Steel structure building sustainable maintenance method and system based on BIM

Abstract

The invention relates to the technical field of data processing, and discloses a BIM-based steel structure building sustainable maintenance method and system. The method comprises the steps of integrating a steel structure digital library through collected data, analyzing component information to obtain a health report, calculating resource consumption to obtain a maintenance strategy, setting repair parameters to form a construction guide, importing the guide into a terminal for field guide recording, and comparing data before and after maintenance to establish a case set. Scientific evaluation, precise maintenance and resource optimization utilization of the steel structure building are realized, so that the service life of the building is prolonged, and resource consumption and environmental influence are reduced.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a BIM-based sustainable maintenance method and system for steel structure buildings. Background Art

[0002] Steel structures are widely used in modern architecture due to their advantages, such as light weight, high strength, short construction period, and large spatial span. As buildings age, steel structural components face various aging and damage problems, such as corrosion, fatigue, deformation, and loose connections. These problems will affect the structural safety and performance of the building. Traditional steel structure maintenance methods mainly rely on manual inspections to detect problems, determine maintenance strategies based on experience, and use traditional processes for repairs. In recent years, with the development of Building Information Modeling (BIM) technology, digital and information-based methods have begun to be introduced into the field of steel structure maintenance. Some researchers have proposed BIM-based steel structure health monitoring methods, which collect structural operation data through sensor networks and combine them with BIM models for visualization. Other studies focus on the application of BIM in the management of the entire building life cycle, integrating maintenance information into BIM models to achieve information sharing and collaborative management.

[0003] However, existing technologies still have many shortcomings in the sustainable maintenance of steel structures. First, traditional steel structure maintenance mostly adopts a passive repair model, lacking scientific health assessment methods and preventive maintenance strategies, leading to problems such as untimely maintenance, excessive maintenance or insufficient maintenance. Second, the maintenance decision-making process lacks sustainability considerations and fails to comprehensively evaluate the resource consumption, environmental impact and economic benefits of maintenance plans, making it difficult to achieve sustainable management of the entire life cycle of steel structures. Third, existing BIM applications focus more on the design and construction stages, and there is less research on their application in the maintenance stage, especially the lack of effective methods for accurately connecting BIM with on-site maintenance and construction. Fourth, maintenance knowledge and experience lack systematic accumulation and intelligent application, resulting in the recurrence of similar problems and low maintenance efficiency. These problems seriously restrict the sustainable development of steel structure buildings and the efficient use of resources. Summary of the Invention

[0004] This application provides a BIM-based sustainable maintenance method and system for steel structure buildings, which is used to achieve scientific evaluation, precise maintenance and optimal resource utilization of steel structure buildings, thereby extending the service life of buildings and reducing resource consumption and environmental impact.

[0005] In the first aspect, the present application provides a BIM-based sustainable maintenance method for steel structure buildings, which includes: collecting steel structure geometric data and material parameters through laser scanning and sensor networks, integrating steel structure three-dimensional information, and obtaining a steel structure digital maintenance basic library; performing structural deformation and surface defect analysis based on component information and monitoring data in the steel structure digital maintenance basic library to obtain a steel structure health assessment report; performing maintenance plan resource consumption and environmental impact calculations on key component data in the steel structure health assessment report to obtain a steel structure sustainable maintenance strategy; performing component repair parameter setting and material configuration based on the steel structure sustainable maintenance strategy to obtain a steel structure maintenance construction guide; importing the steel structure maintenance construction guide into on-site terminal equipment for location guidance and operation identification to obtain a steel structure maintenance implementation record; performing before-and-after maintenance comparison and effect verification on the steel structure maintenance implementation record and the original status data to obtain a steel structure maintenance case data set.

[0006] In a second aspect, the present application provides a BIM-based sustainable maintenance system for steel structure buildings, the BIM-based sustainable maintenance system for steel structure buildings comprising: Integration module, used to collect steel structure geometry data and material parameters through laser scanning and sensor network, integrate steel structure 3D information, and obtain a digital maintenance base for steel structures; An analysis module is used to analyze structural deformation and surface defects based on component information and monitoring data in the steel structure digital maintenance basic library to obtain a steel structure health assessment report; A calculation module is used to calculate the resource consumption and environmental impact of the maintenance plan based on the key component data in the steel structure health assessment report to obtain a sustainable maintenance strategy for the steel structure; A configuration module is used to set component repair parameters and material configuration according to the sustainable maintenance strategy of the steel structure, and obtain a steel structure maintenance construction guide; An import module is used to import the steel structure maintenance construction guide into the on-site terminal device to perform location guidance and operation identification to obtain a steel structure maintenance implementation record; The verification module is used to compare the steel structure maintenance implementation records and original status data before and after maintenance and verify the effect to obtain a steel structure maintenance case data set.

[0007] A third aspect of the present invention provides a computer device comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory to enable the computer device to execute the above-mentioned BIM-based sustainable maintenance method for steel structure buildings.

[0008] A fourth aspect of the present invention provides a computer-readable storage medium having instructions stored therein, which, when executed on a computer, enables the computer to execute the above-mentioned BIM-based sustainable maintenance method for steel structure buildings.

[0009] In the technical solution provided by this application, steel structure information is collected through laser scanning and sensor networks, a digital maintenance basic library for steel structures is established, and accurate mapping of physical entities of steel structures to digital space is achieved, providing a comprehensive and accurate data basis for health assessment and maintenance decisions, and solving the problems of missing and inaccurate data in traditional maintenance; by analyzing structural deformation and surface defects of component information and monitoring data in the digital maintenance basic library, a health assessment report for steel structures is formed, which realizes scientific quantification and accurate grading of the health status of steel structures, and overcomes the subjectivity and uncertainty of traditional empirical judgments; the resource consumption and environmental impact of the maintenance plan are calculated based on the health assessment report data, and a sustainable maintenance strategy for steel structures is obtained, which integrates the concept of sustainable development into the maintenance decision-making process. The process balances structural safety, resource utilization efficiency and environmental protection requirements; based on the sustainable maintenance strategy, component repair parameter settings and material configuration are carried out, and a steel structure maintenance construction guide is formulated, which realizes the refinement and standardization of maintenance design and improves the efficiency and quality of maintenance design; the maintenance construction guide is imported into the on-site terminal equipment for position guidance and operation identification, forming a steel structure maintenance implementation record, and the design intent is accurately transmitted to the construction site through augmented reality technology, solving the problems of large construction deviation and difficult quality control in traditional maintenance; the maintenance implementation record and the original status data are compared before and after maintenance and the effect is verified, a steel structure maintenance case data set is established, and a maintenance knowledge accumulation and experience inheritance mechanism is constructed, which improves the intelligence level of maintenance decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0011] Figure 1 Schematic diagram of an embodiment of a BIM-based sustainable maintenance method for steel structure buildings in an embodiment of the present application; Figure 2 Schematic diagram of an embodiment of a BIM-based sustainable maintenance system for steel structure buildings in an embodiment of the present application; Figure 3 It is a schematic block diagram of the structure of a computer device in an embodiment of the present invention. DETAILED DESCRIPTION

[0012] The embodiments of the present application provide a BIM-based sustainable maintenance method and system for steel structure buildings. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or are inherent to these processes, methods, products or apparatus.

[0013] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 In one embodiment of the present application, a method for sustainable maintenance of a steel structure building based on BIM includes: Step S101: Collecting geometric data and material parameters of steel structures through laser scanning and sensor networks, integrating three-dimensional information of steel structures, and obtaining a digital maintenance basic library for steel structures; Step S102: Perform structural deformation and surface defect analysis based on component information and monitoring data in the steel structure digital maintenance basic library to obtain a steel structure health assessment report; Step S103: Calculate resource consumption and environmental impact of the maintenance plan using key component data in the steel structure health assessment report to obtain a sustainable maintenance strategy for the steel structure; Step S104: According to the sustainable maintenance strategy for steel structures, component repair parameters and material configuration are set to obtain a steel structure maintenance construction guide; Step S105: Import the steel structure maintenance construction guide into the on-site terminal device, perform position guidance and operation identification, and obtain the steel structure maintenance implementation record; Step S106: Perform a pre- and post-maintenance comparison and effect verification on the steel structure maintenance implementation records and original status data to obtain a steel structure maintenance case data set.

[0014] It is understandable that the execution subject of this application can be a BIM-based steel structure building sustainable maintenance system, or a terminal or server, which is not limited here. The embodiment of this application is described by taking the server as the execution subject as an example.

[0015] Specifically, drones equipped with lidar scans the building's exterior from multiple angles to capture its macroscopic geometry. Simultaneously, portable laser scanners perform high-precision, close-range scans of key nodes to capture connection details. These scanned data undergo point cloud processing to form a basic geometric model. Furthermore, information such as steel material, strength grade, and installation date is extracted from building archives to create a basic component information table. A sensor network, including strain sensors, inclination sensors, and displacement sensors, is deployed at key stress-bearing locations within the steel structure to record the structure's dynamic stress state in real time. This heterogeneous data is integrated and correlated to construct a digital maintenance database for steel structures. For example, laser scanning of the main steel beam of an office building generates 3D coordinate point cloud data. This data is combined with hourly dynamic deformation data recorded by strain sensors and Q345B steel parameter information extracted from archives to create a comprehensive digital representation of the beam, achieving a complete mapping of physical entities to digital information. The digital maintenance database for steel structures is then used to conduct health assessments. Time series analysis of sensor data is performed to identify structural deformation trends. For example, after filtering the noise from the displacement sensor data, the maximum displacement change of a node within 24 hours is calculated, and the measured data is compared with the design limit to obtain the deformation anomaly index. At the same time, the surface images captured by the high-definition camera are processed, and surface defects such as rust and cracks are identified through edge detection, and the proportion of the damaged area is calculated. For the surface image of a certain steel column, the pixel comparison algorithm is used to identify the surface rust area as 200 square centimeters, accounting for 15% of the total surface area of the component. Combined with the rust depth information, the surface damage level of the component is determined to be C. Through a comprehensive scoring method, the deformation anomaly index and the surface damage situation are weighted to calculate the component health score, which is divided into five levels from A to E. They are marked with different colors in the BIM model to generate a steel structure health assessment report.

[0016] A sustainable maintenance strategy is developed based on the health assessment report. Class D and Class E components requiring maintenance are screened from the assessment report to create a maintenance list. For the components on the list, applicable technologies are matched from the maintenance method database to generate a preliminary maintenance plan combination. The required steel material consumption, anti-corrosion coating usage, and construction hours for each plan are calculated to generate a resource consumption data table. The carbon footprint of the entire maintenance process is calculated based on the carbon emission coefficient of material production and construction energy consumption parameters to generate environmental impact assessment data. Resource consumption is also converted into economic costs based on market unit prices. Three possible maintenance options for a damaged steel beam are analyzed: Option 1 requires replacement of the entire component, Option 2 involves local reinforcement, and Option 3 involves surface treatment. Through a comprehensive calculation of resource consumption, environmental impact, and cost-effectiveness, Option 2 is determined to best meet sustainability requirements, resulting in a sustainable maintenance strategy for the steel structure. Detailed construction design is conducted based on the sustainable maintenance strategy. The geometric dimensions and damage characteristics of the component to be repaired are extracted to determine the coordinates of the repair area. The force distribution in this area is analyzed to identify weak points in the component and generate a force map. Based on the damage characteristics and load requirements, the appropriate steel type, welding material, and anti-corrosion coating were selected, and the precise material quantities were calculated. Mechanical calculations determined that a damaged steel beam connection required reinforcement with 8mm thick Q345B steel plates, a 300mm weld length, E4303 welding rods, and epoxy zinc-rich primer for anti-corrosion. These parameters were converted into specific construction parameters such as cutting dimensions, welding specifications, and coating thickness. Operational procedures and quality control points were then developed to form a guide for steel structure maintenance and construction.

[0017] Achieve precise on-site maintenance and construction. Maintenance and construction instructions are imported into devices such as AR glasses or tablets and converted into on-site positioning parameters. Technicians use the device to scan the QR code label on the steel structure to locate the component to be maintained. The system overlays the maintenance instructions on the actual component as a virtual image, noting the locations of required cut lines, welding locations, and coating areas. Construction workers follow the instructions, while the device records key quality parameters such as welding temperature, coating thickness, and bolt torque during the construction process. During the reinforcement of a steel beam joint, the system monitored the welding temperature in real time, maintaining it between 450°C and 550°C, and the coating thickness achieved the design requirement of 120 microns. The system automatically records and associates the location information to create a maintenance record for the steel structure. Sensors are used to re-monitor structural performance parameters after maintenance, extracting indicators such as deformation and vibration frequency, and comparing them with pre-maintenance data. Surface imaging is then performed to assess surface quality improvements. For one reinforced steel beam, the maximum displacement after maintenance was reduced by 65%, approaching the design state. Surface rust was completely removed, and the anti-corrosion coating was fully applied. Comparing actual maintenance resource consumption with the budget evaluates the efficiency of the plan. Integrate data on pre-maintenance conditions, adopted technologies, and maintenance effects to create a structured case record and form a steel structure maintenance case dataset.

[0018] In the embodiment of the present application, steel structure information is collected through laser scanning and sensor networks, and a digital maintenance basic library for steel structures is established to achieve accurate mapping of the physical entity of the steel structure to the digital space, providing a comprehensive and accurate data basis for health assessment and maintenance decision-making, and solving the problems of missing and inaccurate data in traditional maintenance; by performing structural deformation and surface defect analysis on the component information and monitoring data in the digital maintenance basic library, a steel structure health assessment report is formed, which achieves scientific quantification and accurate grading of the health status of the steel structure, overcoming the subjectivity and uncertainty of traditional empirical judgment; combining the health assessment report data to calculate the resource consumption and environmental impact of the maintenance plan, and obtaining a sustainable maintenance strategy for the steel structure, integrating the concept of sustainable development into the maintenance decision-making process. , balancing structural safety, resource utilization efficiency and environmental protection requirements; setting component repair parameters and material configuration based on sustainable maintenance strategies, formulating steel structure maintenance construction guidelines, realizing the refinement and standardization of maintenance design, and improving maintenance design efficiency and quality; importing maintenance construction guidelines into on-site terminal equipment for position guidance and operation identification, forming steel structure maintenance implementation records, and realizing the precise transmission of design intent to the construction site through augmented reality technology, solving the problems of large construction deviations and difficult quality control in traditional maintenance; comparing maintenance implementation records with original status data before and after maintenance and verifying the effects, establishing a steel structure maintenance case data set, building a maintenance knowledge accumulation and experience inheritance mechanism, and improving the intelligence level of maintenance decision-making.

[0019] In a specific embodiment, the process of executing step S101 may specifically include the following steps: (1) Use the laser radar carried by the drone to scan the external shape of the steel structure from multiple angles to obtain the geometric contour point cloud data of the steel structure; (2) Use a portable laser scanner to scan the steel structure connection nodes and key parts in detail to collect the detailed geometric feature data of the nodes; (3) Extract steel material specifications, strength grades, manufacturers and installation date information from steel structure building archives and establish a basic information table for steel components; (4) Arrange strain sensors, inclination sensors and displacement sensors at key stress points of the steel structure to record the dynamic stress state data of the steel structure; (5) Perform noise reduction on the point cloud data to remove abnormal points generated during the acquisition process and form a clean point cloud of the steel structure; (6) Fusing the node detail geometric feature data with the clean point cloud to generate complete steel structure geometric data; (7) Add material and history attributes to the complete steel structure geometry data based on the steel component basic information table to construct the steel structure parametric information; (8) Establish an associative mapping between the dynamic stress state data of the steel structure and the parameterized information of the steel structure to obtain the basic digital maintenance library of the steel structure.

[0020] Specifically, the exterior of the steel structure is scanned from multiple angles using a laser radar (LiDAR) mounted on a drone. LiDAR is an active remote sensing technology that acquires three-dimensional spatial information of a target object by emitting laser beams and receiving their reflected signals. The drone platform can scan from multiple angles, avoiding the limited viewing angles and occlusion issues associated with ground-based scanning. In actual operation, the drone flies along a pre-set route, and the LiDAR collects data at a rate of hundreds of thousands of points per second, recording the three-dimensional coordinates (x, y, z) and reflection intensity of each reflection point, forming a point cloud of the steel structure's geometric outline. This point cloud captures the macroscopic geometric features of the steel structure's exterior, including information about the main frame and surrounding protective structure. Portable laser scanners are used to perform detailed scans of the steel structure's connection nodes and key areas. Portable laser scanners offer higher accuracy, typically reaching millimeter or even submillimeter levels, making them suitable for close-range acquisition of node details. Operators scan pre-determined key nodes, such as beam-column joints and support connections, to obtain high-precision geometric data. This data, along with detailed node geometry, provides precise geometric information for subsequent structural analysis.

[0021] Extracting steel material specifications, strength grades, manufacturers, and installation dates from steel structure archives and establishing a basic steel component information table is a crucial method for obtaining non-geometric information about steel structures. By reviewing original design drawings, construction records, and acceptance documents, material parameter information for each component is extracted, including steel type (e.g., Q235B, Q345B), component dimensions, manufacturer, production batch, installation date, and historical maintenance records. This information is organized into a structured data table, assigning basic component attributes to facilitate subsequent integration within the BIM model. Strain sensors, inclination sensors, and displacement sensors are deployed at key stress points within the steel structure to record dynamic stress data. Strain sensors measure local strain changes in components, reflecting the stress state; inclination sensors monitor changes in the structure's tilt angle, used to assess overall structural stability; and displacement sensors record structural deformation, reflecting the structure's response under load. The data collected by these sensors undergoes signal conversion, transmission, and processing to form time series data, reflecting the dynamic performance of the steel structure under actual use.

[0022] The collected point cloud data is subjected to noise reduction to remove outliers generated during the acquisition process, generating a clean point cloud for the steel structure. Point cloud noise reduction primarily targets outliers, including isolated points, outliers, and noise points, caused by factors such as equipment errors and environmental interference. Statistical filtering methods are used to calculate the neighborhood characteristics of each point to determine whether it is an outlier. For example, for a set of points within a fixed radius around a given point, the distance distribution is calculated. If the average distance from a point to its neighbors is significantly greater than the average distance for the entire point cloud, the point is identified as an outlier and removed. Furthermore, a voxelization method is used to divide the space into a regular grid. Cluster analysis is performed on the points within each grid, retaining representative points and removing redundant points. This reduces the data volume while preserving geometric features. The node detail geometric feature data is fused with the clean point cloud to generate the complete steel structure geometry data. The two point cloud data types have different resolutions and coverage, requiring registration and fusion. First, a feature point matching algorithm is used to identify corresponding points in the two point cloud groups. A coordinate transformation matrix is then calculated to transform the node detail point cloud into the coordinate system of the macro point cloud. A multi-resolution fusion strategy is then employed to retain high-precision node detail point cloud data in overlapping areas and macroscopic point cloud data in non-overlapping areas, generating complete and detailed geometric data for the steel structure. Material and historical attributes are added to the complete geometric data based on the steel component basic information table to construct parametric information for the steel structure. This step links the geometric data with the attribute information. Through spatial position matching and component identifier association, the attribute data in the steel component basic information table is mapped to the corresponding geometric model. For example, the point cloud data is segmented into component units using a segmentation algorithm, and then a mapping is established between the component IDs in the steel component basic information table. Attribute information such as material strength, manufacturer, and installation date is then attached to the geometric model, forming a parametric model with rich semantic information. The dynamic stress state data of the steel structure is then mapped to the parametric information of the steel structure, resulting in a digital maintenance base for the steel structure. This step combines real-time monitoring data with the static parametric model to form a dynamic digital twin system. Specifically, a data interface is set up for each key node in the parametric model to connect to the dynamic data stream collected by the sensor and establish a mapping relationship between physical quantities and model positions. The database adopts a relational structure to construct multiple data tables such as steel structure component table, attribute table, monitoring data table, etc., and establishes relationships between tables using component ID as the association key, ultimately forming a comprehensive database containing geometry, material, history and dynamic monitoring information.

[0023] For example, a drone-mounted LiDAR scanned the building from various heights and angles, generating approximately 20 million points of raw point cloud data covering the building's exterior contours. Subsequently, technicians used a portable laser scanner to perform detailed scans of 40 key nodes within the building, acquiring approximately 500,000 high-precision point cloud data points for each node. By consulting the building archives, they extracted material information for each component, including the specifications of the Q345B steel used in the main frame, the types of high-strength bolts used in the connection nodes, and historical maintenance records. A sensor network of 32 strain sensors, 16 inclination sensors, and 24 displacement sensors was installed at key locations within the structure, collecting data hourly. Noise reduction was performed on the raw point cloud data, removing approximately 1.2 million outliers and preserving valid geometric features. A registration algorithm was used to fuse the node detail point cloud with the overall point cloud to generate a complete geometric model. Attribute data from the component basic information table was mapped to the geometric model to form a parametric information model. By linking the real-time sensor data with the parametric model, a basic database for digital maintenance of steel structures was constructed.

[0024] In a specific embodiment, the process of executing step S102 may specifically include the following steps: (1) Extract the structural displacement sensor data from the steel structure digital maintenance basic database, perform time series feature analysis, and obtain the steel structure deformation trend curve; (2) Use a high-resolution camera to capture the surface image of the steel structure, and obtain the surface texture feature map of the steel structure through image enhancement processing; (3) Based on the surface texture feature map of the steel structure, the surface corrosion area and crack direction are identified through the edge detection algorithm to form a steel structure defect distribution map; (4) Compare the deformation trend curve of the steel structure with the theoretical force calculation value, calculate the degree of structural deformation deviation, and generate the deformation anomaly index; (5) According to the steel structure defect distribution map, calculate the corrosion area ratio and crack density value of each component to form the quantitative parameters of surface damage; (6) The deformation anomaly index and the surface damage quantitative parameters are weighted by a comprehensive scoring method, the component health level is divided, and a steel structure health assessment report is obtained.

[0025] Specifically, historical data records from displacement sensors are read from the digital maintenance database to form a time series. The raw data is filtered to remove outliers and noise. Time series feature analysis includes trend analysis, periodicity analysis, and mutation point detection. Trend analysis uses sliding window averaging or polynomial fitting to extract long-term deformation trends; periodicity analysis uses Fourier transforms to identify periodic characteristics of structural deformation; and mutation point detection is used to detect abnormal changes in structural deformation. Through these analysis methods, trend curves are plotted showing the changes in steel structure deformation over different time periods, visually demonstrating the development patterns of structural deformation. Surface condition analysis begins with capturing images of the steel structure surface using a high-resolution camera and performing image enhancement to obtain a surface texture feature map. High-resolution cameras should have sufficient pixel density to capture millimeter-level surface details. Lighting conditions must be controlled during acquisition to avoid strong reflections or shadows. After acquiring the raw images, image enhancement processing is performed, including contrast adjustment, sharpening, and noise suppression. Contrast adjustment enhances image contrast by stretching the image's grayscale histogram. Sharpening uses a high-pass filter to enhance image edges and details. Noise suppression eliminates random noise through median or Gaussian filtering. These processing steps enhance surface texture details that were not readily apparent in the original image, forming a characteristic map of the steel structure's surface texture, providing a visual foundation for subsequent defect identification.

[0026] Based on the steel structure's surface texture feature map, an edge detection algorithm is used to identify surface rust areas and crack orientations, generating a steel structure defect distribution map. Edge detection algorithms, such as the Sobel operator, Canny operator, or LoG operator, are used to identify areas within the image with dramatic grayscale changes, which typically correspond to defect boundaries. For rust area identification, a color segmentation algorithm is also used to identify the rusted areas based on their unique color characteristics. For crack identification, morphological operations are used to extract slender structural features. These algorithms transform the surface texture feature map into a binary defect distribution map, where different types of defects are represented by different colors or markers, visually displaying the distribution of rust areas on the steel structure's surface and the orientation and length of cracks.

[0027] Comparing the deformation trend curve of the steel structure with the theoretical load calculation value, calculating the degree of structural deformation deviation, and generating the deformation anomaly index involves quantitatively evaluating the actual deformation degree of the structure. First, based on the structural theoretical model, the theoretical deformation value under given load conditions is calculated as a benchmark reference value. Then, the deviation between the measured deformation and the theoretical deformation is calculated and expressed as: , in, represents the Deformation Abnormality Index, T is the length of the time series, is the actual deformation at time t, is the theoretical deformation calculated value at time t, A temporal weighting factor reflects the importance of recent data. A larger DAI value indicates that the actual deformation of the structure deviates further from theoretical expectations, and the structural performance may be more abnormal. This indicator considers the relative size of deformation deviations and their temporal distribution, providing a more comprehensive assessment of the degree of structural deformation anomaly.

[0028] According to the steel structure defect distribution map, the corrosion area ratio and crack density of each component are calculated to form the surface damage quantitative parameters, which is a key step in the quantitative evaluation of the surface condition. The calculation formula of the corrosion area ratio is: , in, Indicates the rust area coverage ratio (Rust Area Coverage), is the area of the corroded area, is the total surface area of the component. The crack density is calculated using the following formula: , in, represents the crack density factor (Crack Density Factor), is the number of cracks, is the length of the i-th crack, is the weight coefficient of the i-th crack (related to the crack width and depth), is the total surface area of the component. Combining these two parameters forms a quantitative description of the surface damage of the structure, which intuitively reflects the severity of the surface damage.

[0029] The final step in the health status assessment is to calculate the weights of the deformation anomaly index and the quantitative parameters of surface damage through a comprehensive scoring method, classify the component health levels, and obtain a steel structure health assessment report. The Comprehensive Health Index (CHI) calculation formula is: , in, and They are the weight coefficients of deformation anomaly index, corrosion area ratio and crack density factor, respectively, and are determined according to the importance of different types of components. The closer the CHI value is to 1, the better the health status of the component. According to the CHI value, the health status of the component is divided into five levels from A to E: Level A (excellent state, 0.9≤CHI≤1.0), Level B (good state, 0.8≤CHI<0.9), Level C (caution state, 0.7≤CHI<0.8), Level D (warning state, 0.6≤CHI<0.7), and Level E (dangerous state, CHI<0.6). The health assessment report contains information such as the health level, damage type, damage location and development trend of each component, providing a basis for subsequent maintenance decisions.

[0030] Taking the roof trusses of a steel structure factory as an example, displacement sensor data was extracted from a digital maintenance database, recording the changes in vertical displacement of the nodes over a continuous 90-day period. Time series analysis revealed that the displacement of the mid-span node showed a fluctuating upward trend, with the peak value correlated with temperature changes. Time series feature extraction was performed on the displacement sensor data to plot a deformation trend curve. Simultaneously, the truss surface was photographed using a high-resolution camera to obtain raw images. Contrast enhancement and sharpening were used to enhance the visibility of surface rust and microcracks, generating a surface texture feature map. The Canny edge detection algorithm was applied to the feature map to identify rust areas at the bottom chord connection node and microcracks in the web, generating a defect distribution map. Calculations revealed that the actual maximum vertical displacement of this node was 22.5 mm, compared to a theoretical value of 15 mm. The deformation anomaly index (DAI) was calculated to be 0.35. The defect distribution map showed that the corrosion area ratio (RAC) of the bottom chord connection node was 18%, and the crack density factor (CDF) of the web was 0.015. Substituting these parameters into the Comprehensive Health Index formula, the truss' CHI value was calculated to be 0.73, corresponding to a C (Caution) rating. The health assessment report noted that the truss required attention for corrosion issues at the mid-span lower chord connection and crack development in the right web member. Anti-corrosion treatment and enhanced monitoring were recommended.

[0031] In a specific embodiment, the process of executing step S103 may specifically include the following steps: (1) Filter the information of components with health grades of D and E from the steel structure health assessment report and generate a list of components to be maintained; (2) For each component in the list of components to be maintained, match the applicable maintenance technology from the maintenance method database to form a preliminary maintenance technology combination plan; (3) Based on the preliminary maintenance technology combination plan, calculate the amount of steel, anti-corrosion coating and construction time required for each plan to form a resource consumption data table; (4) Based on the resource consumption data table, combined with the carbon emission coefficient of material production and the construction energy consumption parameters, the carbon footprint value of the entire maintenance process is calculated to generate environmental impact assessment data; (5) Convert the material and labor data in the resource consumption data table according to the market unit price to form a maintenance economic cost budget; (6) By comprehensively balancing the environmental impact assessment data and the maintenance economic cost budget, and comparing the maintenance benefits with the remaining service life of the building, a sustainable maintenance strategy for the steel structure is obtained.

[0032] Specifically, the information of components with health levels of D and E is screened from the steel structure health assessment report to generate a list of components to be maintained. The health assessment report contains the health level information of all components. According to the preset risk level classification standards, components of level D (warning state) and level E (dangerous state) have obvious structural performance degradation or surface damage and require priority maintenance intervention. The screening process is achieved through data filtering operations. Records with health level field values of D or E are extracted from the assessment report database, and key information such as component number, location coordinates, damage type, and damage degree are extracted. The components are arranged in order of priority to form a structured list of components to be maintained.

[0033] For each component in the list of components to be maintained, the applicable maintenance technology is matched from the maintenance method database to form a preliminary maintenance technology combination plan. The maintenance method database is a knowledge base that contains various maintenance technologies for steel structures. Each method is marked with applicable damage types, applicable components, applicable environments and other condition parameters. The matching process uses a multi-condition screening algorithm to retrieve qualified maintenance technologies based on multi-dimensional parameters such as component type, damage characteristics, and location conditions. For example, for steel columns with surface rust, rust removal, anti-corrosion coating and other technologies can be matched; for beam components with excessive deformation, reinforcement or replacement technologies are matched. For each Class D or Class E component, 2-3 optional maintenance technologies are usually screened out and combined to form multiple sets of preliminary maintenance plans for subsequent evaluation and selection.

[0034] Based on the preliminary maintenance technology combination plan, calculate the steel consumption, anti-corrosion coating consumption and construction time required for each plan to form a resource consumption data table. This step requires quantitative calculation of various resource requirements. The steel consumption calculation is achieved through the following formula: , in, represents the total steel material quantity of solution p, is the number of maintenance items involving steel in plan p, The volume of the steel component required for item k maintenance, is the density of steel, is the correction factor to take into account the cutting loss. The calculation formula for the amount of anti-corrosion coating is: , in, represents the protective coating quantity of solution p, is the coating area maintained for item k, is the coating thickness, is the coating density, A correction factor is used to account for paint loss. Construction time is calculated based on standard labor hours and the construction difficulty factor. These calculation results are summarized into a resource consumption data table, providing a data foundation for subsequent evaluation.

[0035] Based on the resource consumption data table, combined with the carbon emission coefficient of material production and construction energy consumption parameters, the carbon footprint value of the entire maintenance process is calculated to generate environmental impact assessment data. The full process carbon footprint calculation adopts the life cycle assessment method, considering the carbon emissions of each link of material production, transportation, construction and waste disposal. The calculation formula is: , in, represents the carbon footprint of solution p, R is the number of resource types, is the consumption of the rth type of resource in plan p, is the unit carbon emission factor of this type of resource, Q is the number of energy types, is the consumption of the qth type of energy in plan p, is the carbon emission factor for that type of energy. The carbon footprint value calculated using this formula serves as a core indicator for environmental impact assessment, quantifying the environmental impact of the maintenance plan.

[0036] The economic evaluation phase involves converting the material and labor data in the resource consumption data table to market unit prices to generate a maintenance economic cost budget. Economic costs include direct costs (materials, labor, and equipment) and indirect costs (management fees, taxes, etc.). Material costs are calculated by multiplying the material consumption by the unit price; labor costs are calculated by multiplying the labor hours by the labor unit price; and equipment costs are calculated by multiplying the equipment hours by the equipment usage rate. Indirect costs are estimated as a certain percentage of direct costs. These cost items are aggregated to form a comprehensive economic cost budget, which serves as the basis for the economic evaluation of the proposed solution. By comprehensively balancing the environmental impact assessment data with the maintenance economic cost budget and comparing the maintenance benefits with the remaining useful life of the building, a sustainable maintenance strategy for the steel structure is determined. This comprehensive evaluation utilizes a multi-objective decision-making approach, weighing multiple objectives, including environmental impact, economic costs, and maintenance benefits. First, the cost-effectiveness index of the proposed solution is calculated, reflecting the input-output ratio. Second, the extended service life of the structure after maintenance is estimated and compared with the remaining useful life of the building to avoid excessive maintenance. Finally, based on these analysis results, the optimal maintenance strategy is determined, including maintenance priorities, technology selection, and implementation schedule.

[0037] Taking a steel office building as an example, a health assessment report identified five Class D columns and two Class E beams with surface corrosion and deformation at their connection points, respectively. This resulted in a maintenance list of seven components. For each component, appropriate technologies were matched from a maintenance method database. For example, mechanical rust removal with anti-corrosion coating and sandblasting with anti-corrosion coating were selected for the rusted columns. Local reinforcement and complete replacement were selected for the deformed beams, resulting in a total of four maintenance technology combinations. For Option 1 (mechanical rust removal with local reinforcement), it was calculated that 42 square meters of anti-corrosion coating (area × thickness × density × 1.15 loss factor) and 0.8 tons of steel plate (volume × density × 1.1 loss factor) would be required, with a total construction time of 96 man-hours. Based on the carbon emission factors for material production (2.2 tons of CO₂ / ton for steel and 3.5 kg of CO₂ / liter for paint) and construction energy consumption (12 kWh / man-hour, 0.6 kg of CO₂ / kWh), the carbon footprint of Option 1 was calculated to be 2.36 tons of CO₂ equivalent. Based on the market price of materials (6,000 yuan / ton for steel and 80 yuan / square meter for paint) and labor costs (100 yuan / man-hour), the economic cost budget for Option 1 was 22,360 yuan. Considering the building's remaining service life of 25 years, Option 1 could extend the component life by 30 years, offering a superior cost-effectiveness compared to other options. It was ultimately determined to be the optimal sustainable maintenance strategy for steel structures.

[0038] In a specific embodiment, the process of executing step S104 may specifically include the following steps: (1) Based on the component information in the sustainable maintenance strategy of steel structures, the geometric dimension data and damage characteristics of the components to be repaired are extracted, and the coordinates of the component repair area and the repair range boundary are determined; (2) Based on the coordinates of the repair area, the force direction and stress distribution of the repair area are extracted from the steel structure mechanics analysis, the weak points of the components are analyzed, and a component force spectrum is formed; (3) Based on the stress spectrum and damage characteristics of the component, select the appropriate steel type, welding material, and anti-corrosion coating from the material database, calculate the material usage, and generate a repair material list; (4) Verify the mechanical properties of the steel types in the repair material list to ensure that the bearing capacity of the repaired components meets the design requirements, and formulate the geometric parameters and connection methods of the repaired components; (5) Convert the geometric parameters of the repaired component into construction operation instructions, decompose them into cutting parameters, welding parameters, and coating parameters, and form a component repair process parameter table; (6) Combine the component repair process parameter table with the maintenance operation process, add construction quality control points and safety precautions, draw a construction guide map, and obtain a steel structure maintenance construction guide.

[0039] Specifically, the 3D geometric data of the component to be repaired is retrieved from the BIM model database, including its spatial coordinates, geometry, and dimensional parameters. Simultaneously, damage characteristics of the component, such as the distribution of corrosion areas, crack orientation, and deformation, are extracted from the health assessment report. Using a spatial analysis algorithm, this damage information is precisely matched to the geometric model to determine the precise coordinates of the component area requiring repair. This process utilizes region segmentation technology to divide the component surface into areas requiring repair and areas requiring no intervention based on damage thresholds. The boundary contours of the repair areas are then calculated to form a closed repair boundary, providing spatial positioning for subsequent precise maintenance. For each identified repair area coordinate, the stress state information for that area is extracted from a steel structure mechanical analysis. Finite element analysis is used in this step to extract the component's stress boundary conditions from the BIM model, including support constraints, connection methods, and load transfer paths. These boundary conditions are then applied to the numerical analysis model to calculate the stress, strain, and internal force distribution of the component under actual operating conditions. The analysis results intuitively demonstrate the magnitude and direction of stress at each location, focusing specifically on areas of stress concentration and identifying weak points. These weak points are often potential starting points for structural failure and require special consideration in maintenance design. The mechanical analysis results are displayed in the form of cloud maps, forming a component stress spectrum and intuitively expressing the mechanical performance status of the component.

[0040] The next key step is to select suitable repair materials from the material database based on the stress map and damage characteristics of the component. The material database stores the mechanical properties parameters, chemical composition, processing performance and durability data of various steel types; the strength grades, applicable steel types, welding process parameters of various welding materials; and the protection level, use environment, coating process requirements and other information of anti-corrosion coatings. The material selection process first considers the matching degree of the mechanical properties of the material and the original component to ensure that the material strength meets the stress requirements; secondly, the welding performance and connection compatibility of the material are considered to ensure that the repair part can form a reliable connection with the original component; finally, the durability and anti-corrosion performance of the material are considered to meet the requirements of the use environment. After the material is selected, the amount of required material is accurately calculated according to the geometric dimensions and design parameters of the repair area, including steel plate area, welding rod length, coating volume, etc., to form a detailed list of repair materials.

[0041] Verifying the mechanical properties of the steel types in the repair material list is an important step in ensuring maintenance quality. The verification process is based on the principles of structural mechanics. First, a mechanical model of the repaired component is established, and the newly added materials and the original component are analyzed as a whole. The stress level of the repaired component under the design load is calculated to ensure that it does not exceed the design strength of the material; the force transmission capacity of the key connection nodes is calculated to verify the reliability of the connection; the stability and deformation of the repaired component are checked to ensure that they meet the requirements of the specification. After the verification is passed, the geometric parameters of the repaired component are further optimized, including the thickness, width, and length of the reinforcement plate, the diameter, number, and spacing of the connecting bolts, the type, position, and size of the welds, etc., and the final connection method is determined, such as welding, bolting, or mixed connection.

[0042] Translating the geometric parameters of the repaired component into specific construction instructions is a critical step in realizing design intent. This process requires breaking down abstract design parameters into a series of specific, executable operational parameters. Cutting parameters specify the precise location, size, and shape of the damaged portion of the original component to be removed or the reinforcement plate to be installed, including the coordinates of the cutting line, cutting depth, and cutting angle. Welding parameters define process elements such as welding position, weld type, welding sequence, preheating temperature, welding current and voltage, and welding speed. Painting parameters include surface treatment level, primer type and thickness, topcoat type and thickness, painting temperature, and humidity requirements. These process parameters are standardized to form a component repair process parameter table, facilitating precise execution by construction personnel.

[0043] Combine the component repair process parameter table with the maintenance operation process to form a complete steel structure maintenance construction guide. Design a specific sequence of operation steps based on the process parameter table, and clarify the work content, operation methods and process connection relationship. Secondly, set quality control points in key processes, such as pre-weld inspection, post-weld flaw detection, surface treatment inspection before painting, etc., and formulate corresponding inspection standards and acceptance methods. Thirdly, for special processes or dangerous operations, add safety precautions, such as high-altitude work protection, welding fire prevention measures, toxic paint protection and other requirements. Finally, express these contents in the form of pictures and texts, and draw an intuitive construction guide map, including a three-dimensional schematic diagram of the maintenance area, a flow chart of the construction steps, a key point diagram of quality inspection, etc., to form a complete steel structure maintenance construction guide to guide precise on-site construction.

[0044] Taking the maintenance of a damaged steel column in a steel structure factory building as an example, geometric data of the column was extracted from the BIM model, confirming it to be an H350×350×12×12 steel column. Damage information was extracted from the health assessment report, revealing severe corrosion and slight deformation at the column base. The corrosion area was approximately 1200 square centimeters, and the deformation reached 8 millimeters. Spatial positioning determined that the entire cross-section of the column base, within a range of 0-500 mm from the ground, required repair. Mechanical analysis revealed that this area was subjected to an axial compressive force of 270 kN and a bending moment of 15 kN·m, with stress concentrated at the flange-web connection. Based on this information, Q345B steel plate was selected from the material database as the reinforcement material, E5015 welding rods as the welding material, and epoxy zinc-rich primer and polyurethane topcoat as the anti-corrosion coatings. Calculations determined that a reinforcement collar of 8 mm thick steel plate, measuring 360×360×500 mm, with a total welding rod length of approximately 6 meters and a coating coverage area of approximately 2 square meters, was required around the column base. Mechanical calculations confirmed that the column base's load-bearing capacity increased by 30% after reinforcement, meeting design requirements. The design was translated into specific operational instructions: first, remove severely corroded areas, then cut the reinforcement steel plates to the dimensions on the drawing. Use 6mm double-sided fillet welds for connection, welding current of 120-130A and welding speed of 250-300mm / min. Pre-painting should achieve Sa2.5 grade, with a primer thickness of 80μm and a topcoat thickness of 60μm. Finally, a construction guide was created that incorporated these parameters, annotated with six quality control points and key safety tips, creating a complete maintenance and construction guide.

[0045] In a specific embodiment, the process of executing step S105 may specifically include the following steps: (1) Convert the spatial coordinate data in the steel structure maintenance construction guide into on-site positioning parameters and establish an electronic map of the maintenance location in the on-site terminal equipment; (2) Based on the electronic map of the maintenance location, the on-site steel structure components are matched and scanned using target recognition technology to confirm the actual location of the components to be maintained; (3) Virtual operation guidance is marked on the actual position of the component to be maintained, and the maintenance process parameters are intuitively projected on the surface of the component to form visual operation instructions; (4) Guide construction workers to complete component repair operations through visual operation instructions, while recording key parameters during construction and generating construction process data streams; (5) Monitor the welding temperature, coating thickness, and bolt torque values in the construction process data stream in real time, compare and verify with the design standards, and record construction quality data; (6) Integrate construction quality data with component maintenance completion photos, associate construction location and technical parameter information, and generate steel structure maintenance implementation records.

[0046] Specifically, the spatial coordinate data in the steel structure maintenance construction guide is converted into on-site positioning parameters, and an electronic map of the maintenance location is established in the on-site terminal equipment. First, the global coordinate information of the component to be maintained is extracted from the BIM maintenance model, including the component's precise position and posture parameters in the building. Then, combining the building's physical coordinate system with the relative coordinate system of the mobile terminal, the absolute coordinates in the BIM model are converted into on-site relative coordinates through a coordinate transformation algorithm. The converted spatial information is displayed in a two-dimensional or three-dimensional graphical format on a mobile terminal (such as a tablet or AR glasses), forming an electronic map of the maintenance location. This map intuitively displays the location of the component to be maintained in the building, its surrounding environment, and the approach route.

[0047] Using object recognition technology to scan and match on-site steel structure components against the electronic map of the maintenance location, confirming the actual location of the component to be maintained is a key step in accurate positioning. Object recognition technology primarily involves two methods: QR code recognition and feature point matching. QR code recognition uses a mobile device to scan and read the information from a pre-attached QR code tag on the component, quickly identifying the component. Feature point matching uses computer vision algorithms to compare the real-time image captured by the terminal device's camera with component features in the BIM model, identifying specific structural shapes, connection nodes, or surface features to locate the target component. Positioning accuracy typically reaches centimeters, meeting the precise requirements of maintenance work. After a successful match, the terminal device automatically adjusts the viewing angle and display scale to precisely align the electronic map with the actual component. A core application of augmented reality technology in maintenance is to mark the actual location of the component to be maintained with virtual operation guides, visually projecting maintenance process parameters onto the component surface to provide visual instructions. This process extracts process parameter information from the maintenance work guide, including key operation points such as cutting line locations, welding locations, and painting ranges. Using an augmented reality rendering engine, this information is overlaid as virtual graphics on the real-time display of the terminal device. When technicians observe the actual component through AR glasses or tablets, they see a virtual image superimposed on the component surface, such as colored lines marking the cutting location, flashing arrows indicating the welding direction, and translucent shadows marking the painting area. At the same time, process parameters such as welding current, preheat temperature, coating thickness and other technical data are also displayed in text or icon form near the corresponding location, forming intuitive and easy-to-understand visual operation instructions.

[0048] Guiding workers through component repair operations through visual instructions while simultaneously recording key parameters and generating a construction process data stream is a crucial step in implementing precision maintenance. Wearing AR glasses or using a tablet, workers perform the actual operations according to the virtual instructions. During the operation, sensor modules connected to the terminal devices collect key process parameter data in real time. For example, infrared thermometers monitor welding temperature, coating thickness gauges measure anti-corrosion coating thickness, and electronic torque wrenches record bolt tightening torque. This collected data is transmitted via a wireless network to a data processing module, forming a time-series construction process data stream that fully records parameter changes throughout the maintenance operation. Real-time monitoring of welding temperature, coating thickness, and bolt torque values in the construction process data stream, as well as comparison and verification against design standards, is crucial for recording construction quality data in quality control. The data processing module receives the construction process data stream and compares each measured parameter in real time against the standard range specified in the maintenance and construction guidelines. For example, the measured welding temperature is compared with the temperature range required by the process (such as 450-550°C), the measured coating thickness is compared with the designed thickness (such as 120 microns), and the actual torque of the bolt is compared with the specified torque (such as 120 Nm). When the parameters deviate from the standard range, the terminal device immediately issues a warning prompt to guide the operator to make adjustments. The comparison results are also recorded as quality control data points, marked as qualified or unqualified, and accompanied by actual measurement values, standard values, and deviation values, forming structured construction quality data.

[0049] The final step in establishing a maintenance file is to integrate construction quality data with photos of component maintenance completion, associate construction locations with technical parameter information, and generate steel structure maintenance implementation records. After the maintenance work is completed, a high-definition camera is used to take completed photos of the repaired components to record the final status of each key part. Through a data integration algorithm, construction quality data, completion photos, construction location coordinates, and technical parameter information are associated according to the component ID to form a complete maintenance implementation record. These records are organized into structured data sets, containing multiple dimensions such as maintenance object information, maintenance time information, maintenance location information, maintenance content information, quality control information, and acceptance result information. The final generated maintenance implementation record is uploaded to the BIM database, updating the component status information in the steel structure digital twin model, providing data support for subsequent building operation and maintenance management and effect evaluation.

[0050] In a specific embodiment, the process of executing step S106 may specifically include the following steps: (1) Extract the component status parameters after maintenance from the steel structure maintenance implementation record, and retrieve the original component status data before maintenance from the steel structure digital maintenance basic library to form a comparison table of data before and after maintenance; (2) Recollect the displacement and strain data of key nodes of the steel structure after maintenance through the sensor network, compare them with the structural monitoring data before maintenance, and calculate the structural performance recovery rate; (3) Perform high-definition imaging scanning on the surface of the steel structure after maintenance, extract surface features through image processing, compare with the surface defect distribution map before maintenance, and obtain the surface quality improvement index; (4) Compare the structural performance recovery rate and surface quality improvement index with the expected goals of the maintenance plan to evaluate the effectiveness of the maintenance technology and generate technical evaluation results; (5) Based on the actual resource consumption data in the maintenance implementation records, recalculate the economic cost and environmental impact of maintenance, compare with the budget value, and form a resource efficiency assessment; (6) Integrate the technical evaluation results with the resource efficiency assessment, correlate the pre-maintenance condition, maintenance technology selection and maintenance effect data, and establish a structural steel structure maintenance case data set.

[0051] Specifically, it is necessary to extract the component status parameters after maintenance from the steel structure maintenance implementation record, and at the same time retrieve the original component status data before maintenance from the steel structure digital maintenance basic library to form a comparison table of data before and after maintenance. The steel structure maintenance implementation record contains the component status information after maintenance is completed, such as geometric dimensions, surface conditions, connection conditions, etc.; while the steel structure digital maintenance basic library stores the original status data before maintenance. Through database query statements, these two parts of data are extracted according to the component ID and organized into a structured comparison table, including three parts: basic component information, status parameters before maintenance, and status parameters after maintenance. This comparison table intuitively shows the status changes of the same component before and after maintenance, providing a data basis for subsequent evaluation.

[0052] An important method for quantifying maintenance effectiveness is to recollect displacement and strain data from key nodes of the steel structure through a sensor network and compare it with pre-maintenance structural monitoring data to calculate the structural performance recovery rate. After maintenance is completed, the sensor network installed at key locations of the steel structure is reactivated to collect displacement and strain data under the same load conditions. The formula for calculating the structural performance recovery rate is: , in, represents the structural performance recovery rate, P is the number of monitoring points, is the weight coefficient of the p-th monitoring point, is the measured value of the pth monitoring point after maintenance, is the measured value of the pth monitoring point before maintenance, is the design value of the pth monitoring point. This formula takes into account the comprehensive performance of multiple monitoring points and evaluates the recovery of structural performance by calculating the degree of improvement in the deviation of the measured value relative to the design value. The closer the SPR value is to 100%, the better the structural performance has recovered. Performing high-definition imaging scanning on the surface of the steel structure after maintenance, extracting surface features through image processing, and comparing it with the surface defect distribution map before maintenance to obtain the surface quality improvement index is a method to evaluate the improvement of the surface condition. Use a high-resolution camera to image the surface of the component after maintenance to obtain a clear surface image. Through image processing technology, including contrast enhancement, edge detection and feature extraction methods, the surface texture features are analyzed to identify potential defect areas, such as residual rust and tiny cracks. The processed image is compared with the surface defect distribution map before maintenance at the pixel level, and the reduction ratio of the defect area and the reduction ratio of the defect severity are calculated. The surface quality improvement index is comprehensively obtained to quantify the degree of improvement in the surface condition.

[0053] The technical evaluation phase compares the structural performance recovery rate and surface quality improvement index with the maintenance plan's expected goals to assess the effectiveness of the maintenance technology and generate technical evaluation results. The maintenance plan's expected target values, including the expected level of structural performance recovery and the expected degree of surface quality improvement, are extracted from the sustainable maintenance strategy for steel structures. The actual measured structural performance recovery rate and surface quality improvement index are compared with the expected target values to calculate the target achievement rate. Based on the achievement rate and incorporating professional evaluation criteria, a qualitative evaluation result of "excellent," "good," "qualified," or "unqualified" is assigned, supplemented with specific quantitative indicators and analytical explanations to form a comprehensive technical evaluation result. The economic and environmental evaluation phase recalculates the economic cost and environmental impact of maintenance based on actual resource consumption data from maintenance implementation records and compares them with budgeted values to generate a resource efficiency assessment. Actual resource data such as steel consumption, anti-corrosion coating usage, and labor hours are extracted from maintenance implementation records to calculate the actual economic cost based on actual market unit prices. Furthermore, the actual carbon footprint and other environmental impact indicators are calculated by incorporating environmental impact factors for materials and energy. Compare these actual values with the estimated values in the maintenance plan budget phase, calculate the cost deviation rate and environmental impact deviation rate, evaluate the efficiency and accuracy of resource utilization, and form a resource efficiency evaluation report.

[0054] Integrating technical evaluation results with resource efficiency assessments, linking pre-maintenance conditions, maintenance technology selection, and maintenance effect data, and establishing a structural steel structure maintenance case data set is a key step in knowledge accumulation. Through data integration algorithms, technical evaluation results and resource efficiency assessments are linked according to component IDs, and pre-maintenance condition data, maintenance technology selection information, and maintenance effect data are linked to form a complete maintenance case record. These records are organized into structured data sets, including multiple dimensions such as case background, problem description, solution, implementation process, effect evaluation, and experience summary. Through labeling and indexing, multi-dimensional retrieval functions based on keywords, similar cases, or semantic understanding are realized, facilitating reference and use for similar maintenance projects in the future.

[0055] The above describes the BIM-based sustainable maintenance method for steel structure buildings in the embodiment of the present application. The following describes the BIM-based sustainable maintenance system for steel structure buildings in the embodiment of the present application. Figure 2 In the embodiment of the present application, an embodiment of a BIM-based sustainable maintenance system for steel structure buildings includes: Integration module, used to collect steel structure geometry data and material parameters through laser scanning and sensor network, integrate steel structure 3D information, and obtain a digital maintenance base for steel structures; An analysis module is used to analyze structural deformation and surface defects based on component information and monitoring data in the steel structure digital maintenance basic library to obtain a steel structure health assessment report; A calculation module is used to calculate the resource consumption and environmental impact of the maintenance plan based on the key component data in the steel structure health assessment report to obtain a sustainable maintenance strategy for the steel structure; A configuration module is used to set component repair parameters and material configuration according to the sustainable maintenance strategy of the steel structure, and obtain a steel structure maintenance construction guide; An import module is used to import the steel structure maintenance construction guide into the on-site terminal equipment to perform location guidance and operation identification to obtain a steel structure maintenance implementation record; The verification module is used to compare the steel structure maintenance implementation records and original status data before and after maintenance and verify the effect to obtain a steel structure maintenance case data set.

[0056] Through the collaborative cooperation of the above components, steel structure information is collected through laser scanning and sensor networks, a digital maintenance basic library for steel structures is established, and accurate mapping of physical entities of steel structures to digital space is achieved, providing a comprehensive and accurate data basis for health assessment and maintenance decisions, and solving the problems of missing and inaccurate data in traditional maintenance; by analyzing structural deformation and surface defects of component information and monitoring data in the digital maintenance basic library, a health assessment report for steel structures is formed, which achieves scientific quantification and accurate classification of the health status of steel structures, overcoming the subjectivity and uncertainty of traditional empirical judgments; combining the data from the health assessment report to calculate the resource consumption and environmental impact of the maintenance plan, a sustainable maintenance strategy for steel structures is obtained, and the concept of sustainable development is integrated into maintenance decisions. The policy-making process balances structural safety, resource utilization efficiency and environmental protection requirements; based on the sustainable maintenance strategy, component repair parameter setting and material configuration are carried out, and a steel structure maintenance construction guide is formulated, which realizes the refinement and standardization of maintenance design and improves the efficiency and quality of maintenance design; the maintenance construction guide is imported into the on-site terminal equipment for position guidance and operation identification, forming a steel structure maintenance implementation record, and the design intent is accurately transmitted to the construction site through augmented reality technology, solving the problems of large construction deviation and difficult quality control in traditional maintenance; the maintenance implementation record and the original status data are compared before and after maintenance and the effect is verified, a steel structure maintenance case data set is established, and a maintenance knowledge accumulation and experience inheritance mechanism is constructed, which improves the intelligence level of maintenance decision-making.

[0057] Reference Figure 3 In an embodiment of the present invention, a computer device is also provided. The computer device may be a server, and its internal structure may be as follows: Figure 3 As shown. The computer device includes a processor, memory, display screen, input device, network interface and database connected via a system bus. The processor of the computer design is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the above method is implemented.

[0058] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0059] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the above-described method when executed by a processor. It is understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0060] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware using a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the above-described method embodiments. Any reference to memory, storage, database, or other media provided herein and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM.

[0061] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0062] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0063] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A sustainable maintenance method for steel structure buildings based on BIM, characterized in that: The BIM-based sustainable maintenance method for steel structure buildings includes: Through laser scanning and sensor networks, geometric data and material parameters of steel structures are collected, and three-dimensional information of steel structures is integrated to obtain a digital maintenance base for steel structures. Perform structural deformation and surface defect analysis based on component information and monitoring data in the steel structure digital maintenance basic library to obtain a steel structure health assessment report; Calculate resource consumption and environmental impact of maintenance plans using key component data from the steel structure health assessment report to obtain a sustainable maintenance strategy for the steel structure; According to the sustainable maintenance strategy for steel structures, component repair parameters and material configuration are set to obtain a steel structure maintenance construction guide; Importing the steel structure maintenance construction guide into the on-site terminal device to perform location guidance and operation identification to obtain a steel structure maintenance implementation record; The steel structure maintenance implementation records and original status data are compared before and after maintenance and the effect is verified to obtain a steel structure maintenance case data set.

2. The BIM-based sustainable maintenance method for steel structure buildings according to claim 1 is characterized in that: The steel structure geometric data and material parameters are collected through laser scanning and sensor network, and the three-dimensional information of the steel structure is integrated to obtain the steel structure digital maintenance basic library, including: The laser radar carried by the drone is used to scan the external form of the steel structure from multiple angles to obtain the geometric outline point cloud data of the steel structure; Use a portable laser scanner to scan the steel structure connection nodes and key parts in detail to collect the detailed geometric feature data of the nodes; Extract steel material specifications, strength grades, manufacturers, and installation date information from steel structure building archives to create a basic information table for steel components; Arrange strain sensors, inclination sensors and displacement sensors at key stress points of the steel structure to record the dynamic stress state data of the steel structure; Performing noise reduction processing on the point cloud data to remove abnormal points generated during the acquisition process to form a clean point cloud of the steel structure; Fusing the node detail geometric feature data with the clean point cloud to generate complete steel structure geometric data; Adding materials and historical attributes to the complete steel structure geometry data according to the steel component basic information table to construct steel structure parametric information; An association mapping is established between the dynamic stress state data of the steel structure and the parameterized information of the steel structure to obtain a digital maintenance basic library for the steel structure.

3. The BIM-based sustainable maintenance method for steel structure buildings according to claim 1 is characterized in that: The structural deformation and surface defect analysis is performed based on the component information and monitoring data in the steel structure digital maintenance basic library to obtain a steel structure health assessment report, including: Extracting structural displacement sensor data from the steel structure digital maintenance basic library, performing time series feature analysis, and obtaining a steel structure deformation trend curve; Use a high-resolution camera to capture the surface image of the steel structure, and obtain the surface texture feature map of the steel structure through image enhancement processing; Based on the steel structure surface texture feature map, the surface corrosion area and crack direction are identified by an edge detection algorithm to form a steel structure defect distribution map; Comparing the deformation trend curve of the steel structure with the theoretical force calculation value, calculating the degree of structural deformation deviation, and generating a deformation anomaly index; Calculating the corrosion area ratio and crack density of each component based on the steel structure defect distribution map to form quantitative surface damage parameters; The deformation anomaly index and the surface damage quantitative parameter are weighted by a comprehensive scoring method, the component health grade is divided, and a steel structure health assessment report is obtained.

4. The BIM-based sustainable maintenance method for steel structure buildings according to claim 1 is characterized in that: The key component data in the steel structure health assessment report is used to calculate the resource consumption and environmental impact of the maintenance plan to obtain a sustainable maintenance strategy for the steel structure, including: Filtering information on components with health grades D and E from the steel structure health assessment report to generate a list of components to be maintained; For each component in the list of components to be maintained, matching applicable maintenance technologies from the maintenance method database to form a preliminary maintenance technology combination plan; Based on the preliminary maintenance technology combination plan, calculate the amount of steel, anti-corrosion coating and construction time required for each plan to form a resource consumption data table; Based on the resource consumption data table, combined with the carbon emission coefficient of material production and construction energy consumption parameters, the carbon footprint value of the entire maintenance process is calculated to generate environmental impact assessment data; Convert the material and labor data in the resource consumption data table according to market unit prices to form a maintenance economic cost budget; By comprehensively balancing the environmental impact assessment data with the maintenance economic cost budget, and comparing the maintenance benefits with the remaining service life of the building, a sustainable maintenance strategy for the steel structure is obtained.

5. The BIM-based sustainable maintenance method for steel structure buildings according to claim 1 is characterized in that: According to the sustainable maintenance strategy for steel structures, component repair parameter settings and material configuration are performed to obtain a steel structure maintenance construction guide, including: Based on the component information in the sustainable maintenance strategy for steel structures, the geometric dimension data and damage characteristics of the components to be repaired are extracted, and the coordinates of the component repair area and the repair range boundary are determined; Based on the coordinates of the repair area, the force direction and stress distribution of the repair area are extracted from the steel structure mechanics analysis, the weak points of the components are analyzed, and a component force spectrum is formed; According to the stress map and damage characteristics of the component, suitable steel types, welding materials, and anti-corrosion coatings are selected from the material database, and the material usage is calculated to generate a repair material list; Verify the mechanical properties of the steel types in the repair material list to ensure that the bearing capacity of the repaired components meets the design requirements, and determine the geometric parameters and connection methods of the repaired components; Converting the geometric parameters of the repaired component into construction operation instructions, decomposing them into cutting parameters, welding parameters, and painting parameters to form a component repair process parameter table; Combine the component repair process parameter table with the maintenance operation process, add construction quality control points and safety precautions, draw a construction guide map, and obtain a steel structure maintenance construction guide.

6. The BIM-based sustainable maintenance method for steel structure buildings according to claim 1 is characterized in that: The steel structure maintenance construction guide is imported into the on-site terminal device for location guidance and operation identification to obtain the steel structure maintenance implementation record, including: Converting the spatial coordinate data in the steel structure maintenance construction guide into on-site positioning parameters and establishing an electronic map of the maintenance location in the on-site terminal equipment; According to the maintenance location electronic map, the on-site steel structure components are matched and scanned by target recognition technology to confirm the actual location of the components to be maintained; The actual position of the component to be maintained is marked with a virtual operation guide, and the maintenance process parameters are intuitively projected onto the surface of the component to form a visual operation instruction; The visual operation instructions are used to guide the construction personnel to complete the component repair operation, while recording the key parameters during the construction and generating a construction process data stream; Real-time monitoring of welding temperature, coating thickness, and bolt torque values in the construction process data stream is performed, compared and verified with design standards, and construction quality data is recorded; The construction quality data is integrated with photos of component maintenance completion, and the construction location and technical parameter information are associated to generate a steel structure maintenance implementation record.

7. The BIM-based sustainable maintenance method for steel structure buildings according to claim 1, characterized in that: The steel structure maintenance implementation records and original status data are compared before and after maintenance and the effect is verified to obtain a steel structure maintenance case data set, including: Extracting the component status parameters after maintenance from the steel structure maintenance implementation record, and simultaneously retrieving the component original status data before maintenance from the steel structure digital maintenance basic library to form a comparison table of data before and after maintenance; The displacement and strain data of key nodes of the steel structure after maintenance are collected again through the sensor network, compared with the structural monitoring data before maintenance, and the structural performance recovery rate is calculated; Perform high-definition imaging scans on the surface of the steel structure after maintenance, extract surface features through image processing, and compare them with the surface defect distribution map before maintenance to obtain the surface quality improvement index; Comparing the structural performance recovery rate and surface quality improvement index with the expected goals of the maintenance plan, evaluating the effectiveness of the maintenance technology, and generating technical evaluation results; Recalculate the economic cost and environmental impact of maintenance based on the actual resource consumption data in the maintenance implementation records, compare them with the budgeted values, and form a resource efficiency assessment; The technical evaluation results were integrated with the resource efficiency assessment, and the pre-maintenance condition, maintenance technology selection and maintenance effect data were correlated to establish a structural steel structure maintenance case dataset.

8. A BIM-based sustainable maintenance system for steel structure buildings, for implementing the BIM-based sustainable maintenance method for steel structure buildings as described in any one of claims 1 to 7, characterized in that: The BIM-based sustainable maintenance system for steel structure buildings includes: Integration module, used to collect steel structure geometry data and material parameters through laser scanning and sensor network, integrate steel structure 3D information, and obtain a digital maintenance base for steel structures; An analysis module is used to analyze structural deformation and surface defects based on component information and monitoring data in the steel structure digital maintenance basic library to obtain a steel structure health assessment report; A calculation module is used to calculate the resource consumption and environmental impact of the maintenance plan based on the key component data in the steel structure health assessment report to obtain a sustainable maintenance strategy for the steel structure; A configuration module is used to set component repair parameters and material configuration according to the sustainable maintenance strategy of the steel structure, and obtain a steel structure maintenance construction guide; An import module is used to import the steel structure maintenance construction guide into the on-site terminal equipment to perform location guidance and operation identification to obtain a steel structure maintenance implementation record; The verification module is used to compare the steel structure maintenance implementation records and original status data before and after maintenance and verify the effect to obtain a steel structure maintenance case data set.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and is characterized in that when the processor executes the computer program, the method for sustainable maintenance of steel structure buildings based on BIM according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor is caused to execute the BIM-based sustainable maintenance method for steel structure buildings according to any one of claims 1 to 7.

Images