Image-text printing sorting route control method and system

Abstract

The invention provides an image-text printing sorting route control method and system, and the method comprises the steps: collecting image-text printing piece surface data through a detection device, processing the data through a recognition algorithm, and obtaining a quantitative index of an anti-mildew treatment effect; comparing the obtained quantitative index with a preset threshold value, and judging whether the image-text printed piece reaches a mildew-proof standard or not so as to obtain a quality state classification; if the quality state classification is standard, obtaining storage route information corresponding to a high standard area from a database, and determining an initial channel sequence; analyzing the initial channel sequence and the current sorting flow data by adopting a path optimization algorithm to obtain dynamically adjusted path channel configuration; matching the dynamically adjusted route channel configuration with the quality state of the image-text printed piece, and judging whether an unlocking condition is met or not so as to obtain a channel access permission; and activating storage area entrance equipment through the obtained channel access authority to obtain a confirmation signal that the image-text printing piece enters the high-standard area.

Description

Technical Field

[0001] This invention relates to the field of information technology, and in particular to a method and system for controlling the sorting route of graphic printing. Background Technology

[0002] In the modern logistics and printing industry, the management and sorting of printed materials is a crucial area that directly relates to product quality and storage efficiency, especially in scenarios involving special storage needs, such as the anti-mold protection of photo-quality prints.

[0003] The importance of this field lies in how to ensure the quality of printed parts through technological means, while improving the accuracy of sorting and storage, ensuring that every product is properly preserved under appropriate conditions, and meeting users' expectations for high-quality delivery.

[0004] However, many current solutions often struggle to balance the dynamic coordination of quality control and route management when faced with complex storage needs.

[0005] Existing methods focus more on improving sorting efficiency, but neglect the special requirements of printed parts in the storage environment and the flexibility of route control. As a result, when faced with printed parts of different quality standards, the system cannot effectively distinguish them and take targeted measures, which increases the risk of defective products being mixed in and affects the reliability of the overall process.

[0006] Focusing on specific technical challenges, the effectiveness of anti-mold treatment becomes a key factor affecting quality during the sorting and storage of printed materials.

[0007] Since the results of anti-mold treatment directly determine whether the printed parts are suitable for entering a specific storage area, if the treatment is not up to standard, the product may become damp or damaged. However, existing technologies lack real-time detection and feedback capabilities, making it impossible to promptly determine the processing status of the printed parts.

[0008] This further complicates route control, as the channels in the storage area often need to be dynamically adjusted based on the test results. If the quality status of the printed parts cannot be accurately matched with the corresponding route channels, defective products may enter the high-standard storage area, resulting in resource waste and management chaos.

[0009] For example, in actual business operations, if the system fails to accurately identify some substandard products after a batch of printed photos has undergone anti-mold treatment, it may mistakenly send these products to the dedicated storage area, ultimately leading to quality problems for the entire batch of products.

[0010] Therefore, how to accurately detect the anti-mold treatment effect in the sorting route and dynamically unlock and control the storage route channels to ensure that only compliant printouts enter the designated area has become a key problem that this study urgently needs to solve. Summary of the Invention

[0011] This invention provides a method for controlling the sorting route of graphic printing, mainly including: The surface data of printed graphics are collected by a detection device and processed by a recognition algorithm to obtain a quantitative index of the anti-mold treatment effect. The obtained quantitative index is compared with a preset threshold to determine whether the printed graphics meet the anti-mold standard, thus obtaining a quality status classification. If the quality status classification is satisfactory, the storage route information of the corresponding high-standard area is retrieved from the database to determine the initial channel sequence. A path optimization algorithm is used to analyze the initial channel sequence and the current sorting flow data to obtain a dynamically adjusted route channel configuration. The dynamically adjusted route channel configuration is matched with the quality status of the printed graphics to determine whether it meets the unlocking conditions, thus obtaining channel access permission. The obtained channel access permission activates the storage area entrance device, obtaining a confirmation signal that the printed graphics have entered the high-standard area.

[0012] This invention provides a graphic printing sorting route control system, mainly comprising: a data acquisition and processing module, used to acquire surface data of graphic prints through a detection device and process the data using a recognition algorithm to obtain a quantitative index of the anti-mold treatment effect; an anti-mold standard judgment module, used to compare the obtained quantitative index with a preset threshold to determine whether the graphic prints meet the anti-mold standard and thus obtain a quality status classification; a storage route acquisition module, used to obtain the storage route information of the corresponding high-standard area from the database if the quality status classification is qualified, and determine the initial channel sequence; a path optimization analysis module, used to analyze the initial channel sequence and the current sorting flow data using a path optimization algorithm to obtain a dynamically adjusted route channel configuration; a channel permission judgment module, used to match the dynamically adjusted route channel configuration with the quality status of the graphic prints to determine whether the unlocking conditions are met and thus obtain channel access permission; and an entrance activation module, used to activate the storage area entrance device through the obtained channel access permission and obtain a confirmation signal for the graphic prints to enter the high-standard area. The technical solution provided by the embodiments of this invention may include the following beneficial effects: This invention discloses an intelligent management method based on the detection of anti-mold effects and optimization of storage paths for printed graphics. Addressing the business scenario of matching the quality classification of printed graphics after anti-mold treatment with high-standard storage areas, this method achieves accurate judgment of quality quantification indicators through data collection and algorithm analysis, and solves the problem of adapting storage routes to sorting traffic by combining dynamic path optimization. First, this invention acquires surface data through a detection device and applies a recognition algorithm to obtain anti-mold effect indicators, which are then compared with preset thresholds to complete quality classification. For compliant printed graphics, storage route information is extracted from a database, and a path optimization algorithm combined with traffic data is used to dynamically adjust channel configuration to ensure efficient sorting. Finally, by matching quality status with route configuration, the entry device of the storage area is activated, confirming entry into the high-standard area. This invention achieves fully automated management of the entire process from quality detection to storage path optimization, improving the storage efficiency and quality assurance capabilities of printed graphics. Attached Figure Description

[0013] Figure 1 This is a flowchart of a graphic printing sorting route control method according to the present invention.

[0014] Figure 2 This is a schematic diagram of the hardware connection of the graphic printing and sorting system of the present invention.

[0015] Figure 3 This is a flowchart of the data processing for detecting the anti-mildew treatment effect of the present invention.

[0016] Figure 4 This is a flowchart for classifying and determining the quality status of the present invention.

[0017] Figure 5 This is a flowchart illustrating the dynamic adjustment of the path optimization algorithm in this invention.

[0018] Figure 6 This is a performance comparison chart between the anti-mildew effect testing method of the present invention and the traditional method.

[0019] Figure 7 This is a flowchart of the channel permission matching and authorization process of the present invention.

[0020] Figure 8 This is a schematic diagram of the laser scanning detection device for the surface of printed parts according to the present invention.

[0021] Figure 9 This is a schematic diagram of the physical layout of the sorting channel and storage area of ​​the present invention.

[0022] Figure 10 This is a schematic diagram of the structure of the entrance gate device for the storage area of ​​the present invention. Detailed Implementation

[0023] like Figure 1As shown, the graphic printing sorting route control method of the present invention includes the following steps: First, in step S101, surface data of graphic prints is collected by a detection device and the data is processed by an identification algorithm to obtain a quantitative index of the anti-mold treatment effect. This quantitative index can objectively reflect the anti-mold treatment quality of the graphic prints. In step S102, the obtained quantitative index is compared with a preset threshold to determine whether the graphic prints meet the anti-mold standard, thereby obtaining a quality status classification. In step S103, if the quality status classification is qualified, the storage route information of the corresponding high standard area is obtained from the database to determine the initial channel sequence. In step S104, the initial channel sequence and the current sorting flow data are analyzed by a path optimization algorithm to obtain a dynamically adjusted route channel configuration, thereby optimizing the sorting efficiency. In step S105, the dynamically adjusted route channel configuration is matched with the quality status of the graphic prints to determine whether the unlocking conditions are met, thereby obtaining channel access permission. Finally, in step S106, the storage area entrance device is activated by the obtained channel access permission to obtain a confirmation signal for the graphic prints to enter the high standard area, completing the entire sorting route control process.

[0024] like Figure 2 As shown, the hardware connection architecture of the graphic printing and sorting system of the present invention includes a central controller 1101, a laser scanning detection device 1102, a flow sensor group 1103, a database server 1104, and an entrance gate device 1105. The central controller 1101 adopts a server rack form, with a multi-layer tray structure inside. Each layer is equipped with indicator lights, and a heat dissipation vent array is located on the right side to ensure stable system operation. The laser scanning detection device 1102 includes a lens module and a laser emission port for collecting data from the surface of packages, emitting a fan-shaped laser beam from the bottom for scanning. The flow sensor group 1103 consists of three independent sensor units, each equipped with a sensing probe and a signal transmission line to monitor the sorting flow in real time. The database server 1104 adopts a cylindrical multi-layer structure to store route information and permission rules. The entrance gate device 1105 has a gate-type structure, including left and right columns, a top beam, and an openable gate, with sensor indicator lights on the top. The wired connection 1106 uses the TCP / IP protocol to connect the laser scanning device, flow sensors, and central controller, as well as the central controller and database server. The Wireless Connection 1107 uses the MQTT protocol to achieve wireless communication between the central controller and the entrance gate equipment. The entire system ensures the reliability and real-time performance of data transmission through both wired and wireless connections.

[0025] like Figure 8As shown, the present invention uses a laser scanning detection device to perform precise detection on the surface of the printed part. The device mainly includes: a laser emitter 801 located at the top of the device, with a heat sink texture on the outer shell and a high-precision lens at the bottom, used to generate a stable laser beam 802; the laser beam 802 is projected vertically downwards onto the surface of a horizontally placed printed part 803, with a scanning resolution set to 1000 dots per square centimeter; when the laser beam irradiates the surface of the printed part, it generates reflected light 804, which carries information about the surface's micro-texture and unevenness, and is captured by a side-mounted light signal receiver 805; the printed part 803 has graphic content printed on its surface and is placed on a detection platform 806, which consists of a stable platform and four support legs, with a reinforced base underneath to provide a stable platform and ensure scanning accuracy; the light signal receiver 805 is a cylindrical device with an optical lens at the front end, and the collected reflected light signal is transmitted to a data processing unit 807 via a signal line; the data processing unit 807 is shaped like a computer host, equipped with a display screen to display waveform data in real time, control buttons, and a heat dissipation grid, and analyzes and processes the light signal to extract surface feature data. This device uses optical principles to project a laser beam onto the surface of a printed part. By analyzing the intensity and phase changes of the reflected light signal, it can accurately capture the microscopic texture features, unevenness, and defect information of the printed surface, providing a reliable data foundation for subsequent image recognition and quality assessment. The entire inspection process is highly automated, fast, and accurate down to the micrometer level.

[0026] The technical solutions of the present invention will be clearly and thoroughly described below with reference to the accompanying drawings. The described embodiments are merely some embodiments of the present invention.

[0027] This embodiment of a graphic printing sorting route control method and system may specifically include: S101. Collect surface data of the printed graphic parts through a detection device and process the data using a recognition algorithm to obtain a quantitative index of the anti-mildew treatment effect.

[0028] The printed parts are scanned using a detection device to obtain raw records of surface data. Based on the acquired surface data, a pre-established image processing tool is used to denoise and standardize the data, resulting in clear surface information. For this clear surface information, a support vector machine algorithm is applied to classify the data and determine the relevant features for anti-mold treatment. If the classified features meet a preset threshold, the anti-mold treatment is deemed successful, and the corresponding effect level is obtained. By comparing the effect level with the surface information, it is determined whether there are any processing deviations in local areas. Based on these local deviations, statistical tools are used to calculate the central tendency of the deviation distribution, determining the direction for deviation correction. If the direction of deviation correction exceeds a preset range, a data backtracking mechanism is used to re-analyze the surface information to determine the final treatment effect.

[0029] like Figure 3 As shown, the data processing flow for detecting the anti-mold treatment effect includes the following steps: First, the surface of the printed part is scanned with a laser scanner to obtain the original surface data record (S1); then, image processing tools are used for noise reduction and standardization to obtain clear surface information (S2); next, the support vector machine algorithm is applied to classify the data and determine the anti-mold treatment features (S3). After obtaining the features, the first judgment is made: if the features meet the preset threshold, the anti-mold treatment is deemed to be up to standard and the effect level is obtained (S4), and then the processing deviation of the local area is compared and analyzed (S5); if the features do not meet the preset threshold, the process returns to step S2 through the dashed path, marked "reprocessing", and the image processing and feature extraction are performed again. After step S5 is completed, the second judgment is made: if the deviation does not exceed the range, the final processing effect is determined (S6); if the deviation exceeds the range, the data backtracking mechanism is activated for re-analysis, the process returns to step S2 through the dashed path, the processing parameters are adjusted, and the detection process is re-executed. In the figure, the dashed arrows represent the backtracking path, the solid arrows represent the normal process, the diamonds represent the judgment nodes, and the rectangles represent the processing steps. This process ensures the accuracy of mold prevention treatment effect detection through two judgment nodes and a backtracking mechanism.

[0030] like Figure 6As shown, the anti-mold detection method using the SVM algorithm combined with Gaussian filtering for noise reduction employed in this invention exhibits significant advantages over traditional detection methods in multiple performance indicators. In terms of detection accuracy, the method of this invention achieves over 95%, while the traditional method only reaches 75%, representing a 20 percentage point improvement. Regarding processing efficiency, the method of this invention processes a single item in 0.5 seconds, while the traditional method requires 2.0 seconds, a four-fold increase in processing speed. In terms of false detection rate control, the method of this invention has a false detection rate of less than 2%, while the traditional method has a false detection rate exceeding 10%, significantly improving reliability. Particularly noteworthy is the ability to identify local deviations; the method of this invention supports deviation identification with 5% accuracy, a capability not possessed by traditional methods. These performance advantages are attributed to the high-precision laser scanning acquisition (resolution 1000 points / cm²) used in step S101, the 5×5 Gaussian filtering kernel noise reduction processing using OpenCV, and the mold density threshold of 0.01 set in the SVM classification algorithm, ensuring the high efficiency and accuracy of anti-mold detection and providing reliable technical support for the quality control of leather products.

[0031] For example, in actual testing of anti-mold treatment for printed parts, the surface of the printed part is first scanned using a laser scanner to obtain a raw record of the surface data. This scanning device typically uses optical principles to project a laser beam onto the surface and captures microscopic textures and unevenness through reflected light signals, thereby forming high-resolution point cloud data.

[0032] Specifically, the scanning process involves equipment calibration to ensure uniform beam distribution. For example, for an A4-sized printed sheet, the scanning resolution is set to 1000 dots per square centimeter, recording raw data such as surface roughness, color deviation, and potential mold stains. This data is stored in matrix form for easy subsequent processing. Based on the acquired surface data, pre-established image processing tools are used to denoise and standardize the data, resulting in clear surface information.

[0033] In one possible implementation, the image processing tool could be a custom module based on the OpenCV library. The denoising part uses a Gaussian filter to remove random noise; for example, setting the filter kernel size to 5x5 and calculating a weighted average for each pixel to smooth the data. Normalization maps data values ​​to the 0-1 range through a normalization operation, avoiding differences between different scanning batches. After this processing, the surface information becomes clearer, highlighting the uniformity of the anti-mold coating. Based on the clear surface information, a support vector machine algorithm is applied to classify the data and determine the relevant features of the anti-mold treatment.

[0034] Specifically, Support Vector Machines (SVMs) are a supervised learning model that separates different categories of data by finding the maximum margin hyperplane. In implementation, the model is first trained using historical samples, such as input data of known compliant and non-compliant printed surfaces, with features including texture entropy and grayscale gradient. Then, new data is classified, outputting feature vectors; for example, mold density below 0.01 is considered a normal feature. This classification helps accurately identify the effectiveness of anti-mold treatments. If the classified features meet a preset threshold, the anti-mold treatment is deemed compliant, and the corresponding effectiveness level is obtained.

[0035] For example, a threshold can be set at a feature similarity greater than 90%. If this is met, the product is categorized into performance levels such as Level 1 (Excellent) and Level 2 (Acceptable). This grading system can improve technical efficiency, such as increasing the efficiency of production quality control and preventing defective products from entering the market. By comparing the performance level with surface information, it can be determined whether there are processing deviations in localized areas.

[0036] In one possible implementation, the comparison involves pixel-level matching, such as overlaying a standard surface template of primary effect with actual information to calculate a difference map. If a local area, such as the edge of a paper, deviates by more than 5%, it is marked as a processing deviation, thus revealing the problem of uneven coating spraying. Based on the processing deviation of the local area, statistical tools are used to calculate the central tendency of the deviation distribution, obtaining the direction of deviation correction.

[0037] Specifically, statistical tools, such as those using mean and standard deviation, can be used to calculate the average position of the deviation point set, revealing a central tendency shifted 3 cm to the left, which guides subsequent adjustments to the spraying equipment. If the deviation correction direction exceeds the preset range, a data backtracking mechanism is used to reanalyze the surface information to determine the final treatment effect.

[0038] In one possible implementation, the backtracking mechanism involves tracing the original scan data backward, for example, reapplying enhancement filters, verifying whether the deviation is caused by noise, and ultimately confirming that the result is at level two qualified, thus ensuring the accuracy and reliability of the detection.

[0039] S102. Based on the obtained quantitative indicators and the preset threshold, determine whether the printed graphic works meet the anti-mildew standards and thus obtain the quality status classification.

[0040] Step 1: Obtain test sample data from the printed materials, recording the printing materials and environmental conditions to obtain a preliminary test dataset. Step 2: Based on the preliminary test dataset, use testing methods to test the samples and obtain quantitative data related to the anti-mildew standard. Step 3: Compare the obtained quantitative data with a preset threshold. If the quantitative data is lower than the preset threshold, it is determined to be non-compliant with the standard, obtaining a preliminary judgment result. Step 4: Based on the preliminary judgment result, and considering the characteristics of the environmental conditions and printing materials, perform a secondary verification of the data comparison results to determine the final judgment result. Step 5: Based on the final judgment result and the anti-mildew standard, classify the quality status of the printed materials and obtain status classification information. Step 6: Using the status classification information, generate detailed records of the quality status, determine whether it meets the standard requirements, and output the classification basis. Step 7: Based on the classification basis, for samples that do not meet the standard, record the details of the relevant environmental conditions and testing methods to determine the subsequent processing direction.

[0041] like Figure 4 As shown, the quality status classification and judgment process includes seven steps. First, in step S100, test sample data is obtained from the printed materials, and the printing materials and environmental conditions are recorded to obtain a preliminary test dataset. Then, in step S200, the samples are tested using an optical scanning method to obtain quantitative data related to the anti-mold standard, such as the mold area ratio of 2.5%. Next, at the judgment node in step S300, the test data is compared with a preset threshold to determine whether the mold area does not exceed 3%. If it is below the threshold, it proceeds to step S400 for secondary verification, and the final judgment result is determined based on the environmental conditions and printing material characteristics; if it meets the threshold, it directly proceeds to step S500. In step S500, the quality status is classified into three levels according to the anti-mold standard: excellent (less than 1%), qualified, or unqualified. Subsequently, in step S600, a detailed record of the quality status is generated and the classification basis is output. Finally, in step S700, the environmental conditions and test details of samples that do not meet the standard are recorded to determine the subsequent processing direction. This process achieves accurate determination of the quality status of printed documents by comparing quantitative data with thresholds, using a secondary verification mechanism, and employing multi-level classification standards.

[0042] For example, when processing printed materials, the first step is to select a suitable test sample from the printouts. For instance, select an A4 paper printout printed with water-based ink as the sample. Then, record in detail the printing materials, such as paper type, and environmental conditions, such as humidity levels. For example, record the paper's fiber density as 80 grams per square meter and the ambient humidity as 60%, thus forming a preliminary test dataset containing these parameters. This dataset can provide a basic reference for subsequent analysis.

[0043] Specifically, based on this preliminary test dataset, optical scanning testing methods can be used to test the samples. For example, a high-resolution scanner can be used to scan the surface of the printed parts to capture image data related to mold growth. The proportion of the mold-covered area can be calculated using quantitative tools to obtain quantitative data related to the anti-mold standard, such as a mold area ratio of 2.5%. This helps to evaluate the anti-mold performance of the printed parts.

[0044] In one embodiment, these quantified data can be compared with a preset threshold, such as the mold area not exceeding 3%. If the quantified data, such as 2.5%, is lower than this threshold, it is initially determined that it does not meet the standard, thus obtaining a preliminary judgment result. This result can be used as the basis for further verification to ensure the accuracy of the judgment.

[0045] For example, based on the initial judgment results, and combined with environmental conditions such as high temperature and humidity and the characteristics of printing materials such as ink water resistance, the data comparison results can be checked a second time. For instance, if the ambient humidity exceeds 70% and the material water resistance is low, the judgment may be adjusted to partially compliant, and a more reliable judgment result can be finally determined. This helps to avoid misjudgments caused by a single factor.

[0046] Specifically, based on this final judgment and in conjunction with anti-mold standards such as the international ISO standard for mold resistance requirements, the quality status of printed graphics is classified as excellent, qualified, or unqualified, and corresponding status classification information is obtained. For example, mold spots with an area of ​​less than 1% are classified as excellent, thereby providing classification guidance for quality management.

[0047] In one embodiment, this status classification information can be used to generate a detailed record, including the specific location and extent of mold on the printed parts, to determine whether it fully meets the standard requirements, and output classification criteria such as comparative analysis based on quantitative data. This record can be used to track the overall quality of the printed parts.

[0048] For example, for samples that are classified as non-compliant, relevant environmental conditions such as a temperature of 25 degrees Celsius and details of the testing methods such as a scan resolution of 300 dpi will be recorded. Then, the direction of subsequent processing will be determined, such as suggesting adjustments to the printing materials or optimization of the storage environment to improve the anti-mold effect.

[0049] Specifically, this approach can be determined by analyzing recorded environmental data. If excessive humidity is the primary cause, then adding a desiccant should be prioritized as an improvement measure, thus forming a continuous quality optimization chain.

[0050] In one embodiment, the logical connection of the entire process is that the output of each step serves as the input of the next step. For example, the initial dataset directly supports the implementation of the detection method, while the final processing direction is derived from the previous classification criteria, ensuring the integrity from sample acquisition to final optimization.

[0051] For example, in actual business operations, if the printed documents are used for archival preservation, the above methods can help identify potential mold risks. For instance, in a batch of historical document printouts, quantitative data comparison reveals that some samples have mold areas of up to 4.2%, exceeding the threshold. After secondary verification, these samples are classified as unqualified, and the ambient humidity of 75% and the infrared scanning used for testing are recorded. This helps determine the direction, such as replacing with low-hygroscopic materials. This not only improves the reliability of preservation but also reduces subsequent maintenance costs.

[0052] S103. If the quality status is classified as compliant, the storage route information of the corresponding high standard area is obtained from the database to determine the initial channel sequence.

[0053] If the quality status is classified as compliant, storage path information related to the high-standard area is extracted from a pre-established database source to obtain a preliminary path data set. Based on this preliminary path data set, a matching process is performed to determine the correspondence between the high-standard area and the regional division, identifying a subset of storage paths consistent with the regional division. By mapping the storage path subset to the initial channels, the channel order is arranged according to preset rules, resulting in an initial channel order list. If the initial channel order list contains path data that does not match the regional division, this data is re-filtered to obtain an updated path subset that meets the high-standard area requirements. Based on the updated path subset and the channel order arrangement rules, the initial channels are ordered to determine the final channel order scheme. By comparing the final channel order scheme with the storage path data, path conflicts are determined. If conflicts exist, the conflicting paths are prioritized to obtain the optimized channel order result.

[0054] like Figure 9As shown, the physical layout of the sorting channel and storage area of ​​this invention, from left to right, includes: an entrance area 901, an inspection area 902, a main sorting channel, and a storage area. Printed parts first enter the system from the entrance area 901 and undergo quality inspection in the inspection area 902, which is equipped with a quality inspection device for real-time monitoring of print quality parameters. The main sorting channel includes three parallel channels: A (labeled 903), B (labeled 904), and C (labeled 905), with arrows within each channel indicating the direction of print material transport. The storage area is divided into two parts: a high-standard storage area 906 located in the upper right and a regular storage area 907 located in the lower right. The high-standard storage area 906 stores prints that meet quality standards; when its capacity load rate is greater than 80%, it is identified as a high-load group, and an entrance gate 908 is installed at its entrance for access control. The regular storage area 907 stores prints that do not meet quality standards; when its capacity load rate is less than 30%, it is identified as a low-load group. Channel A is primarily connected to the high-standard storage area 906, while channel C is primarily connected to the ordinary storage area 907. Channel B serves as a backup channel for dynamic traffic distribution. Based on storage route information obtained from the database and combined with real-time sorting traffic data, the system dynamically adjusts the path allocation of each channel to optimize the path, ensuring storage efficiency in the high-standard area and reasonable utilization of the low-load area.

[0055] For example, after the quality status is determined to be up to standard, the process of extracting storage path information related to the high standard area from a pre-established database source can be understood as first accessing a database specifically for printing material quality management, which stores various path data, such as file storage location and access permission details.

[0056] Specifically, assuming the database source is a cloud system, it contains paths to high-standard zones such as " / high_quality / print_materials / anti_mold / zoneA". During extraction, relevant sets are filtered out based on the compliance status. For example, the path data set may include multiple sub-paths such as " / zoneA / sub1" and " / zoneA / sub2". These paths correspond to the storage locations of prints with excellent anti-mold performance, thus forming a preliminary path data set, which provides a basis for subsequent matching.

[0057] In one embodiment, when matching the correspondence between high-standard areas and regional divisions based on the preliminary path data set, a mapping algorithm can be used.

[0058] For example, a high-standard zone is defined as an area with a mold prevention level higher than 90%. The zone division may be based on geography or function, such as "indoor storage zone" and "outdoor storage zone". The matching process involves comparing path labels with the division criteria. If the path " / zoneA / sub1" is marked as "indoor" and the high-standard zone requires indoor priority, then it is determined to be a consistent subset of storage paths. This filters out subsets such as " / zoneA / sub1" and " / zoneA / sub3", ensuring the logical consistency between the path and the zone division.

[0059] For example, the process of arranging the order of channels by associating a subset of storage paths with the initial channels using preset rules can be specifically described as follows: the initial channel refers to the virtual channel for data transmission, such as channel 1 for fast access and channel 2 for backup. The preset rules may be based on priority, such as "high priority for anti-mold channels first". After arranging, the resulting order list is such as "channel 1 - subset path A, channel 2 - subset path B", which helps to optimize data flow.

[0060] In one embodiment, if there is path data in the initial channel sequence list that does not match the region division, then that part of the data is re-filtered.

[0061] For example, if the path " / zoneB / sub4" in the list belongs to the outdoor zone but the high standard zone requires indoor access, then it is filtered out, and an updated subset of paths is obtained, such as only " / zoneA / sub1" and " / zoneA / sub3" remaining, thus refining the data to meet the requirements.

[0062] For example, the process of adjusting the order of initial channels to determine the final solution based on the updated path subset and the channel order arrangement rules could be adjusted to "channel 1 processes subset path A first, and channel 3 processes subset path B". The rules may include load balancing principles to ensure that channels are not overloaded.

[0063] In one embodiment, a path conflict is determined by comparing the final channel order scheme with the stored path data.

[0064] For example, if channel 1 in the scheme is assigned two overlapping paths such as " / zoneA / sub1" and " / zoneA / sub1_copy", it is identified as a conflict. The conflicting paths are prioritized, such as prioritizing the latest path based on the timestamp, resulting in an optimized result such as "channel 1 - latest path, channel 2 - backup path". This can improve storage efficiency and the reliability of anti-mold quality management in business operations.

[0065] S104. The path optimization algorithm is used to analyze the initial channel sequence and the current sorting flow data to obtain the dynamically adjusted route channel configuration.

[0066] Based on the aforementioned business content and extracted relevant attributes, the following business solution is generated, focusing on the technical process design around interrelated attributes such as path optimization, dynamic adjustment, route configuration, channel configuration, sorting traffic, traffic data, data analysis, optimization analysis, and route planning. The following steps are implemented through information technology processing, employing a logically progressive approach to ensure smooth data flow between steps. Sorting traffic data and initial channel sequence information are acquired in real-time through a data acquisition system to construct a traffic distribution dataset and obtain the current traffic load status. Based on the traffic distribution dataset, data analysis methods are used to identify load differences and bottleneck locations in each channel, determining the distribution of high-load and low-load channels. If the traffic in a high-load channel exceeds a preset threshold, a dynamic adjustment mechanism is triggered. Combined with path optimization analysis, the allocable capacity of backup channels is calculated, and available route planning schemes are determined. Based on the path optimization analysis results, a new route configuration scheme is generated, and traffic is diverted to high-load channels to obtain adjusted channel configuration parameters. The adjusted channel configuration parameters are obtained, mapped to the actual sorting system, and the channel sequence data is updated to determine the new traffic allocation status. Based on the updated traffic allocation status, continuously monitor the sorting traffic data, record load change trends, and obtain the real-time optimized channel operation status.

[0067] like Figure 5 As shown, the dynamic adjustment process of the path optimization algorithm includes the following steps: First, the sorting flow data and initial channel sequence information are acquired in real time through the acquisition system to construct a flow distribution dataset (S100); second, data analysis methods are used to identify the load differences and bottleneck locations of each channel, and when the standard deviation exceeds 1.5 times the average value, it is marked as a bottleneck channel (S200); then, a clustering algorithm is used to divide the channels into high-load groups (capacity utilization greater than 80%) and low-load groups (capacity utilization less than 30%) (S300); finally, it is determined whether the flow of the high-load channel exceeds the threshold. At 90% (judgment node), if the threshold is exceeded, a genetic algorithm is used for path optimization analysis to calculate the allocable capacity of the backup channel (S400), generate a new route configuration scheme, and divert traffic to the high-load channel (S500). The optimization results are then mapped to the actual sorting system, and the channel sequence data is updated (S600). If the threshold is not exceeded, the process proceeds directly to the monitoring stage. Finally, the load change trend is continuously monitored, and the optimization effect data is recorded (S700), forming a closed-loop feedback mechanism. The monitoring data is fed back to the traffic acquisition stage, enabling real-time dynamic adjustment of path optimization. This flowchart clearly illustrates the complete closed-loop control process from traffic acquisition, load identification, threshold judgment to dynamic optimization, ensuring that the sorting system always remains in optimal operating condition.

[0068] For example, in a sorting system, by acquiring sorting flow data and initial channel sequence information in real time through a data acquisition system, a flow distribution dataset can be constructed, thereby obtaining the current flow load status.

[0069] Specifically, this data collection process involves using sensors and IoT devices to monitor the flow of goods in the passageway.

[0070] For example, when goods enter the sorting area, the system records the quantity, type, and processing time of goods in each channel. This data is aggregated into a dataset containing attributes such as channel number, real-time flow value, and load percentage. By analyzing this dataset, the system can visually display which channels are experiencing peak traffic, thus providing a basis for subsequent optimization.

[0071] In one possible implementation, data analysis methods are used to identify the load differences and bottleneck locations of each channel based on the traffic distribution dataset, and to determine the distribution of high-load and low-load channels.

[0072] For example, data analysis methods can be based on statistical model-based load balancing analysis. The principle is to calculate the average flow and standard deviation of each channel. If the standard deviation of a channel's flow exceeds 1.5 times the overall average, it is marked as a bottleneck. The specific process includes first cleaning the dataset to remove outliers, and then using clustering algorithms to divide the channels into high-load groups (e.g., channels with flow exceeding 80% of capacity) and low-load groups (e.g., channels with flow below 30% of capacity). This clearly maps the distribution, paving the way for adjustment mechanisms.

[0073] For example, if the traffic of a high-load channel exceeds a preset threshold, a dynamic adjustment mechanism is triggered. Combined with path optimization analysis, the allocable capacity of the backup channel is calculated, and an available route planning scheme is determined.

[0074] In one possible implementation, the dynamic adjustment mechanism is based on a real-time feedback loop. When the traffic exceeds a threshold such as 90%, the system automatically starts an optimization engine. This engine analyzes the remaining capacity of the backup channel, for example, by estimating the capacity using the formula = total capacity - current occupancy, and combines it with path optimization analysis, which involves graph theory algorithms to find the shortest path or the path with the lowest cost.

[0075] Specifically, the process of determining an available solution involves listing all possible alternative routes, evaluating the distance, estimated time, and compatibility of each route, and selecting an available solution if the capacity of an alternative channel is sufficient to divert 20% of the traffic and there are no path conflicts, thereby ensuring the efficiency of traffic diversion.

[0076] In one possible implementation, a new route configuration scheme is generated based on the path optimization analysis results, and traffic is diverted for high-load channels to obtain the adjusted channel configuration parameters.

[0077] For example, route optimization analysis can use genetic algorithms to simulate multiple configuration schemes. The principle is to iteratively generate route variants and evaluate fitness values ​​to select the best one. Specifically, the optimized route is extracted from the analysis results, and then a portion of the traffic from high-load channels is redirected to low-load channels, such as diverting 30% of the goods from channel A to channel B. The parameters are updated, including new sequence numbers and diversion ratios. This adjusted configuration can balance the overall load and bring more stable sorting efficiency.

[0078] For example, obtain the adjusted channel configuration parameters, map them to the actual sorting system, update the channel sequence data, and determine the new flow allocation status.

[0079] In one possible implementation, this mapping process involves an API interface transmitting parameters to the control system.

[0080] For example, the system will update the sequence table in the database, change the channel order from ABC to ACB, and allocate traffic in real time to ensure that the load of each channel is evenly distributed in the new state.

[0081] Specifically, this update can reduce waiting time and increase throughput.

[0082] For example, based on the updated traffic allocation status, continuously monitor the sorting traffic data, record the load change trend, and obtain the real-time optimized channel operation status.

[0083] Specifically, the monitoring uses time series analysis, which tracks traffic changes every minute and plots trend charts. If the trend shows a decrease in load, the optimization is confirmed to be effective; otherwise, iterative adjustments are made to maintain the long-term stability of the system.

[0084] S105. Match the dynamically adjusted route channel configuration with the quality status of the printed documents to determine whether the unlocking conditions are met and thus obtain channel access permissions.

[0085] By retrieving route channel configuration status data from the system, the latest dynamically adjusted parameter values ​​are extracted and stored as the first dataset. Based on the configuration status data in the first dataset, a pre-established quality assessment model is invoked to generate quality status data related to graphic printing, which is saved as the second dataset. If the quality status data in the second dataset reaches a preset threshold, it is determined that the preliminary conditions are met, and the corresponding unlocking condition data is extracted and saved as the third dataset. For the unlocking condition data in the third dataset, permission rules related to channel access are obtained, permission matching results are generated, and stored as the fourth dataset. If the permission matching results in the fourth dataset meet the preset access permission standards, an authorization instruction for channel access is generated through the system interface and saved as the fifth dataset. Based on the authorization instruction in the fifth dataset, the channel access status record is automatically updated, completing the final confirmation of permission acquisition.

[0086] like Figure 7 As shown, the channel permission matching and authorization process of this invention includes six main steps and two judgment nodes. First, the system obtains status data from the route channel configuration, extracts the latest dynamically adjusted parameter values, and stores them as the first dataset (S105-1). Then, it calls a quality assessment model based on a machine learning framework to analyze and process the first dataset, generating quality status data and saving it as the second dataset (S105-2). At the first judgment node, the system checks whether the quality status reaches a preset threshold (clarity > 80 points). If it does not meet the standard, it returns for reassessment; if it does, it continues the subsequent process (S105-3). Next, the system obtains the channel access permission rules, which are based on Access Control Lists (ACLs), generates permission matching results, and stores them as the fourth dataset (S105-4). At the second judgment node, the system verifies whether the permission matching results meet the standard (score > 90 points). If they do not meet the standard, authorization is rejected; if they do meet the standard, an authorization instruction is generated through the system interface, forming the fifth dataset (S105-5). Finally, the system automatically updates the channel access status record, completing the final confirmation of permission acquisition (S105-6). The entire process employs two threshold-based decision points to achieve dual safeguards for quality control and access verification, ensuring the security and reliability of channel access. The feedback path is represented by dots and lines, allowing for reprocessing when quality assessments fail, demonstrating the process's adaptive nature.

[0087] For example, in a logistics sorting system, the first step is to obtain the configuration status data of the route channels from the central control platform. This data includes parameters such as the width, length, and current load capacity of the channels.

[0088] Specifically, the system extracts the latest dynamically adjusted parameters through a real-time query interface. For example, the width of a certain channel is adjusted from the initial 2 meters to 2.5 meters to accommodate increased package traffic. These parameter values ​​are then organized into a structured first dataset for subsequent processing. This acquisition process, based on a database query mechanism, ensures data real-time performance and accuracy, thus providing a reliable foundation for quality assessment.

[0089] In one possible implementation, a pre-built quality assessment model is invoked based on the configuration status data in the first dataset. This model is a machine learning-based framework used to analyze the impact of aisle configuration on graphic printing tasks. The principle of the quality assessment model is to simulate the stability of the printing process by inputting configuration parameters, such as aisle width and load capacity. For example, the model considers the impact of vibration from the printing equipment and generates quality status data, including print sharpness and error rate metrics. This data is saved as the second dataset. For instance, if the aisle width parameter is 2.5 meters, the model might calculate a print sharpness score of 85, indicating that the quality of graphic printing is high under this configuration. This allows for a quantitative evaluation of the effect of configuration adjustments.

[0090] For example, if the quality status data in the second dataset reaches a preset threshold, such as a clarity score exceeding 80 points, the system determines that the preliminary conditions are met. At this point, the corresponding unlocking condition data, such as the access priority and time limit of the channel, will be extracted and saved as the third dataset.

[0091] Specifically, this judgment process involves threshold comparison logic. If the score is 85, which is higher than the threshold of 80, the system automatically triggers the extraction mechanism to retrieve unlock data from the associated database, ensuring that only channels with qualified quality can enter the next permission process, thereby improving the overall security and efficiency of the business.

[0092] In one possible implementation, for the unlocking condition data in the third dataset, the system retrieves the permission rules related to channel access. These rules define user roles and access levels; for example, administrators are allowed full-time access while operators are limited to work hours. The system then generates permission matching results and stores them as the fourth dataset. The principle of the permission rules is based on an access control list framework. By matching unlocking conditions, such as high priority, with administrator requirements in the rules, a matching score is obtained. A score of 100 indicates a complete compliance, thus clearly assessing the feasibility of access.

[0093] For example, if the permission matching results in the fourth dataset meet the preset access permission standards, such as a matching score of more than 90 points, then an authorization instruction for channel access is generated through the system interface. This instruction includes an access token and a validity period, and is saved as the fifth dataset.

[0094] Specifically, the interface calls the authorization service engine to create a digital signature instruction based on the matching result. For example, it generates a token containing a channel ID and a timestamp for the administrator to ensure the immutability of the instruction. This brings higher security to the business and prevents sorting interruptions caused by unauthorized access.

[0095] In one possible implementation, based on the authorization instructions in the fifth dataset, the system automatically updates the channel access status record, for example, changing the channel status from locked to unlocked, and records the update log to complete the final confirmation of permission acquisition. This update process is implemented through a transaction processing mechanism to ensure data consistency, such as atomically modifying the status field in the database, thereby achieving seamless permission management. In logistics operations, this helps to respond to dynamic needs in real time, improve channel utilization, and reduce human error.

[0096] S106. Activate the storage area entry device through the obtained channel access permission to obtain a confirmation signal that the graphic print has entered the high standard area.

[0097] Access verification information is obtained through the channel access data interface and compared with a pre-established access database to obtain the access verification result. If the access verification result meets the preset conditions, an activation command for the storage area entry device is triggered, and the response status of the entry device is determined. Based on the response status of the entry device, the device interaction log data is obtained to determine whether the device has completed the activation operation. If the device interaction log shows that the activation operation has been completed, a request is sent through the signal transmission module to obtain the graphic printing command signal. Based on the graphic printing command signal, the printing module is invoked to generate the corresponding print content, and the integrity of the print content is determined. Based on the integrity verification result of the print content, a confirmation signal for entering the high-standard area is generated to determine whether the signal transmission was successful. If the confirmation signal transmission was successful, the access control system updates the status data of the area division to obtain the access permission record for the high-standard area.

[0098] like Figure 10As shown, the entrance gate for the storage area adopts a rotary wing gate structure, including a column frame 1001, a rotary gate 1002, a control panel 1003, a signal receiving antenna 1004, status indicator lights 1005, a passageway 1006, an infrared sensor 1007, and a base 1008. The column frame 1001 consists of left and right side columns and a top beam, made of metal, with textured lines on the column surface to enhance mechanical strength. The rotary gate 1002 adopts a double-wing design with a central rotating shaft. When closed, the wing plates block the passage; upon receiving an opening command, the wing plates rotate 90 degrees to either side to create passage space. The control panel 1003 is embedded in the middle of the left side column, integrating an LED display screen and operation buttons. The display screen shows real-time time and equipment status information, while the buttons are used for manual control and parameter settings. The signal receiving antenna 1004 is installed in the center of the top beam, using a T-shaped antenna structure, and receives signals via the MQTT protocol. The cloud-based control system sends activation commands and configuration data. Status indicator lights 1005 are installed on the left and right sides of the top beam, indicating the equipment's operating status through on / off states and color combinations. A lit left light indicates equipment activation, while a lit right light indicates the gate is open. The passageway 1006 is the bottom personnel passage area, with directional arrows on the ground indicating the passage direction. Infrared sensors 1007 are symmetrically installed on the inner sides of the columns on both sides of the passageway, with transmitters and receivers arranged opposite each other to form an infrared beam, monitoring in real time whether personnel or objects are passing through the passageway to prevent people from being trapped by the gate. The base 1008 serves as the foundation for the entire equipment, with anti-slip textures on the surface to ensure stable installation. When the entrance equipment receives the activation command through the signal receiving antenna 1004, the controller starts a self-test program, sequentially checking whether the motor drive of the rotating gate 1002 is normal, whether the beam of the infrared sensor 1007 is connected, and whether the MQTT network connection is stable. After the self-test is completed, the operating status is displayed through the status indicator lights 1005, and a response code is returned to the system. At the same time, the operation timestamp, command type, and execution result are recorded in the equipment log to provide a basis for subsequent auditing and troubleshooting.

[0099] For example, in a real-world business scenario, the process of obtaining permission verification information through the channel permission data interface can be understood as the system first receiving an access request from the user, and then the interface calling the backend service to extract relevant user credential data, such as username, role identifier, and timestamp.

[0100] Specifically, this interface is typically designed as a RESTful API. When a user attempts to access the storage area, the system sends a GET request carrying a token. After parsing the token, the interface compares it with a pre-established permissions database. This database is a relational database such as MySQL, storing a permissions rule table containing fields for user ID, permission level, and validity period. The comparison process involves SQL queries to match these fields. If a match is successful, a verification result is returned; otherwise, a failure code is returned, ensuring that only authorized users can continue subsequent operations. The core of this comparison mechanism is real-time verification, which avoids permission abuse and effectively improves the security level for business applications.

[0101] In one possible implementation, if the permission verification result meets the preset conditions, such as verification passing and the permission level being higher than the threshold 3, the system will trigger the activation command of the storage area entry device. The entry device here may be a smart door lock or a turnstile. The activation command is sent via the MQTT protocol. After receiving the command, the device will perform a self-check and return a response status, such as "activation successful" or "device failure". After determining the status, the system records the log for tracking.

[0102] For example, when obtaining log data of device interaction based on the response status of the entry device, log files can be pulled from the device's embedded system. These logs contain timestamps, operation types, and result codes. Determining whether the activation operation is complete involves parsing specific markers in the logs, such as "activation_complete". If they exist, the operation is confirmed to be complete; otherwise, activation is retried.

[0103] In one possible implementation, if the log shows that activation is complete, a request for the graphic printing instruction signal is sent through a signal transmission module, such as a wireless module. This module uses the TCP / IP protocol for transmission, and the instruction signal includes the print template ID and data parameters. The receiving end parses the data and prepares for the printing task.

[0104] For example, when the printing module is called to generate content, the module loads a template according to the instructions, fills in graphic and textual data such as QR codes and text, and verifies the completeness by checking and calculating to ensure there are no missing parts.

[0105] In one possible implementation, an acknowledgment signal is generated based on the integrity result. Determining successful transmission involves checking the ACK response. If successful, the status data in the access control system is updated to obtain an access permission record.

[0106] For example, this creates a closed loop in the entire process, from permission verification to permission recording, ensuring secure and reliable access to the high-standard zone.

[0107] This invention provides a graphic printing sorting route control system, mainly comprising: a data acquisition and processing module, used to acquire surface data of graphic prints through a detection device and process the data using a recognition algorithm to obtain a quantitative index of the anti-mold treatment effect; an anti-mold standard judgment module, used to compare the obtained quantitative index with a preset threshold to determine whether the graphic prints meet the anti-mold standard and thus obtain a quality status classification; a storage route acquisition module, used to obtain the storage route information of the corresponding high-standard area from the database if the quality status classification is qualified, and determine the initial channel sequence; a path optimization analysis module, used to analyze the initial channel sequence and the current sorting flow data using a path optimization algorithm to obtain a dynamically adjusted route channel configuration; a channel permission judgment module, used to match the dynamically adjusted route channel configuration with the quality status of the graphic prints to determine whether the unlocking conditions are met and thus obtain channel access permission; and an entrance activation module, used to activate the storage area entrance device through the obtained channel access permission and obtain a confirmation signal for the graphic prints to enter the high-standard area. The above description is only a preferred embodiment of the present invention. It should be noted that those skilled in the art can make several improvements and additions without departing from the principle of the present invention, and these improvements and additions should also be considered within the scope of protection of the present invention.

Claims

1. A method for controlling a sorting route for graphic printing, characterized in that, The method includes: The surface data of printed graphics are collected by a detection device and processed by a recognition algorithm to obtain a quantitative index of the anti-mold treatment effect. The obtained quantitative index is compared with a preset threshold to determine whether the printed graphics meet the anti-mold standard, thus obtaining a quality status classification. If the quality status classification is satisfactory, the storage route information of the corresponding high-standard area is retrieved from the database to determine the initial channel sequence. A path optimization algorithm is used to analyze the initial channel sequence and the current sorting flow data to obtain a dynamically adjusted route channel configuration. The dynamically adjusted route channel configuration is matched with the quality status of the printed graphics to determine whether it meets the unlocking conditions, thus obtaining channel access permission. The obtained channel access permission activates the storage area entrance device, obtaining a confirmation signal that the printed graphics have entered the high-standard area.

2. The method according to claim 1, characterized in that, The process of collecting surface data of printed graphics using a detection device and processing the data with a recognition algorithm to obtain quantitative indicators of the anti-mildew treatment effect includes: The surface of the printed part is scanned by a testing device to obtain the original record of the surface data; Based on the acquired surface data, a pre-established image processing tool is used to denoise and standardize the data to obtain clear surface information. Based on clear surface information, the support vector machine algorithm is applied to classify the data and determine the relevant features of the anti-mold treatment; If the features after classification meet the preset threshold, the anti-mold treatment is deemed to have met the standard, and the corresponding effect level is obtained.

3. The method according to claim 1, characterized in that, If the quality status is classified as compliant, the storage route information for the corresponding high-standard area is retrieved from the database to determine the initial channel sequence, including: If the quality status is classified as compliant, the storage path information related to the high standard area is extracted from the pre-established database to obtain a preliminary path data set. Based on the preliminary path data set, a matching process is performed to determine the correspondence between the high-standard area and the regional division, and a subset of storage paths consistent with the regional division is determined. By mapping the subset of storage paths to the initial channels, the channel order is arranged according to preset rules to obtain the order list of the initial channels; If there are path data in the initial channel sequence list that do not match the regional division, then the data will be re-filtered to obtain an updated subset of paths that meet the requirements of the high-standard area. Based on the updated path subset and the channel order arrangement rules, the initial channel order is adjusted to determine the final channel order scheme. By comparing the final channel order scheme with the storage path data, it is determined whether there is a path conflict. If there is a conflict, the conflicting paths are prioritized to obtain the optimized channel order result.

4. The method according to claim 1, characterized in that, The method of using a path optimization algorithm to analyze the initial channel sequence and the current sorting flow data to obtain a dynamically adjusted route channel configuration includes: By acquiring sorting traffic data and initial channel sequence information in real time through the acquisition system, a traffic distribution dataset is constructed to obtain the current traffic load status; Based on the traffic distribution dataset, data analysis methods are used to identify the load differences and bottleneck locations of each channel, and to determine the distribution of high-load and low-load channels. If the traffic of a high-load channel exceeds a preset threshold, a dynamic adjustment mechanism is triggered. Combined with path optimization analysis, the allocable capacity of the backup channel is calculated, and an available route planning scheme is determined. Based on the path optimization analysis results, a new route configuration scheme is generated, traffic is diverted for high-load channels, and the adjusted channel configuration parameters are obtained. Obtain the adjusted channel configuration parameters, map them to the actual sorting system, update the channel sequence data, and determine the new flow allocation status; Based on the updated traffic allocation status, continuously monitor the sorting traffic data, record load change trends, and obtain the real-time optimized channel operation status.

5. The method according to claim 1, characterized in that, The process of matching the dynamically adjusted route channel configuration with the quality status of the printed documents to determine whether the unlocking conditions are met in order to obtain channel access includes: By obtaining the configuration status data of the route channels from the system, the latest dynamically adjusted parameter values ​​are extracted and stored as the first dataset; Based on the configuration status data in the first dataset, the pre-established quality assessment model is called to generate quality status data related to graphic printing, which is then saved as the second dataset. If the quality status data in the second dataset reaches the preset threshold, it is determined that the preliminary conditions are met, the corresponding unlocking condition data is extracted, and it is saved as the third dataset. For the unlocking condition data in the third dataset, obtain the permission rules related to channel access, generate permission matching results, and store them as the fourth dataset; If the permission matching results in the fourth dataset meet the preset access permission standards, then an authorization instruction for channel access is generated through the system interface and saved as the fifth dataset. Based on the authorization instructions in the fifth dataset, the channel access status record is automatically updated to complete the final confirmation of permission acquisition.

6. A graphic printing sorting route control system, characterized in that, The system includes: a data acquisition and processing module, used to acquire surface data of printed graphics through a detection device and process the data using a recognition algorithm to obtain a quantitative index of the anti-mold treatment effect; an anti-mold standard judgment module, used to compare the obtained quantitative index with a preset threshold to determine whether the printed graphics meet the anti-mold standard and thus obtain a quality status classification; a storage route acquisition module, used to obtain the storage route information of the corresponding high-standard area from the database and determine the initial channel sequence if the quality status classification is qualified; a path optimization analysis module, used to analyze the initial channel sequence and the current sorting flow data using a path optimization algorithm to obtain a dynamically adjusted route channel configuration; a channel permission judgment module, used to match the dynamically adjusted route channel configuration with the quality status of the printed graphics to determine whether the unlocking conditions are met and thus obtain channel access permission; and an entrance activation module, used to activate the storage area entrance device through the obtained channel access permission and obtain a confirmation signal for the printed graphics to enter the high-standard area.

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