Dyeing formula intelligent conversion control method and system for sock production

Abstract

The invention relates to the technical field of program control, in particular to a dyeing formula intelligent conversion control method and system for sock production, and the method comprises the steps: building a conversion control model through collecting product data and preset data, automatically dividing a processing region, and calculating the amount of a processing agent; and performing dynamic compensation by combining a material type correction coefficient and a density-permeability relation. And performing regional processing by using the processing hue and the compensated dosage, constructing an automatic control model to compare the processing data with a preset value in real time, and automatically adjusting the processing time, temperature and pH value until reaching the standard when the deviation exceeds the limit, thereby realizing accurate closed-loop control of the dyeing process.

Description

Technical Field

[0001] The present invention relates to the technical field of program control, and in particular to a dyeing formula intelligent conversion control method and system for socks production. Background Art

[0002] In the production process, the adaptive control system can automatically adjust its own parameters according to predetermined criteria to achieve optimal performance, and has been applied in many industrial fields; however, in the field of dyeing formula control, the existing system still has obvious deficiencies in dealing with complex working conditions. The current system lacks sufficient adaptive adjustment capabilities when dealing with real-time changes in process parameters, and cannot automatically optimize the type and amount of dyes based on real-time collected data, resulting in unsatisfactory dyeing effects; at the same time, due to fluctuations in environmental conditions such as temperature and humidity, the system's response speed and intelligence level are insufficient, affecting the stability and consistency of the dyeing process. In addition, the existing adaptive control algorithms often exhibit the defects of slow convergence and poor stability when dealing with nonlinear and multivariable coupling problems in the dyeing process, which limits their application in actual production.

[0003] To this end, a dyeing formula intelligent conversion control method and system for socks production are proposed. Summary of the invention

[0004] The object of the present invention is to provide a dyeing formula intelligent conversion control method and system for hosiery production, by collecting first product data and preset data of a product to be processed; constructing a conversion control model to analyze the preset data, obtaining a product processing area, and combining the first product data to obtain the product area processing color tone and product area processing dosage; the dosage control is specifically as follows: based on the product processing area area, material and target color concentration, the initial treatment agent dosage is calculated; the initial treatment agent dosage is controlled in combination with the correction coefficient of the material type for the material absorption rate; based on the material density and the dye penetration depth, the treatment agent dosage is dynamically compensated to obtain the first processing data; a processing condition automatic control model is constructed to obtain the processing deviation; the processing time, processing temperature and processing pH value are controlled to reduce the processing deviation.

[0005] To achieve the above object, the present invention provides the following technical solutions: A dyeing formula intelligent conversion control method for hosiery production, comprising: Collecting first product data of the product to be processed; obtaining preset data of the product to be processed; Construct a conversion control model to analyze the preset data and obtain the product processing area; and obtain the product area processing color tone and product area processing amount by analyzing the product processing area and the first product data; the control of the product area processing amount is specifically as follows: based on the area of ​​the product processing area, the water absorption rate of the material and the target color concentration, calculate the initial treatment agent amount; adjust and control the initial treatment agent amount in combination with the correction coefficient of the material type for the material absorption rate; dynamically compensate and control the treatment agent amount according to the relationship between the material density and the dye penetration depth; Divide the product to be processed into regions according to the product processing regions to obtain the product regions to be processed; and process the product regions to be processed according to the product region processing color tone and the product region processing amount to obtain first processing data; The processing condition automatic control model is constructed to obtain the processing deviation by comparing the first processing data with the preset data; when the processing deviation is greater than the preset processing deviation, the processing time, processing temperature and processing pH value are controlled until the processing deviation is less than the preset processing deviation.

[0006] Preferably, the first product data includes sock material, material ratio, fabric structure, fabric tension, knitting density and color; the preset data includes target color, dye type and dye ratio; the first processing data includes actual dyed color, dyeing amount, actual dyeing time, actual temperature and actual pH value.

[0007] Preferably, the conversion control model includes a sock dyeing data processing and analysis layer, a sock dyeing area division layer, a regional dyeing hue control layer and a regional dyeing dosage control layer; the sock dyeing data processing and analysis layer obtains sock feature data by preprocessing and extracting features from the first product data; the sock dyeing area division layer divides the sock feature data into regions by a clustering algorithm to obtain product processing areas, boundaries and identifications of different dyeing areas; the regional dyeing hue control layer analyzes the product processing areas, boundaries, identifications and first product data of different dyeing areas by a color matching algorithm to obtain product area processing hues; the regional dyeing dosage control layer analyzes the product processing areas, boundaries, identifications and first product data of different dyeing areas based on material properties and dye dosage of the target color to obtain product area processing dosage.

[0008] Preferably, the regional dyeing tone control layer also includes control of the superposition of multiple colors in the same region, and the specific process is: according to the design pattern and color of the socks, the color type required for each layer of dyeing is analyzed; the initial value of each color is obtained to determine the initial value of each layer of color by combining the color type, the socks material and the dyeing characteristics of the dye; the superposition order of each color is determined by analyzing the interaction between the dyeing process and the multiple colors; the initial value of each layer of color is corrected by a color matching algorithm, and the corrected color parameters are generated by combining the material absorptivity and reflectivity of the socks material and the superposition influence coefficient of the adjacent color layers; based on the corrected color parameters and the superposition order, the actual color chromaticity of each layer of color after superposition is obtained; the actual color is compared with the target color, and if the color difference value exceeds the preset threshold, the color parameters or the superposition order are dynamically adjusted until the color accuracy requirement is met; the specific process is: according to the color difference value distribution, the level where the color deviation is generated is located; if the deviation comes from the single-layer color parameter, the concentration and ratio of the color of the layer are adjusted based on the dye concentration-color rendering relationship; if the deviation comes from the interference of multi-layer superposition, the superposition order is recalculated through the color superposition simulation model, and the superposition color compensation value is updated.

[0009] Preferably, the processing condition automatic control model includes a data acquisition layer, a deviation analysis layer and a parameter control layer; The data acquisition layer obtains the dyeing condition deviation by analyzing the first processed data and the preset data; the dyeing condition deviation includes the temperature difference , pH difference in dyeing and dyeing time difference The deviation analysis layer analyzes the dyeing condition deviation, the color difference between the first processed data and the preset data through a multi-objective weighted fusion algorithm to obtain a comprehensive dyeing deviation value. The parameter control layer controls the comprehensive dyeing deviation value through the PID control algorithm. Controls were performed to obtain adjusted dyeing time, temperature and pH value.

[0010] Preferably, the comprehensive staining deviation value The specific calculation formula is: ; in, is the color difference dynamic weight, is the color difference, is the dynamic weight of the coloring condition deviation, For preset time, To preset pH value, is the preset temperature.

[0011] An intelligent dyeing formula conversion control system for hosiery production, comprising: A multi-parameter acquisition module, used for acquiring first product data of the product to be processed and preset data of the product to be processed; The conversion control model building module is used to build a conversion control model to analyze the preset data and obtain the product processing area; and obtain the product area processing color tone and product area processing amount by analyzing the product processing area and the first product data; the control of the product area processing amount is specifically as follows: based on the area of ​​the product processing area, the water absorption rate of the material and the target color concentration, the initial treatment agent amount is calculated; combined with the correction coefficient of the material type for the material absorption rate, the initial treatment agent amount is adjusted and controlled; according to the relationship between the material density and the dye penetration depth, the treatment agent amount is dynamically compensated and controlled; The dyeing control module for the product to be processed is used to divide the product to be processed into regions according to the product processing regions to obtain the product regions to be processed; and to process the product regions to be processed according to the product region processing color tone and the product region processing amount to obtain the first processing data; The dyeing adaptive parameter adjustment control module constructs an automatic control model for processing conditions to obtain the processing deviation by comparing the first processing data with the preset data; when the processing deviation is greater than the preset processing deviation, the processing time, processing temperature and processing pH value are controlled until the processing deviation is less than the preset processing deviation.

[0012] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention realizes intelligent control of sock dyeing by constructing a conversion control model and an automatic control model for processing conditions. By automatically collecting and analyzing sock data and preset data, the dyeing area is accurately divided, and the dyeing tone and amount are intelligently adjusted. By real-time monitoring of processing deviations and automatically adjusting dyeing conditions, the consistency and stability of dyeing quality are significantly improved.

[0013] 2. The conversion control model provided by the present invention uses a clustering algorithm to divide the characteristic data of socks into regions, and combines the color matching algorithm to accurately control the dyeing tone and dosage of each region. When multiple layers of color are superimposed, the design pattern is analyzed, the color parameters are corrected, and the superposition order is optimized to ensure that the final color effect is consistent with the target. At the same time, when calculating the amount of dye, factors such as the area of ​​the product treatment area, the water absorption rate of the material, and the target color concentration are comprehensively considered, and the correction coefficient of the material type on the material absorption rate and the dynamic compensation mechanism of the material density and the dye penetration depth are introduced to ensure the optimization of the dosage.

[0014] 3. The present invention monitors the deviation in the dyeing process in real time through the processing condition automatic control model; the first processing data and the preset data are analyzed by the data acquisition layer to obtain the temperature difference, pH difference and time difference; the deviation analysis layer uses a multi-objective weighted fusion algorithm to analyze these deviations and color differences to obtain a comprehensive deviation value; the parameter control layer uses a PID control algorithm to analyze the comprehensive deviation value and adjust the dyeing time, temperature and pH value. The present invention dynamically adjusts the dyeing time, temperature and pH value by using a PID control algorithm, quickly responds to process changes, adjusts parameters to adapt to a variety of production scenarios, controls the processing deviation within a preset range, and ensures the stability of product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The present invention provides a flow chart of a dyeing formula intelligent conversion control method for socks production; Figure 2 The present invention provides a structural schematic diagram of a dyeing formula intelligent conversion control system for socks production; Figure 3 A schematic diagram of the conversion control model structure provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Embodiment 1 See also Figure 1 to Figure 2 The present invention provides a dyeing formula intelligent conversion control method for socks production, which is applied to a dyeing formula intelligent conversion control system for socks production. The technical solution is as follows: Collecting first product data of the product to be processed; obtaining preset data of the product to be processed; Construct a conversion control model to analyze the preset data and obtain the product processing area; and obtain the product area processing color tone and product area processing amount by analyzing the product processing area and the first product data; the control of the product area processing amount is specifically as follows: based on the area of ​​the product processing area, the water absorption rate of the material and the target color concentration, calculate the initial treatment agent amount; adjust and control the initial treatment agent amount in combination with the correction coefficient of the material type for the material absorption rate; dynamically compensate and control the treatment agent amount according to the relationship between the material density and the dye penetration depth; Divide the product to be processed into regions according to the product processing regions to obtain the product regions to be processed; and process the product regions to be processed according to the product region processing color tone and the product region processing amount to obtain first processing data; The processing condition automatic control model is constructed to obtain the processing deviation by comparing the first processing data with the preset data; when the processing deviation is greater than the preset processing deviation, the processing time, processing temperature and processing pH value are controlled until the processing deviation is less than the preset processing deviation.

[0018] Furthermore, the first product data includes sock material, material ratio, fabric structure, fabric tension, knitting density and color; the preset data includes target color, dye type and dye ratio; the first processing data includes actual dyed color, dyeing amount, actual dyeing time, actual temperature and actual pH value.

[0019] In this embodiment, by clarifying the specific contents of the first product data (including materials, fabric structure, etc.), the preset data (target color, dye ratio) and the first processing data (actual color, dosage, etc.), the method makes dyeing control more accurate. Detailed data collection and analysis realizes comprehensive monitoring of the dyeing process and ensures the accuracy and consistency of the dyeing effect. This data-driven control method improves the scientificity and predictability of the process and provides a solid foundation for high-quality dyeing.

[0020] Furthermore, the conversion control model includes a sock dyeing data processing and analysis layer, a sock dyeing area division layer, a regional dyeing color tone control layer and a regional dyeing amount control layer, see Figure 3 ; The sock dyeing data processing and analysis layer obtains the sock feature data by preprocessing and extracting features from the first product data; the sock dyeing area division layer divides the sock feature data into regions by a clustering algorithm to obtain product processing areas and boundaries and logos of different dyeing areas; the regional dyeing tone control layer analyzes the product processing areas and boundaries, logos and the first product data of different dyeing areas by a color matching algorithm to obtain product regional processing tones; the regional dyeing dosage control layer analyzes the product processing areas and boundaries, logos and the first product data of different dyeing areas based on material properties and dye dosage of the target color to obtain product regional processing dosage.

[0021] In this embodiment, the conversion control model enhances the flexibility and adaptability of dyeing control through a multi-level design of data processing, area division, color tone control and dosage control. According to the characteristics of different socks, clustering algorithm and color matching algorithm are used to realize personalized dyeing management, which improves the effect and stability of the dyeing process. This structured design provides systematic support for complex dyeing tasks and ensures efficient processing of diversified socks; compared with the adaptive control algorithm, the conversion control model provided in this embodiment has greatly improved dyeing accuracy, area division time, treatment agent dosage error and complex pattern qualification rate, please refer to Table 1 for details; Table 1 Transformation control model effectiveness table

[0022] Furthermore, the regional dyeing tone control layer also includes control of multi-layer color superposition in the same region, and the specific process is: according to the design pattern and color of the socks, the color type required for each layer of dyeing is analyzed; the initial value of each color is obtained to determine the initial value of each layer of color by combining the color type, the socks material and the dyeing characteristics of the dye; the superposition order of each color is determined by analyzing the interaction between the dyeing process and the multi-layer color; the initial value of each layer of color is corrected by the color matching algorithm, and the corrected color parameters are generated by combining the material absorption rate and reflectivity of the socks material and the superposition influence coefficient of the adjacent color layers; based on the corrected color parameters and the superposition order, the actual color chromaticity of each layer of color after superposition is obtained; the actual color is compared with the target color, and if the color difference value exceeds the preset threshold, the color parameter or the superposition order is dynamically adjusted until the color accuracy requirement is met; the specific process is: according to the color difference value distribution, the level where the color deviation is generated is located; if the deviation comes from the single-layer color parameter, the concentration and ratio of the color of the layer are adjusted based on the dye concentration-color rendering relationship; if the deviation comes from the multi-layer superposition interference, the superposition order is recalculated through the color superposition simulation model, and the superposition color compensation value is updated.

[0023] In this embodiment, the multi-layer color superposition control of the regional dyeing tone control layer significantly improves the accuracy of complex pattern dyeing by analyzing the design pattern, correcting the color parameters and optimizing the superposition order. The color parameters are dynamically adjusted in combination with the material characteristics of the socks to ensure that the multi-layer superposition effect is consistent with the target and meets the high-precision requirements, as shown in Table 2. This mechanism provides support for design innovation while ensuring the quality of product appearance.

[0024] Table 2 Multi-layer color overlay correction effect verification table

[0025] Furthermore, the processing condition automatic control model includes a data acquisition layer, a deviation analysis layer and a parameter regulation layer; The data acquisition layer obtains the dyeing condition deviation by analyzing the first processed data and the preset data; the dyeing condition deviation includes the temperature difference , pH difference in dyeing and dyeing time difference The deviation analysis layer analyzes the dyeing condition deviation, the color difference between the first processed data and the preset data through a multi-objective weighted fusion algorithm to obtain a comprehensive dyeing deviation value. The parameter control layer controls the comprehensive dyeing deviation value through the PID control algorithm. The analysis was performed to obtain the adjusted dyeing time, temperature and pH value.

[0026] In this embodiment, the processing condition automatic control model realizes real-time monitoring and dynamic adjustment of the dyeing process through a multi-layer design of data collection, deviation analysis and parameter regulation. The multi-objective weighted fusion and PID control algorithm are used to ensure the precise control of the dyeing conditions, improve the stability and reliability of the dyeing quality, reduce human errors, and improve production efficiency.

[0027] Furthermore, the comprehensive staining deviation value The specific calculation formula is: ; in, is the color difference dynamic weight, is the color difference, is the dynamic weight of the coloring condition deviation, For preset time, To preset pH value, is the preset temperature.

[0028] In this embodiment, by combining the specific calculation formula of the dyeing deviation value, dynamic weight and multi-objective weighted fusion algorithm, the method realizes comprehensive evaluation and precise control of the processing deviation. This quantitative method enhances the controllability of the dyeing process, ensures that the dyeing effect closely matches the preset target, and provides a scientific basis and process consistency for high-quality dyeing.

[0029] Furthermore, it also includes a dyeing area dynamic exchange control process, specifically: After the dyeing process of the current dyeing area is completed, the dyeing area swap control is realized through the following steps: Area dyeing completion judgment: Real-time monitoring of the actual color parameters, treatment agent dosage and processing time of the current dyeing area; calculation of the color difference between the actual color parameters and the target color in the preset data. If the color difference is ≤1.5 and the treatment agent dosage error is ≤5%, the dyeing of the area is determined to be completed; simultaneous verification of whether the dyeing time meets the preset process requirements, if it exceeds the time limit, the alarm mechanism is triggered.

[0030] Next dye region matching logic: Region selection strategy: Based on the region identification sequence generated by the sock dyeing region division layer, the next region is matched according to the following priority: Areas with the same color requirements have the highest priority to reduce the number of dye switching times; areas with adjacent physical locations have second priority to shorten the robot's movement path; areas with complex patterns are processed in advance to avoid dye penetration interference.

[0031] Color Matching Controls: The color matching algorithm in the regional dyeing tone control layer is called to extract the target color parameters of the next area. If the color difference between adjacent areas exceeds the preset color difference, the dye pipeline cleaning process is automatically inserted. Combined with the dynamic correction parameters of the material water absorption rate, the initial dyeing parameters of the next area are generated.

[0032] Dyeing equipment linkage control: The robotic arm positioning system moves the socks to the coordinate position of the next dyeing area; the dye injection system automatically adjusts the nozzle pressure according to the new area and fabric tension; based on the material density-penetration depth relationship model, the dyeing temperature curve corresponding to the area is reloaded.

[0033] The dynamic switching control of the dyeing area added in this embodiment realizes efficient switching of the dyeing area through color difference threshold judgment and multi-dimensional matching strategy. Please refer to Table 3 for details.

[0034] Table 3 Regional exchange control effect verification table

[0035] The present invention realizes accurate management of the dyeing process of socks through intelligent dyeing formula conversion control. By using the conversion control model and the processing condition automatic control model, the first product data and preset data of the socks are automatically analyzed, the dyeing area is accurately divided, and the dyeing tone and dosage are dynamically adjusted to ensure that the dyeing effect is highly consistent with the preset target. This intelligent control significantly reduces the dependence on manual experience and improves the stability of production efficiency and product quality. In particular, in complex design and multi-color dyeing scenarios, the amount of dye is dynamically adjusted based on the area, material water absorption, target color concentration and fabric characteristics, which optimizes resource utilization efficiency and reduces production costs. At the same time, the processing condition automatic control model dynamically adjusts the dyeing time, temperature and pH value by comparing the first processing data with the preset data in real time, reduces rework caused by uneven dyeing or color difference, and ensures the stability and reliability of the dyeing process. This method provides enterprises with an efficient and economical production solution, enhances the flexibility and market competitiveness of the process, and is suitable for diversified sock dyeing needs.

[0036] Embodiment 2 In the production process, the dyeing process is an important link to ensure product quality and appearance. The process is dynamically affected by multiple factors such as dye adsorption characteristics, process parameters, and environmental temperature and humidity, which places extremely high demands on the precise control of the dyeing formula. The adaptive control system can automatically adjust its own parameters according to predetermined criteria to achieve optimal performance, and has been applied in many industrial fields. The present invention provides a dyeing formula intelligent conversion control method for socks production, which is applied to a dyeing formula intelligent conversion control system for socks production; wherein the dyeing formula intelligent conversion control system for socks production includes a multi-parameter acquisition module, a conversion control model construction module, a product dyeing control module to be processed, and a dyeing adaptive parameter adjustment control module; Collecting first product data of the product to be processed; obtaining preset data of the product to be processed; Furthermore, the first product data includes hosiery material, material ratio, fabric structure, fabric tension, knitting density and color; the preset data includes target color, dye type and dye ratio; the first processed data includes actual dyed color, dyeing amount, actual dyeing time, actual temperature and actual pH value. The first product data is obtained through a high-precision spectral sensor, a tension sensor, a material density detector and a high-definition camera; First product data: The physical properties and initial state of the socks are collected in real time through multimodal sensors, including: Sock materials and proportions use material density detectors and spectral sensors to identify fiber components, such as the proportion of cotton, nylon, and spandex, combined with a material database to match properties such as water absorption and dyeing affinity.

[0037] Fabric structure uses high-definition cameras, such as 3D structured light scanning, to capture fabric texture, porosity and weaving methods, such as plain weave and rib, to generate a three-dimensional model to predict the dye penetration path.

[0038] The fabric tension is monitored in real time by embedded tension sensors in different areas of the sock body, and the dye spraying pressure is dynamically adjusted to prevent uneven coloring in deformed areas.

[0039] The knitting density is measured by a laser macro scanner to measure the number of yarn interlacing points per unit area, and a density-penetration depth relationship model is established in combination with historical data to compensate for the amount of dye used in high-density areas.

[0040] The initial color is quantified by a high-precision spectral sensor with a wavelength range of 380-780nm and a resolution of ±0.1nm to determine the Lab* value of the base color of the socks, providing a benchmark for subsequent color overlay.

[0041] Preset data: Define target parameters through process files or user input: Target color: Based on the Pantone color card or the RGB / HEX value provided by the customer, it is converted into the color rendering parameters of the dye formula.

[0042] Dye type and ratio: Select dyes according to material type, such as acid dyes for wool and disperse dyes for polyester, and match the optimal concentration ratio through the database.

[0043] A conversion control model is constructed to analyze the preset data to obtain the product processing area; and by analyzing the product processing area and the first product data, the product area processing color tone and the product area processing amount are obtained.

[0044] In order to achieve high-precision dynamic control of dyeing formula, the multi-parameter acquisition module of the present invention uses multimodal sensing technology to obtain key data of hosiery materials, fabric structures and environmental parameters in real time. Table 4 compares the technical indicators of the traditional detection method and the sensor of the present invention, and verifies the improvement of the detection accuracy of the multi-parameter acquisition module in dimensions such as material ratio, fabric tension, knitting density and initial color quantization, providing high-reliability input data support for the subsequent conversion control model.

[0045] Table 4 Comparison of detection accuracy of multi-parameter acquisition modules

[0046] Furthermore, the conversion control model includes a sock dyeing data processing and analysis layer, a sock dyeing area division layer, an area dyeing tone control layer and an area dyeing amount control layer; the sock dyeing data processing and analysis layer obtains sock feature data by preprocessing and extracting features from the first product data; wherein the sock feature data Include material eigenvectors , fabric structure feature vector and dynamic process parameters ; The sock dyeing area division layer divides the sock feature data into regions through a clustering algorithm to obtain product processing areas and boundaries and identifications of different dyeing areas; through improved DBSCAN clustering, the regions are divided based on density and material similarity; the calculation formula is: ; in, For the The socks feature data to The distance between the feature data of socks, For the Individual socks product characteristic data: water absorption rate of materials, For the Individual socks product characteristic data: water absorption rate of materials, is the water absorption weight of the material, For the The knitting density in the characteristic data of socks, For the The knitting density in the characteristic data of socks, is the knitting density weight; Region boundary identification uses edge detection algorithm to extract cluster boundaries.

[0047] The regional dyeing tone control layer analyzes the product processing area, the boundaries of different dyeing areas, the logo and the first product data through a color matching algorithm to obtain the product area processing tone; the control of the product area processing amount is specifically as follows: based on the area of ​​the product processing area, the water absorption rate of the material and the target color concentration, the initial treatment agent amount is calculated; the initial treatment agent amount is adjusted and controlled in combination with the correction coefficient of the material type for the material absorption rate; the treatment agent amount is dynamically compensated and controlled according to the relationship between the material density and the dye penetration depth; the treatment agent amount is controlled by density-penetration compensation and tension compensation; The calculation formula for the initial treatment agent dosage is: ; in, is the dosage of regional treatment agent, is the area of ​​the region, is the target color concentration, is the correction factor for the water absorption of the material, is the compensation factor of temperature on dye diffusion efficiency, is the difference between the actual temperature and the preset temperature; The regional dyeing dosage control layer analyzes the product processing area, the boundaries of different dyeing areas, the logo and the first product data based on the material properties and the dye dosage of the target color to obtain the product area processing dosage.

[0048] Furthermore, the regional dyeing tone control layer also includes control of the superposition of multiple colors in the same region, and the specific process is: according to the design pattern and color of the socks, the color type required for each layer of dyeing is analyzed; the initial value of each color is obtained to determine the initial value of each layer of color by combining the color type, the socks material and the dyeing characteristics of the dye; by analyzing the interaction between the dyeing process and the multiple colors, the superposition order of each color is determined; the initial value of each layer of color is corrected by the color matching algorithm, and the corrected color parameters are generated by combining the material absorption rate and reflectivity of the socks material and the superposition influence coefficient of the adjacent color layers; the color matching algorithm is: Single-layer color correction is obtained using the CIELAB standard color difference calculation formula; Multi-layer overlay correction is determined by the overlay influence coefficient; The calculation formula is ;in is the correction factor, and Respectively Layer color for The overlay influence coefficient of the layer color, and Respectively Layer and Dye concentration of the layer; Based on the corrected color parameters and superposition order, the actual color chromaticity of each layer of color after superposition is obtained; the actual color is compared with the target color, and if the color difference value exceeds the preset threshold, the color parameters or superposition order are dynamically adjusted until the color accuracy requirement is met; the specific process is: according to the color difference value distribution, the level where the color deviation occurs is located; if the deviation comes from the color parameters of a single layer, the concentration and ratio of the color of the layer are adjusted based on the dye concentration-color rendering relationship; if the deviation comes from multi-layer superposition interference, the superposition order is recalculated through the color superposition simulation model, and the color compensation value after superposition is updated.

[0049] Divide the product to be processed into regions according to the product processing regions to obtain the product regions to be processed; dye the product regions to be processed according to the product region processing hue and product region processing amount to obtain first processing data; The processing condition automatic control model is constructed to obtain the processing deviation by comparing the first processing data with the preset data; when the processing deviation is greater than the preset processing deviation, the processing time, processing temperature and processing pH value are controlled until the processing deviation is less than the preset processing deviation.

[0050] Furthermore, the processing condition automatic control model includes a data acquisition layer, a deviation analysis layer and a parameter regulation layer; The data acquisition layer obtains the dyeing condition deviation by analyzing the first processed data and the preset data; the dyeing condition deviation includes the temperature difference , pH difference in dyeing and dyeing time difference The deviation analysis layer analyzes the dyeing condition deviation, the color difference between the first processed data and the preset data through a multi-objective weighted fusion algorithm to obtain a comprehensive dyeing deviation value. The parameter control layer controls the comprehensive dyeing deviation value through the PID control algorithm. The analysis was performed to obtain the adjusted dyeing time, temperature and pH value.

[0051] Furthermore, the comprehensive staining deviation value The specific calculation formula is: ; in, is the color difference dynamic weight, is the color difference, is the dynamic weight of the coloring condition deviation, For preset time, To preset pH value, is the preset temperature.

[0052] In the process of dynamic control of dyeing deviation, the comprehensive dyeing deviation value formula and PID control algorithm work together to correct the process parameter deviation in real time. Table 5 verifies the optimization effect of the dynamic control mechanism of the present invention on initial color difference, response time and dye compensation amount through multiple sets of experimental data, and proves the rapid response ability and resource utilization advantage of the model in complex dyeing scenarios.

[0053] Table 5 Verification table of comprehensive dyeing deviation control effect

[0054] When multiple layers of color are superimposed, the control of the product area processing amount also includes: Allocate the amount of dye for each layer according to the coverage ratio of each layer of color in the stacking order; Simulate dye diffusion in the overlapping areas of adjacent color layers and adjust the amount of the overlapping area based on the diffusion range; When the color difference between the actual dyeing effect and the target color exceeds the threshold, compensation is preferentially performed by increasing or decreasing the amount of the bottom dye.

[0055] When adjusting the dyeing temperature and pH value, the parameter control layer simultaneously updates the dynamic weight of the product area processing amount, specifically: If the temperature deviation causes the dye activity to decrease, the amount of dye will be increased proportionally; if the pH deviation causes the dye fixation rate to decrease, the amount of dye compensation will be added based on the ion concentration model.

[0056] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A dyeing formula intelligent conversion control method for hosiery production, characterized in that: include: Collecting first product data of the product to be processed; obtaining preset data of the product to be processed; Construct a conversion control model to analyze the preset data and obtain the product processing area; And by analyzing the product treatment area and the first product data, the product area treatment color tone and product area treatment amount are obtained; the product area treatment amount is controlled specifically as follows: based on the area of ​​the product treatment area, the water absorption rate of the material and the target color concentration, the initial treatment agent amount is calculated; the initial treatment agent amount is adjusted and controlled in combination with the correction coefficient of the material type for the material absorption rate; the treatment agent amount is controlled according to the relationship between the material density and the dye penetration depth; The products to be processed are divided into regions according to the product processing regions to obtain the product regions to be processed; the product regions to be processed are processed according to the product region processing color tone and the product region processing dosage to obtain the first processing data; an automatic control model for processing conditions is constructed to obtain the processing deviation by comparing the first processing data with the preset data; when the processing deviation is greater than the preset processing deviation, the processing time, processing temperature and processing pH value are controlled until the processing deviation is less than the preset processing deviation.

2. The method for intelligently converting dyeing recipes for hosiery production according to claim 1, characterized in that: The first product data includes sock material, material ratio, fabric structure, fabric tension, knitting density and color; the preset data includes target color, dye type and dye ratio; the first processing data includes actual dyed color, dyeing amount, actual dyeing time, actual temperature and actual pH value.

3. The method for intelligently converting dyeing formulas for hosiery production according to claim 1 is characterized in that: The conversion control model includes a sock dyeing data processing and analysis layer, a sock dyeing area division layer, a regional dyeing hue control layer and a regional dyeing dosage control layer; the sock dyeing data processing and analysis layer obtains sock feature data by preprocessing and extracting features from the first product data; the sock dyeing area division layer divides the sock feature data into regions by a clustering algorithm to obtain product processing areas and boundaries and identifications of different dyeing areas; the regional dyeing hue control layer analyzes the product processing areas and boundaries, identifications and the first product data of different dyeing areas by a color matching algorithm to obtain product area processing hues; the regional dyeing dosage control layer analyzes the product processing areas and boundaries, identifications and the first product data of different dyeing areas based on material properties and the dye dosage of the target color to obtain product area processing dosage.

4. The method for intelligently converting dyeing recipes for hosiery production according to claim 3 is characterized in that: The regional dyeing tone control layer also includes control of multi-layer color superposition in the same region, and the specific process is: according to the design pattern and color of the socks, the color type required for each layer of dyeing is analyzed; the initial value of each color is obtained to determine the initial value of each layer of color by combining the color type, the socks material and the dyeing characteristics of the dye; the superposition order of each color is determined by analyzing the interaction between the dyeing process and the multi-layer color; the initial value of each layer of color is corrected by the color matching algorithm, and the corrected color parameters are generated by combining the material absorption rate and reflectivity of the socks material and the superposition influence coefficient of the adjacent color layers; based on the corrected color parameters and the superposition order, the actual color chromaticity of each layer of color after superposition is obtained; the actual color is compared with the target color, and if the color difference value exceeds the preset threshold, the color parameters and the superposition order are dynamically adjusted until the color accuracy requirements are met; the specific process of dynamically adjusting the color parameters and the superposition order is: according to the color difference value distribution, the level where the color deviation is generated is located; if the deviation comes from the single-layer color parameter, the concentration and ratio of the color of the current layer are adjusted based on the dye concentration-color rendering relationship; if the deviation comes from the multi-layer superposition interference, the superposition order is recalculated through the color superposition simulation model, and the superposition color compensation value is updated.

5. The method for intelligent conversion control of dyeing formula for hosiery production according to claim 1 is characterized in that: The processing condition automatic control model includes a data acquisition layer, a deviation analysis layer and a parameter regulation layer; The data acquisition layer obtains the dyeing condition deviation by analyzing the first processed data and the preset data; the dyeing condition deviation includes the temperature difference , pH difference in dyeing and dyeing time difference The deviation analysis layer analyzes the dyeing condition deviation, the color difference between the first processed data and the preset data through a multi-objective weighted fusion algorithm to obtain a comprehensive dyeing deviation value. The parameter control layer controls the comprehensive dyeing deviation value through the PID control algorithm. Controls were performed to obtain adjusted dyeing time, temperature and pH value.

6. The method for intelligently converting dyeing recipes for hosiery production according to claim 5 is characterized in that: The comprehensive staining deviation value The specific calculation formula is: ； in, is the color difference dynamic weight, is the color difference, is the dynamic weight of the coloring condition deviation, For preset time, To preset pH value, is the preset temperature.

7. An intelligent dyeing formula conversion control system for hosiery production, characterized in that: include: A multi-parameter acquisition module, used for acquiring first product data of the product to be processed and preset data of the product to be processed; The conversion control model building module is used to build a conversion control model to analyze the preset data and obtain the product processing area; and obtain the product area processing color tone and product area processing amount by analyzing the product processing area and the first product data; the control of the product area processing amount is specifically as follows: based on the area of ​​the product processing area, the water absorption rate of the material and the target color concentration, the initial treatment agent amount is calculated; combined with the correction coefficient of the material type for the material absorption rate, the initial treatment agent amount is adjusted and controlled; according to the relationship between the material density and the dye penetration depth, the treatment agent amount is dynamically compensated and controlled; The dyeing control module for the product to be processed is used to divide the product to be processed into regions according to the product processing regions to obtain the product regions to be processed; and to process the product regions to be processed according to the product region processing color tone and the product region processing amount to obtain the first processing data; The dyeing adaptive parameter adjustment control module constructs an automatic control model for processing conditions to obtain the processing deviation by comparing the first processing data with the preset data; when the processing deviation is greater than the preset processing deviation, the processing time, processing temperature and processing pH value are controlled until the processing deviation is less than the preset processing deviation.

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