Automobile carpet high-definition digital printing frame undercoat and automatic guide and control system and method

Abstract

This invention discloses an automatic cutting system and method for high-definition digital printing of border and background patterns for automotive carpets, belonging to the field of intelligent manufacturing of automotive interior parts. The system includes: a printing processing module that generates a layout drawing containing closed graphics; a border and background pattern intelligent addition module that dynamically determines the border width based on the area and dimensions of the closed graphics, and automatically positions the pattern based on the geometric features of the internal blank areas, with the border width inversely proportional to the pattern size; a digital printing module that prints the border and pattern; an image recognition and cutting module that identifies and cuts the border trajectory; and a feedback control module that compares the actual cutting trajectory with a standard trajectory, generating correction parameters when the deviation exceeds a threshold and feeding them back to the border and background pattern intelligent addition module to adjust subsequent rules. This invention eliminates accumulated errors and improves product consistency and production efficiency through a closed-loop feedback and linkage mechanism.

Description

Technical Field

[0001] This invention relates to the field of intelligent manufacturing technology for automotive interior parts, specifically to a high-definition digital printing border and background pattern and automatic cutting system and method for automotive carpets. Background Technology

[0002] With the booming development of the automotive industry, the demand for personalized automotive interiors, especially car carpets (including floor mats, seat cushions, etc.), is increasing. Traditional car carpet production typically uses a full-coverage, fixed-pattern printing method, followed by manual or semi-automatic cutting. In recent years, with the development of digital printing and automatic cutting technologies, some companies have begun to combine the two in car carpet production.

[0003] In existing technologies, such as those described in US11205023B2, US20250306811A1, CN112507405A, and CN105882129A, technical solutions involving dynamic pattern adjustment, automatic positioning, and image recognition cropping are disclosed. However, these existing technologies generally suffer from the following drawbacks: The processes are independent of each other and lack an effective linkage and feedback mechanism: there is no data interaction between the border width setting in the printing stage and the trajectory recognition in the cutting stage. Deviations found during the cutting process cannot be fed back to the printing stage for correction, resulting in the same cutting deviations appearing repeatedly in subsequent products in the same batch, causing material waste and efficiency loss.

[0004] The border and logo are set independently, lacking visual harmony: The positioning rules of the trademark logo and the border width are independent of each other, which may cause the logo to become disproportionate or shifted in position when the border width is adjusted, affecting the product's aesthetics.

[0005] Unable to adaptively optimize: The existing system cannot record and utilize historical production data. When the same product is produced again, the parameters still need to be reset, which limits production efficiency.

[0006] Therefore, how to achieve a data closed loop between the printing and cutting processes of automotive carpets, as well as the geometric linkage between the border width and the logo positioning, thereby eliminating the cumulative errors caused by independent processes and improving product consistency and production efficiency, has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0007] The present invention aims to solve the above-mentioned problems existing in the prior art, and provides a high-definition digital printing border and background pattern and automatic cutting system and method for automotive carpets. By establishing a closed-loop feedback mechanism between printing and cutting, and a linkage rule between border width and logo size, the invention achieves intelligent, high-precision and high-efficiency production of automotive carpets.

[0008] Therefore, in a first aspect, the present invention provides a high-definition digital printing border and background pattern and automatic cutting system for automotive carpets, comprising: The printing processing module is configured to generate a layout drawing containing at least one closed graphic based on the vehicle model specifications or preset pattern of the car carpet. The border and background pattern intelligent addition module is configured to read the layout diagram and, for each closed shape, dynamically determine and add the width of the border and background pattern based on the area and length and width of the closed shape. At the same time, it automatically locates and adds patterns based on the geometric characteristics of the blank area inside the closed shape. The digital printing module is configured to print the border pattern and design on the automotive carpet substrate based on the processing result of the intelligent border pattern addition module. The image recognition and cropping module is configured to acquire the printed border and background image through a high-speed imaging device, identify the feature trajectory of the border and background, and control the automatic cropping device to crop along the outer or inner edge of the border and background based on the recognition result. The feedback control module is configured to acquire the actual border trajectory data identified by the image recognition and cropping module during the cropping process, compare the actual border trajectory data with the preset standard border trajectory data, and generate correction parameters when the deviation value exceeds the preset threshold and feed them back to the border texture intelligent addition module. The intelligent border and background pattern addition module is further configured to, upon receiving the correction parameters, dynamically adjust the width setting rules and / or the pattern positioning rules of the border and background patterns for subsequent closed graphics to be printed, based on the correction parameters.

[0009] By adopting the above technical solution, this solution constructs a complete closed-loop control system from printing to cutting by setting up a printing processing module, a border and background intelligent addition module, a digital printing module, an image recognition and cutting module, and a feedback control module. The principle is that the border and background generated in the printing stage not only serve as decorative elements but also as positioning references for subsequent cutting; in the cutting stage, high-speed imaging identifies the actual border trajectory and feeds back the deviation data to the printing stage in real time, forming a closed-loop control link of printing-recognition-feedback-correction. The beneficial effects of this technical solution are: it breaks down the process barriers between in-line printing and subsequent cutting in traditional production, realizes cross-process data interaction and collaborative optimization, effectively eliminates cumulative deviations caused by material deformation, equipment errors, and other factors, improves product consistency and yield, while reducing manual intervention and enhancing the intelligence level of the production line.

[0010] Preferably, in the intelligent border and background texture addition module, there is a linkage between the dynamic determination of the border and background texture width and the positioning of the pattern: The positioning reference point of the pattern is determined by the center of the largest inscribed circle of the blank area enclosed by the inner edge contour of the border pattern. The scaling of the pattern is dynamically adjusted according to the width of the border and background texture. Specifically, when the width of the border and background texture increases, the size of the pattern decreases by a preset proportional coefficient; when the width of the border and background texture decreases, the size of the pattern increases by a preset proportional coefficient.

[0011] By adopting the above technical solution, this solution establishes an inverse proportional linkage mechanism between the width of the border and the pattern size. The principle is as follows: using the center of the largest inscribed circle of the blank area enclosed by the inner edge of the border as the pattern positioning reference point, ensuring the pattern is always located at the visual center of the carpet body; simultaneously, the pattern size is dynamically adjusted in reverse according to the border width: the wider the border, the smaller the pattern; the narrower the border, the larger the pattern. This linkage design is based on the principle of visual aesthetics: wide borders inherently have strong decorative qualities, so the pattern should be more compact to avoid crowding; narrow borders have weaker decorative qualities, so the pattern should be enlarged to form a visual focal point. The beneficial effects of this technical solution are: it achieves coordinated optimization of the geometric parameters of the border and the pattern. Regardless of changes in carpet size, the pattern always maintains proportional harmony and centered position with the carpet body, avoiding pattern offset and proportional imbalance caused by independent parameter settings. This significantly improves product aesthetics and brand recognition, and eliminates the need for subsequent hot stamping, saving production costs.

[0012] Preferably, the feedback control module is further configured as follows: The actual border trajectory data is compared with the preset standard border trajectory data to perform deviation analysis and generate a deviation distribution map. When the deviation value exceeds the preset threshold, the feedback control module determines whether the source of the deviation is material deformation or printing error during the printing process, and generates different correction parameters based on the determination result, which are used to adjust the setting rules of the border and background width or the positioning rules of the pattern.

[0013] By adopting the above technical solution, this solution introduces an intelligent discrimination and classification correction mechanism for deviation sources into the feedback control module. The principle is as follows: by statistically analyzing the deviation distribution between the actual cutting trajectory and the standard trajectory (such as consistency verification of deviation direction and dispersion calculation of deviation amplitude), the system can automatically identify systematic sources of deviation (such as printing positioning offset and equipment calibration error) and random sources (such as local material deformation and tension fluctuation). For different types of deviations, the system generates differentiated correction parameters: systematic deviations adjust positioning rules (such as overall offset compensation), and random deviations adjust border width tolerance rules (such as appropriately widening the inner edge range of the border). The beneficial effects of this technical solution are: it achieves precise matching between the correction strategy and the causes of deviations, avoids new deviations or over-correction caused by one-size-fits-all corrections, improves the accuracy and effectiveness of feedback correction, reduces material waste caused by improper correction, and further improves product yield.

[0014] Preferably, the image recognition and cropping module acquires the image of the cropped carpet in real time during the cropping process and feeds back the image data of the cropped edges to the feedback control module; The feedback control module is further configured to identify the cropping accuracy based on the image data of the cropping edge, and when the cropping accuracy is lower than a preset standard, generate a cropping parameter correction instruction and send it to the image recognition cropping module to adjust the trajectory tracking sensitivity or cropping speed of subsequent cropping.

[0015] By adopting the above technical solution, this solution further establishes an adaptive optimization mechanism for cutting parameters based on the closed-loop feedback of printing and cutting. The principle is as follows: the image recognition cutting module, while performing cutting, also acts as a cutting quality detection unit. It acquires real-time images of the cutting edges through high-speed imaging, and the feedback control module uses image processing algorithms (such as edge detection and contour analysis) to identify accuracy indicators such as the smoothness, jaggedness, and offset of the cutting edges. When a decrease in cutting quality is detected, the system dynamically adjusts the trajectory tracking sensitivity (e.g., reducing sensitivity to reduce jitter) or the cutting speed (e.g., increasing speed to improve efficiency), achieving real-time optimization of cutting parameters. The beneficial effects of this technical solution are: it achieves bidirectional collaborative optimization of printing and cutting parameters, forming a complete intelligent manufacturing closed loop, maximizing production efficiency while ensuring cutting accuracy, reducing labor costs for equipment debugging, and improving the automation level of the production line.

[0016] Preferably, the feedback control module is further configured as follows: Record the correction parameters generated each time to form a historical correction database; When car carpets of the same model and specifications are produced again, the intelligent border and background pattern addition module automatically calls the optimal parameters from the historical correction database as the initial settings.

[0017] By adopting the above technical solution, this solution introduces an adaptive learning mechanism based on historical data. The principle is that the feedback control module associates and stores the correction parameters generated during each production process (including positioning offset compensation, border width adjustment, and cutting parameter adjustment) with corresponding metadata such as vehicle model specifications, material batches, and production dates, forming a structured historical correction database. When the same specification product is produced again, the system automatically retrieves and matches the parameter combination from the historical database that achieves the highest cutting accuracy and optimal production efficiency as the initial settings for this production. The beneficial effects of this technical solution are: it transforms the optimization results of a single production run into reusable knowledge assets. As production batches increase, the system's initial parameters continuously approach the optimal solution, achieving continuous learning and self-optimization of the production process. This significantly shortens production preparation time, improves the efficiency and consistency of batch production, reduces reliance on manual experience, and enhances the intelligence level of the production line.

[0018] In a second aspect, the present invention provides a method for high-definition digital printing of border and background patterns for automotive carpets and an automatic cutting method, comprising the following steps: Step S1: Generate a layout diagram containing at least one closed graphic based on the car carpet's model specifications or preset pattern. Step S2: Read the layout diagram, and for each closed graphic, dynamically determine the width of the border and background pattern according to its area and length and width, and automatically position the pattern according to the geometric characteristics of its internal blank area; wherein, the positioning reference point of the pattern is determined by the center of the largest inscribed circle of the blank area enclosed by the inner edge contour of the border and background pattern, and the scaling size of the pattern is inversely proportional to the width of the border and background pattern. Step S3: Based on the determination result of step S2, print the border pattern and design on the automotive carpet substrate; Step S4: Acquire the printed border background image using a high-speed imaging device, identify the feature trajectory of the border background, and control the automatic cutting device to cut along the outer or inner edge of the border background based on the identification result; Step S5: During the cropping process, the actual border trajectory data is obtained and compared with the preset standard border trajectory data. When the deviation value exceeds the preset threshold, correction parameters are generated. Step S6: Feed back the correction parameters to step S2, and dynamically adjust the setting rules for the width of the border and background and / or the positioning rules for the pattern for the closed graphic to be printed subsequently.

[0019] By adopting the above technical solution, this solution systematically and standardizes the closed-loop feedback control process of printing and cutting through a systematic methodology. Its principle lies in forming a complete closed-loop method from layout generation (S1), intelligent addition of borders and patterns (S2), digital printing (S3), image recognition and cutting (S4), deviation comparison and correction parameter generation (S5), and parameter feedback and rule adjustment (S6). The core of this method lies in the inverse linkage between pattern positioning and border width in step S2, and the cross-step feedback of deviation data in steps S5-S6. The beneficial effects of this technical solution are: it transforms the collaborative mechanism of the hardware system into an executable method flow, providing a clear logical framework for computer program implementation; and it further clarifies the system's operating mechanism through the limitation of method steps, enhancing the completeness and feasibility of the technical solution.

[0020] Preferably, in step S2, dynamically determining the width of the border background pattern further includes: If the area S of the closed shape is greater than the first preset area threshold S1, or the length L of the long side is greater than the first preset length threshold L1, then the width of the border background is set to the first width value W1. If the area S of the closed shape is less than the second preset area threshold S2, or the length L of the long side is less than the second preset length threshold L2, then the width of the border background is set to the second width value W2. Where W1>W2, S1≥S2, L1≥L2.

[0021] By adopting the above technical solution, this solution achieves graded dynamic setting of the border width through a dual-parameter threshold judgment of area and long side length. The principle is that different parts of automotive carpets have significant size differences, and a single border width cannot accommodate all sizes. This solution introduces two geometric parameters: area S and long side length L, setting a first threshold (large) and a second threshold (small) respectively, and using "OR" logic for judgment: if either parameter meets the large condition, a wide border W1 is used; if either parameter meets the small condition, a narrow border W2 is used. This dual-parameter "OR" logic design takes into account the geometric characteristics of irregularly shaped carpets (such as long strip carpets with small area but long long sides, which need to be treated as large), avoiding the limitations of single-parameter judgment. The beneficial effect of this technical solution is that it makes the border width and the main size of the carpet form a reasonable proportion, avoiding the problem of a small carpet having an excessively wide border leading to a small main area, or a large carpet having an excessively narrow border leading to visual imbalance, achieving automatic adaptation and visual harmony in border design.

[0022] Preferably, in step S5, generating the correction parameters further includes: The actual border trajectory data is compared with the preset standard border trajectory data to perform deviation analysis and generate a deviation distribution map. Determine whether the deviation originates from material deformation or printing error during the printing process, and generate different correction parameters based on the determination results. These parameters are used to adjust the setting rules for the border and background width or the positioning rules for the pattern.

[0023] By adopting the above technical solution, this approach further refines the steps for identifying and classifying deviation sources at the methodological level. The principle is as follows: by generating a deviation distribution map, the system can visually analyze the central tendency and dispersion of deviations. If the deviation distribution shows high consistency (e.g., all closed shapes shift in the same direction with similar shift amounts), it is determined to be a systematic positioning error, and correction parameters are applied to the positioning rules. If the deviation distribution shows randomness (e.g., the shift direction and magnitude are irregular), it is determined to be material deformation or random printing error, and correction parameters are applied to the border width tolerance rules. The beneficial effects of this technical solution are: it achieves precise matching between the correction strategy and the causes of deviations, avoids new problems caused by one-size-fits-all corrections, improves the reliability of feedback corrections and production stability, and provides operators with a visual basis for deviation analysis, facilitating the tracing of the root cause of problems.

[0024] Preferably, step S7 is also included: Record the correction parameters generated each time to form a historical correction database; When car carpets of the same model and specifications are produced again, the optimal parameters in the historical correction database are automatically called as the initial settings for step S2.

[0025] By adopting the above technical solution, this approach adds steps for historical data reuse and parameter presetting at the methodological level, enabling continuous accumulation and intelligent application of production experience. The principle is to associate and store the correction parameters for each production run with metadata such as vehicle model specifications, material batches, and production dates, forming a structured historical correction database. When products of the same specifications are produced again, the system automatically retrieves the parameter combination from the historical database that achieves the highest cutting accuracy and optimal production efficiency as the initial settings for this production run. The beneficial effects of this technical solution are: it transforms the optimization results of a single production run into reusable knowledge assets. As production batches increase, the system's initial parameters continuously approach the optimal solution, achieving continuous learning and self-optimization of the production process, significantly improving the intelligence level and batch consistency of the production line, while reducing manual debugging costs.

[0026] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0027] Compared with the prior art, the present invention has the following beneficial effects: Establish a closed-loop feedback mechanism for printing and cutting: The feedback control module feeds back the deviation data identified during the cutting process to the printing stage in real time, dynamically correcting the border and logo parameters of subsequent products. This effectively eliminates the cumulative deviations caused by material deformation, printing errors, and other reasons, improving product consistency and yield.

[0028] Border and logo linkage design: Establish an inverse linkage between border width and logo size to ensure that the logo always maintains a suitable visual proportion under different border widths, which improves the product's aesthetics and brand recognition, while avoiding the need for subsequent hot stamping process and saving production costs.

[0029] Adaptive optimization capability: The system records historical correction parameters and forms a database. When the same product specifications are produced again, the optimal parameters can be automatically called, shortening the production preparation time and improving production efficiency.

[0030] Multi-level precision control: The feedback control module not only corrects the printing parameters, but also adjusts the cutting parameters (such as trajectory tracking sensitivity and cutting speed) based on the cutting edge image data, forming a two-way collaborative optimization between printing and cutting. Attached Figure Description

[0031] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0032] Figure 1 This is a schematic diagram of the structure of the high-definition digital printing border and background pattern and automatic cutting system for automotive carpets in an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the intelligent addition of borders and logo patterns to the layout diagram in an embodiment of the present invention; Figure 3 This is a flowchart illustrating the workflow of the feedback control module in an embodiment of the present invention.

[0033] The markings in the attached diagram are as follows: In the diagram: 1. Blanket storage rack before roll-up; 2. Digital printing unit; 3. Border layout width and LOGO positioning processing unit; 4. Steam oven color fixing unit; 5. Drying oven unit; 6. Border recognition automatic cutting unit; 7. Feedback control unit. Detailed Implementation

[0034] 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 specific embodiments. Those skilled in the art should understand that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0035] Example 1: Overall System Structure like Figure 1As shown in the figure, the high-definition digital printing border and background pattern and automatic cutting system for automotive carpets provided in this embodiment includes the following components in sequence along the production process: Carpet rack 1 before unwinding: Used to hold the car carpet roll to be printed. It is fixed with an air shaft to ensure that the carpet substrate is unwound smoothly.

[0036] Digital printing unit 2: Connected to the host computer control system, it adopts an industrial-grade piezoelectric printhead, supports simultaneous printing of multiple colors of ink, and is used to execute printing instructions.

[0037] Border layout width and LOGO positioning processing unit 3: As the core control unit, it includes a printing processing module and a border background intelligent addition module, which are used to generate layout diagrams and intelligently calculate border width and LOGO position.

[0038] Steam curing unit 4: Used to perform high-temperature steam curing treatment on the printed carpet, so that the ink can fully bond with the carpet fibers.

[0039] Oven drying unit 5: Used to dry the carpet after color fixing, remove excess moisture, and ensure the carpet is flat.

[0040] Border Recognition Automatic Cropping Unit 6: As an image recognition and cropping module, it includes a high-speed industrial camera, an image processing unit, and a control unit, used to recognize border trajectories and perform precise cropping.

[0041] Feedback control unit 7: It is connected to the border layout width and LOGO positioning processing unit 3 and the border recognition automatic cropping unit 6 respectively, and is used to receive cropping trajectory data and provide feedback correction parameters.

[0042] The above-mentioned units communicate with each other via industrial Ethernet or fieldbus, forming a complete automated production line from printing to cutting.

[0043] Example 2: Mechanism linking border width and pattern size: like Figure 2 As shown in the figure, this embodiment describes in detail the linkage rules between the border width and the pattern (such as trademark LOGO) size in the border and background texture intelligent addition module (i.e., border layout width and LOGO positioning processing unit 3).

[0044] The system first reads the layout diagram and identifies each closed shape (corresponding to a single car carpet, such as the driver's side floor mat, passenger side floor mat, rear integrated mat, etc.). For each closed shape, the system performs the following operations: 1. Determining the dynamic border width: The system calculates the area S and the length L of the longer side of a closed figure using a two-parameter threshold method. If S > the first preset area threshold S1 (e.g., 0.5 square meters) or L > the first preset length threshold L1 (e.g., 800 mm), it is determined to be a large carpet (e.g., a rear row integrated mat), and the border width is set to the first width value W1 (e.g., 60 mm).

[0045] If S < the second preset area threshold S2 (e.g., 0.15 square meters) or L < the second preset length threshold L2 (e.g., 400 mm), it is determined to be a small carpet (e.g., driver's side floor mat), and the border width is set to the second width value W2 (e.g., 25 mm).

[0046] If S is between S2 and S1 and L is between L2 and L1, it is determined to be a medium-sized carpet (such as a passenger side floor mat), and the border width is set to the default width value W0 (e.g., 40mm).

[0047] Among the thresholds mentioned above, W1 > W0 > W2, S1 ≥ S2, and L1 ≥ L2. This "OR" logic takes into account the geometric characteristics of irregularly shaped carpets—for example, long strip carpets, although smaller in area, have longer sides and need to be treated as large carpets, thus avoiding the limitations of judging by a single parameter.

[0048] 2. Automatic pattern positioning and size linkage: The system further performs pattern positioning and size linkage on each closed shape: Positioning reference point determination: Extract the blank area enclosed by the inner edge contour of the border (i.e., the main area of ​​the carpet), calculate the largest inscribed circle of this blank area, and use the center of this inscribed circle as the placement reference point for the pattern. This positioning method ensures that the pattern is always located in the visual center of the carpet body, unaffected by changes in the border width.

[0049] Size linkage rule: The scaling of the pattern is inversely proportional to the border width. Specifically, when the baseline border width W0 = 40mm, the pattern scaling factor k0 = 0.5 (i.e., the pattern diameter is 0.5 times the diameter of the largest inscribed circle). When the border width is W1 = 60mm, the pattern scaling factor is adjusted to k1 = 0.4; when the border width is W2 = 25mm, the pattern scaling factor is adjusted to k2 = 0.7. This inverse linkage relationship can be expressed as: k = α - β·W, where α and β are preset coefficients, or can be expressed as a piecewise function.

[0050] 3. The principle and effect of the linkage mechanism: This linkage mechanism is designed based on visual aesthetics principles: wide borders inherently possess strong decorative qualities, so the pattern should be restrained to avoid overcrowding; narrow borders have weaker decorative qualities, so the pattern should be enlarged to create a visual focal point. By establishing an inverse linkage between border width and pattern size, the pattern always maintains a harmonious proportion and centered position with the main body of the carpet, regardless of changes in carpet size. This mechanism avoids pattern shifts and proportional imbalances caused by independently set parameters, significantly improving product aesthetics and brand recognition, and eliminating the need for subsequent high-frequency hot stamping processes, thus saving production costs.

[0051] Example 3: Deviation identification and classification correction of the feedback control module: like Figure 3 As shown, this embodiment describes in detail the workflow of the feedback control module (i.e., the feedback control unit 7).

[0052] 1. Data Acquisition: During the cutting process, the image recognition cutting module (border recognition automatic cutting unit 6) records the coordinate data of the actual cutting trajectory in real time. Specifically, the system uses a high-speed industrial camera (sampling frequency ≥30fps) to acquire images of the printed carpet, extracts the feature trajectory of the border pattern through an edge detection algorithm (such as the Canny operator), and generates actual border trajectory data, including the start point, end point, and path point set of each edge of each closed shape.

[0053] 2. Deviation Comparison: The feedback control unit 7 acquires the actual border trajectory data and compares it point-by-point with the preset standard border trajectory data. The preset standard border trajectory data is derived from the theoretical boundary of the closed shape in the layout drawing. The system calculates the deviation value of each sampling point, including the deviation direction (X-direction offset, Y-direction offset) and the deviation magnitude.

[0054] 3. Intelligent identification of deviation sources: When the average deviation of a closed shape exceeds a preset threshold (e.g., 2mm), the system triggers a correction process. The feedback control unit 7 further analyzes the deviation distribution: Deviation analysis is performed between the actual border trajectory data and the standard trajectory data to generate a deviation distribution map. The deviation distribution map graphically displays the direction and magnitude of the deviation at each sampling point, facilitating system analysis and manual review.

[0055] Consistency index for calculating deviations: If the deviation directions of all closed graphics are highly consistent (e.g., all are offset by 2±0.5mm in the positive X-axis direction), it is determined to be a systematic positioning error in the printing process (such as offset of the printing start point, material deviation, etc.).

[0056] If the deviation direction is randomly distributed (e.g., partly to the left, partly to the right, or the deviation amplitude varies greatly), it is determined to be material deformation during the printing process or random printing error (e.g., local stretching of carpet substrate, uneven ink diffusion, etc.).

[0057] 4. Generation of classification correction parameters: Based on the determination of the source of the deviation, the feedback control unit 7 generates different correction parameters: Systematic Deviation: A "positioning offset compensation parameter" is generated and sent to the border layout width and LOGO positioning processing unit 3 to perform overall offset compensation on the position of the border background texture of the subsequent closed graphic. For example, if the actual cutting trajectory is detected to be offset 2mm to the right, a compensation parameter of offset 2mm to the left is generated.

[0058] Random deviation: Generate "border width tolerance adjustment parameters" to appropriately widen the setting range of border shading width to accommodate material deformation. For example, increase the set value of border width by 1-2mm as a tolerance margin, or adjust the fault tolerance threshold of the border recognition algorithm.

[0059] 5. Technical effects: This mechanism achieves a precise match between correction strategies and the causes of deviations, avoiding new deviations or over-correction caused by a one-size-fits-all approach, and improving the accuracy and effectiveness of feedback corrections. Simultaneously, the generation of deviation distribution charts provides operators with a visual basis for deviation analysis, facilitating the tracing of the root cause of problems.

[0060] Example 4: Adaptive optimization of trimming parameters: This embodiment describes a two-way collaborative optimization mechanism between the image recognition and cropping module and the feedback control module.

[0061] 1. Real-time detection of cutting quality: During the cutting process, the image recognition and cropping module, in addition to recording the cutting trajectory data, also acquires real-time images of the cut carpet using a high-speed imaging device and feeds back the image data of the cut edges to the feedback control module. The image acquisition frequency is linked to the cutting speed to ensure that each cut edge has corresponding image data.

[0062] 2. Cutting accuracy recognition: The feedback control module uses image processing algorithms to identify cropping accuracy indicators based on the image data of the cropping edges. Smoothness: Calculates the rate of change of curvature of the trimmed edge curve. Excessive curvature change indicates the presence of jagged edges.

[0063] Offset: Detects the deviation between the cropped edge and the preset border trajectory.

[0064] Completeness: Detects for any abnormalities such as missing cuts or incomplete cutting.

[0065] When any accuracy indicator is lower than the preset standard (such as smoothness threshold or offset threshold), the system determines that the cutting quality is substandard.

[0066] 3. Dynamic adjustment of cutting parameters: Based on the cropping accuracy recognition result, the feedback control module generates a cropping parameter correction instruction and sends it to the image recognition and cropping module: When a jagged edge is detected (smoothness exceeds the standard), the system determines that the trajectory tracking sensitivity is too high, causing jitter, and then reduces the tracking sensitivity parameter.

[0067] When it is detected that the cutting speed is too slow and affecting production efficiency, the cutting speed should be appropriately increased (e.g., the step size should be increased by 5-10%) while ensuring accuracy.

[0068] When the system detects that the offset exceeds the limit, it adjusts the offset compensation value of the cutting trajectory.

[0069] 4. Technical effects: This mechanism achieves bidirectional collaborative optimization of printing and cutting parameters—the border design in the printing stage provides a benchmark for cutting, while the quality feedback in the cutting stage is used to optimize both the printing and cutting parameters themselves. This bidirectional collaboration forms a complete intelligent manufacturing closed loop, maximizing production efficiency while ensuring cutting accuracy, and reducing the labor costs of equipment debugging.

[0070] Example 5: Adaptive learning from historical data: This embodiment describes the system's adaptive learning and knowledge reuse mechanism.

[0071] 1. Historical correction parameter records: The feedback control module records the correction parameters generated during each production process, including: Positioning offset compensation values ​​(X-direction offset, Y-direction offset); Border width adjustment value (tolerance margin, threshold adjustment); Cutting parameter adjustment values ​​(tracking sensitivity, cutting speed); Metadata such as vehicle specifications, material batch, and production date.

[0072] The above data is stored together to form a structured historical correction database. The database uses SQL or time-series database technology to support efficient retrieval and statistical analysis.

[0073] 2. Optimal parameter retrieval and retrieval: When car carpets of the same model and specifications are produced again, the edge pattern intelligent addition module automatically performs the following operations: Based on the current vehicle model specifications, the historical correction database is searched to filter out historical production records of the same specifications and material batches.

[0074] Perform statistical analysis on the selected records to calculate the average, median, or optimal value of each correction parameter (such as the parameter combination with the highest cutting accuracy).

[0075] The system automatically uses the optimal parameters obtained from the analysis as the initial settings for this production run, without requiring manual intervention.

[0076] 3. Continuous optimization mechanism: As production batches increase, the historical correction database continues to accumulate. The system can use machine learning algorithms (such as linear regression, random forest, etc.) to model historical data and predict the optimal initial parameters under different operating conditions, thus upgrading from "experience reuse" to "predictive optimization".

[0077] 4. Technical effects: This mechanism transforms the optimization results of a single production run into reusable knowledge assets. As production batches increase, the initial system parameters continuously approach the optimal solution, enabling continuous learning and self-optimization of the production process. This significantly shortens production preparation time (estimated to be reduced by more than 30%), improves the efficiency and consistency of batch production, reduces reliance on manual experience, and enhances the intelligence level of the production line.

[0078] Example 6: Complete Production Process Example The complete workflow of this invention will be described below in conjunction with a specific production scenario.

[0079] Scenario: A car carpet manufacturer receives an order to produce a complete set of car carpets for a certain brand of SUV, including driver's side floor mats, passenger side floor mats, and rear seat integrated mats, 100 pieces of each size. The carpets need to include the brand logo and specific border patterns.

[0080] Step 1: Layout diagram generation (S1): The operator inputs the vehicle model specifications into the printing processing module, and the system automatically retrieves the carpet outline library for the corresponding vehicle model to generate a layout diagram containing three closed shapes (driver's seat, passenger seat, and rear integrated seat), with each closed shape labeled with its corresponding size parameters.

[0081] Step 2: Smart addition of borders and patterns (S2): The intelligent border and background addition module reads the layout image and performs the following operations on each closed shape: Driver's side floor mat: Area 0.2 square meters, long side 500mm, classified as medium size, border width set at 40mm; maximum inscribed circle diameter 300mm, LOGO scaling factor 0.5, LOGO diameter 150mm.

[0082] Passenger side floor mat: Area 0.18 square meters, long side 480mm, classified as medium size, border width set at 40mm; LOGO diameter 140mm.

[0083] Rear row integrated mat: area 0.6 square meters, long side 900mm, judged as large, frame width set to 60mm; maximum inscribed circle diameter 400mm, LOGO scaling factor 0.4, LOGO diameter 160mm.

[0084] Step 3: Digital printing (S3): Based on the processing results, the digital printing module sequentially prints the border patterns and logo of three closed shapes onto the carpet substrate. During the printing process, the system controls the ink jet volume and leaves blank areas between adjacent closed shapes, saving approximately 15% of ink.

[0085] Step 4: Post-processing: The printed carpets are then passed through a steam oven for color fixing (102℃, 8 minutes) and an oven for drying (120℃, 5 minutes) to ensure that the ink is firmly fixed and the carpet is flat.

[0086] Step 5: Image recognition and cropping (S4): After drying, the carpet enters the edge recognition automatic cutting unit. A high-speed industrial camera (5 megapixels resolution, 60fps frame rate) continuously acquires images of the carpet, and the image processing unit extracts the edge feature trajectory, controlling the cutter to cut along the outer edge of the edge.

[0087] Step 6: Deviation detection and correction parameter generation (S5): During the cutting process, the feedback control module acquires the actual edge trajectory data. Comparison reveals that the actual cutting trajectory of the rear integrated padding is shifted 2.5mm to the right, exceeding the preset threshold of 2mm. The system generates a deviation distribution map, identifies it as a systematic positioning error, and generates a positioning compensation parameter shifted 2.5mm to the left.

[0088] Step 7: Parameter Feedback and Rule Adjustment (S6): The compensation parameters are fed back to the intelligent border and background texture addition module in real time. For the subsequent 100 printed rear row integrated mats, the system automatically shifts the border printing starting point 2.5mm to the left to eliminate positioning deviation.

[0089] Step 8: Historical Data Recording and Reuse (S7): After production is completed, the system stores the corrected parameters (offset compensation of 2.5mm) for this production run, along with the vehicle model specifications and material batch. When the same vehicle model is produced again, the system automatically calls up these compensation parameters as the initial settings, eliminating the need to re-accumulate deviations.

[0090] Production results statistics: Product yield: 98.5% (an improvement of approximately 5% compared to traditional processes); Production efficiency: Average production time per piece is 45 seconds (25% improvement compared to traditional processes); Number of manual interventions: 0 (fully automated process); Ink savings: approximately 15% (due to white space treatment in the intervening areas); Summary of beneficial effects: In summary, this invention achieves significant beneficial effects through the following technical innovations: Printing-Cutting Closed-Loop Feedback: The feedback control module feeds back the deviation data identified during the cutting process to the printing stage in real time, dynamically correcting the border and pattern parameters of subsequent products, effectively eliminating the cumulative deviation caused by material deformation, printing errors, etc., and improving the product yield by 3%-5%.

[0091] Border and pattern linkage design: Establish an inverse linkage relationship between border width and pattern size to ensure that the pattern always maintains a suitable visual proportion under different border widths, which improves the product's aesthetics and brand recognition, while eliminating the need for subsequent high-frequency hot stamping processes and increasing production efficiency by more than 25%.

[0092] Intelligent identification of deviation sources: Through statistical analysis of deviation distribution, it automatically distinguishes between systematic deviations and random deviations, and generates targeted correction parameters, avoiding new problems caused by one-size-fits-all corrections and improving the accuracy and reliability of feedback corrections.

[0093] Adaptive optimization of cutting parameters: Real-time acquisition of cutting edge images and dynamic adjustment of trajectory tracking sensitivity or cutting speed maximize production efficiency while ensuring cutting accuracy, achieving two-way collaborative optimization of printing and cutting.

[0094] Historical data adaptive learning: Historical correction parameters are recorded to form a database. When the same product specifications are produced again, the optimal parameters are automatically called as the initial settings, realizing the continuous accumulation and intelligent reuse of production experience, shortening production preparation time and improving batch consistency.

[0095] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A high-definition digital printing border and background pattern and automatic cutting system for automotive carpets, characterized in that, include: The printing processing module is configured to generate a layout drawing containing at least one closed graphic based on the vehicle model specifications or preset pattern of the car carpet. The border and background pattern intelligent addition module is configured to read the layout diagram and, for each closed shape, dynamically determine and add the width of the border and background pattern based on the area and length and width of the closed shape. At the same time, it automatically locates and adds patterns based on the geometric characteristics of the blank area inside the closed shape. The digital printing module is configured to print the border pattern and design on the automotive carpet substrate based on the processing result of the intelligent border pattern addition module. The image recognition and cropping module is configured to acquire the printed border and background image through a high-speed imaging device, identify the feature trajectory of the border and background, and control the automatic cropping device to crop along the outer or inner edge of the border and background based on the recognition result. The feedback control module is configured to acquire the actual border trajectory data identified by the image recognition and cropping module during the cropping process, compare the actual border trajectory data with the preset standard border trajectory data, and generate correction parameters when the deviation value exceeds the preset threshold and feed them back to the border texture intelligent addition module. The intelligent border and background pattern addition module is further configured to, upon receiving the correction parameters, dynamically adjust the width setting rules and / or the pattern positioning rules of the border and background patterns for subsequent closed graphics to be printed, based on the correction parameters.

2. The high-definition digital printing border and background pattern and automatic cutting system for automotive carpets according to claim 1, characterized in that, In the intelligent border and background texture addition module, there is a linkage between the dynamic determination of the border and background texture width and the positioning of the pattern: The positioning reference point of the pattern is determined by the center of the largest inscribed circle of the blank area enclosed by the inner edge contour of the border pattern. The scaling of the pattern is dynamically adjusted according to the width of the border and background texture. Specifically, when the width of the border and background texture increases, the size of the pattern decreases by a preset proportional coefficient; when the width of the border and background texture decreases, the size of the pattern increases by a preset proportional coefficient.

3. The high-definition digital printing border and background pattern and automatic cutting system for automotive carpets according to claim 1, characterized in that, The feedback control module is also configured to: The actual border trajectory data is compared with the preset standard border trajectory data to perform deviation analysis and generate a deviation distribution map. When the deviation value exceeds the preset threshold, the feedback control module determines whether the source of the deviation is material deformation or printing error during the printing process, and generates different correction parameters based on the determination result, which are used to adjust the setting rules of the border and background width or the positioning rules of the pattern.

4. The high-definition digital printing border and background pattern and automatic cutting system for automotive carpets according to claim 1, characterized in that, During the cropping process, the image recognition and cropping module acquires images of the cropped carpet in real time and feeds back the image data of the cropped edges to the feedback control module. The feedback control module is further configured to identify the cropping accuracy based on the image data of the cropping edge, and when the cropping accuracy is lower than a preset standard, generate a cropping parameter correction instruction and send it to the image recognition cropping module to adjust the trajectory tracking sensitivity or cropping speed of subsequent cropping.

5. The high-definition digital printing border and background pattern and automatic cutting system for automotive carpets according to claim 1, characterized in that, The feedback control module is also configured to: Record the correction parameters generated each time to form a historical correction database; When car carpets of the same model and specifications are produced again, the intelligent border and background pattern addition module automatically calls the optimal parameters from the historical correction database as the initial settings.

6. A high-definition digital printing border and background pattern for automotive carpets and an automatic cutting method, characterized in that, Includes the following steps: Step S1: Generate a layout diagram containing at least one closed graphic based on the car carpet's model specifications or preset pattern. Step S2: Read the layout diagram, and for each closed graphic, dynamically determine the width of the border and background pattern according to its area and length and width, and automatically position the pattern according to the geometric characteristics of its internal blank area; wherein, the positioning reference point of the pattern is determined by the center of the largest inscribed circle of the blank area enclosed by the inner edge contour of the border and background pattern, and the scaling size of the pattern is inversely proportional to the width of the border and background pattern. Step S3: Based on the determination result of step S2, print the border pattern and design on the automotive carpet substrate; Step S4: Acquire the printed border background image using a high-speed imaging device, identify the feature trajectory of the border background, and control the automatic cutting device to cut along the outer or inner edge of the border background based on the identification result; Step S5: During the cropping process, the actual border trajectory data is obtained and compared with the preset standard border trajectory data. When the deviation value exceeds the preset threshold, correction parameters are generated. Step S6: Feed back the correction parameters to step S2, and dynamically adjust the setting rules for the width of the border and background and / or the positioning rules for the pattern for the closed graphic to be printed subsequently.

7. The method for high-definition digital printing border and background patterns and automatic cutting of automotive carpets according to claim 6, characterized in that, In step S2, dynamically determining the width of the border background pattern further includes: If the area S of the closed shape is greater than the first preset area threshold S1, or the length L of the long side is greater than the first preset length threshold L1, then the width of the border background is set to the first width value W1. If the area S of the closed shape is less than the second preset area threshold S2, or the length L of the long side is less than the second preset length threshold L2, then the width of the border background is set to the second width value W2. Where W1>W2, S1≥S2, L1≥L2.

8. The method for high-definition digital printing border and background patterns and automatic cutting of automotive carpets according to claim 6, characterized in that, In step S5, generating the correction parameters further includes: The actual border trajectory data is compared with the preset standard border trajectory data to perform deviation analysis and generate a deviation distribution map. Determine whether the deviation originates from material deformation or printing error during the printing process, and generate different correction parameters based on the determination results. These parameters are used to adjust the setting rules for the border and background width or the positioning rules for the pattern.

9. The method for high-definition digital printing border and background patterns and automatic cutting of automotive carpets according to claim 6, characterized in that, It also includes step S7: Record the correction parameters generated each time to form a historical correction database; When car carpets of the same model and specifications are produced again, the optimal parameters in the historical correction database are automatically called as the initial settings for step S2.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 6 to 9.

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