[0025] (2) Blending and granulation: All ingredients are melt-blended through an extruder, and the melt-blended ingredients are granulated through an extruder to obtain micro-modified particles, wherein the temperature of the plasticizing section of the extruder is set to 170-190°C, and the temperature of the rear metering section is set to 150-170°C.

[0026] (3) Extrusion of small embryos: The micro-modified particles are formed by an extruder to obtain a plate, or the micro-modified particles are injection molded by an injection molding machine to obtain a midsole small embryo.

[0027] (4) Supercritical physical foaming: Place the board or midsole blank into a supercritical foaming reactor, introduce a mixture of carbon dioxide and nitrogen in a ratio of 10:90, and perform supercritical physical foaming for 2-3 hours after heating and pressurizing. After expansion, a TPU foamed board is obtained. In this embodiment, the supercritical physical foaming time is 2.5 hours.

[0028] In order to improve the foaming effect and efficiency during the foaming process, it is necessary to control and adjust the foaming temperature during the supercritical physical foaming process. In this embodiment, the flow chart of the steps for controlling and adjusting the foaming temperature during the supercritical physical foaming process is shown in the attached figure. Figure 2 As shown, specifically: Step 1: During the supercritical physical foaming process, the foaming temperatures at several temperature measuring points in the reactor are collected.

[0029] To more accurately control and regulate the foaming temperature during the supercritical physical foaming process, several temperature measurement points are evenly distributed within the supercritical foaming reactor. In this embodiment, nine temperature measurement points are set. Using thermocouples as temperature measurement elements, real-time data collection is performed on the foaming temperature at each temperature measurement point during the supercritical physical foaming process. In this embodiment, the foaming temperature collection frequency is 10 Hz. In other embodiments, the collection frequency can be adaptively set based on the speed of foaming temperature changes. For example, if the foaming temperature changes rapidly, a higher sampling frequency is suitable to capture detailed information about the foaming temperature changes; if the foaming temperature changes slowly, a lower sampling frequency is suitable to reduce duplication and redundancy in foaming temperature data.

[0030] Furthermore, in order to accurately analyze the nonlinear random fluctuations of temperature, the foaming temperatures of each temperature measuring point at all historical collection moments before each collection moment are arranged in chronological order, and the arranged sequences are normalized by the range normalization function. The normalized sequences are recorded as the foaming temperature sequences of each temperature measuring point at each collection moment.

[0031] Step 2: Obtain the nonlinear evaluation parameters of the foaming temperature by analyzing the high-frequency characteristics and residual characteristics of the foaming temperature change.

[0032] Due to the large temperature difference between the inside and outside of the supercritical foaming reactor, the foaming temperature of supercritical physical foaming is easily affected by external temperature interference, causing nonlinear random fluctuations in the foaming temperature over time. Nonlinear random fluctuations in the foaming temperature can easily lead to rapid temperature increases or excessive temperatures, further exacerbating the risk of thermal runaway. Therefore, in order to avoid thermal runaway in the supercritical physical foaming process, it is necessary to fully consider nonlinear random fluctuations and accurately control and adjust the foaming temperature.

[0033] In order to analyze the nonlinear random fluctuations of the foaming temperature at each temperature measuring point in different historical time periods, this embodiment divides the foaming temperature sequence of each temperature measuring point at each acquisition moment into sequences per minute to obtain foaming temperature subsequences for each temperature measuring point in each historical time period. After the division, the time length of each foaming temperature subsequence is 1 minute. If there is a foaming temperature subsequence with a time length less than 1 minute, the missing values ​​in the foaming temperature subsequence are supplemented by mean filling. Mean filling is a well-known technology, and the specific process is not repeated here.

[0034] Furthermore, the foaming temperature subsequence of each temperature measuring point in each historical time period is used as the input of the moving average method. The foaming temperature subsequence is smoothed by the moving average method, and the smoothed foaming temperature subsequence is recorded as a low-frequency subsequence. The sequence obtained by taking the difference between the corresponding elements of the foaming temperature subsequence and the low-frequency subsequence is recorded as a high-frequency subsequence of each temperature measuring point in each historical time period, reflecting the high-frequency characteristics of temperature changes at different temperature measuring points. The moving average method is a well-known technology, and the specific process is not repeated here.

[0035] Under normal circumstances, the high-frequency characteristics of temperature changes at different measurement points are highly similar, indicating that the foaming temperature at different locations during the supercritical physical foaming process is relatively uniform, resulting in a relatively stable foam cell structure at different locations. However, if the high-frequency characteristics of temperature changes at different measurement points differ greatly, and the degree of disorder in the high-frequency temperature changes at these measurement points increases, it can more clearly indicate nonlinear random fluctuations in the foaming temperature due to external temperature interference, making it less conducive to maintaining a stable foaming environment.

[0036] Based on the above analysis, for each historical time period, the high-frequency change parameters of each temperature measurement point are calculated: Where, is the high-frequency variation parameter of the i-th temperature measurement point, is the approximate entropy of the high-frequency subsequence of the i-th temperature measurement point, is the number of temperature measuring points in the supercritical foaming reactor, is the difference distance of the high-frequency subsequence between the i-th temperature measurement point and the j-th temperature measurement point. The measurement method of the difference distance can be DTW dynamic programming distance, Euclidean distance or Mahalanobis distance. This embodiment uses DTW dynamic programming distance to measure the difference distance.

[0037] The high-frequency variation parameter reflects the possibility that the temperature data collected at each temperature measurement point during the historical time period will be affected by external temperature interference, resulting in nonlinear random fluctuations in the data. The larger the high-frequency variation parameter is, the more it can reflect the nonlinear random fluctuations of the foaming temperature under the influence of external temperature interference. At this time, it is more likely to increase the risk of thermal runaway of foaming, affecting the TPU foaming effect during the supercritical physical foaming process.

[0038] Furthermore, in order to more accurately measure the nonlinear random fluctuations of the foaming temperature in each historical time period, the foaming temperature subsequence of each temperature measuring point in each historical time period is used as the STL time series decomposition algorithm (Seasonal-Trend decomposition using LOESS). The temperature residual sequence of each temperature measuring point in each historical time period is extracted by the STL time series decomposition algorithm. The STL time series decomposition algorithm is a well-known technology, and the specific process is not repeated here.

[0039] The temperature residual sequence reflects the random temperature fluctuations caused by external temperature disturbances. The larger the range of residual fluctuations within the temperature residual sequence and the higher the degree of dispersion, the more likely it is to reflect the nonlinear random fluctuations in the foaming temperature during the supercritical foaming process. Therefore, the range normalization result of the product of the range and standard deviation within the temperature residual sequence for each temperature measurement point in each historical time period is recorded as the residual feature for each temperature measurement point in each historical time period. The larger the residual feature, the more prominent the nonlinear random fluctuations in foaming temperature changes. The range normalization result is well known in the art and will not be further described.

[0040] Therefore, based on the above analysis, the nonlinear evaluation parameters of the foaming temperature in each historical time period are calculated: Where, is the nonlinear evaluation parameter of the foaming temperature in the kth historical time period, is the residual feature of the i-th temperature measurement point in the k-th historical time period, is the high-frequency change parameter of the i-th temperature measurement point in the k-th historical time period.

[0041] The nonlinear evaluation parameters reflect the nonlinear random fluctuations of the foaming temperature in the supercritical foaming reactor during the historical period. Through the residual characteristics and high-frequency change parameters of the unconnected temperature measurement points in the supercritical foaming reactor, a weighted summation method is used to more accurately measure the nonlinear random fluctuations of the foaming temperature. The greater the nonlinear random fluctuation of the foaming temperature, the worse the stability of the foaming temperature during the historical period. It is necessary to promptly avoid the phenomenon of rapid temperature rise and foaming thermal runaway during the nonlinear random fluctuation process.

[0042] Step 3: Obtain random disturbance eigenvalues ​​by weighting the nonlinear evaluation parameters to feedback-regulate the actual foaming temperature. Use a PID controller to control and regulate the foaming temperature based on the feedback foaming temperature and the actual foaming temperature to complete the supercritical physical foaming of the TPU material.

[0043] Furthermore, the nonlinear evaluation parameters corresponding to all historical time periods before each acquisition moment are arranged in chronological order to obtain a nonlinear evaluation parameter sequence for each acquisition moment, reflecting the nonlinear random fluctuation of the foaming temperature in different historical time periods before each acquisition moment.

[0044] In order to accurately respond to the random perturbation characteristics of the foaming temperature at each acquisition moment, the nonlinear evaluation parameters corresponding to the time periods with small time intervals between each acquisition moment should be assigned larger weights, while the nonlinear evaluation parameters corresponding to the time periods with large time intervals should be assigned smaller weights. This allows the emphasis to be placed on the recent data at each acquisition moment when measuring the random perturbation characteristics of the foaming temperature, thereby more accurately measuring the random perturbation characteristics of the foaming temperature at each acquisition moment.

[0045] Based on the above analysis, the random disturbance eigenvalue at each acquisition moment is calculated: Where, is the random disturbance eigenvalue at the tth acquisition moment, is the hyperbolic tangent function, is the number of elements in the nonlinear evaluation parameter sequence at the tth acquisition moment, is the bit number of the element in the nonlinear evaluation parameter sequence at the tth acquisition moment, It is the sth element in the nonlinear evaluation parameter sequence at the tth acquisition moment.

[0046] The random perturbation eigenvalue reflects the random perturbation characteristics of the foaming temperature at each acquisition moment. By setting different weights for the elements in the nonlinear evaluation parameter sequence, the random perturbation characteristics of the foaming temperature at each acquisition moment are accurately measured. The larger the random perturbation eigenvalue, the greater the random perturbation change of the foaming temperature in the supercritical foaming reactor at this time, and the more appropriate it is to lower the foaming temperature in the supercritical foaming reactor, so as to avoid the phenomenon of rapid temperature rise and foaming thermal runaway during the nonlinear random fluctuation process.

[0047] In order to timely avoid the phenomenon of foaming thermal runaway caused by rapid temperature rise during nonlinear random fluctuations, during the preparation of TPU foam materials, if the random disturbance characteristics of the foaming temperature show an upward trend, then it is more likely to cause the foaming temperature to rise rapidly and cause foaming thermal runaway, so it is necessary to appropriately lower the foaming temperature; conversely, if the random disturbance characteristic value shows a downward trend, then the possibility of foaming thermal runaway is smaller at this time. In order to avoid the problem of insufficient foaming due to the decrease in foaming temperature, it is necessary to appropriately increase the foaming temperature.

[0048] Based on the above analysis, the feedback foaming temperature at the current collection moment is calculated: Where, is the feedback foaming temperature at the current collection moment, is the actual foaming temperature at the current collection moment, which is calculated by taking the average foaming temperature of all temperature measurement points at the current collection moment. and The preset minimum foaming temperature and maximum foaming temperature in the TPU supercritical physical foaming process are 100℃ and 150℃ respectively. and are the random disturbance eigenvalues ​​of the current acquisition moment and the previous acquisition moment, is the absolute difference between the random perturbation eigenvalues ​​at the current acquisition moment and the previous acquisition moment.

[0049] The foaming temperature in the TPU supercritical physical foaming process is feedback-regulated by changing the eigenvalue of random disturbance, while ensuring that the foaming temperature after feedback adjustment is within a reasonable range, thereby avoiding excessive or insufficient foaming temperature.

[0050] Therefore, the feedback foaming temperature and the actual foaming temperature at the current collection moment are input into the PID controller. The PID controller generates a control signal for the foaming temperature by the temperature error between the feedback foaming temperature and the actual foaming temperature. The PID controller transmits the control signal to the heater in the supercritical foaming kettle, and controls and adjusts the foaming temperature in the supercritical foaming kettle through the heater, thereby realizing the control and adjustment of the foaming temperature in the supercritical physical foaming process.

[0051] Step 4: The TPU foamed sheet after supercritical physical foaming is sliced ​​by a slicing machine, and laminated with cloth or film by a laminating machine to obtain a foamed finished product.

[0052] The supercritical physical foaming is completed by the above method, and a TPU foamed sheet is obtained after expansion. The remaining preparation steps of the TPU supercritical foaming material preparation process are as follows: (5) Material processing: The expanded TPU foam sheet is surface-trimmed by a grinder to remove irregularities on the surface of the TPU foam sheet, and the surface-trimmed TPU foam sheet is placed in a slicing machine to slice the TPU foam sheet to obtain foam sheets of various thicknesses.

[0053] (6) Finished product: Place foam sheets of various thicknesses in a laminating machine, and use the laminating machine to laminate fabrics or films on the foam sheets of various thicknesses to obtain TPU foamed finished products.

[0054] Thus, the invention of a TPU supercritical foaming material and its preparation process is completed.

[0055] Example 2 (1) Ingredients: In this embodiment, the composition includes 70 parts of TPU particles, 15 parts of ammonium polyphosphate, 1 part of nano-hydroxide, 1 part of a cross-linking agent, 0.1 parts of an anti-drip agent, and 0.5 parts of an anti-hydrolysis agent. The cross-linking agent is di-(tert-butylperoxyisopropyl)benzene (BIBP).

[0056] (2) Blending and granulation.

[0057] (3) Squeeze out the embryo.

[0058] (4) Supercritical physical foaming: The supercritical physical foaming time in this embodiment is 2 hours.

[0059] (5) Material processing: In this embodiment, the expanded TPU foam sheet is molded by a molding machine, and the surface of the molded TPU foam sheet is trimmed by a grinder to remove irregular parts on the surface of the TPU foam sheet, thereby obtaining a molded midsole.

[0060] (6) Finished product: In this embodiment, the molded midsole and the rubber outsole are bonded together by a bonding machine to obtain a shoe sole, wherein the rubber outsole is the bottom material of the footwear product and is mainly made of natural rubber or artificial synthetic rubber.

[0061] In this embodiment, the steps or methods not specifically described are the same as those in Embodiment 1.

[0062] Example 3 (1) Ingredients: In this embodiment, the composition includes 90 parts of TPU particles, 25 parts of ammonium polyphosphate, 5 parts of nano-hydroxide, 3 parts of a cross-linking agent, 3 parts of an anti-dripping agent, and 3 parts of an anti-hydrolysis agent. The cross-linking agent is dicumyl peroxide (DCP).

[0063] (2) Blending and granulation.

[0064] (3) Squeeze out the embryo.

[0065] (4) Supercritical physical foaming: In this embodiment, the supercritical physical foaming time is 3 hours.

[0066] (5) Material processing: In this embodiment, the expanded TPU foam sheet is molded by a molding machine, and the surface of the molded TPU foam sheet is trimmed by a grinder to remove irregular parts on the surface of the TPU foam sheet, thereby obtaining a molded midsole.

[0067] (6) Finished product: In this embodiment, the molded midsole and the rubber outsole are bonded together by a bonding machine to obtain a shoe sole, wherein the rubber outsole is the bottom material of the footwear product and is mainly made of natural rubber or artificial synthetic rubber.

[0068] In this embodiment, the steps or methods not specifically described are the same as those in Embodiment 1.

[0069] The performance of the TPU foamed soles prepared in Examples 1 to 3 and Comparative Examples 1 to 2 of the present application was tested. Examples 1 to 3 were supercritical physical foaming using the foaming temperature control and adjustment method of the present application, while Comparative Example 1 was supercritical physical foaming using a preset fixed foaming temperature of 120° C. in the prior art. Comparative Example 2 was supercritical physical foaming using a preset fixed foaming temperature of 135° C. in the prior art. The test results are shown in Table 1 below: Table 1 The various embodiments in this application are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0070] It should be noted that, unless otherwise specified and limited, terms such as "include", "comprising" or any other variations thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such article or device. In the absence of further restrictions, the phrase "including a ..." defines an element, does not exclude the presence of other identical elements in the article or device including the element. In addition, the term "and\or" used herein includes any and all combinations of one or more related listed items.

[0071] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of the present application and include common knowledge or customary techniques in the art not invented herein.

[0072] It will be understood that the present application is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof.

Claims

1. A preparation process of TPU supercritical foaming material, characterized in that: The process includes the following steps: (1) Ingredients: by weight, weigh 70-90 parts of TPU particles, 10-25 parts of ammonium polyphosphate, 1-5 parts of nano hydroxide, 1-3 parts of cross-linking agent, 0.1-3 parts of anti-dripping agent, and 0.5-3 parts of anti-hydrolysis agent; (2) Blending and granulation: All ingredients are melt-blended and granulated through an extruder to obtain micro-modified particles; (3) Extrusion of small embryos: The micro-modified particles are formed into sheets through an extruder; (4) Supercritical physical foaming: Place the sheet into a supercritical foaming reactor, introduce a mixture of carbon dioxide and nitrogen, and perform supercritical physical foaming for 2-3 hours after heating and pressurizing. After expansion, a TPU foam sheet is obtained; Among them, during the supercritical physical foaming process, the foaming temperature of several temperature measuring points in the kettle is collected; The high-frequency subsequence is constructed by using the difference between the foaming temperature data of each temperature measurement point in any historical period and the smoothed data. In any historical time period, the high-frequency variation coefficient of any temperature measurement point is determined based on the difference distance between any temperature measurement point and the high-frequency subsequence of all temperature measurement points and the degree of disorder of the high-frequency subsequence of any temperature measurement point; and the nonlinear evaluation parameter of the foaming temperature in any historical time period is determined by combining the residual characteristics of the foaming temperature data of each temperature measurement point; The nonlinear evaluation parameters of all historical time periods before each collection moment are weighted and summed using the collection time interval between the historical time period and the collection moment to obtain the random disturbance characteristic value at each collection moment. The difference between the random disturbance characteristic values ​​at adjacent collection moments is used to feedback-regulate the actual foaming temperature. The foaming temperature in the foaming kettle is controlled and adjusted using a PID controller based on the feedback foaming temperature and the actual foaming temperature. The TPU foamed sheet after supercritical physical foaming is sliced ​​by a slicing machine and laminated with fabric or film by a laminating machine to obtain a foamed finished product.

2. The process for preparing a TPU supercritical foaming material according to claim 1, wherein: The cross-linking auxiliary agent is one of dicumyl peroxide or di-(tert-butylperoxyisopropyl)benzene.

3. The preparation process of a TPU supercritical foaming material according to claim 1, characterized in that: The temperature of the plasticizing section of the extruder is set to 170-190°C, and the temperature of the rear metering section is set to 150-170°C.

4. The preparation process of a TPU supercritical foaming material according to claim 1, wherein: The mixed gas is carbon dioxide and nitrogen in a ratio of 10:

90.

5. The process for preparing a TPU supercritical foaming material according to claim 1, wherein: The method for constructing the high-frequency subsequence is: The smoothed sequence of foaming temperature data of each temperature measurement point in any historical time period is recorded as a low-frequency subsequence; The sequence formed by subtracting the corresponding elements between the sequence composed of the foaming temperature data of each temperature measuring point in any historical time period and the low-frequency subsequence is recorded as the high-frequency subsequence of each temperature measuring point in any historical time period.

6. The process for preparing a TPU supercritical foaming material according to claim 5, wherein: The method for determining the high-frequency variation coefficient of any temperature measuring point is: Where, is the high-frequency variation parameter of the i-th temperature measurement point, is the approximate entropy of the high-frequency subsequence of the i-th temperature measurement point, is the number of temperature measuring points in the supercritical foaming reactor, is the difference distance of the high-frequency subsequence between the i-th temperature measurement point and the j-th temperature measurement point.

7. The process for preparing a TPU supercritical foaming material according to claim 6, wherein: The method for determining the nonlinear evaluation parameter of the foaming temperature in any historical time period is: Where, is the nonlinear evaluation parameter of the foaming temperature in the kth historical time period, is the residual feature of the i-th temperature measurement point in the k-th historical time period, is the high-frequency change parameter of the i-th temperature measuring point in the k-th historical time period; wherein, the method for obtaining the residual feature is: extracting the residual sequence of the foaming temperature data of the i-th temperature measuring point in the k-th historical time period; normalizing the range of the product of the range and the standard deviation in the residual sequence, and recording it as the residual feature of the i-th temperature measuring point in the k-th historical time period.

8. The process for preparing a TPU supercritical foaming material according to claim 7, wherein: The method for obtaining the random disturbance characteristic value at each acquisition moment is: Where, is the random disturbance eigenvalue at the tth acquisition moment, is the hyperbolic tangent function, is the number of elements in the nonlinear evaluation parameter sequence at the tth acquisition moment, is the bit number of the element in the nonlinear evaluation parameter sequence at the tth acquisition moment, is the sth element in the nonlinear evaluation parameter sequence at the tth acquisition moment; wherein, the nonlinear evaluation parameter sequence at the tth acquisition moment is obtained by sorting the nonlinear evaluation parameters of all historical time periods before the tth acquisition moment in chronological order.

9. The process for preparing a TPU supercritical foaming material according to claim 1, wherein: The method for obtaining the feedback foaming temperature at the current collection moment is: Where, is the feedback foaming temperature at the current collection moment, is the actual foaming temperature at the current collection moment, which is calculated by taking the average foaming temperature of all temperature measurement points at the current collection moment. and They are the minimum foaming temperature and maximum foaming temperature preset in the TPU supercritical physical foaming process, and are the random disturbance eigenvalues ​​of the current acquisition moment and the previous acquisition moment, is the absolute difference between the random perturbation eigenvalues ​​at the current acquisition moment and the previous acquisition moment.

10. A TPU supercritical foaming material, characterized in that: The invention is prepared by the preparation process according to any one of claims 1 to 9.

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