KR-20260067128-A - System and Method for Generating Waterless Dyeing Patterns based on Artificial Intelligence Learning

KR20260067128AKR 20260067128 AKR20260067128 AKR 20260067128AKR-20260067128-A

Abstract

The present invention relates to a system and method for generating an anhydrous dyeing pattern based on artificial intelligence learning, which implements an anhydrous dyeing device for yarn using vacuum transition to improve dyeing quality and enables the prediction and generation of desired patterns through learning using artificial intelligence. This improves the dyeing quality of yarn, predicts and generates fabric patterns according to the weaving method in advance and provides them to the operator, and predicts and generates yarn dyeing patterns required according to the desired fabric pattern in advance and provides them to the operator, thereby increasing work efficiency.

Inventors

장지상
이재정
김경규
박치균
최경석

Assignees

(주)아셈스

Dates

Publication Date: 20260512
Application Date: 20241105

Claims (11)

A yarn anhydrous dyeing device that generates a yarn pattern by forming a uniform vacuum pressure over the entire surface area of a porous drum, thereby transferring the dye ink of a transfer sheet to the yarn by vacuum transfer, and simultaneously transferring the dye ink of a vacuum barrier sheet wound on a jig inside the yarn to the yarn. A fabric weaving device that produces a fabric using a selected weaving method with yarn produced in a yarn anhydrous dyeing device; Collect yarn patterns produced by the above-mentioned anhydrous yarn dyeing device or fabric patterns produced by the fabric weaving device, and reflect pattern changes according to weaving method to learn output fabric patterns based on yarn patterns or learn necessary yarn patterns based on fabric patterns, A system for generating waterless dyeing patterns based on artificial intelligence learning, characterized by including a pattern learning and prediction generation management server that generates fabric pattern predictions based on yarn patterns or generates yarn pattern predictions based on fabric patterns.
In claim 1, the pattern learning and prediction generation management server is, A pattern collecting unit that collects yarn patterns produced in a yarn anhydrous dyeing device or fabric patterns produced in a fabric weaving device, and A pattern learning unit that learns output fabric patterns based on yarn patterns or learns necessary yarn patterns based on fabric patterns, and A pattern change reflection unit by weaving method that reflects pattern change information that changes according to weaving method in the learning process of the pattern learning unit, and A system for generating an artificial intelligence learning-based waterless dyeing patterns, characterized by including a pattern prediction generation unit that generates a yarn pattern-based fabric pattern prediction or generates a fabric pattern-based yarn pattern prediction using the results of yarn pattern-based output fabric pattern learning or the results of fabric pattern-based necessary yarn pattern learning.
In Clause 2, the pattern collecting unit, A yarn pattern collecting unit that collects the transfer sheet pattern of the yarn anhydrous dyeing device for yarn patterning and the yarn pattern produced by the yarn anhydrous dyeing device, and A system for generating an artificial intelligence learning-based waterless dyeing patterns, characterized by including a fabric pattern collection unit that collects fabric patterns input into a fabric weaving device and fabric patterns produced by a fabric weaving device for fabric patterning.
In Clause 2, the pattern learning unit is, A yarn pattern reference output fabric pattern learning unit that learns an output fabric pattern produced by a fabric weaving device using a yarn pattern produced by a yarn anhydrous dyeing device, and A system for generating an artificial intelligence learning-based waterless dyeing patterns, characterized by including a fabric pattern standard necessary yarn pattern learning unit that learns the necessary yarn pattern required for producing a fabric pattern to be made in a fabric weaving device.
In Clause 2, the pattern prediction generation unit is, A yarn pattern-based fabric pattern prediction generation unit that predicts and generates a fabric pattern produced by a fabric weaving device when fabric weaving is performed using a selected weaving method with yarn produced by a yarn anhydrous dyeing device, using the yarn pattern-based output fabric pattern learning result; A system for generating an artificial intelligence learning-based anhydrous dyeing patterns, characterized by including a fabric pattern standard yarn pattern prediction generation unit that generates a fabric pattern standard yarn pattern prediction using the results of learning a required yarn pattern standard fabric pattern when there is a required fabric pattern to be made in a fabric weaving device, and provides this to a yarn anhydrous dyeing device.
In claim 1, the yarn anhydrous dyeing device is, A dyeing jig comprising a porous drum in the form of a cylindrical drum having a plurality of vacuum holes formed to penetrate inward and outward on the outer surface, and A vacuum barrier sheet made of a material having a plurality of micro-holes formed therein, installed to surround the outer surface of the porous drum, and on which yarn to be dyed is wound, and A transfer sheet that surrounds a yarn wound on the outer surface of the above vacuum barrier sheet, and has dye ink applied to the inner surface in contact with the yarn, and A process chamber into which the above-mentioned dyeing jig is introduced, and A heating means for applying heat to a dyeing jig on which the above vacuum barrier sheet, yarn, and transfer sheet are installed, and A system for generating an artificial intelligence learning-based waterless dyeing patterns, characterized by including a vacuum generating means that communicates with the internal space of the porous drum and sucks in air from the internal space of the porous drum to form a vacuum pressure through the internal space of the porous drum.
A system for generating an artificial intelligence learning-based waterless dyeing patterns, characterized in that, in claim 6, a dye ink for dyeing yarn is applied to the outer surface of the vacuum barrier sheet.
A system for generating an artificial intelligence learning-based anhydrous dyeing pattern, characterized in that, in claim 7, the dye ink applied to the vacuum barrier sheet is applied in a pattern that is inverted from the pattern of the dye ink applied to the transfer sheet.
A step of collecting yarn patterns or fabric patterns from a pattern learning and prediction generation management server; A step of learning output fabric patterns based on yarn patterns or learning necessary yarn patterns based on fabric patterns by reflecting pattern changes according to weaving methods; A method for generating an artificial intelligence learning-based anhydrous dyeing pattern, characterized by including the step of: predicting and generating a fabric pattern to be produced by a fabric weaving device when weaving a fabric using a selected weaving method with yarn produced by a yarn anhydrous dyeing device using a yarn pattern-based output fabric pattern learning result, or predicting and generating a fabric pattern-based yarn pattern using a fabric pattern-based required yarn pattern learning result when there is a required fabric pattern to be produced by the fabric weaving device and providing it to the yarn anhydrous dyeing device.
In claim 9, for dyeing anhydrous yarn using vacuum transition in an anhydrous yarn dyeing device, (S1) A step of winding a vacuum barrier sheet around the outer surface of a porous drum; (S2) A step of winding yarn to be dyed onto the outer surface of the vacuum barrier sheet; (S3) A step of winding a transfer sheet having dye ink applied to the outer surface of the above yarn; (S4) A step of inserting the dyeing jig, on which the vacuum barrier sheet, yarn, and transfer sheet are wound, into the process chamber and connecting the dyeing jig to a vacuum generating means; (S5) A step of applying heat to the dyeing jig; and, (S6) A step of generating vacuum pressure in the internal space of a porous drum by operating the vacuum generating means to vacuum exhaust air in the internal space of a porous drum, thereby transferring dye ink of a transfer sheet to a yarn for dyeing; characterized by comprising the method for generating an artificial intelligence learning-based waterless dyeing pattern.
A method for generating an artificial intelligence learning-based waterless dyeing pattern, characterized in that, in claim 10, dye ink is applied to the outer surface of the vacuum barrier sheet and, when step (S6) is performed, the dye ink of the vacuum barrier sheet is also transferred to the yarn and dyed.

Description

System and Method for Generating Waterless Dyeing Patterns based on Artificial Intelligence Learning The present invention relates to anhydrous dyeing patterning, and more specifically, to a system and method for generating anhydrous dyeing patterns based on artificial intelligence learning, which enables improved dyeing quality by implementing an anhydrous dyeing device for yarn using vacuum transition and predicting and generating desired patterns through learning using artificial intelligence. Generally, to express various patterns or colors in fabrics, a method using different colored threads for the warp and weft was employed. However, this fabric production method resulted in standardized patterns and colors that could not be varied, and obtaining unique images required multiple preparation steps, leading to significant increases in production costs. In addition, in order to partially dye yarn, it is necessary to equip multiple dyeing tanks and go through multiple winding processes, which requires a lot of equipment and the resulting installation costs are a factor that increases production costs. Furthermore, the multiple winding processes are not only very cumbersome, but there is also a problem that dyeing into irregular shapes is not done well. To solve this problem, Korean Registered Utility Model No. 20-0334356 discloses a multi-color dyeing device capable of providing yarns of various colors by spraying pigment onto the outer diameter of yarn wound on a bobbin and performing vacuum suction so that the sprayed pigment can be uniformly absorbed into the inner diameter. However, conventional dyeing devices, including the aforementioned registered utility model, utilize a method of spraying or dipping a liquid mixed with dye, which generates a large amount of pollutants and wastewater during the dyeing process. Consequently, purifying these pollutants requires significant time and cost, which not only reduces economic efficiency but also makes complete purification difficult, thereby having a negative impact on the environment. Accordingly, the applicant has developed a vacuum transfer device (Republic of Korea Registered Patent No. 10-2389252) capable of anhydrous dyeing yarn by winding yarn to be dyed onto the outer surface of a porous drum-shaped jig, covering the outer surface with a transfer sheet coated with dye ink, and then generating vacuum pressure through the internal space of the dyeing jig to transfer the dye ink to the yarn. The 'vacuum transfer device for anhydrous dyeing of yarn' of the aforementioned registered patent has the advantage of improving economic efficiency and eco-friendliness, as the dyeing process can be carried out very quickly and easily using heating and vacuum transfer methods without using liquid, and since there is no need to purify the liquid for dyeing. However, there is a problem in that during the vacuum transfer process of the dye ink from the transfer sheet to the yarn, uneven vacuum pressure occurs between the holes (vacuum holes) of the jig and the outer part of the holes, which may result in marks on the yarn corresponding to the holes of the jig. Meanwhile, depending on the weaving method, the finished fabric is classified into plain weave, twill weave, and satin weave based on how the vertical warp threads and horizontal weft threads are interwoven. When producing fabric using yarns with the same dyeing pattern, the resulting fabric pattern varies depending on the weaving method; therefore, if a specific fabric pattern is desired, it must be woven using yarns with a corresponding dyeing pattern. In such fabric weaving processes, there is a problem of reduced work efficiency due to the many factors that must be considered during the patterning process to weave a fabric with a desired pattern. Therefore, there is a need for the development of new technology that improves the dyeing quality of yarn, predicts and generates desired patterns in advance according to the weaving method to provide to workers, and enables the creation of fabric patterns based on the yarn dyeing pattern. FIG. 1 is a system configuration diagram for generating anhydrous dyeing patterns based on artificial intelligence learning according to the present invention. Figure 2 is a detailed configuration diagram of the pattern learning and prediction generation management server. Figure 3 is a detailed configuration diagram of the pattern collection unit. Figure 4 is a detailed configuration diagram of the pattern learning unit. Figure 5 is a detailed configuration diagram of the pattern prediction generation unit. FIG. 6 is a flowchart illustrating a method for generating an anhydrous dyeing pattern based on artificial intelligence learning according to the present invention. FIG. 7 is a cross-sectional view showing a yarn anhydrous dyeing apparatus using vacuum transition according to an embodiment of the present invention. FIG. 8 is an exploded perspective view showing the anhydrous