Cable insulation layer extrusion temperature control method and system

Abstract

The invention discloses a cable insulation layer extrusion temperature control method and system. According to the invention, through real-time generation of the dynamic temperature reference, the accuracy and adaptability of temperature control are improved. The temperature reference is not a fixed numerical value any more, but is dynamically adjusted by combining the characteristics of the raw materials, the real-time change of the workshop environment and the extrusion speed, so that the temperature of each area can fit the current production condition. The temperature reference is finely adjusted when the temperature of the insulating material is changed, such as the humidity change of the raw material and the fluctuation of the environment temperature, so that the problem of local overheating or insufficient temperature possibly occurring under the traditional fixed temperature setting is avoided, the matching degree of the temperature and an actual production scene is enhanced, and the insulating material is always in a proper molten state in the extrusion process; the real-time refreshing and multi-link synchronization of the dynamic reference enhance the linkage effect of temperature control and subsequent quality assurance, improve the stability of the quality of an insulating layer product, and also reduce the parameter debugging time in production.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of cable production, and particularly relates to a cable insulation layer extrusion temperature control method and system. BACKGROUND

[0002] Cable insulation layer production extrusion refers to a process of continuously heating and melting insulation materials such as plastics or rubbers through an extruder, and coating the conductor surface through a mold under the action of pressure, and forming a uniform insulation layer through cooling and setting. The process usually includes raw material pretreatment, melting extrusion, mold forming, cooling and solidification, online detection and winding, etc. By accurately controlling the extrusion temperature, screw speed, traction speed and cooling water temperature and other parameters, the uniformity of the insulation layer thickness, the smoothness of the surface, and the absence of bubbles or impurities are ensured. Advanced extrusion production lines are equipped with laser diameter measuring instruments, spark testing machines and intelligent control systems, which can realize real-time monitoring and automatic adjustment, and improve the product consistency and qualification rate. The process is widely used in power cable, communication cable and special cable manufacturing, and is a key link to ensure the electrical performance and service life of the cable.

[0003] However, in the prior art, the cable insulation layer extrusion temperature is usually set with fixed parameters, without dynamic adjustment in combination with the characteristics of the raw materials and environmental changes. The temperature reference has low matching degree with the actual production conditions, and is prone to local overheating or insufficient plasticization due to batch differences of raw materials or fluctuations of environmental temperature and humidity. Moreover, there is a lack of real-time linkage with quality detection, temperature adjustment is lagging, and the product quality stability of the insulation layer is affected. SUMMARY

[0004] The purpose of the present application is to solve the above-mentioned problems, and to provide a cable insulation layer extrusion temperature control method and system.

[0005] The technical scheme adopted by the present application is as follows: a cable insulation layer extrusion temperature control method, the method comprising the following steps:

[0006] S1: raw material pretreatment and initial matching of extrusion parameters. The insulation material particles are dried to control the moisture content to be less than or equal to 0.1%, and the feeding amount is adjusted according to the melt index MI value of the raw material batch. When the MI value is greater than 2.5 g / 10 min, the feeding amount is reduced by 5% to 8%, and the parameters of the treated raw materials are synchronized to the subsequent temperature setting module.

[0007] S2: Zone cooperative preheating control of extruder. Start the heating units of the feeding zone, compression zone, homogenization zone and head die of the extruder, and set the preheating rate of each zone according to the raw material MI value in S1: when the MI value is ≤2.5 g / 10 min, the feeding zone is heated at 5 ℃ / min, and the compression zone and the homogenization zone are synchronously heated at 8 ℃ / min; when the MI value is >2.5 g / 10 min, each zone is uniformly heated at 6 ℃ / min to avoid local overheating. During the preheating process, the temperature of each zone is collected in real time, and when the temperature difference between adjacent zones exceeds 3 ℃, the heating rate of the high-temperature zone is automatically reduced.

[0008] S3: Real-time generation of dynamic temperature reference. Based on the raw material parameters in S1, the real-time environmental temperature and humidity of the workshop, and the preset extrusion speed, the dynamic temperature reference of each zone is generated through a coupling algorithm: feeding zone reference = +0.5 x environmental temperature fluctuation value; compression zone reference = feeding zone reference + 15 + 2 x; homogenization zone reference = compression zone reference + 5 - 0.3 x MI value; head die reference = homogenization zone reference ± 3. The dynamic reference is refreshed every 30 seconds and is synchronized to the S4 monitoring system and the S5 control algorithm.

[0009] S4: Multi-dimensional process parameter fusion monitoring. An infrared melt temperature instrument is installed at the end of the homogenization zone of the extruder, K-type thermocouples are built-in each heating zone, and a pressure sensor is arranged at the outlet of the head die. The temperature data and pressure data are fused and analyzed: when the melt temperature deviates from the dynamic reference in S3 by ±5 ℃ or the pressure fluctuation exceeds ±0.3 MPa, the PID parameter adjustment instruction of S5 is triggered immediately, and the abnormal data is marked and sent to S3 for reference correction.

[0010] S5: Online setting of adaptive PID control parameters. The monitoring data of S4 is received: when the temperature fluctuation amplitude is <2 ℃, the conventional PID parameters are used; when the fluctuation amplitude is 2 ℃-5 ℃, the proportional coefficient is automatically increased to 6.5-8.0, and the integral time is shortened to 50-60 s to enhance the response speed; when the fluctuation amplitude is >5 ℃, the differential lead mode is started, and the current PID parameters are recorded to the self-learning database of S8. The adjusted parameters directly drive the power output of the heating unit to control the temperature to return to the dynamic reference in S3.

[0011] S6: Linkage regulation of cooling circulation system. The cooling water temperature and spraying flow are adjusted according to the melt temperature monitored by S4 and the extrusion speed: when Tmelt > head reference in S3 + 3 ℃, Tcold is reduced to 20±2 ℃, and Q is increased by 15%; when Tmelt < head reference in S3 - 3 ℃, Tcold is increased to 28±2 ℃, and Q is reduced by 10%; at the same time, an infrared temperature instrument is installed at the outlet of the cooling water tank to monitor the surface temperature of the insulation layer. If the temperature difference between Ttable and the environment is >15 ℃, the head reference temperature is reduced by 2 ℃ in S3 to avoid excessive cooling stress.

[0012] S7: Real-time feedback of insulation layer quality index. After extrusion, the insulation layer is detected online: a laser thickness gauge monitors the thickness deviation, a surface roughness gauge detects the surface finish, and a breakdown voltage tester samples every 50 meters. If the thickness deviation is > ± 0.05 mm and the surface is rough, it is determined that the homogenization zone temperature is abnormal, and the "homogenization zone reference -3°C" instruction is sent to S3; if the breakdown voltage is not up to standard, the "compression zone reference +2°C" instruction is sent to S3, and the detection data is stored in the S8 database.

[0013] S8: Self-learning optimization of whole-process process parameters. After daily production is completed, S1 raw material parameters, S3 dynamic reference records, S5 PID parameter adjustment records, and S7 quality detection results are retrieved, and a correlation model is established through comparative analysis: when the MI value of a batch of raw materials is 3.0 g / 10 min, if the quality pass rate is highest when the homogenization zone temperature is set to 245°C in historical data, then the homogenization zone reference generation coefficient corresponding to the MI value in S3 is automatically updated; at the same time, according to the effectiveness of the PID parameter adjustment in S5, the parameter recommendation range under different fluctuation amplitudes is optimized, and the update results are used for parameter initial matching in S1 and reference generation in S3 the next day.

[0014] In a preferred embodiment, in step S1, the insulation material particles are subjected to hot air circulation drying treatment, the drying temperature is set to 80°C, and the continuous drying time is controlled to be 4 hours, ensuring that the moisture content of the treated raw material is stably controlled within 0.1%. At the same time, the MI value of the raw material batch is measured using a melt index instrument, and when the MI value is 2.5 g / 10 min or less, the feeding screw speed is set to 45 r / min; if the MI value exceeds 2.5 g / 10 min, the feeding speed is reduced to about 42 r / min, and the feeding amount is reduced by 5% to 8% through frequency adjustment of the feeding motor. After the pretreatment is completed, the moisture content detection results, MI value data, and uniformity index of the particle screening of the raw material are recorded, and they are synchronized to the temperature setting module of the extruder control system through the production line data interaction system, providing basic input for the calculation of subsequent regional temperature parameters.

[0015] In a preferred embodiment, in step S2, the heating units of each functional zone of the extruder are started, including the strip heater of the feeding zone, the cast aluminum heating ring of the compression zone and the homogenization zone, and the embedded heating tube of the head die. The preheating rate is determined according to the MI value of the raw material transmitted in S1: when the MI value is not more than 2.5 g / 10 min, the feeding zone is heated at a rate of 5°C / min from room temperature, and the compression zone and the homogenization zone are synchronously heated at a rate of 8°C / min; if the MI value is greater than 2.5 g / 10 min, all zones uniformly use a heating rate of 6°C / min to avoid local overheating of high fluidity raw materials during the preheating stage. During the preheating process, the temperature of each zone is collected in real time by the built-in platinum resistance sensor, and the sampling interval is 2 seconds. When the measured temperature difference of any adjacent zone exceeds 3°C, the system automatically reduces the heating power of the high-temperature zone, so that the temperature rising rate of the zone is reduced by 1-2°C / min, until the temperature difference is restored to within 3°C, ensuring uniform temperature rise of each zone.

[0016] In a preferred embodiment, in step S3, the temperature reference of each zone of the extruder, including the feeding zone, the compression zone, the homogenization zone, and the head die, is formed by three layers of coupling: the input of the previous parameters, the correction of the same level parameters, and the adjustment of the subsequent feedback. The specific formula is as follows:

[0017] The calculation formula of the temperature reference model of the feeding zone is:

[0018] T1=(T basel -k1×W)+k2×ΔT env +k3×U;

[0019] In the formula:

[0020] T basel represents the basic temperature of the feeding zone; W represents the moisture content of the raw material; ΔT env represents the environmental temperature fluctuation value; U represents the uniformity of the raw material particles; k1, k2, k3 represent the coupling coefficients;

[0021] The calculation formula of the temperature reference model T2 of the compression zone is:

[0022] T2=T1+ΔT 1→2 +k4×(V / V rated )+k5×(P melt / P base );

[0023] ΔT 1→2 represents the basic temperature difference from the feeding zone to the compression zone;

[0024] V / V rated represents the ratio of the actual extrusion speed to the rated speed;

[0025] Pmelt represents the head melt pressure;

[0026] P base represents the reference melt pressure;

[0027] k4, k5 represent coupling coefficients.

[0028] The calculation formula of the temperature reference model T3 of the homogenization zone is:

[0029] T3 = T2 + ΔT 2→3 - k6 x MI + k7 x ΔH melt ;

[0030] In the formula:

[0031] ΔT 2→3 represents the base temperature difference from the compression zone to the homogenization zone;

[0032] MI represents the raw material melt index:

[0033] ΔH melt represents the melt enthalpy deviation;

[0034] k6, k7 represent coupling coefficients;

[0035] The calculation formula of the head die temperature reference model T4 is:

[0036] In the formula:

[0037] ΔT 3→4 represents the base temperature difference from the homogenization zone to the head;

[0038] ΔT qual represents the mass feedback correction value.

[0039] The T4 is dynamically corrected by the real-time mass data of step S7 to form a closed-loop control.

[0040] In a preferred embodiment, in step S4, an infrared melt temperature detector is installed at the end of the homogenizing zone of the extruder, 150 mm away from the entrance of the die head, with a sampling frequency of 1 Hz and a temperature range of 200-300°C, to ensure real-time capture of the true temperature of the melt leaving the homogenizing zone. K-type thermocouples are built into the feeding zone, compression zone, homogenizing zone, and die head, with a sampling frequency of 0.5 Hz, to monitor the bulk temperature of each heating zone. A diffusion silicon pressure sensor is installed in the flow channel at the outlet of the die head, with a range of 0-30 MPa, to monitor the pressure fluctuations during melt extrusion. All collected temperature and pressure data are transmitted to the central controller via industrial Ethernet for fusion analysis: when the melt temperature deviates from the dynamic reference temperature generated in S3 by more than ±5°C, or the pressure fluctuation amplitude exceeds ±0.3 MPa, the controller immediately sends parameter adjustment instructions to the PID adjustment module in S5, and marks the abnormal data in red in the data recording system, while feeding these abnormal information back to the dynamic reference generation module in S3 for subsequent temperature reference correction calculation.

[0041] In a preferred embodiment, in step S5, after receiving the process parameter abnormal signal sent by S4, the PID control module automatically switches the control parameters according to the temperature fluctuation amplitude. When the melt temperature fluctuation amplitude is less than 2°C, the conventional PID parameter combination is used, with a proportional coefficient of 5.0, an integral time of 80 seconds, and a differential time of 20 seconds, to ensure stable operation of the system. If the fluctuation amplitude is between 2°C and 5°C, the proportional coefficient is automatically increased to 6.5-8.0, with the specific value adjusted linearly according to the fluctuation amplitude, while the integral time is shortened to 50-60 seconds to enhance the system's rapid response capability to temperature deviation. When the fluctuation amplitude exceeds 5°C, the differential lead control mode is immediately started, with the differential time extended to 30 seconds to preferentially suppress the rapid change trend of the temperature, while the current PID parameter combination and corresponding fluctuation condition are recorded to the process database to provide data support for subsequent parameter optimization. The adjusted PID parameters are directly controlled by the analog output module to control the power output of the heating unit, with a control accuracy of ±1°C, to ensure that the temperature returns to the dynamic reference range set in S3 within 30 seconds.

[0042] In a preferred embodiment, in step S6, the cooling circulation system adopts a two-stage cooling design, with the first stage being a ring-shaped spray cooling at the outlet of the die head and the second stage being a 6-meter-long cooling water tank. The cooling parameters are adjusted in real time according to the melt temperature and extrusion speed monitored by S4: when the melt temperature is more than 3°C higher than the die head reference temperature set in S3, the cooling water temperature is adjusted to 20±2°C by the water chiller, and the spray pump frequency is increased by 15% to make the spray flow rate reach 8 m 3 / h, to enhance the initial cooling effect; if the melt temperature is lower than the die reference temperature by more than 3°C, the cooling water temperature is increased to 28±2°C, the spraying pump frequency is reduced by 10%, and the flow is reduced to 6m 3 / h, to avoid excessive cooling causing stress concentration in the insulation layer. An infrared temperature detector is installed at the outlet of the cooling water tank to monitor the surface temperature of the insulation layer. When the difference between the surface temperature and the workshop ambient temperature exceeds 15°C, a feedback signal is immediately sent to S3 to reduce the die reference temperature by 2°C, and the cooling stress is relieved by adjusting the extrusion temperature. The water level in the cooling water tank is maintained at 1.5 times the height of the insulation layer diameter to ensure uniform cooling of the insulation layer.

[0043] In a preferred embodiment, in step S7, the extruded insulation layer successively passes through an online quality detection unit. First, a laser thickness gauge is used for radial multi-point measurement at a frequency of 100 times per second, and the thickness deviation is controlled within ±0.05mm. If the deviation of 5 consecutive measurement points exceeds the upper or lower limit, it is determined to be a thickness abnormality. Subsequently, a surface roughness gauge scans the surface of the insulation layer with a contact probe, with a sampling length of 0.8mm and an evaluation length of 4mm. The surface finish needs to reach Ra≤0.8μm. If the Ra value exceeds 0.8μm with orange peel-like lines, it is determined to be a surface quality abnormality. At the same time, a breakdown voltage tester automatically takes a sample every 50 meters, tests at a voltage rise rate of 1kV / s in a 25°C environment, and the breakdown voltage needs to be ≥25kV / mm. If the test value is lower than the standard, it is determined to be an electrical performance abnormality. When thickness abnormality and surface quality abnormality occur simultaneously, an adjustment instruction of “reducing the reference temperature of the homogenization zone by 3°C” is sent to S3. If only the breakdown voltage is not up to standard, the instruction of “increasing the reference temperature of the compression zone by 2°C” is sent. All detection data are stored in real time in a quality database, which provides the basis for the self-learning optimization of S8.

[0044] In a preferred embodiment, in step S8, after the daily production is completed, the system automatically retrieves the full-process data of the day, including the raw material parameters of S1, the dynamic temperature reference record generated by S3, the PID parameter adjustment record of S5, and the quality detection results of S7. By comparative analysis, a raw material-process-quality correlation model is established. For example, when the MI value of a batch of raw materials is 3.0g / 10min, if historical data show that the homogenization zone temperature set to 245°C has the highest insulation layer qualification rate, the homogenization zone reference temperature generation coefficient corresponding to the MI value in S3 is automatically updated to make the reference temperature closer to 245°C. At the same time, according to the effectiveness of the PID parameter adjustment in S5, the parameter recommendation range under different fluctuation amplitudes is optimized. For example, when the fluctuation amplitude is 4°C, the recommended value of the proportional coefficient is adjusted from 7.0 to 7.5, improving the control accuracy. The optimized model parameters are automatically imported into the control system before the next day's production, realizing continuous iterative optimization of process parameters.

[0045] In summary, due to the adoption of the technical scheme, the application has the beneficial effects of:

[0046] 1、In the application, the real-time generation of the dynamic temperature reference improves the accuracy and adaptability of temperature control. The temperature reference is no longer a fixed value, but is dynamically adjusted in combination with the characteristics of the raw material itself, the real-time changes of the workshop environment, and the extrusion speed, so that the temperature of each region can be adapted to the current production conditions. For example, when the moisture content of the raw material changes or the ambient temperature fluctuates, the temperature reference will be fine-tuned to avoid the problems of local overheating or insufficient temperature that may occur under traditional fixed temperature settings, thereby enhancing the matching degree of temperature and actual production scene, and keeping the insulation material in a suitable molten state during the extrusion process.

[0047] 2、In the application, the real-time refreshing and multi-link synchronization of the dynamic reference enhance the linkage effect of temperature control and subsequent quality assurance. The temperature reference is updated every 30 seconds, which can respond to subtle changes in production in a timely manner, and is directly synchronized to the monitoring system and control algorithm, so that abnormal temperature can be quickly discovered and adjusted. In addition, the temperature of the die head mold is fine-tuned according to the surface quality feedback of the insulation layer, forming a closed-loop control of temperature and quality, reducing problems such as surface roughness and thickness deviation caused by inappropriate temperature, and improving the stability of the insulation layer product quality, and reducing the parameter adjustment time in production. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 The figure is a schematic diagram of the process principle of the application. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical scheme and advantages of the application more clear and explicit, the application will be further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the application and do not limit the application.

[0050] Referring to Figure 1 ,

[0051] A cable insulation layer extrusion temperature control method, comprising the following steps:

[0052] S1: raw material pretreatment and initial matching of extrusion parameters. The insulation material particles are dried to control the moisture content to be ≤0.1%, and the feeding amount is adjusted according to the melt index MI value of the raw material batch. When the MI value is >2.5 g / 10 min, the feeding amount is reduced by 5%-8%, and the processed raw material parameters (moisture content, MI value, particle uniformity) are synchronized to the subsequent temperature setting module.

[0053] S2: extruder partition coordination preheating control. Start the heating unit of the extruder feeding zone, compression zone, homogenization zone, and head die, set the preheating rate of each region according to the raw material MI value in S1: when the MI value is ≤2.5 g / 10 min, the feeding zone is heated at 5 ℃ / min, and the compression zone and the homogenization zone are synchronously heated at 8 ℃ / min; when the MI value is >2.5 g / 10 min, each region is uniformly heated at 6 ℃ / min to avoid local overheating. Real-time collection of the temperature of each region is performed during the preheating process. When the temperature difference between adjacent regions exceeds 3 ℃, the heating rate of the high-temperature zone is automatically reduced.

[0054] S3: dynamic temperature reference real-time generation. Based on the raw material parameters (moisture content, MI value), real-time environmental temperature and humidity (updated every 10 minutes), and preset extrusion speed, the dynamic temperature reference of each region is generated through a coupling algorithm: feeding zone reference = (230-0.8 x moisture content) + 0.5 x environmental temperature fluctuation value; compression zone reference = feeding zone reference + 15 + 2 x (extrusion speed / rated speed); homogenization zone reference = compression zone reference + 5-0.3 x MI value; head die reference = homogenization zone reference ± 3 (fine-tuned according to the surface quality of the insulation layer in S7 feedback), the dynamic reference is refreshed every 30 seconds, and is synchronized to S4 monitoring system and S5 control algorithm.

[0055] S4: multi-dimensional process parameter fusion monitoring. An infrared melt temperature instrument (sampling frequency 1 Hz) is installed at the end of the extruder homogenization zone, a K-type thermocouple (sampling frequency 0.5 Hz) is built-in each heating zone, and a pressure sensor (monitoring melt pressure) is arranged at the outlet of the head die. The temperature data (melt temperature, temperature of each zone) and pressure data are fused and analyzed: when the melt temperature deviates from the dynamic reference in S3 by ±5 ℃, or the pressure fluctuation exceeds ±0.3 MPa, the PID parameter adjustment instruction of S5 is triggered immediately, and the abnormal data is marked and sent to S3 for reference correction.

[0056] S5: online setting of adaptive PID control parameters. Receive the monitoring data of S4: when the temperature fluctuation amplitude is <2 ℃, use the conventional PID parameters (proportion coefficient 5.0, integral time 80 s, and differential time 20 s); when the fluctuation amplitude is 2 ℃-5 ℃, automatically increase the proportion coefficient to 6.5-8.0, and shorten the integral time to 50-60 s to enhance the response speed; when the fluctuation amplitude is >5 ℃, start the differential lead mode, and record the current PID parameters to the self-learning database of S8. The adjusted parameters directly drive the power output of the heating unit to control the temperature to return to the dynamic reference in S3.

[0057] S6: Cooling system linkage control. According to the melt temperature (Tmelt) and extrusion speed (Vextrusion) monitored in S4, adjust the cooling water temperature (Tcool) and spray flow rate (Q): when Tmelt > S3 die reference + 3°C, Tcool is reduced to 20±2°C, Q is increased by 15%; when Tmelt < S3 die reference - 3°C, Tcool is increased to 28±2°C, Q is reduced by 10%; at the same time, an infrared temperature detector is installed at the outlet of the cooling water tank to monitor the surface temperature of the insulation layer (Tsurface), if the temperature difference between Tsurface and the environment is > 15°C, feed back to S3 to reduce the die reference temperature by 2°C to avoid excessive cooling stress.

[0058] S7: Real-time feedback of insulation layer quality indicators. Online detection of the extruded insulation layer: laser thickness gauge monitors thickness deviation (requires ≤±0.05mm), surface roughness gauge detects surface finish (Ra≤0.8μm), and breakdown voltage tester samples every 50 meters (requires ≥25kV / mm). If the thickness deviation is >±0.05mm and the surface is rough, it is determined that the homogenization zone temperature is abnormal, and a "homogenization zone reference -3°C" command is sent to S3; if the breakdown voltage is not up to standard, a "compression zone reference +2°C" command is sent to S3, and the detection data is stored simultaneously in S8 database.

[0059] S8: Self-learning optimization of whole process parameters. After daily production is completed, retrieve Sl raw material parameters, S3 dynamic reference records, S5 PID parameter adjustment records, and S7 quality detection results, establish a correlation model through comparative analysis: when the MI value of a batch of raw materials is 3.0g / 10min, if the historical data show that the quality pass rate is highest when the homogenization zone temperature is set to 245°C, then automatically update the homogenization zone reference generation coefficient for the corresponding MI value in S3; at the same time, according to the effectiveness of the PID parameter adjustment in S5, optimize the parameter recommendation range under different fluctuation amplitudes, and update the results for the next day's parameter initial matching in Sl and reference generation in S3.

[0060] In step S1, the insulation material particles are subjected to hot air circulation drying treatment, the drying temperature is set to 80°C, and the continuous drying time is controlled to be within 4 hours to ensure that the moisture content of the treated raw materials is stably controlled within 0.1%. At the same time, the melt index instrument is used to measure the MI value of the raw material batch, when the MI value is 2.5g / 10min or below, the feeding screw speed is set to 45r / min; if the MI value exceeds 2.5g / 10min, the feeding speed is reduced to about 42r / min, and the feeding amount is reduced by 5% to 8% through frequency adjustment of the feeding motor. After the pretreatment is completed, the moisture content detection results, MI value data and uniformity indicators of the raw material particles after sieving (passing rate through 30 mesh sieve ≥98%) are recorded and synchronized to the temperature setting module of the extruder control system through the production line data interaction system, providing basic input for the calculation of subsequent regional temperature parameters.

[0061] In step S2, the heating units of each functional area of the extruder are started, including the strip heater of the feeding area, the cast aluminum heating ring of the compression area and the homogenization area, and the embedded heating tube of the head die. The preheating rate is determined according to the material MI value transmitted in S1: when the MI value is not more than 2.5 g / 10 min, the feeding area is heated at a rate of 5 ℃ / min from room temperature, and the compression area and the homogenization area are synchronously heated at a rate of 8 ℃ / min; if the MI value is greater than 2.5 g / 10 min, all areas uniformly use a heating rate of 6 ℃ / min to avoid local overheating of high flowability raw materials in the preheating stage. During the preheating process, the temperature of each area is collected in real time by the built-in platinum resistance sensor, and the sampling interval is 2 seconds. When the measured temperature difference of any adjacent area exceeds 3 ℃, the system automatically reduces the heating power of the high temperature area, so that the temperature rising rate of the area is reduced by 1-2 ℃ / min, until the temperature difference is restored to within 3 ℃, to ensure that the temperature of each area rises uniformly.

[0062] In step S3, the temperature reference of each area is formed by three layers of coupling of pre-sequencing parameter input, same level parameter correction and subsequent feedback adjustment, and the specific formula is as follows:

[0063] The calculation formula of the temperature reference model (T1) of the feeding area is:

[0064] T1=(T basel -k1×W)+k2×ΔT env +k3×U;

[0065] In the formula:

[0066] T basel represents the basic temperature of the feeding area (a fixed value, such as 230 ℃, which is preset according to the type of insulating material); W represents the water content of the raw material (from the pretreatment data of S1, unit %); ΔT env represents the environmental temperature fluctuation value (real-time environmental temperature-standard environmental temperature 25 ℃, unit ℃); U represents the uniformity of the raw material particles (from S1, 0-1 value, 1 for the most uniform); k1, k2, k3 represent the coupling coefficients (empirical values, such as k1=0.8, k2=0.5, k3=2):

[0067] The calculation formula of the temperature reference model T2 of the compression area is:

[0068] T2=T l +ΔT 1→2 +k4×(V / V rated )+k5×(P melt / P base );

[0069] ΔT 1→2T2 represents the base temperature difference from feeding zone to compression zone (fixed value, such as 15℃, to ensure the raw material compression plasticization);

[0070] V / V rated V represents the actual extrusion speed and the rated speed ratio (process parameter, 0.8-1.2);

[0071] P melt P represents the die melt pressure (real-time monitoring value, unit: MPa);

[0072] P base P represents the reference melt pressure (preset value, such as 15 MPa);

[0073] k4 and k5 represent coupling coefficients (for example, k4=2 and k5=3).

[0074] The calculation formula of the temperature reference model T3 of the homogenization zone is:

[0075] T3=T2+ΔT 2→3 -k6×MI+k7×ΔH melt ;

[0076] In the formula:

[0077] ΔT 2→3 T2 represents the base temperature difference from the compression zone to the homogenization zone (fixed value, such as 5℃, to ensure the melt homogenization);

[0078] MI represents the raw material melt index (from S1, unit: g / 10min, representing the flowability);

[0079] ΔH melt ΔH represents the melt enthalpy deviation (real-time melt enthalpy value minus reference enthalpy value, calculated by infrared temperature measurement, unit: kJ / kg);

[0080] k6 and k7 represent coupling coefficients (for example, k6=0.3 and k7=0.5);

[0081] The calculation formula of the die temperature reference model T4 of the die is:

[0082] In the formula:

[0083] ΔT 3→4 T2 represents the base temperature difference from the homogenization zone to the die (fixed value, ±3℃, preset according to the die structure);

[0084] ΔT qual ΔT represents the quality feedback correction value (from S7 insulation layer quality detection, unit: ℃, such as -2℃ when the surface is rough, +1℃ when the breakdown voltage is low).

[0085] T4 is dynamically corrected using real-time quality data (surface finish, thickness deviation, breakdown voltage) from step S7, forming a closed-loop control (e.g., when coke particles appear on the surface, ΔT...). qual = -3℃ to reduce the temperature of the machine head and avoid localized overheating).

[0086] In step S4, an infrared melt thermometer is installed 150mm from the die inlet at the end of the homogenization zone of the extruder. The sampling frequency is set to 1 time / second, and the temperature measurement range covers 200–300℃ to ensure real-time capture of the actual temperature of the melt as it leaves the homogenization zone. K-type thermocouples are installed in the feeding zone, compression zone, homogenization zone, and die head mold, with a sampling frequency of 0.5 times / second, to monitor the body temperature of each heating zone. A diffused silicon pressure sensor is installed in the flow channel at the die head mold outlet, with a range set to 0–30MPa, to monitor pressure fluctuations during melt extrusion. All collected temperature data (melt temperature, temperature of each zone) and pressure data are transmitted to the central controller via industrial Ethernet for fusion analysis. When the melt temperature deviates from the dynamic reference temperature generated by S3 by more than ±5℃, or the pressure fluctuation exceeds ±0.3MPa, the controller immediately sends a parameter adjustment command to the PID control module of S5 and marks the abnormal data in red in the data recording system. At the same time, these abnormal information are fed back to the dynamic reference generation module of S3 for subsequent temperature reference correction calculations.

[0087] In step S5, after receiving the process parameter anomaly signal sent in S4, the PID control module automatically switches control parameters according to the temperature fluctuation amplitude. When the detected melt temperature fluctuation amplitude is less than 2℃, a conventional PID parameter combination is used, with the proportional coefficient set to 5.0, integral time 80 seconds, and derivative time 20 seconds to ensure stable system operation. If the fluctuation amplitude is between 2℃ and 5℃, the proportional coefficient is automatically increased to the range of 6.5 to 8.0, with the specific value adjusted linearly according to the fluctuation amplitude (the larger the fluctuation, the higher the proportional coefficient), while the integral time is shortened to 50 to 60 seconds to enhance the system's rapid response capability to temperature deviations. When the fluctuation amplitude exceeds 5℃, the derivative-first control mode is immediately activated, with the derivative time extended to 30 seconds to prioritize suppressing the rapid temperature change trend. At the same time, the current PID parameter combination (proportional coefficient, integral time, derivative time) and the corresponding fluctuation situation are recorded in the process database to provide data support for subsequent parameter optimization. The adjusted PID parameters directly control the power output of the heating unit through the analog output module, achieving a control accuracy of ±1℃, ensuring that the temperature returns to the dynamic reference range set by S3 within 30 seconds.

[0088] In step S6, the cooling circulation system adopts a two-stage cooling design. The first stage is an annular spray cooling at the die head outlet, and the second stage is a 6-meter-long cooling water tank. Cooling parameters are adjusted in real time based on the melt temperature and extrusion speed monitored in S4: when the melt temperature exceeds the die head reference temperature set in S3 by more than 3°C, the cooling water temperature is adjusted to 20±2°C by a chiller, and the spray pump frequency is increased by 15%, achieving a spray flow rate of 8m³ / h. 3 / h, to enhance the initial cooling effect; if the melt temperature is more than 3°C lower than the die head reference temperature, the cooling water temperature is increased to 28±2°C, the spray pump frequency is reduced by 10%, and the flow rate is reduced to 6m³ / h. 3 To prevent excessively rapid cooling and stress concentration within the insulation layer, an infrared thermometer is installed at the cooling water tank outlet to monitor the surface temperature of the insulation layer. When the difference between the surface temperature and the ambient workshop temperature exceeds 15°C, a signal is immediately sent to S3 to lower the die head reference temperature by 2°C, thereby alleviating cooling stress by adjusting the extrusion temperature. The water level in the cooling water tank is maintained at 1.5 times the diameter of the insulation layer to ensure uniform cooling.

[0089] In step S7, the extruded insulation layer sequentially passes through the online quality inspection unit. First, a laser thickness gauge performs radial multi-point measurements at a frequency of 100 times / second, with the thickness deviation controlled within ±0.05mm. If the deviation at five consecutive measurement points exceeds the upper or lower limit, it is judged as an abnormal thickness. Subsequently, a surface roughness meter scans the surface of the insulation layer with a contact probe, sampling a length of 0.8mm and evaluating a length of 4mm. The surface finish must reach Ra≤0.8μm. If the Ra value exceeds 0.8μm and is accompanied by an orange peel-like texture, it is judged as an abnormal surface quality. Simultaneously, a breakdown voltage tester automatically extracts a sample every 50 meters and tests it at an ambient temperature of 25℃ with a voltage ramp rate of 1kV / s. The breakdown voltage must be ≥25kV / mm. If the test value is lower than the standard, it is judged as an abnormal electrical performance. When thickness and surface quality abnormalities occur simultaneously, an adjustment command is sent to S3 to "reduce the reference temperature of the homogenization zone by 3°C"; if only the breakdown voltage is not up to standard, a command is sent to "increase the reference temperature of the compression zone by 2°C". All detection data are stored in the quality database in real time, providing a basis for the self-learning optimization of S8.

[0090] In step S8, after the daily production ends, the system automatically retrieves the full-process data for that day, including the raw material parameters from S1 (moisture content, MI value, particle uniformity), the dynamic temperature baseline record generated in S3 (one data point every 30 seconds), the PID parameter adjustment record from S5 (including adjustment time, fluctuation amplitude, and parameter value), and the quality inspection results from S7 (thickness deviation, Ra value, and breakdown voltage). A raw material-process-quality correlation model is established through comparative analysis. For example, if the MI value of a certain batch of raw material is 3.0 g / 10 min, and historical data shows that the insulation layer pass rate is highest (≥99.5%) when the homogenization zone temperature is set to 245℃, the homogenization zone baseline temperature generation coefficient corresponding to the MI value in S3 is automatically updated to bring the baseline temperature closer to 245℃. Simultaneously, based on the effectiveness of the PID parameter adjustment in S5 (temperature regression time, overshoot), the recommended parameter range under different fluctuation amplitudes is optimized. For example, when the fluctuation amplitude is 4℃, the recommended value of the proportional coefficient is adjusted from 7.0 to 7.5 to improve control accuracy. The optimized model parameters are automatically imported into the control system before production the next day, enabling continuous iterative optimization of process parameters.

[0091] A cable insulation layer extrusion temperature control system is provided, which is applied to the above-mentioned cable insulation layer extrusion temperature control method.

[0092] From the above, we can conclude that:

[0093] In this invention, the accuracy and adaptability of temperature control are improved by generating a dynamic temperature reference in real time. The temperature reference is no longer a fixed value, but is dynamically adjusted based on the characteristics of the raw material, real-time changes in the workshop environment, and the extrusion speed, ensuring that the temperature in each area matches the current production conditions. For example, when the humidity of the raw material changes or the ambient temperature fluctuates, the temperature reference will be fine-tuned accordingly, avoiding the problems of localized overheating or insufficient temperature that may occur under traditional fixed temperature settings. This enhances the matching degree between temperature and the actual production scenario, ensuring that the insulating material remains in a suitable molten state throughout the extrusion process.

[0094] In this invention, the real-time updating of the dynamic benchmark and the synchronization of multiple stages enhance the linkage between temperature control and subsequent quality assurance. The temperature benchmark is updated every 30 seconds, enabling timely response to subtle changes in production and direct synchronization with the monitoring system and control algorithm, allowing abnormal temperatures to be quickly detected and adjusted. Furthermore, the die temperature is fine-tuned based on feedback from the insulation layer surface quality, forming a closed-loop control system for temperature and quality. This reduces problems such as surface roughness and thickness deviations caused by unsuitable temperatures, improves the stability of the insulation layer product quality, and reduces parameter debugging time during production.

[0095] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the term "comprising" or any other variations thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0096] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the extrusion temperature of cable insulation layer, characterized in that: The method includes the following steps: S1: Initial matching of raw material pretreatment and extrusion parameters; Dry the insulating material particles to control the moisture content ≤0.1%, and adjust the feed rate according to the melt index (MI) value of the raw material batch. When the MI value is >2.5g / 10min, the feed rate is reduced by 5% to 8%, and the parameters of the treated raw material are synchronized to the subsequent temperature setting module. S2: Extruder zoned coordinated preheating control; activates the heating units of the extruder feeding zone, compression zone, homogenization zone, and die head. Based on the raw material MI value in S1, the preheating rate of each zone is set: when MI value ≤ 2.5g / 10min, the feeding zone heats up at 5℃ / min, while the compression and homogenization zones heat up synchronously at 8℃ / min; when MI value > 2.5g / 10min, all zones heat up uniformly at 6℃ / min to avoid localized overheating. During preheating, the temperature of each zone is collected in real time. When the temperature difference between adjacent zones exceeds 3℃, the heating rate of the high-temperature zone is automatically reduced. S3: Real-time generation of dynamic temperature baselines; Based on the raw material parameters of S1, the real-time ambient temperature and humidity of the workshop, and the preset extrusion speed, dynamic temperature baselines for each area are generated through a coupling algorithm: Feeding zone baseline = +0.5 × ambient temperature fluctuation value; Compression zone baseline = Feeding zone baseline + 15 + 2 ×; Homogenization zone baseline = Compression zone baseline + 5 - 0.3 × MI value; Die head baseline = Homogenization zone baseline ± 3. The dynamic baselines are refreshed every 30 seconds and synchronized to the S4 monitoring system and the S5 control algorithm. S4: Multi-dimensional process parameter fusion monitoring; An infrared melt temperature measuring instrument is installed at the end of the homogenization zone of the extruder, a K-type thermocouple is built into each heating zone, and a pressure sensor is set at the die outlet of the die head. Temperature data and pressure data are fused and analyzed: When the melt temperature deviates from the S3 dynamic benchmark ±5℃, or the pressure fluctuation exceeds ±0.3MPa, the PID parameter adjustment command of S5 is immediately triggered, and the abnormal data is marked and sent to S3 for benchmark correction; S5: Online tuning of adaptive PID control parameters; receives monitoring data from S4, and uses conventional PID parameters when the temperature fluctuation is <2℃; when the fluctuation is 2℃~5℃, it automatically increases the proportional coefficient to 6.5~8.0 and shortens the integral time to 50~60s to enhance the response speed; when the fluctuation is >5℃, it starts the derivative-first mode and records the current PID parameters to the self-learning database of S8. The adjusted parameters directly drive the power output of the heating unit and control the temperature to return to the dynamic reference of S3. S6: Cooling circulation system linkage control; adjusts cooling water temperature and spray flow rate according to the melt temperature and extrusion speed monitored by S4: when T_melt > S3 die head reference +3℃, T_cooling decreases to 20±2℃, Q increases by 15%; when T_melt < S3 die head reference -3℃, T_cooling increases to 28±2℃, Q decreases by 10%; at the same time, an infrared thermometer is installed at the outlet of the cooling water tank to monitor the surface temperature of the insulation layer. If the temperature difference between T_meter and the ambient temperature is >15℃, it is fed back to S3 to reduce the die head reference temperature by 2℃ to avoid excessive cooling stress; S7: Real-time feedback of insulation layer quality indicators; online detection of the extruded insulation layer: laser thickness gauge monitors thickness deviation, surface roughness meter detects surface smoothness, and breakdown voltage tester samples every 50 meters; if the thickness deviation is > ±0.05mm and the surface is rough, it is determined that the homogenization zone temperature is abnormal, and the "homogenization zone reference -3℃" command is sent to S3; if the breakdown voltage does not meet the standard, the "compression zone reference +2℃" command is sent to S3, and the detection data is synchronously stored in the S8 database; S8: Self-learning optimization of process parameters throughout the entire process; after the daily production is completed, the raw material parameters of S1, the dynamic benchmark record of S3, the PID parameter adjustment record of S5, and the quality inspection results of S7 are retrieved, and a correlation model is established through comparative analysis: when the MI value of a certain batch of raw materials is 3.0g / 10min, if the quality pass rate is highest when the homogenization zone temperature is set to 245℃ in the historical data, the homogenization zone benchmark generation coefficient corresponding to the MI value in S3 is automatically updated; at the same time, based on the effectiveness of the PID parameter adjustment in S5, the recommended parameter range under different fluctuation amplitudes is optimized, and the updated results are used for the initial parameter matching of S1 and the benchmark generation of S3 the next day.

2. The method for controlling the extrusion temperature of cable insulation layer as described in claim 1, characterized in that: In step S1, the insulating material particles are subjected to hot air circulation drying. The drying temperature is set to 80℃, and the continuous drying time is controlled at 4 hours to ensure that the moisture content of the processed raw material is stably controlled within 0.1%. At the same time, the MI value of the raw material batch is measured using a melt indexer. When the MI value is 2.5g / 10min or below, the feed screw speed is set to 45r / min. If the MI value exceeds 2.5g / 10min, the feed speed is reduced to about 42r / min. The feed rate is reduced by 5% to 8% by adjusting the frequency of the feed motor. After pretreatment, the moisture content test results, MI value data and particle uniformity index after sieving of the raw materials are summarized and recorded, and synchronized to the temperature setting module of the extruder control system through the production line data interaction system, providing the basic input for the calculation of subsequent zone temperature parameters.

3. The method for controlling the extrusion temperature of cable insulation layer as described in claim 1, characterized in that: In step S2, the heating units of each functional area of ​​the extruder are activated, including the strip heater in the feeding area, the cast aluminum heating rings in the compression and homogenization areas, and the embedded heating tubes in the die head. The preheating rate is determined based on the raw material MI value transmitted in S1: when the MI value does not exceed 2.5 g / 10 min, the feeding area heats up from room temperature at a rate of 5 °C / min, while the compression and homogenization areas heat up synchronously at a rate of 8 °C / min; if the MI value is greater than 2.5 g / 10 min, all areas adopt a uniform heating rate of 6 °C / min to avoid local overheating of high-flowability raw materials during the preheating stage; during the preheating process, the temperature of each area is collected in real time by the built-in platinum resistance sensor with a sampling interval of 2 seconds. When the measured temperature difference between any adjacent areas exceeds 3 °C, the system automatically reduces the heating power of the high-temperature area, reducing the heating rate of that area by 1-2 °C / min until the temperature difference returns to within 3 °C, ensuring that the temperature of each area rises uniformly.

4. The method for controlling the extrusion temperature of cable insulation layer as described in claim 1, characterized in that: In step S3, the temperature reference for each functional area of ​​the extruder—feeding zone, compression zone, homogenization zone, and die head—is formed by a three-layer coupling of pre-parameter input, same-level parameter correction, and subsequent feedback adjustment. The specific formula is as follows: The calculation formula for the temperature reference model in the feeding zone is: T1=(T basel -k1×W)+k2×ΔT env +k3×U; In the formula: T basel Indicates the base temperature of the feeding zone; W represents the moisture content of the raw materials; ΔT env Indicates the ambient temperature fluctuation value; U represents the uniformity of raw material particles; k1, k2, and k3 represent coupling coefficients. The formula for calculating the temperature reference model T2 in the compression zone is: T2=T1+ΔT 1→2 +k4×(V / V rated )+k5×(P melt / P base ); ΔT 1→2 This indicates the basic temperature difference between the feeding zone and the compression zone; V / V rated This represents the ratio of the actual extrusion speed to the rated speed. P melt Indicates the melt pressure at the die head; P base Indicates the reference melt pressure; k4 and k5 represent coupling coefficients; The formula for calculating the temperature reference model T3 in the homogenization zone is: T3T2+ΔT 2→3 -k6×MI+k7×ΔH melt ; In the formula: ΔT 2→3 This represents the basic temperature difference between the compression zone and the homogenization zone; MI indicates the melt flow index of the raw material; ΔH melt Indicates the deviation in melt enthalpy change; k6 and k7 represent coupling coefficients; The calculation formula for the head die temperature reference model T4 is as follows: In the formula: ΔT 3→4 This represents the basic temperature difference between the homogenization zone and the die head; ΔT qua1 This indicates the quality feedback correction value; By dynamically correcting T4 using real-time quality data from step S7, a closed-loop control is formed.

5. The method for controlling the extrusion temperature of cable insulation layer as described in claim 1, characterized in that: In step S4, an infrared melt thermometer is installed 150mm from the die inlet at the end of the homogenization zone of the extruder. The sampling frequency is set to 1 time / second, and the temperature measurement range covers 200-300℃ to ensure real-time capture of the actual temperature of the melt when it leaves the homogenization zone. K-type thermocouples are installed in the feeding zone, compression zone, homogenization zone, and die head mold, with a sampling frequency of 0.5 times / second, to monitor the body temperature of each heating zone. A diffused silicon pressure sensor is installed in the flow channel at the die head mold outlet, with a range set to 0-30MPa, to monitor the pressure fluctuation during melt extrusion. All collected temperature and pressure data are transmitted to the central controller via industrial Ethernet for fusion analysis. When the melt temperature deviates from the dynamic reference temperature generated in S3 by more than ±5℃, or the pressure fluctuation exceeds ±0.3MPa, the controller immediately sends a parameter adjustment command to the PID adjustment module in S5 and marks the abnormal data in red in the data recording system. At the same time, these abnormal information are fed back to the dynamic reference generation module in S3 for subsequent temperature reference correction calculations.

6. The method for controlling the extrusion temperature of cable insulation layer as described in claim 1, characterized in that: In step S5, after receiving the abnormal process parameter signal sent by S4, the PID control module automatically switches control parameters according to the temperature fluctuation amplitude. When the detected melt temperature fluctuation amplitude is less than 2℃, a conventional PID parameter combination is used, with the proportional coefficient set to 5.0, integral time 80 seconds, and derivative time 20 seconds to ensure stable system operation. If the fluctuation amplitude is between 2℃ and 5℃, the proportional coefficient is automatically increased to the range of 6.5 to 8.0, with the specific value adjusted linearly according to the fluctuation amplitude. At the same time, the integral time is shortened to 50 to 60 seconds to enhance the system's rapid response capability to temperature deviations. When the fluctuation amplitude exceeds 5℃, the derivative-first control mode is immediately activated, and the derivative time is extended to 30 seconds to prioritize suppressing the rapid temperature change trend. Simultaneously, the current PID parameter combination and the corresponding fluctuation situation are recorded in the process database to provide data support for subsequent parameter optimization. The adjusted PID parameters directly control the power output of the heating unit through the analog output module, achieving a control accuracy of ±1℃, ensuring that the temperature returns to the dynamic reference range set by S3 within 30 seconds.

7. The method for controlling the extrusion temperature of cable insulation layer as described in claim 1, characterized in that: In step S6, the cooling circulation system adopts a two-stage cooling design. The first stage is an annular spray cooling at the die head outlet, and the second stage is a 6-meter-long cooling water tank. Cooling parameters are adjusted in real time based on the melt temperature and extrusion speed monitored in S4: when the melt temperature is more than 3°C higher than the die head reference temperature set in S3, the cooling water temperature is adjusted to 20±2°C by a chiller, and the spray pump frequency is increased by 15%, so that the spray flow rate reaches 8m³ / h. 3 / h, to enhance the initial cooling effect; if the melt temperature is more than 3°C lower than the die head reference temperature, the cooling water temperature is increased to 28±2°C, the spray pump frequency is reduced by 10%, and the flow rate is reduced to 6m³ / h. 3 / h, to avoid excessive cooling and stress concentration inside the insulation layer; an infrared thermometer is installed at the outlet of the cooling water tank to monitor the surface temperature of the insulation layer. When the difference between the surface temperature and the ambient temperature of the workshop exceeds 15℃, a signal is immediately sent to S3 to reduce the reference temperature of the die head by 2℃ and alleviate the cooling stress by adjusting the extrusion temperature; the water level in the cooling water tank is maintained at 1.5 times the diameter of the insulation layer to ensure uniform cooling of the insulation layer.

8. The method for controlling the extrusion temperature of a cable insulation layer as described in claim 1, characterized in that: In step S7, the extruded insulation layer sequentially passes through an online quality inspection unit. First, a laser thickness gauge performs radial multi-point measurements at a frequency of 100 times / second, with the thickness deviation controlled within ±0.05mm. If the deviation at five consecutive measurement points exceeds the upper or lower limit, it is determined to be an abnormal thickness. Subsequently, a surface roughness meter scans the surface of the insulation layer with a contact probe, sampling a length of 0.8mm and evaluating a length of 4mm. The surface finish must reach Ra≤0.8μm. If the Ra value exceeds 0.8μm and is accompanied by an orange peel-like texture, it is determined to be an abnormal surface quality. Normally, the breakdown voltage tester automatically extracts a sample every 50 meters and tests it at a voltage increase rate of 1kV / s under an ambient temperature of 25℃. The breakdown voltage must be ≥25kV / mm. If the test value is lower than the standard, it is judged as an electrical performance abnormality. When thickness abnormality and surface quality abnormality occur simultaneously, an adjustment command of "reducing the reference temperature of the homogenization zone by 3℃" is sent to S3. If only the breakdown voltage is not up to standard, a command of "increasing the reference temperature of the compression zone by 2℃" is sent. All test data are stored in the quality database in real time, providing a basis for the self-learning optimization of S8.

9. The method for controlling the extrusion temperature of a cable insulation layer as described in claim 1, characterized in that: In step S8, after the daily production is completed, the system automatically retrieves the full process data for that day, including the raw material parameters of S1, the dynamic temperature baseline record generated in S3, the PID parameter adjustment record in S5, and the quality inspection results in S7.

10. A cable insulation layer extrusion temperature control system, characterized in that: The system is applied to a cable insulation layer extrusion temperature control method as described in any one of claims 1 to 9.

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