Rib jacquard fabric texture digitization design system

Abstract

This invention relates to the field of computer-aided design technology, specifically a digital design system for rib jacquard fabric textures. The system includes a jacquard pattern structure conversion module, used to acquire the coordinate parameters of coil nodes and the connection direction parameters of adjacent coil nodes within the design pattern, establish a jacquard directed graph, extract the surface identification parameters of coil nodes, assign cross-layer weight values ​​to directed edge parameters based on the difference in surface identification parameters, and fuse the cross-layer weight values ​​with the jacquard directed graph to generate a weighted graph dataset. In this invention, by comparing risk values ​​with separation threshold parameters, a node reconstruction distribution set is automatically established within abnormal grid areas, replacing the original connection direction attributes to generate a digital jacquard pattern set, thus completing a closed-loop, intelligent repair of design defects. This allows fabric structural defects to be detected and eliminated during the design phase, avoiding repeated trial and error in the physical sampling process and improving design efficiency and first-time success rate.

Description

Technical Field

[0001] This invention relates to the field of computer-aided design technology, and in particular to a digital design system for the texture of ribbed jacquard fabric. Background Technology

[0002] Computer-aided design technology is a technology that uses computer hardware and software, as well as graphics peripherals, to assist engineers in performing a series of tasks such as product design, modification, analysis, and optimization.

[0003] Current computer-aided design (CAD) technology in the field of ribbed jacquard fabric design primarily focuses on the two-dimensional drawing and editing of design sketches. Its core function is to realize the designer's visual creativity, but it lacks an understanding of the inherent three-dimensional physical structure of the fabric. This operational mode leads to a disconnect between design and manufacturing. Computers can only present the colors and arrangement of patterns, failing to simulate the actual physical form and stress state of yarns during weaving due to factors such as interlayering and long-distance floats. For example, when a designer draws a large area of ​​solid color, current technology cannot anticipate that this design will physically create an excessively long float that is not interwoven with other layers. This float is easily snagged and broken during actual wear, causing uneven surface tension in the fabric, affecting aesthetics and durability. Therefore, improvements are needed. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a digital design system for rib jacquard fabric texture.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a digital design system for rib jacquard fabric textures includes:

[0006] The jacquard diagram structure conversion module is used to obtain the coordinate parameters of the coil nodes and the connection direction parameters of the adjacent coil nodes in the design diagram, establish a jacquard directed graph set, extract the surface identification parameters of the coil nodes, assign cross-layer weight values ​​to the directed edge parameters according to the difference of the surface identification parameters, and fuse the cross-layer weight values ​​with the jacquard directed graph set to generate a weighted graph data set.

[0007] The floating line span detection module is used to extract the feature vectors of continuous edges with the same attribute in the weighted graph dataset, generate the cumulative value of the same path, compare the cumulative value of the same path with the built-in span warning threshold, and establish the local tension deviation.

[0008] Combined with the fastness verification module, it is used to retrieve the jacquard matrix color change status items within the local tension deviation distribution area, mark the positions where color change status items are generated as color change connection points, mark the positions where color change status items are not generated as non-interlaced suspension points, calculate and generate a pixel spacing matrix set, extract the maximum peak parameter within the pixel spacing matrix set, fuse the maximum peak parameter with the built-in knitting machine needle pitch parameter, and establish a peeling bubbling risk value.

[0009] The constraint node reconstruction module is used to compare the peeling bubble risk value with the separation threshold parameter, establish a node reconstruction distribution set, and use the node reconstruction distribution set to replace the original connection pointing attribute items of the corresponding area of ​​the weighted graph data set to generate a digital jacquard pattern set.

[0010] Preferably, the steps for obtaining the weighted graph dataset are as follows:

[0011] Obtain the coordinate parameters of the coil nodes and the connection pointing parameters of adjacent coil nodes in the design graph. Convert the coordinate parameters of the coil nodes into graph vertex parameters and the connection pointing parameters of adjacent coil nodes into directed edge parameters. Establish the topological mapping relationship between the graph vertex parameters and the directed edge parameters to generate a jacquard directed graph set.

[0012] Based on the jacquard directed graph, extract the depth scalar and planar coordinate components of the graph vertex parameters corresponding to the coil nodes, and calculate the cross-layer weight values ​​corresponding to the directed edge parameters.

[0013] Assign cross-layer weight values ​​to the corresponding directed edge parameters within the jacquard directed graph set, parse the cross-layer weight values ​​and the topological structure of the jacquard directed graph set, perform accumulation operations on the same origin directed edge paths, update the association attributes of the global graph vertex parameters, and generate a weighted graph data set.

[0014] Preferably, the step of obtaining the cumulative value of the same-direction path is as follows:

[0015] The network topology of the weighted graph dataset is analyzed, the feature vectors of consecutive edges with the same attribute are extracted from the weighted graph dataset, the path is traversed along the corresponding positions of the feature vectors of consecutive edges with the same attribute, and the edge length values ​​on the path are accumulated item by item to generate the cumulative value of the same path.

[0016] Preferably, the step of obtaining the local tension deviation is as follows:

[0017] A built-in span warning threshold is set. If the cumulative value of the same-direction path is greater than the built-in span warning threshold, the coil node position coordinates corresponding to the built-in span warning threshold are filtered. Based on the coil node position coordinates, a topological space search is performed to extract the cross surface layer distribution density parameters.

[0018] The cross-surface layer distribution density parameters are arranged into a diagonal density matrix. The network adjacency matrix contained in the weighted graph dataset is extracted. Matrix multiplication is performed based on the diagonal density matrix and the network adjacency matrix. The product value vector of the operation output is extracted to establish the local tension deviation.

[0019] Preferably, the step of obtaining the pixel spacing matrix set is as follows:

[0020] Retrieve the jacquard matrix color-changing state items within the local tension deviation distribution area, compare the color change characteristics of the internal spectrum of the jacquard matrix color-changing state items, mark the positions where color-changing state items are generated as color-changing connection points, and mark the positions where color-changing state items are not generated as non-interlaced suspension points.

[0021] Extract the planar grid coordinates of the color-changing connection points and the non-interlaced suspended points, measure the straight-line pixel spacing between each non-interlaced suspended point and the adjacent color-changing connection point, and arrange the straight-line pixel spacing values ​​to generate a pixel spacing matrix set.

[0022] Preferably, the step of obtaining the node reconstruction distribution set is as follows:

[0023] Extract the separation threshold parameter, compare the peeling bubbling risk value with the separation threshold parameter, filter the abnormal grid regions corresponding to the peeling bubbling risk value being greater than or equal to the separation threshold parameter, locate the planar boundary vertices inside the abnormal grid regions, and delineate the spatial coordinates of the planar boundary vertices as the reconstruction coordinates.

[0024] Preferably, the step of obtaining the node reconstruction distribution set further includes:

[0025] Alternating positive and negative constraint nodes are inserted into the closed spatial region defined by the reconstructed coordinates. The planar grid coordinate system position of the alternating positive and negative constraint nodes is read. The spatial straight-line spacing between each alternating positive and negative constraint node and its neighboring nodes is measured. The spatial straight-line spacing is converted into a connection distance vector with directional attributes. All connection distance vector data are integrated to establish a node reconstruction distribution set.

[0026] Preferably, the step of obtaining the digital jacquard pattern set is as follows:

[0027] Retrieve the reserved weighted graph data set, perform topological addressing within the weighted graph data set based on the reconstructed coordinates, locate the corresponding area within the weighted graph data set that needs to be repaired, use the node reconstruction distribution set to forcibly replace the original connection pointing attribute items of the corresponding area in the weighted graph data set, recalculate the topological connection weight values ​​around the replacement node, update the underlying correlation between various attribute items, and generate a digital jacquard pattern set.

[0028] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0029] In this invention, visual information within the design drawing is converted into a jacquard directed graph containing three-dimensional spatial relationships. Based on the difference in surface identification parameters of the coil nodes, weighted values ​​are assigned to the directed edges across layers, constructing a weighted graph dataset capable of simulating the physical properties of the fabric. This achieves a transformation from two-dimensional planar design to three-dimensional physical structure quantitative analysis. Based on this dataset, the cumulative value of unidirectional paths is calculated by extracting feature vectors of continuous edges with the same attribute. Combined with a built-in span warning threshold, a local tension deviation is established, enabling the identification of potential stress concentration areas in the fabric structure caused by long floats. Furthermore, by comparing the color-changing status items of high-risk areas, color-changing connection points and non-interlaced suspended points are distinguished. Combined with the pixel spacing matrix set and built-in loom needle pitch parameters, a peeling and bubbling risk value is established. This deeply correlates abstract design defects with specific physical peeling risks, providing measurable failure prediction. Finally, by comparing risk values ​​with separation threshold parameters, a node reconstruction distribution set is automatically established within the abnormal grid area, and this set replaces the original connection pointing attributes, generating a digital jacquard shaping set. This completes the closed-loop, intelligent repair of design defects. This allows fabric structural defects to be detected and eliminated during the design phase, avoiding repeated trial and error in the physical sampling process and improving design efficiency and first-time success rate. Attached Figure Description

[0030] Figure 1 This is a system flowchart of the present invention. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0032] Please see Figure 1 This invention provides a technical solution: a digital design system for the texture of rib jacquard fabrics, comprising:

[0033] The jacquard diagram structure conversion module is used to obtain the coordinate parameters of the coil nodes and the connection direction parameters of adjacent coil nodes in the design diagram, establish a jacquard directed graph set, extract the surface identification parameters of the coil nodes, assign cross-layer weight values ​​to the directed edge parameters according to the difference of the surface identification parameters, and merge the cross-layer weight values ​​with the jacquard directed graph set to generate a weighted graph data set.

[0034] The floating line span detection module is used to extract the feature vectors of continuous edges with the same attribute in the weighted graph dataset, generate the cumulative value of the same path, compare the cumulative value of the same path with the built-in span warning threshold, and establish the local tension deviation.

[0035] Combined with the fastness verification module, it is used to retrieve the jacquard matrix color change status items in the local tension deviation distribution area, mark the positions where color change status items are generated as color change connection points, mark the positions where color change status items are not generated as non-interlaced suspension points, calculate and generate a pixel spacing matrix set, extract the maximum peak parameter in the pixel spacing matrix set, fuse the maximum peak parameter with the built-in knitting machine needle pitch parameter, and establish a peeling bubbling risk value.

[0036] The constraint node reconstruction module is used to compare the stripping bubble risk value with the separation threshold parameter, establish a node reconstruction distribution set, and use the node reconstruction distribution set to replace the original connection pointing attribute items of the corresponding area of ​​the weighted graph data set to generate a digital jacquard pattern set.

[0037] The steps to obtain a weighted graph dataset are as follows:

[0038] Obtain the coordinate parameters of the coil nodes and the connection pointing parameters of adjacent coil nodes in the design graph. Convert the coordinate parameters of the coil nodes into graph vertex parameters and the connection pointing parameters of adjacent coil nodes into directed edge parameters. Establish the topological mapping relationship between the graph vertex parameters and the directed edge parameters to generate a jacquard directed graph set.

[0039] Based on the jacquard directed graph atlas, extract the planar coordinate components of the depth scalar and graph vertex parameters corresponding to the coil nodes, and calculate the cross-layer weight values ​​corresponding to the directed edge parameters. The calculation formula is as follows:

[0040] ;

[0041] in, For the first The parameters of the first graph vertex and the first The cross-layer weight values ​​corresponding to the directed edge parameters between the vertex parameters of the graph. This is the interlayer coupling strength coefficient. For the first The depth scalar corresponding to the vertex parameters of the graph. For the first The depth scalar corresponding to the vertex parameters of the graph. For the maximum reference depth scalar, For the first The horizontal plane coordinate components of the vertex parameters of the graph. For the first The horizontal plane coordinate components of the vertex parameters of the graph. For the first The vertical plane coordinate components of the vertex parameters of the graph For the first The vertical plane coordinate components of the vertex parameters of the graph For the first The parameters of the first graph vertex and the first The fundamental connection length parameter between the vertices of a graph;

[0042] Assign cross-layer weight values ​​to the corresponding directed edge parameters within the jacquard directed graph atlas, parse the cross-layer weight values ​​and the topological structure of the jacquard directed graph atlas, perform accumulation operations on the same origin directed edge paths, update the association attributes of the global graph vertex parameters, and generate a weighted graph dataset.

[0043] Specifically, based on the obtained coordinate parameters of the coil nodes within the design drawing and the connection pointing parameters of adjacent coil nodes, the design drawing data first needs to be parsed. The design drawing is stored in a digital format, such as a 256-color bitmap file, where each color represents a specific yarn or a specific fabric layer. For example, color index 0 represents the front bottom layer yarn, color index 1 represents the front top layer yarn, color index 2 represents the back bottom layer yarn, and color index 3 represents the back top layer yarn. By reading the pixel matrix of the bitmap file, the coordinates of each pixel are... Extract its color value, among which These are the coordinate parameters of the loop nodes. Subsequently, according to the preset weaving sequence logic, the connection relationship of each loop node is determined. This logic is based on the stitch patterns of the knitting process. For example, in a plain weave, the row of loops... Normally connected to and These connections are recorded as a series of connection pointing parameters, such as a directed connection from node A to node B. Then, these extracted parameters are transformed into a graph theory structure, with each unique coil containing node coordinates. It is instantiated as a graph vertex object, assigned a unique identifier, such as V_i, and its coordinates are... As its core attribute storage, each connection pointer parameter, for example, from node A... To node B The connection is transformed into a directed edge E(V_A, V_B) from vertex V_A to vertex V_B. By traversing all the coil nodes and connection points, a set of all vertices and directed edges is constructed. Finally, a topological mapping relationship between these graph vertex parameters and directed edge parameters is established. This mapping relationship is specifically implemented through an adjacency list data structure. Each entry in the adjacency list corresponds to a graph vertex and contains a list of all target vertices connected by outgoing edges of that vertex. After the adjacency list is constructed, a complete jacquard directed graph set that can digitally represent the jacquard fabric coil connection structure is formed.

[0044] The formula for calculating the cross-layer weight value simulates the tension and stability of yarn connections in the physical world, calculating a cross-layer weight value for each directed edge in the jacquard directed graph. This formula integrates the spatial three-dimensional relationship between coils, specifically reflected in two core parts. The first part is the exponential term. This is used to quantify the instability caused by yarn crossing different layers in the fabric thickness direction (Z-axis), when two loops are located in the same layer ( When the number of layers traversed increases, this term is 1, indicating the most stable connection. As the number of layers traversed increases, the value of this term decays exponentially, representing a decrease in connection strength. The second part is the cosine term. This is used to quantify the effect of the yarn connection length on stability in the fabric plane (XY plane), when two loops are closely adjacent in the plane (physical distance in the plane). When the cosine term approaches 0, it approaches 1, indicating high connection strength. As the planar distance increases, this term approaches 0, reflecting the connection slack and instability caused by the long float. This is achieved by combining these two parts with the dimensionless interlayer coupling strength coefficient. By multiplying, the formula can comprehensively evaluate the stability of coil connections in three-dimensional space.

[0045] The steps for obtaining the (interlayer coupling strength coefficient) are as follows: This parameter is a dimensionless adjustment coefficient used to calibrate and scale the entire weighting calculation system. A representative set of rib jacquard fabric samples is selected, covering various situations from structural stability to those with obvious floating threads or peeling risks. Each sample undergoes a physical evaluation, and senior fabric engineers score it based on its structural tightness, hand feel, and appearance defects (such as bubbling), resulting in an empirical stability score ranging from 0 to 100. Simultaneously, this system was used to analyze the digital design drawings of these samples. With the weights temporarily set to 1, calculate the average weight of all edges for each fabric sample. Next, we will establish an empirical stability score. with average weight The functional relationship between them aims to find a... Value, such that after Scaled average weight and The strongest linear correlation is found by the least squares method, i.e., finding... Make Minimum, of which It is a transformation constant, usually The design aims to distribute the calculated weights within a meaningful interval. For example, through testing and regression analysis on 20 different rib jacquard samples, it was found that when... When the value is set to 0.85, the correlation coefficient between the calculated average weight and the expert rating reaches a peak of 0.92. Therefore, It was determined to be 0.85 as a universality factor applicable to this type of fabric.

[0046] The steps to obtain the (planar physical distance) are as follows: This parameter is the actual physical length of the yarn connecting the two loops on the fabric plane, in millimeters (mm). The calculation is based on the pixel coordinates in the design drawing and the physical parameters of the loom. First, the two connected nodes are extracted from the graph vertex parameters of the jacquard directed graph atlas. and Planar pixel coordinates and Then, calculate their Euclidean distance on the pixel grid, i.e., pixel distance. The unit of this distance is "pixel," which has no physical meaning. To convert it into physical length, a pixel-to-millimeter conversion factor needs to be introduced. This coefficient is obtained through the fabric sampling and calibration process. Specifically, a simple fabric with a known design dimension (e.g., a width of 200 pixels) is woven, and then its actual physical width (e.g., 60 mm) is precisely measured using calipers to calculate the coefficient. Finally, the pixel distance is multiplied by the conversion factor to obtain the planar physical distance. For example, if the pixel coordinates of two nodes are (10, 5) and (12, 6) respectively, then their pixel distance is... Pixels, after applying conversion factors, planar physical distance mm.

[0047] and The steps to obtain the (depth scalar) are as follows: these two parameters represent the first... The and the first The layer position of each vertex (i.e., loop) in the fabric thickness direction is a dimensionless integer value, directly parsed from the color information of the design drawing. During the digital design phase, designers assign specific colors to different areas or functions of loops in the design drawing. Each color corresponds to a weaving instruction, which includes the layer information of the loop. The system has a built-in color-layer mapping table to convert pixel color values ​​into specific depth scalars. For example, a typical double-sided rib jacquard fabric contains two main layers, the front and the back. The mapping table can be defined as follows: a red pixel with an RGB value of (255, 0, 0) represents the front loop, and its depth scalar... A blue pixel set to 1 with an RGB value of (0, 0, 255) represents the reverse coil, and its depth scalar... When set to 2, the system reads the pixel color of each coil node position and queries the mapping table when parsing the schematic diagram. For example, if the node... If a pixel is located at coordinates (10, 20) and its color is red (255, 0, 0), then the system will look up the mapping table and... If the value is assigned to 1, then the node it connects to... If a pixel is located at coordinates (11, 20) and its color is blue (0, 0, 255), then... It was assigned the value 2.

[0048] The steps for obtaining the (maximum reference depth scalar) are as follows: This parameter is used to normalize the depth difference, keeping its influence in the formula within a controllable range. Its value is determined by the set of all defined depth scalars in the currently processed illustration, and is a dimensionless integer. This value is determined after the system parses the entire illustration and assigns a depth scalar to each coil node. Then, it will iterate through all the depth scalar values ​​and find the maximum value. and minimum value Maximum reference depth scalar This is the difference between the two, calculated using the following formula: This parameter is calculated dynamically and depends on the specific design. For example, in a design, only the front side is used ( ) and the opposite ( There are two levels, so , ,therefore If a more complex design introduces an additional intermediate layer, for example, the front ( ), intermediate layer ( ), reverse side ( ),So , Calculation In this way, regardless of how many layers are used in the design, The ratio is always constrained to be between 0 and 1.

[0049] The steps to obtain the (basic connection length parameter) are as follows: This parameter represents the basic yarn length between two coils under ideal conditions, and its unit is millimeters (mm), relative to the physical distance in the plane. The dimensions are consistent, and its value is mainly determined by the physical specifications of the loom, namely the needle pitch. The needle pitch refers to the distance between the centers of two adjacent needles on the loom, which is a core process parameter and a basic connection length parameter. The setting aims to provide a physical scale reference for calculating planar distances and to adjust the sensitivity of the cosine term, the value of which is obtained by consulting the loom equipment manual or actual measurement. For example, for a commonly used computerized flat knitting machine, its stitch length... It may be 1.2mm, for the sake of simplifying the model. It can be set to a fixed value related to the stitch length because it mainly serves a regularization function in the formula, preventing issues caused by... When the denominator is extremely small, for example, it can be directly set. mm.

[0050] Calculations based on parameters:

[0051] Define a specific computational scenario, and compute from the vertices of a graph. arrive The cross-layer weight value corresponding to the directed edge ,

[0052] First, obtain all the necessary parameter values.

[0053] The dimensionless interlayer coupling strength coefficient is obtained through the aforementioned empirical calibration. ,

[0054] Obtain nodes from the color-level mapping table of the design diagram. and Depth scalar, setting nodes The coil is on the front side. ,node For reverse coils, ,

[0055] Calculate the maximum reference depth scalar based on all layers used in the design (front layer 1 and back layer 2). ,

[0056] Read nodes from the vertex data of the jacquard directed graph atlas. The plane coordinates are ,node The plane coordinates are (Unit: pixels), set the pixel-to-millimeter conversion factor. mm / pixel

[0057] Set the basic connection length parameter according to the loom specifications. mm,

[0058] Calculate planar physical distance :

[0059] Pixel distance Pixel;

[0060] mm;

[0061] Calculate the absolute value of the depth difference:

[0062] ;

[0063] Substitute all the parameters with unified dimensions into the formula Calculated .

[0064] This result indicates that the connection node and nodes The directed edge has a cross-layer weight of 0.1981. This value is a dimensionless relative strength measure that comprehensively reflects the decrease in physical stability caused by the yarn connection crossing different layers and having a certain distance in the plane. The closer the value is to the sum of its values, the greater the stability. (0.85 here) indicates a more robust connection, while a value closer to 0 indicates a weaker and less stable connection. The weight value of 0.1981 is relatively low, indicating that this connection is a potential weak point. The system will subsequently use this value as the weight attribute of this directed edge and store it in the weighted graph dataset.

[0065] After calculating the cross-layer weights of all corresponding directed edge parameters within the jacquard directed graph, these weights are assigned to each edge in the graph. Specifically, this involves traversing the adjacency list in the jacquard directed graph. For each E(g, h) connection represented in the adjacency list, the calculated weights are... The value is stored as the weight attribute of the edge. Next, the topology of the graph carrying the weight information is parsed, and the association attributes of the graph vertices are updated accordingly. This process aims to aggregate the local weight information of the edges into global parameters that reflect the node state. First, a set of association attributes is initialized for each graph vertex parameter (i.e., coil node), such as "sum of in-degree strength", "sum of out-degree strength", and "average connection strength". Then, all vertices in the graph are traversed again, and for the vertex currently being processed... Retrieve all its incoming edges (pointing to) (edges) and outgoing edges (from) Starting from the edge, sum the cross-layer weights of all incoming edges, and update the result to... Similarly, in the "sum of in-degree strengths" attribute, the weights of all outgoing edges are accumulated, and the "sum of outgoing degree strengths" attribute is updated. The average connection strength can be calculated by adding the sum of in-degree and outgoing degree strengths and dividing by the total number of edges (in-degree plus outgoing degree). For example, a vertex has three ingoing edges with weights of 0.8, 0.5, and 0.9, and two outgoing edges with weights of 0.7 and 0.4. Its sum of in-degree strengths is 2.2, its sum of outgoing degree strengths is 1.1, and its average connection strength is (2.2 + 1.1) / 5 = 0.66. By performing this accumulation and update operation on all vertices in the graph, the jacquard directed graph set that originally only contained connection relationships is transformed into a complex network containing node states and quantified connection strength information, ultimately generating a weighted graph dataset.

[0066] The steps to obtain the cumulative value of the same path are as follows:

[0067] The network topology of the weighted graph dataset is analyzed, the feature vectors of consecutive edges with the same attribute are extracted, the path is traversed along the corresponding positions of the feature vectors of consecutive edges with the same attribute, and the edge length values ​​on the path are accumulated item by item to generate the cumulative value of the same path.

[0068] Specifically, to analyze the network topology of a weighted graph dataset, the first step is to identify continuous edges with the same attributes. Here, edges with the same attributes specifically refer to edges connecting two coil nodes located on the same fabric layer. For example, in a weighted graph dataset, each vertex (coil node) stores its depth scalar. If an edge connects two vertices and Having the same depth scalar, i.e. If the edge is found to be of the same attribute, it is marked as such. Then, to extract the feature vector formed by consecutive edges of the same attribute, a depth-first search algorithm is used to traverse the graph. Starting from any unvisited vertex, the algorithm explores along its outgoing edges. If the outgoing edge is of the same attribute, the algorithm continues along that path, recording the identifiers of all vertices on the path and the physical lengths of the edges (i.e., the planar physical distances calculated in the previous step). The path length is recorded in a temporary path sequence until a non-same-attribute edge or path endpoint is encountered. This process generates one or more path sequences, each representing a continuous floating line. For example, a sequence might be [V1, V2, V3], with corresponding edge lengths [D_{plane(1,2)}, D_{plane(2,3)}]. Subsequently, for each extracted path sequence, path traversal is performed along its corresponding position, and the edge length values ​​on the path are accumulated item by item. Specifically, for the path [V1, V2, ..., Vk], its total length is calculated. This total length This refers to the physical length of the continuous floating line. All identified floating lines and their calculated physical lengths are stored to form a set containing the lengths of multiple floating lines. Each value in this set is a cumulative value of a path in the same direction.

[0069] The steps for obtaining the local tension deviation are as follows:

[0070] Set a built-in span warning threshold. If the cumulative value of the same path is greater than the built-in span warning threshold, filter the coil node position coordinates that exceed the built-in span warning threshold, and perform topological space search based on the coil node position coordinates to extract the cross surface layer distribution density parameters.

[0071] The distribution density parameters of the cross-surface layer are arranged into a diagonal density matrix. The network adjacency matrix contained in the weighted graph dataset is extracted. Matrix multiplication is performed based on the diagonal density matrix and the network adjacency matrix. The product value vector of the operation output is extracted to establish the local tension deviation.

[0072] Specifically, based on the cumulative value of the same-direction path generated in the previous step, a built-in span warning threshold needs to be set first. This threshold is set according to the intended use of the fabric, the type of yarn, and the knitting machine's needle pitch. For example, for a 14-gauge (approximately 1.8 mm) wool sweater worn close to the skin, excessively long floats are generally not allowed to avoid snagging and ensure a smooth surface. Experience shows that floats exceeding 6 consecutive needle positions pose a risk. Therefore, the threshold can be set to 6 * 1.8 mm = 10.8 mm. If a cumulative value of the same-direction path, such as 12.5 mm, exceeds this 10.8 mm threshold, all loop nodes constituting that path will be filtered out, and their planar coordinates will be recorded. For example, if the cumulative length of the path [V10, V11, V12, V13] exceeds the limit, then the coordinates (X10, Y10) to (X13, Y13) will be recorded. All nodes are marked. Then, a topological space search is performed based on the coordinates of these marked coil nodes. This search aims to analyze the structural stability around these long floating line regions. Specifically, for each marked node, all nodes within its neighborhood of radius k (e.g., k=2) are searched in the weighted graph dataset; these are all nodes reachable by no more than two edges. Then, the number of "interface layer" connections within this neighborhood is counted, i.e., the depth scalar of the nodes at both ends of each edge. They are different. The cross-surface layer distribution density parameter is defined as an index to measure the degree of local interweaving, and its calculation can be performed as follows: ,in This is the number of cross-face connections found within the neighborhood of the node. If there are no cross connections within the neighborhood of a node in a long floating line region ( If the density parameter is 1, it indicates the lowest degree of interweaving and the highest risk. Conversely, if there are many cross connections, the parameter value decreases, indicating a more stable structure. Finally, such a cross surface layer distribution density parameter is calculated for each out-of-standard node.

[0073] After obtaining the cross-surface layer distribution density parameters of each node within the area exceeding the warning threshold, these parameters are arranged into a diagonal density matrix. If the area contains If there are 1 node, then It is A matrix, where the diagonal elements The value is equal to the first The distribution density parameters of the cross-surface layer of each node are set, with all off-diagonal elements being 0. Then, these parameters are extracted from the weighted graph dataset. A weighted adjacency matrix consisting of nodes , of which elements Equal to from node To the node Cross-layer weight values ​​of directed edges If there is no connection, the value is 0, based on the diagonal density matrix. and network adjacency matrix Perform matrix multiplication to obtain the product matrix. Product matrix Each element in Represents the node To the node Passing through nodes The contribution of connection tension after self-interlacing sparsity correction, and finally, the product matrix. Summing each row, extracting the product vector from the output, and thus establishing the local tension deviation of each node, the vector contains the nth... element The calculation formula is: ,in, It is the first Local tension deviation at each node It is the total number of nodes in this region. It's a summation index, traversing from 1 to... , It is a product matrix In the Line number The elements of the column, this summation process summarizes the elements from the node. All modified connection tension contributions from the starting point are obtained. The higher the value, the stronger the node. The greater the deviation in local structural tension, the better.

[0074] The steps to obtain the pixel spacing matrix set are as follows:

[0075] Retrieve the jacquard matrix color-changing state items within the local tension deviation distribution area, compare the color change characteristics of the internal spectrum of the jacquard matrix color-changing state items, mark the positions where color-changing state items occur as color-changing connection points, and mark the positions where color-changing state items do not occur as non-interlaced suspended points.

[0076] Extract the planar grid coordinates of the color-changing connection points and the non-interlaced suspended points, measure the straight-line pixel spacing between each non-interlaced suspended point and the nearest color-changing connection point, and arrange the straight-line pixel spacing values ​​to generate a pixel spacing matrix set.

[0077] Specifically, the local tension deviation calculated in the previous stage is retrieved. This deviation exists in the form of a numerical vector, where each value corresponds to the tension concentration of a coil node. First, nodes with values ​​higher than a preset tension threshold are selected. This threshold is set based on the fabric type and historical production data. For example, for easily deformable silk fabrics, the threshold is set to 2.5, while for structurally stable cotton fabrics, it is set to 4.0. The area formed by nodes exceeding the threshold is the "local tension deviation distribution area". Next, the coordinates of this area are mapped back to the original jacquard matrix, i.e., the design diagram, to facilitate the analysis of the color composition of this area. For each pixel (i.e., coil node) in this area, a comparison of the color change characteristics of the pattern is performed. This comparison process is achieved by checking the color values ​​of a central pixel and its eight neighboring pixels (i.e., the moiré neighborhood). If the color value of the central pixel is different from the color value of any of its neighboring pixels, for example, the RGB value of the central pixel is (255, 0, 0) representing the front red yarn, while the RGB value of its right neighboring pixel is (0, ... (0,255) represents the reverse blue yarn. This color difference constitutes a "color change state item," which physically indicates that two different yarns or two different fabric layers have interwoven at this point. The position of the center pixel is marked as a color change connection point because it plays a role in connecting and fixing different fabric structures. Conversely, if the color value of the center pixel is exactly the same as the color values ​​of all its adjacent pixels, such as a continuous red area, it means that no color change has occurred here, and no color change state item has been generated. This indicates that the yarn here is continuously floating on the same layer and has not interwoven with other layers. These positions are therefore marked as uninterwoven suspended points. By traversing all pixels within the local tension deviation distribution area, two sets of detailed coordinate lists are finally obtained: one set is the coordinate set of all color change connection points, and the other set is the coordinate set of all uninterwoven suspended points.

[0078] Based on the set of coordinates of the color-changing connection points and the set of coordinates of the non-interlaced suspended points generated in the previous step, these two sets of planar grid coordinate data are first loaded into the processing program, with the coordinates in... The data is stored in the form of a matrix representing the pixel position of the unstitched yarn point in the jacquard matrix. Next, for each unstitched yarn point, the distance between it and the nearest color-changing connection point needs to be calculated. This process is implemented through an iterative calculation. For any unstitched yarn point P_s(Xs, Ys) in the list, the entire set of color-changing connection point coordinates is traversed, and the linear pixel distance between P_s and each color-changing connection point P_c(Xc, Yc) in the set is calculated. This distance is calculated using the Euclidean distance formula, which is the square root of the sum of the squares of the differences in the x-coordinates and y-coordinates of the two coordinate points. After traversing all color-changing connection points, a series of distance values ​​are obtained. The smallest value is selected as the final linear pixel distance for the unstitched yarn point P_s. This value represents how far an unfixed yarn point is from its nearest "anchor point." This calculation process is repeated for all unstitched yarn points until each yarn point obtains a corresponding minimum linear pixel distance value. Then, to transfer these discrete values... The spacing values ​​are integrated to create a two-dimensional matrix of the same size as the local tension deviation distribution area, namely the pixel spacing matrix. Each coordinate point in this area is traversed. If the coordinate point was marked as a color-changing connection point in the previous step, the value 0 is filled in the corresponding position in the pixel spacing matrix. If the coordinate point is marked as an uninterwoven suspended point, the minimum straight-line pixel spacing value of the point calculated earlier is filled in. Since there may be multiple independent tension deviation areas in the fabric, a corresponding pixel spacing matrix is ​​generated for each area. All these matrices together constitute the final pixel spacing matrix set.

[0079] The steps to obtain the peeling blister risk value are as follows:

[0080] Extract the maximum peak parameter contained within the pixel spacing matrix set. Using the maximum peak parameter, the built-in knitting machine needle pitch parameter, and the local tension deviation, calculate the peeling blister risk value. The calculation formula is as follows:

[0081] ;

[0082] in, To determine the risk of bubbling during peeling. This represents the local tension deviation. For the maximum peak parameter, This refers to the built-in knitting machine needle pitch parameters.

[0083] Specifically, the formula for calculating the risk of peeling and blistering incorporates the local tension deviation obtained from the preceding steps. This represents the internal stress accumulated by structures such as long floating lines, which is the fundamental driving force behind the defects. Secondly, through... This item establishes a non-linear relationship between the longest un-interlaced distance and the physical precision of the loom, where the maximum peak parameter ( ) represents the longest float span, while the built-in knitting machine needle pitch parameter ( ( ) is the basic unit of weaving. The 3 / 2 power form of this ratio causes the risk to increase dramatically with the increase of float length. It simulates the physical phenomenon that when the float length exceeds several stitch lengths, its instability will increase disproportionately. Finally, through The trigonometric function term introduces a smooth geometric factor ranging from 0 to 1. This factor is adjusted based on the relative magnitude of the maximum peak parameter and the needle spacing, especially when the float is very short. When the factor is close to 0, the risk value is suppressed. When the float is long, the factor is close to 1, which allows the effects of geometric instability to be fully released.

[0084] The steps for obtaining the (local tension deviation) are as follows: This parameter is directly derived from the calculation results of the previous step. In the previous step "Establishing Local Tension Deviation," a value quantifying the tension concentration of each coil node has been calculated, forming a product vector. When this step analyzes a specific area with a risk of peeling and bubbling, the values ​​of all nodes within the corresponding area are extracted from this vector, and the maximum value is selected as the representative tension deviation of that area. This maximum value represents the tension state of the most unstable node within the region, best reflecting the risk level of that region. For example, when analyzing a 5x5 pixel risk region, if the local tension deviation values ​​of 25 nodes in that region are retrieved, and the maximum value is found to be 2.85, then the value used for this risk calculation... It is assigned the value 2.85, which is a dimensionless value.

[0085] The steps for obtaining the (maximum peak parameter) are as follows: This parameter is extracted from the pixel spacing matrix generated in the previous step, representing the maximum span of the suspended floating line within the risk area. Its acquisition involves two steps: First, a global scan is performed on the specified pixel spacing matrix to find the maximum value of all elements, with the unit being "pixels." For example, after analyzing the pixel spacing matrix generated for a risk area, the maximum value in the matrix is ​​found to be 8.5 pixels. Second, this pixel-based distance value is converted to physical units (millimeters) using a pre-calibrated pixel-to-millimeters conversion factor. This is accomplished by weaving a sample of known physical dimensions and calculating it against the pixel dimensions of its design drawing, for example... mm / pixel, and finally, substituting into the formula... The value is the converted physical length, calculated using the following formula: Continuing from the previous example, mm, this 2.55 mm is the final value to be substituted into the risk calculation formula. Parameter value.

[0086] The steps to obtain the (built-in knitting machine needle pitch parameter) are as follows: This parameter is an inherent physical parameter of the weaving equipment, referring to the distance between the center points of two adjacent needles on the knitting machine's needle bed. It is a core indicator for measuring the precision of the knitting machine and determining the range of fabric density. Its unit is millimeters (mm). The value of this parameter is not calculated but is obtained directly from the specifications of the production equipment used, or determined by actually measuring the knitting machine's needle bed using precision measuring tools (such as vernier calipers). For example, when the design is for a 14-needle (14G) computerized flat knitting machine, its needle pitch specification is 14 needles per inch. Through unit conversion (1 inch = 25.4 mm), its needle pitch can be calculated as follows: In the system, this value is set as a built-in constant associated with the device model. In this calculation, it is used... mm, this parameter provides a physical scale benchmark for subsequent calculations.

[0087] Calculations based on parameters:

[0088] Define a specific calculation scenario to calculate the peeling bubbling risk value for a risk area. ,

[0089] First, obtain all the necessary parameter values.

[0090] From the calculation results of the previous steps, the maximum local tension deviation corresponding to the current risk area is retrieved to obtain... ,

[0091] By analyzing the pixel spacing matrix and performing unit conversion, the maximum peak parameter per physical unit is obtained. mm,

[0092] From the loom specification parameter library, retrieve the built-in loom needle pitch parameters corresponding to the currently set loom to obtain... mm,

[0093] Calculation begins:

[0094] The ratio in the computational geometric instability term:

[0095] ;

[0096] The square root of the computational geometric instability term:

[0097] ;

[0098] Calculate the ratio part of the trigonometric function factors:

[0099] ;

[0100] Calculate trigonometric factors:

[0101] ;

[0102] Multiply the results of each part to obtain the final risk value: ;

[0103] The results indicate that the risk of peeling and blistering in the specific area analyzed is 4.16. This is a dimensionless comprehensive risk score that quantifies the likelihood and severity of fabric separation or surface blistering defects in the area. The value itself does not represent any physical unit but serves as a relative risk indicator. This value of 4.16 will be passed to the next processing step and compared with a preset separation threshold parameter. If the value is higher than the threshold (e.g., the threshold is set to 3.5), it indicates that the structural defect risk in the area is too high, and the constraint node reconstruction process needs to be initiated to repair the organizational structure. If it is lower than the threshold, the risk is considered to be within an acceptable range and no action is required. Therefore, this value is a key basis for subsequent decision-making and automatic repair processes.

[0104] The steps to obtain the node reconstruction distribution set are as follows:

[0105] Extract the separation threshold parameter, compare the peeling bubbling risk value with the size of the separation threshold parameter, filter the abnormal grid regions corresponding to peeling bubbling risk values ​​that are greater than or equal to the separation threshold parameter, locate the planar boundary vertices inside the abnormal grid regions, and delineate the spatial coordinates of the planar boundary vertices as reconstruction coordinates.

[0106] Alternating positive and negative constraint nodes are inserted into the closed spatial region defined by the reconstructed coordinates. The planar grid coordinate system position of the alternating positive and negative constraint nodes is read. The spatial straight-line spacing between each alternating positive and negative constraint node and its neighboring nodes is measured. The spatial straight-line spacing is converted into a connection distance vector with directional attributes. All connection distance vector data are integrated to establish a node reconstruction distribution set.

[0107] Specifically, a separation threshold parameter is extracted. This parameter is set based on statistical analysis of historical production quality data. One hundred samples of produced rib jacquard fabric are collected, and each sample undergoes physical quality testing. The number of peeling and bubbling defects per square meter is recorded and categorized into "qualified" (less than 2 defects / square meter) and "unqualified" (greater than or equal to 2 defects / square meter). Simultaneously, a risk assessment algorithm is run on the digital jacquard files of these 100 samples to obtain the maximum peeling and bubbling risk value for each sample. By plotting the relationship curve between the risk value and the "unqualified" rate, a risk value point that can distinguish between qualified and unqualified samples with 95% accuracy is found. For example, a value of 3.5... 3.5 is set as the separation threshold parameter. Then, the peeling bubbling risk value of each region calculated in the previous step, for example, 4.16, is compared with the separation threshold parameter 3.5. Since 4.16 is greater than or equal to 3.5, the grid region corresponding to this value is filtered and marked as an abnormal grid region. Next, the boundary of the abnormal grid region needs to be located. The Moore's Neighborhood Tracking algorithm is used. Starting from any abnormal node in the region, its 8 adjacent points are checked in a clockwise direction. The first adjacent point that also belongs to the abnormal region is found and moved to that point. This process is repeated until the starting point is returned. The coordinates of all the nodes passed constitute the set of planar boundary vertices of the region. Finally, based on these planar boundary vertices... Given the coordinates, return to the original jacquard directed graph set to query their corresponding depth scalars. This expands two-dimensional planar coordinate points into three-dimensional spatial coordinate points. The set of these three-dimensional coordinate points is the reconstructed coordinates.

[0108] Within the closed spatial region defined by the reconstructed coordinates from the previous step, node insertion is performed using a checkerboard pattern. First, the main layers of the region are determined. For example, by statistically analyzing the depth scalar of the original nodes within the region, it is found that over 80% of the nodes are frontal (depth scalar). If the area is defined as the front, then virtual grid points are set within the area at fixed intervals (e.g., every 2 pixels). Insert a new constraint node at the specified location and assign it a depth scalar based on the chessboard logic. For example, if... If the sum is even, then insert a constraint node different from the main layer, i.e., a reverse node (depth scalar). If the sum is odd, insert a constraint node (depth scalar) identical to the one in the main layer. These newly inserted nodes are called alternating front and back constraint nodes. Next, the planar mesh coordinate system position and depth scalar of these newly inserted alternating front and back constraint nodes are read. For each newly inserted node, the spatial linear distance between it and its neighboring nodes is measured. The range of neighboring nodes is defined as all other nodes (including the original node and other newly inserted nodes) within a 5x5x3 cubic space centered on the new node. Then, each spatial linear distance is converted into a connection distance vector with directional attributes. Specifically, for a connection from new node A to neighboring node B, its vector is represented as... Finally, the connection distance vector data generated between all these new nodes and their neighboring nodes are integrated to form a list containing all the newly added connection information. This list is the node reconstruction distribution set.

[0109] The steps to obtain the digital jacquard pattern set are as follows:

[0110] Retrieve the reserved weighted graph data set, perform topological addressing within the weighted graph data set based on the reconstruction coordinates, locate the corresponding area within the weighted graph data set that needs to be repaired, use the node reconstruction distribution set to forcibly replace the original connection pointing attribute items of the corresponding area in the weighted graph data set, recalculate the topological connection weight values ​​around the replacement node, update the underlying correlation between various attribute items, and generate a digital jacquard pattern set.

[0111] Specifically, the reserved, unmodified original weighted graph dataset is retrieved, and topological addressing is performed in the adjacency list or adjacency matrix of the weighted graph dataset based on the reconstruction coordinates determined in the previous steps (i.e., the boundaries of the abnormal grid regions). This process is accomplished by traversing all graph vertices and checking whether their coordinates are within the closed region defined by the reconstruction coordinates. All vertices within the region and the edges connecting them are identified and collectively constitute the corresponding region that needs to be repaired. Subsequently, a forced replacement operation is performed, that is, all vertices and edges within the identified regions that need to be repaired are deleted from the weighted graph dataset. Next, the node reconstruction distribution set established in the previous step is read, and new vertices (i.e., nodes with alternating positive and negative constraints) and new edges (defined by the connection distance vector) are created in the graph based on the information contained therein. These new edges not only connect the newly inserted nodes but also connect the new nodes to the original nodes located on the boundaries of the abnormal regions, completing the replacement and reconnection of the structure. The next step is to recalculate the topological connection weight values ​​of all newly created edges by calling the formula initially used to calculate the edge weights. and the three-dimensional coordinates of the two endpoints of the new edge Substitute the values ​​into the formula to calculate the weight of each new edge. Finally, since new nodes and edges have been introduced, the attributes of the boundary nodes connected to these new structures also need to be updated. The "sum of in-degree strength" and "sum of out-degree strength" and other related attributes of these boundary nodes are recalculated. After all weight calculations and attribute updates are completed, the data consistency of the entire graph structure is restored, and the resulting version is the final digital jacquard pattern set.

Claims

1. A digital design system for the texture of ribbed jacquard fabric, characterized in that, The system includes: The jacquard diagram structure conversion module is used to obtain the coordinate parameters of the coil nodes and the connection direction parameters of the adjacent coil nodes in the design diagram, establish a jacquard directed graph set, extract the surface identification parameters of the coil nodes, assign cross-layer weight values ​​to the directed edge parameters according to the difference of the surface identification parameters, and fuse the cross-layer weight values ​​with the jacquard directed graph set to generate a weighted graph data set. The floating line span detection module is used to extract the feature vectors of continuous edges with the same attribute in the weighted graph dataset, generate the cumulative value of the same path, compare the cumulative value of the same path with the built-in span warning threshold, and establish the local tension deviation. Combined with the fastness verification module, it is used to retrieve the jacquard matrix color change status items within the local tension deviation distribution area, mark the positions where color change status items are generated as color change connection points, mark the positions where color change status items are not generated as non-interlaced suspension points, calculate and generate a pixel spacing matrix set, extract the maximum peak parameter within the pixel spacing matrix set, fuse the maximum peak parameter with the built-in knitting machine needle pitch parameter, and establish a peeling bubbling risk value. The constraint node reconstruction module is used to compare the peeling bubble risk value with the separation threshold parameter, establish a node reconstruction distribution set, and use the node reconstruction distribution set to replace the original connection pointing attribute items of the corresponding area of ​​the weighted graph data set to generate a digital jacquard pattern set.

2. The digital design system for rib jacquard fabric texture according to claim 1, characterized in that, The steps for obtaining the weighted graph dataset are as follows: Obtain the coordinate parameters of the coil nodes and the connection pointing parameters of adjacent coil nodes in the design graph. Convert the coordinate parameters of the coil nodes into graph vertex parameters and the connection pointing parameters of adjacent coil nodes into directed edge parameters. Establish the topological mapping relationship between the graph vertex parameters and the directed edge parameters to generate a jacquard directed graph set. Based on the jacquard directed graph, extract the depth scalar and planar coordinate components of the graph vertex parameters corresponding to the coil nodes, and calculate the cross-layer weight values ​​corresponding to the directed edge parameters. Assign cross-layer weight values ​​to the corresponding directed edge parameters within the jacquard directed graph set, parse the cross-layer weight values ​​and the topological structure of the jacquard directed graph set, perform accumulation operations on the same origin directed edge paths, update the association attributes of the global graph vertex parameters, and generate a weighted graph data set.

3. The digital design system for rib jacquard fabric texture according to claim 1, characterized in that, The steps for obtaining the cumulative value of the same-direction path are as follows: The network topology of the weighted graph dataset is analyzed, the feature vectors of consecutive edges with the same attribute are extracted from the weighted graph dataset, the path is traversed along the corresponding positions of the feature vectors of consecutive edges with the same attribute, and the edge length values ​​on the path are accumulated item by item to generate the cumulative value of the same path.

4. The rib jacquard fabric texture digital design system according to claim 1, characterized in that, The steps for obtaining the local tension deviation are as follows: A built-in span warning threshold is set. If the cumulative value of the same-direction path is greater than the built-in span warning threshold, the coil node position coordinates corresponding to the built-in span warning threshold are filtered. Based on the coil node position coordinates, a topological space search is performed to extract the cross surface layer distribution density parameters. The cross-surface layer distribution density parameters are arranged into a diagonal density matrix. The network adjacency matrix contained in the weighted graph dataset is extracted. Matrix multiplication is performed based on the diagonal density matrix and the network adjacency matrix. The product value vector of the operation output is extracted to establish the local tension deviation.

5. The digital design system for rib jacquard fabric texture according to claim 1, characterized in that, The steps for obtaining the pixel spacing matrix set are as follows: Retrieve the jacquard matrix color-changing state items within the local tension deviation distribution area, compare the color change characteristics of the internal spectrum of the jacquard matrix color-changing state items, mark the positions where color-changing state items are generated as color-changing connection points, and mark the positions where color-changing state items are not generated as non-interlaced suspension points. Extract the planar grid coordinates of the color-changing connection points and the non-interlaced suspended points, measure the straight-line pixel spacing between each non-interlaced suspended point and the adjacent color-changing connection point, and arrange the straight-line pixel spacing values ​​to generate a pixel spacing matrix set.

6. The digital design system for rib jacquard fabric texture according to claim 1, characterized in that, The steps for obtaining the node reconstruction distribution set are as follows: Extract the separation threshold parameter, compare the peeling bubbling risk value with the separation threshold parameter, filter the abnormal grid regions corresponding to the peeling bubbling risk value being greater than or equal to the separation threshold parameter, locate the planar boundary vertices inside the abnormal grid regions, and delineate the spatial coordinates of the planar boundary vertices as the reconstruction coordinates.

7. The digital design system for rib jacquard fabric texture according to claim 6, characterized in that, The steps for obtaining the node reconstruction distribution set also include: Alternating positive and negative constraint nodes are inserted into the closed spatial region defined by the reconstructed coordinates. The planar grid coordinate system position of the alternating positive and negative constraint nodes is read. The spatial straight-line spacing between each alternating positive and negative constraint node and its neighboring nodes is measured. The spatial straight-line spacing is converted into a connection distance vector with directional attributes. All connection distance vector data are integrated to establish a node reconstruction distribution set.

8. The digital design system for rib jacquard fabric texture according to claim 1, characterized in that, The steps for obtaining the digital jacquard pattern set are as follows: Retrieve the reserved weighted graph data set, perform topological addressing within the weighted graph data set based on the reconstructed coordinates, locate the corresponding area within the weighted graph data set that needs to be repaired, use the node reconstruction distribution set to forcibly replace the original connection pointing attribute items of the corresponding area in the weighted graph data set, recalculate the topological connection weight values ​​around the replacement node, update the underlying correlation between various attribute items, and generate a digital jacquard pattern set.

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