Construction method, device and equipment of fabricated steel structure building and storage medium

Abstract

The invention discloses a construction method, device and equipment of an assembly type steel structure building and a storage medium, and relates to the technical field of assembly type buildings. The method comprises the steps that in response to a construction instruction of a target building, construction information parameters of the target building are determined, and a reference steel structure design model matched with the target building is determined from a pre-stored structure design model library according to the construction information parameters; determining a target steel structure design model matched with the target building based on the reference steel structure design model; generating a building information model matched with the target building according to the target steel structure design model, generating component manufacturing data based on the building information model and the building information parameters, and converting the component manufacturing data into processing control data; and processing the structural material based on the processing control data to obtain prefabricated parts, and assembling the prefabricated parts on the construction site to obtain a target building. According to the scheme, the design efficiency, the material utilization rate and the construction precision can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of prefabricated building, and in particular to a prefabricated steel structure building construction method, device, equipment and storage medium. BACKGROUND

[0002] Prefabricated steel structure buildings are widely used in industrial plants, residential buildings and public buildings due to their fast construction speed, high industrialization degree and green low carbon advantages.

[0003] At present, designers select similar engineering schemes from existing drawings or experience libraries according to project requirements, and then manually check and adjust them in combination with specification requirements to form construction drawings. Then, process personnel re-model or compile numerical control programs according to the drawings for component processing. After the prefabricated components are transported to the site, construction personnel rely on the drawings to hoist and connect them.

[0004] This method highly depends on manual experience, and the design and manufacturing links are disconnected, which is prone to problems such as inconsistency between drawings and processing data, complex component specifications, high steel consumption, and on-site assembly deviation, resulting in low overall efficiency and difficulty in ensuring the consistency and precision of industrialized construction. SUMMARY

[0005] The present application provides a prefabricated steel structure building construction method, device, equipment and storage medium to solve the problems of relying on manual experience, inconsistency between drawings and processing data, complex component specifications, high steel consumption, and on-site assembly deviation, which can improve design efficiency, material utilization rate and construction precision.

[0006] According to an aspect of the present application, a prefabricated steel structure building construction method is provided, which comprises:

[0007] In response to the construction instruction of the target building, the construction information parameters of the target building are determined, and the reference steel structure design model matched with the target building is determined from the pre-stored structure design model library according to the construction information parameters;

[0008] The target steel structure design model matched with the target building is determined based on the reference steel structure design model;

[0009] The building information model matched with the target building is generated according to the target steel structure design model, the component manufacturing data is generated based on the building information model and the construction information parameters, and the component manufacturing data is converted into processing control data;

[0010] The prefabricated components are obtained by processing the structural materials based on the processing control data, and the prefabricated components are assembled at the construction site to obtain the target building.

[0011] According to another aspect of the present application, there is provided a construction device for a fabricated steel structure building, comprising:

[0012] a first determining module configured to determine construction information parameters of a target building in response to a construction instruction of the target building, and determine a reference steel structure design model matched with the target building from a pre-stored structure design model library according to the construction information parameters;

[0013] a second determining module configured to determine a target steel structure design model matched with the target building based on the reference steel structure design model;

[0014] a building information model generating module configured to generate a building information model matched with the target building according to the target steel structure design model, generate component manufacturing data based on the building information model and the construction information parameters, and convert the component manufacturing data into processing control data;

[0015] a target building construction module configured to process a structural material to obtain a prefabricated component based on the processing control data, and assemble the prefabricated component at a construction site to obtain the target building.

[0016] According to another aspect of the present application, there is provided an electronic device, comprising:

[0017] at least one processor; and

[0018] a memory connected with the at least one processor in communication; wherein,

[0019] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the construction method of the fabricated steel structure building according to any one of the embodiments of the present application.

[0020] According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for enabling a processor to perform the construction method of the fabricated steel structure building according to any one of the embodiments of the present application when executed by the processor.

[0021] According to another aspect of the present application, there is provided a computer program product comprising a computer program for enabling a processor to perform the construction method of the fabricated steel structure building according to any one of the embodiments of the present application when executed by the processor.

[0022] The technical scheme of the embodiment of the present application determines the construction information parameter of the target building in response to the construction instruction of the target building, determines the reference steel structure design model matched with the target building from the pre-stored structure design model library according to the construction information parameter, determines the target steel structure design model matched with the target building based on the reference steel structure design model, generates the building information model matched with the target building according to the target steel structure design model, generates the component manufacturing data based on the building information model and the construction information parameter, and converts the component manufacturing data into the processing control data, processes the structural material based on the processing control data to obtain the prefabricated component, and assembles the prefabricated component at the construction site to obtain the target building, so that the problems of relying on manual experience, inconsistency between drawings and processing data, complex component specifications, high steel consumption and on-site assembly deviation can be solved, and the design efficiency, material utilization rate and construction precision can be improved.

[0023] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0025] Figure 1 is a flow chart of a construction method of a fabricated steel structure building according to an embodiment of the present application;

[0026] Figure 2 is a flow chart of a construction method of a fabricated steel structure building according to an embodiment of the present application;

[0027] Figure 3 is a structural schematic diagram of a construction device of a fabricated steel structure building according to an embodiment of the present application;

[0028] Figure 4 is a structural schematic diagram of an electronic device for implementing the construction method of the fabricated steel structure building according to an embodiment of the present application. DETAILED DESCRIPTION

[0029] In the following, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative effort should belong to the scope of protection of the present application.

[0030] It should be noted that the terms "first", "second" and the like in the description and claims of the present application and the above drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in other than the order illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a list of steps or units need not be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to such processes, methods, products or devices.

[0031] Embodiment one

[0032] Figure 1 It is a flowchart of a construction method of a fabricated steel structure building according to the embodiment one of the present application. The embodiment can be applicable to the case of determining the construction components for the target building to be constructed. The method can be executed by a fabricated steel structure building construction device, which can be realized in the form of hardware and / or software, and can be configured in a computer, a server or a tablet computer or other electronic devices. As shown in the figure, the method comprises: Figure 1

[0033] Step 110, in response to the construction instruction of the target building, determining the construction information parameters of the target building, and determining the reference steel structure design model matched with the target building from the pre-stored structure design model library according to the construction information parameters.

[0034] The target building can be a specific engineering project object to be designed and constructed, i.e. the fabricated steel structure building which has not been designed or constructed yet and is targeted by the current construction task, such as an office building, a museum, a residence or a warehouse, etc., which is not limited in the embodiment.

[0035] The construction instruction can be a digital request for starting the generation process of the target building initiated by a user or a higher system, which can contain a project identification or preliminary requirements.

[0036] ​The construction information parameters are structured parameters for characterizing the features of the target building, which are parsed from the construction instructions, and exemplary can include building type (e.g., office building, residence, factory building), number of floors (e.g., 6 floors, 18 floors), and regional information (e.g., name of the city to which it belongs, seismic fortification intensity, wind pressure partition, or 0.45 kN / m² wind pressure zone, etc.).

[0037] The structural design model library can be a pre-constructed standardized steel structure design model set indexed by construction information parameters, each model of which meets the design specifications of the corresponding region and is engineering-verified; the reference steel structure design model is an initial structure scheme retrieved from the model library that is closest to the target building in type, scale, and environmental conditions.

[0038] Optionally, in the embodiment, after receiving the construction instructions for constructing the target building, the key parameters for characterizing the features of the target building can be parsed from the instructions to form structured construction information parameters. It can be understood that these parameters mainly include building type, such as multi-storey residence, high-rise office building, industrial factory building, school or hospital, etc., for determining the overall structural system, such as frame structure, frame-support structure or tube structure; building scale, mainly referring to the number of main floors above ground, such as 5 floors, 12 floors, 24 floors, etc.; and project location information, which can be provided in the form of province, city or latitude and longitude, which can be automatically associated with the environmental and geological conditions in the national or local design specifications, including seismic fortification intensity, such as 7 degrees or 8 degrees, design basic seismic acceleration, site category, such as type II site, basic wind pressure, such as 0.40 kN / m² or 0.55 kN / m², and snow load, etc.

[0039] Optionally, in the embodiment, a structural design model library can be pre-constructed and maintained. The model library is composed of a plurality of engineering-verified reference steel structure design models, each of which corresponds to a typical building type and scale, and has completed structural calculation and construction drawing deepening under specific regional conditions. Each reference model is accompanied by complete metadata tags, which clearly mark its applicable scope, such as: high-rise office building, 10-18 floors, applicable to 8-degree seismic fortification zone, basic wind pressure less than or equal to 0.50 kN / m², standard column spacing 8.4m x 8.4m.

[0040] Further, based on the extracted construction information parameters, a matching operation can be performed in the model library: candidate models with consistent building types can be filtered, and then models with floor numbers falling within their applicable intervals are retained; further, it is checked whether the seismic fortification intensity, wind pressure, and other key parameters of the project location are within the allowable range of the model. If multiple models simultaneously meet all conditions, the model with the closest floor number, the strongest regional adaptability, or the most historical application times is preferred.

[0041] For example, when receiving a construction instruction of a 15-story steel structure office building project in City A, the construction information parameters can be extracted from the instruction: the building type is a high-rise office building, the number of floors is 15, and the location is City A. According to the relevant information, City A belongs to a 7-degree seismic fortification zone, and the basic wind pressure is 0.30 kN / m². Further, in the pre-stored structure design model library, all reference steel structure design models marked as high-rise office buildings, applicable floor numbers containing 15, and applicable seismic fortification intensity not less than 7 degrees, and wind pressure adaptation range covering 0.30 kN / m² are screened out. After comparison, a verified model originally used for "14-story office building in City A" is selected as the matching result. The model adopts a frame-central support system, with a standard column spacing of 8.4m x 8.4m, and the component section size is clear.

[0042] Step 120, determining a target steel structure design model matched with the target building based on the reference steel structure design model.

[0043] The target steel structure design model can be the final structure scheme after the reference steel structure design model is adapted and optimized to meet the specific needs of the target building, not only meeting the building layout, load conditions and specification requirements of the project, but also achieving comprehensive optimization in steel consumption, component size and type, and construction feasibility.

[0044] Optionally, in this embodiment, after determining the reference steel structure design model matched with the target building from the pre-stored structure design model library according to the construction information parameters, the reference steel structure design model can be further used as the initial solution to construct the input boundary conditions for structure analysis and optimization, combined with the actual construction information parameters of the target building, such as precise plane size, floor height, load difference caused by use function, local wind and snow earthquake parameters, etc. On this basis, a multi-objective optimization engine can be called to iteratively adjust the design variables such as column net position fine-tuning, support arrangement increase and decrease, steel column and steel beam section size, and node connection mode. In each iteration, structural mechanics analysis is automatically performed to check whether the safety indicators such as strength, stability and inter-story drift angle are met, while the total number of steel column and steel beam section sizes used in the current scheme is counted and the total steel consumption is calculated. It can be understood that the optimization process can take the minimization of total steel consumption as the objective function, and take the structure safety compliance and the number of component sizes not exceeding the pre-set upper limit as the constraint conditions, and continue to iterate until convergence. The final output structure scheme that meets all constraints and has optimal steel consumption is the target steel structure design model completely matched with the target building.

[0045] For example, if the reference model is a frame-support system suitable for a 12-18 story office building, and the target building is 15 stories but the standard floor plan is 3 meters wider than the reference model, the optimization process will automatically adjust the outer frame column distance, recheck the beam section capacity under the new span, and may replace the original H400x200 steel beam with H450x200 to balance the stiffness and standardization; At the same time, it will avoid introducing too many new section types, and will control the column and beam section types to less than 8 under the premise of safety, and finally generate a target steel structure design model that not only fits the actual target building, but also has the advantage of industrialized construction.

[0046] Step 130, generating a building information model matching the target building according to the target steel structure design model, generating component manufacturing data based on the building information model and construction information parameters, and converting the component manufacturing data into processing control data.

[0047] Among them, the building information model (Building Information Modeling, BIM) is a digital carrier that expresses the target steel structure design model in a three-dimensional parameterized manner, which not only contains the geometric shape, spatial positioning of the component, but also integrates non-geometric information such as material properties, section type, connection node type, etc. ; Component manufacturing data refers to structured process information used to guide factory production, including part drawings, hole coordinates, bevel forms, welding requirements, and material lists for each steel component; Processing control data is machine instructions that can be directly recognized and executed by numerical control equipment, such as G code, NC file or robot path program, used to drive cutting, drilling, welding and other automated equipment to complete physical processing.

[0048] Optionally, in this embodiment, after determining the target steel structure design model matching the target building, a three-dimensional building information model completely consistent with it can be automatically generated by a BIM modeling engine. Each steel column, steel beam and support in the model is assigned a unique component number and associated with its section size, material, connection node detail drawing and welding grade and other attributes; Further, from the BIM, extract all component geometric profiles, end bevel angles, bolt hole positions and diameters, bevel machining areas and other manufacturing parameters, and combine the regional specification requirements implied in the construction information parameters, such as special requirements for weld toughness in cold regions, to generate a standardized component manufacturing data package, content package; Further, input the above manufacturing data into a numerical control programming module, and automatically compile corresponding processing control data according to the type of target processing equipment, such as fiber laser cutting machine, three-dimensional numerical control drilling machine or six-axis welding robot, etc. For example, it can generate NC code with automatic material sorting instructions for laser cutting machines, and generate KRL scripts based on IGES three-dimensional path for welding robots.

[0049] In step 140, the structural material is processed based on the processing control data to obtain the prefabricated component, and the prefabricated component is assembled at the construction site to obtain the target building.

[0050] In the embodiment, the prefabricated component is a standardized part such as a steel column, a steel beam, or a support, which is accurately manufactured in a factory environment according to the processing control data. Each component has a unique identification (such as a two-dimensional code or an RFID tag) and is attached with geometric dimensions, cross-sectional models, and connection information. The construction site assembly refers to the process of assembling the prefabricated components transported to the construction site into an overall structural system according to the spatial position and connection relationship defined by the target steel structure design model through high-strength bolt connection, on-site welding, or a combination of bolting and welding.

[0051] In the embodiment, the processing control data is sent to the numerical control equipment of the factory production line, which may include, for example, a laser cutting machine, a three-dimensional drilling machine, and a welding robot. The equipment automatically cuts, drills, and bevels the structural material according to the instructions to manufacture prefabricated components such as steel columns, steel beams, and supports that meet the design requirements. A unique identification code is written on the surface of the component or in an embedded tag. The identification is associated with the installation position, the floor to which it belongs, and the connection node type in the target building. After the components are processed and pass the quality inspection, they are transported to the construction site according to the construction schedule.

[0052] Before hoisting, the construction personnel scans the component identification through a handheld terminal, retrieves the positioning information and connection requirements in the target steel structure design model, and checks for errors before using a tower crane or a crawler crane for positioning. Further, according to the pre-defined node structure in the design model, friction-type high-strength bolts are fastened or full-penetration welding is performed to complete the connection. Finally, a complete main structure is formed, and a target building that meets the design intent is built. Figure 1

[0053] The scheme of the embodiment determines the construction information parameters of the target building in response to the construction instructions of the target building, determines a reference steel structure design model matched with the target building from a pre-stored structural design model library according to the construction information parameters, determines a target steel structure design model matched with the target building based on the reference steel structure design model, generates a building information model matched with the target building according to the target steel structure design model, generates component manufacturing data based on the building information model and the construction information parameters, and converts the component manufacturing data into processing control data. The prefabricated component is obtained by processing the structural material based on the processing control data, and the target building is obtained by assembling the prefabricated component at the construction site. This can solve the problems of relying on manual experience, inconsistency between drawings and processing data, complex component specifications, high steel consumption, and on-site assembly deviation, and can improve design efficiency, material utilization, and construction accuracy.

[0054] Embodiment Two

[0055] ​Figure 2 is a flow chart of a method for constructing a fabricated steel structure building according to Embodiment Two of the present application. This embodiment is a further refinement of the above technical solution, and the technical solution in this embodiment can be combined with each optional scheme in one or more of the above embodiments. As shown in the figure, the method comprises: Figure 2

[0056] Step 210: Obtain building data sets of different building types.

[0057] Optionally, in this embodiment, before responding to the construction instruction of the target building, the method can further comprise: obtaining building data sets of different building types, and determining building parameter data of different regional information based on the building data sets; grouping the building parameter data according to building types and regional information, and counting the occurrence frequency of building height and floor number combinations in each group; selecting one or more building height and floor number combinations with the highest occurrence frequency in each group as reference floor type parameters; generating a reference steel structure design model based on the reference floor type parameters, the reference steel structure design model satisfying that the number of steel member cross section types is not more than a preset upper limit, the beam-column connection node adopts a standardized structure, and the main member geometric dimensions meet the modularization requirements; storing the reference steel structure design model according to building types, regional information and structure system classification to form a pre-stored structure design model library.

[0058] The building parameter data can include at least one of the following: building height, number of floors, shape coefficient, wall volume ratio and window volume ratio.

[0059] In this embodiment, the building data set can be a collection of engineering examples covering multiple building types collected from existing completed projects, design institute drawings or public databases, each example containing quantifiable building design and structure information.

[0060] The building parameter data can be key indicators extracted from the building data set to represent the geometric and physical characteristics of the building, including at least building height, number of floors, shape coefficient, wall volume ratio and window volume ratio; the reference floor type parameters are the typical values of the "building height-floor number" combination with the highest occurrence frequency in each group selected by grouping and counting the above parameters according to building types (e.g. residential, office building, factory building) and regional information (e.g. seismic fortification intensity, wind pressure zoning), representing the most common and most representative scale configuration in this category; the reference steel structure design model is a standardized structure scheme generated based on the typical parameters using the industrial design concept, and its core features include: the total number of steel member cross section types is not more than a preset upper limit (e.g. ≤4 types of columns, ≤4 types of beams, total ≤8 types), the beam-column connection node adopts a unified standardized structure, and the main geometric dimensions such as column spacing, span and story height meet the 300mm or 600mm modularization requirements, facilitating component reuse and factory batch production.​

[0061] Optionally, in the embodiment, data of built fabricated steel structure building projects in different regions can be collected to form original building data sets; further, parameters such as building height, floor number, shape coefficient, wall volume ratio, window volume ratio, etc. can be extracted from each project, and the building type label (for example, multi-storey residential building) and regional information (for example, 8-degree seismic region, 0.45 kN / m2 wind pressure, etc.) are associated to form a structured building parameter data table; further, multi-dimensional grouping is performed according to building type-regional information, for example, all high-rise office buildings + 7-degree region projects are grouped into one group, and the occurrence number of different combinations is counted in the group, for example, 54m-15 layers appear 23 times, 58m-16 layers appear 18 times, then 58m-16 layers are selected as the reference floor type parameters of the group; then, based on the parameters, standard column grid and uniform floor height are set, and sectional merging strategy is used for structure arrangement and component selection, on the premise of meeting the strength and displacement limit value, the number of sectional types is strictly controlled, and all nodes use standardized end plate connection detail drawings; finally, the generated model is labeled with metadata such as building type, regional information and structure system (for example, frame-support, pure frame, etc.) and stored in the database to form a pre-stored structure design model library that can be searched and reused.

[0062] The scheme of the embodiment effectively solves the problems of traditional model library relying on subjective experience, lack of regional adaptability and structural uniformity by systematically collecting real building data, statistically analyzing typical floor type parameters, and generating standardized steel structure design models that meet the industrialization constraints based thereon.

[0063] Step 220, in response to the construction instruction of the target building, determining the construction information parameters of the target building, and determining the reference steel structure design model matched with the target building from the pre-stored structure design model library according to the construction information parameters.

[0064] Optionally, in the embodiment, in response to the construction instruction of the target building, the construction information parameters of the target building are determined, and the reference steel structure design model matched with the target building is determined from the pre-stored structure design model library according to the construction information parameters, which can include: analyzing the construction instruction to determine the construction information parameters of the target building; based on the construction information parameters, determining the reference steel structure design model corresponding to the building type and the regional information from the structure design model library.

[0065] The construction information parameters include at least one of the following: building type, floor number, and regional information.

[0066] In an optional implementation of the embodiment, after receiving the construction instruction of the target building, the received construction instruction can be parsed to identify and extract the building type field, the number of floors field and the region field therein. Further, the building type can be mapped to a predefined standardized classification system, the region information can be converted into latitude and longitude through a geographic coding service, and relevant public databases or earthquake-related data can be queried to obtain the corresponding seismic fortification intensity. Further, multi-condition matching can be performed in the structural design model library: candidate models with building type codes consistent with the target in the metadata tags are screened, a subset of which covers the target number of floors is retained, and further verification is performed to ensure that the seismic fortification intensity of the model is not lower than the target requirement and the wind pressure range covers the target value. If there are multiple matching models, the optimal one is selected as the reference steel structure design model according to the principle of minimum floor number deviation, highest regional adaptation accuracy or highest historical calling frequency.

[0067] Step 230, determining a target steel structure design model matched with the target building based on the reference steel structure design model.

[0068] Optionally, in the embodiment, determining a target steel structure design model matched with the target building based on the reference steel structure design model can include: taking the reference steel structure design model as an initial model, calling a target machine learning model pre-trained to iteratively optimize the structure arrangement and member section parameters; in each iteration, checking whether the structure safety meets the preset structure design specification, and calculating the number of steel member specifications and the total steel consumption of the current scheme; when the iteration result meets the structure safety requirement, the number of steel member specifications does not exceed the preset upper limit, and the total steel consumption is not greater than the total steel consumption of the reference steel structure design model, the current iteration result is determined as the target steel structure design model.

[0069] It should be noted that in the embodiment, the target machine learning model is a core algorithm module for driving intelligent optimization of steel structures, which is essentially a closed-loop optimization agent deeply coupled with general structural calculation software, and is not independent to complete the entire design, but realizes intelligent design optimization through an iterative mechanism of AI suggestion-structure calculation-feedback correction.

[0070] The model first generates an initial structural layout and member section parameters based on a reference steel structure design model at runtime. Then, it automatically converts this scheme into an input file (such as.s2k or.mgt format) that can be recognized by general structural calculation software, driving the software to complete structural analysis under static, modal, and seismic actions, and obtain key performance indicators (such as inter-story drift angle, member stress ratio, overall stability coefficient, etc.). If any indicator does not meet the pre-set specification requirements, the current scheme is determined to be unsafe, and the calculation results are fed back to the target machine learning model. The model generates adjustment strategies based on this, such as increasing the beam section in weak areas, adding supports to improve lateral stiffness, or merging similar sections to reduce the number of standard types. The adjusted new scheme is again subjected to structural calculation software for verification.

[0071] When the results of a certain iteration meet all safety requirements, the optimization enters the second phase: under the premise of ensuring safety, further minimize the total steel consumption, minimize the number of steel member section types, and standardize the node construction as multi-objective functions for fine-tuning. At this time, the target machine learning model evaluates the economic efficiency and industrialization level of different schemes, and preferentially selects schemes that consume less steel, have higher component reuse rates, and are easier to mass-produce in factories.

[0072] The target machine learning model is not a black-box end-to-end design, but an intelligent decision hub that works with structural calculation software to efficiently explore the optimal structural scheme that meets the requirements of industrialized construction under the premise of ensuring engineering safety. Its training data comes from a large number of historical projects and their repeatedly verified optimization paths, enabling it to quickly converge to high-quality solutions, significantly better than traditional manual trial calculation methods that rely on engineers' experience.

[0073] In an optional implementation of the embodiment, a reference steel structure design model can be taken as the optimization starting point, and its structural arrangement topology and member cross-section parameters are encoded into a vector input into the target machine learning model. The model outputs a set of adjustment suggestions based on the learned design rules, such as moving a support position, replacing part of the H350 beam with an H300 to reduce weight, or unifying similar column cross-sections. A new candidate scheme is generated accordingly, and a structural analysis engine (such as an automated finite element-based calculation module) is called to perform internal force analysis under static and seismic actions to check whether the stress ratio, slenderness ratio, and overall inter-story drift angle of all members meet the specification limits. If the safety check passes, the number of different cross-section types used in all steel columns and steel beams in the current scheme is counted, and the total steel consumption is calculated. It is determined whether the three termination conditions are met simultaneously: (1) the structure safety meets the standard; (2) the number of steel member specifications is less than or equal to the preset upper limit; (3) the total steel consumption is less than or equal to the original steel consumption of the reference model. If all conditions are met, the current scheme is determined as the target steel structure design model. Otherwise, the current result is fed back to the machine learning model as new input, and the next iteration is started until convergence or the maximum number of iterations is reached.

[0074] The scheme of the embodiment effectively overcomes the defects of traditional steel structure design, such as reliance on manual trial and error, low efficiency, and difficulty in balancing safety and industrialization requirements, by introducing a target machine learning model that works cooperatively with general structural calculation software. Under the premise of ensuring that the structural safety strictly meets national standards, the optimization efficiency is significantly improved, and multiple goals such as reducing steel consumption, reducing the number of member cross-section specifications, and standardizing node construction are automatically achieved.

[0075] Step 240, generating a building information model matching the target building according to the target steel structure design model.

[0076] Optionally, in the embodiment, generating a building information model matching the target building according to the target steel structure design model can include: extracting member geometric data, cross-section types, and connection node types from the target steel structure design model; constructing a three-dimensional structural entity model based on the member geometric data; associating the cross-section types and connection node types as attribute information to the corresponding members in the three-dimensional structural entity model to generate the building information model.

[0077] In an optional implementation of the embodiment, after the target steel structure design model is determined, the geometric data of all components can be further parsed from the data structure of the target steel structure design model, including the bottom and top coordinates of each steel column, the axis endpoints and eccentricity values of each steel beam, the inclination angle of the support rod, etc. Meanwhile, the corresponding section type and connection node type are extracted. Further, the BIM modeling engine is called to generate a three-dimensional structure entity model with a real geometric volume by stretching or sweeping operation based on the component geometric data and the section profile definition. Further, the section type, steel grade, node type, and component unique number are embedded into the attribute table of the corresponding three-dimensional entity in the form of parameterized fields to establish a mapping relationship between geometry and semantics. Finally, an architectural information model file conforming to the industrial standard is output. For example, in the architectural information model file, any selected beam can query the section, material, nodes used at both ends, and geometric length, etc.

[0078] The scheme of the embodiment realizes seamless connection of the structure design results to digital manufacturing and construction by accurately converting the geometric data, section type, and node type in the target steel structure design model into an architectural information model rich in semantic information. The problems of repeated modeling, manual translation errors, and rework caused by the split of design and manufacturing information in the traditional process are avoided, and the integrated efficiency and accuracy from design to prefabrication are significantly improved, providing a reliable data foundation for high-fidelity and automated construction of prefabricated steel structure buildings.

[0079] Step 250, generating component manufacturing data based on the architectural information model and the construction information parameters, and converting the component manufacturing data into processing control data.

[0080] Optionally, in the embodiment, generating component manufacturing data based on the architectural information model and the construction information parameters, and converting the component manufacturing data into processing control data can include: extracting the three-dimensional geometric model of each steel component from the architectural information model; determining the manufacturing process rules corresponding to the target building according to the construction information parameters; generating the processing attributes of each steel component based on the three-dimensional geometric model and the manufacturing process rules; generating the numerical control cutting trajectory, drilling instruction, and welding path based on the three-dimensional geometric model and the processing attributes; compiling the numerical control cutting trajectory, drilling instruction, and welding path into the initial machine code of the corresponding processing equipment; performing processing feasibility checking on the initial machine code to determine whether there is equipment stroke overrun, tool interference, insufficient welding accessibility, or hole position overlapping conflict; when the checking result does not satisfy the preset manufacturing constraint condition, adjusting the processing attributes or process path and regenerating the machine code until the checking passes; determining the machine code that passes the checking as the processing control data.

[0081] The construction information parameters include building type, building height, and region information. The manufacturing process rules include welding level and groove requirement determined based on the seismic fortification level corresponding to the region information, and bolt hole precision and hole diameter tolerance determined based on the building type. The processing attributes include cross-section type, material, hole diameter, hole coordinate, and welding groove parameters. The processing control data can be used to drive a numerical control cutting machine, a drilling machine, or a welding robot to process the structural material to obtain the prefabricated component.

[0082] In an optional implementation of the embodiment, after obtaining the building information model, the three-dimensional geometric model of each steel component can be further extracted from the building information model. For example, the three-dimensional geometric model can include the spatial profile of the component, the end bevel, the hole position, and the groove area. The manufacturing process rules suitable for the project can be determined according to the construction information parameters (including building type, building height, and region information) of the target building. For example, the welding level and groove form can be determined according to the seismic fortification intensity of the region, and the precision level and tolerance requirement of the bolt hole can be determined according to the building type. The three-dimensional geometric model and the manufacturing process rules are combined to generate the processing attributes of each component, including cross-section type, material, hole diameter, hole coordinate, and welding groove parameters. Based on the geometric model and the processing attributes, numerical control cutting trajectories, drilling instructions, and welding paths are automatically generated. These process paths are then compiled into initial machine codes for corresponding processing equipment. The initial machine codes are checked for processing feasibility, and whether there are manufacturing conflicts such as equipment stroke overrun, tool or welding gun interference, welding space unreachability, and hole position overlap due to small spacing is checked. If the check fails, the relevant processing attributes (for example, the hole layout is modified, and the groove angle is optimized) or the process path is adjusted, and the machine code is regenerated and compiled. The checking process is repeated until all preset manufacturing constraints are met. Finally, the machine code that passes the check is determined as the processing control data, which is used to drive the production line equipment to complete the high-precision and conflict-free automatic processing of the component.

[0083] In step 260, the structural material is processed based on the processing control data to obtain the prefabricated component, and the prefabricated component is assembled at the construction site to obtain the target building.

[0084] Optionally, in the embodiment, the processing of the structural material based on the processing control data to obtain the prefabricated components and assembling the prefabricated components at the construction site to obtain the target building can include: issuing the processing control data to the production line equipment, controlling the laser cutting equipment to automatically arrange and cut the steel plate, or controlling the welding robot to perform automatic welding based on the three-dimensional path to manufacture the steel columns, steel beams and support components with unique identification; in the processing process, the production line equipment collects the processing state data in real time and returns the processing state data to the production management system; the production management system generates the component distribution instruction according to the processing state data and the structural arrangement relationship in the target steel structure design model, and transports the prefabricated components that have completed processing to the specified position at the construction site according to the installation order; at the construction site, the prefabricated components are verified and assembled according to the unique identification and the structural arrangement relationship, and the overall structure is formed through bolt connection or welding to complete the main construction of the target building.

[0085] In an optional implementation manner of the embodiment, after the processing control data of each component for constructing the target building is determined, the processing control data can be issued to the production line equipment to drive the laser cutting equipment to automatically arrange and high-precision cut the steel plate, or control the welding robot to perform automatic welding of full penetration or fillet weld according to the three-dimensional welding path, complete the manufacturing of the prefabricated components such as steel columns, steel beams and supports, and write a unique identification code on the surface of each component or in an embedded tag. The identification is associated with the component number, the floor to which it belongs, the installation position and the connection node type in the target steel structure design model; in the processing process, the production line equipment collects the processing state data in real time, including the processing start or end time, the equipment operation parameter, the abnormal alarm information and the actual completed component list, and returns the processing state data to the production management system through an industrial communication protocol; the production management system dynamically generates the component distribution instruction in combination with the processing state data and the structural arrangement relationship in the target steel structure design model, clearly defines the loading order, the transportation batch and the unloading area at the construction site of each component, and ensures that the prefabricated components are sequentially delivered to the specified hoisting position according to the structural installation logic; after the components arrive at the construction site, the construction personnel scan the unique identification on the components through the mobile terminal, call the corresponding structural arrangement information for on-site verification, confirm that there is no error, and according to the connection mode defined in the design model, the prefabricated components are precisely assembled by high-strength bolt fastening or on-site welding, and finally the overall steel structure system meeting the design intention is formed to complete the main construction of the target building.

[0086] The scheme of the embodiment realizes automatic manufacturing from a digital model to a physical component by deeply integrating the processing control data with the production line equipment, and builds a full-chain closed-loop management and control relying on a unique identification and real-time data return. It can ensure the high-precision and traceable production of prefabricated components, effectively avoid misloading, missing loading or secondary transportation, and further guarantee the assembly accuracy and construction efficiency through code scanning verification and model comparison on site. The assembly type steel structure building significantly improves the collaboration, controllability and industrialization level in the manufacturing, transportation and assembly links, and provides reliable support for efficient, accurate and less labor construction.

[0087] In order to better understand the assembly type steel structure building construction method involved in the embodiment, an example is used to illustrate it as follows:

[0088] In the embodiment, the data collection and analysis of different building types can be performed to sort out the building types in each region, i.e. collecting building data in different regions according to climate conditions, and performing preliminary data arrangement; using the main building types sorted out as typical examples, the design concept of industrialized steel structure building is used for building and structure design; by analyzing the collected building drawings, the height, number of floors, shape coefficient, volume rate, wall volume ratio, window volume ratio, etc. of each project are extracted and arranged, and according to the statistical requirements of each index, the typical building type is manually sorted and selected.

[0089] On the basis of manual design, advanced computer optimization algorithm is cited to quickly optimize steel structure calculation and find the optimal structure design scheme (including the optimal steel consumption of structure and reasonable steel member section size). The computer optimization operation idea of modular research and development of industrialized steel structure building is sorted out, the parameter modeling of plane geometric size, member section and load data of structure is completed, the calculation results are automatically extracted and automatic optimization iterative calculation is realized.

[0090] In the embodiment, according to low and high-rise buildings, the following can be preset: pure steel frame structure, pure steel frame-support structure, steel pipe concrete (CFT) frame structure, CFT steel frame-support structure, etc. For low-rise buildings, layered assembly steel frame-support structure with column hinge can be used. According to the building plan layout, preset component library, structure system, structure layer number, etc., manual arrangement suitable for intelligent optimization is performed according to artificial intelligence algorithm, and the boundary condition is set.

[0091] According to the structural arrangement determined by AI intelligence, generate structural model data, drive general structural calculation software for calculation, and if the index of the calculation result does not meet the specification requirements, readjust the cross section and adjust the structural arrangement until the specification requirements are met. According to the previously determined structural model, further structural optimization work is carried out to achieve the requirements of the least amount of steel, lower cost, fewer sizes of steel member cross sections, higher industrialization degree, etc., and comprehensive evaluation is carried out.

[0092] In the present embodiment, CAD drawings, IGS three-dimensional model data, IFC three-dimensional model data, etc. can be acquired, and these data are processed and integrated to generate BIM model data for factory production. A third-party design software is used to export grid body information configuration files to the BIM data target system. Data export application interaction is realized. The production management system automatically generates processing files and programs according to the generated BIM data and drawings. In the generation process, an artificial intervention checking link is set to check and correct parameters such as weld position. At the same time, AI intelligent algorithm is introduced, and the result of artificial correction is taken as training data to train the AI model to increase the accuracy of subsequent automatic programming.

[0093] The generated processing programs are sent to the production line, such as laser cutting automatic layout program of steel plate to improve the utilization rate of steel plate, automatic welding data of robot generated based on IGS / IFC three-dimensional model data, etc. The production line equipment processes and produces according to the received instructions, and real-time production data is fed back to the production system.

[0094] The production plan, real-time state, workshop location and processing completion time of each component are controlled and monitored throughout the process by the production management system.

[0095] In this embodiment, the status and control of a specific production line may include: ① Laser cutting machine: Data generated by BIM is transmitted to the laser cutting machine via the MES system. The laser cutting machine arranges production according to the MES plan and provides real-time feedback on the processing status. ② H-beam welded components: Production is arranged according to the production orders issued by the MES, and the processing output and production line status are provided in real-time. ③ 3D drilling: Receives processing task packages and plans from the MES system, processes each steel beam that has been basically fixed in length, and automatically sprays the corresponding QR code (barcode) on the steel beam after processing. This provides the processing basis for each beam for subsequent automatic welding and painting, and the processing information is fed back to the MES system. ④ Automatic stiffener welding robot: Automatically generates welding programs based on the 3D model provided by the BIM system. By scanning the QR code on the steel beam to identify the steel beam information, the corresponding welding program is retrieved from the system, and the stiffeners are automatically welded at the corresponding positions on the steel beam. After welding, an automatic transport truss transports the welded steel beam to the designated location for stacking. ⑤ Automatic Steel Column Welding Line: Welding programs for standard steel columns of different lengths are pre-input into the welding robot program. An automatic transport robot picks up the steel column from the welding material rack and places it on the welding rotary table. The welding robot automatically selects the welding program based on the different numbers and specifications of the steel column. After welding, the transport robot stacks the steel column on a designated finished product shelf. ⑥ Support Welding Robot: Employs a dual-station method, welding one group at a time. The welding program is pre-set according to standard products. During welding, the welding program is automatically selected based on the component number. ⑦ Spray Painting Line: Uses a suspended method. After shot blasting, when components lose their numbering characteristics, each hanging component is made into a virtual pallet. During loading, the components are scanned and placed in sequence. The position of the components on the spray painting line is monitored in real time during the shot blasting and painting process. After the components are painted and unloaded, the corresponding component's spray code is identified by recognizing the hanging piece (virtual pallet).

[0096] In this embodiment, components are uniquely identified using QR codes, barcodes (ideally, if not used), etc. Scanning the QR code allows for confirmation, modification, and viewing of the component's status, including raw materials arriving at the factory, processing in progress (cutting, assembly, welding, painting), processing completed, component leaving the factory, on-site acceptance completed, installation completed, and welding completed. The various statuses of the tracked components are displayed in the BIM model using color coding.

[0097] Instead of requiring on-site management personnel to upload data, the system should use AI cameras and various sensors to monitor and analyze data in real time, and provide early warnings for unsafe behaviors of people (wearing safety helmets, reflective vests, safety belts, smoking, entering restricted areas, etc.) and unsafe conditions of objects (loose key screws, fire, leaving power on after get off work, water leaks, electrical leaks, gas leaks, damaged protective gear, etc.).

[0098] Don't need the function of uploading data by on-site managers. ①, Establish a quality standard library, search for on-site quality inspection items, and can aggregate and display corresponding drawings, specification requirements, deviation requirements, common quality problems, sample methods, etc. Search for on-site quality problems, and can display standard rectification methods and steps. ②, Use intelligent equipment such as measurement robots, intelligent inspection rulers, intelligent rebound hammers, range finders, etc. to simplify the measurement and quantity work, and automatically upload the data to the management platform for aggregation and analysis. ③, Establish a quality management process, such as quality management personnel not confirming, unable to issue concrete delivery instructions to the mixing plant, similar to not being able to enter the next process, to avoid blind construction without inspection.

[0099] In an optional implementation of the embodiment, first, the determination of the structural system range: according to low and high-rise buildings, preset: pure steel frame structure, pure steel frame-support structure, steel pipe concrete (CFT) frame structure, CFT steel frame-support structure, etc. For low-rise buildings, a layered assembly steel frame-support structure with hinged columns can be used. The above structural systems are automatically determined according to the artificial intelligence algorithm.

[0100] Second, the suitable intelligent optimization of artificial arrangement of structural beams, columns and supports: according to the building plan arrangement, the preset component library, the structural system, the structural layer number, etc., the suitable intelligent optimization of artificial arrangement is carried out according to the artificial intelligence algorithm, and the boundary conditions are set. To reduce the number of AI intelligent optimization iterations, the structural section is intelligently selected in the component library.

[0101] Then, the AI intelligent design optimization cycle calculation is adopted again: according to the structure arrangement determined by AI intelligence, the structure model data is generated, the general structure calculation software is driven for calculation, and if the index of the calculation result does not meet the specification requirements, the section adjustment and the adjustment of the structure arrangement are performed again until the specification requirements are met.

[0102] Finally, the AI intelligent design optimization result is obtained: according to the previously determined structure model, further structure optimization work is carried out to achieve the requirements of the least steel consumption, lower cost, fewer steel member section sizes, higher industrialization degree, etc., and comprehensive evaluation is carried out.

[0103] In the factory production stage, CAD drawings, IGS three-dimensional model data, IFC three-dimensional model data and the like are obtained through a BIM model data generation module, and the data are processed and integrated; a third-party design software is used to export a grid body information configuration file to a BIM data target system, to realize data export application interaction and generate BIM model data for production. Then the BIM model data are transmitted to a production management system module, and the production management system automatically generates processing files and procedures according to the drawings and model data, arranges professionals to check parameters such as weld positions during the generation process, corrects errors in time, and inputs the corrected data into an AI intelligent algorithm for training, to improve the accuracy of subsequent automatic programming.

[0104] The generated processing procedures are sent to a production line equipment module, and a laser cutting machine produces according to the instructions and plans of the MES system and feeds back the processing state in real time; a three-dimensional drill processes and sprays a two-dimensional code on a steel beam, to provide a basis for subsequent processing; a web plate automatic assembly and welding robot, a steel column robot automatic welding line, a support welding robot and the like perform welding operations according to corresponding procedures and component information, and an automatic handling equipment completes the handling and stacking of components; a spraying line realizes the identification and position tracking of components through virtual pallet technology.

[0105] During the production process, all the equipment feeds back production data to the production management system in real time, and the production management system monitors and manages the whole production process, accurately masters the production progress and state of each component, and intelligently calculates the task completion time. Through the Internet of Things and big data technology, the whole-link production data are collected, to provide rich training data for AI intelligent production and continuously optimize the production process and equipment management.

[0106] The application collects and analyzes building data, and combs typical building floor types in various regions at home and abroad according to regions, types and floors. Building structure engineers design a structure model based on the combed typical building floor types, and propose boundary conditions as calculation data of an AI algorithm of industrialized steel structure. An AI optimization algorithm of a computer is used to optimize steel structure calculation, to find an optimal structure design scheme (including an optimal steel amount and reasonable steel component section size), to comb building characteristics meeting industrialized building production, and to obtain building production modules from single optimization to group optimization. Thus, the obtained building production modules are used to generate an AI industrialized integrated production of steel structure prefabricated buildings, and intelligent construction is performed.

[0107] Embodiment three

[0108] Figure 3 is a structural schematic view of a prefabricated steel structure building construction device according to the embodiment three of the application. Figure 3As shown, the device comprises a first determination module 310, a second determination module 320, a building information model generation module 330, and a building module 340.

[0109] The first determination module 310 is configured to determine construction information parameters of the target building in response to a building instruction of the target building, and determine a reference steel structure design model matched with the target building from a pre-stored structure design model library according to the construction information parameters.

[0110] The second determination module 320 is configured to determine a target steel structure design model matched with the target building based on the reference steel structure design model.

[0111] The building information model generation module 330 is configured to generate a building information model matched with the target building according to the target steel structure design model, generate component manufacturing data based on the building information model and the construction information parameters, and convert the component manufacturing data into processing control data.

[0112] The target building building module 340 is configured to process a structural material to obtain a prefabricated component based on the processing control data, and assemble the prefabricated component at a construction site to obtain the target building.

[0113] The scheme of the embodiment can solve the problems of relying on manual experience, inconsistent drawings and processing data, complex component specifications, high steel consumption, and on-site assembly deviation, and can improve design efficiency, material utilization rate, and construction precision.

[0114] In an optional implementation of the embodiment, the building device of the fabricated steel structure building further comprises a data acquisition module configured to acquire building data sets of different building types, and determine building parameter data of different regional information based on the building data sets, wherein the building parameter data comprises at least one of the following: building height, number of floors, shape coefficient, wall volume ratio, and window volume ratio.

[0115] grouping the building parameter data according to building types and region information, and counting occurrence frequencies of combinations of building heights and floor numbers in each group;

[0116] selecting one or more combinations of building heights and floor numbers with the highest occurrence frequencies in each group as reference floor type parameters;

[0117] generating a reference steel structure design model based on the reference floor type parameters, the reference steel structure design model satisfying that the types of steel member cross-section specifications are not more than a preset upper limit, beam-column connection nodes adopt standardized construction, and main member geometric dimensions meet modularization requirements;

[0118] storing the reference steel structure design model according to building types, region information and structure systems, and forming the pre-stored structure design model library.

[0119] In an optional implementation of the embodiment, the first determination module 310 is specifically configured to parse the construction instructions to determine construction information parameters of the target building, the construction information parameters including at least one of the following: a building type, a number of floors and region information;

[0120] based on the construction information parameters, determining a reference steel structure design model corresponding to the building type and the region information from the structure design model library.

[0121] In an optional implementation of the embodiment, the second determination module 320 is specifically configured to take the reference steel structure design model as an initial model, and call a target machine learning model pre-trained to iteratively optimize structure arrangement and member cross-section parameters;

[0122] In each iteration, it is checked whether the structure safety meets a preset structure design specification, and the number of steel member specification types and the total steel consumption of the current scheme are calculated;

[0123] When the iteration result meets the structure safety requirement, the number of steel member specification types is not more than the preset upper limit, and the total steel consumption is not greater than the total steel consumption of the reference steel structure design model, the current iteration result is determined as the target steel structure design model.

[0124] In an optional implementation of the embodiment, the building information model generation module 330 is specifically configured to extract member geometric data, cross-section types and connection node types in the target steel structure design model;

[0125] constructing a three-dimensional structure entity model based on the member geometric data;

[0126] Correlate the cross-sectional type and the connection node type as attribute information to corresponding components in the three-dimensional structure entity model, to generate the building information model.

[0127] In an optional implementation of the embodiment, the building information model generation module 330 is further specifically configured to extract a three-dimensional geometric model of each steel component from the building information model;

[0128] Determine a manufacturing process rule corresponding to the target building according to the construction information parameter;

[0129] Generate a machining attribute of each steel component based on the three-dimensional geometric model and the manufacturing process rule;

[0130] Generate a numerical control cutting track, a drilling instruction and a welding path based on the three-dimensional geometric model and the machining attribute;

[0131] Compile the numerical control cutting track, the drilling instruction and the welding path into initial machine code of corresponding machining equipment; perform machining feasibility verification on the initial machine code to determine whether there is equipment stroke overrun, tool interference, insufficient welding accessibility or hole position overlapping conflict;

[0132] When the verification result does not satisfy a preset manufacturing constraint condition, adjust the machining attribute or the process path and regenerate the machine code until the verification passes;

[0133] Determine the machine code that passes the verification as the machining control data.

[0134] In an optional implementation of the embodiment, the target building construction module 340 is specifically configured to issue the machining control data to production line equipment, control a laser cutting device to perform automatic layout cutting on a steel plate, or control a welding robot to perform automatic welding based on a three-dimensional path, to manufacture steel columns, steel beams and support components with unique identifications;

[0135] In the machining process, the production line equipment collects machining state data in real time and returns the machining state data to a production management system;

[0136] The production management system generates a component distribution instruction according to the machining state data and a structure arrangement relationship in the target steel structure design model, and transports the prefabricated components that have completed machining to specified positions at a construction site in installation order;

[0137] At the construction site, the prefabricated components are verified and assembled according to the unique identifications and the structure arrangement relationship, to form an overall structure through bolt connection or welding, and complete the main construction of the target building.

[0138] The construction device of the fabricated steel structure building provided in the embodiment of the present application can execute the construction method of the fabricated steel structure building provided in any embodiment of the present application, and has the function modules and beneficial effects corresponding to the execution method.

[0139] In the technical solution of the embodiment of the present application, the collection, storage, use, processing, transmission, provision and disclosure of the construction information parameters and the like are in line with the relevant laws and regulations and do not violate public order and good customs.

[0140] Embodiment four

[0141] Figure 4 A structural schematic diagram of an electronic device 10 that can be used to implement embodiments of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices such as personal digital processors, cellular telephones, smart phones, wearable devices (e.g., headsets, glasses, watches, etc.), and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present application described and / or claimed in this document.

[0142] As shown in Figure 4 The electronic device 10 includes at least one processor 11, and a memory, such as a Read-Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11, wherein the memory stores a computer program that can be executed by the at least one processor. The processor 11 can execute various appropriate actions and processes according to the computer program stored in the ROM 12 or loaded from the storage unit 18 to the RAM 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An Input / Output (I / O) interface 15 is also connected to the bus 14.

[0143] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, a loudspeaker, etc.; a storage unit 18, such as a magnetic disk, an optical disk, a mobile hard disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0144] The processor 11 can be various general and / or special purpose processing components having processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various special-purpose Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, a Digital Signal Processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the construction method of the fabricated steel structure building.

[0145] In some embodiments, the construction method of the fabricated steel structure building can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the construction method of the fabricated steel structure building described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the construction method of the fabricated steel structure building by other any appropriate means, such as by means of firmware.

[0146] The various embodiments of the systems and techniques described above can be implemented in digital electronic circuitry, integrated circuitry, a Field-Programmable Gate Array (FPGA), an Application-Specific Integrated Circuit (ASIC), an Application-Specific Standard Product (ASSP), a System on a Chip (SOC), a Complex Programmable Logic Device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0147] Computer programs used to implement the methods of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed by the processor of the machine, implements the functions / acts specified in the flow diagrams and / or block diagrams. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as part of a standalone software package, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0148] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a RAM, a ROM, an erasable programmable read-only memory (EPROM), an optical fiber, a compact disc - read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0149] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a Cathode Ray Tube (CRT) or a Liquid Crystal Display (LCD) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0150] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), blockchain networks, and the Internet.

[0151] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and virtual private service (VPS).

[0152] It should be understood that the various forms of flow shown above can be reordered, additional steps added, or steps deleted. For example, the steps described in the present application can be performed in parallel, in series, or in a different order, as long as the desired results of the technical solutions of the present application can be achieved, which are not limited herein.

[0153] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0154] The embodiment of the present application further provides a computer program product comprising a computer program which, when executed by a processor, implements the database detection method provided by any embodiment of the present application.

[0155] The computer program product can be written in one or more programming languages or combinations of languages to implement the operations of the present application, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as "C" language or similar programming languages. The program code can be executed entirely on a user computer, partially on a user computer, as a separate software package, partially on a user computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user computer through any kind of network, including LAN or WAN, or can be connected to an external computer (for example, through the Internet using an Internet service provider).

[0156] It should be noted that in the embodiments of the present application, some software, components, models and other prior art solutions can be mentioned, which should be considered as exemplary, and the purpose is only to illustrate the feasibility of the implementation of the technical solutions of the present application, but does not mean that the applicant has or will necessarily use the solution.

[0157] It should be noted that the above are only preferred embodiments of the present application and the technical principles applied. Those skilled in the art will understand that the present application is not limited to the specific embodiments herein, and those skilled in the art can make various obvious changes, readjustments and substitutions without departing from the scope of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments, and can include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A method of constructing a fabricated steel building structure, characterized by, The method comprises: determining construction information parameters of the target building in response to a construction instruction of the target building, and determining a reference steel structure design model matched with the target building from a pre-stored structure design model library according to the construction information parameters; determining a target steel structure design model matched with the target building based on the reference steel structure design model; generating a building information model matched with the target building according to the target steel structure design model, generating component manufacturing data based on the building information model and the construction information parameters, and converting the component manufacturing data into processing control data; processing a structural material based on the processing control data to obtain prefabricated components, and assembling the prefabricated components at a construction site to obtain the target building.

2. The method of fabricating a building of the assembled steel structure according to claim 1, wherein, Before responding to the construction instruction of the target building, the method further comprises: obtaining building data sets of different building types, and determining building parameter data of different regional information based on the building data sets; wherein the building parameter data comprises at least one of the following: building height, floor number, shape coefficient, wall volume ratio, and window volume ratio; grouping the building parameter data according to building types and regional information, and counting the occurrence frequency of building height and floor number combinations in each group; selecting one or more building height and floor number combinations with the highest occurrence frequency in each group as reference floor type parameters; generating a reference steel structure design model based on the reference floor type parameters, wherein the reference steel structure design model meets the requirements that the types of steel component cross-section specifications do not exceed a preset upper limit, the beam-column connection nodes adopt standardized construction, and the main component geometric dimensions meet the modularization requirements; storing the reference steel structure design model according to building types, regional information, and structure system classification to form the pre-stored structure design model library.

3. The method of fabricating a modular steel building structure of claim 1, wherein, The method comprises: analyzing the construction instruction to determine the construction information parameters of the target building; the construction information parameters comprise at least one of the following: building type, floor number, and regional information; based on the construction information parameters, determining a reference steel structure design model corresponding to the building type and regional information from the structure design model library.

4. The method of fabricating a modular steel building structure of claim 1, wherein, The method comprises: taking the reference steel structure design model as an initial model, and calling a pre-trained target machine learning model to iteratively optimize the structure arrangement and component cross-section parameters; in each iteration, checking whether the structure safety meets a preset structure design specification, and calculating the number of steel component specification types and the total steel consumption of the current scheme; when the iteration result meets the structure safety requirement, the number of steel component specification types does not exceed the preset upper limit, and the total steel consumption is not greater than the total steel consumption of the reference steel structure design model, determining the current iteration result as the target steel structure design model.

5. The method of fabricating a modular steel building structure of claim 1, wherein, The generating of the building information model matched with the target building according to the target steel structure design model comprises: extracting component geometric data, section type and connection node type in the target steel structure design model; constructing a three-dimensional structure entity model based on the component geometric data; associating the section type and connection node type as attribute information to the corresponding component in the three-dimensional structure entity model to generate the building information model.

6. The method of fabricating a building of the assembled steel construction, according to claim 5, characterized in that, The generating of component manufacturing data based on the building information model and the construction information parameter, and the conversion of the component manufacturing data into processing control data, comprises: extracting a three-dimensional geometric model of each steel component from the building information model; determining a manufacturing process rule corresponding to the target building according to the construction information parameter; generating a processing attribute of each steel component based on the three-dimensional geometric model and the manufacturing process rule; generating a numerical control cutting track, drilling instruction and welding path based on the three-dimensional geometric model and the processing attribute; compiling the numerical control cutting track, drilling instruction and welding path into initial machine code of the corresponding processing equipment; performing processing feasibility verification on the initial machine code to determine whether there is equipment stroke overrun, tool interference, insufficient welding accessibility or hole position overlapping conflict; when the verification result does not satisfy the preset manufacturing constraint condition, adjusting the processing attribute or process path and regenerating the machine code until the verification passes; determining the machine code that passes the verification as the processing control data.

7. The method of fabricating a modular steel building structure of claim 1, wherein, The processing of the structural material based on the processing control data to obtain prefabricated components, and the assembly of the prefabricated components at the construction site to obtain the target building, comprises: downloading the processing control data to the production line equipment to control the laser cutting equipment to automatically arrange and cut the steel plate, or to control the welding robot to perform automatic welding based on the three-dimensional path to manufacture steel columns, steel beams and support components with unique identification; in the processing process, the production line equipment collects processing state data in real time and returns the processing state data to the production management system; the production management system generates component distribution instructions according to the processing state data and the structure arrangement relationship in the target steel structure design model, and transports the prefabricated components that have completed processing to the specified position at the construction site according to the installation order; at the construction site, the prefabricated components are verified and assembled according to the unique identification and the structure arrangement relationship to form an overall structure through bolt connection or welding to complete the main construction of the target building.

8. A construction device of a fabricated steel structure building, characterized by, comprises: a first determination module configured to determine construction information parameters of a target building in response to a construction instruction of the target building, and determine a reference steel structure design model matched with the target building from a pre-stored structure design model library according to the construction information parameters; a second determination module configured to determine a target steel structure design model matched with the target building based on the reference steel structure design model; The building information model generation module is configured to generate a building information model matched with the target building according to the target steel structure design model, generate component manufacturing data based on the building information model and the construction information parameters, and convert the component manufacturing data into processing control data; The target building construction module is configured to process a structural material to obtain a prefabricated component based on the processing control data, and assemble the prefabricated component at a construction site to obtain the target building.

9. An electronic device, comprising: The electronic device comprises: at least one processor; and a memory connected to the at least one processor in communication; wherein The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the construction method of the fabricated steel structure building according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for enabling the processor to implement the construction method of the fabricated steel structure building according to any one of claims 1-7 when executed.

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