High-temperature co-extrusion material interface detection method, device and equipment and storage medium

Abstract

The invention provides a high-temperature co-extrusion material interface detection method and a related device. The method comprises the steps that technological parameters of multiple layers of melts are set respectively, the multiple layers of melts form an incremental viscosity gradient at the die head converging position in the layer thickness direction, and the technological parameters at least comprise a temperature parameter or a back pressure parameter; periodic mechanical shear excitation is applied to an interface between the adjacent melts, and a dynamic response signal corresponding to the excitation is synchronously collected; analyzing the dynamic response signal to obtain a viscoelastic parameter representing the interfacial viscosity or the elastic modulus; and comparing the viscoelastic parameter with a preset threshold value, and outputting a judgment signal for representing the viscoelastic state of the interface. According to the invention, the problem of lack of real-time monitoring of the interface transition zone in the prior art is solved, and the quality stability of the multilayer high-temperature polymer material product is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of detection of high-temperature polymer material extrusion process, and in particular to a high-temperature co-extrusion material interface detection method, device, equipment and storage medium. BACKGROUND

[0002] High-temperature polymer material extrusion forming is a polymer processing technology, mainly used for preparing high-temperature engineering plastics (such as polyether ether ketone (PEEK), polyether ketone ketone ketone (PEKK), polyimide (PI), etc.) into pipes, plates, films or special-shaped parts. With the continuous improvement of application requirements, a single material is often difficult to meet the complex functional requirements. Multi-layer co-extrusion technology emerges as the times require, which can combine multiple materials with different functional characteristics into a product with a multi-layer structure in one forming process.

[0003] In the multi-layer co-extrusion process, there are differences in viscosity, thermal expansion coefficient and thermal conductivity between different material layers. These differences lead to the formation of a performance gradient transition zone in the interface area. The molecular chain entanglement density and crystalline structure of this transition zone are significantly different from those of the two side matrix materials, and it is easy to become a stress concentration area during product use, leading to interlayer separation, crack propagation and other failure phenomena. The current technology lacks real-time monitoring of the microstate of the transition zone, making it difficult to discover and prevent interface performance abnormalities in a timely manner, affecting the quality stability and use reliability of multi-layer products. SUMMARY

[0004] The main purpose of the present application is to solve the technical problem that the existing multi-layer high-temperature polymer material extrusion forming technology lacks real-time monitoring of the microstate of the interface transition zone and is difficult to discover and prevent interface performance abnormalities in a timely manner.

[0005] To achieve the above-mentioned purpose, the present application provides a high-temperature co-extrusion material interface detection method, comprising: By setting the process parameters of the multi-layer melt respectively, an increasing viscosity gradient is formed along the layer thickness direction at the converging position of the die, and the process parameters at least include temperature parameters or back pressure parameters; A periodic mechanical shear excitation is applied to the interface between adjacent melts, and a dynamic response signal corresponding to the excitation is synchronously collected; The dynamic response signal is analyzed to obtain a viscoelastic parameter representing the interface viscosity or elastic modulus; The viscoelastic parameter is compared with a preset threshold value, and a judgment signal representing the viscoelastic state of the interface is output.

[0006] To achieve the above-mentioned purpose, the present application also provides a high-temperature co-extrusion material interface detection device, comprising: a process parameter control module, configured to set process parameters of the multilayer melt respectively, so that the multilayer melt forms an increasing viscosity gradient along the layer thickness direction at the die merging position, wherein the process parameters at least include temperature parameters or back pressure parameters; an excitation signal generation module, configured to apply a periodic mechanical shear excitation to the interface between the adjacent melts, and synchronously collect a dynamic response signal corresponding to the excitation; a signal analysis processing module, configured to analyze the dynamic response signal, and obtain a viscoelastic parameter representing the viscosity or elastic modulus of the interface; a state determination output module, configured to compare the viscoelastic parameter with a preset threshold, and output a determination signal representing the viscoelastic state of the interface.

[0007] To achieve the above object, the embodiment of the present application further provides a high-temperature co-extrusion material interface detection device, comprising a memory and at least one processor, the memory stores instructions, and the memory and the at least one processor are interconnected through a circuit; the at least one processor calls the instructions in the memory, so that the high-temperature co-extrusion material interface detection device executes the steps of the high-temperature co-extrusion material interface detection method.

[0008] To achieve the above object, the embodiment of the present application further provides a computer readable storage medium, which stores instructions, and when the instructions are run on a computer, the computer executes the steps of the high-temperature co-extrusion material interface detection method.

[0009] The technical scheme provided by the embodiment of the present application can establish an increasing viscosity gradient along the layer thickness direction at the die merging position by setting the temperature parameters and back pressure parameters of the melts of each layer respectively in the process of extruding and forming the multilayer high-temperature polymer material. The key of this gradient design is that the outer layer material maintains a relatively low temperature to maintain appropriate fluidity, while the inner layer material adopts a higher temperature to ensure sufficient melting, and the parameters of the middle layer material are between the two. When the melts with different viscosities converge in the die, a transition region with a thickness of only a few microns is naturally formed between the adjacent material layers, the viscosity value of the region is between the two base materials, and the molecular chain entanglement density and crystalline structure both show gradient change characteristics. When periodic mechanical shear excitation is applied to these interface regions, the transition region is most sensitive to external excitation because its viscosity is much lower than that of the base melt on both sides, and deformation and flow are preferentially generated, thereby forming a dynamic signal with interface characteristics in the complex system response.

[0010] By means of special analysis and processing of the collected dynamic response signals, characteristic parameters directly reflecting the changes of the interfacial viscosity and elastic modulus can be extracted from the signals. The physical meaning of these parameters lies in quantitatively describing the microstate of the interfacial transition region: when the molecular chain entanglement density of the interfacial region decreases, the corresponding viscosity parameter will decrease; when the elastic energy storage capacity of the interface changes, the elastic modulus parameter will fluctuate accordingly. By comparing the extracted viscoelastic parameters with the preset safety threshold, it can be judged in real time whether the interface state deviates from the normal range. Once an abnormal signal is detected, the system immediately outputs the corresponding judgment signal, providing timely and accurate state information for subsequent process intervention. The core advantage of this detection method is that it can capture the subtle changes in the interfacial transition region at the molecular scale, and these changes are the root cause of the failure phenomena such as interlayer separation and crack propagation in the subsequent use process, thereby realizing the technical leap from macroscopic appearance inspection to microscopic state monitoring. BRIEF DESCRIPTION OF DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only show some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from the structures shown in these drawings without creative labor.

[0012] Figure 1 An embodiment schematic diagram of the interfacial detection method for the high-temperature co-extrusion material in the embodiment of the present application; Figure 2 An embodiment schematic diagram of the interfacial detection device for the high-temperature co-extrusion material in the embodiment of the present application; Figure 3 An embodiment schematic diagram of the interfacial detection equipment for the high-temperature co-extrusion material in the embodiment of the present application.

[0013] The implementation of the object of the present application, functional features and advantages will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0014] It should be understood that the specific embodiments described herein are merely intended to explain the present application and not to limit the present application.

[0015] In order to better understand the above technical solutions, the exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0016] It is noted that in the claims the reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude other parts not listed in the claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The application can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claim enlisting a number of means, several of these means can be embodied by one and the same item of hardware. The use of the terms "first", "second", and "third", etc. does not limit the order in the use, but they are used to distinguish these claims from each other. If the specification states a combination of features or elements, the combination can be applied to provide any number of systems or devices that are not particular limited to the different embodiments described in the specification.

[0017] High temperature polymer multi-layer co-extrusion technology plays a key role in high-end application fields such as aerospace, electronics and electrical appliances, and automotive industry. Typical products include multi-functional composite pipe for air inlet of aircraft engine, multi-layer heat dissipation plate for electronic equipment, and lightweight structural parts for automobile, etc. These products usually adopt a three-layer or multi-layer structure design. The outer layer material bears the function of flame retardation and protection, the middle layer material provides structural load bearing capacity, and the inner layer material realizes electric shielding or other special functions. In the high temperature extrusion environment of about 380℃, the melts of different functional materials converge in the die to form a layered composite structure. The interface bonding quality between the layers directly determines the overall performance and service life of the final product.

[0018] However, due to the significant differences in viscosity, thermal expansion coefficient and thermal conductivity characteristics of the materials in each layer, a performance transition zone will be formed in the interface area. The molecular chain entanglement density and microstructure of the transition zone are significantly different from those of the base materials on both sides, and it is easy to become a stress concentration area. In the actual service process, under the action of temperature cycle, mechanical vibration and other loads, these weak interfaces often become the starting point of crack initiation and propagation, leading to serious consequences such as interlayer separation, air tightness failure or interruption of the conductive network. The traditional quality control method mainly relies on appearance inspection and sampling test after molding, which cannot grasp the microstate changes of the interface in real time during the production process. When problems are found, it is often too late. In order to fundamentally solve this problem, an embodiment of the present application provides a high temperature co-extrusion material interface detection method, which can timely find interface abnormalities so as to take corresponding measures and ensure that the multi-layer product has stable and reliable interface bonding performance.

[0019] Figure 1 A flow chart of the high temperature co-extrusion material interface detection method provided by an embodiment of the present application. In this embodiment, the method comprises the following steps: S10, by setting the process parameters of the multi-layer melt respectively, an increasing viscosity gradient is formed in the layer thickness direction of the multi-layer melt at the die convergence position, and the process parameters at least include temperature parameters or back pressure parameters; The following will be specifically described for the steps involved in the above embodiments: Specifically, the viscosity differentiation control of each layer material at the confluence position of the die is realized by setting the temperature parameters and back pressure parameters of the multi-layer melt respectively. The multi-layer melt refers to two or more layers of melt of different functional materials, which can be a double-layer structure, a three-layer structure or more layers in specific implementation. Taking a three-layer structure as an example, the viscosity-temperature correlation parameters of each layer melt are calculated according to the thermal conductivity of the flame-retardant filler of the outer layer melt, the molecular chain entanglement density of the middle layer melt and the percolation threshold of the conductive network of the inner layer melt. The viscosity-temperature correlation parameter is a dimensionless parameter describing the sensitivity of the viscosity of the melt to temperature, which is obtained by fitting the viscosity test data of each layer melt at different temperatures into the Arrhenius equation η = A·exp(B / T), where η represents the dynamic viscosity of the melt (unit: Pa·s), A is a pre-exponential factor related to the molecular structure of the material, B is an activation energy parameter (unit: K) reflecting the energy barrier of molecular flow, and T is the absolute temperature of the melt (unit: K). The B value obtained by fitting is used as the correlation parameter. The correlation parameter of the outer layer PI melt containing high thermal conductivity flame-retardant filler is usually higher than that of pure resin, indicating that the viscosity fluctuation is more severe when the temperature changes. Based on the calculated correlation parameters, the temperature of each layer melt is set to increase layer by layer, and the temperature of the outer layer is relatively low to maintain appropriate fluidity, and the temperature of the inner layer is the highest to ensure that the conductive network is fully dispersed to form a dynamic temperature distribution data. The back pressure parameters are coupled and matched by adjusting the screw back pressure valve and the metering section pressure control system. When the viscosity of a certain layer decreases due to temperature rise, the back pressure of the layer is increased to maintain the flow balance. This layered parameter setting method can generate a stable viscosity gradient at the confluence position of the die, so that the outer layer material maintains a relatively high viscosity, the inner layer material presents a lower viscosity, and an increasing viscosity distribution is formed between the layers, providing the necessary physical conditions for the formation of the interface quasi-liquid transition layer.

[0020] S20, applying a periodic mechanical shear excitation to the interface between adjacent melts, and synchronously collecting dynamic response signals corresponding to the excitation; In an embodiment of the present application, step S20 can be completed by steps S21-S23: S21, calculating the interface resonance frequency window according to the interface characteristics between adjacent melts, and determining the start frequency, cutoff frequency and scan rate of linear sweep according to the resonance frequency window to obtain sweep parameter configuration; S22, applying a periodic shear excitation with increasing frequency to the multi-layer melt according to the sweep parameter configuration, so that each adjacent interface produces a differentiated frequency response, and the excitation-response time series data at each frequency point is synchronously collected to obtain frequency-division response data; S23, performing harmonic decomposition processing on the frequency-division band response data to extract a fundamental frequency response component, a second harmonic component and a high-order harmonic component reflecting the interfacial viscoelastic characteristics, and obtaining an interfacial characteristic response spectrum according to the amplitude ratio and phase relationship of each harmonic component, the interfacial characteristic response spectrum being used for subsequent signal analysis processing.

[0021] The following will be specifically described for the steps involved in the above embodiments: The interfacial property refers to the physical properties of the contact region between adjacent melts, including parameters such as interfacial thickness, viscosity difference and elastic modulus difference. The interfacial resonance frequency window refers to the frequency band in which the response amplitude of the interface is significantly amplified in a certain frequency range. The storage modulus and loss modulus of each layer of material are determined by a dynamic mechanical analyzer, and the characteristic relaxation frequency of the material is identified. For a multi-layer melt structure, each adjacent interface has different resonance characteristics. For example, in a double-layer structure, there is only one interfacial resonance frequency, while in a three-layer structure, there are two different interfacial resonance frequencies. According to the resonance characteristics of each interface, the linear sweep parameters are determined: the starting frequency is set to the lowest value of all the interfacial resonance frequencies, the cutoff frequency is set to the highest value, and the sweep rate is determined to be 5-10 Hz per second according to the frequency resolution requirement. The sweep parameter configuration includes three numerical values of starting frequency, cutoff frequency and sweep rate, forming a complete excitation parameter setting scheme. This frequency range design based on the intrinsic characteristics of the material can ensure that the excitation signal covers the sensitive response interval of all interfaces, avoiding the omission of key frequency bands and resulting in poor detection effect.

[0022] A periodic shear excitation of increasing frequency is applied to the multi-layer melt by a screw back pressure servo control system. The specific implementation is to superimpose a sinusoidal pressure modulation signal on the screw back pressure control valve, and the frequency of the modulation signal is linearly increased from the starting frequency to the cutoff frequency according to the sweep parameter configuration, and the amplitude is controlled within ±2% of the average back pressure. The periodic shear excitation is transmitted to the melt inside through the periodic change of back pressure, generating alternating shear stress at each adjacent interface. The differential frequency response refers to the phenomenon that different interfaces produce different response characteristics due to the difference in material characteristics under the same excitation. A high-temperature pressure sensor array is installed in the die to detect the pressure fluctuations of each interface. The number of sensors is determined according to the number of melt layers, one sensor is installed for a double-layer structure, and two sensors are installed for a three-layer structure. The excitation-response time series data refers to the complete data sequence of the excitation signal and the interface response signal recorded synchronously at each excitation frequency point. The acquisition frequency is set to more than 10 times the excitation frequency, and the excitation time at each frequency point is 5 cycles. The frequency-division band response data is divided into several segments according to a frequency interval of 0.5 Hz, each segment containing the complete response data of the frequency point. This excitation method based on pressure modulation can effectively stimulate the dynamic response characteristics of the interface while maintaining normal extrusion process.

[0023] The frequency band response data is processed by a fast Fourier transform algorithm for harmonic decomposition, converting the time domain response signal into a frequency domain spectral line distribution. The fundamental frequency response component corresponds to the spectral line amplitude at the excitation frequency, directly reflecting the linear response strength of the interface to the excitation. The second harmonic component is located at the spectral line at twice the excitation frequency, and when the interface has a nonlinear response, this component will be significantly enhanced. The high-order harmonic component includes the third, fourth and higher order harmonics, reflecting the complex nonlinear characteristics of the interface. The amplitude ratio is calculated by dividing the amplitude of each harmonic by the amplitude of the fundamental frequency, and the phase relationship is obtained by calculating the difference between the phase of each harmonic and the phase of the fundamental frequency. The interface characteristic response spectrum is a two-dimensional graph with frequency as the horizontal axis and response amplitude as the vertical axis, clearly showing the response strength distribution and harmonic characteristics of each frequency point, containing complete information of the fundamental frequency and each harmonic. This signal processing method based on harmonic analysis can accurately extract the characteristic information related to the viscoelastic properties of the interface from the complex response signal, providing accurate data basis for subsequent interface state analysis.

[0024] S30, analyzing the dynamic response signal to obtain a viscoelastic parameter representing the viscosity or elastic modulus of the interface; In an embodiment of the present application, step S30 can be completed by steps S31-S34: S31, time-frequency domain registration of the dynamic response signal and the preset baseline data, and point-by-point difference operation on the registered signal to obtain a difference signal; S32, Hilbert transform processing of the difference signal to extract the instantaneous amplitude and instantaneous phase of the difference signal, and constructing a time domain difference envelope according to the instantaneous amplitude; S33, determining the energy storage-energy dissipation frequency demarcation point of the corresponding interface according to the material properties of each layer of melt, and dividing the difference envelope in the frequency domain according to the energy storage-energy dissipation frequency demarcation point to obtain energy storage harmonic region data and energy dissipation harmonic region data; S34, calculating the time domain envelope slope of the energy storage harmonic region data, calculating the phase rotation rate of the energy dissipation harmonic region data according to the time variation of the instantaneous phase, and constructing a viscoelastic parameter representing the interface state according to the envelope slope and the phase rotation rate.

[0025] The following describes the steps involved in the above embodiment: The processing of the dynamic response signal and the preset baseline data adopts a time-frequency domain registration technology to ensure the accurate correspondence of the data. The time-frequency domain registration refers to the process of accurately aligning two signals on the time axis and the frequency axis, eliminating the influence of time delay and frequency offset. The preset baseline data refers to the reference signal data collected in advance during the dynamic establishment of the system. In the specific implementation process, the time delay between the dynamic response signal and the preset baseline data is calculated through a cross-correlation algorithm, and then the response signal is compensated by time translation. The frequency domain registration adjusts the frequency reference of the response signal by comparing the spectral characteristics of the two signals. After the registration is completed, the registered signals are subjected to point-by-point difference operation, that is, the numerical value of the response signal at each time point is subtracted from the numerical value of the baseline data at the corresponding time point. For example, when the amplitude of the response signal at a certain time is 1.2V and the corresponding preset baseline data is 1.0V, the difference result is 0.2V. The difference signal reflects the change amount of the interface state relative to the reference state, effectively eliminates the influence of the inherent noise of the system and environmental interference, extracts the weak interface state change signal from the complex background signal, and significantly improves the signal-to-noise ratio and detection accuracy of the signal.

[0026] The difference signal is processed by Hilbert transform to extract instantaneous characteristic parameters. Hilbert transform is a mathematical transformation method that can convert real number signals into complex number signals, thereby extracting the instantaneous amplitude and instantaneous phase information of the signal. The instantaneous amplitude represents the envelope size of the signal at each time, reflecting the time variation of the signal strength. The instantaneous phase represents the phase angle of the signal at each time, reflecting the phase variation law of the signal. Hilbert transform is realized in a digital signal processor through an algorithm, and the calculation process includes steps such as Fourier transform, phase adjustment and inverse Fourier transform of the original signal. According to the extracted instantaneous amplitude data, a time domain difference envelope is constructed, which is a curve of the instantaneous amplitude changing with time, directly showing the intensity variation trend of the difference signal. For example, when the interface transition layer thickness fluctuates, the corresponding difference envelope will fluctuate, and the fluctuation amplitude reflects the severity of the thickness change. The time domain difference envelope can extract the instantaneous characteristics directly related to the physical state of the interface from the complex difference signal, avoiding the limitations of traditional amplitude detection methods that cannot capture transient changes.

[0027] The energy storage-energy dissipation frequency demarcation point refers to a critical frequency point at which the material changes from mainly exhibiting energy storage characteristics to mainly exhibiting energy dissipation characteristics, and the frequency point is closely related to the molecular motion characteristics of the material. The energy storage modulus and the loss modulus of each layer of material are determined by a dynamic thermal mechanical analyzer, and the frequency point at which the energy storage modulus is equal to the loss modulus is the energy storage-energy dissipation frequency demarcation point. For example, the demarcation point frequency of a polyimide material is 15 Hz, and the demarcation point frequency of a polyether ketone ketone material is 8 Hz. According to the determined frequency demarcation point, the time domain difference envelope is divided in the frequency domain, and the part below the demarcation point frequency is classified as energy storage harmonic region data, and the part above the demarcation point frequency is classified as energy dissipation harmonic region data. The energy storage harmonic region data reflects the elastic energy storage characteristics of the interface, and the energy dissipation harmonic region data reflects the viscous energy dissipation characteristics of the interface. This frequency domain division method based on the intrinsic characteristics of the material can accurately identify the response mechanism of the interface at different frequencies.

[0028] The energy storage harmonic region data and the energy dissipation harmonic region data are respectively subjected to different parameter calculations to extract the viscoelastic characteristic indexes of the interface. The time domain envelope slope is calculated for the energy storage harmonic region data, and the slope reflects the rate of change of the energy storage characteristics with time, and the slope value of the fitting straight line is obtained by linear fitting of the envelope curve. A positive envelope slope indicates an increase in energy storage capacity, corresponding to an increase in interface stiffness, and a negative envelope slope indicates a decrease in energy storage capacity, corresponding to an interface softening. The phase rotation rate is calculated for the energy dissipation harmonic region data, and the parameter reflects the speed of change of the phase with time, and is calculated by time differentiation of the instantaneous phase data. The size of the phase rotation rate reflects the activity degree of the energy dissipation process of the interface, and the larger the value, the more intense the molecular motion, and the more unstable the interface. The viscoelastic parameters are constructed by the combination of the envelope slope and the phase rotation rate, and comprehensively characterize the changes in the energy storage and energy dissipation characteristics of the interface. This frequency domain parameter extraction method can simultaneously capture the changes in the elastic and viscous characteristics of the interface, realize comprehensive quantitative analysis of the complex viscoelastic behavior of the interface, and provide a reliable data basis for accurate evaluation of the interface state.

[0029] In an embodiment of the present application, the preset baseline data is obtained by the following method: Before the establishment of the steady state of the multi-layer melt, the screw and the traction device are synchronously locked at a low frequency, and the torque-displacement signal and the tension-displacement signal are continuously collected in time sequence within the locking window, and the instantaneous viscosity fluctuation of each adjacent interface is recorded to obtain a multi-dimensional baseline signal group; The multi-dimensional baseline signal group is subjected to frequency domain decomposition and amplitude normalization processing to extract baseline characteristic data representing system inertia parameters, material batch parameters and interface coupling parameters; The baseline characteristic data is weighted and synthesized as a zero point reference for difference calculation to obtain the preset baseline data.

[0030] The steps involved in the above embodiments are described in detail as follows: Data acquisition before the establishment of the multi-layer melt steady state ensures the capture of complete characteristic information of the dynamic establishment process of the system. Before the establishment of the steady state, it refers to the transition stage from the beginning of the convergence to the complete stability of the flow state of the multi-layer melt, at which time the dynamic characteristics of the system are the most abundant. Low-frequency synchronous locking is to set the screw rotation speed and the traction device speed to a fixed value and keep them running synchronously, eliminating the random vibration interference of the mechanical system, and the locking frequency is controlled within the range of 5-15 Hz to avoid the influence of high-frequency mechanical vibration on signal acquisition. The locking window refers to the time period of the equipment in the synchronous locking state, which is set to 30-60 seconds to ensure the sufficiency of data acquisition. The torque-displacement signal is obtained through the torque sensor installed at the driving end of the screw, reflecting the resistance change in the screw pushing process. The tension-displacement signal is obtained synchronously through the tension sensor and displacement sensor on the traction device, reflecting the stress state of the profile in the traction process. The instantaneous viscosity fluctuation refers to the real-time change value of the viscosity at the interface with time, which is obtained by calculating the pressure drop data measured by the high-temperature pressure sensor and the flow data measured by the volumetric flowmeter according to the pipeline flow theory. The multi-dimensional baseline signal group refers to the comprehensive data set containing mechanical signals, interface state signals and process parameter signals, which is synchronously acquired according to the preset time interval, and the acquisition frequency is set to 100 Hz to ensure the integrity of the signal. This multi-dimensional signal acquisition method during the dynamic establishment of the system can fully capture the running characteristics of the system in the non-steady state, providing complete system characteristic information for subsequent differential analysis.

[0031] The multi-dimensional baseline signal group is processed by fast Fourier transform algorithm for frequency domain decomposition, which converts time domain signal into frequency spectrum distribution in frequency domain, and identifies the signal components in different frequency bands. Amplitude normalization processing is to unify the amplitudes of signals from different sources to the same numerical range, eliminating the influence of magnitude difference on subsequent analysis, which is realized by dividing the amplitude of each signal by its maximum value, and the amplitude range after processing is 0-1. System inertia parameters are parameters representing the inherent dynamic characteristics of the mechanical system, mainly reflecting the mass, stiffness and damping characteristics of the equipment, which are obtained by analyzing the frequency response characteristics of the torque signal. Material batch parameters reflect the differences in rheological properties, thermal stability, etc. of different batches of raw materials, which are obtained by analyzing the statistical characteristics of the tension signal. The interface coupling parameter represents the strength and coupling degree of the interaction between adjacent interfaces, which is obtained by analyzing the correlation of the instantaneous viscosity fluctuation data of each interface. When the viscosity fluctuation of one interface causes synchronous fluctuation of another interface, the correlation coefficient is high, indicating that the interface coupling strength is large. The baseline characteristic data contains the values and corresponding frequency distribution information of the above three types of parameters, forming a complete description of the system characteristics. This classification extraction method can orderly decompose complex multi-dimensional signals according to physical meaning, providing classified and clear characteristic parameters for subsequent data synthesis.

[0032] The baseline characteristic data is weighted and synthesized according to the importance of different parameter types. The weight coefficients are determined according to the influence degree of various parameters on the interface detection accuracy. The weight of the system inertia parameter is set to 0.3, the weight of the material batch parameter is set to 0.4, and the weight of the interface coupling parameter is set to 0.3. The weighted synthesis is realized by multiplying each type of parameter by the corresponding weight coefficient and then summing, for example, when the system inertia parameter is 10, the material batch parameter is 15, and the interface coupling parameter is 12, the weighted synthesis result is 10*0.3+15*0.4+12*0.3=12.6. The zero reference refers to the reference value used as the benchmark in subsequent difference calculation. All dynamic signal changes are compared and analyzed based on this benchmark. The preset baseline data includes the comprehensive value after weighted synthesis and the corresponding time sequence information, which serves as the standard reference benchmark for the entire detection system. This weight weighted synthesis method can reasonably allocate the influence weight according to the importance of different parameters, form comprehensive benchmark data, ensure that the subsequent difference analysis has a stable and reliable reference standard, and at the same time avoid the deviation influence of single parameter abnormality on the overall benchmark.

[0033] S40, compare the viscoelastic parameters with a preset threshold value, and output a judgment signal for representing the viscoelastic state of the interface.

[0034] In an embodiment of the present application, the multilayer melt includes an outer layer melt, a middle layer melt, and an inner layer melt; and step S40 can be completed by steps S41-S43: S41, respectively obtain the viscoelastic parameters of the outer-middle interface and the middle-inner interface; S42, calculate the difference between the two interface viscoelastic parameters, and construct an interface coupling factor according to the difference; S43, compare the interface coupling factor with a preset synergistic state threshold value, and output a judgment signal reflecting the synergistic state of the multi-interface.

[0035] The following specifically describes the steps involved in the above embodiment: The characteristic values of each interface are obtained by calculating the viscoelastic parameters of two adjacent interfaces in the three-layer structure. The viscoelastic parameters of the outer-middle interface are obtained by analyzing the envelope slope and phase rotation rate of the interface region between the outer polyimide melt and the middle polyether ketone ketone melt, and the viscoelastic parameters of the middle-inner interface are obtained by analyzing the corresponding parameters of the interface region between the middle polyether ketone ketone melt and the inner conductive polyether ether ketone melt. In the specific implementation process, the data processing system extracts the corresponding values of each interface from the storage harmonic region data and the energy consumption harmonic region data obtained in the foregoing steps, for example, the envelope slope of the outer-middle interface is 0.15, the phase rotation rate is 2.3 rad / s, the envelope slope of the middle-inner interface is 0.12, and the phase rotation rate is 1.8 rad / s. The viscoelastic parameters of each interface are composed of the corresponding envelope slope and phase rotation rate, forming the characteristic parameter pair of the interface. This interface parameter acquisition method can independently evaluate the viscoelastic properties of each interface, avoid the detection accuracy decline caused by the mutual interference of multi-interface signals, and ensure the accurate identification of the state of each interface.

[0036] The difference calculation of the interface viscoelastic parameters is realized by numerical subtraction operation, and the envelope slope difference and the phase rotation rate difference are calculated respectively. The envelope slope difference is equal to the envelope slope of the outer-middle interface minus the envelope slope of the middle-inner interface, and the phase rotation rate difference is equal to the phase rotation rate of the outer-middle interface minus the phase rotation rate of the middle-inner interface. Taking the above example values as an example, the envelope slope difference is 0.15-0.12=0.03, and the phase rotation rate difference is 2.3-1.8=0.5 rad / s. The interface coupling factor is a comprehensive parameter reflecting the interaction strength of two interfaces, which is calculated by weighted combination of the envelope slope difference and the phase rotation rate difference. The weighting coefficients are determined according to the influence of each parameter on the interface coupling degree, the weight of the envelope slope difference is 0.6, the weight of the phase rotation rate difference is 0.4, and the interface coupling factor=0.03×0.6+0.5×0.4=0.218. The value of the interface coupling factor directly reflects the degree of coordinated change of the two interfaces, the larger the value, the stronger the mutual influence between the interfaces, the better the coordination, and the smaller the value, the stronger the independence of the interfaces. This coupling factor construction method based on difference analysis can quantitatively characterize the coordination characteristics of the multi-interface system, and provide reliable numerical basis for interface coordination control.

[0037] The cooperative state threshold is a critical value for judging whether the interface cooperation degree is normal, which is determined according to the interface bonding strength requirement of the multilayer material in aerospace application. The threshold setting is based on statistical analysis of a large amount of experimental data. When the interface coupling factor is greater than 0.25, the interface cooperative state is good, when the interface coupling factor is less than 0.15, the interface cooperative state is poor, and when the interface coupling factor is between 0.15 and 0.25, the interface cooperative state is critical. The comparison process is realized by a numerical comparator, which compares the calculated interface coupling factor with the preset cooperative state threshold. The determination signal outputs different state identifiers according to the comparison result. When the interface coupling factor is greater than 0.25, the “good cooperation” signal is output, when the interface coupling factor is less than 0.15, the “abnormal cooperation” signal is output, and when the interface coupling factor is between 0.15 and 0.25, the “critical cooperation” signal is output. The determination signal reflecting the multi-interface cooperative state provides a decision basis for subsequent process adjustment or quality control. The operator or automatic control system takes corresponding measures according to the determination signal. This state determination method based on threshold comparison can realize the automatic identification and classification of the multi-interface cooperation degree, avoid the uncertainty of subjective judgment, and ensure the objectivity and accuracy of the interface state evaluation.

[0038] In an embodiment of the present application, the detection method is repeatedly executed, further comprising: Collecting viscoelastic parameters at multiple time points in the repeated detection process, and calculating the change trend of the viscoelastic parameters with time; According to the change trend of the viscoelastic parameters, extrapolation prediction is carried out to predict the numerical change of the interface viscoelastic parameters in the future time period; When the prediction result exceeds the safety range, an early warning signal is output.

[0039] The following specifically describes the steps involved in the above embodiment: The repeated detection process refers to the process of repeatedly performing the interface state detection program at a certain time interval in the continuous extrusion process. In specific implementation, during the continuous extrusion of the same batch of materials, the detection system repeatedly performs the complete process of excitation application, signal acquisition and parameter analysis according to the preset time interval, and the time interval is set to 5-10 seconds to ensure capturing the real-time dynamic changes of the interface state. The viscoelasticity parameters at multiple time points are automatically recorded and stored on the continuous production line by the data acquisition system, and the envelope slope and phase rotation rate values obtained by each detection are saved in the database in chronological order. For example, at 5 detection times of the continuous extrusion process, the envelope slopes corresponding to time points t1, t2, t3, t4, t5 are 0.15, 0.17, 0.19, 0.21, and 0.23, respectively. The change trend is calculated by linear regression analysis, taking time as the independent variable and viscoelasticity parameters as the dependent variable, and the slope of the regression straight line is calculated as the change trend value. Taking the above envelope slope data as an example, the change trend is increased by 0.02 each time by least squares fitting. This trend analysis method based on time series data in continuous process can identify the real-time development direction of the interface state in the production process, and distinguish between stable state, deteriorating state and improving state, providing a reliable data basis for prediction analysis.

[0040] The extrapolation prediction extends the identified change trend to the future time period by mathematical extrapolation algorithm. In the specific implementation process, the prediction algorithm selects the appropriate extrapolation method according to the numerical characteristics of the change trend: when the absolute value of the change trend is less than 0.01, constant value prediction is used; when the change trend is positive and greater than 0.01, linear growth prediction is used; when the change trend is negative and the absolute value is greater than 0.01, linear decay prediction is used. The future time period is set to 15-30 seconds, which can cover the response delay of process parameter adjustment. For example, when the change trend of the envelope slope is increased by 0.02 each time, and the current value is 0.23, the predicted value after 3 detections is 0.23+3x0.02=0.29. The predicted change of the interface viscoelasticity parameter in the future time period provides forward-looking information for process adjustment decision-making in continuous production process, so that the operator can take preventive measures before the interface abnormality occurs. This prediction method based on trend extrapolation can change passive response to active prevention, significantly improving the timeliness and effectiveness of interface quality control in continuous extrusion process.

[0041] The safety range is a pre-set interface viscoelasticity parameter normal operation interval, which is determined according to the interface bonding strength requirement and the material failure threshold of aerospace application. The upper limit and the lower limit of the safety range are obtained by statistical analysis of a large number of experimental data, for example, the safety range of the envelope slope is 0.10-0.30, and the safety range of the phase rotation rate is 1.0-3.0 rad / s. The comparison of the prediction result with the safety range is realized by a numerical comparator, and the early warning condition is triggered when the prediction value exceeds the upper limit or the lower limit of the safety range. The early warning signal contains the abnormal type identification and the emergency level, and when the prediction value slightly exceeds the safety range, a "mild early warning" signal is output, and when the prediction value significantly exceeds the safety range, a "serious early warning" signal is output. The early warning signal is output to the operation interface and the automatic control unit through the alarm module of the control system, which provides decision support for timely process intervention. This prediction-based early warning mechanism can provide sufficient reaction time before the interface failure occurs in the continuous extrusion process, and avoid product quality problems and production losses caused by interface abnormalities.

[0042] In an embodiment of the present application, process control is carried out based on the early warning signal, including: judging the risk type of interface failure according to the early warning signal, and determining the corresponding process parameter adjustment strategy for different risk types; adjusting the temperature parameter and the back pressure parameter synchronously according to the process parameter adjustment strategy, so that the interface viscoelasticity parameter returns to the pre-set safety range; continuously monitoring the adjustment effect to form a closed loop control.

[0043] The following is a specific description of the steps involved in the above embodiment: The early warning signal classifies the risk type according to the physical mechanism of the interface abnormality. The risk types of interface failure mainly include three modes: viscosity reduction risk, elastic modulus abnormality risk and interface peeling risk, which correspond to different failure mechanisms. The viscosity reduction risk refers to the risk that the interface transition layer viscosity continuously decreases, resulting in insufficient interface bonding force. The judgment standard is that the envelope slope prediction value is negative and the absolute value exceeds 0.1. The elastic modulus abnormality risk refers to the risk that the interface elastic properties mutate, resulting in stress concentration. The judgment standard is that the phase rotation rate prediction value exceeds 3.5 rad / s and the change rate is greater than 0.2 rad / s². The interface peeling risk refers to the risk that the interface completely loses the ability to bond, resulting in delamination. The judgment standard is that the envelope slope and phase rotation rate simultaneously exceed the safe range and the prediction trend continuously deteriorates. The process parameter adjustment strategy formulates corresponding treatment schemes according to the different risk types: for viscosity reduction risk, the strategy of increasing back pressure is adopted; for elastic modulus abnormality risk, the strategy of reducing temperature gradient is adopted; for interface peeling risk, the comprehensive strategy of simultaneously adjusting temperature and back pressure is adopted. For example, when the viscosity reduction risk is detected, the system automatically calls the back pressure increase strategy, and increases the back pressure of the middle layer melt from 10 MPa to 11 MPa. This risk classification method based on failure mechanism can accurately identify the root cause of interface abnormality, ensure the pertinence and effectiveness of the adjustment strategy, and avoid the poor effect caused by the general adjustment method.

[0044] The synchronous adjustment of process parameters realizes the coordinated control of temperature parameters and back pressure parameters through a distributed control system. Temperature parameter adjustment is realized through power control of regional heaters. When the temperature gradient needs to be reduced, the system automatically reduces the heating power of the high-temperature region and increases the heating power of the low-temperature region, with the adjustment amplitude controlled within ±5°C to avoid excessive adjustment. Back pressure parameter adjustment is realized through the opening control of screw back pressure valves. When the back pressure needs to be increased, the system automatically reduces the opening of the back pressure valve to increase the melt flow resistance, with the adjustment amplitude controlled within ±10% of the original back pressure value. Synchronous adjustment means that temperature parameters and back pressure parameters are adjusted simultaneously according to the preset time sequence relationship, avoiding system imbalance caused by single parameter adjustment. For example, when the comprehensive adjustment strategy is adopted, the system adjusts the temperature distribution while adjusting the back pressure, ensuring the stability of the viscosity gradient. The goal of parameter adjustment is to make the interface viscoelastic parameters return to the preset safe range, and the adjustment effect is judged by real-time monitoring of the adjusted parameter values. The judgment standard for safety range regression is that the envelope slope returns to the range of 0.10-0.30 and the phase rotation rate returns to the range of 1.0-3.0 rad / s. This synchronous adjustment mechanism can accurately control the interface state while maintaining the overall process stability, avoiding new process problems caused by improper parameter adjustment timing.

[0045] Closed-loop control achieves automatic system optimization through continuous monitoring of adjustment effects and feedback regulation. Continuous monitoring refers to continuing the interface detection program after parameter adjustment to track changes in the interface viscoelastic parameters in real time. The monitoring interval is set to 2-3 seconds to quickly capture the adjustment effect. The adjustment effect is evaluated by comparing the parameter values ​​and trends before and after adjustment. When the parameter values ​​return to the safe range and the trend stabilizes, the adjustment is considered effective. Feedback regulation refers to the process of fine-tuning the process parameters based on the monitoring results. When the initial adjustment effect is not ideal, the system automatically calculates the secondary adjustment amount and performs fine adjustment. For example, if the envelope slope has not fully returned to the safe range after the initial back pressure adjustment, the system automatically performs a secondary fine-tuning of the back pressure, with an adjustment range of 50% of the initial adjustment amount. The closed-loop control cycle is set to 30-60 seconds to ensure that the system has sufficient time to reach a new equilibrium state. The control algorithm uses a proportional-integral-derivative controller, with the proportional coefficient set to 0.5, the integral time set to 10 seconds, and the derivative time set to 2 seconds. These parameters are determined based on experimental calibration of the system response characteristics. This closed-loop control mechanism enables the automatic maintenance and optimization of the interface state, significantly improving the stability of the production process and the consistency of product quality, while reducing the need for manual intervention and the impact of operational errors.

[0046] The above describes the high-temperature co-extrusion material interface detection method in the embodiments of the present invention. The following describes the high-temperature co-extrusion material interface detection device in the embodiments of the present invention. Please refer to [link / reference]. Figure 2 One embodiment of the high-temperature co-extruded material interface detection device of the present invention includes: The process parameter control module 101 is used to set the process parameters of the multilayer melt separately, so that the multilayer melt forms an increasing viscosity gradient along the layer thickness direction at the confluence position of the die head. The process parameters include at least temperature parameters or back pressure parameters. The excitation signal generation module 102 is used to apply periodic mechanical shear excitation to the interface between adjacent melts and to simultaneously acquire the dynamic response signal corresponding to the excitation. The signal analysis and processing module 103 is used to analyze the dynamic response signal to obtain viscoelastic parameters characterizing the interface viscosity or elastic modulus. The state determination output module 104 is used to compare the viscoelastic parameters with a preset threshold and output a determination signal to characterize the viscoelastic state of the interface.

[0047] above Figure 2 The high-temperature co-extrusion material interface detection device in this embodiment of the invention is described in detail from the perspective of modular functional entities. The high-temperature co-extrusion material interface detection device in this embodiment of the invention is described in detail below from the perspective of hardware processing.

[0048] Figure 3is a structural schematic diagram of a high-temperature co-extrusion material interface detection device provided by an embodiment of the present application. The high-temperature co-extrusion material interface detection device 200 can have great differences due to different configurations or performances, and can include one or more processors 210 (for example, one or more processors) and a memory 220, one or more storage media 230 (for example, one or more mass storage device ends) storing application programs 233 or data 232. The memory 220 and the storage media 230 can be temporary storage or persistent storage. The programs stored in the storage media 230 can include one or more modules (not shown in the figure), and each module can include a series of instruction operations in the high-temperature co-extrusion material interface detection device 200. Further, the processor 210 can be configured to communicate with the storage media 230 and execute a series of instruction operations in the storage media 230 on the high-temperature co-extrusion material interface detection device 200 to realize the steps of the high-temperature co-extrusion material interface detection method described above.

[0049] The high-temperature co-extrusion material interface detection device 200 can also include one or more power supplies 240, one or more wired or wireless network interfaces 250, one or more input / output interfaces 260, and / or one or more operating systems 231, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art can understand that the high-temperature co-extrusion material interface detection device 200 can also include other components, and the components shown in the figure are not exhaustive. Figure 3 The structure of the high-temperature co-extrusion material interface detection device shown in the figure does not constitute a limitation on the high-temperature co-extrusion material interface detection device provided by the present application, and can include more or fewer components than shown in the figure, or combine certain components, or different component arrangements.

[0050] The present application also provides a computer readable storage medium, which can be a non-volatile computer readable storage medium, and can also be a volatile computer readable storage medium. The computer readable storage medium has instructions stored therein, and when the instructions are run on a computer, the computer executes the steps of the high-temperature co-extrusion material interface detection method.

[0051] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system or device, unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0052] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application or the entire or part of the technical solutions that essentially contribute to the prior art can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0053] The above description is only the preferred embodiments of the present application, and does not limit the patent scope of the present application. Any equivalent structural transformation made based on the inventive concept of the present application, or direct / indirect application in other related technical fields, is included in the patent protection scope of the present application.

Claims

1. A method for detecting the interface of high-temperature co-extruded materials, characterized in that, include: By setting the process parameters of the multilayer melt separately, the multilayer melt forms an increasing viscosity gradient along the thickness direction at the confluence position of the die head. The process parameters include at least temperature parameters or back pressure parameters. Periodic mechanical shearing excitation is applied to the interface between adjacent melts, and dynamic response signals corresponding to the excitation are collected simultaneously; The dynamic response signal is analyzed to obtain viscoelastic parameters characterizing the interfacial viscosity or elastic modulus. The viscoelastic parameters are compared with a preset threshold, and a judgment signal is output to characterize the viscoelastic state of the interface.

2. The method for detecting the interface of high-temperature co-extruded materials according to claim 1, characterized in that, The process of applying periodic mechanical shearing excitation to the interface between adjacent melts and simultaneously acquiring the dynamic response signal corresponding to the excitation includes: The interface resonant frequency window is calculated based on the interface characteristics between adjacent melts, and the starting frequency, cutoff frequency and scanning rate of the linear sweep are determined based on the resonant frequency window to obtain the sweep parameter configuration. According to the frequency sweep parameter configuration, a periodic shear excitation with an increasing frequency is applied to the multilayer melt, so that each adjacent interface produces a differentiated frequency response, and excitation-response time series data is synchronously collected at each frequency point to obtain frequency band response data. The frequency band response data is subjected to harmonic decomposition processing to extract the fundamental frequency response component, second harmonic component and higher harmonic component that reflect the viscoelastic properties of the interface. The interface characteristic response spectrum is obtained according to the amplitude ratio and phase relationship of each harmonic component. The interface characteristic response spectrum is used for subsequent signal analysis and processing.

3. The method for detecting the interface of high-temperature co-extruded materials according to claim 1, characterized in that, The analysis of the dynamic response signal to obtain viscoelastic parameters characterizing the interfacial viscosity or elastic modulus includes: The dynamic response signal is registered with the preset baseline data in the time and frequency domain, and the registered signal is subjected to point-by-point differential operation to obtain the differential signal. The differential signal is subjected to Hilbert transform to extract the instantaneous amplitude and instantaneous phase of the differential signal, and a time-domain differential envelope is constructed based on the instantaneous amplitude. Based on the material properties of each layer of melt, the energy storage-energy dissipation frequency boundary point of the corresponding interface is determined, and the differential envelope is divided into frequency domains according to the energy storage-energy dissipation frequency boundary point to obtain energy storage harmonic region data and energy dissipation harmonic region data. The time-domain envelope slope is calculated for the energy storage harmonic region data, the phase rotation rate is calculated for the energy dissipation harmonic region data based on the time change of the instantaneous phase, and viscoelastic parameters characterizing the interface state are constructed based on the envelope slope and the phase rotation rate.

4. The method for detecting the interface of high-temperature co-extruded materials according to claim 3, characterized in that, The preset baseline data is obtained through the following methods: Before the steady state of the multilayer melt is established, the screw and the traction device are locked at low frequency. Within the locking window, torque-displacement signals and tension-displacement signals are continuously collected in time sequence. At the same time, the instantaneous viscosity fluctuations of each adjacent interface are recorded to obtain a multidimensional baseline signal group. The multidimensional baseline signal group is subjected to frequency domain decomposition and amplitude normalization processing to extract baseline feature data characterizing system inertial parameters, material batch parameters and interface coupling parameters, respectively. The baseline feature data is weighted and synthesized according to weights to serve as the zero-point reference for differential calculation, thereby obtaining the preset baseline data.

5. The method for detecting the interface of high-temperature co-extruded materials according to claim 1, characterized in that, The multilayer melt includes an outer melt, a middle melt, and an inner melt; The step of comparing the viscoelastic parameter with a preset threshold and outputting a determination signal characterizing the viscoelastic state of the interface includes: The viscoelastic parameters of the outer-middle layer interface and the middle-inner layer interface were obtained respectively. Calculate the difference in viscoelastic parameters between the two interfaces, and construct the interface coupling factor based on the difference; The interface coupling factor is compared with a preset cooperative state threshold, and a judgment signal reflecting the cooperative state of multiple interfaces is output.

6. The method for detecting the interface of high-temperature co-extruded materials according to claim 1, characterized in that, The detection method is further enhanced by repeatedly performing the above-described detection method: Viscoelastic parameters were collected at multiple time points during repeated testing, and the changing trend of viscoelastic parameters over time was calculated. Extrapolate and predict the changes in the viscoelastic parameters of the interface over a future time period based on the changing trend of the viscoelastic parameters. When the prediction result exceeds the safe range, an early warning signal is output.

7. The method for detecting the interface of high-temperature co-extruded materials according to claim 6, characterized in that, Process control based on the aforementioned warning signal includes: Based on the warning signal, determine the risk type of interface failure, and determine the corresponding process parameter adjustment strategy for different risk types; According to the process parameter adjustment strategy, the temperature parameter and back pressure parameter are adjusted synchronously to bring the interfacial viscoelastic parameter back to the preset safe range.

8. A device for detecting the interface of high-temperature co-extruded materials, characterized in that, The detection device includes: The process parameter control module is used to set the process parameters of the multilayer melt separately, so that the multilayer melt forms an increasing viscosity gradient along the layer thickness direction at the confluence position of the die head. The process parameters include at least temperature parameters or back pressure parameters. The excitation signal generation module is used to apply periodic mechanical shear excitation to the interface between adjacent melts and simultaneously acquire the dynamic response signal corresponding to the excitation. The signal analysis and processing module is used to analyze the dynamic response signal to obtain viscoelastic parameters characterizing the interface viscosity or elastic modulus. The state determination output module is used to compare the viscoelastic parameters with a preset threshold and output a determination signal to characterize the viscoelastic state of the interface.

9. A high-temperature co-extruded material interface testing device, characterized in that, The high-temperature co-extruded material interface detection includes: a memory and at least one processor, wherein the memory stores instructions; The at least one processor invokes the instructions in the memory to cause the high-temperature co-extrusion material interface detection device to perform the steps of the high-temperature co-extrusion material interface detection method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing instructions thereon, characterized in that, When the instruction is executed by the processor, it implements the steps of the high-temperature co-extruded material interface detection method as described in any one of claims 1 to 7.

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