Intelligent deviation rectification control method and system for cable sheath extrusion

Abstract

The invention provides an intelligent deviation rectification control method and system for cable sheath extrusion, and relates to the technical field of cable sheaths, and the method comprises the steps: reading a core body monitoring signal of a cable core body in a cable sheath extrusion control process; activating an infrared thermal image sensor to execute temperature field distribution acquisition; sending the core body monitoring signal and the time sequence temperature field data set to a feature extraction layer; inputting the real-time offset vector characteristic, the circumferential temperature uniformity characteristic and the longitudinal cooling gradient characteristic of the core body into the factorization eccentric model, and executing eccentric decomposition of the cable protection sleeve; and performing multi-scale discrimination by using a sliding window, performing correction based on transient deviation and trend deviation, and configuring intelligent correction parameters by using a correction result to perform correction processing. According to the method and the device, the problem that in the prior art, due to dependence on single dimension and lack of deep analysis on causes, the deviation correction control precision is insufficient is solved, and the deviation correction control precision is improved through multi-sensor fusion and factorization of the eccentric model.

Description

Technical Field

[0001] This application relates to the field of cable sheath technology, and in particular to an intelligent correction control method and system for cable sheath extrusion. Background Technology

[0002] In the extrusion production of cable sheaths, deviation control is a core element in ensuring product quality. Currently, commonly used deviation control methods rely primarily on monitoring a single geometric dimension, such as radial thickness or shape, to determine the production quality of the cable sheath. However, this method only focuses on the geometric dimensions of the cable sheath and cannot simultaneously perceive multi-physics coupling parameters such as temperature field distribution, material cooling gradient, and core dynamic alignment during production. Because detection lags significantly behind the hot extrusion stage and lacks multi-dimensional in-depth analysis of the causes of deviation, accurate feedforward control is difficult to achieve, easily leading to adjustment oscillations or overcompensation. In actual production, due to the complexity of the causes of deviation, a single control method cannot accurately identify and promptly respond to various dynamic changes in deviation, resulting in insufficient deviation control accuracy and delayed response, thus affecting the production quality and stability of the cable sheath.

[0003] In summary, existing technologies suffer from technical problems such as insufficient accuracy and delayed response due to reliance on detection in a single geometric dimension and a lack of in-depth analysis of the causes of eccentricity, which further affect the production quality of cable sheaths. Summary of the Invention

[0004] The purpose of this application is to provide an intelligent correction control method and system for cable sheath extrusion, in order to solve the technical problems in the prior art, which are due to the reliance on detection of a single geometric dimension and the lack of in-depth analysis of the causes of eccentricity, resulting in insufficient correction control accuracy and response lag, which further affects the production quality of cable sheaths.

[0005] In view of the above problems, this application provides an intelligent correction control method and system for cable sheath extrusion.

[0006] In a first aspect, the application provides an intelligent deviation correction control method for cable sheath extrusion, which is implemented by an intelligent deviation correction control system for cable sheath extrusion. In the process of cable sheath extrusion control, the electromagnetic sensor array is activated synchronously, which is arranged circumferentially along the cable sheath extrusion position, and the core monitoring signal of the cable core is read according to the electromagnetic sensor array. The infrared thermal imaging sensor is activated to collect the temperature field distribution of the cable sheath surface, and the time-series temperature field dataset is established. The core monitoring signal and the time-series temperature field dataset are sent to the feature extraction layer to establish the core real-time offset vector feature, the circumferential temperature uniformity feature and the longitudinal cooling gradient feature. The core real-time offset vector feature, the circumferential temperature uniformity feature and the longitudinal cooling gradient feature are input into the factorized eccentricity model to perform eccentricity decomposition of the cable sheath, and the eccentricity decomposition result is established. The multi-scale discrimination of the eccentricity decomposition result is performed by using the sliding window, the eccentricity decomposition result is corrected based on the transient deviation and the trend deviation, the intelligent deviation correction parameters are configured by using the correction result, and the deviation correction processing is performed.

[0007] Optionally, cable data including cable outer diameter data, cable inner diameter data and cable die structure is acquired. After the cable data is sent to the geometric factor transmission layer in the factorized eccentricity model, the geometric approximate transmission fitting of the core real-time offset vector feature is performed by using the geometric factor transmission layer, and the geometric approximate transmission fitting result is established. The circumferential temperature uniformity feature is sent to the flow transmission layer in the factorized eccentricity model to perform linear mapping analysis of temperature-local flow rate difference-thickness difference, and the flow transmission fitting result is established. The longitudinal cooling gradient feature is sent to the cooling factor transmission layer in the factorized eccentricity model to perform shrinkage analysis under the influence of local cooling rate, and the cooling shrinkage fitting result is established. The geometric approximate transmission fitting result, the flow transmission fitting result and the cooling shrinkage fitting result are synchronously sent to the decomposition authentication layer to perform decomposition authentication fitting, and the eccentricity decomposition result is established.

[0008] Optionally, the geometric approximate transmission fitting result, the flow transmission fitting result and the cooling shrinkage fitting result are predicted eccentricity synthesis by using a preset synthesis weight, and the initial predicted eccentricity synthesis result is established. After the measured eccentricity value is read, residual error calculation is performed by using the initial predicted eccentricity synthesis result and the measured eccentricity value, and the residual error calculation result is established. The correlation factor of the residual error calculation result and each fitting component is used, and the adaptive preset synthesis weight adjustment iteration is performed by using the correlation factor and the residual error calculation result as weight adjustment indexes. The decomposition optimization is completed according to the adjustment iteration result, and the eccentricity decomposition result is established.

[0009] Optionally, two-stage sliding windows are established for the eccentric decomposition result, the two-stage sliding windows including a short window mapped with transient fluctuation and a long window mapped with trend deviation; after statistical features are calculated respectively by using the two-stage sliding windows, transient deviation and trend deviation discrimination are performed, and transient correction component and trend correction component are established; the eccentric decomposition result is corrected by using the transient correction component and the trend correction component.

[0010] Optionally, the correction result is analyzed to obtain a geometric correction component, a flow correction component and a cooling correction component; after gain distribution is adaptively performed according to transient deviation and trend deviation in the correction result, independent control optimization of multiple actuators is performed based on the geometric correction component, the flow correction component and the cooling correction component, and independent response strategy is established; intelligent correction parameters are configured according to the independent response strategy, and correction processing is performed.

[0011] Optionally, the independent response strategy is taken as an initial strategy, mechanism coordination analysis of multiple actuators is performed, and actuator coordination compensation is established; after the initial strategy is updated by using the actuator coordination compensation, a coordination response strategy is established; the coordination response strategy is taken as an intelligent correction parameter, and correction processing is performed.

[0012] Optionally, independent correction response accuracy targets, energy consumption targets and correction response time targets are established, and a multi-target balance function is generated; independent control optimization is performed by using the multi-target balance function, and the independent response strategy is established.

[0013] Optionally, deviation early warning identification is performed on the correction result, and a deviation early warning signal is established; the deviation early warning signal is executed according to a corresponding early warning strategy to report early warning, and after receiving early warning adjustment feedback, intelligent correction parameters are configured based on the correction result, and correction processing is performed.

[0014] Optionally, a node deviation database is established according to the correction result, and node attention is established by using the node deviation database; attention control management of cable sheath extrusion is performed through the node attention.

[0015] In a second aspect, the present application also provides an intelligent deviation correction control system for cable sheath extrusion, for executing the intelligent deviation correction control method for cable sheath extrusion as described in the first aspect, wherein the intelligent deviation correction control system for cable sheath extrusion comprises: a signal acquisition module, configured to activate an electromagnetic sensor array synchronously in the process of cable sheath extrusion control, the electromagnetic sensor array is arranged circumferentially along the cable sheath extrusion position, and a core monitoring signal of a cable core is read according to the electromagnetic sensor array; a temperature field acquisition module, configured to activate an infrared thermal imaging sensor to perform temperature field distribution acquisition of a cable sheath surface, and establish a time-series temperature field dataset; a feature extraction module, configured to send the core monitoring signal and the time-series temperature field dataset to a feature extraction layer, establish a core real-time offset vector feature, a circumferential temperature uniformity feature, and a longitudinal cooling gradient feature; an eccentric decomposition module, configured to input the core real-time offset vector feature, the circumferential temperature uniformity feature, and the longitudinal cooling gradient feature into a factorized eccentric model, perform eccentric decomposition of the cable sheath, and establish an eccentric decomposition result; and a result correction module, configured to perform multi-scale discrimination of the eccentric decomposition result by using a sliding window, correct the eccentric decomposition result based on transient deviation and trend deviation, configure intelligent deviation correction parameters by using the correction result, and perform deviation correction processing.

[0016] The one or more technical solutions provided in the present application have at least the following beneficial effects: by activating an electromagnetic sensor array synchronously in the process of cable sheath extrusion control, the electromagnetic sensor array is arranged circumferentially along the cable sheath extrusion position, a core monitoring signal of a cable core is read according to the electromagnetic sensor array; an infrared thermal imaging sensor is activated to perform temperature field distribution acquisition of a cable sheath surface, and a time-series temperature field dataset is established; the core monitoring signal and the time-series temperature field dataset are sent to a feature extraction layer, a core real-time offset vector feature, a circumferential temperature uniformity feature, and a longitudinal cooling gradient feature are established; the core real-time offset vector feature, the circumferential temperature uniformity feature, and the longitudinal cooling gradient feature are input into a factorized eccentric model, eccentric decomposition of the cable sheath is performed, and an eccentric decomposition result is established; multi-scale discrimination of the eccentric decomposition result is performed by using a sliding window, the eccentric decomposition result is corrected based on transient deviation and trend deviation, intelligent deviation correction parameters are configured by using the correction result, and deviation correction processing is performed. That is, by using the electromagnetic sensor array and the infrared thermal imaging sensor, the cable core and the temperature field distribution are monitored in real time, the core real-time offset vector feature, the circumferential temperature uniformity feature, and the longitudinal cooling gradient feature are extracted, and are input into the factorized eccentric model for eccentric decomposition, the eccentric decomposition result is discriminated by using the sliding window, and is corrected in combination with the transient deviation and the trend deviation, thereby improving the accuracy of the deviation correction control, and improving the production efficiency and the product quality.

[0017] The above description is only a summary of the technical solutions of the present application. In order to enable the technical means of the present application to be more clearly understood, and to be implemented according to the content of the description, and in order to enable the above and other purposes, characteristics and advantages of the present application to be more apparent and easy to understand, the following specific embodiments of the present application are described. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only exemplary, and other drawings can also be obtained according to the provided drawings without creative labor for those skilled in the art.

[0019] Figure 1 Flowchart of the intelligent deviation correction control method for cable sheath extrusion of the present application.

[0020] Figure 2 Structure diagram of the intelligent deviation correction control system for cable sheath extrusion of the present application.

[0021] Explanation of reference signs: signal acquisition module 11, temperature field acquisition module 12, feature extraction module 13, eccentricity decomposition module 14, result correction module 15. DETAILED DESCRIPTION

[0022] The present application provides an intelligent deviation correction control method and system for cable sheath extrusion, which solves the technical problem that the production quality of cable sheath is affected due to the lack of deep analysis of the causes of eccentricity and the dependence on single geometric dimension detection, resulting in insufficient correction control accuracy and response lag. Through the electromagnetic sensor array and infrared thermal imaging sensor, the cable core and temperature field distribution are monitored in real time, the real-time offset vector features of the core, the circumferential temperature uniformity features and the longitudinal cooling gradient features are extracted, and are input into the factorization eccentricity model for eccentricity decomposition. The eccentricity decomposition results are discriminated by a sliding window, and are corrected in combination with transient deviation and trend deviation, thereby improving the accuracy of the deviation correction control, and improving the production efficiency and product quality.

[0023] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. It should be understood that this application is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0024] Example 1, please refer to the appendix. Figure 1 This application provides an intelligent deviation correction control method for cable sheath extrusion, wherein the intelligent deviation correction control method for cable sheath extrusion is executed by an intelligent deviation correction control system for cable sheath extrusion, and the intelligent deviation correction control method for cable sheath extrusion specifically includes the following steps: During the extrusion control of the cable sheath, an electromagnetic sensor array is activated synchronously. The electromagnetic sensor array is arranged circumferentially along the extrusion position of the cable sheath, and the core monitoring signal of the cable core is read according to the electromagnetic sensor array.

[0025] Specifically, during the control process of cable sheath extrusion, an electromagnetic sensor array is simultaneously activated to monitor the displacement and eccentricity of the cable core in real time. During cable extrusion, core positional misalignment can lead to sheath eccentricity, affecting the quality of the final product. To effectively monitor this misalignment, the electromagnetic sensor array is circumferentially positioned around the cable sheath extrusion location; these sensors surround the cable, sensing changes in the cable core in real time. Whether it's radial or axial displacement, these electromagnetic signals can accurately capture it. The electromagnetic sensor array is a network of multiple electromagnetic sensors that uses the principle of electromagnetic wave induction to detect the position, movement, or other electromagnetic characteristics of the cable core, monitoring changes in its position to identify whether core misalignment has occurred.

[0026] The circumferential arrangement is to surround the electromagnetic sensor array around the extrusion position of the cable sheath, forming a complete annular monitoring array, ensuring that monitoring can be carried out in all directions of the cable. The electromagnetic sensor array is arranged around the extrusion position of the cable sheath, usually forming a circular array structure, which can collect data in multiple directions at the same time. For example, if the cable core deviates during the extrusion process, the sensor array can sense the displacement of the core relative to the sheath and generate a corresponding core monitoring signal, reflecting the real-time deviation data of the core. By frequently reading these signals, the sensor array can monitor the position change of the cable core in real time and determine whether eccentricity has occurred. By synchronously activating the electromagnetic sensor array, real-time monitoring of the cable core during the extrusion process is achieved, improving the control accuracy of the cable sheath extrusion process.

[0027] The infrared thermal imaging sensor is activated to collect the temperature field distribution of the cable sheath surface, and a time-series temperature field data set is established.

[0028] Specifically, the infrared thermal imaging sensor is a sensor that detects the temperature of an object by infrared radiation. It captures the infrared radiation emitted by the surface of an object to draw a temperature distribution image of the object, and is commonly used to detect areas with uneven temperatures. Activating the infrared thermal imaging sensor is to collect the temperature field distribution of the cable sheath surface in real time, so as to fully understand the temperature changes during the cooling process. Through the infrared thermal imaging sensor, a temperature distribution image can be formed on the surface of the cable sheath, and the temperature state of different areas can be displayed in real time. The real-time collected data is organized into a time-series temperature field data set, i.e. a data set is generated according to the temperature data at different time points to record the temperature change trend of the cable sheath surface during the extrusion process. For example, at the beginning of the extrusion process, the sheath may be at a high temperature, such as 200°C, and as the cooling process progresses, the temperature will gradually decrease. By recording the temperature change at each time point, a complete temperature evolution curve is obtained, which not only allows analysis of whether there is temperature unevenness on the surface of the sheath, but also reflects the working efficiency and uniformity of the cooling system. The time-series temperature field data set is a collection of cable sheath surface temperature data collected in chronological order. At each time point, the temperature data recorded by the thermal imaging sensor is organized into a continuous sequence, which is usually used to analyze temperature change trends and dynamic factors affecting temperature distribution. Through real-time monitoring by the infrared thermal imaging sensor, accurate temperature information of each point on the surface of the cable sheath is obtained, and the temperature distribution is fully understood, avoiding temperature unevenness.

[0029] The core monitoring signal and the time-series temperature field data set are sent to the feature extraction layer to establish a core real-time deviation vector feature, a circumferential temperature uniformity feature, and a longitudinal cooling gradient feature.

[0030] Specifically, the core monitoring signals and the time-series temperature field dataset are sent to the feature extraction layer to extract representative features. The feature extraction layer is responsible for analyzing the core monitoring signals and the temperature field dataset to extract important features related to cable eccentricity, temperature uniformity, and cooling efficiency. The electromagnetic sensor array provides real-time core monitoring signals that reflect the position changes of the core during the production process. Through the feature extraction layer, the core monitoring signals are converted into a vector feature representing the core offset, i.e., the core real-time offset vector feature, which describes the offset of the core in different directions. The core real-time offset vector feature is a feature vector extracted from the core monitoring signals that describes the core offset, reflecting the radial or longitudinal offset of the cable core. For example, if the core is radially offset by 1 mm and longitudinally offset by 0.5 mm, the feature vector is (1 mm, 0.5 mm).

[0031] The time-series temperature field dataset records the temperature data of each point on the surface of the cable sheath. By analyzing the time-series temperature field dataset, the feature extraction layer can calculate the circumferential temperature uniformity, i.e., whether the temperature of the cable sheath is uniform in the circumferential direction. The circumferential temperature uniformity feature is a feature extracted from the analysis of the time-series temperature field dataset that reflects the uniformity of the temperature distribution of the cable sheath in the circumferential direction. For example, assume that the temperature of a certain region of the cable sheath is 150°C, while the temperature on the other side is 130°C. This temperature difference is detected and converted into a feature value, reflecting the temperature uniformity problem in that region.

[0032] In addition to the circumferential temperature, the longitudinal gradient of the cooling process, i.e., the temperature change along the extrusion direction, is also very important for the quality of the cable sheath. By analyzing the time-series temperature field dataset, the feature extraction layer can calculate the longitudinal gradient of the temperature during the cooling process. If the temperature of the cable sheath changes too drastically from the extrusion head to the cooling zone, it may cause uneven cooling, which in turn affects the quality of the sheath. The longitudinal cooling gradient feature is a feature that describes the temperature change gradient of the cable sheath in the longitudinal direction. The cooling gradient affects the quality of the cable sheath, and a too high or too low cooling gradient may cause the sheath to be unstable or uneven. For example, if the temperature of a certain region suddenly drops from 200°C to 120°C during the cooling process, the feature extraction layer will convert this temperature change into a cooling gradient feature, indicating that the cooling efficiency of that region is uneven.

[0033] By extracting the core real-time offset vector feature, the circumferential temperature uniformity feature, and the longitudinal cooling gradient feature, the eccentricity problem and the temperature non-uniformity problem of the cable sheath during the extrusion process can be accurately identified, avoiding the blind adjustment caused by the traditional method of relying on geometric size detection, thereby improving the overall production quality.

[0034] The core real-time offset vector feature, the circumferential temperature uniformity feature, and the longitudinal cooling gradient feature are input into a factorization eccentricity model to perform eccentric decomposition of the cable jacket, and an eccentric decomposition result is established.

[0035] Further, the application further includes the following steps: obtaining cable data including cable outer diameter data, cable inner diameter data, and cable die structure; after the cable data is sent to a geometric factor transfer layer in the factorization eccentricity model, the geometric factor transfer layer is used to perform geometric approximation transfer fitting on the core real-time offset vector feature, and a geometric approximation transfer fitting result is established; the circumferential temperature uniformity feature is sent to a flow transfer layer in the factorization eccentricity model, and linear mapping analysis of temperature-local flow rate difference-thickness difference is performed to establish a flow transfer fitting result; the longitudinal cooling gradient feature is sent to a cooling factor transfer layer in the factorization eccentricity model, and shrinkage analysis under the influence of local cooling rate is performed to establish a cooling shrinkage fitting result; the geometric approximation transfer fitting result, the flow transfer fitting result, and the cooling shrinkage fitting result are synchronized to a decomposition authentication layer to perform decomposition authentication fitting, and an eccentric decomposition result is established.

[0036] Further, the application further includes the following steps: performing predicted eccentricity synthesis on the geometric approximation transfer fitting result, the flow transfer fitting result, and the cooling shrinkage fitting result by a preset synthesis weight to establish an initial predicted eccentricity synthesis result; after a measured eccentricity value is read, residual error calculation is performed on the initial predicted eccentricity synthesis result and the measured eccentricity value to establish a residual error calculation result; the correlation factor of each fitting component is used, and the correlation factor and the residual error calculation result are used as weight adjustment indicators to perform adaptive preset synthesis weight adjustment iteration; decomposition optimization is completed according to the adjustment iteration result, and an eccentric decomposition result is established.

[0037] Specifically, the cable data is obtained, including cable outer diameter data, cable inner diameter data, and cable die structure, which reflects the physical size of the cable and the design of the extrusion die. The cable outer diameter data is the diameter information of the outside of the cable, which is used to determine the external size of the cable; the cable inner diameter data is the diameter information of the inside of the cable, which usually refers to the diameter of the core of the cable. It is closely related to the shape, thickness, and eccentricity of the jacket; the cable die structure is the design structure of the mold, which usually refers to the shape design of the cable jacket extruded from the mold during the extrusion molding process, including the geometric shape and size of the die, which directly affects the shape and uniformity of the jacket.

[0038] Cable data is fed into the geometric factor transfer layer in the factorized eccentricity model, which combines the cable's geometric data with other factors to analyze how changes in the geometry affect the eccentricity of the cable jacket. In the factorized eccentricity model, the geometric factor transfer layer is used to handle the effects of cable geometry on eccentricity, combining the cable's geometric data with the core's real-time offset characteristics for fitting analysis. In the geometric factor transfer layer, the cable's geometric data is combined with the core's real-time offset vector characteristics for analysis through geometric fitting. By analyzing the relationship between the cable's geometric parameters and the core's offset characteristics, the degree of cable jacket eccentricity can be estimated. For example, assuming a cable outer diameter of 10 mm and an inner diameter of 8 mm, the die structure is designed as a circle, but during actual production, the core has shifted by 1 mm, resulting in uneven thickness of the jacket. Through fitting analysis, it may be concluded that the jacket's eccentricity is 0.2 mm. The geometric approximation transfer fitting results reveal the effects of core offset and die structure on the jacket's eccentricity under the current cable geometry.

[0039] The circumferential temperature uniformity feature is sent to the flow transfer layer in the factorized eccentricity model to analyze how the temperature field interacts with the flow characteristics of the cable. When the cable material flows in the die, changes in flow rate can affect the formation of the cable. The relationship between temperature and flow rate is very important because at higher temperature locations, flow can be slower, while at lower temperature locations, flow can be faster, and this difference directly affects the uniformity of the jacket thickness. In the factorized eccentricity model, the flow transfer layer is mainly used to analyze the flow characteristics during the cable extrusion process, especially the correlation between local flow rate differences and temperature fields when the cable material flows in the extrusion die. Through this level of analysis, the effects of temperature field non-uniformity and flow rate non-uniformity on the cable jacket eccentricity can be understood.

[0040] In the flow transfer layer, the relationship between temperature field, local flow rate difference, and jacket thickness difference is modeled through linear mapping analysis to analyze how temperature differences at different locations affect flow rate changes, which in turn affect the uniformity of the cable jacket thickness. For example, in areas with higher temperatures, the flow rate can be lower, resulting in thinner cable jacket thickness in that area, while in areas with lower temperatures, the flow rate is higher, resulting in thicker jacket thickness in that area. Temperature differences between different locations on the cable surface due to temperature field non-uniformity can cause the cable jacket to have uneven thickness; local flow rate differences are the differences in flow speed of the cable material at different locations, which are usually related to factors such as die design and flow channel resistance, and flow rate differences can cause uneven formation of the cable jacket, leading to eccentricity; thickness differences are the differences in thickness of the cable jacket at different locations, which are usually caused by non-uniformity of the temperature field and flow rate field, and the presence of thickness differences directly affects the quality of the cable.

[0041] The flow transfer fit is obtained by linear mapping analysis and describes the specific effects of temperature and flow rate differences on the cable jacket eccentricity. The flow transfer fit is obtained by linear mapping analysis of temperature, flow rate, and thickness differences and describes the flow transfer process eccentricity fit that quantifies the specific effects of non-uniformity on cable eccentricity during the flow process. For example, using the flow transfer layer analysis method, the temperature difference is linearly mapped with the flow rate difference. Assuming that the flow rate is 1.0 m / s in the area with a higher temperature and 1.3 m / s in the area with a lower temperature, the flow rate difference is 0.3 m / s, and it is found that the temperature difference increases by 10°C, and the flow rate difference will cause the cable jacket thickness difference to increase by 0.05 mm. Due to a temperature difference of 20°C, the jacket thickness difference is 0.1 mm.

[0042] The longitudinal cooling gradient feature is input into the cooling factor transfer layer in the factorization eccentricity model, which is used to analyze the effects of different cooling rates on the cable jacket forming quality during the cooling process. Temperature changes during the cooling process affect the shrinkage behavior of the material, so a mathematical relationship model between the cooling rate and the shrinkage amount can be established through the cooling factor transfer layer. In the cooling factor transfer layer, the shrinkage amount under the influence of the local cooling rate is analyzed. Assuming that the surface temperature of the cable jacket decreases from 230°C to 150°C during the cooling process, the cooling rate is 5°C per second. Under this cooling rate, the cable jacket may shrink by 2%. In contrast, a 1% shrinkage difference occurs in areas with a slower cooling rate. These differences will cause the thickness of the cable jacket to change, thereby affecting the degree of cable eccentricity. Through the analysis between the local cooling rate and the shrinkage amount, the cooling shrinkage fit is established to describe the relationship between temperature, cooling rate, and shrinkage amount during the cooling process. For example, through multiple tests, it is assumed that the cooling rate increases by 1°C / s, and the shrinkage amount of the cable jacket increases by 0.1%. The cooling shrinkage fit is obtained by analyzing the shrinkage amount, combined with factors such as cooling rate and cooling time, and finally the data fit result is obtained, which describes the relationship between shrinkage and eccentricity during the cooling process.

[0043] The geometric approximation transmission fitting result, the flow transmission fitting result, and the cooling shrinkage fitting result are synchronized to the decomposition authentication layer to perform decomposition authentication fitting. Through the processing of the decomposition authentication layer, the factorized eccentricity model can verify each factor to ensure the accuracy of the predicted results of the eccentricity. By presetting the synthesis weight, the synthesis of each fitting result is performed to generate an initial predicted eccentricity synthesis result, which is a comprehensive prediction based on factors such as geometry, flow, and cooling. The decomposition authentication layer is part of the factorized eccentricity model and is used to perform the synthesis and verification of all fitting results to ensure the accuracy and reliability of the eccentricity decomposition results. The preset synthesis weight gives different weight values to different fitting results, and the preset of the weight value is usually based on experience or experimental data to adjust the importance of these fitting results in the final synthesis. By presetting the synthesis weight, different weights are given to the geometric approximation transmission fitting result, the flow transmission fitting result, and the cooling shrinkage fitting result, and a preliminary prediction of the eccentricity is made based on these weighted results to obtain the initial predicted eccentricity synthesis result. The weight is usually set according to experience or experimental data. For example, the weight of the geometric approximation transmission fitting result is 0.5, the weight of the flow transmission fitting result is 0.3, and the weight of the cooling shrinkage fitting result is 0.2.

[0044] The actual measured eccentricity value of the cable sheath is obtained by actual measurement. The initial predicted eccentricity synthesis result is compared with the actual measured eccentricity value to calculate the residual error, i.e., the difference between the predicted value and the actual measured value. For example, if the initial predicted eccentricity synthesis result is 0.8 mm and the actual measured eccentricity value is 1.0 mm, then the residual error is 0.2 mm. The correlation factor of each fitting component calculated from the calculated residual error is used as a weight adjustment index to perform adaptive preset synthesis weight adjustment iteration. For example, in some cases, the geometric approximation transmission fitting result may have a greater impact on the eccentricity, while in other cases, the cooling shrinkage fitting result has a more significant impact. Adaptive preset synthesis weight adjustment iteration refers to adjusting the weight of each fitting result after calculating the residual error to optimize iteratively, and by adjusting the weight adaptively, the influence of each fitting result is more accurately reflected in the final eccentricity prediction, achieving the purpose of optimizing the model. After multiple rounds of adaptive weight adjustment iteration, the optimization of the eccentricity decomposition is completed, and the final eccentricity decomposition result is obtained, which accurately reflects the actual eccentricity of the cable sheath and its causes. For example, if the influence of the geometric factor is 0.2 mm, the influence of the flow factor is 0.1 mm, and the influence of the cooling factor is 0.15 mm, then through the optimization calculation of the decomposition authentication layer, the final eccentricity decomposition result is 0.25 mm. Through comprehensive analysis of multiple dimensions, the eccentricity of the cable sheath is accurately predicted, and the extrusion process is optimized.

[0045] The multi-scale discrimination of eccentricity decomposition results is performed by using a sliding window, the eccentricity decomposition results are corrected based on transient deviation and trend deviation, the corrected results are used to configure intelligent correction parameters, and correction processing is performed.

[0046] Further, the application further includes the following steps: establishing a two-stage sliding window for the eccentricity decomposition results, the two-stage sliding window including a short window mapped with transient fluctuations and a long window mapped with trend deviation; after calculating statistical features by using the two-stage sliding window respectively, performing transient deviation and trend deviation discrimination, establishing transient correction components and trend correction components; and correcting the eccentricity decomposition results by using the transient correction components and the trend correction components.

[0047] Specifically, when processing the eccentricity decomposition results, a two-stage sliding window is established, including a short window mapped with transient fluctuations and a long window mapped with trend deviation. The sliding window is a technique for time series data processing, which calculates statistical features of data by constantly moving a fixed-size window. In the cable extrusion process, the sliding window can be used to analyze and correct eccentricity data in different time periods. The short window is used to process short-term, transient fluctuation data, focusing on real-time changes and instantaneous disturbances; the long window is used to process long-term trend deviation, focusing on long-term, gradually changing eccentricity trends in the cable production process. The short window is usually set to a small time range, such as 5 seconds or 10 seconds, so that it can quickly respond to short-term disturbances that change rapidly. The long window is set to a longer time range, such as 30 seconds, 1 minute or longer, to smooth the processing of long-term, gradually changing deviations. For example, in a certain cable extrusion process, the short window is set to 10 seconds and the long window is set to 30 seconds. The short window is used to correct transient fluctuations caused by rapid temperature changes or slight mold vibrations in the cable production process, while the long window is mainly used to handle long-term eccentricity problems caused by gradual equipment aging.

[0048] By using the two-stage sliding window respectively, statistical features such as mean, standard deviation, maximum value, minimum value, etc. are calculated, which helps to distinguish transient deviation and trend deviation, perform transient deviation and trend deviation discrimination, and extract transient correction components and trend correction components respectively. The transient correction component is a correction for eccentricity fluctuations caused by short-term disturbances, which plays a compensating role in a short period of time, avoiding the influence of these instantaneous fluctuations on the final quality of the cable sheath. The trend correction component is a correction for long-period deviations, which is usually used to dynamically adjust the decomposition proportion factor and the intelligent correction parameter, ensuring long-term stability and preventing eccentricity problems caused by gradually changing factors.

[0049] The eccentricity decomposition results are corrected by using the transient correction components and the trend correction components. The final correction formula is: corrected (t)=e trend_corrected(t) + e transient_filtered (t), wherein e trend_corrected (t) represents a trend correction component, e transient_filtered (t) represents a transient correction component. Transient fluctuations and long-term deviations are processed separately, and a comprehensive corrected eccentricity value is finally obtained. For example, if after correction, the transient correction component is -0.03 mm, and the trend correction component is +0.18 mm, then the final corrected eccentricity value is 0.15 mm.

[0050] By combining the short window and the transient correction component, instantaneous fluctuations caused by external disturbances, equipment vibration and other factors are effectively eliminated, ensuring that short-term eccentricity problems of the cable sheath are quickly corrected. By combining the long window and the trend correction component, eccentricity problems caused by long-term changes such as equipment aging and temperature changes can be effectively adjusted, ensuring the stability of the cable sheath production process. By the mutual cooperation of the two-stage sliding window and the correction component, short-term and long-term eccentricity deviations are simultaneously corrected, providing a more accurate eccentricity value prediction, thereby ensuring the final quality of the cable sheath.

[0051] Further, the application further includes the following steps: analyzing the correction result to obtain a geometric correction component, a flow correction component, and a cooling correction component; after adaptive gain distribution of transient deviations and trend deviations in the correction result, independent control optimization of multiple actuators is performed based on the geometric correction component, the flow correction component, and the cooling correction component, and an independent response strategy is established; intelligent correction parameters are configured according to the independent response strategy, and correction processing is performed.

[0052] Further, the application further includes the following steps: establishing independent correction response accuracy targets, energy consumption targets, and correction response time targets, and generating a multi-target balance function; independent control optimization is performed using the multi-target balance function, and the independent response strategy is established.

[0053] Further, the application further includes the following steps: taking the independent response strategy as an initial strategy, performing mechanism coordination analysis of multiple actuators, and establishing actuator coordination compensation; after updating the initial strategy using the actuator coordination compensation, a coordination response strategy is established; the coordination response strategy is taken as an intelligent correction parameter, and correction processing is performed.

[0054] Specifically, the corrected eccentricity decomposition results are analyzed to obtain geometric correction components, flow correction components, and cooling correction components. The geometric correction component refers to the correction made based on the geometric characteristics of the cable sheath. It is usually compensated by the geometric deviation of the cable profile to ensure that the cable sheath profile meets the design requirements. The flow correction component refers to the correction based on the flow characteristics during the extrusion of the cable sheath. It mainly compensates for the eccentricity caused by local flow rate difference, uneven flow, etc., to ensure the uniformity of the flow conditions. The cooling correction component refers to the adjustment of the cable sheath processing during the cooling stage to compensate for the eccentricity problem caused by uneven cooling. For example, assuming that the outer diameter of the cable sheath deviates at some positions, the geometric correction component is +0.02 mm, the flow correction component is -0.01 mm, and the cooling correction component is +0.03 mm.

[0055] In the correction results, the influence of transient deviation and trend deviation on the correction process needs to be adaptively adjusted with gain distribution. Transient deviation usually represents short-term fluctuations with small gain, while trend deviation represents long-term changes with large gain. The process of gain distribution is dynamic and can be adjusted according to real-time data feedback. Gain distribution refers to the dynamic adjustment of transient deviation and trend deviation in the correction process, and the influence of each correction component is optimized by the distribution of gain coefficients. The gain of transient deviation is usually small, and the gain of trend deviation is large to ensure long-term stability.

[0056] An independent correction response accuracy target, an energy consumption target, and a correction response time target are established to generate a multi-objective balance function. The independent correction response accuracy target refers to the requirement that the deviation of the cable outer diameter and inner diameter and other geometric dimensions should be controlled within a certain range through correction operation during the cable sheath extrusion process. For example, the error of the cable outer diameter should not exceed ±0.02 mm. The energy consumption target refers to the need to reduce energy consumption as much as possible during the correction control to improve energy use efficiency, which is usually set as the energy consumption per product, such as energy consumption per ton of product (kWh / ton). Assuming that the target is set to control the energy consumption within 10 kWh during the production of each ton of cable to reduce energy consumption. The correction response time target refers to the time interval from the occurrence of eccentricity to the completion of correction. The target is to complete the correction operation within a specified time to avoid negative impact on production speed, such as requiring each correction operation to be completed within 1 minute to avoid long production cycles.

[0057] The independent correction response accuracy target, energy consumption target, and correction response time target are integrated through a multi-objective balancing function, and the independent correction response accuracy target, energy consumption target, and correction response time target are comprehensively considered to find a balanced solution. Each target is assigned a weight according to its importance in the overall production process, which is usually determined by expert experience or simulation analysis. For example, the weight of the independent correction response accuracy target may be 0.5, the weight of the energy consumption target may be 0.3, and the weight of the correction response time target may be 0.2. Using the multi-objective balancing function, the independent control optimization of multiple actuators is performed based on the geometric correction component, the flow correction component, and the cooling correction component to find the best control parameters so that each target can reach the optimal value. The role of the multi-objective balancing function is to weight and average the independent correction response accuracy target, energy consumption target, and correction response time target, thereby providing a comprehensive target for subsequent optimization algorithms. The parameters of different actuators are optimized for each correction component, i.e., the geometric correction component, the flow correction component, and the cooling correction component. The optimization target of each actuator is independent, but they share a multi-objective balancing function to ensure the comprehensive optimization of their respective targets. For example, by adjusting the size, shape of the die, or the operating speed of the extruder, the outer diameter and inner diameter of the cable are adjusted to ensure they are within the specified range. The geometric size is optimized by controlling the die temperature and pressure; the flow state is optimized by adjusting the flow rate regulator and pressure control system to ensure uniform flow of the cable sheath during extrusion; and the cooling system is optimized, such as by adding cooling nozzles or adjusting the cooling water flow rate, to reduce temperature differences and ensure uniform cooling of the cable sheath surface, thereby avoiding eccentricity caused by temperature differences.

[0058] Through independent control optimization, the best control strategy for each correction target is obtained, which is called an independent response strategy. Each strategy is optimized for a specific target. For example, the strategy for the geometric correction component is to adjust the die temperature to 200°C and maintain the extrusion rate at 2.5 m / min; the strategy for the flow correction component is to increase the die pressure to 3.0 MPa through a booster pump and adjust the flow rate to 2.8 m / s; and the strategy for the cooling correction component is to adjust the cooling nozzle to 50°C and adjust the cooling water flow rate to 0.6 m / s.

[0059] Although each control strategy is independent, it still needs to work synergistically to achieve the final production target. Therefore, during optimization, the mutual influence between actuators also needs to be considered. For example, if the flow rate is too high while the geometric correction is being performed, it may cause uneven flow and affect the geometric size. Therefore, the parameter adjustment of the actuators needs to work synergistically to ultimately ensure that all targets are optimized.

[0060] The independent response strategy is obtained by optimizing each control strategy independently for different correction targets. The independent response strategy is used as the initial strategy to perform a multi-actuator coordination analysis to establish actuator coordination compensation. In actual production, multiple actuators do not work independently, but interact with each other, so it is necessary to analyze the interaction between each actuator to ensure that they work in coordination to achieve the best correction effect. For example, when the die temperature is set to 200℃, it will cause the flow rate to increase or decrease, thereby affecting the flow state of the cable sheath. If the flow rate is too fast, it will cause uneven flow, affecting the thickness distribution of the cable sheath. Therefore, it is necessary to adjust the parameters of the flow rate controller to work in coordination with the temperature controller to ensure uniform flow.

[0061] Through actuator coordination analysis, the interaction between actuators is compensated. The compensation process is to adjust the control parameters of each actuator to minimize the mutual influence between them, thereby ensuring the optimization of the overall target. The purpose of compensation is to correct the deviation caused by the lack of coordination between each actuator. For example, assume that in the case of die temperature 200℃, the flow rate controller is adjusted to 3.0 m / s, and the cooling nozzle temperature is adjusted to 50℃, which is caused by uneven cooling and leads to uneven surface temperature of the product. Actuator coordination compensation can compensate for this difference by adjusting the temperature of the cooling nozzle or the flow rate of the cooling water, thereby ensuring uniform cooling effect.

[0062] After actuator coordination compensation, the initial independent response strategy is updated to a coordinated response strategy, which not only considers the independent target of each actuator, but also integrates the coordination between actuators to ensure multi-objective optimization throughout the process. The coordinated response strategy can dynamically adjust the parameters of each actuator to respond to disturbances and changes in the production process. For example, during production, if a slight deviation in the geometric size of the cable sheath is detected, the coordinated response strategy will adjust multiple parameters such as die temperature, flow rate, and cooling water flow rate to rebalance each target and correct the deviation.

[0063] The obtained synergistic response strategy is used as an intelligent correction parameter for correction processing. By adjusting the parameters of the actuator in real time, the eccentricity problem of the cable sheath is corrected in real time. For example, assuming that at a certain moment, the outer diameter deviation of the cable sheath is +0.05 mm, the flow rate is 2.8 m / s, and the cooling water flow rate is 0.55 m / s. According to the synergistic response strategy, the flow rate is adjusted to 2.5 m / s, and the cooling water flow rate is adjusted to 0.6 m / s, and the die temperature is maintained at 200°C, ensuring that the outer diameter of the cable sheath returns to the target value. Correction processing refers to correcting the eccentricity problem of the cable sheath by adjusting the control parameters of the actuator. Through the synergistic compensation and synergistic response strategy of the actuator, the deviation caused by the uncoordination of each actuator is eliminated, thereby significantly improving the accuracy of the geometric size, flow state and cooling uniformity of the cable sheath, and ensuring the consistency and quality of the product.

[0064] Further, the present application further comprises the following steps: identifying deviation warning based on the correction result, establishing a deviation warning signal; executing the deviation warning signal according to the corresponding warning strategy to report the warning, and after receiving the warning adjustment feedback, configuring intelligent correction parameters based on the correction result, and executing correction processing.

[0065] Specifically, after intelligent correction processing, the difference between the real-time correction result and the standard value is compared. If a parameter deviates from the pre-set allowed range, the deviation will be identified and a warning will be triggered. Usually, a threshold range is established to achieve this, for example, if the outer diameter deviation of the cable sheath exceeds ±0.1 mm, a warning signal will be triggered. Once the deviation warning is identified, a deviation warning signal is sent to the relevant personnel, prompting the need to take timely measures. The form of the warning signal can be diverse, such as graphical display, sound alarm or message push, etc.

[0066] According to the pre-set warning strategy, when the deviation is detected, the warning is automatically triggered according to the priority. The warning strategy will specify the warning level of different deviations, for example: a slight deviation triggers a yellow warning, prompting the relevant personnel to check and adjust; a serious deviation triggers a red warning, automatically adjusting the production parameters or suspending production. After receiving the warning signal, the relevant personnel will adjust the feedback according to the warning information to restore the production state by adjusting the production parameters. For example, the relevant personnel adjusts the die temperature or flow rate according to the warning suggestion, or adjusts the parameters of the cooling equipment.

[0067] After receiving the adjustment feedback, the intelligent correction parameters are dynamically configured according to the current production status and the correction results, including die temperature, flow rate, cooling water flow rate, etc., to ensure that the production process is always in an optimal control state. Based on the configured intelligent correction parameters, real-time correction processing is performed. According to the feedback intelligent correction parameters, each link of the production process is automatically adjusted to ensure that the size, temperature and cooling distribution of the cable sheath meet the requirements. For example, after detecting that the outer diameter deviation is too large, it is recommended to adjust the flow rate and die temperature. The relevant personnel adjust the flow rate from 2.5 m / s to 2.3 m / s and the die temperature from 210°C to 200°C, and feedback to the control center. After adjusting the cooling flow rate and die temperature, the temperature and cooling nozzle configuration are automatically adjusted to restore the sheath outer diameter to 8.0 mm, thereby avoiding further deviation from the target specification.

[0068] Through real-time monitoring and early warning mechanisms, deviations are quickly identified and warnings are issued, reducing response time and enabling quick adjustments to ensure that the production quality of the cable sheath is not affected. The combination of deviation warning signals and correction processing allows the production process to be adjusted in real time, preventing long-term deviation accumulation and reducing the frequency of product defects, thereby improving production stability.

[0069] Further, the application further includes the following steps: establishing a node deviation database according to the correction results, establishing node attention using the node deviation database, and performing attention control management of cable sheath extrusion through the node attention.

[0070] Specifically, during the extrusion of the cable sheath, each production node will produce certain deviations. In order to track these deviations, the deviation of each node needs to be recorded to form a node deviation database, i.e., a node deviation database is established according to the correction results. The node deviation database contains the deviation data of each node, including node identification, deviation value, deviation cause, etc. The node identification is used to record which specific node, such as time point, production stage, etc.; the deviation value is used to record the size and direction of the deviation, such as the deviation of the outer diameter, temperature or cooling speed; and the deviation cause is used to record possible deviation causes, such as excessive die temperature, insufficient cooling water flow rate, etc.

[0071] The node attention is established using the node deviation database, i.e., based on historical data and the current production status, key nodes that may affect product quality are identified, especially those nodes that frequently deviate, to ensure that these nodes do not deviate from the target or that when a deviation occurs, timely adjustments are made. Based on the node attention, attention control management is implemented, i.e., for those nodes marked as attention, the key control parameters in the extrusion process are dynamically adjusted. For example, near certain nodes, such as nodes with large temperature changes, the die temperature, cooling rate, flow rate, etc. are automatically adjusted to ensure that these nodes do not continue to deviate from the target.

[0072] The attention control management refers to monitoring and managing the nodes of attention, dynamically adjusting the parameters of the cable sheath extrusion process, such as temperature, pressure, flow rate, etc., to ensure consistency at key nodes during production and correct deviations in real time to ensure the quality of the final product. Through attention control management, deviations are corrected in real time and the production process is stabilized. For example, if the temperature of a certain node starts to deviate from the set range, the temperature control device is automatically adjusted to correct the deviation and avoid further affecting the quality of the product. Through attention control management, deviations are corrected in real time and the production process is stabilized. For example, if the temperature of a certain node starts to deviate from the set range, the temperature control device is automatically adjusted to correct the deviation and avoid further affecting the quality of the product.

[0073] Using the node deviation database and node attention mechanism, each node in the production process is monitored in real time to ensure that key nodes are always within the control range and parameters are adjusted in time to avoid the accumulation of deviations. By identifying and managing attention nodes, unstable factors in production are effectively avoided, reducing the impact of sudden problems on production quality and improving the stability and consistency of production.

[0074] In summary, the intelligent deviation correction control method for cable sheath extrusion provided by the present application has the following beneficial effects: by synchronously activating an electromagnetic sensor array during cable sheath extrusion control, the electromagnetic sensor array is arranged circumferentially along the cable sheath extrusion position, and a core monitoring signal of the cable core is read according to the electromagnetic sensor array; an infrared thermal imaging sensor is activated to perform temperature field distribution collection of the cable sheath surface, and a time series temperature field dataset is established; the core monitoring signal and the time series temperature field dataset are sent to a feature extraction layer to establish a core real-time offset vector feature, a circumferential temperature uniformity feature, and a longitudinal cooling gradient feature; the core real-time offset vector feature, the circumferential temperature uniformity feature, and the longitudinal cooling gradient feature are input into a factorized eccentricity model to perform eccentricity decomposition of the cable sheath, and an eccentricity decomposition result is established; multi-scale discrimination of the eccentricity decomposition result is performed using a sliding window, the eccentricity decomposition result is corrected based on transient deviation and trend deviation, the corrected result is used to configure intelligent deviation correction parameters, and deviation correction processing is performed. That is, by using the electromagnetic sensor array and the infrared thermal imaging sensor, the cable core and the temperature field distribution are monitored in real time, the core real-time offset vector feature, the circumferential temperature uniformity feature, and the longitudinal cooling gradient feature are extracted, and input into the factorized eccentricity model for eccentricity decomposition. The eccentricity decomposition result is discriminated by a sliding window, corrected in combination with transient deviation and trend deviation, and the accuracy of the deviation correction control is improved, thereby improving production efficiency and product quality.

[0075] Embodiment two, based on the same inventive concept as the intelligent correction control method for cable sheath extrusion in the foregoing embodiment one, the present application also provides an intelligent correction control system for cable sheath extrusion, please refer to the attached Figure 2 , the intelligent correction control system for cable sheath extrusion comprises: a signal acquisition module 11, used for synchronously activating an electromagnetic sensor array during the process of cable sheath extrusion control, the electromagnetic sensor array is arranged circumferentially along the cable sheath extrusion position, and a core monitoring signal of a cable core is read according to the electromagnetic sensor array; a temperature field acquisition module 12, used for activating an infrared thermal imaging sensor to perform temperature field distribution acquisition of a cable sheath surface, and establish a time-series temperature field data set; a feature extraction module 13, used for sending the core monitoring signal and the time-series temperature field data set to a feature extraction layer, establishing a core real-time offset vector feature, a circumferential temperature uniformity feature and a longitudinal cooling gradient feature; an eccentric decomposition module 14, used for inputting the core real-time offset vector feature, the circumferential temperature uniformity feature and the longitudinal cooling gradient feature into a factorized eccentric model, performing eccentric decomposition of the cable sheath, and establishing an eccentric decomposition result; and a result correction module 15, used for performing multi-scale discrimination of the eccentric decomposition result by using a sliding window, performing eccentric decomposition result correction based on transient deviation and trend deviation, configuring intelligent correction parameters by using the correction result, and performing correction processing.

[0076] Further, the eccentric decomposition module 14 in the intelligent correction control system for cable sheath extrusion is also used for: acquiring cable data, the cable data comprising cable outer diameter data, cable inner diameter data and cable die structure; after sending the cable data to a geometric factor transmission layer in the factorized eccentric model, performing geometric approximate transmission fitting on the core real-time offset vector feature by using the geometric factor transmission layer, and establishing a geometric approximate transmission fitting result; sending the circumferential temperature uniformity feature to a flow transmission layer in the factorized eccentric model, performing linear mapping analysis of temperature-local flow rate difference-thickness difference, and establishing a flow transmission fitting result; sending the longitudinal cooling gradient feature to a cooling factor transmission layer in the factorized eccentric model, performing shrinkage analysis under the influence of local cooling rate, and establishing a cooling shrinkage fitting result; synchronously sending the geometric approximate transmission fitting result, the flow transmission fitting result and the cooling shrinkage fitting result to a decomposition authentication layer to perform decomposition authentication fitting, and establishing an eccentric decomposition result.

[0077] Further, the eccentricity decomposition module 14 in the intelligent deviation correction control system for cable sheath extrusion is further used for: establishing an initial predicted eccentricity synthesis result by predicting eccentricity synthesis of the geometric approximation transmission fitting result, the flow transmission fitting result and the cooling shrinkage fitting result through a preset synthesis weight; after reading a measured eccentricity value, performing residual error calculation using the initial predicted eccentricity synthesis result and the measured eccentricity value to establish a residual error calculation result; performing adaptive preset synthesis weight adjustment iteration using the residual error calculation result and the correlation factor of each fitting component, and taking the correlation factor and the residual error calculation result as weight adjustment indexes; and completing decomposition optimization according to the adjustment iteration result to establish an eccentricity decomposition result.

[0078] Further, the result correction module 15 in the intelligent deviation correction control system for cable sheath extrusion is further used for: establishing a two-stage sliding window for the eccentricity decomposition result, the two-stage sliding window including a short window for mapping transient fluctuations and a long window for mapping trend deviations; performing transient deviation and trend deviation discrimination after respectively calculating statistical characteristics using the two-stage sliding window to establish a transient correction component and a trend correction component; and correcting the eccentricity decomposition result using the transient correction component and the trend correction component.

[0079] Further, the result correction module 15 in the intelligent deviation correction control system for cable sheath extrusion is further used for: analyzing the correction result to obtain a geometric deviation correction component, a flow deviation correction component and a cooling deviation correction component; performing independent control optimization of multiple actuators based on the geometric deviation correction component, the flow deviation correction component and the cooling deviation correction component after adaptively performing gain distribution according to transient deviations and trend deviations in the correction result to establish an independent response strategy; and configuring intelligent deviation correction parameters according to the independent response strategy and performing deviation correction processing.

[0080] Further, the result correction module 15 in the intelligent deviation correction control system for cable sheath extrusion is further used for: taking the independent response strategy as an initial strategy, performing mechanism coordination analysis of multiple actuators to establish actuator coordination compensation; updating the initial strategy using the actuator coordination compensation to establish a coordination response strategy; taking the coordination response strategy as intelligent deviation correction parameters to perform deviation correction processing.

[0081] Further, the result correction module 15 in the intelligent deviation correction control system for cable sheath extrusion is further used for: establishing an independent deviation correction response accuracy target, an energy consumption target and a deviation correction response time target to generate a multi-target balance function; performing independent control optimization using the multi-target balance function to establish the independent response strategy.

[0082] Further, the result correction module 15 in the intelligent deviation correction control system for cable sheath extrusion is further used for: identifying deviation pre-warning of the correction result, establishing a deviation pre-warning signal; executing pre-warning according to the corresponding pre-warning strategy, and after receiving the pre-warning adjustment feedback, configuring intelligent deviation correction parameters based on the correction result, and executing deviation correction processing.

[0083] Further, the result correction module 15 in the intelligent deviation correction control system for cable sheath extrusion is further used for: establishing a node deviation database according to the correction result, and establishing a node focus by using the node deviation database.

[0084] The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the difference from other embodiments. Figure 1 The intelligent deviation correction control method for cable sheath extrusion in Embodiment One and the specific examples are also applicable to the intelligent deviation correction control system for cable sheath extrusion in the present embodiment. Through the foregoing detailed description of the intelligent deviation correction control method for cable sheath extrusion, those skilled in the art can clearly know the intelligent deviation correction control system for cable sheath extrusion in the present embodiment. Therefore, for the sake of brevity of the specification, it will not be described in detail here.

[0085] The above description of the disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0086] Obviously, for those skilled in the art, without departing from the principles of the present application, the present application can be improved and modified in several ways, and these improvements and modifications also fall within the protection scope of the present application.

Claims

1. A method for intelligent correction control for cable jacket extrusion, characterized in that, The method comprises the following steps: In the process of cable protective sleeve extrusion control, synchronously activate an electromagnetic sensor array arranged circumferentially along the cable protective sleeve extrusion position, read the core monitoring signal of the cable core according to the electromagnetic sensor array; Activate the infrared thermal imaging sensor to perform temperature field distribution collection of the cable protective sleeve surface, and establish a time series temperature field data set; Send the core monitoring signal and the time series temperature field data set to a feature extraction layer to establish a core real-time offset vector feature, a circumferential temperature uniformity feature, and a longitudinal cooling gradient feature; Input the core real-time offset vector feature, the circumferential temperature uniformity feature, and the longitudinal cooling gradient feature into a factorized eccentricity model to perform eccentric decomposition of the cable protective sleeve, and establish an eccentric decomposition result; Use a sliding window to perform multi-scale discrimination of the eccentric decomposition result, correct the eccentric decomposition result based on transient deviation and trend deviation, use the correction result to configure intelligent correction parameters, and perform correction processing.

2. The intelligent correction control method for cable jacket extrusion of claim 1, wherein, The method comprises the following steps: Obtain cable data, which comprises cable outer diameter data, cable inner diameter data, and cable die structure; After sending the cable data to a geometric factor transfer layer in the factorized eccentricity model, use the geometric factor transfer layer to perform geometric approximation transfer fitting on the core real-time offset vector feature, and establish a geometric approximation transfer fitting result; Send the circumferential temperature uniformity feature to a flow transfer layer in the factorized eccentricity model, perform linear mapping analysis of temperature-local flow rate difference-thickness difference, and establish a flow transfer fitting result; Send the longitudinal cooling gradient feature to a cooling factor transfer layer in the factorized eccentricity model, perform shrinkage analysis under the influence of local cooling rate, and establish a cooling shrinkage fitting result; Synchronize the geometric approximation transfer fitting result, the flow transfer fitting result, and the cooling shrinkage fitting result to a decomposition authentication layer to perform decomposition authentication fitting, and establish an eccentric decomposition result.

3. The intelligent correction control method for cable jacket extrusion of claim 2, wherein, The method comprises the following steps: Perform predicted eccentricity synthesis of the geometric approximation transfer fitting result, the flow transfer fitting result, and the cooling shrinkage fitting result by a preset synthesis weight, and establish an initial predicted eccentricity synthesis result; After reading a measured eccentricity value, use the initial predicted eccentricity synthesis result and the measured eccentricity value to perform residual error calculation, and establish a residual error calculation result; Use the correlation factor of the residual error calculation result and each fitting component, and use the correlation factor and the residual error calculation result as weight adjustment indexes to perform adaptive preset synthesis weight adjustment iteration; Complete decomposition optimization according to the adjustment iteration result, and establish an eccentric decomposition result.

4. The intelligent correction control method for cable jacket extrusion of claim 3, wherein, The method comprises the following steps: Two-stage sliding windows are established for the eccentric decomposition result, including a short window mapped with transient fluctuation and a long window mapped with trend deviation; After calculating statistical features by using the two-stage sliding windows respectively, transient deviation and trend deviation discrimination are performed to establish transient correction components and trend correction components; The eccentric decomposition result is corrected by using the transient correction components and the trend correction components.

5. The intelligent correction control method for cable jacket extrusion of claim 1, wherein, The corrected result is used to configure intelligent correction parameters, and correction processing is performed, including: The corrected result is analyzed to obtain geometric correction components, flow correction components, and cooling correction components; After adaptive gain distribution is performed according to transient deviation and trend deviation in the corrected result, independent control optimization of multiple actuators is performed based on the geometric correction components, the flow correction components, and the cooling correction components to establish an independent response strategy; Intelligent correction parameters are configured according to the independent response strategy, and correction processing is performed.

6. The intelligent correction control method for cable jacket extrusion of claim 5, wherein, The correction processing performed according to the independent response strategy includes: The independent response strategy is used as an initial strategy, mechanism coordination analysis of multiple actuators is performed, and actuator coordination compensation is established; After the initial strategy is updated by using the actuator coordination compensation, a coordination response strategy is established; The coordination response strategy is used as an intelligent correction parameter, and correction processing is performed.

7. The intelligent correction control method for cable jacket extrusion of claim 5, wherein, The independent control optimization of multiple actuators based on the geometric correction components, the flow correction components, and the cooling correction components to establish an independent response strategy includes: An independent correction response accuracy target, an energy consumption target, and a correction response time target are established, and a multi-objective balance function is generated; The independent control optimization is performed by using the multi-objective balance function, and the independent response strategy is established.

8. The intelligent correction control method for cable jacket extrusion of claim 1, wherein, Before the corrected result is used to configure intelligent correction parameters, the following steps are included: Deviation early warning identification is performed on the corrected result, and a deviation early warning signal is established; The deviation early warning signal is reported according to a corresponding early warning strategy, and after receiving early warning adjustment feedback, intelligent correction parameters are configured based on the corrected result, and correction processing is performed.

9. The intelligent correction control method for cable jacket extrusion of claim 1, wherein, The corrected result is used to configure intelligent correction parameters, and correction processing is performed, including: A node deviation database is established according to the corrected result, and node attention is established by using the node deviation database; Attention control management of cable sheath extrusion is performed through the node attention.

10. An intelligent correction control system for cable jacket extrusion, characterized by, The intelligent correction control system for cable sheath extrusion includes the following steps for implementing the intelligent correction control method for cable sheath extrusion according to any one of claims 1 to 9: A signal acquisition module is configured to activate an electromagnetic sensor array synchronously during cable sheath extrusion control, the electromagnetic sensor array is arranged circumferentially along a cable sheath extrusion position, and a core monitoring signal of a cable core is read according to the electromagnetic sensor array; A temperature field acquisition module is configured to activate an infrared thermal imaging sensor to perform temperature field distribution acquisition of a cable sheath surface, and a time-series temperature field dataset is established; A feature extraction module is configured to send the core monitoring signal and the time-series temperature field dataset to a feature extraction layer to establish a core real-time offset vector feature, a circumferential temperature uniformity feature, and a longitudinal cooling gradient feature. The eccentric decomposition module is configured to input the core real-time offset vector feature, the circumferential temperature uniformity feature, and the longitudinal cooling gradient feature into a factorization eccentric model, perform eccentric decomposition of the cable protective sleeve, and establish an eccentric decomposition result. The result correction module is configured to perform multi-scale discrimination of the eccentric decomposition result by using a sliding window, correct the eccentric decomposition result based on transient deviation and trend deviation, configure intelligent correction parameters by using the correction result, and perform correction processing.

Images