Steel structure high-precision prefabrication construction method

Abstract

The invention discloses a steel structure high-precision prefabrication construction method, and relates to the technical field of steel structure construction. The method comprises the six steps of construction early-stage preparation, three-dimensional collaborative deepening modeling, prefabricated part precision machining, module pre-assembly precision control, dynamic precision monitoring and feedback and finished product acceptance and delivery. Data standardization management is achieved by building a construction database, three-dimensional modeling and typesetting optimization are completed through Tekla Structures and kernel master software, automatic machining is achieved in combination with a numerical control cutting machine and a welding robot, precision control is conducted through simulation pre-assembly software and a total station, and whole-process dynamic feedback is achieved through an Internet of Things monitoring system. According to the method, the problems of design and machining disjoint, low precision and poor efficiency in the prior art are solved, the component cutting error is smaller than or equal to + / -0.3 mm, the welding deformation is smaller than or equal to 0.5 mm / m, the pre-assembly first-pass yield is larger than or equal to 98%, the comprehensive cost is reduced by 32%, and the method is suitable for factory prefabrication of various steel structure projects and has remarkable economic and social benefits.

Description

Technical Field

[0001] This invention relates to the field of steel structure construction technology, and in particular to a high-precision prefabrication construction method for steel structures. Specifically, it relates to a high-precision prefabrication construction method for steel structures that integrates three-dimensional modeling, CNC machining and dynamic monitoring, and is applicable to the factory prefabrication production of various steel structure components such as industrial plants, high-rise buildings, and bridge projects. Background Technology

[0002] With the accelerated industrialization and digital transformation of my country's construction industry, steel structures, with their outstanding advantages such as high material strength, short construction cycle, and good environmental friendliness, are increasingly widely used in engineering fields such as industrial plants, super high-rise buildings, and long-span bridges. According to the "2024 China Steel Structure Industry Development Report" released by the China Steel Structure Association, my country's total steel structure output reached 128 million tons in 2023, a year-on-year increase of 9.1%, of which the proportion of factory-prefabricated steel structures increased to 68%, an increase of 25 percentage points compared with 2020. Prefabrication of steel structures has become a core path to promote the high-quality development of the construction industry, and its core technological demands focus on improving component processing accuracy, shortening production cycles, and reducing overall costs through digital means.

[0003] In existing technologies, prefabricated steel structure construction mainly relies on traditional processing methods, such as the steel structure installation method disclosed in Chinese patent application CN107246072A. This method includes: fabricating templates based on the number of steel structure columns and the dimensions of the column base plates; laying out pre-reserved holes according to the installation locations of the steel structure, and placing anchor bolts in each pre-set hole; installing the templates onto the anchor bolts in each pre-reserved hole, and adjusting the anchor bolts with templates to their pre-set positions; grouting the anchor bolts in their pre-set positions; after the grout meets the pre-set conditions, removing the templates, hoisting the steel structure onto the anchor bolts, and tightening the anchor bolts; and performing secondary grouting on the base plates of the steel structure columns to complete the steel structure installation. While this method, which combines manual layout with ordinary machine tool processing, improves production efficiency to some extent, it has the following significant drawbacks: 1. Disconnect between design and manufacturing data transmission: In this traditional method, design drawings need to be manually broken down into manufacturing sketches by technicians, and then laid out on-site using tools such as measuring tapes and chalk lines. During this process, errors from manual drawing interpretation and layout operations accumulate, resulting in dimensional deviation rates of 4%-6% for complex node components. Construction data from a heavy industrial building project shows that the rework rate of components caused by such errors reached 15%, resulting in direct economic losses exceeding 3 million yuan for a single project, and severely impacting on-site installation progress. 2. Manufacturing accuracy is significantly affected by human factors: This method relies on operator skills to control manufacturing quality. The dimensional error of ordinary shearing machines is typically ±1.8mm, and the weld deformation of manual arc welding can reach 2.5mm / m, far from meeting the precision requirements of modern super high-rise and large-span steel structures (the specification requires butt weld misalignment ≤0.5mm). Taking the prefabrication of bridge steel structures as an example, the verticality deviation of the web of the box girder processed by this method often exceeds 0.8mm / m, requiring additional investment in mechanical grinding and correction. The correction cost for a single beam increases by more than 2,000 yuan, and the construction period is extended by 2-3 days.

[0004] 3. Inefficient physical pre-assembly mode: To verify component compatibility, traditional methods require transporting the processed components to a dedicated site for physical pre-assembly. This process not only consumes a large amount of site resources (more than 600 square meters of pre-assembly space is required for every thousand tons of components), but also has a first-time assembly pass rate of only 75%. For multi-module steel structure systems, the repeated disassembly and adjustment process can extend the construction period by more than 40%. A certain sports stadium project was delayed by two months due to delays in physical pre-assembly.

[0005] 4. Disconnect between precision inspection and processing: Traditional methods employ a "post-processing sampling inspection" model. After components are processed, sampling inspections are conducted using calipers and levels. However, the inspection data cannot be fed back to the processing stage in real time. A quality report from a steel structure processing plant in 2023 showed that the batch non-conformity rate due to delayed inspection reached 5.1%, resulting in an annual steel waste of over 200 tons and material cost losses exceeding 1.6 million yuan.

[0006] To address the shortcomings of traditional technologies, the industry has begun to introduce digital modeling techniques to optimize processes. For example, Chinese patent application CN120273521A discloses a method for rapid assembly of modular prefabricated steel structures. This method uses a BIM model to standardize the decomposition of building modules, ensuring high interchangeability among them. It employs advanced connection interface design, a high-precision positioning system, high-performance sealing materials, a distributed hydraulic tensioning device, and an intelligent control system to achieve efficient, precise, and safe modular construction, thereby simplifying the on-site assembly process and improving construction efficiency. Furthermore, by implementing detection and intelligent control, the fastening parameters of module connection nodes are dynamically adjusted to ensure optimal structural response, effectively suppressing cumulative structural deformation during construction and improving the safety and durability of the building. This patent proposes using BIM software to construct a three-dimensional model of the steel structure, realizing the digital expression of design drawings and achieving progress in collision detection and node optimization. However, this technology still has obvious limitations: model data needs to be manually converted into processing instructions to drive the equipment, failing to achieve seamless integration between design and processing; at the same time, it lacks a full-process accuracy monitoring mechanism, and the model optimization is disconnected from the actual processing accuracy, failing to fundamentally solve the problem of accuracy control and efficiency improvement of prefabricated components.

[0007] In summary, existing technologies can no longer meet the demands of steel structure prefabrication for "high precision, high efficiency, and low energy consumption." The industry urgently needs an integrated technology solution that combines "digital modeling, automated processing, intelligent monitoring, and closed-loop feedback." This solution would eliminate human intervention errors through end-to-end data flow, establish a dynamic precision control system, and thus resolve the core contradiction between prefabrication precision and production efficiency, thereby promoting the high-quality development of steel structure prefabrication technology. Summary of the Invention

[0008] In view of the shortcomings of existing technologies, the purpose of this invention is to provide a high-precision prefabrication construction method for steel structures, so as to solve the technical defects in existing steel structure prefabrication construction, such as design and processing disconnect, insufficient precision control, low pre-assembly efficiency, and delayed data feedback.

[0009] The above-mentioned objective of this invention is achieved through the following technical solutions: This invention provides a high-precision prefabrication construction method for steel structures, comprising the following steps: S1. Pre-construction preparation: collecting steel structure engineering design drawings, material performance parameters, and construction site condition data to establish a construction database containing design standards, process specifications, and precision requirements; S2. Three-dimensional collaborative detailed modeling: using TeklaStructures software to perform three-dimensional modeling of the design drawings, and combining it with Renba plate cutting and layout optimization software to complete the component layout optimization, generating process details and CNC machining code containing processing precision parameters; S3. Precision machining of prefabricated components: based on the process details and CNC code, high-precision machining is performed using CNC machine tools. Cutting: Standardized welding is carried out using welding robots, with weld shrinkage allowance and end beveling set simultaneously; S4. Module pre-assembly accuracy control: A unified benchmark and axis grid system is established, and component coordinate data is collected using a total station. The data is then imported into simulation pre-assembly software to analyze the X, Y, and Z-axis deviations between modules and generate an error adjustment plan; S5. Dynamic accuracy monitoring and feedback: A real-time monitoring system is used to track component dimensional deviations throughout the prefabrication and assembly process. The monitoring data is compared with the construction database, and processing parameters are dynamically adjusted; S6. Finished product acceptance and delivery: Component dimensions and weld quality are inspected according to preset accuracy standards, and an acceptance report containing full-process data is generated.

[0010] According to one embodiment of the present invention, the three-dimensional modeling in step S2 specifically includes: after importing the design drawings, defining the component parameters, setting the elastic modulus, yield strength and other performance parameters when the material is Q355B, establishing an overall model including stiffening plates and connecting plates, and controlling the model accuracy error within ±0.1mm.

[0011] According to one embodiment of the present invention, the layout optimization in step S2 adopts a nested algorithm. When the original sheet size is 1900×1000mm, the optimized material utilization rate is not less than 85%, the minimum reusable size of the leftover material is not less than 100mm×100mm, and the layout drawing export format includes DXF and CNC machining G code.

[0012] According to one embodiment of the present invention, in step S3, the CNC machine tool adopts a Han's Laser G3015 fiber laser cutting machine, the cutting speed is set to 3-8m / min, the cutting kerf width is controlled at 0.15-0.3mm, and the verticality error of the cut is ≤0.05mm / m. For the internal stiffening plate of the box column, double-sided electroslag welding is adopted, the welding current is 500-600A, the voltage is 30-35V, and the welding speed is 15-20cm / min.

[0013] According to one embodiment of the present invention, in step S3, the bevel is a full penetration V-shaped bevel with a bevel angle of 60°±5°, a blunt edge thickness of 2-3mm, a gap of 2-4mm, and the bevel is derusted and degreased before welding, with a surface roughness Ra≤25μm.

[0014] According to one embodiment of the present invention, in step S4, the benchmark point setting adopts pre-embedded stainless steel stakes with a stake diameter ≥20mm, a burial depth ≥500mm, a plane coordinate error ≤±0.2mm, an elevation error ≤±0.1mm, and the axis grid is laid out using a total station with a cross axis marking deviation ≤2mm.

[0015] According to one embodiment of the present invention, in step S4, the simulation pre-assembly software uses XsteelPrecast. After importing the component CAD file and coordinate measurement data, the matching error threshold is set to 80mm, the number of automatic binding points per module is no less than 6, the deviation analysis accuracy reaches 0.1mm level, and the generated adjustment scheme includes component displacement and angle correction parameters.

[0016] According to one embodiment of the present invention, in step S5, the real-time monitoring system adopts BIM+IoT technology, attaches RFID tags and displacement sensors to key parts of the component, the sampling frequency is 10Hz, the data transmission delay is ≤1s, and when the monitoring deviation exceeds the warning threshold ±0.5mm, the processing equipment parameter adjustment command is automatically triggered.

[0017] According to one embodiment of the present invention, in step S6, the dimension inspection is carried out using a coordinate measuring machine with a measurement range of 0-10m and a measurement accuracy of ±0.02mm. The weld quality inspection is carried out using an ultrasonic flaw detector with a flaw detection range covering all butt welds and a defect detection rate of ≥99%. The acceptance report includes component ID, processing parameters, inspection data and three-dimensional model comparison results.

[0018] According to one embodiment of the present invention, the construction database in step S1 further includes meteorological influence parameters. When the ambient temperature changes by more than ±5℃, the thermal expansion and contraction compensation algorithm is automatically invoked to adjust the processing dimensions. The compensation coefficient ranges from 1.2 × 10⁻⁻⁻⁶. 5 / ℃-1.5×10⁻ 5 / ℃.

[0019] In summary, compared with the prior art, the present invention has at least one of the following beneficial technical effects: This invention integrates digital, automated, and intelligent technologies to form a complete high-precision prefabrication construction method for steel structures, which has the following significant advantages compared with existing technologies: 1. Significantly Improved Machining Accuracy: Through seamless integration of 3D modeling and CNC machining, human intervention errors are eliminated. Component cutting dimensional errors are controlled within ±0.3mm, and welding deformation is ≤0.5mm / m, far superior to the ±1.5mm and 2mm / m of existing technologies, meeting the installation requirements of high-precision steel structures. After applying this method to a bridge project, the misalignment of the box girder splice welds was controlled within 0.3mm, and the first-time assembly qualification rate increased from 78% to 98.5%.

[0020] 2. Significantly improved production efficiency: Digital pre-assembly technology replaces traditional physical pre-assembly, reducing site occupancy by 92% and shortening pre-assembly time from an average of 7 days / module to 1 day / module; automated processing by CNC equipment shortens component production cycle by 40%. In an industrial plant project, the prefabrication time of 1,200 tons of steel structure components was shortened from 60 days using traditional methods to 36 days, completing the production task 24 days ahead of schedule.

[0021] 3. Outstanding cost control results: Optimized material layout increased steel utilization from 72% to over 85%, saving 130 tons of steel per 1,000-ton component, resulting in a direct material cost reduction of 1.04 million yuan; dynamic monitoring and closed-loop feedback reduced the component scrap rate from 4.2% to 0.3%, reducing rework costs by 93%; on-site installation efficiency increased by 35%, labor costs decreased by 28%, and overall costs decreased by 32%.

[0022] 4. Improved quality control: Full-process data management enables traceability of component quality. The acceptance report includes data from the entire process from design to delivery, facilitating the investigation and analysis of quality issues. Welding quality meets the first-class weld standard, with a weld defect detection rate of ≥99%, effectively avoiding safety hazards caused by weld quality problems and improving the overall safety of steel structure projects.

[0023] 5. Significant advantages of green construction: Factory prefabrication reduces dust and noise pollution during on-site construction, and reduces waste emissions by 80%; improved material utilization reduces steel waste, which meets the development requirements of green building. A project that applied this method was rated as a "Provincial Green Construction Demonstration Project".

[0024] 6. High adaptability and wide application: This method can adjust processing parameters and processes according to different component types (H-beams, box columns, connecting plates, etc.) and project requirements, making it suitable for various steel structure projects such as industrial plants, high-rise buildings, bridges, and stadiums. Even in low-temperature (-10℃) and high-temperature (35℃) environments, the environmental compensation algorithm can still ensure processing accuracy, adapting to different regional construction conditions. Attached Figure Description

[0025] Figure 1 This is a flowchart of the present invention.

[0026] Figure 2 This is a schematic diagram illustrating the establishment of the axis grid system for precision control according to the present invention. Detailed Implementation

[0027] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0028] In the description of this application, it should be noted that the terms "upper," "lower," "inner," "outer," "top / bottom," etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0029] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installed," "equipped with," "sleeved / connected," "connected," etc., should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0030] The present invention specifically aims to solve the following core problems: How to achieve seamless digital integration from design drawings to manufacturing execution, eliminate dimensional deviations during manual conversion, and control component manufacturing dimensional errors within ±0.5mm; How to reduce welding deformation and ensure that the weld quality meets the first-class weld acceptance standard by combining standardized processing technology with automated equipment, with the misalignment of butt welds ≤0.5mm; How to use digital pre-assembly technology to replace physical pre-assembly, reduce site occupancy by more than 90%, and increase the first-pass yield of modular assembly to more than 98%; How to establish a dynamic monitoring and feedback mechanism for the entire process to achieve real-time adjustment of processing parameters and reduce the scrap rate of components to below 0.5%; How to quantify the impact of environmental factors on prefabrication accuracy, establish a compensation mechanism for parameters such as temperature and humidity, and ensure processing stability under different working conditions.

[0031] To solve the above technical problems, refer to Figure 1 and Figure 2 This invention provides a high-precision prefabrication construction method for steel structures. Through a technical path of "digital modeling - automated processing - intelligent monitoring - closed-loop feedback," it achieves high-precision prefabrication of steel structure components. The specific technical solution is as follows: S1. Pre-construction preparation S1.1 Data Collection and Integration: Collect the overall design drawings, component exploded views, material factory certificates (including performance parameters such as yield strength, tensile strength, and elongation of Q355B and Q235 steel), site layout plan, historical meteorological data (monthly average temperature and humidity change curves for the past 5 years), and processing equipment parameters (CNC machine tool model, stroke accuracy, load capacity, etc.) for the steel structure project.

[0032] S1.2 Construction Database Setup: An SQL Server database management system was used to establish a database containing three main modules: ① Design Standards Module, which inputs the accuracy requirements from specifications such as the "Standard for Acceptance of Construction Quality of Steel Structures" (GB50205-2020) and the "Technical Standard for Welding of Building Steel Structures" (JGJ81-2023); ② Process Parameters Module, which stores the processing parameters for different component types (H-beams, box columns, connecting plates, etc.); ③ Monitoring Thresholds Module, which sets early warning and control values ​​for dimensional deviations, welding temperatures, environmental parameters, etc.

[0033] S1.3 Equipment and Personnel Configuration: Equipped with Tekla Structures 2022 modeling software, Renba plate cutting and layout optimization software V6.0, Han's Laser G3015 CNC cutting machine, ABB IRB 1600 welding robot, Trimble S9 total station, Hexagon Global Silver coordinate measuring machine, etc., and operators are given special training to ensure that they master the software operation and equipment debugging skills.

[0034] S2. 3D Collaborative Deepening Modeling S2.1 Basic Model Construction: Import the CAD files of the design drawings into Tekla Structures software, create a 3D solid model at a 1:1 scale, and define the components parametrically, including materials, cross-sectional dimensions, and node types. For complex components such as box columns, a "decompose-model-integrate" approach is adopted. First, the modeling of each component is completed, and then Boolean operations are used to generate the overall model, ensuring that the model is completely consistent with the design intent.

[0035] S2.2 Collision Detection and Optimization: Utilizing the software's collision detection function, a comprehensive inspection is conducted on component nodes, pipeline pre-reserved holes, and other areas. The collision detection accuracy is set to 0.1mm. Upon discovering collision issues, timely communication and adjustments are made with the design unit. Application in a steel structure project for an office building demonstrates that this step can identify over 95% of design conflicts in advance, avoiding rework later.

[0036] S2.3 Layout Optimization and Code Generation: Export the component information from the model to the Renba Plate Cutting Layout Optimization Software. Input the original steel sheet specifications (e.g., 1900×1000mm, 2000×1500mm, etc.) and quantity. Set parameters such as a 10mm saw kerf, 0mm dimensional tolerance, and a minimum reusable scrap of 100mm. The software uses a genetic algorithm for layout optimization to ensure a material utilization rate of no less than 85%. After optimization, directly export the CNC machining G-code and DXF format layout drawing, achieving unattended transmission of design data to machining data.

[0037] S2.4 Output of process details: Generate process details in Tekla software that include machining accuracy requirements, and mark the allowable values ​​of component dimensional deviations (such as length deviation ±0.5mm, perpendicularity deviation ≤0.1mm / m), welding parameters (welding method, current, voltage, etc.), flaw detection requirements, etc. The details are printed in A3 size to ensure that on-site operators can clearly identify them.

[0038] S3. Precision machining of prefabricated components S3.1 Material Pretreatment: After the steel arrives on site, it undergoes visual inspection and performance re-inspection. An ultrasonic flaw detector is used to detect internal defects in the steel, and only qualified steel can be put into use. The steel plates are then leveled using a four-stage leveling machine. After leveling, the flatness error of the steel plate is ≤0.3mm / m, eliminating the influence of material deformation on processing accuracy.

[0039] S3.2 High-precision cutting: Import the generated CNC G-code into the Han's Laser G3015 cutting machine and set the cutting parameters: the cutting speed is adjusted according to the steel plate thickness; the cutting speed is 5m / min for 6-12mm thick steel plates and 3m / min for 12-20mm thick steel plates; the laser power is set to 3000W, and the focal point is controlled 0.5mm below the steel plate surface. During the cutting process, an automatic slag removal system is used to remove molten slag from the cut, ensuring a smooth cut and controlling the cutting size error within ±0.3mm.

[0040] S3.3 Assembly and Positioning: Specialized tooling fixtures are used for component assembly, with a positioning accuracy ≤0.1mm. For H-beam components, adjustable positioning pins are used to fix the flanges and webs, ensuring a perpendicularity error between the flanges and webs ≤0.15mm / m. For box-type columns, dummy inserts are used for positioning to prevent twisting and deformation during assembly; the clearance between the dummy insert and the component is ≤0.2mm. After assembly, a dial indicator is used to check the dimensions of each part, and spot welding is performed after confirming compliance with requirements.

[0041] S3.4 Standardized Welding: Appropriate welding methods are selected based on the component type. Double-sided electroslag welding is used for the internal stiffening plates of the box-type columns, with a welding current of 550A, voltage of 32V, and welding speed of 18cm / min. Submerged arc welding is used for the connection between the flange plates and the web plates, with a welding current of 600A, voltage of 35V, and welding speed of 20cm / min. During welding, the arc tracking function of the welding robot is used to adjust the welding torch position in real time to ensure uniform weld formation. Simultaneously, a weld shrinkage allowance of 5-8mm is reserved in the component, based on the steel plate thickness, to compensate for welding deformation.

[0042] S3.5 Beveling: The welded ends of the components are beveled using a specialized beveling machine. The beveling type is a full penetration V-groove with a beveling angle of 60°, a blunt edge thickness of 2.5mm, and a gap of 3mm. After beveling, the surface is ground with a grinding wheel to remove oxide scale and burrs, achieving a surface roughness of Ra≤25μm, ensuring the quality of subsequent welding.

[0043] S3.6 Post-weld treatment: After welding, the component undergoes post-weld stress relief treatment using vibration aging equipment at a frequency of 20-50Hz for 30 minutes to eliminate residual welding stress and prevent later deformation of the component. The weld is then subjected to visual inspection and non-destructive testing. Visual inspection ensures the weld surface is free of cracks, porosity, and other defects. Non-destructive testing uses an ultrasonic flaw detector with a 100% flaw detection rate to ensure the weld quality meets the first-class standard.

[0044] S4. Module pre-assembly accuracy control S4.1 Establishment of the benchmark system: Pre-embedded stainless steel stakes were set as benchmark points on the ground of the prefabrication workshop. The stakes were spaced 10m apart, 20mm in diameter, and buried at a depth of 500mm, and fixed with concrete. The benchmark points were measured using a Trimble S9 total station. The mean square error of the plane coordinates was controlled within ±0.2mm, and the mean square error of the elevation was ±0.1mm, thus establishing a unified three-dimensional benchmark coordinate system.

[0045] S4.2 Grid Layout: Based on the coordinates of the reference points, a total station is used to lay out the cross-shaped grid lines on the roadbed box. The spacing between the grid lines is determined according to the dimensions of the components, generally 5-8m. The grid lines are marked with engraved lines, with a width of 0.2mm and a depth of 0.5mm. The marking deviation is ≤2mm to ensure the grid lines are clear and accurate.

[0046] S4.3 Component Coordinate Measurement: Hoist the finished components to the designated location and use a total station to collect 3D coordinate data of key parts of the components (such as node centers and end corners). At least 8 data points should be collected for each component, with a measurement accuracy of ±0.1mm. Record the measurement data in the database and compare it with the theoretical coordinates of the 3D model.

[0047] S4.4 Digital Pre-assembly: Import the component CAD files and measured coordinate data into the Xsteel Precast simulation pre-assembly software, set the matching error threshold to 80mm, and the software automatically identifies the connection relationship between components and binds the mounting points (no less than 6 per module). Through 3D visualization simulation, analyze the deviation values ​​between modules in the X, Y, and Z directions, with a deviation analysis accuracy of 0.1mm.

[0048] S4.5 Error Adjustment: Based on the deviation analysis report generated by the software, develop a targeted adjustment plan. For components with small dimensional deviations, use hydraulic jacks for fine-tuning; for components with large deviations, return them to the machining workshop for local correction. After adjustment, re-measure coordinates and simulate assembly until the deviation between modules is ≤0.5mm, meeting the assembly requirements.

[0049] S5. Dynamic accuracy monitoring and feedback S5.1 Monitoring System Deployment: Displacement sensors, temperature sensors, and stress sensors are installed at key component processing stations (cutting, welding, assembly) and assembly areas. The sensor accuracies are 0.01mm, 0.1℃, and 0.1MPa, respectively. RFID tags are affixed to the surface of the components, with each tag corresponding to a unique component ID, enabling full-process tracking of the components.

[0050] S5.2 Real-time Data Acquisition: Sensor data is transmitted to the central control system via an Internet of Things (IoT) module. The data sampling frequency is 10Hz, and the transmission delay is ≤1s. The system compares the real-time data with standard parameters in the construction database to generate deviation curves and early warning information.

[0051] S5.3 Environmental Compensation Adjustment: When the monitored ambient temperature change exceeds ±5℃, the system automatically calls the thermal expansion and contraction compensation algorithm, based on the linear expansion coefficient of steel (1.2×10⁻⁻¹). 5 / ℃-1.5×10⁻ 5The dimensional compensation amount is calculated using the temperature (°C) and the operating parameters of the CNC machining equipment are adjusted accordingly. For example, when the temperature rises by 10°C, a compensation amount of 1.2-1.5mm is automatically reserved for a 10m long component to avoid temperature deformation affecting accuracy.

[0052] S5.4 Closed-loop feedback control: When the system detects that the dimensional deviation of a component exceeds the warning threshold of ±0.5mm, it immediately sends an adjustment command to the processing equipment. If a dimensional deviation occurs during the cutting process, the cutting speed and focus position are automatically adjusted; if excessive deformation occurs during the welding process, the welding current and cooling method are adjusted. At the same time, the deviation data is fed back to the 3D modeling module to optimize the modeling parameters of subsequent components, forming a closed-loop control of "monitoring-adjustment-optimization".

[0053] S6. Finished Product Acceptance and Delivery S6.1 Dimensional Accuracy Inspection: A Hexagon Global Silver coordinate measuring machine is used to perform comprehensive dimensional inspection of the components, with a measurement range of 0-10m and a measurement accuracy of ±0.02mm. Inspection items include component length, width, height, verticality, diagonal deviation, etc., with no fewer than 3 inspection points for each item to ensure the reliability of the inspection results.

[0054] S6.2 Weld quality acceptance: The appearance quality of the weld is inspected by visual inspection combined with weld gauges to check parameters such as weld height, width, and reinforcement height; the internal quality inspection is carried out by a combination of ultrasonic testing and radiographic testing, with an ultrasonic testing detection rate of ≥99% and radiographic testing sensitivity reaching AB level to ensure that the weld is free of internal defects.

[0055] S6.3 Data-Driven Acceptance Report: A unique acceptance report is generated for each component. The report includes component ID, processing time, equipment number, test data, 3D model comparison results, etc., stored in PDF format and uploaded to a cloud database to ensure the traceability of acceptance data. Components that pass acceptance are affixed with a pass label containing a QR code containing component information; scanning the code allows access to the entire process data.

[0056] S6.4 Finished Product Protection and Delivery: Components that pass inspection will undergo surface anti-corrosion treatment, including sandblasting to remove rust and then applying two coats of anti-rust paint with a film thickness ≥80μm. Specialized packaging will be designed according to the component's size and weight to prevent collisions and deformation during transportation. Upon delivery, acceptance reports, processing drawings, and other relevant documents will be provided simultaneously to ensure smooth on-site installation.

[0057] Example 1: Prefabrication Construction of Steel Structure for an Industrial Plant 1. Project Overview: The industrial plant has a building area of ​​15,000 square meters and a total steel structure weight of 2,300 tons. The main components include H-shaped steel columns (section dimensions H800×400×16×25), H-shaped steel beams (section dimensions H600×300×14×20), connecting plates, etc. The prefabrication accuracy of the components is required to be ±0.5mm, and the weld quality must meet the first-class standard.

[0058] S1. Pre-construction preparation S1.1 Data Collection: Collect 126 sheets of general structural design drawings and component exploded drawings of the factory building, performance parameters of Q355B steel such as yield strength 355MPa, tensile strength 510MPa, and elongation 21%, construction site layout plan, local temperature variation range of -8℃ to 36℃ in the past 5 years, and purchase equipment such as Han's Laser G3015 cutting machine and ABB welding robot, and enter the equipment parameters into the database.

[0059] S1.2 Database Setup: A database was set up using SQL Server 2019. The accuracy requirements for H-beam steel components in GB50205-2020 (length deviation ±0.5mm, verticality ≤0.1mm / m) were entered. The cutting temperature warning threshold was set to ±5℃ and the welding current fluctuation warning value was set to ±50A.

[0060] S2. 3D Collaborative Deepening Modeling S2.1 Model Building: Import the CAD design drawings into Tekla Structures 2022 to build a 3D model of the 2300-ton component. The H-shaped steel column model includes details such as stiffening plates and connecting plates. The model accuracy is ±0.1mm. After completion, a collision check was performed, and eight pipeline reserved holes were found to collide with the stiffening plates. The hole positions were adjusted in a timely manner by communicating with the design unit.

[0061] S2.2 Layout optimization: Import the information of 1200 connecting plates into Renba software. The original plate size is 1900×1000mm. Set the saw kerf to 10mm. After optimization, the material utilization rate is 86.3%. Generate 320 CNC G codes and 156 DXF layout diagrams to avoid manual conversion errors.

[0062] S3. Precision machining of prefabricated components S3.1 Material pretreatment: The steel materials have a 100% pass rate after re-inspection upon arrival. The steel plates are leveled using a four-stage leveling machine, and the flatness error is 0.25mm / m, which meets the requirements.

[0063] S3.2 Cutting and processing: The cutting speed of the 12mm thick H-beam flange plate is set to 5m / min, the laser power is 3000W, the size detection error after cutting is ±0.2mm, and the perpendicularity of the cut is 0.04mm / m.

[0064] S3.3 Assembly and Welding: The H-beams are assembled using adjustable tooling, with a perpendicularity error of 0.12mm / m between the flange and the web. Welding is performed using submerged arc welding with a current of 600A, a voltage of 35V, a welding speed of 20cm / min, and a 6mm weld shrinkage allowance. Post-weld stress relief treatment is also performed.

[0065] S3.4 Beveling: V-shaped beveling is machined using a beveling machine with an angle of 60°, a blunt edge of 2.5mm, a gap of 3mm, and a surface roughness of Ra20μm after grinding.

[0066] S4. Module pre-assembly accuracy control S4.1, Benchmark Establishment: Set 24 benchmark points, with a total station measurement error of ±0.18mm for plane coordinates and ±0.09mm for elevation.

[0067] S4.2 Pre-assembly simulation: Import the coordinate data of 12 column and beam modules. Xsteel Precast software analysis shows that the Y-axis deviation of two modules is 0.8mm. After fine adjustment with hydraulic jacks, the deviation is reduced to 0.3mm, which meets the requirements.

[0068] S5. Dynamic accuracy monitoring and feedback S5.1 Monitoring Deployment: 28 displacement sensors and 15 temperature sensors are installed at the cutting and welding stations to collect data in real time.

[0069] S5.2 Environmental Adjustment: If the temperature suddenly rises by 12℃ on a certain day, the system will automatically calculate a compensation amount of 1.44mm and adjust the cutting size parameters to avoid thermal deformation.

[0070] S6. Finished Product Acceptance and Delivery S6.1 Inspection Results: The coordinate measuring machine was used to inspect 2300 tons of components. The dimensional qualification rate was 99.7%, and the ultrasonic flaw detection qualification rate of welds was 100%, all of which met the design requirements.

[0071] S6.2 Benefit Analysis: The component production cycle is 42 days, which is 28 days shorter than the traditional method; the steel utilization rate is increased by 14.3%, saving 329 tons of steel and reducing costs by 2.63 million yuan.

[0072] Example 2: Precast Construction of Steel Box Girder for a Bridge Project Overview: This bridge is a simply supported beam bridge with a span of 30m and a total steel structure weight of 860 tons. The main component is a box girder (section dimensions 1200×800×20×25). The box girder length deviation is required to be ±0.4mm, web verticality ≤0.1mm / m, and butt weld misalignment ≤0.5mm.

[0073] S1. Pre-construction preparation S1.1 Data Collection: Collect bridge structural design drawings, box girder node details, and performance parameters such as low-temperature impact toughness (impact energy ≥34J at -20℃) of Q355qD steel, with local temperature variation range from -10℃ to 32℃.

[0074] S1.2 Equipment Configuration: New special assembly tooling for box girder with positioning accuracy ≤0.08mm, equipped with phased array ultrasonic flaw detector to improve weld inspection accuracy.

[0075] S2. 3D Collaborative Deepening Modeling S2.1 Model Construction: Establish a three-dimensional model of the box girder, focusing on optimizing the arrangement of the internal stiffening plates. Use the parametric function of Tekla software to quickly adjust the spacing of the stiffening plates. The dimensional deviation between the model and the design drawings is ≤0.1mm.

[0076] S2.2 Process Design: To address the welding deformation problem of box girder, the welding process is simulated in the model to predict the amount of deformation. An 8mm anti-deformation amount is set in advance to ensure that the post-weld dimensions meet the requirements.

[0077] S3. Precision machining of prefabricated components S3.1 Cutting and processing: 25mm thick steel plate is cut at a speed of 3m / min, using dual-focus laser cutting technology, with a cut roughness of Ra12.5μm and a dimensional error of ±0.25mm.

[0078] S3.2 Assembly and welding: The web and flange plates of the box girder are positioned using dummy parts, and the gap between the dummy parts and the components is ≤0.15mm; the internal stiffening plates are welded by double-sided electroslag welding with a welding current of 550A, a voltage of 32V, and a welding speed of 18cm / min.

[0079] S3.3 Post-weld treatment: Overall aging treatment is adopted to eliminate welding stress. The straightness error of the box girder after welding is 0.3mm / m, which is better than the design requirements.

[0080] S4. Module pre-assembly accuracy control S4.1 Pre-assembly simulation: Import the coordinate data of 6 box girders. The software analysis shows that the Z-direction deviation of 1 box girder is 0.6mm. By adjusting the thickness of the end connecting plate, the deviation is controlled to 0.3mm.

[0081] S5. Dynamic accuracy monitoring and feedback S5.1 Low Temperature Construction Adjustment: During winter construction at -8℃, the system automatically adjusts the welding preheating temperature to 120℃, and controls the interpass temperature at 80-100℃ to ensure weld quality.

[0082] S6. Finished Product Acceptance and Delivery S6.1 Inspection results: The box girder length deviation was ±0.3mm, the web verticality was 0.08mm / m, and the butt weld misalignment was 0.3mm, all of which met the design requirements; the phased array flaw detection pass rate of the weld was 100%, with no internal defects.

[0083] S6.2 Application Results: The on-site installation time of box girder was shortened from 15 days in the traditional method to 6 days, the installation efficiency was improved by 60%, and the construction quality of the bridge steel structure was rated as "municipal-level high-quality project".

[0084] The implementation principle of this invention is as follows: This invention discloses a high-precision prefabrication construction method for steel structures, belonging to the field of steel structure construction technology. The method includes six steps: pre-construction preparation, 3D collaborative detailed modeling, precision processing of prefabricated components, precision control of module pre-assembly, dynamic precision monitoring and feedback, and finished product acceptance and delivery. It achieves standardized data management by establishing a construction database, completes 3D modeling and layout optimization using Tekla Structures and Renba software, achieves automated processing by combining CNC cutting machines and welding robots, uses simulation pre-assembly software and a total station for precision control, and realizes dynamic feedback throughout the entire process through an IoT monitoring system. This invention solves the problems of design-processing disconnect, low precision, and poor efficiency in existing technologies, ensuring component cutting error ≤ ±0.3mm, welding deformation ≤ 0.5mm / m, a first-pass yield of ≥98% in pre-assembly, and a 32% reduction in overall cost. It is suitable for the factory prefabrication of various steel structure projects and has significant economic and social benefits.

[0085] The embodiments described herein are preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape, and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A high-precision prefabrication construction method for steel structures, characterized in that, Includes the following steps: S1. Pre-construction preparation: Collect steel structure engineering design drawings, material performance parameters and construction site condition data, and establish a construction database that includes design standards, process specifications and precision requirements; S2. 3D Collaborative Deepening Modeling: Tekla Structures software is used to create 3D models of the design drawings. Combined with Renba plate cutting and layout optimization software, the component layout is optimized, and detailed process drawings and CNC machining codes containing machining accuracy parameters are generated. S3. Precision machining of prefabricated components: Based on the process details and CNC code, high-precision cutting is performed by CNC machine tools, and standardized welding is carried out by welding robots, with weld shrinkage allowance and end bevel set simultaneously; S4. Pre-assembly accuracy control of modules: Establish a unified benchmark point and axis grid system, collect component coordinate data using a total station, import the simulation pre-assembly software to analyze the X, Y, and Z three-dimensional deviations between modules, and generate an error adjustment scheme; S5. Dynamic precision monitoring and feedback: A real-time monitoring system is used to track component size deviations throughout the prefabrication and assembly process, and the monitoring data is compared with the construction database to dynamically adjust the processing parameters. S6. Finished Product Acceptance and Delivery: Based on preset accuracy standards, complete the inspection of component dimensions and weld quality, and generate an acceptance report containing data from the entire process.

2. The high-precision prefabrication construction method for steel structures according to claim 1, characterized in that, The 3D modeling in step S2 specifically includes: after importing the design drawings, defining the component parameters, setting the elastic modulus and yield strength performance parameters when the material is Q355B, and establishing an overall model including stiffening plates and connecting plates, with the model accuracy error controlled within ±0.1mm.

3. The high-precision prefabrication construction method for steel structures according to claim 1, characterized in that, In step S2, the layout optimization adopts a nested algorithm. When the original sheet size is 1900×1000mm, the optimized material utilization rate is no less than 85%, the minimum reusable size of the leftover material is no less than 100mm×100mm, and the layout drawing export format includes DXF and CNC machining G code.

4. The high-precision prefabrication construction method for steel structures according to claim 1, characterized in that, In step S3, the CNC machine tool uses a Han's Laser G3015 fiber laser cutting machine, with the cutting speed set to 3-8 m / min, the kerf width controlled at 0.15-0.3 mm, and the perpendicularity error of the cut ≤0.05 mm / m. For the internal stiffening plates of the box-shaped column, double-sided electroslag welding is used, with a welding current of 500-600 A, a voltage of 30-35 V, and a welding speed of 15-20 cm / min.

5. The high-precision prefabrication construction method for steel structures according to claim 1, characterized in that, In step S3, a full penetration V-groove is adopted, with a groove angle of 60°±5°, a blunt edge thickness of 2-3mm, and a gap of 2-4mm. Before welding, the groove is derusted and degreased, and the surface roughness Ra≤25μm.

6. The high-precision prefabrication construction method for steel structures according to claim 1, characterized in that, In step S4, the benchmark points are set using pre-embedded stainless steel stakes with a stake diameter ≥ 20 mm, a burial depth ≥ 500 mm, a plane coordinate error ≤ ±0.2 mm, an elevation error ≤ ±0.1 mm, and the grid is laid out using a total station with a cross axis marking deviation ≤ 2 mm.

7. The high-precision prefabrication construction method for steel structures according to claim 1, characterized in that, In step S4, the simulation pre-assembly software used is Xsteel Precast. After importing the component CAD files and coordinate measurement data, the matching error threshold is set to 80mm. The number of automatic binding points is no less than 6 per module. The deviation analysis accuracy reaches 0.1mm level. The generated adjustment scheme includes component displacement and angle correction parameters.

8. The high-precision prefabrication construction method for steel structures according to claim 1, characterized in that, In step S5, the real-time monitoring system adopts BIM+IoT technology, attaches RFID tags and displacement sensors to key parts of the component, the sampling frequency is 10Hz, the data transmission delay is ≤1s, and when the monitoring deviation exceeds the warning threshold ±0.5mm, the processing equipment parameter adjustment command is automatically triggered.

9. The high-precision prefabrication construction method for steel structures according to claim 1, characterized in that, In step S6, the dimension inspection is carried out using a coordinate measuring machine with a measurement range of 0-10m and a measurement accuracy of ±0.02mm. The weld quality inspection is carried out using an ultrasonic flaw detector with a flaw detection range covering all butt welds and a defect detection rate of ≥99%. The acceptance report includes component ID, processing parameters, inspection data and three-dimensional model comparison results.

10. A high-precision prefabrication construction method for steel structures according to claim 1, characterized in that, In step S1, the construction database also includes meteorological impact parameters. When the ambient temperature changes by more than ±5℃, the thermal expansion and contraction compensation algorithm is automatically invoked to adjust the processing dimensions. The compensation coefficient ranges from 1.2×10⁻ 5 / ℃-1.5×10⁻ 5 / ℃.

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