Method, system and equipment for optimizing insulation layer quality in high-density winding of multi-core cables

Abstract

The present invention discloses a method, system and equipment for optimizing the quality of the insulation layer in the high-density winding of multi-core cables, which relates to the field of cable technology, including: obtaining the production requirements of the multi-core cable and determining the multi-core arrangement guiding factor; performing winding structure design on multiple insulating core wires and determining the multi-core winding structure layout; making control decisions on a multi-core synchronous winding device and obtaining a first synchronous winding control space; performing insulation layer quality loss inspection on the first synchronous winding control space and obtaining a second synchronous winding control space; performing multi-level joint optimization on the second synchronous winding control space and obtaining a synchronous winding control strategy, and controlling the multi-core synchronous winding device to perform adaptive winding on multiple insulating core wires. The present invention solves the technical problems of the prior art in that the insulation layer is easily damaged during the high-density winding process of multi-core cables and the winding control lacks an adaptive adjustment mechanism, thereby achieving the technical effect of improving the winding quality of the insulation layer and realizing adaptive control of the winding process.

Description

Technical Field

[0001] The present invention relates to the technical field of cables, and in particular to a method, system and equipment for optimizing the quality of insulation layers in high-density winding of multi-core cables. Background Art

[0002] With the development of electronic communications, power transmission, and industrial automation, the transmission density and space utilization of multi-core cables have become increasingly demanding. High-density winding technology for multi-core cables has gradually become a key process in cable manufacturing. However, the winding process of multi-core cables typically relies on fixed winding methods or manual adjustments based on experience, lacking detailed modeling of the complex relationship between winding structure and core quality. As a result, the insulation layer is susceptible to compression, friction, and even misalignment and damage under high-density winding, affecting the insulation performance and overall stability of the cable. Summary of the Invention

[0003] The present application provides a method, system and equipment for optimizing the quality of the insulation layer during high-density winding of multi-core cables, which is used to solve the technical problems in the prior art that the insulation layer is easily damaged during high-density winding of multi-core cables and the winding control lacks an adaptive adjustment mechanism.

[0004] In view of the above problems, the present application provides a method, system and equipment for optimizing the quality of the insulation layer in high-density winding of multi-core cables.

[0005] In a first aspect of the present application, a method for optimizing the quality of an insulation layer in high-density winding of a multi-core cable is provided, the method comprising:

[0006] Obtain the multi-core cable production requirements corresponding to multiple insulated core wires, perform fitness analysis on the multivariate winding attribute factors in combination with the core wire detection data set, and determine the multi-core arrangement guiding factor; based on the core wire detection data set, design the winding structure of the multiple insulated core wires according to the multi-core arrangement guiding factor, and determine the multi-core winding structure layout; make control decisions on the multi-core synchronous winding device according to the multi-core winding structure layout and the core wire detection data set, and obtain the first synchronous winding control space; perform insulation layer quality loss inspection on the first synchronous winding control space according to the insulation layer quality loss threshold, and obtain the second synchronous winding control space; perform multi-level joint optimization on the second synchronous winding control space according to the winding control evaluation model, and obtain the synchronous winding control strategy; control the multi-core synchronous winding device according to the synchronous winding control strategy to perform adaptive winding on the multiple insulated core wires.

[0007] A second aspect of the present application provides a system for optimizing the quality of insulation layers in high-density winding of multi-core cables, the system comprising:

[0008] A fitness analysis module is used to obtain the multi-core cable production requirements corresponding to multiple insulated core wires, perform fitness analysis on the multivariate winding attribute factors in combination with the core wire detection data set, and determine the multi-core arrangement guiding factor; a winding structure design module is used to design the winding structure of the multiple insulated core wires based on the core wire detection data set and the multi-core arrangement guiding factor, and determine the multi-core winding structure layout; a control decision module is used to make control decisions on the multi-core synchronous winding device according to the multi-core winding structure layout and the core wire detection data set, and obtain the first synchronous winding control space; a loss inspection module is used to perform insulation layer quality loss inspection on the first synchronous winding control space according to the insulation layer quality loss threshold, and obtain the second synchronous winding control space; a joint optimization module is used to perform multi-level joint optimization on the second synchronous winding control space according to the winding control evaluation model to obtain a synchronous winding control strategy; an adaptive winding module is used to control the multi-core synchronous winding device to perform adaptive winding on the multiple insulated core wires according to the synchronous winding control strategy.

[0009] The third aspect of the present application provides an electronic device, comprising: a memory for storing executable instructions; and a processor for executing the executable instructions stored in the memory to implement the method for optimizing the quality of the insulation layer in high-density winding of multi-core cables provided in the present application.

[0010] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0011] The present application obtains the multi-core cable production demand corresponding to multiple insulated core wires, performs fitness analysis on the multivariate winding attribute factors in combination with the core wire detection data set, and determines the multi-core arrangement guiding factor; based on the core wire detection data set, the winding structure of the multiple insulated core wires is designed according to the multi-core arrangement guiding factor, and the multi-core winding structure layout is determined; control decisions are made on the multi-core synchronous winding device according to the multi-core winding structure layout and the core wire detection data set to obtain a first synchronous winding control space; an insulation layer quality loss test is performed on the first synchronous winding control space according to the insulation layer quality loss threshold to obtain a second synchronous winding control space; a multi-level joint optimization is performed on the second synchronous winding control space according to the winding control evaluation model to obtain a synchronous winding control strategy; the multi-core synchronous winding device is controlled according to the synchronous winding control strategy to perform adaptive winding on the multiple insulated core wires. The present invention solves the technical problems in the prior art that the insulation layer is easily damaged during the high-density winding process of multi-core cables and the winding control lacks an adaptive adjustment mechanism. By constructing a fitness analysis mechanism of multivariate winding attribute factors, a hierarchical control strategy for synchronous winding space and a multi-level joint optimization model, the technical effect of improving the winding quality of the insulation layer and realizing adaptive control of the winding process is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0013] Figure 1 A schematic flow chart of a method for optimizing insulation quality in high-density winding of multi-core cables provided in an embodiment of the present application;

[0014] Figure 2 A schematic diagram of the structure of the insulation layer quality optimization system for high-density winding of multi-core cables provided in an embodiment of the present application;

[0015] Figure 3 This is a schematic diagram of the structure of an exemplary electronic device of this application.

[0016] Explanation of the accompanying drawings: bus 300, receiver 301, processor 302, transmitter 303, memory 304, bus interface 305, fitness analysis module 11, winding structure design module 12, control decision module 13, loss detection module 14, joint optimization module 15, adaptive winding module 16. DETAILED DESCRIPTION

[0017] This application provides a method, system and equipment for optimizing the quality of the insulation layer in the high-density winding of multi-core cables, aiming to solve the technical problems in the existing technology that the insulation layer is easily damaged during the high-density winding of multi-core cables and the winding control lacks an adaptive adjustment mechanism. By constructing a fitness analysis mechanism of multi-element winding attribute factors, a hierarchical control strategy of the synchronous winding space and a multi-level joint optimization model, the technical effect of improving the insulation layer winding quality and realizing adaptive control of the winding process is achieved.

[0018] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0019] It should be noted that any variations of the terms "include" and "have" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices.

[0020] Example 1, as Figure 1 As shown, the present application provides a method for optimizing the quality of the insulation layer in high-density winding of a multi-core cable, the method comprising:

[0021] Step S100: obtaining the multi-core cable production requirements corresponding to the plurality of insulated core wires, performing fitness analysis on the multivariate winding attribute factors in combination with the core wire detection data set, and determining the multi-core arrangement guiding factor.

[0022] In this embodiment, the current cable order is first parsed and, in conjunction with the company's internal Manufacturing Execution System (MES) or product process database, the production requirements for multi-core cables corresponding to multiple insulated cores are extracted. These production requirements include process constraints such as the number of cores, cable diameter, winding density, minimum bend radius, and operating environment (e.g., high temperature, high frequency, vibration), among others.

[0023] The fitness analysis of the multivariate winding attribute factors was then conducted using a core wire inspection dataset. This dataset, collected through quality inspection of multiple insulated core wires using core wire inspection equipment, includes characteristic information such as the geometric dimensional accuracy (such as diameter and roundness) and material properties (such as flexibility and tensile strength) of each core wire.

[0024] Based on the production requirements and core test data sets for multi-core cables, a variety of winding methods were introduced as candidate winding attribute factors, including concentric spiral winding, layered winding, non-uniform pitch winding, and programmable pitch winding. Each winding method was compared and analyzed with the production requirements and core test data to form a winding attribute fitness evaluation table. From this table, the most suitable winding method under current production conditions was selected, and the guiding factor for multi-core arrangement was ultimately determined.

[0025] Furthermore, in the method provided in the embodiment of the application, the production requirements of a multi-core cable corresponding to a plurality of insulated core wires are obtained, and a fitness analysis of the multi-element winding attribute factors is performed in combination with the core wire detection data set to determine the multi-core arrangement guiding factor, which also includes:

[0026] The multivariate winding attribute factors include concentric spiral winding, layered structure winding, non-uniform pitch winding and programmable pitch winding; the fitness of the multivariate winding attribute factors is evaluated according to the multi-core cable production requirements and the core wire detection data set, and a winding attribute fitness evaluation table is constructed; the multivariate winding attribute factors are screened for winding attribute fitness maximization according to the winding attribute fitness evaluation table to obtain the multi-core arrangement guiding factor.

[0027] In the embodiment of the present application, the multi-element winding attribute factors include concentric spiral winding (i.e., all core wires are arranged symmetrically around the central spiral), layered structure winding (i.e., the core wires are wound separately according to the levels), non-uniform pitch winding (used in scenarios with special pitch requirements such as signal transmission), and programmable pitch winding (dynamically adjusting the pitch and rotation speed according to the core wire characteristics through stepper control or servo motor).

[0028] When evaluating the fitness of multi-element winding attribute factors based on the production requirements of multi-core cables and core wire inspection datasets, a property comparison method is used. First, each winding method is statically compared with the production requirements for adaptability. For example, a concentric spiral is suitable for high-voltage cables with high symmetry requirements, while a layered structure is suitable for multiple core wire combinations. Each winding method is then dynamically analyzed for process adaptability with the core wire inspection data. For example, when the flexibility difference is large, the layered structure is more effective in reducing stress accumulation. To achieve quantitative evaluation, the above matching process is further converted into two scoring matrices. The first is to score the matching degree of winding attribute factors based on the production requirements of multi-core cables, forming the first winding attribute matching evaluation matrix; the second is to score the process adaptability of the winding factors based on the core wire inspection data, forming the second winding attribute matching evaluation matrix. The two matrices are then weighted and fused according to the preset fitness weight conditions to generate the final winding attribute fitness evaluation table.

[0029] Finally, based on the winding attribute fitness evaluation table, a fitness maximization screening strategy is employed to sort the fitness scores corresponding to all winding attribute factors in the evaluation table, prioritizing the winding method with the highest fitness score. Through this process, the optimal multi-core arrangement guidance factor is obtained under the current manufacturing conditions.

[0030] Furthermore, in the method provided in the embodiment of the application, the fitness evaluation of the multi-element winding attribute factor is performed according to the multi-core cable production requirements and the core wire detection data set, and a winding attribute fitness evaluation table is constructed, which also includes:

[0031] According to the multi-core cable production requirements, the multi-component winding property factors are evaluated for matching, and a first winding property matching evaluation matrix is ​​obtained; according to the core wire detection data set, the multi-component winding property factors are evaluated for matching, and a second winding property matching evaluation matrix is ​​obtained; according to the winding property fitness weight condition, the first winding property matching evaluation matrix and the second winding property matching evaluation matrix are weighted calculated to generate the winding property fitness evaluation table.

[0032] In this embodiment, when evaluating the matching of the winding structure of a multi-core cable, structural requirement parameters are first extracted from the cable production task. These parameters include target cable diameter, cable profile, allowable number of cabling layers, symmetry level, and winding tightness, and are typically stored in a structured process specification in an MES (Manufacturing Execution System) or process database. Simultaneously, each predefined winding method is standardized as a set of structural attribute vectors. For example, concentric spiral winding can be set with parameters such as "circumferential symmetry = 5," "winding level = 1," and "pitch variation rate = 0." These structural vectors are mapped one-to-one to the target production requirement vectors, and the distance is measured using the Euclidean distance formula. The smaller the distance, the closer the winding method matches the requirement. After performing this operation across all matching dimensions, a first set of scoring data is generated and organized by winding method into a first winding attribute matching evaluation matrix. Each row of this matrix corresponds to a winding method, and each column corresponds to the matching score for a structural dimension. The scores are normalized to the range [0, 1].

[0033] Next, the core wire inspection subsystem acquires quality data for each core wire currently being wound. This data is collected by online inspection devices (such as laser diameter gauges, image recognition equipment, and insulation thickness probes) and aggregated into a test dataset that includes indicators such as maximum core wire diameter difference, flexibility level, surface defect rate, and insulation layer fluctuation coefficient. Each indicator has preset compatibility criteria for the winding method. For example, layered winding allows for larger diameter differences, while concentric spiral winding requires higher flexibility. By comparing these test values ​​with the predefined tolerance ranges for the winding method, the feasibility of the winding method under the current core wire working conditions is determined. This comparison is performed using a threshold function. If a parameter falls within the tolerance range, it is scored as 1; if it falls within the critical boundary, it is scored as 0.5; and if it exceeds the tolerance range, it is scored as 0. Finally, the adaptability scores of all winding methods under each core wire process parameter are summarized to form a second winding attribute matching evaluation matrix. Its structure is consistent with the first matrix, and the scores are also normalized.

[0034] The two evaluation matrices are then weighted and fused based on the preset winding attribute fitness weight conditions. The weights are set to 0.6 for the production demand matching dimension and 0.4 for the core quality adaptability dimension. The scores for the corresponding positions in the two matrices are read item by item and fused using a linear weighted formula: fitness score = 0.6 × first matrix score + 0.4 × second matrix score. After completing this calculation for all winding methods, a winding attribute fitness evaluation table is obtained. Each row of this evaluation table corresponds to a winding method, and its column vector represents the comprehensive adaptability given the structural requirements and core conditions.

[0035] Step S200: Based on the core wire detection data set, a winding structure design is performed on the plurality of insulated core wires according to the multi-core arrangement guiding factor to determine a multi-core winding structure layout.

[0036] In this embodiment, a winding structure design is performed for multiple insulated core wires based on a core wire detection dataset to ultimately determine the multi-core winding structure layout. Key parameters for each core wire are first extracted from the core wire detection dataset, including core wire diameter, flexibility level, insulation thickness, and surface defect identification. Data screening is then used to remove records with outliers or missing items. All parameters are then normalized to ensure a uniform comparison scale for all data, supporting subsequent layout determination and pitch calculation.

[0037] The design method for the arrangement structure is then determined based on the selected multi-core arrangement guidance factor, and the arrangement guidance factor is converted into an arrangement framework on the cable core cross-section using a structural mapping method. For example, when the guidance factor is "layered winding," the cores are arranged into multiple concentric circular bands within the cross-section according to the process presets, with parameters such as the specific number of cores, interlayer spacing, and angular offset set for each layer. If the guidance factor is "concentric spiral winding," an equidistant spiral path is used to divide the cross-section into circumferential positions. Each position point is defined with a unique number, radius position, and target level, forming the basic framework for the core spatial layout.

[0038] The cores are then arranged one by one using a sequential matching method. Specifically, using flexibility as the core ranking criterion, the most flexible cores are prioritized for placement in areas with smaller inner diameters and lowest stress concentrations (such as the inner layer or around the central axis). Cores with lower flexibility or minor defects are assigned to outer layers or low-stress areas to avoid insulation damage due to insufficient curvature radius. Each core is assigned based on its position number within the structural template and matched to its characteristics until all cores are properly arranged within the layout.

[0039] After completing the core wire position allocation, the pitch planning method is executed to calculate the corresponding pitch for each core wire, combining the radial position of the core wire in the cross section and the length of the winding path. The pitch calculation process takes into account three aspects: the first is the radial position of the core wire in the cross section, that is, the distance between the core wire and the central axis of the cable core. The larger the distance, the longer the arc that its winding path needs to cover per unit length; the second is the length of the winding path, which depends on the length of the core wire required to wrap around the cable core for one circle, and is related to its radius and the cable core pitch angle; the third is the cable core tightness and molding stability in the process requirements. The tightness requirement determines that the winding pitch must avoid being too sparse or too dense to ensure that the overall structure of the cable is full and not loose; molding stability requires balanced winding tension to prevent structural deviation.

[0040] During the calculation process, the pitch is set using a linear function or a piecewise constant function model. Based on the core radius r and the helix angle θ, a preliminary estimate of the pitch p is made using the formula p = 2πr / tan(θ). The tan(θ) value is then adjusted based on the target density to accommodate the cable diameter control and wire density distribution required by the process. All pitch data is organized into a table corresponding to core number and pitch value, with information on the winding direction (clockwise or counterclockwise) and the starting point of each core's path.

[0041] Finally, the entire winding structure is verified using a spatial conflict detection method. The minimum spacing between any two core wires during the winding process is calculated one by one to determine if there is any overlap less than the set process safety distance (e.g., 1.5mm). If a conflict is found, the system returns to the pitch or position adjustment stage for fine-tuning until all core wires are routed without crossover or interference, meeting the requirements for layout independence and equipment processing tolerances.

[0042] Through the above steps, the multi-core winding structure layout is determined based on full consideration of the core wire performance, arrangement guidance factors and actual process characteristics of the winding path, and the spatial position, winding pitch, winding direction and tension area of ​​each core wire are output.

[0043] Step S300: making a control decision on the multi-core synchronous winding device according to the multi-core winding structure layout and the core wire detection data set to obtain a first synchronous winding control space.

[0044] In the present embodiment, a path trajectory calculation method is first used to calculate the spatial winding path of the core wires, combining the starting angle, winding radius, winding pitch, and winding direction information of each core wire in the multi-core winding structure layout. This path calculation is based on the radial position of the core wire in the cable core cross section. It is unfolded along the cable core axial direction and the angular changes and axial displacements during the winding process are calculated step by step to form a complete path coordinate point sequence.

[0045] Then, based on a tension segment mapping method, the corresponding winding tension is set using the flexibility level and insulation thickness fluctuation values ​​of each core wire in the core wire inspection data set as input. By searching a preset tension setting table, the flexibility level is mapped to a base tension value, which is then corrected and compensated for insulation thickness fluctuations. If the fluctuation exceeds the process threshold, the tension level is reduced to reduce local stress during the winding process. The resulting tension value becomes the target output parameter of the tension control device.

[0046] Next, a rhythm parameter matching method is used to determine the feed speed and movement time of each core during the synchronous winding process. The physical distance required for each core winding is calculated using the pitch information and path length provided by the winding structure layout. Combined with the preset cable core spindle speed, the required core feed rate per unit time is calculated. The rhythm parameters of all cores are synchronized through time alignment to ensure consistent tempo throughout the winding cycle, preventing structural misalignment or tension instability.

[0047] After the above parameters are generated, the path parameters, tension parameters, and cadence parameters for each core wire are combined into independent control decision units through a control instruction assembly method. These decision units include guide servo execution instructions, tension output instructions, and winding feed speed settings. After being bound to the core wire numbers, they form a structured control file that serves as a direct input to the device-side execution logic.

[0048] Finally, based on the control space construction method, all core wire control decision units are encapsulated into a multi-core winding control set, forming the first synchronous winding control space. This control space is composed of multiple winding control decisions, each covering the three dimensions of path control, tension control, and rhythm control. These decisions are independent of each other while maintaining coordinated synchronization at the execution level, ensuring that the multi-core synchronous winding device can achieve precise and coordinated operation.

[0049] Step S400: performing an insulation layer quality loss inspection on the first synchronous winding control space according to an insulation layer quality loss threshold to obtain a second synchronous winding control space.

[0050] In an embodiment of the present application, when performing insulation loss inspection on the first space of the synchronous winding control system based on the insulation loss threshold, the insulation loss prediction is first performed for each control decision in the first space of the synchronous winding control system based on the core wire detection data set, forming an insulation loss prediction sequence, i.e., a loss risk coefficient corresponding to each control decision. This sequence is then compared to determine whether each insulation loss prediction coefficient is less than the insulation loss threshold pre-set by technical experts, and a loss inspection result sequence is generated accordingly. Finally, based on this result sequence, the control decisions in the first space of the synchronous winding control system are optimized and eliminated, and control strategies within the acceptable insulation performance range are screened out to form a new control set, i.e., the second space of the synchronous winding control system.

[0051] Furthermore, in the method provided in the embodiment of the application, the insulation layer quality loss test is performed on the first synchronous winding control space according to the insulation layer quality loss threshold to obtain the second synchronous winding control space, and further includes:

[0052] Based on the core wire detection data set, the insulation layer quality loss of the first space of the synchronous winding control is predicted to obtain an insulation layer quality loss prediction sequence; it is determined whether each insulation layer quality loss prediction coefficient in the insulation layer quality loss prediction sequence is less than the insulation layer quality loss threshold to obtain a loss inspection result sequence; according to the loss inspection result sequence, the first space of the synchronous winding control is optimally screened to obtain the second space of the synchronous winding control.

[0053] In an embodiment of the present application, when predicting the insulation layer quality loss of the first synchronous winding control space based on the core wire detection data set, each synchronous winding control decision in the first synchronous winding control space is used as the first retrieval constraint, and the flexibility, insulation layer thickness fluctuation, defect mark and other attributes of the corresponding core wire in the core wire detection data set are used as the second retrieval constraint, and a winding device cluster is established in the networked multi-core synchronous winding devices of the same model. Through joint retrieval, winding quality samples under similar control parameters and core wire conditions are screened out from the historical operation data of the winding device cluster to form a first insulation layer quality loss retrieval set. Then, the representative insulation damage risk value is extracted from the sample set using the centralized value calculation method as the insulation layer quality loss prediction coefficient under this control decision. This process is repeated for all control decisions, and the insulation layer quality loss prediction sequence is generated and summarized in sequence.

[0054] Next, a threshold determination method is used to determine whether each insulation loss prediction coefficient within the insulation loss prediction sequence is less than the insulation loss threshold. Each insulation loss prediction coefficient in the prediction sequence is compared against the preset insulation loss threshold. If a prediction coefficient is less than the threshold, the control strategy will not cause significant insulation damage and is marked as "qualified." Otherwise, it is marked as "failed." This item-by-item comparison outputs a loss verification result sequence, which corresponds to the judgment result of whether each synchronous winding control decision meets the insulation protection requirements.

[0055] Finally, an optimization search and screening operation is performed based on the loss test result sequence to screen and reorganize the control decisions in the first space of synchronous winding control. Using the "threshold condition" as the screening logic, all control decisions with prediction coefficients less than the insulation quality loss threshold are extracted. These qualified control strategies are then combined into a new control set, which is the second space of synchronous winding control.

[0056] Furthermore, in the method provided in the embodiment of the application, the insulation layer quality loss prediction of the first space of the synchronous winding control is performed based on the core wire detection data set to obtain an insulation layer quality loss prediction sequence, and further includes:

[0057] Any synchronous winding control decision in the first space of the synchronous winding control is used as the first retrieval constraint, and the core wire detection data set is used as the second retrieval constraint; the multi-core synchronous winding device is interconnected with the same type of equipment to determine the winding device cluster; the winding device cluster is searched for insulation layer quality loss samples according to the first retrieval constraint and the second retrieval constraint to obtain a first insulation layer quality loss retrieval set; the first insulation layer quality loss retrieval set is calculated as a centralized value to obtain a first insulation layer quality loss prediction coefficient, and the first insulation layer quality loss prediction coefficient is added to the insulation layer quality loss prediction sequence.

[0058] In this embodiment, a feature parameter extraction method is first employed, taking any synchronous winding control decision in the first synchronous winding control space as input. The core control parameters of the decision, such as winding pitch, tension setting value, and path curvature, are extracted to form a structured control feature set as the first search constraint. Simultaneously, a physical attribute extraction method is used to extract information such as the core wire flexibility level, insulation thickness fluctuation range, and defect identification corresponding to the control decision from the core wire inspection dataset. After normalization, this information is used as the second search constraint to characterize the core wire's physical properties and its stress response capability.

[0059] Then, the equipment logic aggregation method is executed to cluster all multi-core synchronous winding devices according to conditions such as model and process consistency to form a cluster of winding devices with consistent data sources.

[0060] On this basis, through the historical data joint retrieval method, the aforementioned first and second retrieval constraints are used to conduct a joint query on the historical operation records in the winding device cluster to obtain the winding execution data that meets the dual conditions, and extract the insulation layer quality loss samples therein, that is, the insulation layer quality loss coefficient collected in the historical records, such as insulation compression ratio, crack occurrence probability, etc., to form a structured first insulation layer quality loss retrieval set.

[0061] The unweighted median statistical method is then applied to the retrieval set to sort the loss coefficients in the sample and extract their medians. This is used as a representative risk indicator for the current control decision, resulting in the first insulation layer quality loss prediction coefficient. This prediction coefficient is then added to the insulation layer quality loss prediction sequence.

[0062] The above process is repeated for each control decision in the first space of synchronous winding control, that is, feature parameter extraction, core wire attribute extraction, equipment cluster matching, historical sample retrieval and median statistics are performed in sequence for each decision, and finally a complete insulation layer quality loss prediction sequence is generated.

[0063] Step S500: performing multi-level joint optimization on the synchronous winding control second space according to the winding control evaluation model to obtain a synchronous winding control strategy.

[0064] In this embodiment of the present application, when performing a multi-level joint optimization search for the synchronous winding control second space based on a winding control evaluation model, the winding control evaluation expectations are first set, clarifying basic requirements such as winding efficiency constraints and cabling structure stability constraints. Then, based on the pre-trained winding control evaluation model, the control decisions in the synchronous winding control second space are preliminarily screened according to these expectations, and a synchronous winding control third space that meets the hard constraints is constructed. Next, weights are set for key performance indicators such as winding efficiency, cabling structure stability, and insulation layer quality loss, and a comprehensive evaluation winding control optimality function is established. Finally, with the goal of maximizing optimality, the control strategies in the third space are globally evaluated and screened, generating the optimal synchronous winding control strategy, which serves as the winding parameter configuration scheme executed by the final device.

[0065] Furthermore, in the method provided in the embodiment of the application, a multi-level joint optimization is performed on the second space of the synchronous winding control according to the winding control evaluation model to obtain a synchronous winding control strategy, which further includes:

[0066] A winding control evaluation expectation is set, wherein the winding control evaluation expectation includes a winding efficiency constraint and a cabling structure stability constraint; based on the winding control evaluation model, the second space of the synchronous winding control is optimized and screened according to the winding control evaluation expectation, and a third space of the synchronous winding control is constructed; weights are assigned to the winding control joint optimization indicators, and a winding control optimality function is constructed, wherein the winding control joint optimization indicators include winding efficiency, cabling structure stability and insulation layer quality loss; according to the winding control optimality function, the third space of the synchronous winding control is optimized to maximize the winding control optimality, and the synchronous winding control strategy is generated.

[0067] In this embodiment, the winding control evaluation expectations are first set. These expectations include winding efficiency constraints and cabling structure stability constraints. The winding efficiency constraint is used to limit the minimum winding length required per unit time to meet basic production cycle requirements. The cabling structure stability constraint is used to limit key indicators such as path deviation rate and tension fluctuation rate to ensure the uniformity and stability of the formed structure.

[0068] Based on the set winding control evaluation expectations, the winding control evaluation model is called to screen each control strategy in the second space of synchronous winding control one by one. Each synchronous winding control k-th decision is extracted in turn and passed as input to the winding control evaluation model along with its corresponding core wire detection data set for analysis. The model outputs the evaluation results of the control strategy, including the k-th winding efficiency coefficient and the k-th cabling structure stability coefficient. Based on the comparison of these two indicators with the evaluation expectations, if the efficiency and structural stability of the strategy meet the minimum standards, it will be added to the third space of synchronous winding control; otherwise, it will be removed. By executing this screening process for all strategies one by one, a third control subspace containing only qualified control strategies is finally constructed.

[0069] Next, the winding control joint optimization index is weighted and the winding control optimization function is constructed. The winding control joint optimization index includes three aspects: winding efficiency, cabling structure stability and insulation layer quality loss. Afterwards, technical experts set weight coefficients according to process priorities and construct a performance weighting mechanism. For example, the winding efficiency weight is 0.4, the cabling structure stability weight is 0.35, and the insulation layer quality loss weight is 0.25. Then, based on the above weight setting and normalization processing method, a winding control optimization function is constructed to perform a comprehensive score evaluation on each control strategy. The constructed winding control optimization function is ,in, is the winding efficiency corresponding to the kth decision of synchronous winding control, To synchronize the winding control, the stability of the cabling structure corresponding to the k-th decision is: is the insulation layer mass loss coefficient corresponding to the kth decision of synchronous winding control, To synchronize winding and control the maximum winding efficiency in the third space, Synchronous winding controls the maximum stability of the cable structure in the third space. The maximum value of the mass loss coefficient of the insulation layer in the third space is controlled for synchronous winding. 、 and They represent the winding efficiency weight, the cabling structure stability weight and the insulation layer quality loss weight respectively. The optimal winding control corresponding to the k-th decision of synchronous winding control is obtained.

[0070] Finally, the winding control optimality function is used to calculate all control strategies in the synchronous winding control third space one by one, sort them according to their scores, and perform optimality maximization screening. The strategy with the highest score is finally selected as the synchronous winding control strategy and used as the final device execution instruction.

[0071] Furthermore, in the method provided in the embodiment of the application, based on the winding control evaluation model, the second synchronous winding control space is optimized and screened according to the winding control evaluation expectation to construct the third synchronous winding control space, and further includes:

[0072] According to the second space of synchronous winding control, the kth decision of synchronous winding control is extracted, where k is a positive integer; the kth decision of synchronous winding control and the core wire detection data set are input into the winding control evaluation model to obtain the kth winding control evaluation result, wherein the kth winding control evaluation result includes the kth winding efficiency coefficient and the kth cabling structure stability coefficient; it is determined whether the kth winding control evaluation result meets the winding control evaluation expectation; if the kth winding control evaluation result meets the winding control evaluation expectation, the kth decision of synchronous winding control is added to the third space of synchronous winding control.

[0073] In the embodiment of the present application, the kth decision of synchronous winding control is first randomly extracted from the second space of synchronous winding control, where k is a positive integer. Then, the kth decision of synchronous winding control and the core wire detection data set are input into the pre-trained winding control evaluation model to obtain the kth winding control evaluation result. The kth winding control evaluation result includes the kth winding efficiency coefficient and the kth cabling structure stability coefficient . The winding control evaluation model is trained in advance based on historical winding process data. Its training data comes from the database of winding tasks that have been executed on industrial sites, and has clear structured input and performance output annotations. During the training stage, the input data of the winding control evaluation model includes key control parameters involved in the control strategy, such as winding pitch, path curvature, tension setting value, guide speed, etc., and is combined with the physical performance characteristics of the corresponding core wire in the core wire detection data, such as flexibility level, insulation thickness fluctuation range and defect marking information. These inputs together constitute a complete set of strategy feature vectors, which serve as a joint description of winding behavior and material state. The corresponding output data are performance indicators obtained by measurement and recording after the actual winding task is completed, including winding efficiency values ​​and cable structure stability indicators. The winding control evaluation model is obtained by integrating the input and output data for supervised learning training.

[0074] After obtaining the evaluation result of the k-th control strategy, a logical judgment is made between it and the set winding control evaluation expectation. The winding control evaluation expectation is the process baseline parameter set before optimization, including the minimum allowable value of winding efficiency and the minimum tolerance value of structural stability. It is the basic requirement for the control strategy in terms of executability and safety. With the lower efficiency limit, Compare and judge with the lower stability limit. If the kth control strategy meets or exceeds the set threshold for both indicators, it indicates that it has the ability to reach full production capacity and maintain stable molding quality in actual operation. The strategy is added to the third space of synchronous winding control. If any indicator fails to meet expectations, the strategy is directly eliminated and does not enter the next round of optimization.

[0075] Through the above processing flow, the construction of the synchronous winding control third space is completed.

[0076] Step S600: controlling the multi-core synchronous winding device to adaptively wind the multiple insulated core wires according to the synchronous winding control strategy.

[0077] In an embodiment of the present application, when a multi-core synchronous winding device is controlled according to a synchronous winding control strategy to adaptively wind multiple insulated core wires, the winding process's execution status is synchronously collected to form a core wire winding status monitoring set and a winding device status monitoring set. Anomaly detection is performed on each of these monitoring sets to identify possible core wire winding anomalies and device operation anomalies, and the core wire winding anomaly detection results and winding device anomaly detection results are output. Based on this, feedback adjustment is performed on the currently executed winding control strategy in combination with the detection results, achieving dynamic correction and stable control of the winding process.

[0078] Furthermore, in the method provided in the embodiment of the application, controlling the multi-core synchronous winding device to adaptively wind the multiple insulated core wires according to the synchronous winding control strategy further includes:

[0079] According to the synchronous winding control strategy, the multi-core synchronous winding device is controlled to wind the multiple insulated core wires to obtain a core wire winding state monitoring set and a winding device state monitoring set; anomaly detection is performed on the core wire winding state monitoring set and the winding device state monitoring set respectively to determine the core wire winding anomaly detection result and the winding device anomaly detection result; and the synchronous winding control strategy is feedback-adjusted according to the core wire winding anomaly detection result and the winding device anomaly detection result.

[0080] In the embodiments of the present application, a real-time data acquisition method is first used to acquire two types of monitoring data from the execution site while executing the control strategy. Specifically, according to the synchronous winding control strategy, the multi-core synchronous winding device is controlled to perform winding, and state information during operation is collected using displacement sensors and tension sensors on the winding guide pulleys and encoders on the actuator motors within the device. Data directly related to the core wire operation (such as the core wire path, tension curve, and arrangement position) is recorded as a core wire winding state monitoring set, and the device operating parameters (such as current changes, drive load, and speed fluctuations) are recorded as a winding device state monitoring set.

[0081] A fixed threshold judgment method is then used to perform anomaly detection on the two monitoring sets mentioned above. For the core wire winding status monitoring set, technical experts set standard indicators such as the tension deviation threshold and the path offset threshold. For example, if the tension deviation exceeds ±15%, or the path deviates from the target line by more than 2mm, it is considered an anomaly. For the winding device status monitoring set, it is determined whether the motor current exceeds the normal range or whether there is abnormal jitter in a certain section of the operating speed. In this way, the core wire winding anomaly detection results and the winding device anomaly detection results are output separately, with logical identifiers (such as normal / abnormal) or numerical identifiers (such as deviation rate) indicating whether the current execution status meets the strategy expectations.

[0082] Finally, a parameter fine-tuning correction method is used to implement feedback adjustments to the synchronous winding control strategy to address anomalies identified during the aforementioned testing. For core winding anomalies, the tension setpoint is automatically adjusted based on the direction of tension deviation, for example, by reducing the tension output to alleviate insulation stress. If path deviation is detected, the path guide angle is fine-tuned to achieve a corrective action. For winding device anomalies, the operating speed is reduced, the drive curve is adjusted, or a local resynchronization mechanism is triggered to ensure that the entire device operates within a controllable range. These adjustments are accomplished through real-time updates of the control strategy's internal parameters, enabling feedback adjustments to the synchronous winding control strategy.

[0083] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects:

[0084] The present application obtains the multi-core cable production demand corresponding to multiple insulated core wires, performs fitness analysis on the multivariate winding attribute factors in combination with the core wire detection data set, and determines the multi-core arrangement guiding factor; based on the core wire detection data set, the winding structure of the multiple insulated core wires is designed according to the multi-core arrangement guiding factor, and the multi-core winding structure layout is determined; control decisions are made on the multi-core synchronous winding device according to the multi-core winding structure layout and the core wire detection data set to obtain a first synchronous winding control space; an insulation layer quality loss test is performed on the first synchronous winding control space according to the insulation layer quality loss threshold to obtain a second synchronous winding control space; a multi-level joint optimization is performed on the second synchronous winding control space according to the winding control evaluation model to obtain a synchronous winding control strategy; the multi-core synchronous winding device is controlled according to the synchronous winding control strategy to perform adaptive winding on the multiple insulated core wires. The present invention solves the technical problems in the prior art that the insulation layer is easily damaged during the high-density winding process of multi-core cables and the winding control lacks an adaptive adjustment mechanism. By constructing a fitness analysis mechanism of multivariate winding attribute factors, a hierarchical control strategy for synchronous winding space and a multi-level joint optimization model, the technical effect of improving the winding quality of the insulation layer and realizing adaptive control of the winding process is achieved.

[0085] Embodiment 2 is based on the same inventive concept as the method for optimizing the quality of the insulation layer in high-density winding of multi-core cables in the above embodiment. Figure 2 As shown, the present application provides a system for optimizing the quality of the insulation layer in high-density winding of multi-core cables. The system and method embodiments in the present application are based on the same inventive concept. The system includes:

[0086] The fitness analysis module 11 is used to obtain the multi-core cable production requirements corresponding to multiple insulated core wires, perform fitness analysis on the multivariate winding attribute factors in combination with the core wire detection data set, and determine the multi-core arrangement guiding factor; the winding structure design module 12 is used to design the winding structure of the multiple insulated core wires based on the multi-core arrangement guiding factor based on the core wire detection data set, and determine the multi-core winding structure layout; the control decision module 13 is used to make control decisions on the multi-core synchronous winding device according to the multi-core winding structure layout and the core wire detection data set, and obtain the first synchronous winding control space; the loss inspection module 14 is used to perform insulation layer quality loss inspection on the first synchronous winding control space according to the insulation layer quality loss threshold, and obtain the second synchronous winding control space; the joint optimization module 15 is used to perform multi-level joint optimization on the second synchronous winding control space according to the winding control evaluation model to obtain the synchronous winding control strategy; the adaptive winding module 16 is used to control the multi-core synchronous winding device to perform adaptive winding on the multiple insulated core wires according to the synchronous winding control strategy.

[0087] Furthermore, the system is also used to implement the following functions:

[0088] The multivariate winding attribute factors include concentric spiral winding, layered structure winding, non-uniform pitch winding and programmable pitch winding; the fitness of the multivariate winding attribute factors is evaluated according to the multi-core cable production requirements and the core wire detection data set, and a winding attribute fitness evaluation table is constructed; the multivariate winding attribute factors are screened for winding attribute fitness maximization according to the winding attribute fitness evaluation table to obtain the multi-core arrangement guiding factor.

[0089] Furthermore, the system is also used to implement the following functions:

[0090] According to the multi-core cable production requirements, the multi-component winding property factors are evaluated for matching, and a first winding property matching evaluation matrix is ​​obtained; according to the core wire detection data set, the multi-component winding property factors are evaluated for matching, and a second winding property matching evaluation matrix is ​​obtained; according to the winding property fitness weight condition, the first winding property matching evaluation matrix and the second winding property matching evaluation matrix are weighted calculated to generate the winding property fitness evaluation table.

[0091] Furthermore, the system is also used to implement the following functions:

[0092] Based on the core wire detection data set, the insulation layer quality loss of the first space of the synchronous winding control is predicted to obtain an insulation layer quality loss prediction sequence; it is determined whether each insulation layer quality loss prediction coefficient in the insulation layer quality loss prediction sequence is less than the insulation layer quality loss threshold to obtain a loss inspection result sequence; according to the loss inspection result sequence, the first space of the synchronous winding control is optimally screened to obtain the second space of the synchronous winding control.

[0093] Furthermore, the system is also used to implement the following functions:

[0094] Any synchronous winding control decision in the first space of the synchronous winding control is used as the first retrieval constraint, and the core wire detection data set is used as the second retrieval constraint; the multi-core synchronous winding device is interconnected with the same type of equipment to determine the winding device cluster; the winding device cluster is searched for insulation layer quality loss samples according to the first retrieval constraint and the second retrieval constraint to obtain a first insulation layer quality loss retrieval set; the first insulation layer quality loss retrieval set is calculated as a centralized value to obtain a first insulation layer quality loss prediction coefficient, and the first insulation layer quality loss prediction coefficient is added to the insulation layer quality loss prediction sequence.

[0095] Furthermore, the system is also used to implement the following functions:

[0096] A winding control evaluation expectation is set, wherein the winding control evaluation expectation includes a winding efficiency constraint and a cabling structure stability constraint; based on the winding control evaluation model, the second space of the synchronous winding control is optimized and screened according to the winding control evaluation expectation, and a third space of the synchronous winding control is constructed; weights are assigned to the winding control joint optimization indicators, and a winding control optimality function is constructed, wherein the winding control joint optimization indicators include winding efficiency, cabling structure stability and insulation layer quality loss; according to the winding control optimality function, the third space of the synchronous winding control is optimized to maximize the winding control optimality, and the synchronous winding control strategy is generated.

[0097] Furthermore, the system is also used to implement the following functions:

[0098] According to the second space of synchronous winding control, the kth decision of synchronous winding control is extracted, where k is a positive integer; the kth decision of synchronous winding control and the core wire detection data set are input into the winding control evaluation model to obtain the kth winding control evaluation result, wherein the kth winding control evaluation result includes the kth winding efficiency coefficient and the kth cabling structure stability coefficient; it is determined whether the kth winding control evaluation result meets the winding control evaluation expectation; if the kth winding control evaluation result meets the winding control evaluation expectation, the kth decision of synchronous winding control is added to the third space of synchronous winding control.

[0099] Furthermore, the system is also used to implement the following functions:

[0100] According to the synchronous winding control strategy, the multi-core synchronous winding device is controlled to wind the multiple insulated core wires to obtain a core wire winding state monitoring set and a winding device state monitoring set; anomaly detection is performed on the core wire winding state monitoring set and the winding device state monitoring set respectively to determine the core wire winding anomaly detection result and the winding device anomaly detection result; and the synchronous winding control strategy is feedback-adjusted according to the core wire winding anomaly detection result and the winding device anomaly detection result.

[0101] Example three. Based on the inventive concept of the method for optimizing the quality of the insulation layer in high-density winding of multi-core cables in the above-mentioned example, the present application also provides an electronic device, comprising: at least one processor; a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the steps of any one of the methods described in the above-mentioned example one.

[0102] Figure 3 This is a schematic diagram of the structure of an exemplary electronic device of this application. Figure 3 In the figure, the bus architecture is represented by bus 300, which can include any number of interconnected buses and bridges. Bus 300 connects various circuits including one or more processors represented by processor 302 and memory represented by memory 304. Bus 300 can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are all well known in the art and therefore will not be described further herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. Receiver 301 and transmitter 303 can be the same component, namely a transceiver, which provides a unit for communicating with various other devices over a transmission medium. Processor 302 is responsible for managing bus 300 and general processing, while memory 304 can be used to store data used by processor 302 when performing operations.

[0103] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0104] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

[0105] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. A method for optimizing the quality of the insulation layer in high-density winding of multi-core cables, characterized in that: include: Obtain the multi-core cable production requirements corresponding to multiple insulated cores, perform fitness analysis on the multi-element winding attribute factors based on the core detection data set, and determine the multi-core arrangement guidance factor; Based on the core wire detection data set, performing winding structure design on the plurality of insulated core wires according to the multi-core arrangement guiding factor to determine a multi-core winding structure layout; Making a control decision on the multi-core synchronous winding device according to the multi-core winding structure layout and the core wire detection data set to obtain a first synchronous winding control space; Performing an insulation layer quality loss inspection on the first synchronous winding control space according to an insulation layer quality loss threshold to obtain a second synchronous winding control space; Performing multi-level joint optimization on the second space of synchronous winding control according to the winding control evaluation model to obtain a synchronous winding control strategy; Controlling the multi-core synchronous winding device to adaptively wind the multiple insulated core wires according to the synchronous winding control strategy; Performing an insulation layer quality loss inspection on the first synchronous winding control space according to an insulation layer quality loss threshold to obtain a second synchronous winding control space includes: Performing insulation layer quality loss prediction on the synchronous winding control first space based on the core wire detection data set to obtain an insulation layer quality loss prediction sequence; determining whether each insulation layer quality loss prediction coefficient in the insulation layer quality loss prediction sequence is less than the insulation layer quality loss threshold, and obtaining a loss inspection result sequence; The first synchronous winding control space is optimally selected according to the loss inspection result sequence to obtain the second synchronous winding control space.

2. The method for optimizing the quality of the insulation layer in high-density winding of a multi-core cable according to claim 1, characterized in that: Obtain the multi-core cable production requirements corresponding to multiple insulated cores, perform fitness analysis on the multi-element winding attribute factors based on the core detection data set, and determine the multi-core arrangement guidance factors, including: The multi-element winding attribute factors include concentric spiral winding, layered structure winding, non-uniform pitch winding and programmable pitch winding; Performing fitness evaluation on the multi-element winding attribute factors according to the multi-core cable production requirements and the core wire detection data set, and constructing a winding attribute fitness evaluation table; The multi-element winding attribute factor is screened for winding attribute fitness maximization according to the winding attribute fitness evaluation table to obtain the multi-core arrangement guiding factor.

3. The method for optimizing the quality of the insulation layer in high-density winding of a multi-core cable according to claim 2, characterized in that: The fitness evaluation of the multi-element winding attribute factors is performed according to the multi-core cable production requirements and the core wire detection data set, and a winding attribute fitness evaluation table is constructed, including: Performing a matching evaluation on the multi-element winding property factors according to the multi-core cable production requirements to obtain a first winding property matching evaluation matrix; Performing a matching evaluation on the multivariate winding attribute factors according to the core wire detection data set to obtain a second winding attribute matching evaluation matrix; According to the entanglement attribute fitness weight condition, a weighted calculation is performed on the entanglement attribute matching evaluation first matrix and the entanglement attribute matching evaluation second matrix to generate the entanglement attribute fitness evaluation table.

4. The method for optimizing the quality of the insulation layer in high-density winding of a multi-core cable according to claim 1, wherein: Predicting insulation layer quality loss in the synchronous winding control first space based on the core wire detection data set to obtain an insulation layer quality loss prediction sequence includes: Taking any synchronous winding control decision in the first synchronous winding control space as a first search constraint and taking the core wire detection data set as a second search constraint; Interconnecting the multi-core synchronous winding devices with the same model to determine a winding device cluster; Performing an insulation layer quality loss sample search on the winding device cluster according to the first search constraint and the second search constraint to obtain a first insulation layer quality loss search set; A centralized value calculation is performed on the first insulating layer mass loss retrieval set to obtain a first insulating layer mass loss prediction coefficient, and the first insulating layer mass loss prediction coefficient is added to the insulating layer mass loss prediction sequence.

5. The method for optimizing the quality of the insulation layer in high-density winding of a multi-core cable according to claim 1, wherein: A multi-level joint optimization is performed on the second space of the synchronous winding control according to the winding control evaluation model to obtain a synchronous winding control strategy, including: Setting a winding control evaluation expectation, wherein the winding control evaluation expectation includes a winding efficiency constraint and a cabling structure stability constraint; Based on the winding control evaluation model, the second synchronous winding control space is optimized and screened according to the winding control evaluation expectation to construct a third synchronous winding control space; Weights are assigned to winding control joint optimization indicators to construct a winding control optimization function, wherein the winding control joint optimization indicators include winding efficiency, cabling structure stability, and insulation layer quality loss; The synchronous winding control strategy is generated by optimizing the winding control quality by maximizing the winding control quality of the synchronous winding control third space according to the winding control quality function.

6. The method for optimizing the quality of the insulation layer in high-density winding of a multi-core cable according to claim 5, characterized in that: Based on the winding control evaluation model, the second synchronous winding control space is optimized and screened according to the winding control evaluation expectation to construct a third synchronous winding control space, including: Extracting a k-th decision of the synchronous winding control according to the second synchronous winding control space, where k is a positive integer; Inputting the kth synchronous winding control decision and the core wire detection data set into the winding control evaluation model to obtain a kth winding control evaluation result, wherein the kth winding control evaluation result includes a kth winding efficiency coefficient and a kth cabling structure stability coefficient; determining whether the kth winding control evaluation result meets the winding control evaluation expectation; If the k-th winding control evaluation result meets the winding control evaluation expectation, the k-th synchronous winding control decision is added to the synchronous winding control third space.

7. The method for optimizing the quality of the insulation layer in high-density winding of a multi-core cable according to claim 1, characterized in that: Controlling the multi-core synchronous winding device to adaptively wind the multiple insulated core wires according to the synchronous winding control strategy includes: Controlling the multi-core synchronous winding device to wind the multiple insulated core wires according to the synchronous winding control strategy to obtain a core wire winding state monitoring set and a winding device state monitoring set; Performing abnormality detection on the core wire winding state monitoring set and the winding device state monitoring set respectively, and determining a core wire winding abnormality detection result and a winding device abnormality detection result; Feedback adjustment is performed on the synchronous winding control strategy according to the core wire winding abnormality detection result and the winding device abnormality detection result.

8. The insulation layer quality optimization system for multi-core cable high-density winding is characterized by: The system comprises: The fitness analysis module is used to obtain the multi-core cable production requirements corresponding to multiple insulated cores, perform fitness analysis on the multi-element winding attribute factors based on the core detection data set, and determine the multi-core arrangement guidance factors; a winding structure design module, configured to perform winding structure design on the plurality of insulated core wires based on the core wire detection data set and the multi-core arrangement guide factor, and determine a multi-core winding structure layout; A control decision module, configured to make a control decision on the multi-core synchronous winding device according to the multi-core winding structure layout and the core wire detection data set, and obtain a first synchronous winding control space; a loss inspection module, configured to perform an insulation layer quality loss inspection on the first synchronous winding control space according to an insulation layer quality loss threshold, and obtain a second synchronous winding control space; A joint optimization module, configured to perform multi-level joint optimization on the synchronous winding control second space according to a winding control evaluation model to obtain a synchronous winding control strategy; An adaptive winding module, configured to control the multi-core synchronous winding device to perform adaptive winding on the multiple insulated core wires according to the synchronous winding control strategy; The system is also used to implement the following functions: Based on the core wire detection data set, the insulation layer quality loss of the first space of the synchronous winding control is predicted to obtain an insulation layer quality loss prediction sequence; it is determined whether each insulation layer quality loss prediction coefficient in the insulation layer quality loss prediction sequence is less than the insulation layer quality loss threshold to obtain a loss inspection result sequence; according to the loss inspection result sequence, the first space of the synchronous winding control is optimally screened to obtain the second space of the synchronous winding control.

9. An electronic device, characterized in that: The electronic device comprises: a memory for storing executable instructions; The processor is configured to implement the method for optimizing the quality of the insulation layer in high-density winding of a multi-core cable according to any one of claims 1 to 7 when executing the executable instructions stored in the memory.

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