Intelligent installation control method and system for super-long and large-span steel structure net rack roof

Abstract

The application provides an intelligent installation control method and system for an ultralong large-span steel structure net rack roof, relates to the technical field of industrial control, and determines first and second type installation nodes by analyzing the installation process of the ultralong large-span steel structure net rack roof, collects basic installation information of steel components, respectively simulates modeling of the first type installation node and the second type installation node, constructs a first dynamic model and a second dynamic model, and controls the installation of the target installation node being performed by using the first dynamic model or the second dynamic model. The technical problem that the existing technology has low industrial control intelligence of the ultralong large-span steel structure net rack roof, resulting in insufficient overall construction safety and precision is solved. The technical effect of intelligent construction decision and industrial control and improved overall construction safety and precision is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial control, and particularly relates to an intelligent installation control method and system for a super-long large-span steel structure net rack roof. BACKGROUND

[0002] With the increasing number of super-long large-span public buildings, the steel structure net rack roof as a key stress and enclosure system has been widely used in important buildings such as large sports stadiums, exhibition centers and transportation hubs. Such structures are usually assembled by a large number of steel components in the air, which puts high requirements on the precision of component installation, the stability of node connection and the safety of the construction process. At present, the installation of the super-long large-span steel structure net rack roof mainly relies on manual experience and static construction plans for control, and cannot be flexibly adjusted according to the actual situation of the construction site. This not only leads to low construction efficiency, but also increases the risk in the construction control process. In addition, the traditional industrial control method is also difficult to effectively cope with uncertain factors such as weather changes and structural deformation, and the slight deformation of the structure in the stress process may also lead to a significant decrease in installation precision.

[0003] The prior art has the technical problem of low intelligence of industrial control of the super-long large-span steel structure net rack roof, which leads to insufficient overall construction safety and precision. SUMMARY

[0004] The present application provides an intelligent installation control method and system for a super-long large-span steel structure net rack roof, which solves the technical problem of low intelligence of industrial control of the super-long large-span steel structure net rack roof in the prior art, which leads to insufficient overall construction safety and precision.

[0005] In view of the above problems, the present application provides an intelligent installation control method and system for a super-long large-span steel structure net rack roof.

[0006] In a first aspect of the present application, an intelligent installation control method for an ultra-long large-span steel structure net rack roof is provided, the method comprising: reading and analyzing an installation process of the ultra-long large-span steel structure net rack roof to determine first type installation nodes and second type installation nodes, wherein the first type installation nodes are nodes corresponding to a support construction method, and the second type installation nodes are installation nodes corresponding to a cantilever construction method; collecting basic installation information of steel members for the first type installation nodes and the second type installation nodes respectively; performing simulation modeling of hoisting parameters responding to dynamic weather changes for the first type installation nodes based on the basic installation information to construct a first dynamic model; performing simulation modeling of cantilever parameters in a dynamic cantilever stage and simulation modeling of stable cantilever parameters in a static cantilever stage for the second type installation nodes based on the basic installation information to construct a second dynamic model; and performing installation control on a target installation node being performed by using the first dynamic model or the second dynamic model.

[0007] In a second aspect of the present application, an intelligent installation control system for an ultra-long large-span steel structure net rack roof is provided, the system comprising: an installation node determination module configured to read and analyze an installation process of the ultra-long large-span steel structure net rack roof to determine first type installation nodes and second type installation nodes, wherein the first type installation nodes are nodes corresponding to a support construction method, and the second type installation nodes are installation nodes corresponding to a cantilever construction method; an information collection module configured to collect basic installation information of steel members for the first type installation nodes and the second type installation nodes respectively; a first dynamic model construction module configured to perform simulation modeling of hoisting parameters responding to dynamic weather changes for the first type installation nodes based on the basic installation information to construct a first dynamic model; a second dynamic model construction module configured to perform simulation modeling of cantilever parameters in a dynamic cantilever stage and simulation modeling of stable cantilever parameters in a static cantilever stage for the second type installation nodes based on the basic installation information to construct a second dynamic model; and an installation control module configured to perform installation control on a target installation node being performed by using the first dynamic model or the second dynamic model.

[0008] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0009] The method provided in this application analyzes the installation process of an ultra-long span steel structure grid roof to determine a first type of installation node and a second type of installation node. The first type of installation node corresponds to the support construction method, and the second type of installation node corresponds to the cantilever construction method. Foundation installation information of the steel components is collected for both the first and second type of installation nodes. Based on the foundation installation information, a simulation model is built for the hoisting parameters of the first type of installation node to cope with dynamic weather changes, constructing a first dynamic model. Based on the foundation installation information, a simulation model is built for the cantilever parameters during the dynamic cantilever stage and the stable cantilever parameters during the static cantilever stage for the second type of installation node, constructing a second dynamic model. The installation of the target installation node is controlled using either the first or second dynamic model. This achieves intelligent construction decision-making and industrial control, improving the overall safety and accuracy of construction and increasing installation efficiency. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 A schematic diagram of the intelligent installation control method for the ultra-long span steel structure space frame roof provided in this application;

[0012] Figure 2 A structural schematic diagram of the intelligent installation control system for the ultra-long span steel structure space frame roof provided in this application.

[0013] Explanation of reference numerals in the attached diagram: Module 11 for determining installation nodes, Module 12 for information acquisition, Module 13 for constructing the first dynamic model, Module 14 for constructing the second dynamic model, and Module 15 for installation control. Detailed Implementation

[0014] This application provides an intelligent installation control method and system for ultra-long span steel structure space frame roofs, addressing the technical problem of insufficient intelligence in the industrial control of ultra-long span steel structure space frame roofs in existing technologies, leading to inadequate overall construction safety and precision. It achieves intelligent construction decision-making and industrial control, improving overall construction safety and precision, and increasing installation efficiency.

[0015] The technical solutions of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. It should be understood that the present invention is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention. It should also be noted that, for ease of description, only the parts related to the present invention are shown in the accompanying drawings, not all of them.

[0016] Example 1, as Figure 1 As shown, this application provides an intelligent installation control method for ultra-long span steel structure space frame roofs, the method comprising:

[0017] The installation process of the ultra-long span steel structure grid roof is read and analyzed to determine the first type of installation node and the second type of installation node. The first type of installation node is the node corresponding to the support construction method, and the second type of installation node is the installation node corresponding to the cantilever construction method.

[0018] Specifically, an ultra-long span steel space frame roof is a roofing system assembled from multiple steel components connected in a grid structure. It is commonly used in large-span buildings such as stadiums and exhibition halls. The steel components are assembled one by one, with each node representing a component. Components include roof panels, purlins, roof trusses, brackets, skylight frames, and supports. The process involves collecting relevant technical documents, construction drawings, construction plans, and engineering case studies related to the target ultra-long span steel space frame roof. These documents typically contain detailed installation steps, technical requirements, node connection methods, and material specifications. The collected data is then analyzed to obtain the installation process information for the steel space frame roof. Installation process analysis tools, such as AI-assisted drawing analysis modules and AI-StructureCAD tools, are used to analyze multiple components and their connection relationships. If a node is located on an existing support platform or ground support structure, it is marked as a first-type installation node. If the installation of a node relies on the gradual construction of a cantilever structure without direct support, it is marked as a Type II installation node. An installation node refers to the connection point of a component during installation. Each node typically corresponds to a connection point between one component and another. For example, in the space frame structure of an exhibition hall, the nodes in the middle area of ​​the roof truss are supported by temporary scaffolding and can be considered Type I installation nodes; while the roof panels in the edge skylight area cantilever outside the completed roof truss and have no independent support, thus they are Type II installation nodes. By classifying and identifying the structural types and support methods of installation nodes in ultra-long span steel space frame roofs through analysis, we can not only improve the relevance and accuracy of subsequent simulation modeling but also optimize installation path planning, achieve intelligent construction decision-making and industrial control, and improve the overall safety and accuracy of construction.

[0019] For the first type of installation node and the second type of installation node, respectively, the foundation installation information of the steel components is collected.

[0020] Furthermore, the basic installation information for any steel component includes the structural parameters of the steel component, the installation location of the steel component, the connection points with other structures, and the connection method.

[0021] Specifically, after classifying the installation nodes, for each steel component corresponding to the first and second types of installation nodes, foundation installation information for multiple steel components is collected from the target steel structure space frame roof data. This foundation installation information refers to data that must be known before the formal installation of the components and affects the installation process. This includes steel component structural parameters, installation location, connection points with other structures, and connection methods. Structural parameters, such as the component's geometric dimensions and weight, are used to determine the hoisting method and construction machinery configuration. The installation location refers to the component's spatial coordinates and orientation within the entire space frame roof, determining installation accuracy and structural compatibility. Connection points are the locations where components connect to other components or foundation structures, such as node numbers and connection surface coordinates. Connection methods refer to the specific installation methods for the components, such as welding, bolting, or plugging, and also include installation connection procedure requirements, such as whether immediate connection is required after hoisting or welding is done after other structures are in place. The installation connection procedure is determined in advance by the project's technical personnel according to the construction plan, which specifies the installation time, dependent components, and construction logic for each component, and can be uploaded through the user terminal. By collecting and acquiring basic installation information of steel components, we can more accurately understand the characteristics and installation requirements of each component, thereby improving the accuracy and consistency of component positioning and installation.

[0022] Based on the basic installation information, simulation modeling is performed on the hoisting parameters of the first type of installation node to cope with dynamic weather changes, and a first dynamic model is constructed.

[0023] Furthermore, based on the basic installation information, simulation modeling is performed on the hoisting parameters for the first type of installation node to cope with dynamic weather changes, constructing a first dynamic model, including: determining the target hoisting equipment for the installation of the ultra-long span steel structure grid roof, and collecting hoisting construction modeling data; performing digital modeling with the hoisting construction modeling data to generate a hoisting equipment twin model, wherein the controllable input variables of the hoisting equipment twin model are structural parameters, weather conditions, and installation location, and the simulation results include the hoisting parameters of the target hoisting equipment under different weather conditions; based on the hoisting equipment twin model, simulation training is performed on the changes in hoisting parameters under dynamic weather conditions using the steel component structural parameters and steel component installation location in the basic installation information corresponding to the first type of installation node, establishing the first dynamic model.

[0024] Specifically, based on the structural parameters of the components in the target ultra-long span steel structure space frame roof and the actual conditions of the construction site, such as lifting radius, height, and load, a matching process is performed in the construction equipment resource library to determine the target lifting equipment for installing the steel structure space frame roof, such as tower cranes, crawler cranes, and truck cranes. Then, based on construction drawings, equipment manuals, and site surveys, the necessary lifting construction modeling data for the lifting task is collected, including but not limited to equipment parameters, workspace constraints, construction site layout, component installation locations, and path planning requirements. Equipment parameters include boom length, maximum lifting capacity, and slewing radius. The collected data is cleaned to remove redundant, erroneous, or incomplete information, and the data is standardized to ensure consistency in format, units, and accuracy across different sources. Next, using 3D modeling software or digital twin modeling tools, such as SolidWorks and Autodesk, a 3D dynamic model consistent with the real equipment is constructed based on the collected lifting construction modeling data, generating a lifting equipment twin model. During the construction process, it is necessary to ensure that the lifting equipment twin model accurately reflects the actual structure and function of the lifting equipment. Based on the requirements of the hoisting operation, the controllable input variables of the hoisting equipment twin model are determined, including the structural parameters of the components (such as weight and dimensions), the weather conditions at the construction site (such as wind speed, wind direction, and temperature), and the spatial coordinate information of the component installation location. After inputting simulation data under different weather conditions, the hoisting equipment twin model can output the corresponding hoisting parameters, such as hoisting path, boom extension length, and hoisting operation speed.

[0025] Based on the completed twin model of the hoisting equipment, and combined with the foundation installation information corresponding to the first type of installation node, a refined simulation training was conducted on the hoisting process of steel components with support construction methods under dynamic weather conditions to establish a first dynamic model. Model configurations related to the first type of installation node, including the structural parameters and installation position coordinates of the node component, were extracted from the twin model and used as input variables. Dynamic weather data such as different wind speeds and directions were overlaid, and multiple rounds of simulation calculations and parameter training were performed to identify the hoisting parameters of the component under various weather conditions, thereby generating a lightweight first dynamic model that highly matches the first type of installation node. While retaining the core features of the twin model, the first dynamic model performs refined simulations on the steel components corresponding to the first type of installation node, enabling efficient and accurate node-level intelligent hoisting operations. Since the first type of installation node is a node type of support construction method, it is only necessary to hoist the component to the corresponding installation position. Through digital simulation technology to simulate weather changes, the first dynamic model can automatically match the corresponding hoisting parameters according to real-time weather, achieving intelligent control decisions and improving the safety of industrial control construction and the installation efficiency of steel structure grid roofs.

[0026] Furthermore, digital modeling is performed using the hoisting construction modeling data to generate a twin model of the hoisting equipment, including: configuring weather simulation boundary constraints; and performing digital simulations of structural parameters, weather conditions, and installation location using the hoisting construction modeling data according to the weather simulation boundary constraints to generate the twin model of the hoisting equipment.

[0027] Specifically, after constructing a simulation model and inputting relevant data, the simulation model performs calculations based on the modeling data. However, under extreme weather conditions, no matter how the hoisting parameters are adjusted, the hoisting position cannot be stabilized and balanced. Therefore, to avoid model deviations that are theoretically feasible but practically impossible to implement, before generating the hoisting equipment twin model, weather simulation boundary constraints are first set based on historical meteorological data, construction safety standards, and the extreme operating conditions marked in the equipment manual. Weather simulation boundary constraints refer to the extreme values ​​of weather conditions set in the simulation system, used to constrain the environmental input range during the simulation process. For example, the maximum wind speed must not exceed 8 m / s and / or the angle between the wind direction and the hoisting path must not exceed 75° and / or rainy / snowy weather or temperatures below -10°C. When weather variables, such as wind speed, wind direction, and temperature, exceed this boundary value, the current weather is considered unsuitable for construction, and the hoisting simulation is stopped or marked as infeasible to ensure construction safety. Then, according to the set weather simulation boundary constraints, combined with the hoisting construction modeling data, digital simulations are performed under structural parameters, weather conditions, and installation positions to conduct multi-scenario simulation calculations and generate the hoisting equipment twin model. During the simulation, the twin model of the hoisting equipment will automatically detect whether the weather input is within the boundary constraints: if it is within the workable range, the simulation output will be generated normally to obtain the simulation results; if it is in the extreme range, a construction infeasibility warning will be output, marking that operation cannot be carried out under this weather condition. Through the boundary constraint mechanism, the simulation results can be accurate and reliable, thereby improving the reliability of the simulation model and ensuring construction safety.

[0028] Based on the aforementioned basic installation information, simulation modeling of cantilever parameters in the dynamic cantilever phase and stable cantilever parameters in the static cantilever phase are performed for the second type of installation node to construct a second dynamic model.

[0029] Furthermore, based on the aforementioned basic installation information, simulation modeling of cantilever parameters in the dynamic cantilever stage and stable cantilever parameters in the static cantilever stage are performed for the second type of installation node to construct a second dynamic model. This includes: determining the cantilever construction platform used for the ultra-long span steel structure grid roof, and collecting construction modeling data for the dynamic cantilever stage by combining the component structural parameters and steel component installation positions in the basic installation information of the second type of installation node, and constructing a digital model for the dynamic cantilever stage; extracting the connection points and connection methods between the corresponding steel components and other structures in the basic installation information of the second type of installation node; performing a connection influence offset analysis of the steel components under static conditions based on the connection points and connection methods between the corresponding steel components and other structures, and generating a digital model for the static cantilever stage; and constructing the second dynamic model using the digital model for the dynamic cantilever stage and the digital model for the static cantilever stage.

[0030] Specifically, the second type of installation node refers to nodes constructed using a cantilever construction method. These nodes lack a supporting structure underneath during installation and rely on the existing structure for extension and connection, making the construction more difficult and risky than the first type of nodes with support. Based on this, a cantilever construction platform was selected for the ultra-long span steel structure space frame roof. This platform is the structural support system upon which the cantilever operation depends, such as temporary supports, climbing platforms, or connection systems with existing components. Next, the structural parameters of the components and the installation positions of the steel components were obtained from the foundation installation information of the second type of installation node. Based on the cantilever construction platform and the foundation installation information of the second type of installation node, construction modeling data for the dynamic cantilever stage was collected. The dynamic cantilever stage refers to the process where the component is hoisted to the target position but not yet fixed; the structure is in an unstable, wind-affected, temporary suspended state. Similar to the construction method of the first dynamic model, a digital model of the dynamic cantilever stage was constructed. Once the component is positioned at the target node, welding or bolting connections are required, entering the static cantilever stage. The static cantilever stage refers to the stage when the component is positioned and connection operations are performed. Based on the basic installation information of the second type of installation node, the connection points and connection methods between the corresponding steel components and other structures are determined, such as welding, bolting, and combined connections. Based on these connection points and methods, a static connection influence cancellation analysis is performed on the steel components to assess the impact of the connection process on the static stability of the steel components. Connection influence cancellation analysis involves modeling and simulating potential displacement, rotation, and stress concentration issues that may occur during the connection process, calculating potential displacement errors or angular deviations, and pre-setting compensation measures in the model to cancel and correct these errors. Examples include setting pre-offsets during hoisting and force balance adjustments during the connection process to ensure the component position does not shift, generating a static cantilever stage digital model. Furthermore, the dynamic and static cantilever stage digital models obtained for the two stages of the second type of installation node are integrated into a single model, forming a second dynamic model. The outputs of both the dynamic and static cantilever stage digital models are used as parameters for the two sequential stages. Through the second dynamic model, the overall stability and safety of the ultra-long span steel structure grid roof during cantilever construction can be comprehensively evaluated. Moreover, the connection influence cancellation simulation ensures that the position of the connected components does not shift, achieving precise control.

[0031] Furthermore, based on the connection points and connection methods between the corresponding steel components and other structures, a static connection influence cancellation analysis is performed on the steel components to generate a static cantilever stage digital model. This includes: performing an external force application influence analysis on the steel components based on the connection points and connection methods to generate position offsets under the influence of external forces; and performing a synchronous cancellation simulation of connection influences under static conditions on the steel components based on the position offsets to generate the static cantilever stage digital model. The synchronous cancellation simulation of connection influences includes simulation of adjusting the cantilever parameters.

[0032] Specifically, since the steel components are not fully stable and fixed during the cantilever stage, the connection points may be subjected to combined loads such as wind loads, bending moments caused by the component's own weight, and transmitted forces from adjacent components during welding or bolt tightening, leading to small displacements, rotations, or deformations in the components. Therefore, the influence of external forces on the steel components during the cantilever connection process is analyzed based on the connection points and connection methods. Based on the location and mechanical properties of the connection points, combined with weather simulation data, static simulation calculations are performed to generate the positional offset of the component under the influence of external forces. This positional offset represents the error caused by the connection when no compensation is made. Then, a synchronous offset simulation of the connection influence under static conditions is performed based on the positional offset. Using the optimization algorithm in the simulation software, compensation measures are automatically found for a new round of simulation. The above steps are repeated to iteratively optimize the model until the error converges to an acceptable range, generating the static cantilever stage digital model. The synchronous offset simulation of the connection influence includes the simulation of adjusting the cantilever parameters, i.e., the adjustment process includes adjusting the design parameters of the cantilever construction platform, such as the cantilever length and cantilever angle. By performing synchronous cancellation simulation of the connection effects of steel components under static conditions based on the position offset, the connection accuracy and structural stability of the second type of installation node can be ensured, thereby improving the intelligence, safety and control accuracy of industrial control.

[0033] Furthermore, based on the connection points and connection methods, an analysis of the impact of external force application is performed on the steel components to generate the positional offset under the influence of external force. This includes: training an external force application prediction model based on historical external force application monitoring data, analyzing the connection points and connection methods, and generating external force application results; and based on the structural information of the steel components, performing a positional offset analysis under the influence of external force application results to generate the positional offset.

[0034] Specifically, the process begins by retrieving external force monitoring data accumulated from previous ultra-long span steel structure roof installation projects or the current project's history. This data includes wind loads, torque generated by the self-weight of components at different angles, force transmission between adjacent components, and dynamic disturbances during the connection process. An external force application prediction model is then trained based on this monitoring data. For example, samples of external force data monitored in historical projects are collected, such as the correlation between wind speed and component sway amplitude, and the stress conditions at nodes under different connection methods. This data is then cleaned and features extracted. The external force application monitoring data and steel component structural information are used as input features, and node stress values ​​are used as output labels. Machine learning algorithms, such as neural network models, are then used to train the model, resulting in an external force application prediction model capable of predicting the external force application outcome under given new connection scenarios and environmental conditions. Based on the connection construction information of the current target node, this information is input into the external force application prediction model to calculate the current external force application result. This result represents the distribution of the main external forces actually acting on the component under this connection method, including direction, magnitude, and point of application. By combining the results of the applied external force and utilizing the structural information of the steel component, a positional offset analysis under the influence of the external force is performed. For example, the results of the applied external force and the structural information of the target steel component are input into a finite element simulation tool to construct a stress calculation scenario. Subsequently, through analytical calculation, the response of the component under the action of the external force is evaluated, obtaining its displacement, rotation angle, or overall attitude change in space, thereby outputting the positional offset of the component. By obtaining the positional offset of the steel component in the cantilever stage, a quantitative basis is provided for subsequent analysis of connection influence cancellation, thereby ensuring that the second dynamic model has a high-precision connection error control capability and comprehensively improving the construction safety and accuracy controllability of the cantilever node.

[0035] The installation of the target installation node is controlled using either the first dynamic model or the second dynamic model.

[0036] Specifically, after the construction of the first or second dynamic model is completed, the intelligent industrial control phase of the actual construction stage will begin. This involves real-time control, guidance, and feedback of the current construction node using the constructed first or second dynamic model. Before hoisting or connection operations, the type of installation node is identified. If it is a supported node (Type 1 installation node), the first dynamic model is loaded; if it is a cantilevered node (Type 2 installation node), the second dynamic model is loaded, ensuring the safety, accuracy, and adaptability of the entire installation process.

[0037] Furthermore, before controlling the installation of the target installation node using the first dynamic model or the second dynamic model, the process includes: constructing a construction feasibility judgment mechanism based on weather simulation boundary constraints; collecting weather forecast information for a preset construction time zone and inputting it into the construction feasibility judgment mechanism for judgment; if the judgment passes, issuing an installation feasibility control command.

[0038] Furthermore, before controlling the installation of the target installation node using the first dynamic model or the second dynamic model, the method further includes: if the determination fails, issuing an installation infeasibility warning.

[0039] Specifically, before applying the first or second dynamic model to the target installation node for construction control, a weather simulation-based feasibility assessment is first conducted to ensure that construction operations are carried out under safe and controllable environmental conditions. A feasibility assessment mechanism is built based on preset weather simulation boundary constraints to analyze and evaluate weather conditions during the upcoming construction period, thereby determining whether to allow the commencement of hoisting or connection operations at that node. Weather forecast data for the planned construction period is collected and used as input to the feasibility assessment mechanism for comparison and analysis. The input weather data is verified against the boundary constraints one by one, generating assessment results. When all meteorological conditions are within the safe boundary range, the current construction condition is deemed feasible, and an installation feasibility control command is automatically issued, initiating the corresponding dynamic model and entering the installation control process. However, if any indicator exceeds the limit, such as high wind speed, unfavorable wind direction, or excessively low temperature for high-altitude operations, construction is deemed infeasible, and an installation infeasibility warning is immediately issued, notifying construction personnel to suspend the installation operation plan. Through the discrimination mechanism, the system has shifted from passively waiting for weather changes to actively predicting construction conditions. This not only improves the scientific nature of operational decisions but also provides a safety guarantee for the industrial control decisions of overall intelligent installation, ensuring that installation operations are carried out in a safe and controllable environment, and ensuring construction safety and reliability.

[0040] Example 2, based on the same inventive concept as the intelligent installation control method for the ultra-long span steel structure grid roof in the aforementioned examples, such as... Figure 2 As shown, this application provides an intelligent installation control system for an ultra-long span steel structure space frame roof, wherein the system includes:

[0041] The installation node determination module 11 is used to read and analyze the installation process of the ultra-long span steel structure grid roof to determine the first type of installation node and the second type of installation node. The first type of installation node is the node corresponding to the support construction method, and the second type of installation node is the installation node corresponding to the cantilever construction method. The information acquisition module 12 is used to collect the foundation installation information of the steel components for the first type of installation node and the second type of installation node respectively. The first dynamic model construction module 13 is used to perform simulation modeling of hoisting parameters to cope with dynamic weather changes for the first type of installation node based on the foundation installation information to construct the first dynamic model. The second dynamic model construction module 14 is used to perform simulation modeling of cantilever parameters in the dynamic cantilever stage and stable cantilever parameters in the static cantilever stage for the second type of installation node based on the foundation installation information to construct the second dynamic model. The installation control module 15 is used to perform installation control on the target installation node in progress using the first dynamic model or the second dynamic model.

[0042] Furthermore, the information acquisition module 12 is also used to perform the following steps: the basic installation information of any steel component includes the structural parameters of the steel component, the installation position of the steel component, the connection points with other structures, and the connection method.

[0043] Furthermore, the first dynamic model construction module 13 is also used to perform the following steps: determine the target hoisting equipment for the installation of the ultra-long span steel structure grid roof, and collect hoisting construction modeling data; perform digital modeling using the hoisting construction modeling data to generate a hoisting equipment twin model, wherein the controllable input variables of the hoisting equipment twin model are structural parameters, weather conditions, and installation location, and the simulation results include the hoisting parameters of the target hoisting equipment under different weather conditions; based on the hoisting equipment twin model, perform simulation training on the changes in hoisting parameters under dynamic weather conditions using the steel component structural parameters and steel component installation location in the foundation installation information corresponding to the first type of installation node, and establish the first dynamic model.

[0044] Furthermore, the first dynamic model construction module 13 is also used to perform the following steps: configure weather simulation boundary constraints; according to the weather simulation boundary constraints, perform digital simulation of structural parameters, weather conditions and installation position using the hoisting construction modeling data to generate the hoisting equipment twin model.

[0045] Furthermore, the second dynamic model construction module 14 is also used to perform the following steps: determine the cantilever construction platform for the ultra-long span steel structure grid roof, and collect construction modeling data for the dynamic cantilever stage by combining the component structural parameters and steel component installation positions in the foundation installation information of the second type of installation node, and construct a digital model for the dynamic cantilever stage; extract the connection points and connection methods between the corresponding steel components and other structures in the foundation installation information of the second type of installation node; perform a connection influence offset analysis of the steel components under static conditions based on the connection points and connection methods between the corresponding steel components and other structures, and generate a digital model for the static cantilever stage; and construct the second dynamic model using the digital model for the dynamic cantilever stage and the digital model for the static cantilever stage.

[0046] Furthermore, the second dynamic model construction module 14 is also used to perform the following steps: perform an external force application influence analysis on the steel component based on the connection point and connection method, and generate the position offset under the influence of external force; based on the position offset, perform a synchronous cancellation simulation of the connection influence under static conditions of the steel component, and generate the digital model of the static cantilever stage, wherein the synchronous cancellation simulation of the connection influence includes the simulation of adjusting the cantilever parameters.

[0047] Furthermore, the second dynamic model construction module 14 is also used to perform the following steps: training an external force application prediction model based on historical external force application monitoring data, analyzing the connection points and connection methods, and generating external force application results; and performing position offset analysis under the influence of external forces based on the steel component structural information and the external force application results to generate the position offset amount.

[0048] Furthermore, the installation control module 15 is also used to perform the following steps: constructing a construction feasibility judgment mechanism based on weather simulation boundary constraints; collecting weather forecast information for a preset construction time zone, inputting it into the construction feasibility judgment mechanism for judgment, and issuing an installation feasibility control command if the judgment passes.

[0049] Furthermore, the installation control module 15 is also used to perform the following steps: if the determination fails, issue an installation infeasibility warning message.

[0050] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0051] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. An intelligent installation control method for an ultra-long and large-span steel structure net rack roof, characterized in that, The method comprises the following steps: reading the installation process of the super-long large-span steel structure grid roof and analyzing to determine a first type of installation node and a second type of installation node, wherein the first type of installation node is a node corresponding to a support construction method, and the second type of installation node is an installation node corresponding to a cantilever construction method; collecting basic installation information of steel members for the first type of installation node and the second type of installation node respectively; based on the basic installation information, simulating and modeling hoisting parameters of the first type of installation node for dynamic weather changes, and constructing a first dynamic model, specifically including: determining a target hoisting equipment for installing the super-long large-span steel structure grid roof, and collecting hoisting construction modeling data; performing digital modeling on the hoisting construction modeling data to generate a hoisting equipment twin model, wherein the controllable input variables of the hoisting equipment twin model are structure parameters, weather conditions and installation positions, and the simulation results include hoisting parameters of the target hoisting equipment under different weather conditions; based on the hoisting equipment twin model, performing hoisting parameter change simulation training on the steel member structure parameters and the steel member installation positions in the basic installation information corresponding to the first type of installation node under dynamic changes of weather conditions, and establishing the first dynamic model; based on the basic installation information, performing cantilever parameter simulation modeling in a dynamic cantilever stage and stable cantilever parameter simulation modeling in a static cantilever stage for the second type of installation node, and constructing a second dynamic model, specifically including: determining a cantilever construction platform for installing the super-long large-span steel structure grid roof, and collecting construction modeling data in the dynamic cantilever stage in combination with the member structure parameters and the steel member installation positions in the basic installation information of the second type of installation node to construct a digital model in the dynamic cantilever stage; extracting the connection points and connection modes of the corresponding steel members and other structures in the basic installation information of the second type of installation node; based on the connection points and connection modes of the corresponding steel members and other structures, performing connection influence offset analysis under the static state of the steel members to generate a digital model in the static cantilever stage; constructing the second dynamic model based on the digital model in the dynamic cantilever stage and the digital model in the static cantilever stage; controlling the installation of the target installation node being performed based on the first dynamic model or the second dynamic model.

2. The intelligent installation control method of the super-long and large-span steel structure grid roof according to claim 1, characterized in that, The basic installation information of any steel member includes steel member structure parameters, steel member installation positions, connection points with other structures and connection modes.

3. The intelligent installation control method of the super-long and large-span steel structure grid roof according to claim 1, characterized in that, performing digital modeling on the hoisting construction modeling data to generate a hoisting equipment twin model, including: configuring weather simulation boundary constraints; performing digital simulation on the hoisting construction modeling data under structure parameters, weather conditions and installation positions according to the weather simulation boundary constraints to generate the hoisting equipment twin model.

4. The intelligent installation control method of the super-long and large-span steel structure grid roof according to claim 1, characterized in that, based on the connection points and connection modes of the corresponding steel members and other structures, performing connection influence offset analysis under the static state of the steel members to generate a digital model in the static cantilever stage, including: performing external force application influence analysis on the steel members based on the connection points and connection modes to generate position offset amounts under the influence of external forces; Based on the position offset, a connection influence synchronous offset simulation under a static state of the steel member is performed to generate the digital model of the static overhanging stage, wherein the connection influence synchronous offset simulation includes adjustment simulation of overhanging parameters.

5. The intelligent installation control method of the super-long and large-span steel structure grid roof according to claim 4, characterized in that, Based on the connection points and the connection mode, an external force application influence analysis is performed on the steel member to generate the position offset under the influence of external force, including: Based on historical external force application monitoring data, an external force application prediction model is trained, and the connection points and the connection mode are analyzed to generate an external force application result; Based on the steel member structure information, a position offset analysis under the influence of external force is performed based on the external force application result to generate the position offset.

6. The intelligent installation control method of the super-long and large-span steel structure grid roof cover of claim 3, characterized in that, Before the installation control of the target installation node in progress is performed based on the first dynamic model or the second dynamic model, including: A construction feasibility determination mechanism is constructed with weather simulation boundary constraints; Weather prediction information of a preset construction time zone is collected and input into the construction feasibility determination mechanism for judgment. If the judgment passes, an installation feasible control instruction is issued.

7. The intelligent installation control method of the super-long and large-span steel structure grid roof according to claim 6, characterized in that, If the judgment fails, an installation infeasible warning information is issued.

8. The intelligent installation control system for the super-long and large-span steel structure grid roof, characterized in that, The steps of the intelligent installation control method for the super-long large-span steel structure net rack roof of any one of claims 1-7, comprising: An installation node determination module for reading and analyzing the installation process of the super-long large-span steel structure net rack roof to determine first type installation nodes and second type installation nodes, wherein the first type installation nodes are nodes corresponding to the support construction mode, and the second type installation nodes are installation nodes corresponding to the overhanging construction mode; An information collection module for collecting basic installation information of steel members for the first type installation nodes and the second type installation nodes respectively; A first dynamic model construction module for simulating dynamic weather changes based on the basic installation information for the first type installation nodes to construct a first dynamic model; A second dynamic model construction module for simulating overhanging parameters of a dynamic overhanging stage and stable overhanging parameters of a static overhanging stage based on the basic installation information for the second type installation nodes to construct a second dynamic model; An installation control module for performing installation control on a target installation node in progress based on the first dynamic model or the second dynamic model.

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