Setting, printing and inspection integrated intelligent control method and system for high-speed jet color weaving machine

Abstract

The invention provides a setting, printing and inspection integrated intelligent control method and system for a high-speed jet color loom, and belongs to the field of high-end textile equipment manufacturing. The technical problem that an existing high-speed jet color loom is low in automation degree is solved. In order to solve the technical problem, the technical scheme adopted by the invention is as follows: the color setting, color printing and color inspection integrated color weaving control method for the high-speed jet color weaving machine adopts an artificial intelligence algorithm driven by dynamic multi-source data cycle feedback and calling of a multi-parameter correction strategy to carry out integrated intelligent control; a yarn weaving and printing defect real-time two-dimensional evaluation framework is combined, whole-machine whole-process self-adaptive variable-speed scheduling is carried out, an integrated intelligent control system is built through a multi-module processing program, and the quality and efficiency of fabric jet printing are improved; the invention is applied to the high-speed jet color weaving machine.

Description

Technical Field

[0001] The invention provides a method and system for intelligent control of the integrated setting, printing and inspection of a high-speed jet color loom, belonging to the field of high-end textile equipment manufacturing. Background Art

[0002] With the rapid development of the textile industry, high-speed jet color looms are increasingly used to improve production efficiency and product quality. From an industrial perspective, the application of jet color looms can be divided into two categories: standardized production and personalized customization. Among them, personalized customization has begun to take shape in the production of colored fabrics. The key advantages of high-speed jet digital color looms in advanced manufacturing include digital parameter setting, intelligent printing process, and real-time and accuracy of online quality detection. They are widely used in fashion apparel, home textiles, technical textiles and other fields with strict requirements on color and quality. This makes the development of high-end manufacturing methods for high-speed jet color weaving equipment increasingly important.

[0003] High-speed jet color looms lack seamless integration between color setting, printing and detection. Although they have advantages in speed and mass production, they are difficult to adapt to the complex and changeable color weaving process due to their reliance on fixed operating parameters. At the same time, printing deviations are difficult to identify in time, resulting in a high scrap rate. In contrast, digital looms are more outstanding in flexibility and pattern processing capabilities, but there are challenges in high-speed production and real-time adjustment. Realizing integrated intelligent control of high-speed jet color looms and improving the degree of automation and product quality have become key issues that need to be urgently addressed in the textile industry.

[0004] To solve the above problems, the present invention proposes an intelligent control method and system for the integrated printing and inspection of a high-speed jet color loom based on an adaptive color enhancement strategy for variable speed transmission of fabric patterns. The present invention realizes the two-dimensional evaluation and parametric correction of weaving and printing defects through a multi-layer fabric multi-surface pattern fine printing and local optimization device, and effectively improves the production efficiency and product quality of the textile printing and dyeing process by using multi-source data loop feedback and intelligent control methods, and reduces resource consumption in the production process through an integrated process flow. Summary of the invention

[0005] In order to overcome the deficiencies in the prior art, the present invention aims to solve the technical problem of providing an improved intelligent control method and system for integrating printing and inspection of a high-speed jet color loom.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: the color setting, printing and color inspection integrated color weaving control method for high-speed jet color looms is to use dynamic multi-source data loop feedback and call multi-parameter correction strategy driven artificial intelligence algorithm for integrated intelligent control, and combine the real-time two-dimensional evaluation framework of yarn weaving and printing defects to perform adaptive speed scheduling of the whole machine and the whole process, and build an integrated intelligent control system through a multi-module program. The specific molding method includes the following steps: S1: Import and preprocess the original pattern of colored fabrics and intelligently extract the corresponding main color features; S2: pixelation of the original pattern of the colored fabric and rapid generation of color separation pattern by point-by-point primary color ink coloring signal; S3: Steady-state printing parameter generation of color-woven color separation patterns and sequential extraction of process detection signals; S4: Modeling of dynamic printing parameter correction of color-separated woven patterns based on multi-source data loop feedback; S5: Evaluation of yarn color weaving and printing defects after curing and acquisition of dual-source color data; S6: Pre-compensation of the yarn base color ink coloring signal under variable speed scheduling generates dynamic printing correction parameters.

[0007] The step S1 specifically includes: The imported colored fabric original pattern can be colored fabric pattern data obtained through color 3D scanning, or colored fabric pattern data designed by three-dimensional software. The imported colored fabric pattern data is first pre-processed by boundary positioning coding and color space conversion, and then the color main feature area division required for accurate reproduction of the colored fabric original pattern is determined according to the weaving speed ratio Ra value of warp weaving and weft weaving. The correlation weight parameterization extraction of the color main feature area of ​​the colored fabric original image is performed with color complexity, texture details and geometric features as key elements to meet the spatial arrangement of warp yarns and color selection optimization.

[0008] The step S2 specifically includes: In the CIEL*a*b* uniform color space, the color of each pixel point of the original colored fabric pattern after pixelation is performed according to the CMYK four-primary color subtractive color separation model, and the primary color ink is distributed point by point to generate a colored fabric color separation pattern with adjustable local color features. The local part is the main color feature area, and the primary color ink distribution method can be completed by training through an artificial intelligence algorithm.

[0009] The step S3 specifically includes: By analyzing the coloring characteristics of the yarn itself, the variable speed transmission characteristics of the entire process, and the printing characteristics of the color loom, the compiler plans the printing path and height of the array nozzle under the set printing pressure, and calculates the printing speed and duration of each pixel point of the color separation pattern of the color fabric one by one until a steady-state printing parameter file of the color separation pattern of the color fabric is generated. During the generation process, the full-process detection signals are extracted one by one in sequence to meet the multi-factor control required for the color separation pattern of the color fabric.

[0010] The step S4 specifically includes: Through a multi-source data loop feedback mechanism, a multi-factor control variable set and a weight parameter set that affect the dynamic printing quality of color woven color separation patterns are established. Then, artificial intelligence algorithm training and analysis are performed on the variable set and parameter set to generate the corresponding numerical model, and its physical meaning is verified. Combined with the full-process detection signal, the dynamic printing parameter correction model of color woven color separation patterns is further optimized.

[0011] The step S5 specifically includes: After the yarn color weaving and printing is completed, the radio frequency resonance curing method is used for pre-curing, and the multi-spectral data of the color fabric boundary positioning code area and the high-precision high-speed camera data of the color main feature area are obtained simultaneously. The compiled multi-spectral data comparison model and the color image comparison model are combined to evaluate the weaving and printing defects after the dual-source color data is acquired. After comparing with the preset deviation threshold, the optimization adjustment direction of the color reproduction quality of the color fabric is given to ensure that the color deviation ΔE≤2 and the edge clarity deviation ≤1 pixel.

[0012] The step S6 specifically includes: If the color inspection deviation of the colored fabric exceeds the preset threshold value Th, the non-stop speed regulating device is started to adjust the speed of the colored fabric through the printing, curing and detection integrated device according to a certain proportion Sa, and the pre-set color saturation and new printing parameter compensation correction are performed through the multi-source data feedback mechanism to achieve dynamic intelligent control of the colored fabric, and iterative optimization is performed multiple times to meet the high-precision and high-speed printing requirements of different colored fabrics.

[0013] The adaptive color enhancement strategy for variable-speed transmission of fabric patterns refers to starting from the color composition and geometric features of the fabric pattern, with the goal of optimizing the color transition and detail expression between the current fabric layers, forming four types of optimization methods: global color enhancement and local detail enhancement on the fabric surface, and continuous printing and discrete printing of different fabric layers. Combined with the color distribution data and material properties of the fabric pattern, the color ratio and printing order of the printing process are comprehensively planned according to the visual effect, color fastness and fabric texture.

[0014] The adaptive color enhancement strategy model for variable speed transmission of fabric patterns refers to the analysis of color transition and detail performance based on the case library of variable speed transmission of fabric patterns, and the numerical relationship model between objective evaluation and subjective perception of the color transmission effect of fabric patterns is constructed through machine learning or deep learning network training. Color complexity is 0.4, geometric features are 0.3, and texture details are 0.3.

[0015] A high-speed jet color loom printing and inspection integrated intelligent control method and system, characterized in that: comprising a high-speed jet color loom, a parallel integrated multi-layer fabric printing device, and a control system, wherein the control system controls the operation of the high-speed jet color loom and the multi-layer fabric printing device, wherein the control system integrates the operation program of the high-speed jet color loom printing and inspection integrated intelligent control method according to any one of claims 1 to 9; The system is mainly composed of an advanced algorithm analysis module, a complex speed change transmission algorithm module, a multi-dimensional complexity analysis module, a fine printing control module, a real-time monitoring and feedback module, and an adaptive multi-source data feedback mechanism; The advanced algorithm parsing module is used to import and parse fabric patterns, extract color and detail information, and optimize color reproduction and detail performance; The complex variable speed transmission algorithm module accurately divides the fabric pattern into regions and adjusts the printing speed by setting weight parameters; The multidimensional complexity analysis module is used to calculate the printing parameters and dynamically adjust the printing pressure, speed and nozzle opening and closing time; The fine printing control module is used to generate a control signal to adjust the spray angle and printing pressure of the nozzle to ensure the precise alignment of multiple layers of fabric; The real-time monitoring and feedback module evaluates the printing effect through a high-resolution monitoring system and implements parameterized corrections; The adaptive multi-source data feedback mechanism ensures continuous improvement of printing quality and efficient execution of intelligent defect correction through real-time feedback and iterative optimization.

[0016] The beneficial effects of the present invention compared with the prior art are as follows: the present invention realizes accurate color control under different fabric areas and speed conditions through the adaptive color enhancement strategy of variable speed transmission of fabric patterns. The strategy can dynamically adjust the printing speed and color concentration to ensure that the color consistency and detail performance of the fabric pattern are optimal under high-speed operation, significantly improving the quality and efficiency of printing.

[0017] The present invention proposes a multi-layer fabric multi-surface pattern fine printing and local optimization technology. The specific beneficial effect of this technology compared with the existing technology is: through multi-layer printing and fine processing of local areas, high-precision reproduction of complex patterns is achieved. Combined with an intelligent control system, the printing parameters can be automatically adjusted according to the specific needs of the fabric, ensuring that the pattern and color of each layer of fabric are uniform and consistent, thereby improving the overall visual effect.

[0018] The present invention proposes a two-dimensional evaluation and parameterized correction strategy for weaving and printing defects. The specific beneficial effect of this strategy compared with the existing technology is: by real-time monitoring of defects in the printing process, using a two-dimensional evaluation model for analysis, various defects can be quickly identified and classified. Based on this model, the system can automatically generate correction parameters and adjust the printing settings in real time to ensure that the fabric surface is flawless and improve the product qualification rate.

[0019] The present invention proposes a multi-source data loop feedback and intelligent control method. The specific beneficial effect of this method compared with the prior art is: by integrating multiple data sources, including sensor data, visual inspection results and production parameters, comprehensive monitoring and feedback of the printing process is achieved. The intelligent control system can dynamically adjust according to real-time data, optimize the printing path and process flow, and improve production efficiency and product quality.

[0020] In summary, the intelligent control method and system of the high-speed jet color loom of the present invention are efficient and accurate, can effectively improve the quality and efficiency of fabric printing, and provide an innovative path for the intelligent development of high-speed jet color looms. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The present invention will be further described below in conjunction with the accompanying drawings: Figure 1 A flow chart of a method and system for intelligently controlling printing and inspection integrated high-speed jet color loom of the present invention; DETAILED DESCRIPTION

[0022] like Figure 1 As shown, the present invention aims to provide an intelligent control method and system for a high-speed jet color loom. The color weaving control method for the high-speed jet color loom, which integrates color setting, printing and color inspection, adopts dynamic multi-source data loop feedback and calls a multi-parameter correction strategy driven artificial intelligence algorithm for integrated intelligent control, and combines the real-time two-dimensional evaluation framework of yarn weaving and printing defects to perform adaptive speed scheduling of the whole process of the whole machine, and builds an integrated intelligent control system through a multi-module program, thereby realizing efficient and high-quality fabric printing production planning.

[0023] In order to achieve the above-mentioned object, the present invention specifically adopts the following technical solutions: An intelligent control method for a high-speed jet color loom is based on an adaptive color enhancement strategy for variable speed transmission of fabric patterns. By integrating a multi-source data loop feedback device and an improved printing control system in parallel on the loom, fine printing and defect correction of multi-layer fabric multi-surface patterns are achieved. The specific control method includes the following steps: S1: Import the fabric design pattern, perform preprocessing to extract key color main features, analyze color concentration distribution and printing speed requirements, generate preliminary printing path planning and basic control signals, and ensure that the printing path adapts to the fabric characteristics; S2: Pixelate the original fabric pattern, generate the color separation pattern and the corresponding base color ink setting control signal point by point, and meet the requirements of high-speed generation and accurate color separation, providing a stable color separation basis for subsequent printing; S3: Generate steady-state printing parameters based on the color-woven color separation pattern, including color consistency and detail restoration parameters, extract process detection signal sequence, and ensure accuracy and real-time monitoring capabilities during the printing process; S4: Based on the loop feedback mechanism of multi-source data, the printing parameters are analyzed in real time and dynamic correction modeling is performed. The printing path and color concentration signal are optimized, and dynamic control parameters are generated to ensure the efficiency and stability of the printing process; S5: After the printing is completed, the fabric defects are evaluated and classified through the dual-source data of yarn color data and cured fabric, and the causes of defects and their impact are analyzed to provide guidance for subsequent corrections; S6: In view of the color deviation that may occur under variable speed scheduling, the pre-compensation parameters of the base color ink setting signal are generated in advance, and dynamic printing correction is performed to ultimately ensure that all fabric areas meet the expected color and quality standards. The color difference calculation formula based on real-time monitoring is combined with pressure and speed control signals. It combines real-time color difference feedback with dynamic adjustment of printing speed and pressure to ensure the accuracy of color restoration and the stability of printing quality during the printing process. Specifically, the formula combines color deviation, printing speed and pressure parameters to dynamically generate control signals, so that the system can adapt to the diverse needs of complex fabrics and maintain accurate color restoration in real-time adjustments, and realize dynamic adjustment and feedback during the printing process. The formula is as follows: in: S feedback is the feedback control signal, V base As the basic printing speed, λ controls the effect of the color difference ΔE on the feedback signal, · The degree of smooth adjustment when the control pressure P deviates from the target value. This formula combines color difference feedback and pressure deviation to achieve dynamic adjustment of speed and pressure during printing, thereby effectively controlling color accuracy and printing smoothness. base +λ·ΔE term combines the basic speed and the feedback correction of color difference. As the color difference changes during the printing process, the system can immediately speed up or slow down the printing speed to adjust to the appropriate color reproduction range. Gaussian distribution term It is used to adjust the effect of pressure deviation on the overall feedback. When the pressure is too high or too low, this item will be reduced, making the printing speed adjustment more gentle, thus avoiding excessive correction of speed and pressure during printing.

[0024] The adaptive color enhancement strategy for variable speed transmission of fabric patterns refers to starting from the color components of the fabric pattern and their dynamic changing relationship, with the goal of optimizing the color consistency and detail expression in the current fabric area, forming four types of control methods, including overall adjustment and local fine-tuning of the printing path, and dynamic control and stable control of the printing speed. Combined with the distribution data of fabric color concentration and the characteristics of the printing material, the composition ratio and printing order of the printed colors (primary color, auxiliary color, transparent color) in the fabric area are comprehensively planned according to the visual effect, color reproduction and complexity of the printing path, which has a planning idea of ​​adaptive control.

[0025] The multi-source data loop feedback device is composed of a real-time monitoring sensor, a data processing module, a feedback control system, a printing path adjustment module and a quality assessment unit; the real-time monitoring sensor is used to capture color changes and defect information during the fabric printing process, and transmit the data to the data processing module; the data processing module analyzes real-time data through an algorithm to generate printing adjustment suggestions; the feedback control system dynamically adjusts the printing parameters according to the analysis results to optimize the printing path and speed; the printing path adjustment module adopts a multi-axis motion control system, which can flexibly adjust the printing path to adapt to the complexity of different fabric patterns; the quality assessment unit is used to perform quality inspection on the fabric after printing, and feed back the results to the data processing module for further optimization.

[0026] The high-speed jet loom intelligent control optimization model is based on the performance and defect analysis of the high-speed jet loom operation data case library, and constructs a numerical relationship model between the high-speed jet loom operation efficiency and product quality through machine learning algorithm or optimization algorithm training; wherein the performance indicators include five parameters: speed, tension, energy consumption, noise and vibration; the quality indicators include fabric density, color consistency and defect rate; the numerical relationship model between the performance indicators and the quality indicators is calculated by analyzing the performance indicators and quality indicator parameters of each sample respectively, performing linear regression on the difference between the two, and calculating the optimization weight.

[0027] The intelligent control signal of the high-speed jet loom is digitally planned and expressed through a functional function including process parameters (such as weaving speed, weft tension, jet pressure, pattern complexity, temperature control, etc.) and adaptive parameters (such as real-time adjustment frequency, tension adjustment amplitude, nozzle diameter, jet angle and vibration amplitude, etc.).

[0028] The present invention makes full use of the characterization advantages of the intelligent control optimization model of the high-speed jet loom, monitors and accurately controls the quality fluctuations of the fabric during the high-speed jet loom process in real time, effectively improves the efficiency and quality stability of fabric production, and reduces manual intervention and energy consumption through automated process flow. The intelligent adjustment method and device of the present invention are accurate and efficient, can effectively control fabric density and color consistency, and provide an innovative solution for the intelligent upgrade of high-speed jet looms.

[0029] Implementation Case 1 When producing a fabric with a complex pattern, a fabric design with a complex pattern is selected, and the pattern contains four main colors: red, green, blue and yellow. The pattern is divided into four main color areas: red area, green area, blue area and yellow area. Each color area is further divided into five subdivision areas according to complexity: R1, R2, R3, R4, R5. For each subdivision area, the advanced algorithm parsing module is used to extract color and detail information. The adaptive color extraction strategy is applied to adjust the color extraction parameters. The color extraction parameters of the red area are set to 0.85, the green area is 0.9, the blue area is 0.88, and the yellow area is 0.87. The complex variable speed transfer algorithm module is used to adjust the printing speed for each subdivision area. The printing speed of the red area is set to 1.2 m / s and the pressure is 0.25 MPa; the speed of the green area is 1.1 m / s and the pressure is 0.23 MPa; the speed of the blue area is 1.3 m / s and the pressure is 0.26 MPa; the speed of the yellow area is 1.0 m / s and the pressure is 0.24 MPa. During the printing process, the real-time monitoring system evaluates the printing effect. If the color deviation in a certain area exceeds ΔE=2, a parameter correction is performed through the adaptive multi-source data feedback mechanism.

[0030] Implementation Case 2 When producing a traditional embroidery pattern, select an embroidery pattern with fine textures, including three main colors: purple, orange and cyan. Divide the pattern into three main color areas: purple area, orange area and cyan area. Each color area is further divided into three sub-areas based on texture characteristics: P1, P2, P3. Perform multidimensional complexity analysis on each sub-area. Dynamically adjust the printing parameters, and set the printing pressure of the purple area to 0.28MPa and the speed to 1.1m / s; the pressure of the orange area to 0.27MPa and the speed to 1.0m / s; the pressure of the cyan area to 0.29MPa and the speed to 1.2m / s. Generate a control signal to adjust the nozzle's spray angle. Ensure accurate alignment of multiple layers of fabric, and adjust the nozzle angle to 45 degrees. The real-time monitoring system evaluates the printing effect. If the edge clarity deviation is detected to exceed 1 pixel, a parametric correction is performed.

[0031] It should be noted that the integration relationship between the functional modules used in the present invention is clear and feasible. Except for those specifically described in the embodiments, the specific integration method can bring about corresponding technical effects and solve the technical problems proposed by the present invention without relying on specific software programs. The modules, components, models and connection methods of specific hardware involved in the present invention, except for those specifically described, are all prior arts such as published patents, published journal articles or common knowledge that can be obtained by technicians in this field before the application date, and there is no need to elaborate, so that the technical solution provided in this case is clear, complete and feasible, and the corresponding physical products can be reproduced or obtained according to the technical means.

[0032] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments may still be modified, or some or all of the technical features therein may be replaced by equivalents. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A high-speed jet color loom printing and inspection integrated intelligent control method and system, characterized in that: The integrated color weaving control method for color setting, printing and color inspection of high-speed jet color looms adopts dynamic multi-source data loop feedback and calls multi-parameter correction strategy driven artificial intelligence algorithm for integrated intelligent control, and combines the real-time two-dimensional evaluation framework of yarn weaving and printing defects to perform adaptive speed scheduling of the whole machine and the whole process, and builds an integrated intelligent control system through a multi-module processing program; the integrated color weaving control method specifically includes the following steps: S1: Import and preprocess the original pattern of colored fabrics and intelligently extract the corresponding main color features; S2: pixelation of the original pattern of the colored fabric and rapid generation of color separation pattern by point-by-point primary color ink coloring signal; S3: Steady-state printing parameter generation of color-woven color separation patterns and sequential extraction of process detection signals; S4: Modeling of dynamic printing parameter correction of color-separated woven patterns based on multi-source data loop feedback; S5: Evaluation of yarn color weaving and printing defects after curing and acquisition of dual-source color data; S6: Pre-compensation of the yarn base color ink coloring signal under variable speed scheduling generates dynamic printing correction parameters.

2. The intelligent control method and system for integrated printing and inspection of high-speed air-jet color loom according to claim 1, characterized in that: The step S1 specifically includes: The imported colored fabric original pattern can be colored fabric pattern data obtained through color 3D scanning, or colored fabric pattern data designed by three-dimensional software. The imported colored fabric pattern data is first pre-processed by boundary positioning coding and color space conversion, and then the color main feature area division required for accurate reproduction of the colored fabric original pattern is determined according to the weaving speed ratio Ra value of warp weaving and weft weaving. The correlation weight parameterization extraction of the color main feature area of ​​the colored fabric original pattern is performed with color complexity, texture details and geometric features as key elements to meet the spatial arrangement of warp yarns and color selection optimization.

3. The intelligent control method and system for integrated printing and inspection of high-speed jet color loom according to claim 1, characterized in that: The step S2 specifically includes: In CIEL * a * b * In a uniform color space, the color of each pixel of the original colored fabric pattern after pixelation is performed according to the CMYK four-primary color halftone color separation model, and the primary color ink is distributed point by point to generate a colored fabric color separation pattern with adjustable local color features; the local area is the main color feature area, and the primary color ink distribution method can be completed by training through an artificial intelligence algorithm.

4. The intelligent control method and system for integrated printing and inspection of high-speed air-jet color loom according to claim 1, characterized in that: The step S3 specifically includes: By analyzing the coloring characteristics of the yarn itself, the variable speed transmission characteristics of the entire process, and the printing characteristics of the color loom, the compiler plans the printing path and height of the array nozzle under the set printing pressure, and calculates the printing speed and duration of each pixel point of the color separation pattern of the color fabric one by one until a steady-state printing parameter file of the color separation pattern of the color fabric is generated. During the generation process, the full-process detection signals are extracted one by one in sequence to meet the multi-factor control required for the color separation pattern of the color fabric.

5. The intelligent control method and system for integrated printing and inspection of high-speed air-jet color loom according to claim 1, characterized in that: The step S4 specifically includes: Through a multi-source data loop feedback mechanism, a multi-factor control variable set and weight parameter set that affect the dynamic printing quality of color-separated woven patterns are established. Then, artificial intelligence algorithm training and analysis are performed on the variable set and parameter set to generate the corresponding numerical model, and its physical meaning is verified. Combined with the full-process detection signal, the dynamic printing parameter correction model of color-separated woven patterns is further optimized.

6. The intelligent control method and system for integrated printing and inspection of high-speed jet color loom according to claim 1, characterized in that: The step S5 specifically includes: After the yarn color weaving and printing is completed, the radio frequency resonance curing method is used for pre-curing, and the multi-spectral data of the color fabric boundary positioning code area and the high-precision high-speed camera data of the color main feature area are obtained simultaneously. The compiled multi-spectral data comparison model and the color image comparison model are combined to evaluate the weaving and printing defects after the dual-source color data is acquired. After comparing with the preset deviation threshold, the optimization adjustment direction of the color reproduction quality of the color fabric is given to ensure that the color deviation ΔE≤2 and the edge clarity deviation ≤1 pixel.

7. The intelligent control method and system for integrated printing and inspection of high-speed jet color loom according to claim 1, characterized in that: The step S6 specifically includes: If the color inspection deviation of the colored fabric exceeds the preset threshold value Th, the non-stop speed regulating device is started to adjust the speed of the colored fabric through the printing, curing and detection integrated device according to a certain proportion Sa, and the pre-set color saturation and new printing parameter compensation correction are performed through the multi-source data feedback mechanism to achieve dynamic intelligent control of the colored fabric, and iterative optimization is performed multiple times to meet the high-precision and high-speed printing requirements of different colored fabrics.

8. The intelligent control method and system for integrated printing and inspection of high-speed air-jet color loom according to claim 1, characterized in that: The adaptive color enhancement strategy for variable-speed transmission of fabric patterns refers to starting from the color composition and geometric features of the fabric pattern, with the goal of optimizing the color transition and detail expression between the current fabric layers, forming four types of optimization methods: global color enhancement and local detail enhancement on the fabric surface, and continuous printing and discrete printing of different fabric layers. Combined with the color distribution data and material properties of the fabric pattern, the color ratio and printing order of the printing process are comprehensively planned according to the visual effect, color fastness and fabric texture.

9. The intelligent control method and system for integrated printing and inspection of a high-speed jet color loom according to claim 2, characterized in that: The adaptive color enhancement strategy model for variable speed transfer of fabric patterns refers to a color transition and detail performance analysis based on a case library of variable speed transfer of fabric patterns, and constructs a numerical relationship model between objective evaluation and subjective perception of the color transfer effect of fabric patterns through machine learning or deep learning network training; color complexity 0.4, geometric features 0.3, and texture details 0.

3.

10. The intelligent control method and system for integrated printing and inspection of a high-speed jet color loom according to claim 1, characterized in that: It comprises a high-speed jet color loom, a parallel integrated multi-layer fabric printing device, and a control system, wherein the control system controls the operation of the high-speed jet color loom and the multi-layer fabric printing device, wherein the control system integrates an operation program of the high-speed jet color loom device, printing and inspection integrated intelligent control method according to any one of claims 1 to 9; The system is mainly composed of an advanced algorithm analysis module, a complex speed change transmission algorithm module, a multi-dimensional complexity analysis module, a fine printing control module, a real-time monitoring and feedback module, and an adaptive multi-source data feedback mechanism; The advanced algorithm parsing module is used to import and parse fabric patterns, extract color and detail information, and optimize color reproduction and detail performance; The complex variable speed transmission algorithm module accurately divides the fabric pattern into regions and adjusts the printing speed by setting weight parameters; The multidimensional complexity analysis module is used to calculate the printing parameters and dynamically adjust the printing pressure, speed and nozzle opening and closing time; The fine printing control module is used to generate a control signal to adjust the spray angle and printing pressure of the nozzle to ensure the precise alignment of multiple layers of fabric; The real-time monitoring and feedback module evaluates the printing effect through a high-resolution monitoring system and implements parameterized corrections; The adaptive multi-source data feedback mechanism ensures continuous improvement of printing quality and efficient execution of intelligent defect correction through real-time feedback and iterative optimization.

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