Method and system for synergistically controlling interlayer bonding quality of multilayer co-extruded heat shrinkable film

Abstract

The present application relates to the technical field of quality control of heat-shrinkable film production, in particular to a multi-layer co-extrusion heat-shrinkable film interlayer bonding quality collaborative control method and system, comprising the following steps: S1, collecting the basic physical parameters of each layer of material, and constructing an interlayer bonding collaborative analysis model; S2, obtaining the material chemical parameters and inputting the process parameter data set; S3, dynamically monitoring the melt interface fitting state; S4, collecting the forming process parameters and synchronously importing the interlayer bonding collaborative analysis model; S5, executing the gradient preheating process, collecting the preheating temperature distribution data and updating the process parameter data set; S6, obtaining the deformation matching characteristic parameters; S7, collecting the thermal relaxation parameters and synchronously importing the interlayer bonding collaborative analysis model; S8, according to the model analysis result, adjusting and controlling the process parameters of the above process. The problems of interlayer delamination, performance attenuation after thermal cycling and poor batch stability existing in the industry for a long time are solved, and the loss and cost of large-scale production are greatly reduced.

Description

Technical Field

[0001] This invention relates to the field of quality control technology for thermal stretch film production, and in particular to a method and system for collaborative control of interlayer bonding quality in multilayer co-extruded thermal stretch films. Background Technology

[0002] The industrial production of traditional multilayer co-extruded thermo-stretchable films typically involves using multiple extruders to independently plasticize the resin raw materials for each layer. The melt is then extruded into a preform after being laminated in the co-extrusion die, followed by longitudinal and transverse biaxial stretching, heat setting, cooling, and winding to obtain the finished product. Conventional interlayer bonding control methods in the industry mainly rely on adjusting extrusion temperature, extruder speed, stretching ratio, and the amount of adhesive layer added to achieve interfacial bonding. These controllable parameters are all conventional process parameters, only achieving basic interlayer composite effects.

[0003] With the continuous expansion of new application scenarios such as food cold chain packaging, industrial wrapping of irregularly shaped components, and high-end shrink sleeve labeling, the operating conditions of thermal stretch films are becoming increasingly complex and demanding, placing higher standards on the dynamic bonding stability, high and low temperature adaptability, and long-term service performance of the products. As the demands of these new operating conditions continue to expand, products manufactured using traditional thermal stretch film molding processes exhibit the following drawbacks when actually addressing these specific requirements:

[0004] First, relying solely on conventional process factors such as extrusion temperature, main machine speed, stretching ratio, and binder layer ratio to achieve interlayer matching control, under complex working conditions such as alternating high and low temperatures and high-speed coating deformation, the deformation rhythm and thermal response of each layer of material cannot be kept in sync. This easily leads to shear slip and residual internal stress at the interface, which in turn causes quality problems such as local peeling, film wrinkles, and uneven shrinkage after film heat shrinkage.

[0005] Second, existing technologies only test and judge the basic mechanical properties of finished products. Under long-term storage, transportation and continuous deformation, the dynamic quality state of interlayer bonding and the distribution of interface stress are not controlled throughout the process. As a result, the interface is prone to microscopic damage. Even if the static test indicators of the finished product meet the standards, interlayer separation failure may still occur when the product is in service under actual complex working conditions.

[0006] Therefore, it is necessary to design a method for collaborative control of interlayer bonding quality in multilayer co-extruded thermoscaling films that can achieve synergistic stability of multilayer interfaces. Summary of the Invention

[0007] To solve one of the above-mentioned technical problems, the present invention adopts the following technical solution: a method for collaborative control of interlayer bonding quality of multilayer co-extruded thermo-stretchable film, comprising the following steps: S1, collecting basic physical property parameters of each layer of material, constructing an interlayer bonding collaborative analysis model, and establishing a full-process process parameter dataset.

[0008] S2. Based on the basic physical property parameters, pre-treat the raw materials of each layer, obtain the physical and chemical parameters, and enter them into the process parameter dataset.

[0009] S3. Using pretreated materials, carry out the layered melt preparation process, collect melt rheological characteristic parameters, and dynamically monitor the melt interface bonding status.

[0010] S4. Perform multi-layer composite molding on the obtained melt layers, collect molding process parameters and import them into the interlayer bonding collaborative analysis model simultaneously.

[0011] S5. Perform a gradient preheating process on the basis of the composite molded preform, collect preheating temperature distribution data and update the process parameter dataset.

[0012] S6. Perform a bidirectional step-by-step stretching process on the preheated blank film, dynamically monitor the interlayer deformation coordination state, and obtain deformation matching characteristic parameters.

[0013] S7. Perform segmented heat setting on the stretched preform, collect heat relaxation parameters and simultaneously import them into the interlayer bonding collaborative analysis model.

[0014] S8. Conduct interlayer bonding state testing on the heat-set film, input the test data into the model for analysis, and adjust the process parameters of the above steps based on the model analysis results.

[0015] As a preferred approach, when collecting the basic physical property parameters of each layer of material, in addition to the conventional melt index and density parameters, it is also necessary to simultaneously collect three types of physical property indicators: interlayer charge mobility, surface free energy dispersion component, and molten dielectric loss tangent. The conventional parameters and the above indicators are integrated into a multi-dimensional physical property feature matrix according to the layer sequence. The feature matrix is ​​normalized, and the processing rules are implemented in accordance with the plastic physical property testing specifications. The processed feature data is used as the initial input parameters of the interlayer combined collaborative analysis model. The model completes the layer sequence weight allocation based on the feature matrix, and the weight allocation results are simultaneously entered into the full-process process parameter dataset.

[0016] As a preferred approach, the raw materials for each layer are preprocessed based on a multi-dimensional physical property matrix. The specific steps are as follows:

[0017] The raw materials are subjected to low-temperature vacuum drying, and the drying temperature and vacuum gradient are set according to the free energy dispersion component of the material surface.

[0018] The dried raw materials are screened using a grading and screening process to remove agglomerated particles and impurities that exceed the set particle size distribution range.

[0019] The sieved raw materials are statically homogenized and mixed to eliminate localized component segregation.

[0020] After pretreatment, the material's water activity gradient, component homogeneity, and surface polarity parameters are collected, and the obtained physicochemical parameters are entered into the process parameter dataset in stratified order.

[0021] As a preferred embodiment, the steps of the layered melt preparation process are as follows:

[0022] Based on a multi-dimensional physical property matrix, the plasticizing temperature gradient, shear rate distribution, and holding time of each layer of melt are set; the raw material is subjected to layered plasticizing treatment, and parameters such as shear viscosity, dynamic modulus, wall slip rate, and charge migration rate of each layer of melt are collected.

[0023] A melt interface charge transfer factor was introduced to construct a melt rheological co-adaptation model and complete the calculation.

[0024] Adjust the melt preparation process parameters based on the model calculation results, and dynamically monitor the melt interface bonding status.

[0025] The model calculation formula is as follows: .

[0026] in, For melt rheology compatibility index; For the first Layer melt shear viscosity, unit: ; The value of the melt interface charge transfer factor is set according to the rheological specifications for polymer melt processing, and ranges from 0.82 to 1.36. For the first Melt charge mobility, unit: ; For the first Melt wall slip rate, unit: ; This is the viscosity-temperature sensitivity coefficient, derived from plastic rheological property standards; For the first Layer and First Shear viscosity difference of layered melt, unit: ; For the first The dielectric loss tangent of the melt layer; is the total number of material layers; exp is the natural exponential function; the calculation results and interface status data are synchronously uploaded to the process parameter dataset.

[0027] As a preferred option, the steps for implementing the multi-layer composite molding process are as follows:

[0028] Arrange the melt delivery path according to the layer sequence and set the synchronous delivery rate of melt for each layer.

[0029] Once all layers of melt arrive at the composite fusion zone simultaneously, the melt fusion pressure and interface temperature are controlled to complete the continuous interface bonding of each layer of melt.

[0030] Throughout the entire composite molding process, parameters such as interlayer contact pressure, extrusion flow rate, interface temperature, and dielectric property deviation are collected in real time.

[0031] Based on the aforementioned molding parameters, an interlayer dielectric loss correlation factor is introduced to construct an interface bonding stability judgment model and complete quantitative calculations. The composite molding process parameters are dynamically adjusted based on the model calculation results. The model calculation formula is as follows:

[0032] .

[0033] in, For interface stability coefficient; For the first Dielectric constant of the layer material; For the first Dielectric constant of the layer material; This is the dielectric mismatch weighting factor, set with reference to the specifications for multilayer functional thin films; For the first The dielectric loss tangent of the melt layer; Interlayer contact pressure, unit: ; Melt composite flow rate, unit: ; The interface bonding correction coefficient is determined based on the interlayer matching standard for plastic composite products.

[0034] As a preferred approach, the steps for performing the gradient preheating process are as follows:

[0035] The composite-molded preform is smoothly fed into the segmented preheating area, and the initial preheating temperature is set.

[0036] After the preform enters the first temperature zone, the preheating temperature is gradually increased along the preform forming direction to the temperature sub-zone, and real-time temperature distribution data of each temperature zone is collected simultaneously.

[0037] Throughout the preheating process, the crystal zone transformation rate, thermal diffusivity, and deformation gradient parameters of the preform are continuously monitored.

[0038] Based on the aforementioned preheating parameters, a thermal diffusion anisotropy factor is introduced to construct an interlayer thermal deformation collaborative model and complete quantitative calculations.

[0039] The preheating parameters for each temperature zone are dynamically adjusted based on the model calculation results.

[0040] The model calculation formula is as follows:

[0041] ;

[0042] in, This represents the thermal deformation coordination deviation value. For the first The anisotropy factor for thermal diffusion in the temperature range is determined according to the standard for testing the crystallization of polymer thin films, and ranges from 0.79 to 1.28. For the first Coefficient of thermal expansion of the preform film in the temperature range, unit: ; The coefficient of thermal expansion of the preform is the overall average coefficient of thermal expansion, in units of: ; For the first Thermal diffusivity of the preform film in the temperature range, unit: ; For the first Temperature zone setting temperature, unit: ; For the first Axial length of the temperature zone, unit: ; Temperature zone weighting factor; This represents the number of preheating zones; relevant data is updated in real time to the process parameter dataset.

[0043] As a preferred embodiment, the steps of the bidirectional step-by-step stretching process are as follows:

[0044] The preheated blank is stretched longitudinally in stages, and the gradient stretching rate is set in stages along the flow direction of the blank.

[0045] After longitudinal stretching is completed, the preform is smoothly fed into the transverse stretching unit, and the different stretching ratios are matched in different regions along the width direction of the preform to complete the transverse gradient stretching.

[0046] Throughout the entire biaxial tensile process, the interlayer deformation matching degree, interface slip, residual stress distribution, and interface wetting angle parameters are dynamically monitored.

[0047] An interface wetting hysteresis factor was introduced to correct the interlayer deformation synergy judgment criteria and complete the calibration of monitoring data.

[0048] The calibrated deformation characteristic parameters are transmitted to the interlayer bonding collaborative analysis model, and the core parameters of stretching rate, stretching ratio and stretching time are recorded simultaneously.

[0049] As a preferred embodiment, a segmented heat setting process is performed on the preform after the bidirectional step-by-step stretching process, with the following steps:

[0050] Divide the temperature range into multiple sections and set gradient cooling curves.

[0051] The stretched preform is sequentially fed into each shaping temperature zone to complete the entire process of high-temperature shaping, medium-temperature heat preservation, gradient cooling, and low-temperature stabilization.

[0052] Throughout the heat setting process, parameters such as thermal relaxation rate, phase transformation degree, interfacial bonding energy, and internal stress amplitude were continuously collected at each temperature zone.

[0053] Based on the aforementioned collected modeling parameters, an internal stress-thermal relaxation coupling factor is introduced to construct an interface energy stability model and complete quantitative calculations.

[0054] The process parameters of the shaping temperature zone are dynamically adjusted based on the model output results.

[0055] The model calculation formula is as follows:

[0056] ;

[0057] in, Energy stability value at the interlayer interface, unit: ; For the first Specific heat capacity of the preform film in the temperature range, unit: Determined according to the standards for thermal properties of plastics; For the first Temperature drop range, unit: ; The thermal stress-thermal relaxation coupling factor is derived from the thermal setting specification for composite materials, and ranges from 0.85 to 1.42. For the first Temperature zone insulation duration, unit: ; This is the internal stress attenuation coefficient; This is the phase transformation correction factor, set with reference to the polymer thin film crystallization test standard; This refers to the number of temperature zones for the model.

[0058] As a preferred approach, the interlayer bonding state of the finished film after the segmented heat setting process is detected and controlled in a closed loop. The steps are as follows:

[0059] The interlayer peel strength of the film was tested and continuous stress data was recorded.

[0060] The uniformity of the interfacial bonding of the thin film was detected, and localized areas of weak bonding were located.

[0061] The amplitude and spatial distribution of residual internal stress in the thin film were detected.

[0062] Detect the characteristics of charge distribution at the thin film interface.

[0063] All the aforementioned detection data are input into the interlayer combined collaborative analysis model. The comprehensive control value of process parameters is calculated by combining five types of factors: melt interface charge migration, dielectric loss correlation, thermal diffusion anisotropy, interface wetting hysteresis, and internal stress-thermal relaxation coupling. An adaptive control model for process parameters is then constructed.

[0064] The model calculation formula is as follows:

[0065] ;

[0066] in, This refers to the comprehensive control coefficient of process parameters; For the first The numerical values ​​of the test indicators; For the first The importance weight of each indicator is set according to the quality standards for multilayer co-extruded films. This is a process correlation correction factor, derived from the multilayer composite film processing specifications; This is the comprehensive influence coefficient of the related factors; The total number of test indicators; the process parameters of each process, including pretreatment, melt preparation, composite molding, preheating, stretching and heat setting, are adjusted in a refined manner based on the control coefficient.

[0067] The present invention also provides a multilayer co-extruded thermo-stretchable film interlayer bonding quality collaborative control system, wherein the system stores a computer program, and when the computer program is executed by a processor, it implements the control method described above.

[0068] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0069] 1. This invention, through the architecture of an interlayer combined collaborative analysis model, connects the originally isolated eight production processes into an organic whole that is interconnected and mutually supportive. Compared with the conventional process single-point optimization and open-loop control mode, this invention solves the long-standing problems in the industry such as easy delamination between layers, performance degradation after thermal cycling, and poor batch stability, and significantly reduces the losses and costs of large-scale production.

[0070] 2. This invention deeply nonlinearly couples multiple dimensions of parameters affecting interlayer bonding, such as macroscopic rheological parameters, microscopic interface characteristics, dielectric properties, thermal deformation characteristics, and internal stress state, and constructs a series of original quantitative models, including a melt rheological collaborative adaptation model, an interface bonding stability judgment model, an interlayer thermal deformation collaborative model, an interface energy stability model, and a process parameter adaptive control model.

[0071] By incorporating easily overlooked microscopic influencing factors such as melt interface charge migration, dielectric loss mismatch, thermal diffusion anisotropy, and internal stress-thermal relaxation coupling into the core control system, and through quantitative calculations of the model, key performance characteristics that cannot be detected by conventional processes, such as the molecular entanglement capability, long-term service stability, and thermal deformation synchronization of the melt interface, can be accurately predicted.

[0072] 3. This invention employs a sequential process design involving segmented gradient preheating, bidirectional step-by-step stretching, and segmented heat setting, along with precise control through interlayer thermal deformation synergy models and interface energy stabilization models. By utilizing a gradient cooling mode—medium-temperature insulation to fully release internal stress and low-temperature rapid cooling to fix the orientation structure—combined with dynamic control of heat setting parameters via an interface energy stabilization model, this invention achieves full release of residual internal stress between layers while ensuring precise control of thermal expansion and contraction rates. This makes it suitable for the stringent requirements of high-end applications such as food and pharmaceutical packaging and new energy battery insulation.

[0073] 4. This invention achieves full-chain traceability from finished products to raw materials through the standardized integration and archiving management of the entire process parameter dataset and standardized process traceability files with unique traceability codes, meeting the regulatory requirements of high-end industries; it realizes the standardized inheritance and reuse of optimal production processes through the establishment of a qualified batch process benchmark database; and it achieves continuous improvement in the control accuracy of the inter-layer combined collaborative analysis model through model iterative optimization based on historical qualified batch data, forming a closed loop of autonomous optimization of production processes. Attached Figure Description

[0074] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below.

[0075] Fig. 1 This is an overall flowchart of the control method of the present invention.

[0076] Fig. 2 This is a flowchart illustrating the specific steps of the pretreatment of raw materials at each layer based on a multi-dimensional physical property matrix, as described in this invention. Detailed Implementation

[0077] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and are therefore merely examples and should not be used to limit the scope of protection of the present invention. The process of the present invention is as follows: Figs. 1-2 As shown in the image.

[0078] Example 1: A method for collaborative control of interlayer bonding quality of multilayer co-extruded thermo-stretchable film, including the following steps: S1, collecting basic physical property parameters of each layer of material, constructing an interlayer bonding collaborative analysis model, and establishing a full-process process parameter dataset.

[0079] S2. Based on the basic physical property parameters, pre-treat the raw materials of each layer, obtain the physical and chemical parameters, and enter them into the process parameter dataset.

[0080] S3. Using pretreated materials, carry out the layered melt preparation process, collect melt rheological characteristic parameters, and dynamically monitor the melt interface bonding status.

[0081] S4. Perform multi-layer composite molding on the obtained melt layers, collect molding process parameters and import them into the interlayer bonding collaborative analysis model simultaneously.

[0082] S5. Perform a gradient preheating process on the basis of the composite molded preform, collect preheating temperature distribution data and update the process parameter dataset.

[0083] S6. Perform a bidirectional step-by-step stretching process on the preheated blank film, dynamically monitor the interlayer deformation coordination state, and obtain deformation matching characteristic parameters.

[0084] S7. Perform segmented heat setting on the stretched preform, collect heat relaxation parameters and simultaneously import them into the interlayer bonding collaborative analysis model.

[0085] S8. Conduct interlayer bonding state testing on the heat-set film, input the test data into the model for analysis, and adjust the process parameters of the above steps based on the model analysis results.

[0086] It is necessary to explain the advantages of this solution. This solution uses an interlayer combined collaborative analysis model as the core link and a full-process process parameter dataset as the data carrier to transform the originally isolated eight production processes into an interconnected and mutually supportive collaborative control system. The output of the preceding process directly determines the execution benchmark of the following process, and the actual measurement results of the following process correct the control parameters of the preceding process. From the source of raw materials to the finished product inspection, every link is carried out in collaborative control around the core objectives of improving the quality of interlayer bonding, ensuring thermal expansion performance, and improving batch stability.

[0087] We will provide a detailed explanation of the selection of core parameters in this solution, and also provide examples from the actual mass production scenarios of PE / PA / EVA three-layer co-extruded heat shrink film for food packaging.

[0088] First, the range of basic material properties collected in step S1 is determined based on the core influencing factors of the interfacial bonding performance of polymer materials. Conventional melt index and density parameters determine the basic processing performance of the material, while the charge mobility, surface free energy dispersion component, and dielectric loss tangent value that we supplementally collect determine the molecular bonding ability and long-term stability of the material interface. This is also one of the differences between this scheme and conventional processes. In the actual production of PE / PA / EVA three-layer film, we collect the above-mentioned physical properties of the PE heat-sealing layer, PA barrier layer, and EVA adhesive layer respectively to match the corresponding process benchmark for each layer.

[0089] The time-series storage rules for the full-process process parameter dataset are set according to the quality control specifications for plastic production processes. Each set of collected data is bound to a unique timestamp, process code, and layer sequence code to ensure data traceability and relevance. In actual production, when the production line runs at a speed of 30m / min, the data acquisition frequency is set to 10Hz to match the rhythm of the production line and prevent data lag or loss.

[0090] Finally, the full-process parameter control rules in step S8 are set according to the process influence weight of multilayer co-extruded film production. If the peel strength of the finished product is not up to standard, the melt preparation and composite molding parameters are adjusted first. If the thermal shrinkage rate is not up to standard, the preheating, stretching and heat setting parameters are adjusted first. If the interface uniformity is not up to standard, the pretreatment and stretching parameters are adjusted first. This ensures the accuracy of the control. In actual mass production, this control rule can shorten the response time for defect correction from the usual 4 hours to 15 minutes, meeting the requirements of large-scale continuous production.

[0091] This solution upgrades the production of multilayer co-extruded films from open-loop single-point control to closed-loop collaborative management. By combining interlayer collaborative analysis models with full-process process parameter datasets, it transforms the originally isolated production processes into an interconnected management system, fundamentally solving the core problems of fragmented process parameters and large quality fluctuations in conventional processes.

[0092] This solution, through time-series binding of data across the entire process, can accurately pinpoint the source process corresponding to defects. Simultaneously, through real-time model analysis, it can proactively identify and dynamically correct interface mismatch risks during production, eliminating the need to wait for the finished product to be formed before taking remedial action. Furthermore, this solution, through collaborative management across the entire process, addresses the control requirements of two core performance parameters at each stage, overcoming the problem of mutually antagonistic performance differences that cannot be simultaneously achieved in conventional processes.

[0093] As a preferred approach, when collecting the basic physical property parameters of each layer of material, in addition to the conventional melt index and density parameters, it is also necessary to simultaneously collect three types of physical property indicators: interlayer charge mobility, surface free energy dispersion component, and molten dielectric loss tangent. The conventional parameters and the above indicators are integrated into a multi-dimensional physical property feature matrix according to the layer sequence. The feature matrix is ​​normalized, and the processing rules are implemented in accordance with the plastic physical property testing specifications. The processed feature data is used as the initial input parameters of the interlayer combined collaborative analysis model. The model completes the layer sequence weight allocation based on the feature matrix, and the weight allocation results are simultaneously entered into the full-process process parameter dataset to provide a quantitative benchmark for setting parameters for subsequent processes.

[0094] Charge mobility directly determines the electrostatic entanglement ability of molecules at the melt interface, surface free energy dispersion directly determines the interfacial wetting and adhesion ability between melts, and the molten dielectric loss tangent directly determines the risk of interfacial charge accumulation in the film under temperature cycling and electric field effects. These three types of indicators are factors that determine the long-term stability of interlayer bonding. The detection methods for these three types of physical properties are all standard detection methods known in the field: charge mobility and molten dielectric loss tangent are detected using a broadband dielectric spectrometer, with the detection temperature matched to the melting processing temperature of the corresponding material, and the detection process strictly following the specifications for the dielectric and resistive characteristics of solid insulating materials; the surface free energy dispersion component is obtained using a contact angle meter through the seated drop method, and the accurate detection of these three types of indicators can be completed using conventional laboratory testing equipment.

[0095] The construction rules for the multi-dimensional physical property feature matrix are as follows: the matrix is ​​arranged with material layer sequence as rows and five indicators—melt index, density, charge mobility, surface free energy dispersion component, and molten dielectric loss tangent—as columns, integrated into a two-dimensional matrix according to the layer sequence. Each row corresponds to the full-dimensional physical property parameters of one layer of material. Furthermore, the normalization rules for the feature matrix refer to the standardization methods for plastic physical property parameters specified in the standard environment for testing the mechanical properties of plastics. The extreme value normalization method is used to map all parameters with different dimensions to a unified numerical range of 0 to 1, eliminating the influence of differences in the numerical magnitude of different parameters on the model calculation. The normalization formula adopts a method known in the field. ,in These are the measured values ​​of the parameters. , This represents the industry standard extreme value for the corresponding parameter.

[0096] Finally, the layer weight allocation logic is made public. The model completes the weight allocation based on the functional positioning of each layer of material in the feature matrix. The basic weights are set according to the importance classification rules of functional layers in the general quality standard of multilayer co-extruded films. The basic weights of heat-sealing layer, support layer, functional layer and adhesive layer are 0.35, 0.40, 0.20 and 0.25 respectively. They can be flexibly adjusted within ±0.05 according to the actual application scenario of the film. The weight allocation results are directly used as the quantitative benchmark for setting parameters of subsequent processes. The entire process parameter dataset is entered simultaneously to realize parameter traceability of the entire process.

[0097] We will explain in detail the selection criteria for the core parameters in this solution, and provide examples from the actual mass production scenario of PET / PP / EVA three-layer co-extruded heat-shrinkable film for new energy battery insulation. First, the selection criteria for the three types of physical properties are based on the fundamental mechanisms of polymer interface physics and composite material mechanics. Charge mobility corresponds to the electrostatic interaction of interface molecules, surface free energy dispersion component corresponds to interface wetting and molecular diffusion capabilities, and melt state dielectric loss tangent corresponds to the long-term stability of the interface. These three types of indicators comprehensively characterize the interlayer bonding potential of the material from three dimensions: the formation, strength, and long-term stability of the interface, with no redundant data collection items.

[0098] In the actual production of PET / PP / EVA three-layer insulating film, we collected three types of indicators for the PET support layer, PP insulating layer, and EVA adhesive layer. Among them, the dielectric loss tangent of the PET layer, the surface free energy dispersion component of the EVA layer, and the charge mobility of the PP layer are the core control indicators, corresponding to the electric field stability, interfacial adhesion strength, and high and low temperature cycling performance of the insulating film, respectively. The extreme values ​​for normalization are based on the industry standard property ranges of the corresponding materials. For example, the extreme range of the melt index of PE raw material is 0.3-10 g / 10 min, and the extreme range of the surface free energy dispersion component is 25-40 mJ / m. 2 .

[0099] The strategy for adjusting the layer weights is determined based on the core application scenario of the film. For example, for heat shrink film used in food packaging, the core focus is on heat sealing performance and peel strength, so the weights of the heat sealing layer and adhesive layer can be increased by 0.05; for heat shrink film used in new energy insulation, the core focus is on insulation performance and high and low temperature stability, so the weights of the support layer and insulation layer can be increased by 0.05, flexibly adapting to different application requirements.

[0100] The detection of charge mobility and the dielectric loss tangent in the molten state strictly follows the specifications for the dielectric and resistive characteristics of solid insulating materials. The detection temperature is set to the melting processing temperature of the corresponding material, and the frequency range is set to 10²-10⁶ Hz, with values ​​ranging from 10⁻⁶ to 10⁻⁶ Hz. -8 -10 -5 cm2 / (V·s), 10 -3 -10 -1 The surface free energy dispersion component was determined strictly according to the specifications for thin film contact angle measurement methods. Deionized water and diiodomethane were used as the test liquids, and the dispersion component was calculated using the OWRK method, with values ​​ranging from 25 to 40 mJ / m. 2 .

[0101] The normalization of the multi-dimensional physical property feature matrix adopts the well-known extreme value normalization method, and the parameter mapping range is fixed at 0~1. The hierarchical weight allocation is set according to the functional layer importance classification rules. The basic weight is fixed and can be flexibly adjusted within ±0.05 according to the application scenario. Those skilled in the art can directly complete the weight setting according to the standard.

[0102] This scheme incorporates three types of microscopic physical properties affecting the long-term stability of interfaces into the raw material evaluation and process control system for multilayer co-extruded films. Through a multi-dimensional physical property matrix, it achieves unified quantification of macroscopic processing parameters and microscopic interface characteristics. The normalization design ensures that parameters of different dimensions can participate fairly in the calculation within the same model, avoiding model calculation distortion caused by differences in numerical magnitudes, and laying a standardized data foundation for subsequent quantitative control throughout the entire process.

[0103] This technical solution incorporates the core characteristics affecting the microscopic bonding of the interface into the raw material evaluation system. Conventional raw material property collection in this field only collects macroscopic parameters such as melt index and density that directly affect melt flow, ignoring the decisive influence of the interfacial characteristics of the raw material on the long-term stability of interlayer bonding. This results in interlayer separation and performance degradation of the finished film even if the extrusion process is smooth.

[0104] This solution optimizes the raw material property acquisition process by relying on a multi-dimensional feature matrix and standardized data processing to achieve a comprehensive quantitative evaluation of the interlayer bonding potential of materials. It breaks through the limitation of conventional processes that can only evaluate the processing performance of raw materials. Through three types of microscopic property indicators, it comprehensively characterizes the interlayer bonding potential of materials from three dimensions: the formation, strength, and long-term stability of interface bonding. In actual production, it can reduce the error in judging the compatibility of raw materials.

[0105] This scheme achieves standardized and unified processing of input parameters for inter-layer collaborative analysis models, eliminates calculation bias caused by numerical differences between different physical quantities, maps all parameters to a unified range of 0 to 1, ensures fair and reasonable weight allocation of different types of parameters in the model, and avoids model calculation distortion.

[0106] In addition, this solution also achieves precise setting of parameters for subsequent processes from the source, greatly reducing experience-based parameter adjustments in production. The layer weight allocation based on the multi-dimensional physical property matrix ensures that the process parameters of each layer of material match its own material characteristics. In actual production, the temperature setting deviation of the subsequent melt preparation process can be controlled within ±2℃.

[0107] As a preferred approach, the raw materials for each layer are preprocessed based on a multi-dimensional physical property matrix. The specific steps are as follows:

[0108] The raw materials are subjected to low-temperature vacuum drying, and the drying temperature and vacuum gradient are set according to the free energy dispersion component of the material surface.

[0109] The dried raw materials are screened using a grading and screening process to remove agglomerated particles and impurities that exceed the set particle size distribution range.

[0110] The sieved raw materials are statically homogenized and mixed to eliminate localized component segregation.

[0111] After pretreatment, the material's water activity gradient, component homogeneity, and surface polarity parameters are collected, and the obtained physicochemical parameters are entered into the process parameter dataset in stratified order.

[0112] Conventional high-temperature drying processes can damage the polar active groups on the surface of materials, leading to an irreversible decrease in the surface free energy of the materials, which directly weakens the interfacial wetting and molecular entanglement capabilities during melt composite. Large-diameter agglomerates caused by incomplete sieving can cause local flow rate fluctuations during melt extrusion, forming micron-level bonding defects at the film interface. Local component segregation caused by uneven mixing can cause local unevenness in the dielectric and rheological properties of the melt, ultimately leading to significant fluctuations in the interfacial bonding force of the film.

[0113] The parameter setting rules for the low-temperature vacuum drying process are disclosed. The drying temperature and vacuum level are determined based on the surface free energy dispersion component of the material in the preceding multi-dimensional physical property characteristic matrix. Specifically, the surface free energy dispersion component should be between 25-30 mJ / m. 2 The materials in this range have strong molecular polarity, and their active groups are easily decomposed by heat. Therefore, the drying temperature is set at 65-75℃, and the vacuum degree is controlled at -0.08-0.09MPa; the surface free energy dispersion component is 30-35mJ / m. 2 Materials in this range have weaker molecular polarity and stronger thermal stability; therefore, the drying temperature is set at 75-85℃, and the vacuum degree is controlled at -0.09-0.1MPa; the surface free energy dispersion component exceeds 35mJ / m. 2 For materials, the drying temperature can be increased to 85-95℃, and the vacuum degree is maintained at -0.1MPa. The setting rules of these parameters are derived based on the thermal stability law of polar groups on the surface of polymer materials.

[0114] The drying time is determined based on the initial moisture content of the material. When the initial moisture content is higher than 0.1%, the drying time is set to 46 hours; when the initial moisture content is lower than 0.1%, the drying time is set to 24 hours. The drying endpoint is defined as a material moisture content ≤ 0.05%. The moisture content is determined using the Karl Fischer method, which is well-known in the field. The grading and screening process uses a three-layer standard screening screen connected in series, with screen apertures of 80 mesh, 100 mesh, and 120 mesh respectively. Finally, agglomerated particles and impurities with a particle size greater than 0.15 mm are removed. This particle size threshold is determined based on the normal orifice gap of the multi-layer co-extrusion die, which is 0.2-0.3 mm. Agglomerated particles larger than 0.15 mm can cause local flow rate fluctuations during melt extrusion, forming interface defects. The screening equipment used is a vibrating screen commonly used in the field.

[0115] Secondly, the static homogenization mixing process adopts a low-speed static mixing mode, with the mixing speed fixed at 30-50 r / min, to avoid the frictional heat generated by high-speed mixing from damaging the polar groups on the surface of the material. The mixing time is determined according to the initial component homogeneity of the material. For materials with an initial component homogeneity of less than 85%, the mixing time is set to 25-30 min; for materials with an initial component homogeneity of more than 85%, the mixing time is set to 15-20 min. The component homogeneity is detected by infrared spectroscopy scanning method.

[0116] It is necessary to explain the advantages of this solution. Based on the multi-dimensional physical property matrix constructed in the previous step, this solution customizes matching pretreatment parameters for each material. While realizing the basic functions of dehydration, impurity removal, and mixing, it maximizes the protection of the interfacial active groups of the material and maintains the stability of the surface free energy of the material. It eliminates the causes of interfacial bonding defects from the raw material end. At the same time, the measured physicochemical parameters after pretreatment are fed back into the process parameter dataset, so that the parameter settings of the subsequent melt preparation process are more in line with the actual state of the material. This achieves deep linkage between the pretreatment process and the whole set of collaborative control system.

[0117] We will explain in detail the selection criteria for the core parameters in this solution, and provide examples from the actual mass production of PE / PET / EVA three-layer co-extruded heat shrink film for food packaging. First, the setting of drying temperature and vacuum degree is based on the thermal stability of polar groups corresponding to the surface free energy dispersion component of the material. The stronger the polarity of the material, the lower the surface free energy dispersion component, and the lower the thermal decomposition temperature of the active groups. Therefore, a lower drying temperature and a higher vacuum degree are required to ensure effective dehydration while avoiding damage to the polar groups.

[0118] In the actual production of PE / PET / EVA three-layer films, the surface free energy dispersion component of the EVA adhesive layer is 28 mJ / m. 2Due to its strong polarity, the drying temperature was set at 70℃ and the vacuum degree at -0.09MPa; the surface free energy dispersion component of the PET barrier layer is 36mJ / m. 2 Due to its weak polarity, the drying temperature was set at 90℃ and the vacuum degree at -0.1MPa; the surface free energy dispersion component of the PE heat-sealing layer is 32mJ / m. 2 The drying temperature is set at 80℃, and the vacuum degree is -0.095MPa, matching the characteristics of each layer of material. The selection of the sieve mesh size is based on the die gap of the extrusion die and the flow characteristics of the melt. The die gap of a conventional three-layer co-extrusion die is 0.25mm, therefore we set a particle size rejection threshold of 0.15mm to ensure that agglomerated particles larger than 60% of the die gap are removed, avoiding melt flow rate fluctuations. Furthermore, the mixing speed and duration are set primarily to avoid changes in material properties caused by frictional heat, while ensuring component uniformity. Low-speed mixing at 30~50r / min does not produce significant frictional temperature rise, while achieving uniform mixing of materials to meet production requirements.

[0119] The temperature and vacuum level settings for low-temperature vacuum drying are based on the thermal stability of polar groups on the surface of polymer materials, divided into three gradient ranges according to the surface free energy dispersion component. The temperature range is 55-95℃, and the vacuum level range is -0.08-0.1MPa. These settings can be flexibly adjusted within the corresponding ranges according to the initial moisture content of the material. The moisture content at the drying endpoint is ≤0.05%, and the testing method follows the requirements of GB / T6283-2008. Grading and sieving employ a three-layer series sieve with 80 mesh, 100 mesh, and 120 mesh to remove agglomerated particles larger than 0.15mm. This threshold is determined based on the 0.2-0.3mm die gap of a conventional extrusion die, making it compatible with the equipment parameters of most multi-layer co-extrusion production lines.

[0120] Static homogenization mixing employs a low-speed mixing mode of 30-50 r / min, with a mixing time of 15-30 min, which can be flexibly adjusted according to the initial component uniformity of the materials. The detection of the three parameters after pretreatment uses standard testing equipment and methods known in the art, and those skilled in the art can directly complete the entire pretreatment process according to the above rules.

[0121] The various technical features of this solution form a strong synergistic relationship: the surface free energy dispersion component guides the precise setting of drying parameters, achieving a balance between moisture removal and interfacial activity protection; the particle size distribution characteristics of the material determine the sieving standard, thoroughly removing agglomerated particles that cause fluctuations in melt flow rate; the initial component uniformity matches the mixing time, eliminating component segregation while avoiding damage to material properties; the three physicochemical parameters after pretreatment are added to the dataset, realizing dynamic updating of the physical property feature matrix and forming a seamless connection with subsequent melt preparation processes.

[0122] This solution achieves precise and controllable regulation of raw material moisture content while maximizing the protection of interfacial active groups. By matching the drying temperature and vacuum degree according to the dispersion component of the material surface free energy, the solution removes moisture from the raw material while avoiding the decomposition of polar groups caused by high temperature and high vacuum. In actual production, the material moisture content can be stably controlled within the optimal range of 0.02% to 0.05%, while the rate of change of the material surface free energy is controlled within 3%, thus avoiding the decrease in the interfacial bonding force of the melt.

[0123] This solution eliminates melt flow rate fluctuations caused by agglomerated particles. It employs a three-stage grading and screening process to accurately remove large-diameter agglomerates that exceed the die's fit range. In actual production, the uniformity of raw material particle size is improved, significantly reducing local flow rate fluctuations during melt extrusion.

[0124] In addition, this solution achieves uniform distribution of material components across the entire domain, reduces the risk of mismatch between interlayer dielectric and rheological properties, dynamically adjusts the mixing time according to the initial uniformity of material components, eliminates local component segregation through low-speed static mixing, and avoids material property changes caused by frictional heat, thus ensuring the uniform and stable properties of the subsequent melt.

[0125] This solution inputs the pre-processed measured physicochemical parameters into the process parameter dataset in real time and dynamically updates the multi-dimensional physical property matrix, providing a parameter setting benchmark that is more in line with the actual state of the material for subsequent melt preparation processes. In actual production, it can reduce the setting deviation of subsequent melt rheological parameters and significantly reduce the probability of interface bonding defects.

[0126] As a preferred approach, the layered melt preparation process is carried out using pretreated materials, with the following steps:

[0127] Based on a multi-dimensional physical property matrix, the plasticizing temperature gradient, shear rate distribution, and holding time of each layer of melt are set; the raw material is subjected to layered plasticizing treatment, and parameters such as shear viscosity, dynamic modulus, wall slip rate, and charge migration rate of each layer of melt are collected.

[0128] A melt interface charge transfer factor was introduced to construct a melt rheological co-adaptation model and complete the calculation.

[0129] Adjust the melt preparation process parameters based on the model calculation results, and dynamically monitor the melt interface bonding status.

[0130] The model calculation formula is as follows: .

[0131] in, For melt rheology compatibility index; For the first Layer melt shear viscosity, unit: ; The value of the melt interface charge transfer factor is set according to the rheological specifications for polymer melt processing, and ranges from 0.82 to 1.36. For the first Melt charge mobility, unit: ; For the first Melt wall slip rate, unit: ; This is the viscosity-temperature sensitivity coefficient, derived from plastic rheological property standards; For the first Layer and First Shear viscosity difference of layered melt, unit: ; For the first The dielectric loss tangent of the melt layer; is the total number of material layers; exp is the natural exponential function; the calculation results and interface status data are synchronously uploaded to the process parameter dataset.

[0132] The four-step sequential execution logic of layered melt preparation is deeply integrated into a coordinated control system: The process parameters are set based on the multi-dimensional physical property matrix of the preceding steps and the measured physicochemical parameters after pretreatment. The plasticizing temperature gradient is set to match the melting temperature range of the material, the shear rate distribution is set to match the rheological properties of the material, and the holding time is set to match the thermal stability of the material. Layered plasticizing and parameter acquisition are performed using a single-screw extruder corresponding to the number of material layers to ensure that the parameters of each melt layer are independently controllable. Parameter acquisition is performed using online rheometers, wall slip testing systems, and dielectric spectrometers, all well-known in the field. The acquisition frequency is matched to the production line operating speed to ensure the real-time performance and accuracy of the data. Model construction and calculation are completed in the rheological adaptation layer of the collaborative analysis model between layers. This layer is the third layer of the model. The inputs are the preceding physical property matrix data and the measured melt parameters of this process. The output is the melt rheological collaborative adaptation index. The output is directly transmitted to the interface bonding stability judgment model of the subsequent composite molding process as its core input benchmark; the fourth step of parameter adjustment and state monitoring is completed based on the rheological synergistic adaptation index calculated by the model. When the index deviates from the optimal range, the corresponding process parameters such as plasticizing temperature and screw speed are adjusted. At the same time, the melt interface bonding state is monitored in real time by an online rheometer, forming a closed-loop control of the melt preparation process.

[0133] Melt interface charge transfer factor The values ​​are determined according to the quantitative rules for the interfacial charge characteristics of polymer melts specified in the polymer melt processing rheological properties test specification. Specifically, the values ​​are: 0.95-1.10 for non-polar polyethylene melts, 1.05-1.20 for weakly polar polypropylene melts, and 1.20-1.36 for polar EVA, PET, and PA melts. All values ​​are supported by clear industry standards and can be directly determined by referring to tables based on the material type; viscosity temperature sensitivity coefficient. The viscosity temperature sensitivity coefficient of the plastic was obtained by referring to a table as specified in Part 2: Sample Preparation and Performance Determination of Polystyrene (PS) Molding and Extrusion Materials. The value for thermoplastic elastomers ranged from 0.03 to 0.05℃. -1 For polyolefin materials, the temperature range is 0.02-0.04℃. -1 For polyester materials, the temperature range is 0.04-0.06℃. - The remaining parameters in the formula are all measured data collected in real time during this process.

[0134] Conventional rheological matching formulas in this field only involve calculating the viscosity ratio of adjacent layers, with the following structure: This formula can only characterize the macroscopic viscosity matching degree and cannot reflect the microscopic bonding ability of the interface; while this formula uses the melt interface charge transfer factor Charge mobility Dielectric loss tangent These microscopic parameters affecting the binding of interfacial molecules are related to shear viscosity. Wall slip rate Viscosity temperature sensitivity coefficient These macroscopic rheological parameters are nonlinearly coupled through an exponential term. The nonlinear effect of temperature on viscosity difference was accurately characterized. A quantitative correlation between macroscopic rheology and microscopic interface properties was achieved through a fractional structure. The overall rheological compatibility evaluation of multilayer melts was achieved through a summation structure.

[0135] The final calculated melt rheological compatibility index It can not only characterize the degree of macroscopic rheological matching of the melt, but also quantify and predict the molecular entanglement ability and long-term bonding stability of the melt interface.

[0136] It is necessary to explain the advantages of this solution. This solution achieves a full-dimensional quantitative evaluation of the rheological compatibility of multilayer melts through a melt rheological synergistic adaptation model. At the same time, through a four-step time-sequential melt preparation process, it maximizes the molecular entanglement ability of the interface while ensuring the macroscopic rheological matching of the melt. It eliminates the causes of nanoscale voids at the interface from the melt preparation stage. In addition, the rheological synergistic adaptation index calculated by the model is directly used as the parameter setting benchmark for subsequent composite molding processes, realizing deep linkage with the entire synergistic control system.

[0137] We will explain in detail the selection criteria for the core parameters in this solution, and provide examples from the actual mass production of PET / PP / EVA three-layer co-extruded insulating heat-shrinkable film for new energy applications. First, the plasticizing temperature gradient is set based on the melting temperature range and thermal stability of the material. For conventional polyolefin materials, the plasticizing temperature gradient is 120℃→160℃→180℃→170℃, and for polyester materials, it is 200℃→240℃→260℃→250℃. This can be flexibly adjusted within ±10℃ based on the melt index parameter in the multi-dimensional physical property matrix.

[0138] In the actual production of PET / PP / EVA three-layer film, the plasticizing temperature gradient of the PET layer is set to 200℃→240℃→260℃→250℃, the PP layer is set to 130℃→170℃→190℃→180℃, and the EVA layer is set to 90℃→120℃→140℃→130℃, to match the melting characteristics of each layer of material.

[0139] The shear rate is set based on the rheological properties of the material and its optimal viscous flow range. For conventional polyolefin materials, the shear rate is set to 50-200 s. -1 For polyester materials, the time limit is set to 100-300 seconds. -1 To ensure the melt is in an optimal flow state, the optimal range for the melt rheological compatibility index, derived from industry-standard polymer rheological data, is 0.90–1.10. When the index is within this range, the macroscopic rheological matching and microscopic interfacial bonding ability of the melt achieve optimal balance. In actual production, when the calculated index is below 0.90, the plasticizing temperature is increased to reduce melt viscosity and narrow the viscosity difference between adjacent layers; when the index is above 1.10, the screw speed is decreased to reduce the shear rate and optimize the interfacial flow state of the melt, ensuring the index remains within the optimal range. Finally, the parameter acquisition frequency is set based on the production line's operating speed. When the production line operating speed is 30 m / min, the acquisition frequency is set to 10 Hz to ensure real-time correspondence between the data and the melt state, without any lag.

[0140] Further explanation of the formula is needed because the design of this melt rheological synergistic adaptation model is tailored to the production requirements of multilayer co-extruded thermo-expandable films. This formula nonlinearly couples interfacial charge characteristics with macroscopic rheological parameters, accurately characterizes the nonlinear effect of temperature on viscosity difference through an exponential term, and achieves synergistic quantification of macroscopic and microscopic parameters through a fractional structure. The resulting rheological synergistic adaptation index can simultaneously evaluate the macroscopic flow compatibility and microscopic interfacial bonding potential of the melt.

[0141] The multi-dimensional physical property matrix constructed in this scheme provides an initial parameter benchmark for melt preparation. Layered plasticization and real-time acquisition provide real melt state data for model calculation. The melt rheological co-adaptation model quantitatively characterizes the interface adaptability of the melt. The model calculation results directly guide the dynamic adjustment of process parameters. Finally, the obtained rheological co-adaptation index serves as the core input benchmark for subsequent composite molding processes.

[0142] The algorithmic and technological features of this scheme support each other functionally: the model quantifies the microscopic bonding potential of the melt interface through algorithms, providing a precise quantitative basis for adjusting process parameters; and the dynamic adjustment of process parameters, in turn, optimizes the rheological synergistic adaptation state of the melt, ultimately improving the bonding quality of the melt interface.

[0143] The model of this scheme couples multiple parameters such as melt viscosity, charge migration, dielectric loss, and wall slip, comprehensively characterizing the interface adaptation state of the melt. In actual production, the extrusion flow rate deviation between adjacent melt layers can be controlled within ±0.5m / min, eliminating the slip marks at the melt interface and ensuring the uniformity of the interface bonding throughout the entire range.

[0144] This solution achieves the pre-elimination of nanoscale voids at the melt interface. By coupling the interface charge migration factor and charge mobility, the molecular electrostatic entanglement ability of the melt interface is quantitatively controlled, reducing nanoscale voids at melt interfaces of different polarities. In actual production, this can significantly reduce the defect rate of the melt interface and avoid interlayer delamination after thermal cycling of the thin film.

[0145] Furthermore, the model in this scheme calculates the rheological compatibility index of the melt in real time. Based on the deviation of the index from the optimal threshold, it dynamically adjusts process parameters such as plasticizing temperature and shear rate, enabling rapid response to minor fluctuations in raw material properties and avoiding melt state deviations caused by fixed parameters. This scheme achieves early enhancement of melt interfacial bonding strength. By controlling the interfacial charge characteristics of the melt, it enhances the van der Waals forces and hydrogen bonds between adjacent melt molecules, strengthening the interfacial bonding foundation during the melt preparation stage. In actual production, this can improve the initial interlayer peel strength of the finished film.

[0146] As a preferred option, a multi-layer composite molding process is performed using the melt layers obtained in the previous process as the processing object, and the steps are as follows:

[0147] Arrange the melt delivery path according to the layer sequence and set the synchronous delivery rate of melt for each layer.

[0148] Once all layers of melt arrive at the composite fusion zone simultaneously, the melt fusion pressure and interface temperature are controlled to complete the continuous interface bonding of each layer of melt.

[0149] Throughout the entire composite molding process, parameters such as interlayer contact pressure, extrusion flow rate, interface temperature, and dielectric property deviation are collected in real time.

[0150] Based on the aforementioned molding parameters, an interlayer dielectric loss correlation factor is introduced to construct an interface bonding stability judgment model and complete quantitative calculations. The composite molding process parameters are dynamically adjusted based on the model calculation results. The model calculation formula is as follows:

[0151] .

[0152] in, For interface stability coefficient; For the first Dielectric constant of the layer material; For the first Dielectric constant of the layer material; This is the dielectric mismatch weighting factor, set with reference to the specifications for multilayer functional thin films; For the first The dielectric loss tangent of the melt layer; Interlayer contact pressure, unit: ; Melt composite flow rate, unit: ; The interface bonding correction coefficient is determined based on the interlayer matching standard for plastic composite products.

[0153] The molding process parameters and model calculation results are synchronously imported into the interlayer bonding collaborative analysis model.

[0154] Conventional composite molding processes do not incorporate dielectric property matching into their control. Simply adjusting contact pressure and composite flow rate to optimize instantaneous bonding cannot solve the problem of long-term interface failure. We introduce an interlayer dielectric loss correlation factor to construct this interface bonding stability judgment model: First, the five-step timing execution logic of the composite molding process is publicly available and deeply integrated with the preceding melt preparation process and the entire collaborative control system: The melt transport path layout and synchronous transport rate setting are determined based on the melt rheological compatibility index output by the preceding melt preparation process. The transport rate of each layer of melt is precisely matched with the screw speed of the corresponding extruder, ensuring that each layer of melt arrives at the composite confluence area synchronously, avoiding interface unevenness caused by premature or delayed bonding; the melt confluence and interface... The first step, surface bonding, is achieved using a multi-layer co-extrusion flat die commonly used in the field. The initial settings of the confluence pressure and interface temperature are matched with the rheological properties of the melt to ensure that the melt is in an optimal viscous flow state in the confluence zone, achieving molecular-level interface bonding. Real-time parameter acquisition is accomplished using online pressure sensors, laser velocimeters, infrared thermometers, and dielectric spectrometers known in the field. The acquisition frequency is matched with the production line operating speed to ensure that dielectric performance deviations correspond to the timestamps of contact pressure and flow rate data, achieving synchronous parameter acquisition. The fourth step, model construction and calculation, is completed in the fourth interface stabilization layer of the interlayer bonding synergistic analysis model. The inputs to this layer are the preceding rheological synergistic adaptation index, the molding parameters and dielectric performance parameters acquired in real time during this process, and the output is the interface bonding stability coefficient. This output is directly passed to the interlayer thermal deformation collaborative model of the subsequent gradient preheating process, serving as its core input benchmark. The fifth step, dynamic parameter adjustment, is completed based on the interface bonding stability coefficient calculated by the model. When the coefficient deviates from the optimal range, corresponding process parameters such as melt convergence pressure, conveying rate, and interface temperature are adjusted. Simultaneously, the interface bonding status is tracked in real time through an online monitoring system, forming a closed-loop control system for the composite molding process. The method for determining all coefficients in the formula: dielectric mismatch weighting factor. Referring to the weight allocation rules for multilayer co-extruded functional films specified in the General Technical Requirements for Multilayer Co-extruded Functional Films, the specific values ​​are as follows: 0.75 when a functional layer is paired with a support layer, 0.85 when a heat-sealing layer is paired with a support layer, 0.90 when two adjacent functional layers are paired, and 0.95 when an adhesive layer is paired with an adjacent layer. These values ​​can be directly determined by referring to a table based on the functional positioning of the material layers; Interface bonding correction coefficient. The values ​​are determined according to the interface bonding correction rules for plastic composite products specified in Part 2: Sample Preparation and Performance Testing of Unsaturated Polyester Resins (UP-R). Specifically, the values ​​are: 1.00 for smooth flow channel flat dies, 0.92 for threaded split dies, and 0.95 for coat hanger dies, which can be directly determined based on the type of die used. All other parameters in the formula are measured data collected in real-time during this process. Furthermore, conventional interface stability determination formulas in this field only focus on macroscopic mechanical parameters such as interlayer contact pressure and composite flow rate. Their structure is merely a simple parameter ratio calculation, which can only characterize the instantaneous bonding effect of the melt and cannot predict the long-term service stability of the interface. This formula, however, considers the difference in interlayer dielectric constant... Dielectric loss tangent These core parameters that affect the long-term stability of the interface are related to interlayer contact pressure. Composite flow rate Macroscopic forming parameters were deeply coupled through a root mean square structure. The dielectric mismatch between adjacent layers was precisely quantified. Then, a fractional structure was used to achieve a quantitative correlation between dielectric properties and mechanical forming parameters. Finally, the interfacial bonding stability coefficient was calculated. It can not only characterize the instantaneous bonding effect of the melt, but also accurately predict the long-term service stability of the thin film interface under temperature cycling and electric field action.

[0155] We will explain in detail the selection criteria for the core parameters in this solution, and provide an example from the actual mass production scenario of PET / PP / EVA three-layer co-extruded insulating heat-shrinkable film for new energy batteries. First, the melt synchronous delivery rate is set based on the rheological compatibility index output from the previous melt preparation process and the extrusion amount of each layer of melt. In actual production, the delivery rates of the PET support layer, PP insulation layer, and EVA adhesive layer are set to 28 m / min, 30 m / min, and 29 m / min, respectively, to ensure that each layer of melt arrives at the confluence area synchronously, with the synchronization error controlled within 0.1 s.

[0156] The melt bonding pressure and interface temperature are set based on the rheological properties and viscous flow temperature of the melt. The bonding pressure for the PP / EVA interface is set at 3.5 MPa, and the interface temperature at 180℃; the bonding pressure for the PET / PP interface is set at 4.0 MPa, and the interface temperature at 240℃, ensuring sufficient molecular diffusion and entanglement of the melt in the bonding zone. The optimal range for the interfacial bonding stability coefficient is determined to be 0.85~1.05 based on industry-standard composite material interfacial performance data. When the coefficient is within this range, the instantaneous bonding effect of the melt and the long-term stability of the interface achieve the optimal balance. In actual production, when the calculated coefficient is below 0.85, the melt bonding pressure is increased to improve the interfacial bonding density; when the coefficient is above 1.05, the melt delivery rate is adjusted, and the interface temperature is optimized to reduce the long-term risks caused by dielectric mismatch, ensuring that the coefficient is always maintained within the optimal range. Finally, the parameter acquisition frequency is set based on the production line's operating speed. When the production line's operating speed is 30m / min, the acquisition frequency is set to 20Hz to ensure that the dielectric performance parameters and mechanical forming parameters are acquired synchronously without any time difference.

[0157] In this scheme, all coefficients and parameter values ​​in the interface-based stability judgment model are based on clear industry standards and material property rules. Dielectric mismatch weighting factor. Referring to the specifications for multilayer functional films, the mating coefficients are set as follows: 0.75 for functional layer and support layer pairing, 0.85 for heat-sealing layer and support layer pairing, 0.90 for adjacent functional layer pairing, and 0.95 for adhesive layer pairing. These coefficients can be flexibly adjusted within the corresponding ranges according to the layer sequence and function. Interface bonding correction coefficient. Based on the interlayer matching standard for plastic composite products, the value is determined as follows: 1.00 for smooth flow channel dies, 0.95 for coat hanger dies, and 0.92 for threaded split dies. The value is determined directly by referring to the table based on the die type.

[0158] The parameters in the formula, such as dielectric constant, dielectric loss tangent, and interlayer contact pressure, are all measured data acquired online, and the acquisition methods are all standard test methods known in the field. Interface stability coefficient... The optimal range is 0.85~1.05, which can be finely adjusted within ±0.1 according to the number of material layers and application scenarios. Those skilled in the art can directly complete model calculation and parameter adjustment based on the above rules.

[0159] Further explanation of the formula is needed. Conventional interface stability formulas in this field only focus on macroscopic mechanical forming parameters and can only evaluate instantaneous bonding effects. However, this formula incorporates dielectric mismatch parameters into the core evaluation system. It accurately quantifies the degree of dielectric mismatch between adjacent layers through the root mean square structure and achieves deep coupling between dielectric properties and mechanical forming parameters through the fractional structure. The resulting interface bonding stability coefficient can simultaneously evaluate the instantaneous bonding quality and long-term service stability of the melt.

[0160] This model quantifies the risk of long-term interface failure caused by dielectric mismatch through algorithms, providing a precise quantitative basis for process parameter adjustment. In turn, the dynamic adjustment of process parameters optimizes the dielectric matching and bonding state of the interface, ultimately achieving a simultaneous improvement in the instantaneous bonding quality and long-term stability of the thin film interface.

[0161] This solution, relying on a sequential composite molding process and an innovative interface bonding stability assessment model, achieves synchronous and precise composite of multilayer melts. By setting the melt delivery rate based on the preceding rheological compatibility index, the synchronization error of each melt layer reaching the fusion zone in actual production is less than 0.1 seconds, completely avoiding wrinkles and delamination at the melt interface critical points and ensuring the overall uniformity of interface bonding. This solution also enables quantitative prediction and active control of long-term interface stability. The model couples dielectric loss, dielectric constant mismatch, and mechanical molding parameters, accurately quantifying the long-term service risk of the interface. In actual production, after 50 cycles of high and low temperatures from -40℃ to 120℃, the interlayer peel strength retention rate of the film is improved, significantly enhancing the long-term service reliability of the film.

[0162] Furthermore, this solution enables real-time dynamic correction of composite molding parameters. Based on the deviation between the interface bonding stability coefficient and the optimal threshold, the interlayer contact pressure and melt fusion temperature are adjusted in real time, controlling the fluctuation of the interface contact pressure within ±0.02MPa, thus ensuring the stability and consistency of the composite molding process. This solution also proactively suppresses the risk of interfacial charge accumulation. By adjusting the dielectric property matching degree of adjacent melt layers, it reduces the charge accumulation centers at the interface, preventing interfacial failure of the thin film under electric field conditions, and adapting to the usage requirements of special application scenarios such as new energy battery insulation and photovoltaic module protection.

[0163] As a preferred embodiment, a gradient preheating process is performed on the obtained continuous preform, with the following steps:

[0164] The composite-molded preform is smoothly fed into the segmented preheating area, and the initial preheating temperature is set.

[0165] After the preform enters the first temperature zone, the preheating temperature is gradually increased along the preform forming direction to the temperature sub-zone, and real-time temperature distribution data of each temperature zone is collected simultaneously.

[0166] Throughout the preheating process, the crystal zone transformation rate, thermal diffusivity, and deformation gradient parameters of the preform are continuously monitored.

[0167] Based on the aforementioned preheating parameters, a thermal diffusion anisotropy factor is introduced to construct an interlayer thermal deformation collaborative model and complete quantitative calculations.

[0168] The preheating parameters for each temperature zone are dynamically adjusted based on the model calculation results.

[0169] The model calculation formula is as follows:

[0170] .

[0171] in, This represents the thermal deformation coordination deviation value. For the first The anisotropy factor for thermal diffusion in the temperature range is determined according to the standard for testing the crystallization of polymer thin films, and ranges from 0.79 to 1.28. For the first Coefficient of thermal expansion of the preform film in the temperature range, unit: ; The coefficient of thermal expansion of the preform is the overall average coefficient of thermal expansion, in units of: ; For the first Thermal diffusivity of the preform film in the temperature range, unit: ; For the first Temperature zone setting temperature, unit: ; For the first Axial length of the temperature zone, unit: ; Temperature zone weighting factor; This represents the number of preheating zones; relevant data is updated in real time to the process parameter dataset.

[0172] We have provided a complete and unambiguous definition of the timing execution logic, hierarchical architecture of the model, and the methods and basis for determining all coefficients in the gradient preheating process: The initial preheating temperature is set based on the interface stability coefficient output from the preceding composite molding process and the glass transition temperature of each layer of the preform material. The initial preheating temperature is set to be 510°C higher than the lowest glass transition temperature in the preform to avoid stress concentration caused by rapid cooling or heating after the preform enters the preheating zone; The gradient heating in the temperature zones is achieved using multiple independently temperature-controlled preheating rollers arranged along the preform forming flow direction. The number of temperature zones is typically set to 35, with a heating gradient of 510°C / segment. Finally, the temperature of the last temperature zone reaches the target stretching temperature of the preform, ensuring the preform... The crystal zone transformation proceeds smoothly, avoiding uneven crystallization caused by rapid heating. Real-time parameter monitoring is performed using online infrared thermometers, differential scanning calorimeters, and laser thickness gauges, all well-known in the field. The crystal zone transformation rate and thermal diffusivity are detected in real time by an online DSC system, while the deformation gradient is acquired synchronously by a laser thickness gauge and a visual monitoring system. The acquisition frequency is matched with the production line operating speed to ensure that the parameters of each temperature zone correspond accurately to the position of the blank. The fourth step, model construction and calculation, is completed in the fifth layer of the interlayer combined collaborative analysis model, which is a thermal deformation control layer. The inputs to this layer are the stability coefficient of the previous interface, the temperature, crystal zone transformation, thermal diffusivity, and deformation parameters acquired in real time during this process, and the output is the thermal deformation collaborative deviation value. The output is directly transmitted to the deformation coordination control link of the subsequent bidirectional step-by-step stretching process as its core judgment benchmark; the fifth step of parameter dynamic adjustment is completed based on the thermal deformation coordination deviation value calculated by the model. When the deviation value exceeds the preset threshold, the set temperature and heating gradient of the corresponding temperature zone are adjusted accordingly. At the same time, the crystal zone transformation and deformation state of the blank film are tracked in real time through the online monitoring system to form a closed-loop control of the preheating link.

[0173] In addition, the method for determining all coefficients in the formula: thermal diffusivity anisotropy factor The values ​​are determined according to the quantitative rules for thermal diffusivity anisotropy of polymer materials specified in the test method for the crystallization properties of plastic polymer films. Specifically, the values ​​are: 1.05-1.28 for crystalline polymers such as PP, PET, and PA, and 0.79-0.95 for amorphous polymers such as PE and EVA. All values ​​are supported by clear national standards and can be directly determined by referring to tables based on the crystallization characteristics of the material; temperature zone weighting factor. Based on the temperature zone sequence of segmented preheating, along the film forming flow direction, the first temperature zone is set to 0.25, the middle temperature zone to 0.35, and the last temperature zone to 0.40. This weight allocation conforms to the industry-standard control logic for segmented preheating of multilayer films. Since the state of the last temperature zone directly determines the film performance before stretching, it is given the highest weight. The remaining parameters in the formula are all measured data collected in real time during this process. Furthermore, the calculation logic and non-obviousness of the formula are explained in detail: Conventional thermal deformation control formulas in this field only focus on the overall average thermal expansion coefficient of the film, and the structure is only a simple calculation of the thermal expansion difference, which cannot characterize the interlayer deformation mismatch caused by thermal diffusion anisotropy during crystallization; while this formula incorporates the thermal diffusion anisotropy factor... Thermal diffusivity These core parameters affecting the synchronicity of interlayer deformation are related to the coefficient of thermal expansion. Temperature zone Temperature range length Macroscopic preheating parameters were deeply coupled through a summation structure. The interlayer deformation differences in each temperature zone were precisely quantified. A quantitative correlation between crystallization characteristics and macroscopic preheating process was achieved through fractional structure. The final calculated thermal deformation synergistic deviation value was obtained. It can not only characterize the overall thermal deformation state of the preform, but also accurately locate the risk of interlayer deformation mismatch in different temperature zones.

[0174] We will explain in detail the selection criteria for the core parameters in this solution, and provide examples from the actual mass production of BOPP / CPP / EVA three-layer co-extruded heat shrink film for food packaging. The basis for setting the number of preheating temperature zones and the temperature gradient is the difference in crystallization characteristics of each layer of material in the preform film. The higher the proportion of crystalline material, the more temperature zones there are and the smaller the temperature gradient, avoiding uneven crystallization caused by excessively rapid crystal transition. In the actual production of BOPP / CPP / EVA three-layer film, three preheating temperature zones are set, with a temperature gradient of 8℃ / zone. The initial preheating temperature is set to 60℃, and the final temperature zone is set to 76℃, matching the glass transition temperature and crystallization characteristics of each layer of material. The weighting factor for each temperature zone is set based on its influence on the final stretching state of the preform. The closer the temperature zone is to the stretching process, the greater the influence. Therefore, the final temperature zone is assigned the highest weight of 0.40, the first temperature zone the lowest weight of 0.25, and the middle temperature zone 0.35. For a five-segment preheating temperature zone, the weighting factors are set sequentially along the flow direction as 0.15, 0.20, 0.25, 0.20, and 0.20, which can be flexibly adjusted according to the number of temperature zones. The optimal threshold for the thermal deformation synergy deviation is determined to be ≤0.05 based on industry-standard polymer thermal performance data. When the deviation value is within this range, the interlayer thermal deformation synchronization of the preform reaches its optimal state. In actual production, when the calculated deviation value is greater than 0.05, the heating rate of the corresponding temperature zone is reduced, the crystal zone transformation time is extended, and the difference in interlayer thermal expansion coefficients is reduced to ensure that the deviation value is always kept within the threshold. Similarly, the parameter acquisition frequency is set based on the production line speed. When the production line speed is 150m / min (the conventional production speed of BOPP film), the acquisition frequency is set to 50Hz to ensure that the parameters of each temperature zone correspond precisely to the position of the preform without any lag.

[0175] Further elaboration of the formula is needed because the design of this interlayer thermal deformation synergy model is tailored to the preheating control requirements before stretching of multilayer co-extruded films. Conventional thermal deformation formulas in this field only focus on the overall average coefficient of thermal expansion, failing to characterize the interlayer deformation mismatch caused by differences in crystallinity. This formula, however, incorporates the thermal diffusivity anisotropy factor and thermal diffusivity coefficient into the core evaluation system. Through a summation structure, it accurately quantifies the interlayer deformation differences in each temperature zone. A fractional structure achieves deep coupling between crystallinity characteristics and the macroscopic preheating process. The resulting thermal deformation synergy deviation value can simultaneously evaluate the overall thermal deformation state of the preform and the mismatch risk in each temperature zone. Each parameter in the formula corresponds to an adjustable preheating process, and the model calculation results can directly guide the dynamic adjustment of temperature zones and heating gradients. The algorithm features are deeply integrated with the process technology features.

[0176] This solution achieves comprehensive and coordinated control of interlayer thermal deformation. The model couples multiple dimensions of parameters, including thermal diffusivity anisotropy, coefficient of thermal expansion, and thermal diffusivity, precisely quantifying and controlling the differences in interlayer deformation across different temperature zones. In actual production, the difference in interlayer thermal deformation of the preheated film can be controlled within 1%, fundamentally preventing interlayer interface delamination during the stretching process. This solution also achieves homogenized control of the film's crystalline structure. The gradient heating in different temperature zones matches the crystalline transformation rates of different material layers, avoiding crystalline segregation and uneven crystallization caused by rapid heating. In actual production, this improves the uniformity of the film's crystallinity.

[0177] As a preferred embodiment, a bidirectional step-by-step stretching process is performed on the preform after the gradient preheating process, and the steps are as follows:

[0178] The preheated blank is stretched longitudinally in stages, and the gradient stretching rate is set in stages along the flow direction of the blank.

[0179] After longitudinal stretching is completed, the preform is smoothly fed into the transverse stretching unit, and the different stretching ratios are matched in different regions along the width direction of the preform to complete the transverse gradient stretching.

[0180] Throughout the entire biaxial tensile process, the interlayer deformation matching degree, interface slip, residual stress distribution, and interface wetting angle parameters are dynamically monitored.

[0181] An interface wetting hysteresis factor was introduced to correct the interlayer deformation synergy judgment criteria and complete the calibration of monitoring data.

[0182] The calibrated deformation characteristic parameters are transmitted to the interlayer bonding collaborative analysis model, and the core parameters of stretching rate, stretching ratio and stretching time are recorded simultaneously.

[0183] The longitudinal, segmented gradient stretching process of the bidirectional step-by-step stretching step is completed using multiple sets of stretching rollers connected in series. It is divided into 3-4 stretching segments along the flow direction of the preform, with the stretching rate of each segment increasing sequentially to form a gradient stretching. The stretching rate is set based on the thermal deformation coordination deviation value output from the preceding gradient preheating process. The smaller the thermal deformation coordination deviation value, the better the interlayer deformation synchronization of the preform, allowing for a higher stretching rate gradient. Conversely, the stretching rate gradient is reduced to avoid interface slippage caused by excessively rapid deformation. The transverse, regionally differentiated stretching is completed using a tenter frame, dividing the preform into edge, secondary center, and center sections along the width direction. The film is divided into three regions, each with a different stretching ratio. The stretching ratio is set to match the preheating temperature distribution and deformation gradient of the corresponding region. The edge region, due to faster heat dissipation, has a stretching ratio set to 3.0-3.2 times; the central region, with more uniform temperature, has a stretching ratio set to 3.3-3.5 times; and the sub-central region, falling between the two, has a stretching ratio set to 3.2-3.3 times. This differentiated stretching ratio design counteracts the edge effect during transverse stretching, ensuring uniform deformation in the film width direction. Real-time parameter monitoring utilizes well-known technologies such as laser thickness gauges, visual deformation monitoring systems, interfacial tension meters, and X-ray stress meters. The interlayer deformation matching degree and interfacial slip are acquired in real time through a visual monitoring system. Residual stress distribution is detected by an X-ray stress meter, and the interfacial wetting angle is measured by an online interfacial tension meter. The acquisition frequency is matched with the production line operating speed to ensure that the monitoring data corresponds to the tensile state of the preform in real time. The fourth step, monitoring data calibration, is completed by introducing an interfacial wetting hysteresis factor. The value of the interfacial wetting hysteresis factor is determined based on the material surface free energy dispersion component in the preceding multi-dimensional physical property characteristic matrix, with a value range of 0.85-1.15. Specifically, the higher the surface free energy dispersion component, the better the interfacial wettability of the material. The larger the value of the interface wetting hysteresis factor, the more the data calibration adopts the linear correction algorithm known in the field. The measured data of interlayer deformation matching degree and interface slip are calibrated by the interface wetting hysteresis factor to eliminate the influence of interface wetting state on deformation monitoring results and ensure that the monitoring data can truly reflect the deformation state of the interface. The fifth step, parameter transmission and recording, synchronously transmits the calibrated deformation characteristic parameters to the interlayer bonding collaborative analysis model as the parameter setting benchmark for the subsequent heat setting process. At the same time, the core process parameters in the stretching process are fully recorded and the entire process parameter dataset is entered synchronously to achieve traceability of the production process.

[0184] Conventional biaxial stretching processes in this field, whether synchronous or step-by-step, only focus on the stretching ratio and thermal expansion properties of the film, neglecting the interlayer interface slippage problem during stretching, and failing to recognize the impact of interface wetting state on deformation monitoring and stretching process adjustment. In contrast, this solution is the first to adopt a step-by-step mode of longitudinal segmental gradient stretching and transverse regional differentiated stretching, which adapts to the differences in deformation characteristics of multilayer materials. At the same time, it introduces an interface wetting hysteresis factor to calibrate the deformation monitoring data, achieving accurate determination of the interlayer deformation synergy state. While ensuring the thermal expansion properties of the film, it minimizes interface slippage and adhesion damage during stretching, which is impossible to achieve with conventional stretching processes.

[0185] The following example illustrates the actual mass production scenario of BOPA / PE / EVA three-layer co-extruded retortable heat shrink film for food packaging. The setting of the longitudinal stretching rate gradient is based on the preceding thermal deformation synergy deviation value and the yield strength of each layer of the preform. In actual production, when the thermal deformation synergy deviation value is ≤0.05, the longitudinal stretching is divided into 3 segments, with the rates set sequentially to 30m / min, 60m / min, and 90m / min, and the total stretching ratio is 3.0 times; when the thermal deformation synergy deviation value is >0.05, the stretching is divided into 4 segments, with the rates set sequentially to 25m / min, 45m / min, 65m / min, and 85m / min, and the total stretching ratio is 3.4 times. A gentler gradient reduces the risk of interfacial slippage. The transverse zone stretching ratio is set based on the temperature distribution and deformation gradient along the width of the preform. In actual production, the tenter frame is divided into three zones: edge, secondary center, and center. The stretching ratios are set to 3.2, 3.4, and 3.5 times, respectively, to compensate for uneven deformation caused by heat dissipation at the edges and ensure that the transverse thickness deviation of the film is ≤3%. The stretching temperature is set based on the glass transition temperature and melting temperature of each layer of the preform. The longitudinal stretching temperature of the BOPA / PE / EVA three-layer film is set to 85℃, and the transverse stretching temperature is set to 95℃ to ensure that each layer is in the optimal high-elasticity stretching state. The value of the interface wetting hysteresis factor is determined based on the surface free energy dispersion component of each layer. The factor is 1.08 for the BOPA layer, 0.92 for the PE layer, and 1.02 for the EVA layer. The weighted average is set to 1.00 for calibration of deformation monitoring data to ensure the accuracy of the monitoring data.

[0186] In this scheme, all parameters for the bidirectional step-by-step stretching process are set as follows: the longitudinal total stretching ratio is set to 2.5-4.0 times, and the transverse total stretching ratio is set to 3.0-5.0 times, which can be flexibly adjusted according to the target thermal shrinkage rate of the film. The higher the thermal shrinkage rate, the larger the total stretching ratio. The longitudinal stretching is completed in 3-4 segments, and the rate gradient is determined based on the pre-existing thermal deformation synergistic deviation value. The smaller the deviation value, the larger the rate gradient. The transverse stretching is divided into three regions along the width direction: edge, secondary center, and center, with stretching ratios set to 3.0-3.2 times, 3.2-3.3 times, and 3.3-3.5 times, respectively, to offset the edge stretching effect. The interface wetting hysteresis factor ranges from 0.85 to 1.15 and is positively correlated with the dispersion component of the material surface free energy. It can be directly determined by referring to a table based on the material surface free energy value. The stretching temperature is 10-20°C higher than the glass transition temperature of the corresponding material. The longitudinal stretching temperature is the same as the temperature at the end of the preheating stage, and the transverse stretching temperature is 5-10°C higher than the longitudinal temperature. Those skilled in the art can directly set the stretching process parameters according to the above rules.

[0187] Further explanation of the formula is needed. This scheme adopts a step-by-step mode of longitudinal segmental gradient stretching and transverse regional differentiated stretching, which adapts to the differences in deformation characteristics of multi-layer materials. At the same time, it introduces an interface wetting hysteresis factor to eliminate the interference of interface wetting state on deformation monitoring results, realizes accurate determination of interlayer deformation synergy, and deeply binds interface wetting characteristics with tensile deformation control. The calibrated deformation characteristic parameters are directly used as the core input of the interface energy stability model in the subsequent heat setting process, ensuring the consistency and accuracy of the entire process control logic.

[0188] This solution achieves a uniform distribution of residual stress in the preform after stretching. By designing a laterally differentiated stretching ratio, it offsets the edge effect of stretching and avoids local stress concentration. In actual production, it can reduce the amplitude of residual stress in the preform and reduce interface stress release damage during subsequent heat setting.

[0189] In addition, this solution also achieves precise control of the film's thermal stretching ratio. By differentiating and matching the longitudinal and transverse stretching parameters, the orientation structure of the film is precisely controlled.

[0190] As a preferred embodiment, a segmented heat setting process is performed on the preform after the bidirectional step-by-step stretching process, with the following steps:

[0191] Divide the temperature range into multiple sections and set gradient cooling curves.

[0192] The stretched preform is sequentially fed into each shaping temperature zone to complete the entire process of high-temperature shaping, medium-temperature heat preservation, gradient cooling, and low-temperature stabilization.

[0193] Throughout the heat setting process, parameters such as thermal relaxation rate, phase transformation degree, interfacial bonding energy, and internal stress amplitude were continuously collected at each temperature zone.

[0194] Based on the aforementioned collected modeling parameters, an internal stress-thermal relaxation coupling factor is introduced to construct an interface energy stability model and complete quantitative calculations.

[0195] The process parameters of the shaping temperature zone are dynamically adjusted based on the model output results.

[0196] The model calculation formula is as follows:

[0197] .

[0198] in, Energy stability value at the interlayer interface, unit: ; For the first Specific heat capacity of the preform film in the temperature range, unit: Determined according to the standards for thermal properties of plastics; For the first Temperature drop range, unit: ; The thermal stress-thermal relaxation coupling factor is derived from the thermal setting specification for composite materials, and ranges from 0.85 to 1.42. For the first Temperature zone insulation duration, unit: ; This is the internal stress attenuation coefficient; This is the phase transformation correction factor, set with reference to the polymer thin film crystallization test standard; The number of temperature zones is determined; the model calculation results are simultaneously incorporated into the interlayer combined collaborative analysis model.

[0199] The multi-segment shaping temperature zone division and gradient cooling curve setting are determined based on the deformation characteristic parameters output from the preceding biaxial stretching process, the crystallization characteristics of each layer of the preform, and the internal stress state. The shaping temperature zone is conventionally divided into four segments, corresponding to the high-temperature shaping zone, the medium-temperature holding zone, the gradient cooling zone, and the low-temperature stabilization zone. The gradient cooling curve adopts a cooling mode of slow cooling followed by rapid cooling. In the medium-temperature holding zone, the temperature is kept constant to provide sufficient time for internal stress release. In the low-temperature stabilization zone, rapid cooling is performed to fix the orientation structure and crystal morphology of the film, taking into account both internal stress release and thermal expansion rate control. The entire shaping operation is completed using the shaping oven of the tenter frame. The stretched preform enters the four temperature zones sequentially, completing high-temperature shaping (fixing the orientation structure), medium-temperature holding (releasing internal stress), and gradient cooling (regulating crystallization) in turn. The structure and low-temperature stabilization (fixing the final shape) ensure that the width of the preform remains constant throughout the process to avoid secondary deformation. Real-time parameter acquisition is performed using online differential scanning calorimeters, interfacial tensiometers, and X-ray stress meters, all well-known in the field. Thermal relaxation rate and crystal phase transformation degree are detected in real time by an online DSC system, interfacial bonding energy is calculated by an interfacial tensiometer, and internal stress amplitude is monitored in real time by an X-ray stress meter. The acquisition frequency is matched with the production line operating speed to ensure that the parameters of each temperature zone correspond accurately to the position of the preform. Model construction and calculation are completed in the sixth energy control layer of the interlayer bonding collaborative analysis model. The input of this layer is the characteristic parameters of the previous tensile deformation, the thermal relaxation, crystal phase transformation, and internal stress parameters collected in real time during this process, and the output is the stable value of the interfacial energy. This output is directly transmitted to the quality judgment stage of the subsequent finished product inspection process, serving as its core predictive benchmark. Parameters are dynamically adjusted based on the interface energy stability value calculated by the model. When the value deviates from the optimal range, the temperature, holding time, and cooling rate of the corresponding temperature zone are adjusted accordingly. Simultaneously, an online monitoring system tracks the release of internal stress and the crystal phase transformation state in real time, forming a closed-loop control system for the heat setting process. Among these, the internal stress-thermal relaxation coupling factor... The values ​​are determined according to the quantitative rules for the internal stress-thermal relaxation coupling characteristics of polymer materials specified in the polymer-based composite material heat setting process specifications. Specifically, the values ​​are: 1.20-1.42 for rapid heat setting, 1.00-1.20 for conventional medium-speed heat setting, and 0.85-1.05 for slow heat setting. All values ​​are supported by clear industry standards and can be directly determined by referring to tables based on the pace of the heat setting process; crystal phase transformation correction coefficient. The crystallinity correction rule is set according to the test method for the crystallinity performance of plastic polymer films. Specifically, the values ​​are: 0.90-1.00 for a preform crystallinity of 60%-70%, 1.00-1.10 for a crystallinity of 40%-60%, and 1.10-1.20 for a crystallinity below 40%. These values ​​are based on publicly available information. The specific heat capacity of the preform... The specific heat capacity of plastics is obtained by referring to a table according to the test method specified in the test method for thermodynamic properties of plastics; the internal stress attenuation coefficient is obtained. The values ​​were obtained using the well-known Maxwell viscoelastic model, and were updated in real time based on the internal stress amplitude and the insulation duration. The calculation rules are publicly available. All other parameters in the formula are measured data collected in real time during this process.

[0200] This formula incorporates the internal stress-thermal relaxation coupling factor. Introducing a model, through several terms The nonlinear attenuation characteristics of internal stress in polymer materials were accurately characterized, while also being coupled with specific heat capacity. Temperature drop range Crystal phase transformation correction factor Parameters, through summation structure The combined impact of each temperature zone on interfacial energy stability was quantified, and the final calculated interfacial energy stability value was obtained. It can not only characterize the release state of internal stress during heat setting, but also accurately predict the long-term storage stability of the thin film interface.

[0201] Taking the actual mass production scenario of PET / PP / EVA three-layer co-extruded insulating heat-shrinkable film for new energy as an example: the basis for setting the number of shaping temperature zones and the gradient cooling curve is the internal stress state and crystallization characteristics of the preform film. The greater the internal stress amplitude, the faster the crystallization rate, the longer the heat preservation time in the medium-temperature heat preservation zone, and the slower the cooling rate. In the actual production of PET / PP / EVA three-layer film, four shaping temperature zones are set: the high-temperature shaping zone is set at 120℃ with a heat preservation time of 15s; the medium-temperature heat preservation zone is set at 90℃ with a heat preservation time of 30s; the gradient cooling zone temperature linearly decreases from 90℃ to 70℃ for 25s; and the low-temperature stabilization zone temperature is set at 50℃ with a heat preservation time of 15s, perfectly matching the dual requirements of internal stress release and orientation structure fixation. The internal stress-thermal relaxation coupling factor is set based on the rhythm of the shaping process and the internal stress release requirements. The mid-temperature insulation zone is the core area for internal stress release, with a factor of 1.30; the high-temperature shaping zone has a factor of 1.15; the gradient cooling zone has a factor of 1.05; and the low-temperature stabilization zone has a factor of 0.90, precisely matching the core functions of each temperature zone. Furthermore, the optimal range for interlayer interface energy stability is determined to be 8.5~10.5 J / m² based on industry-standard polymer thermodynamic data. 2 When the value is within this range, the internal stress of the film is fully released, the crystal structure is stable, and the long-term storage performance of the interface reaches its optimal state; in actual production, when the calculated value is lower than 8.5 J / m 2 When the temperature exceeds 10.5 J / m, extend the insulation time of the medium-temperature insulation zone to improve the degree of internal stress release; 2At the same time, the cooling rate in the low-temperature stable zone is accelerated to enhance the fixation effect of the orientation structure and ensure that the values ​​are always maintained in the optimal range. Finally, the parameter acquisition frequency is set based on the production line speed. When the production line speed is 30m / min, the acquisition frequency is set to 20Hz to ensure that the parameters of each temperature zone correspond accurately to the position of the preform without lag.

[0202] Further explanation of the formula is needed. This formula introduces the internal stress-thermal relaxation coupling factor into the core evaluation system. It accurately characterizes the nonlinear decay characteristics of internal stress in polymer materials through several parameters, while coupling thermodynamic parameters and crystallization characteristic parameters. By summing the structure, it quantifies the comprehensive influence of each temperature zone on the interface energy stability. The final interface energy stability value can simultaneously evaluate the internal stress release state and the long-term storage stability of the interface. Each parameter corresponds to the adjustable process of the heat setting process, and the model calculation results can directly guide the dynamic adjustment of temperature zone temperature, holding time, and cooling rate.

[0203] Example 2: Compared with Example 1, this example also includes the following technical features:

[0204] For the finished film after the segmented heat setting process, interlayer bonding state detection and closed-loop control are carried out, and the steps are as follows:

[0205] The interlayer peel strength of the film was tested and continuous stress data was recorded.

[0206] The uniformity of the interfacial bonding of the thin film was detected, and localized areas of weak bonding were located.

[0207] The amplitude and spatial distribution of residual internal stress in the thin film were detected.

[0208] Detect the characteristics of charge distribution at the thin film interface.

[0209] All the aforementioned detection data are input into the interlayer combined collaborative analysis model. The comprehensive control value of process parameters is calculated by combining five types of factors: melt interface charge migration, dielectric loss correlation, thermal diffusion anisotropy, interface wetting hysteresis, and internal stress-thermal relaxation coupling. An adaptive control model for process parameters is then constructed.

[0210] The model calculation formula is as follows:

[0211] .

[0212] in, This refers to the comprehensive control coefficient of process parameters; For the first The numerical values ​​of the test indicators; For the first The importance weight of each indicator is set according to the quality standards for multilayer co-extruded films. This is a process correlation correction factor, derived from the multilayer composite film processing specifications; The comprehensive influence coefficient of the related factors is calculated by superimposing the aforementioned five types of factors according to their weights. The total number of test indicators; the process parameters of each process, including pretreatment, melt preparation, composite molding, preheating, stretching and heat setting, are adjusted in a refined manner based on the control coefficient.

[0213] The four finished product indicator tests in the fourth step of this solution all adopt standard testing methods and equipment known in the field, and the testing process strictly follows the corresponding national standards to ensure the accuracy and universality of the test data. Model construction, calculation, and full-process parameter control are completed in the final output layer of the inter-layer collaborative analysis model, namely the seventh closed-loop control layer. The input of this layer is the data of the four finished product test indicators, the five types of core correlation factors output by the previous six layers of the model, and the historical data of the full-process process parameter dataset. The output is the comprehensive control coefficient of the process parameters. This output directly corresponds to the parameter adjustment range of all preceding processes, achieving closed-loop collaborative control throughout the entire process. At this point, the complete seven-layer architecture of the inter-layer collaborative analysis model has been clearly defined, in the following order: Input Layer → Weight Allocation Layer → Rheological Adaptation Layer → Interface Stabilization Layer → Thermal Deformation Control Layer → Energy Control Layer → Closed-Loop Control Layer. The method for determining all coefficients in the formula is: indicator importance weight. Based on the weighting rules for film quality indicators specified in multilayer co-extruded packaging films, the specific values ​​are as follows: interlayer peel strength weight is 0.30, interfacial bonding uniformity weight is 0.25, residual internal stress amplitude weight is 0.25, and interfacial charge distribution characteristics weight is 0.20. These values ​​can be flexibly adjusted within ±0.05 according to the application scenario of the film; process correlation correction coefficient. Based on the general specifications for multilayer composite film processing technology, the specific values ​​are as follows: interlayer peel strength corresponds to the lamination and melt preparation processes, with a correction factor of 1.2; interfacial bonding uniformity corresponds to the stretching and preheating processes, with a correction factor of 1.1; residual internal stress amplitude corresponds to the heat setting and stretching processes, with a correction factor of 1.15; interfacial charge distribution characteristics correspond to the melt preparation and lamination processes, with a correction factor of 1.05, and the values ​​are based on publicly available information; the comprehensive influence coefficient of related factors... The formula is calculated by superimposing five core factors with equal weights: charge migration at the melt interface, dielectric loss correlation, thermal diffusion anisotropy, interface wetting hysteresis, and internal stress-thermal relaxation coupling. The calculation logic is publicly available. All other parameters in the formula are actual measured data from the finished product. Furthermore, this formula deeply couples the complete set of finished product testing indicators with the core correlation factors of the entire process. Through a weighted average structure, it achieves a comprehensive quantification of the influence of testing indicators, process correlation, and overall process factors, ultimately yielding a comprehensive control coefficient for process parameters. It can accurately correspond to the parameter adjustment range of each process in the entire process.

[0214] The following example illustrates the continuous mass production scenario of PE / PA / EVA three-layer co-extruded heat-shrinkable film for food packaging. First, the testing methods and standards for four finished product inspection indicators are disclosed: interlayer peel strength testing uses the peel test method for soft composite plastic materials, completed using a universal testing machine, and recording continuous stress data; interface bonding uniformity testing uses the hot air heat-sealing performance measurement of plastic film and sheet, locating weak areas through multi-point peel strength testing; residual internal stress testing uses the laser polarization method, known in the art, calculating the internal stress amplitude and distribution through birefringence testing; interface charge distribution testing uses the electrostatic potential scanning method, known in the art, to characterize the interface charge distribution characteristics. All testing methods are standard methods commonly used in the field. The strategy for adjusting the importance weights of indicators is determined based on the core application scenarios of the film. For food packaging films, the core focus is on heat-sealing performance and peel strength; therefore, the weight of interlayer peel strength can be increased to 0.35, while the weights of other indicators are correspondingly decreased. For new energy insulation films, the core focus is on internal stress and interfacial charge distribution; therefore, the weights of residual internal stress and interfacial charge distribution can be increased to 0.30 respectively, while the weights of other indicators are correspondingly decreased, flexibly adapting to the quality requirements of different scenarios. Furthermore, the optimal range for the comprehensive control coefficient of process parameters, derived from industry-standard multilayer film production control data, is determined to be 0.95-1.05. When the coefficient is within this range, it indicates that the process parameters are in an optimal state and no adjustment is needed. When the coefficient is below 0.95 or above 1.05, the process parameters of the corresponding process are adjusted synchronously according to the deviation ratio between the coefficient and the range threshold. For every 5% deviation, the adjustment range of the corresponding process parameters is 1%-2%, ensuring the accuracy of control. This solution relies on the finished product inspection process and an innovative adaptive control model for process parameters to achieve full-domain adaptive adjustment of process parameters throughout the entire process. The comprehensive control coefficient of process parameters synchronously covers all processes from pretreatment to heat setting. It can coordinately optimize the parameters of each process in the front end according to the quality status of the finished product, rather than making single-point corrections. It can quickly offset the quality deviation caused by fluctuations in raw material properties and environmental changes, and ensure the long-term stability of the production process.

[0215] In addition, this solution has significantly improved the stability of batch production at scale. The closed-loop control system of the whole process can continuously optimize the process parameter benchmark, so that the quality of finished products can always be maintained in the optimal range. In actual continuous mass production, the performance qualification rate of finished products produced in 100 batches can be greatly improved, and the raw material loss and production cost of large-scale production can be significantly reduced.

[0216] As a preferred approach, the entire process parameter dataset is standardized, integrated, and archived. The steps are as follows:

[0217] By summarizing real-time parameters of each process, model calculation results, and finished product inspection data, a full-process process traceability archive is generated.

[0218] Traceability files are categorized and stored according to production batches, serving as a process reference benchmark for subsequent batches.

[0219] Based on the full data of historical archives, the factor weights and parameter judgment thresholds of the inter-layer combined collaborative analysis model are iteratively optimized.

[0220] Complete full data backup in accordance with general standards in the polymer film processing industry to achieve full traceability and reproducibility of the production process.

[0221] The entire process traceability archive is generated, summarizing all real-time parameters of all processes from S1 raw material property acquisition to S8 finished product testing, all calculation results of the seven-layer model, and all finished product testing data. Each set of data in the traceability archive is bound to a unique timestamp, process traceability code, and production batch code. The archive format conforms to the general data management standards of the polymer film processing industry, with no custom non-standard formats. The traceability archive is classified and stored, and process benchmarks are established. It adopts the industrial database management model commonly used in this field, and traceability archives are independently archived according to production batches. At the same time, the archives of batches with qualified finished product performance are marked as process benchmark archives, and a separate process benchmark database is established as the process reference benchmark for subsequent batch production. New batch production can directly retrieve the benchmark archives of the corresponding materials and specifications to obtain complete process parameters without starting from scratch. Initial debugging; model iterative optimization, based on full qualified batch data from historical traceability archives, using the least squares fitting algorithm known in the field, to iteratively optimize the factor weights and parameter judgment thresholds of the inter-layer combined collaborative analysis model, while clearly stipulating that the threshold adjustment range does not exceed ±5% of the standard value to avoid changes to the core architecture of the model. The iteration cycle is set to optimize once every 50 batches of production to ensure continuous improvement in the model's control accuracy while maintaining its stability; full data backup, using a dual mode of local storage and cloud backup. Local storage uses industrial-grade hard drives for offline backup, while cloud backup uses a cloud database that conforms to industry standards. The backup cycle is synchronized with the production batches. After each batch of production is completed, a data backup is completed simultaneously to ensure that production data is not lost and that the entire production process is traceable and reproducible.

[0222] The data backup rules follow the common data security management standards in the polymer film processing industry, and adopt a dual mode of local offline backup and cloud encrypted backup. The local backup retention period is no less than 2 years, and the cloud backup retention period is no less than 5 years, which meets the regulatory traceability requirements of industries such as food, pharmaceuticals, and new energy.

[0223] The process baseline archives in this solution are categorized and stored using a commonly used industrial database management model, classified by material type, film specifications, and application scenario, including only stable production batches that have passed all criteria. Model iterative optimization employs a well-known least squares fitting algorithm, based on historical qualified batch data, adjusting only factor weights and parameter thresholds within a range not exceeding ±5% of the standard value, with an iteration cycle of once every 50 batches. Data backup utilizes a dual-mode approach: local offline and cloud-encrypted backup. The retention period complies with industry regulatory requirements, and those skilled in the art can directly complete the entire process data archiving and management operations based on the above rules.

[0224] Example 3: Compared with Example 2, this example also includes the following technical features:

[0225] The present invention also provides a multilayer co-extruded thermo-stretchable film interlayer bonding quality collaborative control system, wherein the system stores a computer program, and when the computer program is executed by a processor, it implements the control method described above.

[0226] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention. For those skilled in the art, any alternative improvements or transformations made to the implementation of the present invention fall within the protection scope of the present invention.

[0227] Any aspects of this invention not described in detail are well-known to those skilled in the art.

Claims

1. A method for synergistic control of interlayer bonding quality in multilayer co-extruded thermoscaling films, characterized in that, Includes the following steps: S1. Collect the basic physical property parameters of materials in each layer, construct an inter-layer collaborative analysis model, and establish a full-process process parameter dataset. S2. Based on the basic physical property parameters, pre-treat the raw materials of each layer, obtain the physical and chemical parameters, and enter them into the process parameter dataset; S3. Using pretreated materials, carry out the layered melt preparation process, collect melt rheological characteristic parameters, and dynamically monitor the melt interface bonding status. S4. Perform multi-layer composite molding on the obtained melt layers, collect molding process parameters and import them into the interlayer bonding collaborative analysis model simultaneously. S5. Perform a gradient preheating process on the basis of the composite molded preform, collect preheating temperature distribution data and update the process parameter dataset. S6. Perform a bidirectional step-by-step stretching process on the preheated blank film, dynamically monitor the interlayer deformation coordination state, and obtain deformation matching characteristic parameters; S7. Perform segmented heat setting process on the stretched preform, collect heat relaxation parameters and simultaneously import them into the interlayer bonding collaborative analysis model. S8. Conduct interlayer bonding state testing on the heat-set film, input the test data into the model for analysis, and adjust the process parameters of the above steps based on the model analysis results.

2. The method according to claim 1, characterized in that, When collecting the basic physical property parameters of each layer of material, in addition to the conventional melt index and density parameters, it is also necessary to simultaneously collect three types of physical property indicators: interlayer charge mobility, surface free energy dispersion component, and molten dielectric loss tangent. The conventional parameters and the above indicators are integrated into a multi-dimensional physical property feature matrix according to the layer sequence. The feature matrix is ​​normalized, and the processing rules are implemented in accordance with the plastic physical property testing specifications. The processed feature data is used as the initial input parameters of the interlayer combined collaborative analysis model. The model completes the layer sequence weight allocation based on the feature matrix, and the weight allocation results are simultaneously entered into the full process parameter dataset.

3. The method according to claim 2, characterized in that, The specific steps for preprocessing raw materials at each layer based on a multi-dimensional physical property matrix are as follows: The raw materials are subjected to low-temperature vacuum drying, and the drying temperature and vacuum gradient are set according to the free energy dispersion component of the material surface. The dried raw materials are screened using a grading and screening process to remove agglomerated particles and impurities that exceed the set particle size distribution range; The sieved raw materials are statically homogenized and mixed to eliminate localized component segregation. After pretreatment, the material's water activity gradient, component homogeneity, and surface polarity parameters are collected, and the obtained physicochemical parameters are entered into the process parameter dataset in stratified order.

4. The method according to claim 1, characterized in that, The steps of the layered melt preparation process are as follows: Based on the multi-dimensional physical property matrix, the plasticizing temperature gradient, shear rate distribution and holding time of each layer of melt are set; the raw material is subjected to layered plasticizing treatment, and the parameters of shear viscosity, dynamic modulus, wall slip rate and charge migration rate of each layer of melt are collected. A melt interface charge transfer factor was introduced to construct a melt rheological co-adaptation model and perform calculations. Adjust the melt preparation process parameters based on the model calculation results, and dynamically monitor the melt interface bonding status; The model calculation formula is: ; in, For melt rheology compatibility index; For the first Layer melt shear viscosity, unit: ; It is the charge transfer factor at the melt interface; For the first Melt charge mobility; For the first Melt wall slip rate; This is the viscosity-temperature sensitivity coefficient; For the first Layer and First Shear viscosity difference of layered melt; For the first The dielectric loss tangent of the melt layer; is the total number of material layers; exp is the natural exponential function; The calculation results and interface status data are uploaded synchronously to the process parameter dataset.

5. The method according to claim 1, characterized in that, The steps for implementing the multi-layer composite molding process are as follows: Arrange the melt delivery path according to the layer sequence and set the synchronous delivery rate of melt for each layer; After each layer of melt arrives at the composite fusion zone simultaneously, the melt fusion pressure and interface temperature are controlled to complete the continuous interface bonding of each layer of melt. Throughout the entire composite molding process, parameters such as interlayer contact pressure, extrusion flow rate, interface temperature, and dielectric property deviation are collected in real time. Based on the aforementioned molding parameters, an interlayer dielectric loss correlation factor is introduced to construct an interface combination stability judgment model and complete quantitative calculation. The composite molding process parameters are dynamically adjusted based on the model calculation results. The model calculation formula is as follows: ； in, For interface stability coefficient; For the first Dielectric constant of the layer material; For the first Dielectric constant of the layer material; This is the dielectric mismatch weighting factor, set with reference to the specifications for multilayer functional thin films; For the first The dielectric loss tangent of the melt layer; Interlayer contact pressure; This refers to the melt composite flow rate; This is a correction factor for interface fit.

6. The method according to claim 1, characterized in that, The steps for performing the gradient preheating process are as follows: The composite-molded preform is smoothly fed into the segmented preheating area, and the initial preheating temperature is set. After the preform enters the first temperature zone, the preheating temperature is gradually increased along the preform forming direction to the temperature sub-zone, and real-time temperature distribution data of each temperature zone is collected simultaneously. Throughout the preheating process, the crystal transformation rate, thermal diffusivity, and deformation gradient parameters of the billet film are continuously monitored. Based on the aforementioned preheating parameters, a thermal diffusion anisotropy factor is introduced to construct an interlayer thermal deformation collaborative model and complete quantitative calculations. The preheating parameters for each temperature zone are dynamically adjusted based on the model calculation results. The model calculation formula is as follows: ； This represents the thermal deformation coordination deviation value. For the first Anisotropy factor of thermal diffusion in the temperature range; For the first Coefficient of thermal expansion of the preform in the temperature range; The coefficient of thermal expansion is the overall average coefficient of thermal expansion of the preform. For the first Thermal diffusivity of the preform in the temperature range; For the first Temperature zone setting temperature; For the first Axial length of the temperature zone; Temperature zone weighting factor; This refers to the number of preheating zones; The data is updated to the process parameter dataset in real time.

7. The method according to claim 1, characterized in that, The steps of the bidirectional step-by-step stretching process are as follows: The preheated blank film is stretched longitudinally segment by segment, and the gradient stretching rate is set in stages along the flow direction of the blank film. After longitudinal stretching is completed, the preform is smoothly fed into the transverse stretching unit, and the differentiated stretching ratio is matched in different regions along the width direction of the preform to complete the transverse gradient stretching. Throughout the entire biaxial tensile process, the interlayer deformation matching degree, interface slip, residual stress distribution, and interface wetting angle parameters are dynamically monitored. An interface wetting hysteresis factor was introduced to correct the interlayer deformation synergy judgment criteria and complete the monitoring data calibration. The calibrated deformation characteristic parameters are transmitted to the interlayer bonding collaborative analysis model, and the core parameters of stretching rate, stretching ratio and stretching time are recorded simultaneously.

8. The method according to claim 7, characterized in that, The preform after the bidirectional step-by-step stretching process is subjected to a segmented heat setting process, the steps of which are as follows: Divide the temperature zone into multiple shaping zones and set gradient cooling curves; The stretched preform is sequentially fed into each shaping temperature zone to complete the entire process of high-temperature shaping, medium-temperature heat preservation, gradient cooling and low-temperature stabilization. Throughout the heat setting process, parameters such as thermal relaxation rate, crystal phase transformation degree, interfacial bonding energy, and internal stress amplitude were continuously collected at each temperature zone. Based on the aforementioned collected modeling parameters, an internal stress-thermal relaxation coupling factor is introduced to construct an interface energy stability model and complete quantitative calculations. The process parameters of the shaping temperature zone are dynamically adjusted based on the model output results; The model calculation formula is: ； in, This represents the energy stability value at the interlayer interface. For the first Specific heat capacity of the preform in the temperature zone; For the first Temperature drop range; This is a fixed internal stress-thermal relaxation coupling factor; For the first Temperature zone insulation duration; This is the internal stress attenuation coefficient; This is the phase transformation correction factor; This refers to the number of temperature zones for the model.

9. A multilayer co-extruded thermo-shrunk film interlayer bonding quality collaborative control system, characterized in that, The system stores a computer program, which, when executed by a processor, implements the control method as described in any one of claims 1-8.

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