A process and method for suppressing the extrusion of flocculent material in high-voltage cable insulation layer

Abstract

The application relates to the technical field of cable manufacturing, and provides an extrusion process and method for inhibiting flocculation of high-voltage cable insulation layer mixtures, which comprises the following steps: adopting an alternatingly arranged strong shearing zone and stress relaxation zone to perform extrusion treatment on a high polymer material melt; at least two physical parameters representing melt flow resistance are synchronously collected during the extrusion process; the micro-defect state of the melt is identified based on the synchronous pulsation characteristics of the physical parameters; and a corresponding hierarchical control strategy is executed in response to the micro-defect state satisfying a preset risk condition. The application realizes online prediction and self-adaptive hierarchical control of micro-flocculation defects, and gives consideration to the dispersion effect and stress elimination of the melt.

Description

Technical Field

[0001] This application relates to the field of cable manufacturing technology, specifically to an extrusion process and method for suppressing flocculent material in the insulation layer of high-voltage cables. Background Technology

[0002] In the precision extrusion manufacturing process of high-voltage and ultra-high-voltage cross-linked polyethylene power cable insulation layers, the insulation material is typically a precision polymer cross-linked material. Due to differences in formulation systems, melt viscosity index, and rheological properties between different batches or manufacturers of raw materials, multiple batches of mixed materials are inevitably fed into the production process. In existing technologies, conventional extrusion screws typically employ a consistent screw height and groove depth throughout the entire process. This structure faces a dilemma when handling mixed melts: if the radial clearance is large, the shear force is insufficient to effectively disperse micron-sized raw rubber flocs caused by melt incompatibility; if the radial clearance is small to enhance shear, it leads to the accumulation of enormous internal stress in the melt, resulting in electric field concentration and stress cracking during cable operation. Furthermore, existing online monitoring methods mainly rely on single absolute changes in pressure or torque to identify large particulate impurities. They lack effective dynamic characterization methods for microscopic flocculent defects caused by mixed incompatibility, meaning these defects are often only discovered during finished product factory testing or cross-sectional inspection, resulting in significant resource waste and quality risks. Therefore, there is an urgent need for a technical solution that can simultaneously predict micro-defects online and eliminate melt stress during the extrusion process. Summary of the Invention

[0003] To address the problem that existing technologies cannot simultaneously achieve online prediction of micro-defects and elimination of melt stress, this application proposes an extrusion process and method for suppressing flocculent material in high-voltage cable insulation layer mixtures, thereby enabling real-time identification, graded treatment, and effective release of melt stress during the mixing and extrusion process.

[0004] To achieve the above objectives, this application adopts the following technical solution: An extrusion process for suppressing flocculent material in high-voltage cable insulation layers includes: extruding a polymer melt using alternating high-shear zones and stress relaxation zones; simultaneously acquiring at least two physical parameters characterizing the flow resistance of the polymer melt during the extrusion process; identifying the microscopic defect state of the polymer melt based on the synchronous pulsation characteristics of the at least two physical parameters; and executing a corresponding graded control strategy in response to the microscopic defect state meeting preset risk conditions.

[0005] The above scheme solves the contradiction between high shear and low stress from a physical structure perspective by constructing functionally decoupled alternating processing regions along the extrusion path. It utilizes the strong shear zone to provide the mechanical energy required to break up agglomerates, while using the stress relaxation zone to provide thermodynamic space for the polymer chains to stretch and reset. Based on this, by extracting the synchronous pulsation characteristics of multiple physical quantities that characterize flow resistance, it accurately captures the rheological disturbance signals caused by microscopic incompatibility and eliminates environmental noise interference such as temperature and voltage. This enables online prediction and adaptive hierarchical control of nascent defects.

[0006] As one implementation method, an alternating configuration of a strong shear zone and a stress relaxation zone is used to extrude a polymer melt. This includes: conveying the polymer melt using an extrusion screw; the extrusion screw is alternately equipped with strong shear units and melt relaxation reflux units along the material conveying direction; the strong shear units constitute a strong shear zone, and the melt relaxation reflux units constitute a stress relaxation zone; wherein the radial gap between the screw tip of the strong shear unit and the barrel is less than a preset gap threshold to break up micro-agglomerates in the polymer melt; the screw groove depth of the melt relaxation reflux unit is greater than the screw groove depth of the strong shear unit to release the internal stress of the polymer melt.

[0007] This preferred scheme achieves a "break-release" cyclical iterative mechanism through a specific screw geometry. The extremely small radial gap forces the melt to undergo high-intensity tensile and shear flow fields, specifically targeting the secondary refinement of the phase separation region that has melted but is unevenly mixed; while the subsequent deep-groove recirculation unit, through the instantaneous expansion of the flow channel volume, causes a sharp drop in melt pressure, allowing the molecular chains to retract under entropy drive and eliminate orientation stress, thereby ensuring the dispersion effect while avoiding damage to the insulating electrical properties caused by residual stress.

[0008] As one implementation method, at least two physical parameters characterizing the flow resistance of polymer melt are simultaneously acquired, including: simultaneously acquiring the die head melt pressure and screw torque; based on the synchronous pulsation characteristics of the at least two physical parameters, the micro-defect state of the polymer melt is identified, including: extracting the high-frequency pulsation amplitude of the die head melt pressure and the high-frequency pulsation amplitude of the screw torque; when the high-frequency pulsation amplitude of the die head melt pressure and the high-frequency pulsation amplitude of the screw torque synchronously exceed a preset pulsation baseline, it is determined that there are micro-defects in the polymer melt.

[0009] This preferred approach leverages the unique behavior of micro-flocs in the flow field. Unlike the increased steady-state drag caused by macroscopic impurities, the continuous generation, breakup, and recombination of micron-sized flocs induce high-frequency viscoelastic fluctuations within the melt. These fluctuations are simultaneously coupled and reflected in the pressure and torque fields. By locking the "synchronous" pulsation characteristics of the two parameters, single-parameter spurious signals caused by heating coil switching, power grid fluctuations, or mechanical vibrations can be effectively filtered out, significantly improving the signal-to-noise ratio and robustness of defect identification.

[0010] As one implementation method, in response to the micro-defect state meeting preset risk conditions, a corresponding hierarchical control strategy is executed, including: when the high-frequency pulsation amplitude of the die head melt pressure and the high-frequency pulsation amplitude of the screw torque synchronously exceed a first risk threshold but do not exceed a second risk threshold, an online parameter adjustment and repair action is performed; when the high-frequency pulsation amplitude of the die head melt pressure and the high-frequency pulsation amplitude of the screw torque synchronously exceed the second risk threshold, a shutdown alarm is triggered; wherein, the second risk threshold is greater than the first risk threshold.

[0011] This preferred approach establishes a differentiated response mechanism based on risk level. Minor defects in their nascent stage are treated as controllable process windows, and unplanned downtime is avoided through online intervention. For severe incompatibilities exceeding the material's self-healing capabilities, production is immediately halted to prevent mass scrap, thereby maximizing production continuity and overall equipment efficiency while ensuring product quality standards.

[0012] As one implementation method, the online parameter adjustment and repair action includes: automatically reducing the extrusion speed and / or fine-tuning the die temperature; the method further includes: periodically acquiring microscopic inspection data of the insulation slice, the microscopic inspection data including at least one of floc percentage, particle size, or quantity; automatically updating a first risk threshold based on the microscopic inspection data to offset equipment wear or process drift; automatically updating the first risk threshold based on the microscopic inspection data includes: statistically analyzing the floc percentage in the microscopic inspection data of the insulation slice within a preset time period; when the floc percentage is greater than a preset qualified percentage, decreasing the first risk threshold by a preset step size; when the floc percentage is less than or equal to the preset qualified percentage, increasing the first risk threshold by a preset step size, so that the first risk threshold dynamically approaches the actual defect critical point.

[0013] This preferred scheme constructs a closed-loop self-learning system of "online perception - offline verification - model correction". By feeding the laboratory microscopic characterization results as the truth value to the online discrimination model, the system can adaptively compensate for the attenuation of shear efficiency caused by screw wear or the baseline drift caused by seasonal temperature differences. The dynamic bidirectional adjustment mechanism of the threshold ensures that the discrimination standard is always anchored on the true quality boundary, solving the industry problem of accuracy degradation after long-term operation of traditional fixed threshold algorithms.

[0014] As one implementation method, before extruding the polymer melt using alternating high shear zones and stress relaxation zones, the method further includes: using a rheometer to replicate the temperature and shear rate parameters of the extruder and collecting the pressure and torque pulsation baseline under steady state; if the pressure and torque pulsation baseline shows synchronous high-frequency pulsation, the material is determined to be incompatible and feeding is prohibited.

[0015] This preferred solution moves the quality control checkpoint forward to the raw material intake stage. By accurately replicating the rheological conditions of mass production in a laboratory environment, it identifies material combinations with extremely poor batch compatibility in advance, preventing unqualified raw materials from entering the expensive extrusion production line. This reduces trial-and-error costs and equipment contamination risks from the source, forming a dual protection system that complements online control in both time and space.

[0016] Furthermore, this application also provides an extrusion system for suppressing flocculent material in high-voltage cable insulation layers, comprising: an extrusion screw assembly including alternating high-shear zones and stress relaxation zones for extruding polymer melt; a multi-parameter synchronous acquisition module for synchronously acquiring at least two physical parameters characterizing the flow resistance of the polymer melt during the extrusion process; and a defect identification and grading control module for identifying the microscopic defect state of the polymer melt based on the synchronous pulsation characteristics of at least two physical parameters, and executing a corresponding grading control strategy in response to the microscopic defect state meeting preset risk conditions.

[0017] The aforementioned system, through deep integration of hardware structure and intelligent algorithms, transforms the physical efficiency of alternating shear-relaxation and the information efficiency of multi-parameter synchronous sensing into executable industrial control commands, providing a standardized hardware and software carrier for the precision manufacturing of high-voltage cable insulation layers.

[0018] Compared with the prior art, the beneficial effects of the present invention are: The proposed technical solution, through alternating configurations of strong shear zones and stress relaxation zones, achieves functional decoupling and spatiotemporal synergy between melt dispersion and stress relaxation at the physical level. This overcomes the inherent contradiction in traditional single-structure screw extruders during compounding extrusion—where strong shear inevitably leaves stress, while weak shear makes it difficult to eliminate flocs—ensuring the microscopic uniformity and macroscopic electrical properties of the insulating material. Simultaneously, based on the synchronous pulsation characteristic recognition mechanism of the die head melt pressure and screw torque, it reveals the intrinsic correlation between the evolution of microscopic flocs and the high-frequency coupling of macroscopic rheological parameters, effectively eliminating environmental noise interference and achieving precise capture and graded treatment of nascent defects, avoiding excessive downtime or missed defects leading to scrap. Furthermore, combined with a closed-loop self-calibration strategy using microscopic section data, the discrimination threshold can dynamically evolve with equipment status and process environment, eliminating model drift during long-term operation and ensuring the consistency and reliability of quality control throughout the entire lifecycle. Attached Figure Description

[0019] Figure 1 This is a flow chart of the extrusion process for suppressing flocculent material in the insulation layer of high-voltage cables, according to an embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application.

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

[0022] like Figure 1 As shown, this embodiment provides an extrusion process for suppressing flocculent material in high-voltage cable insulation layers. This method achieves proactive suppression and adaptive control of microscopic defects during extrusion through deep coupling of physical structure modification and intelligent sensing control logic. The method mainly includes the following steps: Step S100: The polymer melt is extruded using alternating high shear zones and stress relaxation zones.

[0023] Specifically, this step breaks through the limitations of the traditional uniform structure of extrusion screws by constructing functionally decoupled alternating processing zones along the melt delivery path. The high-shear zone is configured to provide high-intensity mechanical shear energy, specifically for breaking up micro-agglomerates and raw rubber flocs generated by mixing raw materials from different batches or manufacturers. The stress relaxation zone follows closely behind, configured to provide sufficient flow channel volume and thermodynamic space, allowing the melt subjected to high shear to release accumulated internal stress and promote the stretching and repositioning of polymer chains. This alternating configuration is not a simple structural assembly, but a spatiotemporal collaborative design based on the principles of polymer rheology. This allows the melt to repeatedly undergo a cycle of "break-up and release" during its journey, effectively avoiding damage to the electrical properties of insulating materials from residual stress while ensuring uniform micro-dispersion. This fundamentally solves the industry dilemma of balancing high-shear dispersion and low-stress molding. In this embodiment, the temperatures of each section of the extruder barrel are set as follows: feeding section 100°C, compression section 115°C, metering section 115°C, and die head 120°C.

[0024] Step S200: During the extrusion process, at least two physical parameters characterizing the melt flow resistance of the polymer material are collected simultaneously.

[0025] Specifically, to accurately capture rheological disturbances caused by microscopic incompatibilities, this embodiment abandons the traditional approach of relying on a single absolute value for monitoring and instead adopts a multi-physical quantity synchronous sensing mechanism. Physical parameters characterizing flow resistance can be parameters that reflect the internal friction and viscoelastic state of the melt, such as melt pressure at the die head, screw torque, melt viscosity, or motor power. By synchronously acquiring at least two such parameters, the system can construct a multi-dimensional feature vector of the melt flow state. For example, when micron-sized flocs exist in the melt, their continuous generation, breakup, and reorganization in the flow field induce high-frequency viscoelastic fluctuations, which are simultaneously coupled and reflected in the pressure and torque fields. The synchronous acquisition mechanism ensures that the data used for subsequent analysis are strictly aligned on the time axis, laying a data foundation for eliminating environmental noise interference.

[0026] Step S300: Identify the microscopic defect state of the polymer melt based on the synchronous pulsation characteristics of at least two physical parameters.

[0027] Specifically, the core of this step lies in utilizing "synchronous pulsation" as a specific fingerprint of microscopic defects. Unlike the increase in steady-state resistance caused by macroscopic impurities or the single-parameter anomalies caused by equipment failure, the rheological disturbances caused by microscopic flocculent defects have significant characteristics of high-frequency, small-amplitude, and multi-parameter synchronous jumps. The system performs time-frequency domain analysis on the collected physical parameters, extracts their high-frequency pulsation amplitudes, and determines whether these pulsations synchronously exceed a preset baseline within a time window. Only when multiple parameters characterizing flow resistance simultaneously exhibit a consistent pulsation trend are they confirmed as genuine microscopic defect signals. This judgment logic can effectively filter out single-parameter pseudo-signals caused by heating coil switching, grid voltage fluctuations, or mechanical vibrations, significantly improving the signal-to-noise ratio and robustness of defect identification, and achieving accurate capture of nascent defects.

[0028] Step S400: In response to the micro-defect state meeting the preset risk conditions, the corresponding hierarchical control strategy is executed.

[0029] Specifically, this step establishes a differentiated response mechanism based on risk levels to balance product quality and production efficiency. The system categorizes identified micro-defects into different risk levels based on their severity (e.g., the magnitude and duration of pulsation), and matches them with corresponding control actions. For severe risks exceeding the material's self-healing capabilities, a shutdown alarm is immediately triggered to prevent batch scrap. For minor risks in their early stages, they are treated as adjustable process windows, and online parameter adjustments are performed, such as adjusting speed, temperature, or back pressure, relying on the screw's alternating structural characteristics to eliminate defects online. This tiered control strategy avoids the traditional "shutdown for abnormalities" approach, maximizing production continuity and overall equipment efficiency while ensuring a minimum product quality.

[0030] It should be understood that although this embodiment describes the method in a specific order of steps, in practical applications, steps S200 and S300 can be executed in real time in parallel, and the execution result of step S400 can also be fed back to step S100 to dynamically adjust the extrusion process parameters. Furthermore, the specific implementation methods of the above steps are not limited to those described in this embodiment; any technical means capable of achieving the same function should be covered within the scope of protection of this application. Example

[0031] As one implementation method, an alternating configuration of high-shear zones and stress relaxation zones is used to extrude polymer melt. This includes: conveying the polymer melt using an extrusion screw; the extrusion screw is alternately equipped with high-shear units and melt relaxation / recirculation units along the material conveying direction; the high-shear units constitute the high-shear zone, and the melt relaxation / recirculation units constitute the stress relaxation zone. This alternating arrangement is not a simple splicing of functional areas, but rather a periodic processing unit designed based on the rheological properties of the polymer melt. In specific implementations, the high-shear units and melt relaxation / recirculation units can be arranged in repeated groups, for example, using a four-segment or more combination layout of "high-shear-relaxation-high-shear-relaxation". In this embodiment, the extrusion screw has a screw diameter of 200 mm, a length-to-diameter ratio (L / D) of 22, and an operating speed range of 4-20 rpm. Two sets of alternating strong shear units and melt relaxation reflux units are set up. In each set, the axial length of the strong shear unit is 300mm and the axial length of the melt relaxation reflux unit is 400mm, to ensure that the melt can undergo multiple dispersion and homogenization cycles during the process of passing through the entire screw assembly.

[0032] In this design, the radial gap between the screw tip and the barrel of the high-shear unit is smaller than a preset gap threshold to generate shearing and tearing forces that break down microscopic agglomerates in the polymer melt. Specifically, this radial gap is a key geometric parameter determining the shearing efficiency. In precision extrusion of XLPE insulation materials, the preset gap threshold is set to 90 μm, while the radial gap of a conventional XLPE extrusion screw is typically 300 μm. When the melt flows through this micron-sized narrow gap, the melt is forced to withstand extremely high shear rates and tensile stresses due to the rapid contraction of the flow channel cross-section, forming a strong shearing and tearing force field. This high-intensity mechanical action is specifically designed to further refine and break down microscopic raw rubber flocs or phase-separated regions that have already melted but are not fully dispersed due to poor compatibility, reducing their size to the micron or even nanometer scale without affecting electrical properties. Compared to the larger uniform gap of traditional screws, this locally minimizing gap design can achieve targeted removal of stubborn agglomerates without significantly increasing the overall melt temperature.

[0033] The groove depth of the melt relaxation and reflux unit is greater than that of the high-shear unit to provide flow channel space for releasing the internal stress of the polymer melt. Specifically, the ratio of the groove depth of the melt relaxation and reflux unit to that of the high-shear unit is typically greater than 1.3. In this embodiment, the groove depth of the conventional screw is 13 mm, the groove depth of the high-shear unit is 16.25 mm (corresponding to a 25% increase in screw height), and the groove depth of the melt relaxation and reflux unit is 22 mm, resulting in a groove depth ratio of approximately 1.35. When the melt, having undergone high-intensity shear, leaves the narrow gap and enters the deep groove region, the flow channel volume expands instantaneously, and the melt pressure drops sharply. This sudden pressure release provides valuable thermodynamic relaxation space for the polymer chains, allowing the molecular chains, which were forced to orient and stretched in the high-shear field, to retract and reset, thereby effectively dissipating the accumulated elastic deformation energy. Meanwhile, the deepened grooves allow for minute local backflow and tumbling of the melt, further promoting macroscopic uniformity of temperature and composition. This structural design fundamentally solves the technical paradox in traditional processes that "enhanced shearing inevitably leads to increased residual stress," ensuring that the final extruded insulation layer has both excellent microscopic dispersion and maintains a stable state with low internal stress, thus avoiding the risk of electric field distortion or insulation cracking caused by stress concentration during cable operation. Example

[0034] As one implementation method, at least two physical parameters characterizing the melt flow resistance of polymer materials are simultaneously acquired, including: simultaneously acquiring the die head melt pressure and screw torque. Specifically, the die head melt pressure directly reflects the outlet resistance state of the melt as it passes through the die, while the screw torque characterizes the overall shear resistance and viscoelastic response of the melt throughout the entire conveying and plasticizing process. These two parameters are chosen as monitoring targets because they capture the melt state from the end boundary conditions of the flow field and the global energy input dimension, respectively, and are physically highly complementary and coupled. Compared to monitoring only a single parameter, this dual-parameter combination can construct a more complete melt rheological characteristic vector, providing a multi-dimensional data foundation for subsequent accurate identification of microscopic defects. In this embodiment, the sampling frequency of both the pressure sensor and the torque sensor is set to 100-150Hz to ensure that high-frequency pulsating signals caused by microscopic flocs can be captured.

[0035] Based on the synchronous pulsation characteristics of at least two physical parameters, the microscopic defect state of polymer melt is identified, including: extracting the high-frequency pulsation amplitude of the die head melt pressure and the high-frequency pulsation amplitude of the screw torque; when the high-frequency pulsation amplitude of the die head melt pressure and the high-frequency pulsation amplitude of the screw torque synchronously exceed a preset pulsation baseline, it is determined that microscopic defects exist in the polymer melt. Specifically, the extraction of high-frequency pulsation amplitude is usually achieved by high-pass filtering or short-time Fourier transform of the original signal to separate the rapid fluctuation components induced by the formation, breakage, and recombination of micro-flocs, and to eliminate the low-frequency trend terms generated by the steady-state operation of the equipment. The "synchronous exceedance" emphasized here is a key criterion for distinguishing between real defects and environmental noise. In actual production, the periodic switching of the heating coil may cause individual pressure fluctuations, the instantaneous drop in grid voltage may cause instantaneous torque anomalies, and mechanical vibration may also cause pseudo-signals of a single parameter. However, these external interference factors rarely excite high-frequency resonance of pressure and torque simultaneously and in phase. Only when microscopic raw rubber flocs are present inside the melt due to incompatibility in the mixture will their non-uniform motion in the flow field simultaneously disturb the pressure and torque fields, forming a specific synchronous pulsation fingerprint. In this embodiment, the criterion for "synchronization" is: the high-frequency pulsation amplitudes of pressure and torque simultaneously exceed a preset baseline within a 0.05s time window, which is considered synchronous pulsation. Therefore, this judgment logic can effectively filter out various single-parameter environmental noises, significantly improve the signal-to-noise ratio and robustness of defect identification, and avoid invalid shutdowns caused by false alarms.

[0036] In response to micro-defect conditions meeting preset risk conditions, the system executes corresponding graded control strategies, including: when the high-frequency pulsation amplitude of the melt pressure at the die head and the high-frequency pulsation amplitude of the screw torque simultaneously exceed a first risk threshold but not a second risk threshold, an online parameter adjustment and repair action is performed; when the high-frequency pulsation amplitude of the melt pressure at the die head and the high-frequency pulsation amplitude of the screw torque simultaneously exceed the second risk threshold, a shutdown alarm is triggered; wherein, the second risk threshold is greater than the first risk threshold. Specifically, this dual-threshold graded mechanism discretizes the severity of continuous defects into executable decision intervals. The first risk threshold corresponds to minor defects in their nascent stage, at which point, although a small amount of flocs have appeared in the melt, they have not yet formed macroscopic aggregation and are still within the adjustable range of the process window. By defining this interval as the "repairable zone," the system avoids the coarse response of "shutdown if abnormal" in traditional control, maximizing production continuity while ensuring quality. It should be understood that the specific values ​​of the first and second risk thresholds are not fixed, but can be calibrated and dynamically adjusted according to the rheological properties, product specifications, and historical production data of different grades of XLPE materials to adapt to changing operating conditions. In this embodiment, the first risk threshold is set as ΔP>2ΔP0 and ΔM>2ΔM0 (i.e., the pulsation amplitude exceeds the baseline by more than 10%), and the second risk threshold is set as ΔP>4ΔP0 and ΔM>4ΔM0 (i.e., the pulsation amplitude exceeds the baseline by more than 20%), where ΔP0 is the steady-state pressure pulsation baseline and ΔM0 is the steady-state torque pulsation baseline. The second risk threshold corresponds to a severe incompatibility state that exceeds the material's self-healing ability or endangers the product's electrical performance baseline. In this case, production must be immediately stopped to prevent batch scrap or equipment overload damage.

[0037] During online parameter adjustment and repair, the system automatically reduces the extrusion speed and / or fine-tunes the die temperature, relying on the strong shear unit to shear and break down micro-flocs online. Specifically, this repair strategy is not simply a compensation of process parameters, but a physicochemical process deeply synergistic with the alternating screw structure described in Example 2. When minor defects are identified, appropriately reducing the extrusion speed can prolong the residence time of the melt in the narrow gap region of the strong shear unit, giving micro-flocs more opportunities to be refined and dispersed by high-intensity shear tearing forces; at the same time, fine-tuning the die temperature can improve the local fluidity of the melt, reduce the interfacial tension caused by viscosity differences, and promote better fusion of poorly compatible components in the stress relaxation zone. This composite repair mechanism of "parameter adjustment + structural empowerment" fully utilizes the physical functions of the screw itself to eliminate defects, rather than simply relying on passive changes in thermal or shear history, thereby achieving quality self-healing without stopping the machine. For example, during a 66kV cable insulation extrusion process, the system detected that the synchronous pulsation amplitude of pressure and torque was between the first and second risk thresholds. It then automatically reduced the screw speed by 5%-10% from the rated value and fine-tuned the die temperature by ±3℃. After about 3 minutes of adaptive adjustment, the synchronous pulsation signal returned to the baseline level. The production process was not interrupted, and subsequent slice testing showed that the proportion of flocs was qualified, verifying the effectiveness of the graded repair strategy. Example

[0038] As one implementation method, online parameter adjustment and repair actions are performed, including: automatically reducing the extrusion speed by 5%-10% (minimum not less than 5 rpm) and / or adjusting the die temperature by ±3°C, relying on the strong shear unit to shear and break down micro-flocs online. Specifically, this repair strategy is not an isolated process parameter compensation, but a physical process deeply coordinated with the alternating screw structure described in Example 2. When the system identifies a slight defect between the first and second risk thresholds, automatically reducing the extrusion speed can significantly prolong the residence time of the melt in the narrow gap region of the strong shear unit. According to the principles of polymer rheology, the shear dispersion effect depends not only on the shear rate, but also on the cumulative shear strain. Although reducing the speed slightly reduces the instantaneous shear rate, it significantly increases the duration of the melt subjected to high-intensity shear tearing forces, giving stubborn micro-flocs that might escape at normal flow rates a greater chance to be thoroughly refined and dispersed. At the same time, fine-tuning the die temperature can improve the local flowability differences of the melt, reduce the interfacial tension caused by viscosity mismatch, and promote better integration of poorly compatible components in the subsequent stress relaxation zone. This composite repair mechanism of "parameter adjustment + structural empowerment" makes full use of the screw's own physical functions to eliminate defects, achieving quality self-healing without stopping the machine, and avoiding the efficiency loss and material waste caused by relying solely on heating degradation or stopping the machine for cleaning in traditional processes.

[0039] The method also includes: periodically acquiring microscopic inspection data of the insulation slices. The microscopic inspection data includes at least one of the following: floc percentage, particle size, or quantity. Specifically, the frequency of periodic acquisition can be set according to the production rhythm. For example, sampling is performed once for each roll of cable produced. In this embodiment, two samples are taken for each observation: once after the pre-rheological experiment, once every half hour after the large-scale machine empty extrusion, and once at the beginning and end of each product in formal production. Microscopic inspection data is an objective quality characterization obtained through imaging analysis of the slice samples using an optical microscope or electron microscope. The floc percentage refers to the ratio of the total projected area of ​​all microscopic flocs in the field of view to the total area of ​​the field of view; it is the most direct indicator reflecting the microscopic uniformity of the insulation layer. Compared to the indirect rheological signals acquired by online sensors, microscopic inspection data represents the "true value" of product quality, providing an irreplaceable benchmark for the calibration of the online discrimination model. It should be understood that, in addition to the floc percentage, parameters such as the maximum floc particle size and the number of flocs per unit area can also be used as feedback variables, as long as they can quantitatively characterize the severity of microscopic defects. In this embodiment, the qualified criteria for flocs also include: the effective diameter of a single floc shall not exceed 0.1 mm, and the number of flocs per unit area shall not exceed 1 / mm².

[0040] The first risk threshold is automatically updated based on microscopic inspection data to offset equipment wear or process drift. Specifically, during the long-term operation of the extrusion system, the tips of the screw edges of the high-shear unit gradually wear due to continuous friction, leading to increased radial clearance and decreased shear efficiency. Simultaneously, seasonal changes in ambient temperature or minor fluctuations in raw material batches can cause drift in the melt rheological baseline. If the first risk threshold remains fixed, as the equipment ages, minor defect signals that could trigger online repair may fall below the threshold due to weakened shear force, resulting in missed detections; or, due to baseline drift, frequent false triggering of repair actions may occur, causing unnecessary production capacity losses. This embodiment introduces microscopic inspection data as feedback to construct a closed-loop self-learning system of "online sensing - offline verification - model correction," enabling the judgment criteria to dynamically adjust with the evolution of equipment status and process environment. This fundamentally solves the industry problem of accuracy degradation after long-term operation of fixed threshold algorithms, ensuring the consistency and reliability of quality control throughout the entire lifecycle.

[0041] The system automatically updates the first risk threshold based on microscopic inspection data. This includes: statistically analyzing the proportion of flocs in the microscopic inspection data of insulation sections within a preset time period; decreasing the first risk threshold by a preset step size when the proportion of flocs is greater than the preset acceptable proportion; and increasing the first risk threshold by a preset step size when the proportion of flocs is less than or equal to the preset acceptable proportion, so that the first risk threshold dynamically approaches the actual defect threshold. Specifically, the preset acceptable proportion is the quality acceptance baseline determined according to the electrical performance requirements of the product. For example, for the insulation layer of 66kV and above high-voltage cables, this value is usually set to ≤0.1%. When the statistically obtained proportion of flocs is greater than the preset acceptable proportion, it indicates that the current first risk threshold setting is too lenient, and some minor defects that should have been identified and triggered online repair are being missed. At this time, the system decreases the first risk threshold by a preset step size (e.g., adjusting by 0.02MPa or 0.5N·m each time), which is equivalent to improving the sensitivity of the system and expanding the triggering range of the online repair mechanism to more actively intercept nascent defects. Conversely, when the proportion of flocs is less than or equal to the preset acceptable proportion, it indicates that the current quality control level meets the requirements, and there may even be a situation where the threshold is too strict, leading to over-repair. In this case, the system increases the first risk threshold according to the preset step size, appropriately relaxes the triggering conditions for online repair, releases the process window, improves production efficiency, and avoids melt thermal history fluctuations caused by excessive intervention. This two-way adjustment mechanism makes the first risk threshold no longer a static empirical value, but a dynamic variable that can track the real defect critical point in real time. For example, in a certain continuous production process, as the wear of the strong shear unit intensifies, the system detects that the proportion of flocs in three consecutive sampling cycles exceeds the 0.1% acceptable line. It then automatically adjusts the first risk threshold step by step according to the correction formula, which is: ΔP0 new = K·ΔP0 measured + (1-K)·ΔP0 historical arithmetic average, where K=0.3. After the adjustment, the proportion of flocs in subsequent sampling cycles falls back to below 0.1%, successfully compensating for the shear efficiency decay caused by mechanical wear, and verifying the effectiveness of the closed-loop self-calibration mechanism. Example

[0042] As one implementation method, before extruding the polymer melt using alternating high shear zones and stress relaxation zones, the method further includes: using a rheometer to replicate the temperature and shear rate parameters of the extruder and collecting the pressure and torque pulsation baseline under steady state; if the pressure and torque pulsation baseline shows synchronous high-frequency pulsation, the material is determined to be incompatible and feeding is prohibited.

[0043] Specifically, this embodiment moves the quality control checkpoint further upstream from online monitoring during the production process to the raw material access stage, constructing a source interception defense line independent of the online extrusion control system. In actual production, XLPE insulation materials from different batches or manufacturers often differ in their formulation systems, molecular weight distributions, and additive contents. These differences lead to melt incompatibility that is highly dependent on operating conditions and cannot be effectively identified by conventional melt flow rate (MI) or density testing alone. Therefore, this embodiment uses a rheometer as a production access quality inspection device to strictly replicate the real operating parameters of the mass production extruder, including heating temperature (128-132℃), shear rate (60-100 s⁻¹), melt residence time (5-10 min), and pressure (2-8 MPa) of each section, so that the laboratory sample testing environment is as close as possible to the thermomechanical history of the actual production line. It should be understood that "replication" here does not require all parameters to be absolutely identical, but rather to be equivalent in a rheological sense, that is, to ensure that the shear stress level and thermal history experienced by the test sample can induce the same type of microphase separation behavior as in the large-scale extrusion process.

[0044] Under replicated operating conditions, the system waits for the melt to completely melt and reach thermal equilibrium and flow stability before collecting steady-state pressure and torque pulsation baselines. This step is crucial because during the transition phase between heating and solid bed breakup, the melt itself generates severe unsteady fluctuations. Failure to eliminate interference signals during this phase can easily lead to misjudgments. Only when the temperature curve flattens and the average pressure and torque tend to be constant (in this embodiment, the criterion is: after the material melts, melt pressure and torque are collected within 2 minutes; when the relative fluctuation of pressure and torque is ≤5% of the baseline, steady state is determined), does the system activate a high-frequency sampling window to extract the pressure and torque pulsation amplitudes at this time as baseline data. This steady-state baseline represents the intrinsic rheological noise level of the current material combination under specific operating conditions and serves as a reference for subsequent judgment of whether abnormal fluctuations exist. In this embodiment, the typical range of the steady-state pressure pulsation baseline ΔP0 is 0.1-0.2 MPa, and the typical range of the steady-state torque pulsation baseline ΔM0 is 0.3-1.2 N·m.

[0045] If synchronous high-frequency pulsations are detected in the pressure and torque pulsation baselines during steady-state baseline acquisition, it is directly determined that the batch of mixture has a serious risk of microscopic incompatibility, and a feeding prohibition command is automatically triggered. The judgment logic here is consistent with the logic of online identification in Example 3, that is, using the synchronous pulsation of two parameters as a specific fingerprint of microscopic defects. In a controlled laboratory environment, after eliminating external interference factors such as power grid fluctuations and mechanical vibrations, if synchronous high-frequency fluctuations in pressure and torque can still be observed, it is confirmed that the fluctuation originates from the phase separation or the generation and breakage dynamics of raw rubber flocs inside the material. This means that once this material combination is put into a large production line, even relying on the alternating shear-relaxation screw structure in Example 2, it is difficult to completely eliminate the defects, or a great sacrifice of production capacity is required for online repair. Therefore, by intercepting such high-risk materials outside of production through pre-screening, not only is the expensive loss of high-voltage cable insulation layers avoided, but also the contamination of the extruder die and screw by unqualified melt is prevented, ensuring the cleanliness and operational stability of the production system from the source. For example, during a multi-batch XLPE blending verification, the rheometer detected that the amplitude of the pressure and torque synchronous pulsation exceeded the baseline by more than 4 times under the replicated 128-132℃ / 60-100 s⁻¹ operating conditions (i.e., ΔP>4ΔP0 and ΔM>4ΔM0, with typical values ​​being ΔP>0.8 MPa and ΔM>2.0 N·m). The system immediately determined that the batch of raw materials was incompatible and locked. Subsequent microscopic analysis of the cross-sections confirmed that the material did indeed contain a large number of micron-sized unmelted agglomerates, successfully avoiding a potential batch quality incident. Example

[0046] This embodiment provides an extrusion system for suppressing flocculent material in high-voltage cable insulation layers. This system solidifies the process methods described in the previous embodiments into a standardized hardware and software integrated architecture, providing a reproducible physical carrier for the precision manufacturing of high-voltage cable insulation layers. The extrusion system includes an extrusion screw assembly, a multi-parameter synchronous acquisition module, and a defect identification and grading control module.

[0047] The extrusion screw assembly includes alternating high-shear zones and stress relaxation zones for extruding polymer melts. Specifically, the extrusion screw assembly is the mechanical execution terminal of the system, and its physical structure directly determines the dispersion quality and stress state of the melt. In this embodiment, the extrusion screw assembly adopts the special screw described in Example 2, which has alternating high-shear units and melt relaxation recirculation units along the axial direction. The high-shear units construct a high-shear flow field through micron-level radial gaps, while the melt relaxation recirculation units construct stress-relieving cavities by deepening the screw grooves. It should be understood that the extrusion screw assembly includes not only the screw body but also the precisely fitted barrel, drive motor, and transmission box, which together constitute a dynamic execution unit capable of accurately responding to speed and torque adjustment commands. This alternating hardware configuration is the physical basis for realizing subsequent online repair functions, ensuring that when the control system issues parameter adjustment commands, the melt can generate the expected rheological response within the corresponding functional segment.

[0048] A multi-parameter synchronous acquisition module is used to simultaneously acquire at least two physical parameters characterizing the melt flow resistance of polymer materials during the extrusion process. Specifically, the multi-parameter synchronous acquisition module is the sensing front end of the system, and its core lies in the hardware-level implementation of "synchronization." This module typically includes a pressure sensor located at the die head, a torque sensor mounted on the drive motor shaft or reducer, and a high-speed data acquisition card connected to them. To ensure the accuracy of subsequent defect identification, the sampling actions of the pressure and torque sensors are triggered by the same clock source, or microsecond-level time alignment is achieved through a hardware interrupt mechanism, thereby ensuring that the acquired pressure and torque signals strictly correspond on the time axis. This hardware-level synchronous acquisition mechanism fundamentally eliminates the risk of data misalignment caused by communication delays or software scheduling jitter, providing a high-fidelity raw data stream for accurately extracting the synchronous pulsation characteristics of the two parameters. In addition, the multi-parameter synchronous acquisition module can also include auxiliary sensing units such as temperature sensors and flow meters to build a more comprehensive melt state monitoring network, but the synchronous acquisition of pressure and torque remains a necessary condition for identifying microscopic defects.

[0049] The defect identification and grading control module is used to identify the microscopic defect state of the polymer melt based on the synchronous pulsation characteristics of at least two physical parameters, and executes the corresponding grading control strategy in response to the microscopic defect state meeting preset risk conditions. Specifically, the defect identification and grading control module is the decision-making center of the system, usually composed of an industrial programmable logic controller, an industrial control computer, or a dedicated embedded computing unit. This module communicates with the multi-parameter synchronous acquisition module through a digital bus or a multi-channel analog interface to receive synchronously aligned pressure and torque data streams in real time. In terms of internal processing logic, the defect identification and grading control module is configured to run the signal processing algorithms and control strategies described in Examples 3 to 5, including high-frequency pulsation amplitude extraction, dual threshold comparison, online parameter adjustment calculation, and closed-loop self-calibration update. After identifying the microscopic defect state, the defect identification and grading control module sends control commands to the actuators such as the frequency converter and heating temperature controller of the extruder through the analog output interface or fieldbus, such as automatically reducing the speed setpoint or fine-tuning the die head temperature target value. Meanwhile, this module also reserves a data interface for connecting to external microscopic inspection equipment, used to receive offline slice inspection results and dynamically adjust the internally stored risk threshold parameters accordingly. It should be understood that although this embodiment describes each function as an independent module, in actual engineering implementation, the multi-parameter synchronous acquisition module and the defect discrimination and grading control module can also be integrated onto the same high-performance control board, or deployed in the form of distributed I / O, as long as a complete closed loop of signal acquisition, logic discrimination, and control output can be achieved.

[0050] Through the above system architecture, this embodiment transforms abstract process methods into concrete hardware connections and signal flows. The extrusion screw assembly provides physical-level defect suppression capabilities, the multi-parameter synchronous acquisition module provides information-level defect perception capabilities, and the defect discrimination and hierarchical control module organically couples the two through real-time closed-loop control. This integrated hardware and software design not only ensures the feasibility and stability of the technical solution but also provides standardized interface specifications for the intelligent transformation of high-voltage cable insulation extrusion production lines, enabling extrusion equipment of different specifications to acquire microscopic defect self-healing capabilities by adding or replacing corresponding modules.

[0051] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An extrusion process for suppressing flocculent material in high-voltage cable insulation layers, characterized in that, include: The polymer melt is extruded using alternating high shear zones and stress relaxation zones. During the extrusion process, at least two physical parameters characterizing the melt flow resistance of the polymer material are collected simultaneously; Based on the synchronous pulsation characteristics of the at least two physical parameters, the microscopic defect state of the polymer melt is identified; In response to the micro-defect state meeting the preset risk conditions, the corresponding hierarchical control strategy is executed.

2. The extrusion process according to claim 1, characterized in that, The extrusion process of polymer melt using alternating high-shear zones and stress-relaxation zones includes: The polymer melt is conveyed by an extrusion screw, and the extrusion screw is alternately equipped with a strong shear unit and a melt relaxation and reflux unit along the material conveying direction. The strong shear unit constitutes the strong shear zone, and the melt relaxation and reflux unit constitutes the stress relaxation zone. Wherein, the radial gap between the tip of the screw of the high shear unit and the barrel is less than a preset gap threshold, so as to break up the micro-agglomerates in the polymer melt; The groove depth of the melt relaxation and reflow unit is greater than that of the high shear unit, so as to release the internal stress of the polymer melt.

3. The extrusion process according to claim 1, characterized in that, The synchronous acquisition of at least two physical parameters characterizing the melt flow resistance of the polymer material includes: Simultaneously collect the melt pressure at the die head and the screw torque; The identification of the microscopic defect state of the polymer melt based on the synchronous pulsation characteristics of the at least two physical parameters includes: The high-frequency pulsation amplitude of the melt pressure at the die head and the high-frequency pulsation amplitude of the screw torque are extracted. When the high-frequency pulsation amplitude of the melt pressure at the die head and the high-frequency pulsation amplitude of the screw torque simultaneously exceed the preset pulsation baseline, it is determined that the polymer melt has microscopic defects.

4. The extrusion process according to claim 3, characterized in that, The step of executing a corresponding hierarchical control strategy in response to the microscopic defect state satisfying a preset risk condition includes: When the high-frequency pulsation amplitude of the melt pressure at the die head and the high-frequency pulsation amplitude of the screw torque synchronously exceed the first risk threshold but do not exceed the second risk threshold, an online parameter adjustment and repair action is performed. When the high-frequency pulsation amplitude of the melt pressure at the die head and the high-frequency pulsation amplitude of the screw torque synchronously exceed the second risk threshold, a shutdown alarm is triggered. Wherein, the second risk threshold is greater than the first risk threshold.

5. The extrusion process according to claim 4, characterized in that, The online parameter tuning and repair action includes: Automatically reduce extrusion speed or fine-tune die temperature; The method further includes: Microscopic inspection data of insulating slices are acquired periodically, and the microscopic inspection data includes at least one of floc percentage, particle size or number; The first risk threshold is automatically updated based on the microscopic detection data to offset equipment wear or process drift. The automatic updating of the first risk threshold based on the microscopic detection data includes: The proportion of flocs in the microscopic detection data within a preset time period is statistically analyzed. When the proportion of flocs is greater than the preset qualified proportion, the first risk threshold is reduced by a preset step size; When the proportion of flocs is less than or equal to the preset qualified proportion, the first risk threshold is increased by the preset step size so that the first risk threshold dynamically approaches the actual defect critical point.

6. The extrusion process according to claim 1, characterized in that, Before extruding the polymer melt using alternating high-shear zones and stress-relaxation zones, the method further includes: The temperature and shear rate parameters of the extruder were replicated using a rheometer, and the baseline of pressure and torque pulsation under steady state was collected. If the pressure and torque pulsation baselines show synchronous high-frequency pulsation, the materials are determined to be incompatible and feeding is prohibited.

7. An extrusion system for suppressing flocculent material in high-voltage cable insulation, characterized in that, include: An extrusion screw assembly, comprising alternating high-shear zones and stress-relaxation zones, is used for extruding polymer melts; A multi-parameter synchronous acquisition module is used to simultaneously acquire at least two physical parameters characterizing the melt flow resistance of the polymer material during the extrusion process; The defect identification and hierarchical control module is used to identify the microscopic defect state of the polymer material melt based on the synchronous pulsation characteristics of the at least two physical parameters, and to execute the corresponding hierarchical control strategy in response to the microscopic defect state meeting the preset risk conditions.

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