Rust-proof and corrosion-resistant super-high-strength square tube full-life-cycle rust-proof tube control method and system

Abstract

This invention relates to the field of pipeline corrosion protection technology, specifically to a method and system for full-lifecycle rust prevention and control of ultra-high strength square tubes with rust and corrosion resistance. The method includes the following steps: extracting image anomaly markers, combining them with standard classification and adaptation, verifying indicators, generating access or blocking markers, changing status, and archiving. In this invention, defect areas are identified by acquiring images and film thickness information, and their location and classification are completed by combining structural coordinates and component codes. Based on image texture, boundary morphology, and foreign object characteristics, and combined with set standards, a regional adaptation level is established. Coverage status is determined from multiple dimensions, improving the accuracy and reliability of surface assessment. The determination results simultaneously generate access or blocking instructions. Embedded process control ensures stable switching connections, avoids protection interruptions, and status information is uniformly archived to form a structural-level traceability record, covering all stages of identification, judgment, repair, feedback, and archiving, enhancing adaptability, consistency, and full-process controllability.

Description

Technical Field

[0001] This invention relates to the field of pipeline corrosion protection technology, and in particular to a method and system for rust prevention and control throughout the entire life cycle of rust-resistant and corrosion-resistant ultra-high strength square pipes. Background Technology

[0002] The field of pipeline corrosion protection technology mainly involves structural treatments, surface treatments, and management methods adopted to prevent oxidation, rust, and media corrosion on the surface of metal pipelines and pipe materials during manufacturing, storage, transportation, installation, and service. Core aspects of this technology include controlling the protective state of the pipe substrate, configuring corrosion protection measures, maintaining rust prevention, and ensuring the continuous integration of corrosion protection methods at different stages. By identifying the surface condition of the pipes and combining it with process control, material handling, and management procedures, a methodological management approach for corrosion prevention is adopted for pipelines at different stages of use to reduce corrosion risks and maintain the stability of the pipes. Among them, the traditional rust prevention and corrosion-resistant ultra-high strength square pipe full life cycle rust prevention management method refers to the rust prevention management method adopted for ultra-high strength steel square pipes that are prone to rusting from the time of production to the end use. For ultra-high strength square pipes in exposed or partially protected states, electrochemical corrosion and environmental rust occur under different environmental conditions. The traditional method adopts specific means such as surface coating with rust-preventive oil, coating with anti-corrosion coating, film sealing, drying storage, and regular inspection and recoating to complete rust prevention management according to the stage of the square pipe. It also arranges rust prevention measures in the manufacturing stage, storage and transportation stage, construction stage, and use and maintenance stage through process connection to form a holistic rust prevention management method.

[0003] In existing technologies, rust prevention management relies on manual identification and phased treatment methods, such as surface oiling, film sealing, and periodic inspections. This lack of real-time assessment of the protection status and precise location of defect areas leads to high identification error rates and difficulty in timely repair of blind spots in protection coverage. Because manual operation dominates the defect discovery process, it struggles to address micro-corrosion and localized damage to square tubes in complex storage and transportation environments, often resulting in unannounced rust spread in areas of humidity fluctuation and mechanical friction. Furthermore, the absence of a multi-parameter joint judgment mechanism makes it easy to overlook the overall status assessment due to a single indicator meeting the requirements, leading to loose coordination during measure switching and interruptions in protection measures. Information transmission is also largely based on phased records, lacking a unified index of structural levels and process nodes. This makes it difficult for subsequent management to accurately locate the origin and evolution of protection defects, hindering effective traceability and closed-loop quality control. During project construction or maintenance, the lack of full lifecycle records often causes old problems to recur, affecting the continuous optimization of protection strategies and effective control of implementation costs. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide a method for rust prevention and control throughout the entire life cycle of rust-resistant and corrosion-resistant ultra-high strength square tubes, comprising the following steps:

[0005] S1: Obtain square tube image and thickness information, extract color difference, coating breakage and abnormal film thickness boundaries, pair the abnormal boundaries with structural coordinates, associate component codes and classify the abnormal boundaries, and generate a node front protection missing marker map;

[0006] S2: Extract texture, morphology and foreign object features based on the node front protection missing marker map, obtain the adhesion, surface and contamination standards, combine the texture, morphology, foreign object features, adhesion standards, surface standards and contamination standards to classify and generate a coverage status adaptation relationship table;

[0007] S3: Based on the coverage state adaptation relationship table, obtain adhesion, roughness and residue, obtain adhesion, roughness and cleanliness thresholds, determine that the adhesion is greater than or equal to the adhesion threshold, determine that the roughness and residue are less than or equal to the roughness threshold and the cleanliness threshold, and generate a measure switching consistency determination result.

[0008] S4: Extract the identifier and status from the consistency judgment result of the measure switching, bind the access identifier generated by the item and instruction, synchronize the failed item to the repair queue to generate the blocking identifier, change the status identifier, and generate the node switching process feedback status.

[0009] S5: Invoke the process identifier, area information, and structure code in the consistency judgment result between the node switching process feedback status and the measure switching, establish a data index entry, archive the structure status information corresponding to the structure code, and generate a node record entry.

[0010] As a further embodiment of the present invention, the protective defect marking map includes color difference areas, coating break areas, and abnormal film thickness areas; the coverage state adaptation relationship table includes image texture distribution, boundary morphology features, and residual foreign matter features; the measure switching consistency judgment result includes adhesion judgment result, roughness judgment result, and pollution residue amount judgment result; the node switching process feedback status includes access identifier, process blocking identifier, and status identifier conversion record; the full-cycle node record entries include process identifier, area information, and structure code.

[0011] As a further aspect of the present invention, the process of obtaining adhesion, roughness and residue is as follows: obtaining the adhesion data obtained by pull-off test, wherein the adhesion threshold is limited to the lower limit of a continuous range not less than a preset standard value;

[0012] The roughness is quantified using a surface profile scanning method, and the roughness threshold is no greater than the upper limit of the corresponding coverage state record value in the coverage state adaptation relationship table.

[0013] As a further aspect of the present invention, the residual amount is quantified by an image grayscale residual mapping method, and the cleanliness threshold is no greater than the maximum allowable value of the corresponding level of the pollution standard; when the adhesion is not less than the adhesion threshold, and the roughness and the residual amount are both not greater than the roughness threshold and the cleanliness threshold, the corresponding item in the consistency judgment result of the measure switching is marked as a pass state, otherwise it is marked as a fail state.

[0014] As a further aspect of the present invention, the specific steps of S1 are as follows:

[0015] S101: Obtain image data and thickness information collected by the surface condition detection device at the rust prevention measure conversion node during the storage and transportation stage, extract color parameters from the image and establish a color difference feature group, call the film thickness data at the corresponding position in the thickness information, perform position alignment comparison analysis on the color difference feature group and film thickness data, and filter abnormal boundary positions based on the color difference threshold and film thickness threshold to generate an abnormal area boundary index set.

[0016] S102: Based on the abnormal region boundary index set, extract the corresponding spatial mapping points in the structural layer coordinate matrix, call the layer reference coordinate values ​​to calculate the mapping relationship, extract the protective component code and match it with the mapping point position, aggregate the mapping relationship and code information, and generate a region coordinate pairing information set;

[0017] S103: Based on the area coordinate pairing information set, call the abnormal boundary and protection status fields for classification, construct a classification mark layer, and superimpose the classification area and code according to the layer coordinates to obtain the node front protection missing mark map.

[0018] As a further aspect of the present invention, the specific steps of S2 are as follows:

[0019] S201: Based on the classified areas in the pre-node protection missing marker image, extract the image texture distribution, boundary contour parameters and residual foreign object features, call the grayscale information in the texture distribution, the continuity parameters in the boundary contour and the color channel data in the foreign object features, perform feature filtering and normalization processing, and generate a regional surface structure feature group.

[0020] S202: Call the surface structure feature group of the region, calculate the adaptation value of the region under the level field according to the adhesion performance level field, surface treatment level field and pollution tolerance standard field in the anti-rust coating task sheet, and filter the adaptation index based on the matching result of the adaptation value and the pollution standard to obtain the region level adaptation index set.

[0021] S203: Based on the set of regional level adaptation indicators, establish a mapping relationship between the indicator results and the corresponding regional index in the marker map, call the task sheet level field to classify the region, and write the classification and level benchmark data into the status mapping table to generate a coverage status adaptation relationship table.

[0022] As a further aspect of the present invention, the specific steps of S3 are as follows:

[0023] S301: Based on the area parameters in the coverage state adaptation relationship table, call the area adhesion value and the preset adhesion acceptance threshold to perform threshold determination, write the determination result into the area status field, and index and encode the area status field to generate an adhesion determination identifier set.

[0024] S302: Call the adhesion determination identifier set, and according to the area roughness value and pollution residue value in the coverage status adaptation relationship table, perform threshold determination with the preset roughness acceptance threshold and the preset cleanliness acceptance threshold respectively, perform logical summary of the determination combination results and write them into the area status label field to obtain the area acceptance status label set.

[0025] S303: Based on the set of regional acceptance status labels, retrieve the code of the part to which the region belongs and perform part aggregation, calculate the pass label ratio value corresponding to the part, and write the part code, regional status label and ratio value into the consistency summary table to generate the measure switching consistency judgment result.

[0026] As a further aspect of the present invention, the specific steps of S4 are as follows:

[0027] S401: Invoke the measures to switch the part identification code and adaptation status in the consistency judgment result, retrieve the items marked as passed in the adaptation status field, bind the part identification code corresponding to the passed item with the node control instruction parameter set, and write the binding result into the admission field to generate an identification code sequence and generate an admission identification set.

[0028] S402: Based on the access identifier set, retrieve the entries marked as failed in the adaptation status field, extract the identifier code of the corresponding part of the failed entry and synchronously write it with the entry parameter set of the repair process queue, and establish a process status field and a blocking condition field for the written entries. Complete the entry locking based on the blocking condition field and obtain the process blocking identifier set.

[0029] S403: Based on the process blocking identifier set, call the status identifier field in the node console, perform status mapping conversion for the admission field and the blocking field, write the admission identifier and the blocking identifier into the node switching record table, and perform status summary encoding on the node switching record table to generate the node switching process feedback status.

[0030] As a further aspect of the present invention, the specific steps of S5 are as follows:

[0031] S501: Call the process identifier, area information and structure code in the consistency judgment result of the node switching process feedback status and the measure switching, extract the node number corresponding to the structure segment, match the node number with the structure code, and combine and aggregate the process identifier and area information to generate a node structure index entry set.

[0032] S502: Based on the node structure index entry set, extract the node status data corresponding to each structural segment, sort the status data by node number, and perform field alignment operation with the process identifier field. At the same time, construct a mapping relationship table between area fields and status values, aggregate all fields and write them into the form data structure to obtain the protection status registration field set.

[0033] S503: Based on the protection status registration field set, write the structural segment status data into the archive registration module, establish a timestamp index for the written records, generate an index record field with the node number as the primary key, incorporate all status registration data into the archive entry structure, and generate a full-cycle node record entry.

[0034] A rust-proof and corrosion-resistant ultra-high strength square tube full life-cycle rust prevention and control system, including:

[0035] The missing marker generation module is used to perform S1: to obtain the images and thickness information collected by the surface condition detection device at the rust prevention measure conversion node during the storage and transportation of ultra-high strength square tubes, extract the regional boundaries including color difference, broken coating and abnormal film thickness, match the region with the coordinates of the structural layer, associate the code of the protective component, complete the regional classification and generate the protective missing marker map before the node;

[0036] The adaptation relationship construction module is used to execute S2: Based on the classified areas in the node front protection missing mark map, extract the image texture distribution, boundary morphology and residual foreign matter characteristics of the areas, call the adhesion performance level, surface treatment level and pollution tolerance standard set in the anti-rust coating task sheet, establish the corresponding area adaptation level, and generate the coverage status adaptation relationship table.

[0037] The consistency judgment module is used to execute S3: based on the area parameters in the coverage state adaptation relationship table, it calls the preset adhesion acceptance threshold, the preset roughness acceptance threshold and the preset cleanliness acceptance threshold, performs a judgment that the adhesion value is greater than or equal to the value, performs a judgment that the roughness value and the amount of pollution residue are less than or equal to the value, marks the area as passed or failed according to the judgment result, summarizes it to the corresponding part, and generates the measure switching consistency judgment result.

[0038] The node switching feedback module is used to execute S4: call the part identification code and adaptation status in the consistency judgment result of the measures, bind the items marked as passed with the control command to generate an access identifier, synchronize the items marked as failed to pass to the repair process queue and generate a process blocking identifier, and at the same time perform status identifier conversion in the node console to generate node switching process feedback status.

[0039] The full-cycle record archiving module is used to execute S5: call the process identifier, area information and structure code in the node switching process feedback status and the consistency judgment result of the measure switching, establish data index entries according to the node number of the ultra-high strength square tube, include the status information of all structural sections into the protection status record form set for archiving and registration, and generate full-cycle node record entries.

[0040] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0041] In this invention, defect areas are identified by acquiring images and film thickness information, and the location and classification are completed by combining structural coordinates and component codes. Based on image texture, boundary morphology and foreign object characteristics, and combined with set standards, regional adaptation levels are established. Coverage status is determined from multiple dimensions, improving the accuracy and reliability of surface assessment. The determination results generate access or blocking instructions simultaneously. Embedded process control ensures stable connection of switching links and avoids protection interruption. Status information is uniformly archived to form a structural-level traceability record, covering all aspects of identification, determination, repair, feedback and archiving, enhancing adaptability, consistency and full-process controllability. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a schematic diagram of the steps of the present invention;

[0044] Figure 2 This is a detailed schematic diagram of S1 of the present invention;

[0045] Figure 3 This is a detailed schematic diagram of S2 of the present invention;

[0046] Figure 4 This is a detailed schematic diagram of S3 of the present invention;

[0047] Figure 5 This is a detailed schematic diagram of S4 of the present invention;

[0048] Figure 6 This is a detailed schematic diagram of S5 of the present invention;

[0049] Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0050] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0051] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0052] Please see Figure 1 This invention provides a method for rust prevention and control throughout the entire life cycle of rust-resistant and corrosion-resistant ultra-high strength square tubes, including the following steps:

[0053] S1: Obtain images and thickness information collected by surface condition detection device at the rust prevention measure conversion node during the storage and transportation of ultra-high strength square tubes. Extract the regional boundaries including color difference, coating breakage and film thickness anomaly, and match the region with the coordinates of the structural layer. At the same time, associate the code of the protective component, complete the regional classification and generate a protective missing mark map before the node.

[0054] S2: Based on the classified areas in the pre-node protection missing marker map, extract the image texture distribution, boundary morphology and residual foreign matter characteristics of the areas, call the adhesion performance level, surface treatment level and pollution tolerance standard set in the anti-rust coating task sheet, establish the corresponding area adaptation level, and generate the coverage status adaptation relationship table.

[0055] S3: Based on the regional parameters in the coverage status adaptation relationship table, call the preset adhesion acceptance threshold, preset roughness acceptance threshold and preset cleanliness acceptance threshold, perform a judgment of greater than or equal to the adhesion value, and perform a judgment of less than or equal to the roughness value and the amount of pollution residue. According to the judgment results, mark the region as passed or failed, and summarize it to the corresponding part to generate the consistency judgment result of the measure switching.

[0056] S4: Invoke the part identifier code and adaptation status in the consistency judgment result of the measures to switch, bind the items marked as passed with the control command to generate the access identifier, synchronize the items marked as failed to pass to the repair process queue and generate the process blocking identifier, and at the same time perform the status identifier conversion in the node console to generate the node switching process feedback status.

[0057] S5: Call the process identifier, area information and structure code in the status and measure switching consistency judgment result of the node switching process feedback, establish data index entries according to the node number of the ultra-high strength square tube, include the status information of all structural sections into the protection status record form set for archiving and registration, and generate full cycle node record entries.

[0058] The protective gap marking map includes color difference areas, coating break areas, and abnormal film thickness areas; the coverage status adaptation table includes image texture distribution, boundary morphology features, and residual foreign matter features; the measure switching consistency judgment results include adhesion judgment results, roughness judgment results, and pollution residue amount judgment results; the node switching process feedback status includes access identification, process blockage identification, and status identification conversion record; the full cycle node record entries include process identification, area information, and structure code.

[0059] Please see Figure 2 The specific steps of S1 are as follows:

[0060] S101: Obtain image data and thickness information collected by the surface condition detection device at the rust prevention measure conversion node during the storage and transportation stage, extract color parameters from the image and establish a color difference feature group, call the film thickness data at the corresponding position in the thickness information, perform position alignment comparison analysis on the color difference feature group and film thickness data, and filter abnormal boundary positions based on the color difference threshold and film thickness threshold to generate an abnormal area boundary index set.

[0061] Table 1. Surface condition sampling data during storage and transportation.

[0062]

[0063] As shown in Table 1, both region index 002 and region index 004 exhibit a combination of large overall color offset value and low film thickness measurement value. The following paragraphs will use this combination of features as a continuous input data source for anomaly boundary screening and status marking.

[0064] After acquiring image data and thickness information, pixel-level denoising is performed on each frame of the image. The image is then divided into grids according to a fixed window size. The mean values ​​of the red, green, and blue channels are extracted for each grid, and the brightness and saturation dispersion within the same grid are written into the color parameter record line. Subsequently, using the reference image stored at the previous workstation before the storage and transportation stage conversion node as the control source, the color parameters at the same grid position are subtracted and weighted to obtain the comprehensive color offset value. The grid position number and the comprehensive color offset value are combined to form a color difference feature group entry. Next, the set of film thickness measurement points with the same grid position number is read from the thickness information. Missing thickness points and obvious outliers are first removed. Outlier determination is based on sorting the film thickness measurement values ​​within the same grid from smallest to largest. If the difference between the minimum and second smallest values ​​exceeds 12 micrometers, the minimum value is marked as an outlier and removed. The remaining film thickness measurement values ​​are then averaged to obtain the film thickness data for that grid. When performing correlation analysis, the comprehensive color offset value of each grid in the color difference feature group is compared with the corresponding film thickness. Data is aligned with the same position number, and candidate points for abnormal boundaries are filtered according to a threshold rule. The threshold rule is determined by two sets of experimental data. The first set is the distribution of the comprehensive color shift value of the confirmed qualified anti-rust coating sample under the same illumination and distance, with a 9th percentile of 3.4. The second set is the distribution of the mean film thickness of the confirmed sample with severely insufficient film thickness, with a 1st percentile of 22 micrometers. Therefore, grids with a comprehensive color shift value of not less than 3.5 and a film thickness of not more than 22 micrometers are marked as abnormal candidates. For example, region index 002 in Table 1 has a comprehensive color shift value of 4.9 and a film thickness measurement value of 21 micrometers. It is directly substituted into the above judgment logic to obtain the abnormal candidate mark. Then, boundary connectivity is sorted for the abnormal candidate points. Adjacent candidate points are merged into the same abnormal connected domain according to the eight-neighbor rule. The outer contour point set is extracted for each connected domain and sorted clockwise. Finally, the grid position number of the outer contour point is written into the abnormal region boundary index set. Each record in the index set contains the connected domain number, the boundary point sequence and the corresponding image frame number, which serves as the input for subsequent spatial mapping.

[0065] S102: Based on the abnormal region boundary index set, extract the corresponding spatial mapping points in the structural layer coordinate matrix, call the layer reference coordinate values ​​to calculate the mapping relationship, extract the protection component code and match it with the mapping point position, aggregate the mapping relationship and code information, and generate a region coordinate pairing information set;

[0066] After reading the connected component numbers and boundary point sequences one by one from the abnormal region boundary index set, spatial mapping points matching the boundary point grid position numbers are retrieved in the structural layer coordinate matrix. These spatial mapping points are mapped to 3D coordinate values ​​using the row and column indices of the structural coordinate matrix. During reading, the grid position numbers are first split into row and column indices, and then the corresponding horizontal, vertical, and height coordinate values ​​are extracted from the coordinate matrix to form the spatial mapping points. Subsequently, the layer reference coordinate values ​​are called to calculate the mapping relationship. These reference coordinate values ​​come from benchmark measurement points in the same structural segment and include the benchmark point's horizontal, vertical, and height coordinate values. The mapping relationship calculation uses a combination of translation and scaling correction. First, the horizontal, vertical, and height offsets between the current spatial mapping point and the benchmark point are calculated. Then, the horizontal and vertical offsets are scaled according to the layer scaling factor, which is obtained from actual measurements on the calibration board. The distance between the two marker points on the calibration board in the image coordinates is 200 pixels, corresponding to a structural real distance of 5. Since the initial value is 0 mm, the scaling factor is set to 0.25 mm per pixel. The corrected offset is then merged with the reference point coordinates to obtain the mapped coordinates of the boundary point in the structure layer. Next, the protective component code is extracted and matched with the mapped point position. The matching process uses the nearest neighbor rule: first, the bounding box coordinate range of each component is read from the component code list; then, it is determined whether the mapped coordinates fall within the bounding box range. If multiple bounding boxes are included, the distance from the mapped coordinates to the center point of each bounding box is calculated, and the smallest distance is selected as the matching result. For example, if a boundary point has a horizontal coordinate of 1250 mm, a vertical coordinate of 480 mm, and a height of 260 mm, it falls within the range of component code segment A and overlaps with the adjacent segment B. The distance to the center points of the two segments is compared, and segment A with the smaller distance is selected. Finally, the mapping relationship and coding information are aggregated into a region coordinate pairing information set. Each record contains a connected component number, boundary point sequence mapping coordinates, matched component code, and scaling factor identifier, for subsequent classification and labeling overlay.

[0067] S103: Based on the information set paired with the regional coordinates, call the abnormal boundary and protection status fields to classify, construct a classification mark layer, and overlay the classification area and code according to the layer coordinates to obtain the protection missing mark map in front of the node;

[0068] After retrieving the connected component number, boundary mapping coordinates, and matching code from the regional coordinate pairing information set, the abnormal boundary field and protection status field are first called to perform classification. The protection status field is taken from the field records before the conversion node, and the field value is discretized into three categories: missing, weak, and contamination residue. The criteria for missing are that the membrane thickness data is not greater than 10 micrometers, the criteria for weak are that the membrane thickness data is greater than 10 micrometers and not greater than 22 micrometers, and the criteria for contamination residue are that the membrane thickness data is greater than 22 micrometers and the comprehensive color offset value is not less than 3.5. This classification does not use any external method name, but directly compares each item according to the threshold conditions and writes the category label. Subsequently, when constructing the classification label layer, a raster plane of the same size as the structural segment is created according to the resolution of the structural layer, and the boundary mapping coordinates of each connected component are converted into raster values. The system indexes the grid and applies fill markings to the regions within the boundaries. The fill marking values ​​use category codes: 1 for missing categories, 2 for weak categories, and 3 for contamination / residue categories. Next, the classification regions and codes are overlaid based on layer coordinates. Matched component codes are written to the encoding channel of the same grid. If multiple records appear in the same grid, the one with the larger category code is retained, and the number of conflicts is recorded in the conflict list. For example, if region index 004 is determined to be a weak category, the category code is written as 2, and the corresponding component code is written, forming a dual-channel marking system of category and encoding channels. Finally, a node-front protection missing marker map is output. When the marker map is exported as an image, the pixel-to-structure coordinate mapping index table is retained, and the connected component numbers and component codes are written to the metadata as the location basis for subsequent texture and foreign object feature extraction.

[0069] Please see Figure 3 The specific steps of S2 are as follows:

[0070] S201: Based on the classified regions in the pre-node protection missing marker image, extract the image texture distribution, boundary contour parameters and residual foreign object features, call the grayscale information in the texture distribution, the continuity parameters in the boundary contour and the color channel data in the foreign object features, perform feature filtering and normalization processing, and generate regional surface structure feature groups.

[0071] After reading the classified regions one by one from the pre-node protection missing marker image, the original image is first cropped according to the region boundary box and then illumination homogenization is performed. Illumination homogenization uses grayscale histogram stretching, mapping the minimum grayscale value of the cropped image to 10 and the maximum grayscale value to 245, and then stretching the intermediate grayscale values ​​proportionally. Subsequently, when extracting the image texture distribution, the cropped image is grayscaled and grayscale co-occurrence statistics are calculated at a fixed step size. The statistics are calculated separately for directions of 0 degrees, 45 degrees, 90 degrees, and 135 degrees, and then the four directions are... Contrast, homogeneity, and entropy are combined into a texture distribution record; when extracting boundary contour parameters, edge detection is first performed on the classification region mask to obtain the boundary pixel chain, and then the boundary continuity parameter is calculated. The continuity parameter is characterized by the number of breakpoints in the boundary pixel chain and the average rate of change of curvature. The number of breakpoints is obtained by counting the number of times the distance between adjacent boundary pixels is greater than 2 pixels, and the average rate of change of curvature is obtained by averaging the absolute values ​​of the angle changes of three consecutive points; when extracting residual foreign object features, they are first processed according to color channel differences in the cropped image. Candidate foreign object segmentation is performed, marking pixels with a difference greater than 18 between the red and blue channels as candidates. Connected component merging is then performed on the candidate regions, recording the area, aspect ratio, and average color channel value of each connected component. Subsequently, grayscale information from the texture distribution, continuity parameters from the boundary contour, and color channel data from the foreign object features are used to perform feature filtering and normalization. The filtering rule is to remove redundant items strongly correlated with the region area, retaining only six items: contrast, entropy, number of breakpoints, average curvature change rate, number of connected components in the foreign object, and average color difference of the foreign object. Each item is normalized to the range of 0 to 1 according to the minimum and maximum range of the batch of regions. For example, if a region has a contrast of 12.4, an entropy of 5.1, 8 breakpoints, and 3 connected components in the foreign object, and the contrast range of the same batch of regions is 6.0 to 15.0, the contrast normalization result is taken as the relative position of this value within the range. The same applies to other items. Finally, a region surface structure feature group is generated, with each record bound to a region index, component code, and six normalized feature values, serving as input for subsequent level adaptation calculations.

[0072] S202: Call the regional surface structure feature group, calculate the regional adaptation value under the level field according to the adhesion performance level field, surface treatment level field and pollution tolerance standard field in the anti-rust coating task sheet, and filter the adaptation index based on the matching result of the adaptation value and the pollution standard to obtain the regional level adaptation index set.

[0073] After reading the surface structure feature group of the area, the adhesion performance level, surface treatment level, and contamination tolerance standard fields in the anti-rust coating task sheet are called to perform adaptation value calculation. First, the level fields are quantified into level baseline scores. The adhesion performance level is mapped from high to low as 100, 80, 60, and 40. The surface treatment level is mapped from strict to lenient cleanliness as 100, 85, 70, and 55. The contamination tolerance standard is mapped from low to high allowable residue as 100, 75, 50, and 25. Then, the adaptation value under the level field is calculated for each area. The score is derived from three combined parts: the first part is the surface uniformity score, calculated by averaging and inverting the normalized values ​​of texture contrast and entropy; the second part is the boundary perturbation score, calculated by averaging the normalized values ​​of the number of boundary breakpoints and the normalized value of the average rate of change of curvature; and the third part is the foreign object residue score, calculated by averaging the normalized values ​​of the number of connected domains of foreign objects and the normalized value of the average color difference of foreign objects. The surface uniformity score, boundary perturbation score, and foreign object residue score are then combined with a weight of 0.4, 0.3, and 0.3 respectively to form the structural score. The weighting is based on verification data from completed samples. Comparative verification was conducted using different weight combinations. When the weight combinations for surface uniformity, boundary disturbance, and foreign matter residue were 0.4, 0.3, and 0.3, the structural score showed high consistency with the actual rework judgment. Consistency decreased when the weight of surface uniformity was reduced; therefore, a fixed weight of 0.4, 0.3, and 0.3 was adopted. Subsequently, the structural score was multiplied by the baseline score and proportionally adjusted according to the contamination tolerance standard score to obtain the appropriate value. For example, if the task sheet specifies an adhesion performance baseline score of 80, a surface treatment baseline score of 85, and a contamination tolerance standard score of 7... 5. A certain area has a structural score of 0.62. Next, based on the matching results of the adaptation value and the pollution standard, adaptation indicators are screened. The matching result is obtained by comparing the foreign matter residue score with the pollution tolerance standard score. If the residue amount conversion value corresponding to the foreign matter residue score does not exceed the allowable value of the pollution tolerance standard, the match is passed; otherwise, the match is not passed. The residue amount conversion is to divide the total area of ​​the foreign matter connected domain by the area of ​​the area and then convert it into the residue coverage rate per square meter. Finally, the area level adaptation indicator set is output. The indicator set records the area index, adaptation value, matching pass flag and the corresponding level field value.

[0074] S203: Based on the regional level adaptation index set, establish a mapping relationship between the index results and the corresponding regional index in the marker map, call the task sheet level field to classify the region, and write the classification and level benchmark data into the status mapping table to generate a coverage status adaptation relationship table.

[0075] Based on the regional level adaptation index set, a mapping relationship is first established between the index results and the corresponding regional indices in the labeling map. The mapping relationship table uses the regional index as the key, and the adaptation value, matching pass label, and component code are written to the same row. Then, the task sheet level field is called to classify the regions. The classification rules are executed according to the adaptation value range: an adaptation value of not less than 35 is marked as Level 1 adaptation, an adaptation value of not less than 25 and less than 35 is marked as Level 2 adaptation, an adaptation value of not less than 15 and less than 25 is marked as Level 3 adaptation, and an adaptation value less than 15 is marked as Level 4 adaptation. At the same time, if the matching passes, it is marked as failing, and a contamination failure label is added to the classification result. The interval boundary is determined by sample experiments. The lowest adaptation value of 35 is selected from 40 samples that achieve a pass rate of 0.95 in the subsequent adhesion verification, and the pass rate is in the range of 0.80 to 0.95. The adaptation value range is 25 to 35, and the adaptation value range for the pass rate in the range of 0.60 to 0.80 is 15 to 25. Therefore, the fixed interval thresholds are 35, 25, and 15. Then, the classification and grade benchmark data are written into the status mapping table. The fields of the status mapping table are written according to the area index, component code, first- to fourth-level adaptation labels, adhesion performance grade benchmark score, surface treatment grade benchmark score, pollution tolerance standard score, and matching pass mark. A timestamp and batch number are added to each record. For example, if the adaptation value of area index 002 is 31.6 and the match is passed, then the classification is second-level adaptation, and the grade benchmark score is written as 80, 85, and 75 according to the task order. Finally, a coverage status adaptation relationship table is generated. Each record in the table corresponds one-to-one with the area index, which can be directly retrieved and called for subsequent threshold determination and consistency summary.

[0076] Please see Figure 4 The specific steps of S3 are as follows:

[0077] S301: Based on the area parameters in the coverage status adaptation relationship table, call the area adhesion value and the preset adhesion acceptance threshold to perform threshold judgment, write the judgment result into the area status field, and index and encode the area status field to generate an adhesion judgment identifier set.

[0078] Table 2 Acceptance Threshold Setting and Verification Data Table

[0079]

[0080] Table 2 lists the distribution of the verification data on which the threshold setting is based. The relationship between the percentage of detached area, the quantified value of dust level, and the boundary of the marker will be directly used in subsequent paragraphs for threshold value selection and judgment logic.

[0081] After reading the area parameters from the coverage status adaptation table, the area adhesion value and the preset adhesion acceptance threshold are used to perform threshold judgment. The area adhesion value comes from the on-site verification record and is quantified by the percentage of the peeled area after grid crossing and tape removal. The quantification process involves selecting 3 measurement points in each area, drawing a grid of the same size at each measurement point and pasting tape of the same specification. After peeling, the percentage of peeled pixel area is averaged to obtain the area peeled area percentage. Then, the peeled area percentage is converted into an adhesion value grade score. A peeled area percentage of no more than 5 corresponds to a grade score of 100, a peeled area percentage of more than 5 and no more than 10 corresponds to a grade score of 70, and a peeled area percentage of more than 10 corresponds to a grade score of 40. The adhesion acceptance threshold is set based on the data in Table 2. The upper limit of the percentage of detached area for the sample is set to 5. In Table 2, the maximum percentage of detached area for the sample is 4. Therefore, the threshold is set to 5. When judging each region, the percentage of detached area in the region is compared with the threshold of 5. If it is not greater than 5, the region is judged as passed and the region status field is written as passed; otherwise, it is written as failed. For example, the percentages of detached area at 3 measuring points in a certain region are 2, 4 and 6 respectively. The average is 4. This result is substituted into the judgment logic to get passed and written. Then, the region status field is indexed and encoded. The encoding rule is to write status code 1 for passing and status code 0 for failing. At the same time, the region index and status code are combined to form an adhesion judgment identifier set. The identifier set is grouped and stored by component code and batch number is appended for subsequent roughness and cleanliness judgment combination calls.

[0082] S302: Call the adhesion judgment label set, and perform threshold judgment with the preset roughness acceptance threshold and the preset cleanliness acceptance threshold according to the area roughness value and the pollution residue value in the coverage status adaptation relationship table. Logically summarize the judgment combination results and write them into the area status label field to obtain the area acceptance status label set.

[0083] After calling the adhesion judgment mark set, the area roughness value and contamination residue value are read from the coverage state adaptation table. The area roughness value is obtained through the contour pin measurement point. Five measurement lines are taken for each area and the average is calculated. The contamination residue value is obtained by jointly quantifying the dust level and the water-soluble salt residue. The dust level is obtained by sampling with pressure-sensitive tape and comparing it with the standard chart to obtain levels 1 to 5 and writing the values ​​into numbers. The water-soluble salt residue is obtained by converting the conductivity after wiping the sample to milligrams per square meter. Then, threshold judgment is performed against the preset roughness acceptance threshold and the preset cleanliness acceptance threshold. The roughness threshold is set based on the allowable anchor pattern range of the coating process card. The roughness of the verified samples is concentrated between 45 and 75 micrometers, and the minimum roughness of the verified samples in Table 2 is 55. Therefore, the lower limit threshold for roughness is set to 45 and the upper limit threshold is set to 75. The cleanliness threshold is set based on dust level not greater than 2 and water-soluble salt residue not greater than 25 milligrams per square meter. The composition per square meter is based on the following criteria: the maximum quantified dust level value for the passed samples is 2, and the maximum water-soluble salt residue value for the passed samples is 22. To cover fluctuations in the field, the salt residue threshold is set to 25. Subsequently, a combined judgment is performed on each area, and a logical summary is written into the area status label field. The logical summary rule is that if the adhesion passes, the roughness falls between 45 and 75, the dust level is not greater than 2, and the salt residue is not greater than 25, a "full pass" label is written. For other cases, the corresponding label is written according to the failure item. The labels use fixed Chinese terms: adhesion failure, roughness failure, dust failure, and salt residue failure. If multiple failures occur simultaneously, they are written in order. For example, if an area has passed adhesion, a roughness of 38 micrometers, a dust level of 1, and a salt residue of 18, then "roughness failure" is written. Finally, the area acceptance status label set is obtained, and the labels and area index are written together as input for the part aggregation calculation.

[0084] S303: Based on the regional acceptance status label set, retrieve the code of the part to which the region belongs and perform part aggregation, calculate the pass label ratio value corresponding to the part, and write the part code, regional status label and ratio value into the consistency summary table to generate the measure switching consistency judgment result.

[0085] Based on the regional acceptance status label set, first retrieve the part code to which each region belongs and perform part aggregation. The part codes come from the matching results of the aforementioned regional coordinate pairing information set. During aggregation, the regional indexes are merged into the same set according to the part codes. Then, calculate the pass label ratio corresponding to the part. The pass label ratio is calculated by taking the ratio of the number of regions marked with the "all pass" label in the part set to the total number of regions in the part set, and converting this ratio into a percentage. For example, if a part code contains 12 regions, of which 9 regions are marked with the "all pass" label, then the pass label ratio is 75%. Finally, write the part code, regional status label, and ratio value into the consistency database. The summary table, with the location code as the primary key, records the pass rate of the annotations and the label count for each area under that location. The count field records the number of all passes, the number of failures in adhesion, roughness, dust, and salt residue. Finally, the consistency judgment result for the measure switching is generated. The judgment rule outputs the consistency level according to the pass rate range: a pass rate of not less than 90% outputs high consistency, a pass rate of not less than 70% and less than 90% outputs medium consistency, and a pass rate of less than 70% outputs low consistency. The consistency level is written to the result record for direct retrieval in subsequent access and blocking processes.

[0086] Please see Figure 5 The specific steps of S4 are as follows:

[0087] S401: Invoke the part identifier code and adaptation status in the consistency judgment result of the switching measures, retrieve the items marked as passed in the adaptation status field, bind the part identifier code corresponding to the passed item with the node control instruction parameter set, and write the binding result into the admission field to generate an identifier code sequence and generate an admission identifier set.

[0088] After reading the part identification code and adaptation status from the consistency judgment result of the measure switching, the items marked as passed in the adaptation status field are retrieved. The adaptation status field uses a consistency level of high or medium consistency and no adhesion failure labels in the part as the passing condition. During the filtering, the consistency level and label count are compared one by one, and a list of passed items is output. Then, the part identification code corresponding to the passed item is bound to the node control instruction parameter set. The node control instruction parameter set consists of node number, switching permission flag, switching time window start point, switching time window end point, and review batch number. During binding, the part identification code is matched to the corresponding part identification code. The node number is assigned and the switch permission is marked as allowed. Simultaneously, the time window is set to a 30-minute range from the current timestamp. Next, the binding result is written to the admission field to generate an identifier code sequence. This sequence is generated by sorting the part identifier codes in ascending order and appending the batch number suffix. The sort number is then written to the sequence position field. For example, if both part identifier codes 1203 and 1208 pass, the sequence is written with 1203 first and 1208 last. Finally, an admission identifier set is generated. Each record in the set contains the part identifier code, node number, and switch time window field for subsequent state mapping conversion and record table writing.

[0089] S402: Based on the access identifier set, retrieve the entries marked as failed in the adaptation status field, extract the identifier code of the corresponding part of the failed entry and write it synchronously with the entry parameter set of the repair process queue, and establish a process status field and a blocking condition field for the written entries. Complete the entry locking based on the blocking condition field and obtain the process blocking identifier set.

[0090] Based on the failed entries outside the admission identifier set, entries marked as failed in the adaptation status field are retrieved. Failed entries include parts with low consistency or any failed tag. Then, the corresponding part identifier code of the failed entry is extracted and synchronously written to the repair process queue entry parameter set. The entry parameter set includes queue number, process type, review requirements, and write-back node number. During writing, queue entries are created according to the part identifier code, and the failed tags are mapped to process types: adhesion failure is mapped to coating rework, roughness failure to surface reprocessing, and dust and salt residue failures to cleaning and rewashing. Next, a process status field and a blocking condition field are established for the written entries. The process status field is set to pending processing, in progress, or completed. One of the three states is initialized as pending. The blocking condition field is written with the blocking level according to the number and severity of the failed items. The severity rule is that adhesion failure is recorded as level 3, roughness failure as level 2, and dust failure and salt residue failure as level 1. If multiple items appear in the same location, the highest level is taken as the blocking level. Then, the item is locked according to the blocking condition field. The locking rule is that when the blocking level is not less than 2, a locking mark is written and entry into the node switching allowed list is prohibited. When the blocking level is 1, a time-limited review mark is written and a review deadline timestamp is generated for 60 minutes from the current time. Finally, the process blocking identifier set is obtained. The identifier set records the location identifier code, blocking level, locking mark and queue number, which are used as input for the node console state mapping conversion.

[0091] S403: Based on the process blocking identifier set, call the status identifier field in the node console, perform status mapping conversion for the admission field and the blocking field, write the admission identifier and the blocking identifier into the node switching record table, and perform status summary encoding on the node switching record table to generate the node switching process feedback status.

[0092] Based on the process blocking identifier set, the status identifier field in the node console is called. A status mapping conversion is performed on the admission and blocking fields. The status mapping uses dual-channel writing: the admission identifier is written to the switch-allowed state, and the blocking identifier is written to the switch-prohibited state. If both admission and blocking exist for the same node, blocking takes priority and a conflict flag of 1 is written. Subsequently, the admission and blocking identifiers are written to the node switching record table. The record table fields include node number, part identifier code, mapped status, write timestamp, and batch number. During writing, data is aggregated by node number and sorted by part identifier code within the same node. Then, the node switching record table is processed... The status summary code is generated according to the following rules: the number of allowed switches and the number of prohibited switches within the same node are counted separately. If the number of prohibited switches is 0, the summary code is written as 100. If the number of prohibited switches is not 0 and the proportion is not greater than 20, the summary code is written as 70. If the proportion of prohibited switches is greater than 20, the summary code is written as 40. For example, if a node contains 10 parts, of which 2 are prohibited switches, the proportion is 20, and the summary code is written as 70. Finally, the node switching process feedback status is generated. The feedback status records the node number, summary code, allowed number, prohibited number, and conflict identifier, which are used for subsequent node structure index entry set generation and archiving registration.

[0093] Table 3 Comparison of Key Fields in Full-Cycle Node Records

[0094]

[0095] Table 3 shows the correspondence between node summary codes and archive writing time. Subsequent paragraphs will bind the node summary codes and locations to the structural coding dimension through prior results such as proportions, forming a traceable full-cycle node record entry.

[0096] Please see Figure 6 The specific steps of S5 are as follows:

[0097] S501: Call the process identifier, area information and structure code in the consistency judgment result of the node switching process feedback status and measure switching, extract the node number corresponding to the structure segment, match the node number with the structure code, and combine and aggregate the process identifier and area information to generate a node structure index entry set.

[0098] After reading the process identifier, area information, and structure code from the consistency judgment result of the node switching process feedback status and measure switching, the node number corresponding to the structure segment is extracted first. The node number is retrieved from the mapping table of the structure code in the structure list. During the retrieval, the node number list is read by using the structure code as the key, and the node number is matched and verified with the structure code. The verification rule is that there is a write record with the same node number in the node switching record table and the batch number is consistent. Then, the process identifier and area information are combined and aggregated. The combined aggregation is grouped by node number. The consistency level, pass label ratio value, area label count, and node summary code of all parts under the node are written into the same aggregation row, and the aggregation row is bound to the structure code. For example, if node 01 in Table 3 matches the structure code G01, the node summary code 70, the set of part pass label ratio values, and the prohibition quantity 2 are written into the same aggregation row. Then, a node structure index entry set is generated. The entry set fields include node number, structure code, part identifier code list, pass label ratio value list, node summary code, and process identifier. The list fields are expanded and stored in the order of part identifier code, and an index number is written for subsequent sorting and alignment.

[0099] S502: Based on the node structure index entry set, extract the node status data corresponding to each structural segment, sort the status data by node number, and perform field alignment operation with the process identifier field. At the same time, construct a mapping relationship table between area fields and status values, aggregate all fields and write them into the form data structure to obtain the protection status registration field set.

[0100] Based on the node structure index entry set, node status data corresponding to each structural segment is extracted. The node status data comes from the node switching record table, containing the mapped status and write timestamp for each part. After sorting the status data by node number, a field alignment operation is performed with the process identifier field. The alignment operation uses a double-key matching of node number and batch number. Upon successful matching, the process identifier is written to the process identifier column of the status data row. Simultaneously, a mapping relationship table between region fields and status values ​​is constructed. This mapping relationship table uses the region index as the key, writing the region acceptance status label, part identifier code, node number, and mapped status to the same row. The structure code field of the row is written as the corresponding structure code in the index entry set; then all fields are aggregated and written into the form data structure. The form data structure is organized into pages according to the structure code. Each page lists the part identifier code, switching status, pass label ratio value, fail label count and node summary code in segments according to node number; for example, if structure code G02 corresponds to node 02, the number of switches prohibited is 0 and the summary code is 100, then the page is written with the switching status as allowed and a list of pass label ratio values ​​is attached; finally, the protection status registration field set is obtained. The field set is output with the structure code as the index for the archiving registration module to write.

[0101] S503: Based on the protection status registration field set, write the structural segment status data into the archive registration module, establish a timestamp index for the written records, and generate an index record field with the node number as the primary key. Incorporate all status registration data into the archive entry structure to generate full-cycle node record entries.

[0102] Based on the protection status registration field set, the structural segment status data is written to the archiving registration module. During writing, an archiving entry header is created according to the structural code, and then the corresponding node number segment data is appended to the entry body line by line. A timestamp index is established for the written record, which takes the millisecond-level timestamp of the writing completion time, and the batch number, structural code, and node number are written together into the index key. Subsequently, an index record field is generated using the node number as the primary key. The index record field contains the summary code, allowed quantity, prohibited quantity, conflict identifier, and archiving writing time in seconds for that node. The archiving writing time is obtained by subtracting the writing start timestamp and the writing completion timestamp. For example, in Table 3, the archiving writing time for node 03 is 5.0 seconds, and the summary code is 40, so the corresponding value is written into the index record field. Finally, all status registration data is incorporated into the archiving entry structure. The archiving entry structure is divided into volumes by batch number and sorted by structural code to generate full-cycle node record entries. The entries can be retrieved by structural code to find the node summary code and the location through the annotation ratio value and other prior results, and maintain consistency with the mapping link of the area acceptance status label.

[0103] Please see Figure 7 A rust-proof and corrosion-resistant ultra-high strength square tube full life-cycle rust prevention and control system, including:

[0104] The missing marker generation module is used to perform S1: to obtain the images and thickness information collected by the surface condition detection device at the rust prevention measure conversion node during the storage and transportation of ultra-high strength square tubes, extract the regional boundaries including color difference, broken coating and abnormal film thickness, match the region with the coordinates of the structural layer, associate the code of the protective component, complete the regional classification and generate the protective missing marker map before the node;

[0105] The adaptation relationship construction module is used to execute S2: Based on the classified areas in the pre-node protection missing marker map, extract the image texture distribution, boundary morphology and residual foreign matter characteristics of the areas, call the adhesion performance level, surface treatment level and pollution tolerance standard set in the anti-rust coating task sheet, establish the corresponding area adaptation level, and generate the coverage status adaptation relationship table.

[0106] The consistency judgment module is used to execute S3: based on the area parameters in the coverage status adaptation relationship table, it calls the preset adhesion acceptance threshold, preset roughness acceptance threshold and preset cleanliness acceptance threshold, performs a judgment of greater than or equal to the adhesion value, performs a judgment of less than or equal to the roughness value and the amount of contamination residue, marks the area as passed or failed according to the judgment results, summarizes them to the corresponding parts, and generates the measure switching consistency judgment result.

[0107] The node switching feedback module is used to execute S4: call the part identification code and adaptation status in the consistency judgment result of the measure switching, bind the items marked as passed with the control command to generate the admission identifier, synchronize the items marked as failed to pass to the repair process queue and generate the process blocking identifier, and at the same time perform the status identifier conversion in the node console to generate the node switching process feedback status.

[0108] The full-cycle record archiving module is used to execute S5: call the process identifier, area information and structure code in the status and measure switching consistency judgment results of the node switching process, establish data index entries according to the node number of the ultra-high strength square tube, include the status information of all structural sections into the protection status record form set for archiving and registration, and generate full-cycle node record entries.

[0109] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for rust prevention and control throughout the entire life cycle of rust-resistant and corrosion-resistant ultra-high strength square tubes, characterized in that: Includes the following steps: S1: Obtain square tube image and thickness information, extract color difference, coating breakage and abnormal film thickness boundaries, pair the abnormal boundaries with structural coordinates, associate component codes and classify the abnormal boundaries, and generate a node front protection missing marker map; S2: Extract texture, morphology and foreign object features based on the node front protection missing marker map, obtain the adhesion, surface and contamination standards, combine the texture, morphology, foreign object features, adhesion standards, surface standards and contamination standards to classify and generate a coverage status adaptation relationship table; S3: Determine the detection area based on the coverage state adaptation relationship table, collect the adhesion, roughness and residue corresponding to the detection area, obtain the adhesion, roughness and cleanliness thresholds, determine that the adhesion is greater than or equal to the adhesion threshold, determine that the roughness and the residue are less than or equal to the roughness threshold and the cleanliness threshold, and generate a measure switching consistency determination result. S4: Extract the identifier and status from the consistency judgment result of the measure switching, bind the access identifier generated by the item and instruction, synchronize the failed item to the repair queue to generate the blocking identifier, change the status identifier, and generate the node switching process feedback status. S5: Invoke the process identifier, area information, and structure code in the consistency judgment result between the node switching process feedback status and the measure switching, establish a data index entry, archive the structure status information corresponding to the structure code, and generate a node record entry.

2. The method for full life-cycle rust prevention and control of rust-resistant and corrosion-resistant ultra-high strength square tubes according to claim 1, characterized in that, The protective defect marking map includes color difference areas, coating break areas, and abnormal film thickness areas; the coverage status adaptation table includes image texture distribution, boundary morphology features, and residual foreign matter features; the measure switching consistency judgment result includes adhesion judgment result, roughness judgment result, and pollution residue amount judgment result; the node switching process feedback status includes access identifier, process blocking identifier, and status identifier conversion record; the full-cycle node record entries include process identifier, area information, and structure code.

3. The method for full life-cycle rust prevention and control of rust-resistant and corrosion-resistant ultra-high strength square tubes according to claim 1, characterized in that, The process of obtaining adhesion, roughness and residue is as follows: obtaining the adhesion data obtained by pull-off test, wherein the adhesion threshold is limited to the lower limit of a continuous range not less than a preset standard value; The roughness is quantified using a surface profile scanning method, and the roughness threshold is no greater than the upper limit of the corresponding coverage state record value in the coverage state adaptation relationship table.

4. The method for full life-cycle rust prevention and control of rust-resistant and corrosion-resistant ultra-high strength square tubes according to claim 1, characterized in that: The residual amount is quantified using an image grayscale residual mapping method, and the cleanliness threshold is no greater than the maximum allowable value of the corresponding level of the pollution standard. When the adhesion is not less than the adhesion threshold, and the roughness and the residual amount are both not greater than the roughness threshold and the cleanliness threshold, the corresponding item in the consistency judgment result of the measure switching is marked as passed; otherwise, it is marked as failed.

5. The method for full life-cycle rust prevention and control of rust-resistant and corrosion-resistant ultra-high strength square tubes according to claim 1, characterized in that, The specific steps of S1 are as follows: S101: Obtain image data and thickness information collected by the surface condition detection device at the rust prevention measure conversion node during the storage and transportation stage, extract color parameters from the image and establish a color difference feature group, call the film thickness data at the corresponding position in the thickness information, perform position alignment comparison analysis on the color difference feature group and film thickness data, and filter abnormal boundary positions based on the color difference threshold and film thickness threshold to generate an abnormal area boundary index set. S102: Based on the abnormal region boundary index set, extract the corresponding spatial mapping points in the preset structural layer coordinate matrix, call the preset layer reference coordinate values ​​to calculate the mapping relationship, extract the protective component code and match it with the mapping point position, aggregate the mapping relationship and code information, and generate a region coordinate pairing information set; S103: Based on the area coordinate pairing information set, call the abnormal boundary and protection status fields for classification, construct a classification mark layer, and superimpose the classification area and code according to the layer coordinates to obtain the node front protection missing mark map.

6. The method for full life-cycle rust prevention and control of rust-resistant and corrosion-resistant ultra-high strength square tubes according to claim 1, characterized in that, The specific steps of S2 are as follows: S201: Based on the classified areas in the pre-node protection missing marker image, extract the image texture distribution, boundary contour parameters and residual foreign object features, call the grayscale information in the texture distribution, the continuity parameters in the boundary contour and the color channel data in the foreign object features, perform feature filtering and normalization processing, and generate a regional surface structure feature group. The normalization process includes: using the minimum and maximum values ​​of corresponding features in the same batch region as normalization parameters, performing linear mapping on the feature values ​​so that the normalized feature values ​​fall into the 0-1 range. S202: Call the surface structure feature group of the region, read the anti-rust coating task sheet corresponding to the region, calculate the adaptation value of the region under the level field according to the adhesion performance level field, surface treatment level field and pollution tolerance standard field in the anti-rust coating task sheet, and filter the adaptation index based on the matching result of the adaptation value and the pollution standard to obtain the region level adaptation index set. S203: Based on the set of regional level adaptation indicators, establish a mapping relationship between the indicator results and the corresponding regional index in the marker map, call the level field of the anti-rust coating task sheet to classify the region, and write the classification and level benchmark data into the status mapping table to generate a coverage status adaptation relationship table.

7. The method for full life-cycle rust prevention and control of rust-resistant and corrosion-resistant ultra-high strength square tubes according to claim 1, characterized in that, The specific steps for S3 are as follows: S301: Based on the area parameters in the coverage state adaptation relationship table, call the area adhesion value and the preset adhesion acceptance threshold to perform threshold determination, write the determination result into the area status field, and index and encode the area status field to generate an adhesion determination identifier set. S302: Call the adhesion determination identifier set, and according to the area roughness value and pollution residue value in the coverage status adaptation relationship table, perform threshold determination with the preset roughness acceptance threshold and the preset cleanliness acceptance threshold respectively. Perform AND logic combination determination on the determination combination result and write it into the area status label field. When the adhesion determination passes, the roughness determination passes, and the cleanliness determination passes, write the pass label; otherwise, write the fail label and obtain the area acceptance status label set. S303: Based on the set of regional acceptance status labels, retrieve the code of the part to which the region belongs and perform part aggregation, calculate the pass label ratio value corresponding to the part, and write the part code, regional status label and ratio value into the consistency summary table to generate the measure switching consistency judgment result.

8. The rust prevention and control method for ultra-high strength square tubes with rust and corrosion resistance throughout their entire life cycle, as described in claim 1, wherein the specific steps of S4 are as follows: S401: Invoke the measures to switch the part identification code and adaptation status in the consistency judgment result, retrieve the items marked as passed in the adaptation status field, bind the part identification code corresponding to the passed item with the node control instruction parameter set, and write the binding result into the admission field to generate an identification code sequence and generate an admission identification set. S402: Based on the access identifier set, retrieve the entries marked as failed in the adaptation status field, extract the identifier code of the corresponding part of the failed entry and synchronously write it with the preset repair process queue entry parameter set, and establish a process status field and a blocking condition field for the written entry, complete the entry locking according to the blocking condition field, and obtain the process blocking identifier set. S403: Based on the process blocking identifier set, call the preset status identifier field in the node console, perform status mapping conversion for the admission field and the blocking field, write the admission identifier and the blocking identifier into the node switching record table, and perform status summary encoding on the node switching record table to generate the node switching process feedback status.

9. The method for full life-cycle rust prevention and control of rust-resistant and corrosion-resistant ultra-high strength square tubes according to claim 1, characterized in that, The specific steps of S5 are as follows: S501: Call the process identifier, area information and structure code in the consistency judgment result of the node switching process feedback status and the measure switching, extract the node number corresponding to the structure segment, match the node number with the structure code, and combine and aggregate the process identifier and area information to generate a node structure index entry set. S502: Based on the node structure index entry set, extract the node status data corresponding to each structure segment, sort the status data by node number, match and associate the node number with the batch number, and write the process identifier field into the corresponding status data record. At the same time, construct a mapping relationship table between area fields and status values, aggregate all fields and write them into the form data structure to obtain the protection status registration field set. S503: Based on the protection status registration field set, write the structural segment status data into the archive registration module, establish a timestamp index for the written records, generate an index record field with the node number as the primary key, incorporate all status registration data into the archive entry structure, and generate a full-cycle node record entry.

10. A rust-proof and corrosion-resistant ultra-high strength square tube full life-cycle rust prevention and control system, characterized in that: The system is used to implement the rust prevention and control method for the entire life cycle of rust-resistant and corrosion-resistant ultra-high strength square tubes as described in any one of claims 1-9. The system includes: The missing marker generation module is used to perform S1: to obtain the images and thickness information collected by the surface condition detection device at the rust prevention measure conversion node during the storage and transportation of ultra-high strength square tubes, extract the regional boundaries including color difference, broken coating and abnormal film thickness, match the region with the coordinates of the structural layer, associate the code of the protective component, complete the regional classification and generate the protective missing marker map before the node; The adaptation relationship construction module is used to execute S2: Based on the classified areas in the node front protection missing mark map, extract the image texture distribution, boundary morphology and residual foreign matter characteristics of the areas, call the adhesion performance level, surface treatment level and pollution tolerance standard set in the anti-rust coating task sheet, establish the corresponding area adaptation level, and generate the coverage status adaptation relationship table. The consistency judgment module is used to execute S3: based on the area parameters in the coverage state adaptation relationship table, it calls the preset adhesion acceptance threshold, the preset roughness acceptance threshold and the preset cleanliness acceptance threshold, performs a judgment that the adhesion value is greater than or equal to the value, performs a judgment that the roughness value and the amount of pollution residue are less than or equal to the value, marks the area as passed or failed according to the judgment result, summarizes it to the corresponding part, and generates the measure switching consistency judgment result. The node switching feedback module is used to execute S4: call the part identification code and adaptation status in the consistency judgment result of the measure switching, bind the items marked as passed with the control command to generate the admission identifier, synchronize the items marked as failed to pass to the repair process queue and generate the process blocking identifier, and at the same time perform the status identifier conversion in the node console to generate the node switching process feedback status. The full-cycle record archiving module is used to execute S5: call the process identifier, area information and structure code in the node switching process feedback status and the consistency judgment result of the measure switching, establish data index entries according to the node number of the ultra-high strength square tube, include the status information of all structural sections into the protection status record form set for archiving and registration, and generate full-cycle node record entries.

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