Graph-free construction method for simply supported girder bridge

Abstract

The invention discloses a simply supported girder bridge graph-free construction method which comprises the following steps: receiving a simply supported girder bridge BIM model delivered in a design stage, analyzing to obtain a girder body size, reinforcing steel bar processing parameters, material information and structure feature point coordinates, and binding analysis data and component EBS codes for storage; extracting coordinates of feature points of the structure, driving the intelligent total station to perform lofting, and calibrating deviation in real time through double guidance of augmented reality and laser indication; a standardized machining list is generated based on the steel bar machining parameters, and numerical control equipment is driven to automatically conduct steel bar machining operation and associate EBS codes; 4D simulation is carried out based on the BIM model, and an optimal construction scheme is generated through construction period-cost-safety risk weighted analysis; and a construction progress plan is extracted based on the optimal construction scheme, and a material demand plan is generated and intelligently distributed. According to the method, design and construction full-process data closed-loop driving is achieved, the dependence bottleneck of a traditional drawing is broken through, and the construction precision, the cooperation efficiency and the quality controllability are remarkably improved.

Description

Technical Field

[0001] This invention belongs to the field of bridge engineering construction technology, and in particular relates to a method for constructing simply supported beam bridges without drawings. Background Technology

[0002] In the field of bridge engineering construction, simply supported beam bridges are widely used in infrastructure construction such as highways, railways, and municipal transportation due to their simple structural form, clear stress distribution, and convenient construction. Traditional construction methods for simply supported beam bridges rely heavily on design drawings. From foundation construction and prefabrication of beams to on-site scaffolding, detailed paper or electronic drawings are required as the core guiding principles for each stage.

[0003] However, this construction model relying on drawings has revealed numerous problems in practical application. On the one hand, the construction layout stage requires technicians to repeatedly compare data with drawings for conversion and on-site annotation, which is not only time-consuming and labor-intensive but also prone to insufficient layout accuracy due to human error, affecting the subsequent construction quality. On the other hand, during the process of process selection, due to the limitations of the information in the drawings, technicians find it difficult to quickly and comprehensively obtain the adaptability parameters of different construction processes, often needing to rely on experience for judgment, which may lead to suboptimal process selection, increased construction costs, or extended construction periods. Simultaneously, material reporting relies on the material usage list in the drawings, but changes in geological conditions and environmental factors during actual construction often lead to discrepancies between material requirements and the design drawings. If adjustments are not made in a timely manner, material waste or supply shortages can easily occur. In the quality acceptance and work completion assessment stages, the traditional model requires quantity calculation and quality evaluation based on drawings. Because the process of verifying the information in the drawings with the actual on-site construction conditions is cumbersome, inconsistencies in data and low acceptance efficiency often occur, affecting the progress of the project.

[0004] In recent years, although there have been some attempts at drawing-free construction within the industry, significant limitations exist:

[0005] (1) Information fragmentation: Data in the design, construction and operation and maintenance phases are isolated from each other. The BIM model is only used for design visualization and cannot be deeply integrated with business links such as construction layout and steel bar processing, resulting in the model data being unable to effectively guide actual construction.

[0006] (2) The process is not closed: the completed delivery data is mostly unstructured documents (such as scanned copies of paper acceptance reports), lacking connection with the design model. The construction process data cannot be reused in the operation and maintenance phase, making it difficult to support intelligent detection and maintenance decisions.

[0007] (3) Insufficient accuracy: It still relies on manual calculation of layout data and setting of steel bar processing parameters. The error is generally above ±10mm, and the construction accuracy of key components (such as supports and prestressed ducts) is difficult to guarantee.

[0008] (4) Limited efficiency improvement: Digital tools are only introduced in a single link (such as precast beam production), without achieving full-process collaboration. The shortening of the construction period is usually less than 5%, and there is a tendency for gaps to appear in the connection between various processes.

[0009] With the ever-increasing demands for efficiency, precision, and intelligence in modern engineering construction, traditional blueprint-based construction methods and existing fragmented, blueprint-free approaches are no longer sufficient to meet the needs of rapid, high-quality construction of simply supported beam bridges. Therefore, developing a blueprint-free construction model that integrates foundation, prefabrication, and track laying processes, encompassing the entire process from construction layout and process comparison to material submission, quality acceptance, and cost assessment, has become a key direction for addressing current construction challenges and promoting the upgrading of simply supported beam bridge construction technology. Summary of the Invention

[0010] To address the aforementioned problems, embodiments of the present invention provide a method for constructing a simply supported beam bridge without drawings, the method comprising:

[0011] Receive the BIM model of the simply supported beam bridge delivered during the design phase, analyze and obtain the beam dimensions, steel reinforcement processing parameters, material information and structural feature point coordinates, and bind and store the analyzed data with the component EBS code;

[0012] Extract the coordinates of feature points of the structure, drive the intelligent total station to lay out, and calibrate the deviation in real time through dual guidance of augmented reality and laser pointer;

[0013] A standardized processing list is generated based on the steel bar processing parameters, which drives the CNC equipment to automatically perform steel bar processing operations and associates them with EBS codes.

[0014] Based on the BIM model, 4D simulation is performed, and the optimal construction plan is generated through weighted analysis of schedule, cost, and safety risks.

[0015] Based on the optimal construction scheme, the construction schedule plan is extracted, the material demand plan is generated, and intelligent delivery is carried out.

[0016] Real-time collection of construction data and dynamic adjustment of process parameters in the optimal construction plan;

[0017] Acceptance units are divided according to EBS codes, and on-site parameters are compared with model standards using intelligent image recognition technology to generate acceptance results and automatically calculate prices.

[0018] Integrate the data to form a structured as-built model that supports EBS coding traceability.

[0019] Furthermore, the method for analyzing the steel bar processing parameters includes:

[0020] The spatial coordinates of the reinforcing bars in the BIM model are converted into vector processing paths that can be executed by CNC equipment; the risk of reinforcing bar collision is detected through spatial topology analysis, and when the risk exceeds the safety threshold, batch processing instructions are automatically generated and avoidance paths are planned; a set of processing instructions containing timing control is generated based on the bending angle parameters.

[0021] Furthermore, the weighted analysis includes:

[0022] The system normalizes indicators for project duration, cost, and safety risks; dynamically adjusts weight allocation based on real-time environmental risk levels; and automatically rejects the current plan and generates a set of alternative plans when the safety risk level rises to a preset warning value.

[0023] Furthermore, the material requirements planning and intelligent delivery includes:

[0024] Construct a material supply and demand gap calculation model and integrate construction progress and inventory data in real time; when it is identified that the supplier response cycle exceeds the tolerance limit of the construction period, automatically activate a multi-level response mechanism: prioritize the search of the backup supplier database to generate an expedited order; if no supplier is available, trigger the strategic reserve material mobilization agreement.

[0025] Furthermore, the dynamic adjustment method includes:

[0026] Establish a mapping relationship database between abnormal process parameters and quality defects; when the construction parameters monitored in real time trigger the early warning rules in the mapping relationship database, automatically generate a process adjustment instruction; the process adjustment instruction can only be executed after passing the compliance verification of construction specifications.

[0027] Furthermore, the implementation method of the intelligent image recognition technology includes:

[0028] The convolutional neural network synchronously extracts features such as rebar spacing, protective layer thickness, and surface defects; when the feature recognition confidence level is lower than a set threshold, it automatically requests manual review and labels learning samples; and updates the neural network weights online based on the review results.

[0029] Furthermore, the method for executing the automatic pricing includes:

[0030] It monitors building material market price fluctuation signals in real time; when the price fluctuation of main materials exceeds the threshold agreed in the contract, it automatically switches to the current information price to re-price; the pricing result is linked with the acceptance data to generate tamper-proof electronic reports.

[0031] Furthermore, the method for constructing the structured as-built model includes:

[0032] Each optimization record of the construction plan is associated with the version of the sensor data package that triggered the optimization; a multi-dimensional data traceability channel is constructed according to EBS encoding, including a design parameter traceability channel, a process adjustment decision chain, a quality acceptance evidence set, and a cost change trajectory.

[0033] Furthermore, the execution method of the multidimensional data traceability channel includes:

[0034] When a quality defect query request is received, the process adjustment records associated with the process are traced back along the multi-dimensional traceability channel; the root cause of the defect is analyzed based on the comparison of solution versions, and optimization decision suggestions are output.

[0035] A method for constructing a simply supported beam bridge without drawings, the method further includes:

[0036] A drone equipped with a laser scanning module automatically flies along the beam axis to collect key feature point cloud data; the point cloud registration algorithm is used to compare the on-site point cloud with the BIM model to identify positioning deviations; a three-dimensional deviation heat map is generated and fed back to the construction management platform in real time to drive the dynamic calibration of the layout coordinates.

[0037] The technical effects and advantages of the no-drawing construction method for simply supported beam bridges provided by this invention are as follows:

[0038] This invention enables closed-loop data-driven design and construction processes, breaking through the bottleneck of traditional reliance on drawings and significantly improving construction accuracy, collaborative efficiency, and quality controllability. This invention binds BIM models with EBS coding, creating a direct channel from design parameters to construction layout, material processing, and schedule control. This eliminates information fragmentation across stages, automatically converting design model analysis data into CNC machining instructions and total station layout coordinates, avoiding the errors of manual calculations and the time-consuming process of repeated drawing verification in traditional methods. It integrates a dual verification mechanism of intelligent total station laser guidance and UAV point cloud verification, enabling dynamic deviation correction for key components such as embedded supports, solving the problem of accumulated errors in manual layout under complex environments, and significantly improving accuracy control compared to traditional methods. A 4D simulation-based multi-objective optimization model of schedule, cost, and safety risk dynamically adjusts weight allocation based on real-time environmental monitoring data, achieving adaptive iteration of process solutions. A material supply and demand gap model links construction progress and inventory data, intelligently resolving supply chain disruptions through a multi-level response mechanism. A mapping database of abnormal process parameters and quality defects is established, allowing real-time monitoring of parameter deviations during key processes such as concrete curing and tensioning, automatically triggering compensation commands to reduce quality defects such as beam cracks. Attached Figure Description

[0039] Figure 1 This is a flowchart of a construction method for a simply supported beam bridge without drawings, as shown in Example 1.

[0040] Figure 2 This is a flowchart of a construction method for a simply supported beam bridge without drawings, as shown in Example 2.

[0041] Figure 3 This is a schematic diagram illustrating the data flow of each stage in the construction method of a simply supported beam bridge without drawings. Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] Example 1:

[0044] Please see Figure 1 As shown, an embodiment of the present invention provides a method for construction of a simply supported beam bridge without drawings, which realizes a closed loop of design and construction data linkage based on a construction management platform, including the following steps:

[0045] S1: Receive the BIM model of the simply supported beam bridge delivered during the design phase, analyze and obtain the beam dimensions, steel reinforcement processing parameters, material information and structural feature point coordinates, and bind and store the analyzed data with the component EBS code;

[0046] S2: Extract the coordinates of the structural feature points from step S1, drive the intelligent total station to lay out, and calibrate the deviation in real time through dual guidance of augmented reality and laser pointer;

[0047] S3: Generate a standardized processing list based on the steel bar processing parameters in step S1, drive the CNC equipment to automatically perform steel bar processing operations and associate EBS codes;

[0048] S4: Based on the BIM model, perform 4D simulation and generate the optimal construction plan through weighted analysis of schedule, cost and safety risks;

[0049] S5: Based on the optimized construction scheme in step S4, extract the construction schedule plan, generate the material demand plan, and intelligently deliver the materials;

[0050] S6: Real-time acquisition of construction data from step S5 and dynamic adjustment of process parameters in the optimal construction scheme;

[0051] S7: Divide acceptance units according to EBS codes, compare on-site parameters with model standards through intelligent image recognition technology, generate acceptance results and automatically calculate prices;

[0052] S8: Integrate data to form a structured as-built model that supports EBS coding traceability.

[0053] The data integrated in S8 includes the design data from S1, the preferred construction scheme from step S4, the optimization records from step S6, and the acceptance and pricing data from step S7.

[0054] Analyzing key parameters in the BIM model of a simply supported beam bridge, including:

[0055] Beam dimensions (span, cross-sectional dimensions, camber, etc.);

[0056] Rebar processing parameters (type, quantity, spacing, spatial coordinates, etc.);

[0057] Material information (concrete strength grade, prestressed steel strand specifications, etc.);

[0058] Coordinates of structural feature points (component mileage, coordinates, elevation, etc.).

[0059] The analysis of rebar processing parameters is achieved through secondary development of BIMBase. The platform adds a function to output bridge pile foundation positioning information, which can directly output the spatial coordinate positioning information of rebar (accuracy ±1mm). The analyzed information is associated with the platform database and bound with the EBS code of the corresponding component to form a digital foundation for construction. The transmission between the design model and the platform adopts the railway IFC Alignment 1.0 standard and expands the railway engineering-specific attribute set (such as the pre-camber of simply supported beams and the spatial coordinates of rebar) to ensure lossless transmission of geometric and attribute information.

[0060] In step S2, the three-dimensional coordinates of structural feature points (such as the corner points of the abutment, the apex of the pier, the position of the beam support, etc.) are extracted from the BIM model, and the coordinate data is sent to a smart total station with a 5G module (with a built-in dedicated layout program) via 5G / Bluetooth.

[0061] The construction management platform and the total station use remote network data transmission to synchronize layout data in real time. The station information, layout coordinates, and accuracy information of the measurement and layout are temporarily recorded and stored in the total station. When the equipment is offline or the network is interrupted, the stored data can be used to continue the layout. After the network is restored, the data is automatically re-transmitted to the platform.

[0062] During the layout process, a dual guidance system of "AR overlay + laser indication" is employed. This includes: a tablet app (connected to the total station via Bluetooth) overlays virtual target points from the BIM model onto the actual site, displaying real-time deviations in the X, Y, and Z axes (e.g., "X: +1.2mm →" indicates a 1.2mm adjustment to the right). Simultaneously, the total station emits a laser beam pointing to the target point, and construction personnel use the deviation data and laser placement to complete the positioning. The layout results are fed back to the platform in real time and compared with the model coordinates. When the deviation exceeds a preset threshold (default ±3mm, ±2mm for critical components), the platform automatically issues an audible and visual warning, with the deviation data changing from green to yellow (approaching the threshold) and then to red (exceeding the threshold).

[0063] In step S3, the steel reinforcement processing stage, the spatial location data of the steel reinforcement in the BIM model is first intelligently analyzed. Specifically, the system automatically converts the geometric coordinates of each steel reinforcement in the 3D model (e.g., the curved coordinates of the main reinforcement of the beam) into a vector processing path that can be recognized by the CNC bending machine. This path accurately describes the feed direction and bending point of the steel reinforcement on the processing platform. Subsequently, through a spatial topology analysis algorithm, the system automatically detects possible physical interference within the steel reinforcement group (e.g., the spacing between adjacent stirrup hooks is too small). When the collision risk probability exceeds a preset safety threshold (e.g., a node is detected to have a collision risk of more than 15%), the system will automatically split the reinforcement. The system generates process batches and avoidance path instructions, such as prioritizing the processing of the bottom layer of steel mesh and then processing the upper layer of steel mesh that intersects it after it is moved out of the work area. At the same time, for the bending angle characteristics of each steel bar (such as a 135° seismic hook), the system generates a processing instruction set containing timing control. This processing instruction set not only includes bending angle parameters, but also embeds process control logic (for example, when performing a 90° bend on a 28mm diameter HRB400 steel bar, the system automatically sets a 2-second holding time to prevent springback). In the final standardized processing list, all processing instructions are dynamically associated with the EBS code of the corresponding component to ensure the traceability of subsequent construction.

[0064] In the construction scheme optimization stage of step S4, the 4D simulation of the BIM model by the system will be simultaneously connected to the real-time environmental monitoring module. Based on the BIM model, a construction process simulation scenario will be built, and different construction schemes (such as beam erection method, formwork system, pouring sequence, etc.) will be imported. Combined with constraints such as construction period, cost, and safety, the feasibility of each scheme will be compared through 4D simulation (which refers to adding a time dimension to the three-dimensional BIM model to simulate the progress and resource input of the construction process).

[0065] The platform automatically extracts quantitative indicators for each scheme: construction period (such as precast beam production cycle, on-site erection efficiency), cost (material loss, machinery rental cost), and safety risk value (such as high-altitude operation time, support settlement warning value). It calculates the comprehensive score of the scheme through a weighted analysis method (construction cost weight 40%, cost weight 30%, safety weight 30%) and selects the scheme with the highest score.

[0066] The platform provides visual instructions for the optimal solution and generates a 3D work instruction manual (including process steps, key parameters, and quality control points). During construction, the platform dynamically adjusts process parameters based on on-site feedback data (such as concrete pouring speed and formwork deformation). For example, when the formwork deformation exceeds ±1mm, the platform automatically suggests adjusting the pouring sequence to achieve continuous process optimization.

[0067] When the real-time environmental monitoring module detects a change in risk level (such as wind speed increasing from level 4 to level 6), the system automatically increases the safety weight ratio (e.g., from the base value of 30% to 50%), while correspondingly reducing the weights of construction period and cost. If the safety risk level exceeds the preset warning value (e.g., a red rainstorm warning triggers an 80% risk threshold), the system will immediately reject the current construction plan and intelligently generate a set of alternative plans based on the historical database (e.g., replacing the high-altitude hoisting plan with a ground assembly plan). The entire process achieves closed-loop optimization through a three-dimensional weighted scoring model of construction period, cost, and safety. The final output of the optimal construction plan not only meets the requirements of dynamic risk management but also enables precise resource allocation through the schedule plan in step S5.

[0068] In the material delivery phase of step S5, the system, based on the schedule extracted from the optimized construction plan (e.g., the concrete pouring of pier No. 2 needs to be completed in the 3rd week), achieves precise control through a dynamically constructed material supply and demand gap calculation model. This model integrates two key data in real time: one is the actual on-site construction progress reported in step S6 (e.g., a 20% increase in rebar tying efficiency leading to earlier concrete demand), and the other is warehouse inventory data collected by IoT sensors (e.g., the current cement reserves are only sufficient for 3 days). When the model identifies supply chain risks, especially when the supplier's standard response cycle exceeds the tolerance limit for the construction period (e.g., a supplier of a certain type of bearing typically requires 15 days for delivery, but the process tolerance only allows for a 10-day delay), the system immediately activates a multi-level response mechanism, including:

[0069] First, the pre-set backup supplier database is searched, an expedited order is automatically generated, and a premium procurement agreement is activated (e.g., paying a 20% expedited fee to backup supplier B). If the database shows no available suppliers (e.g., extreme weather causing regional stockouts), the project's strategic reserve material mobilization agreement is triggered, and materials are directly allocated from the agreement reserve warehouse (e.g., mobilizing prestressed steel strands from a neighboring section's reserve). All allocation instructions are bound to specific components through EBS codes, ensuring that the material delivery trajectory is traceable back to the as-built model in step S8. Based on the priority of construction procedures, the platform intelligently schedules transportation equipment to achieve precise delivery of materials to the work site according to plan, reducing the amount of materials piled up on site.

[0070] In the dynamic optimization of the construction process in step S6, the system compares the real-time collected construction data (such as concrete vibration frequency and formwork installation accuracy) with the pre-set mapping relationship database of abnormal process parameters and quality defects. This database is built based on historical engineering big data and establishes corresponding rules for key process deviations and potential quality problems (for example, when the prestressed tension fluctuation exceeds ±5%, the probability of beam crack risk increases to 25%). When the real-time data of the sensor triggers the early warning rule (such as the humidity of a section of the beam curing environment being lower than the design value of 60% for 2 consecutive hours), the system automatically generates process adjustment instructions (such as starting the spray system to increase humidification to 75%).

[0071] Based on the BIM model decomposed structure (EBS), acceptance units are divided, and the quality standards for each unit are clearly defined (such as rebar spacing 15±2cm, concrete strength ≥C50). During acceptance, the supervisors retrieve the model information and acceptance standards of the corresponding unit through a mobile terminal, and use intelligent image recognition technology to capture on-site images and automatically measure actual parameters (such as rebar spacing and protective layer thickness).

[0072] Acceptance data is uploaded to the platform in real time and automatically compared with quality standards. Once qualified, an electronic acceptance report is generated (linked to component EBS codes and acceptance personnel information). Non-conformities automatically trigger the rectification process. The platform pushes rectification notices to the construction team and tracks the rectification progress. After rectification is completed, acceptance data must be re-uploaded until the process is closed and qualified.

[0073] In the acceptance phase of step S7, the system acquires component images in real time through intelligent image acquisition equipment (such as high-precision industrial cameras) deployed at the construction site. Based on a pre-trained convolutional neural network model, it simultaneously extracts three key acceptance features: rebar mesh spacing (e.g., allowable deviation of main bar spacing ±10mm), concrete cover thickness (e.g., detection error zone ±5mm for a design value of 40mm), and surface defects (e.g., identification of cracks with a width exceeding 0.2mm).

[0074] When the confidence level of feature recognition is lower than the preset threshold (e.g., the confidence level of a protective layer thickness detection result is only 65%, which is lower than the 85% acceptance decision threshold), the system automatically triggers a manual review request on the acceptance interface and marks the image as a sample to be learned and pushes it to the engineer's terminal. The judgment result entered by the engineer after on-site review (e.g., confirming that the actual protective layer thickness is 38mm) will update the neural network weights online in real time, such as strengthening the recognition ability of the shadow features of rebar positioning. The hierarchical relationship definition of EBS coding includes: Project > Unit Project > Sub-project > Item Project > Component. EBS coding and BIM components adopt a one-to-one mapping rule, that is, each BIM component corresponds to a unique EBS code. The platform associates BIM model components with EBS codes one by one and clarifies the unit price of each component. The updated model is immediately applied to the acceptance of subsequent similar components (e.g., all edge beams with EBS codes starting with "B1-"), forming a closed-loop optimization mechanism of "recognition-verification-learning".

[0075] In the automatic pricing stage of step S7, the system monitors price fluctuation signals in real time (such as rebar futures index and cement regional listed price) by connecting to the building materials market data platform. When the price fluctuation of the main material exceeds the threshold agreed in the contract (for example, the monthly increase in the unit price of steel bars reaches ±5%), the system automatically triggers the repricing mechanism: the original contract benchmark price is replaced by the information price released by the government in the current period (such as the "Construction Project Cost Information" for the current month of construction), and the acceptance data in step S7 (such as the steel bar usage of the beam with EBS code "G2-05" that has been accepted) is used for dynamic pricing. This process embeds triple anti-tampering protection, namely, the pricing formula call record, the information price version timestamp and the acceptance data hash value are jointly encrypted to generate electronic reports. For example, after a batch of concrete is repriced due to the increase in the price of sand and gravel, the report will simultaneously record the image characteristics of the material acceptance (corresponding to the crack detection results) and the adjusted settlement amount. The final structured data is directly synchronized to the as-built model in step S8.

[0076] A unified data platform was built to integrate data from the entire process, including design models, construction records, quality data, and pricing information. Information confidentiality and security requirements (including data encryption and hierarchical access control) were implemented in accordance with T / CRBIM 003-2015 "Railway Engineering Information Model Data Storage Standard (Version 1.0)".

[0077] All participating parties (design, construction, supervision, and construction units) can access the platform through access control to achieve real-time data sharing. In the user management module of the railway engineering geological results data service system, user accounts can be added, user information can be edited, and user operation permissions can be set (such as construction personnel can only view data for their own process, and supervisors can view acceptance data).

[0078] Establish a data traceability mechanism, which allows users to query the entire lifecycle information from design to construction (such as design parameters, processing records, and acceptance results) through the unique EBS code of each component; utilize big data analytics to identify optimization points in the construction process (such as a high processing loss rate for a certain type of steel bar, suggesting adjustments to the processing technology) and provide experience data for subsequent projects.

[0079] Methods for constructing structured as-built models include:

[0080] Each optimization record of the construction plan is associated with the version of the sensor data package that triggered the optimization; a multi-dimensional data traceability channel is constructed according to EBS encoding, including a design parameter traceability channel, a process adjustment decision chain, a quality acceptance evidence set, and a cost change trajectory.

[0081] In step S8, when constructing the structured as-built model, the system establishes a full lifecycle data traceability architecture through the EBS coding system. Taking the pier component numbered "P3-12" in a bridge project as an example, its as-built model includes the following interrelated data dimensions:

[0082] Design parameter traceability channel:

[0083] Link the original BIM design data from step S1 (e.g., concrete strength grade C40, design value of steel reinforcement cover thickness 45mm), and record the design change version (e.g., adjustment of reinforcement ratio in BIM model V1.2). Process adjustment decision chain:

[0084] Embedded dynamic optimization process record:

[0085] Environmental sensor data package V2.3 (including temperature 28℃ / humidity 60% monitoring value), triggered process instructions (adjustment instruction to increase maintenance humidity to 75%), risk warning events (such as the ground assembly scheme activated during the Typhoon Mangkhut warning).

[0086] Quality acceptance evidence set:

[0087] The results of the intelligent recognition are bound to the image of the rebar spacing detection (measured value 202mm and design value 200mm), the crack recognition report (maximum crack width 0.18mm), and the material acceptance record (cement 28-day strength test report number CT2023-0876).

[0088] Cost change trajectory:

[0089] Record automatic pricing events, namely the initial contract price (comprehensive unit price of steel bars of 4850 yuan / ton), the price fluctuation trigger point (the market price monthly increase of 7.2% exceeds the threshold), and the re-pricing result (calculated based on the information price of 5180 yuan / ton in the current month).

[0090] Data across all dimensions is dynamically correlated through a version control mechanism. When the material delivery system updates the mix proportions of a certain batch of concrete (due to substandard aggregate gradation), this event will be updated simultaneously.

[0091] Process decision chain (record mix ratio adjustment instruction number MD2023-0412);

[0092] Cost trajectory (triggered by concrete unit price increasing from 350 yuan / m³) 3 Change to 368 yuan / m 3 );

[0093] Quality evidence set (with simultaneous updates to the strength test report for this batch of test blocks);

[0094] The final generated as-built model supports traceability; for example, querying "P3-12 pier cost data" can be expanded layer by layer.

[0095] (1) Current total settlement price → (2) Steel reinforcement price adjustment details → (3) Price adjustment basis (provincial information price) → (4) Related construction period (2023.08.15-08.28) → (5) Concurrent process records (humidity control instructions) → (6) Original design parameters (BIM model component attributes); forming a complete evidence chain covering "design-construction-acceptance-cost", all data versions are verified by blockchain hash value to ensure immutability, and information confidentiality and security requirements (including data encryption and hierarchical management of permissions) are implemented in accordance with T / CRBIM 003-2015 "Railway Engineering Information Model Data Storage Standard (Version 1.0)".

[0096] After the structured as-built model was put into operation, when the engineering management personnel discovered a 0.25mm excessive crack in the pier component "P3-12" and submitted a query request, the system immediately activated the full-process data traceability mechanism. First, it located the process adjustment decision chain of the component through EBS coding and automatically extracted all key operation records during construction: the system retrieved the dynamic optimization log and found that on August 20, 2023, the humidity was lower than the threshold (60% measured vs. 65% standard value) due to environmental sensors, triggering a compensation instruction to increase the curing humidity to 75%; at the same time, it linked the typhoon warning event record, showing that on August 25 of the same year, the concrete pouring was interrupted for 4 hours due to excessive wind speed.

[0097] The system then performed a comparative analysis of the scheme versions: the standard curing process specified in the original design scheme (version BIM_V1.0) was compared with the emergency scheme actually implemented during the typhoon (version EXE_V4.5) using three-dimensional parameters. The analysis revealed that during actual construction, the humidity compensation coefficient was only 92% of the set value due to the typhoon (actual K=1.08, required K=1.15), resulting in a 12% decrease in the early strength development rate of concrete. At this time, cross-validation of material delivery data confirmed that the temperature of the cement batch used that day reached 32℃ upon arrival, which, although cooling measures had been taken, still exceeded the specification limit.

[0098] Based on multi-dimensional data coupling analysis, the system identified the root cause of the cracks as the combined effect of insufficient humidity compensation and excessive material temperature under extreme typhoon weather. The system automatically output two actionable decision suggestions: first, increase the humidity compensation coefficient for similar working conditions to 1.25; second, add a high-temperature cement-specific retarder feeding procedure.

[0099] The entire analysis process generates a tamper-proof report, in which the crack location coordinates (X: 125.6, Y: 88.3) are directly linked to the original acceptance image, and the material cost data is synchronously cited to support the price fluctuation monitoring records (proving that non-cost control factors caused the process defects), forming a legally valid basis for determining technical responsibility.

[0100] Example 2:

[0101] like Figure 2 As shown, this embodiment further improves upon the design of Embodiment 1. The difference is that in actual operation of Embodiment 1, it was found that the total station signal was easily blocked under complex terrain, leading to accumulated coordinate offsets and causing excessive installation deviations in key components (such as embedded parts for supports), failing to meet high-precision positioning requirements. Based on this, a drawing-free construction method for simply supported beam bridges is proposed:

[0102] S2.1: The drone equipped with the laser scanning module flies automatically along the beam axis to collect key feature point cloud data (such as the three-dimensional coordinates of the anchor bolt hole group of the support); the point cloud registration algorithm is used to compare the on-site point cloud with the BIM model to identify positioning deviations (for example, the X-direction deviation of the embedded plate of support No. 3 is detected); a three-dimensional deviation heat map is generated and fed back to the construction management platform in real time to drive the dynamic calibration of the layout coordinates.

[0103] After the total station layout is completed in step S2, the system automatically activates the UAV verification mechanism. The UAV, equipped with a high-precision laser scanner, flies autonomously along the design axis of the beam and performs three-dimensional point cloud scanning on key structural feature points (such as the anchor bolt hole group of the support). The scanned data is matched and compared with the BIM design model imported in step S1 through the point cloud registration engine of the construction management platform (this coordinate system follows the railway IFC Alignment 1.0 standard). When a positioning deviation is detected (for example, a measurable displacement occurs in the embedded plate of the support of pier No. 3), the system generates a three-dimensional deviation heat map and pushes it to the construction terminal in real time.

[0104] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

[0105] The above description is merely a preferred embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present application, based on the technical solution and concept of the present application, should be covered within the scope of protection of the present application.

Claims

1. A method for constructing a simply supported beam bridge without drawings, characterized in that the method... include: Receive the BIM model of the simply supported beam bridge delivered during the design phase, analyze and obtain the beam dimensions, steel reinforcement processing parameters, material information and structural feature point coordinates, and bind and store the analyzed data with the component EBS code; Extract the coordinates of feature points of the structure, drive the intelligent total station to lay out, and calibrate the deviation in real time through dual guidance of augmented reality and laser pointer; A standardized processing list is generated based on the steel bar processing parameters, which drives the CNC equipment to automatically perform steel bar processing operations and associates them with EBS codes. Based on the BIM model, 4D simulation is performed, and the optimal construction plan is generated through weighted analysis of schedule, cost, and safety risks. Based on the optimal construction scheme, the construction schedule plan is extracted, the material demand plan is generated, and intelligent delivery is carried out. Real-time collection of construction data and dynamic adjustment of process parameters in the optimal construction plan; Acceptance units are divided according to EBS codes, and on-site parameters are compared with model standards using intelligent image recognition technology to generate acceptance results and automatically calculate prices. Integrate the data to form a structured as-built model that supports EBS coding traceability.

2. The method for constructing a simply supported beam bridge without drawings according to claim 1, characterized in that, The analytical methods for the steel bar processing parameters include: The spatial coordinates of the reinforcing bars in the BIM model are converted into vector processing paths that can be executed by CNC equipment; the risk of reinforcing bar collision is detected through spatial topology analysis, and when the risk exceeds the safety threshold, batch processing instructions are automatically generated and avoidance paths are planned; a set of processing instructions containing timing control is generated based on the bending angle parameters.

3. The method for constructing a simply supported beam bridge without drawings according to claim 1, characterized in that, The weighted analysis includes: The system normalizes indicators for project duration, cost, and safety risks; dynamically adjusts weight allocation based on real-time environmental risk levels; and automatically rejects the current plan and generates a set of alternative plans when the safety risk level rises to a preset warning value.

4. The method for constructing a simply supported beam bridge without drawings according to claim 1, characterized in that, The aforementioned material requirements planning and intelligent delivery includes: Construct a material supply and demand gap calculation model and integrate construction progress and inventory data in real time; when it is identified that the supplier response cycle exceeds the tolerance limit of the construction period, automatically activate a multi-level response mechanism: prioritize the search of the backup supplier database to generate an expedited order; if no supplier is available, trigger the strategic reserve material mobilization agreement.

5. The method for constructing a simply supported beam bridge without drawings according to claim 1, characterized in that, The dynamic adjustment method includes: Establish a mapping relationship database between abnormal process parameters and quality defects; when the construction parameters monitored in real time trigger the early warning rules in the mapping relationship database, automatically generate a process adjustment instruction; the process adjustment instruction can only be executed after passing the compliance verification of construction specifications.

6. The method for constructing a simply supported beam bridge without drawings according to claim 1, characterized in that, The implementation method of the intelligent image recognition technology includes: The convolutional neural network synchronously extracts features such as rebar spacing, protective layer thickness, and surface defects; when the feature recognition confidence level is lower than a set threshold, it automatically requests manual review and labels learning samples; and updates the neural network weights online based on the review results.

7. The method for constructing a simply supported beam bridge without drawings according to claim 1, characterized in that, The method for executing the automatic pricing includes: It monitors building material market price fluctuation signals in real time; when the price fluctuation of main materials exceeds the threshold agreed in the contract, it automatically switches to the current information price to re-price; the pricing result is linked with the acceptance data to generate tamper-proof electronic reports.

8. The method for constructing a simply supported beam bridge without drawings according to claim 1, characterized in that, The method for constructing the structured as-built model includes: Each optimization record of the construction plan is associated with the version of the sensor data package that triggered the optimization; a multi-dimensional data traceability channel is constructed according to EBS encoding, including a design parameter traceability channel, a process adjustment decision chain, a quality acceptance evidence set, and a cost change trajectory.

9. A method for constructing a simply supported beam bridge without drawings according to claim 8, characterized in that, The execution method of the multidimensional data traceability channel includes: When a quality defect query request is received, the process adjustment records associated with the process are traced back along the multi-dimensional traceability channel; the root cause of the defect is analyzed based on the comparison of solution versions, and optimization decision suggestions are output.

10. A method for constructing a simply supported beam bridge without drawings according to claim 1, characterized in that, The method also includes: A drone equipped with a laser scanning module automatically flies along the beam axis to collect key feature point cloud data; the point cloud registration algorithm is used to compare the on-site point cloud with the BIM model to identify positioning deviations; a three-dimensional deviation heat map is generated and fed back to the construction management platform in real time to drive the dynamic calibration of the layout coordinates.

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