Intelligent control method for installation configuration of large-span steel structure

Abstract

The application discloses a large-span steel structure installation position intelligent control method and relates to the related field of building engineering.The method comprises the following steps: extracting design position parameters of each rod piece; establishing a calculation analysis model; performing construction simulation to obtain a predicted position; extracting a design position, calculating a position difference between the design position and the predicted position; adjusting installation position parameters, performing construction simulation iteration until the position difference is less than or equal to a position deviation threshold, and obtaining a construction scheme; performing on-site construction, obtaining actual position parameters in real time, obtaining a corrected construction scheme according to the actual position parameters, and performing installation position control. The method solves the technical problem that the existing large-span steel structure installation position control ignores dynamic factors in the construction process, leading to a large deviation between a predicted result and an actual situation, comprehensively considers various dynamic factors in the construction process, accurately predicts an actual position of the structure, adjusts in real time according to the predicted result, and ensures the technical effect of the installation precision of the structure.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of construction engineering, and particularly relates to a large-span steel structure installation position intelligent control method. BACKGROUND

[0002] The large-span steel structure is widely applied in large public buildings such as gymnasiums, exhibition halls, airport terminals and the like due to its unique spatial form, good mechanical properties and beautiful appearance. In the existing large-span steel structure installation process, the construction personnel performs static calculation and analysis on the steel structure based on the structural parameters in the design drawing to obtain the theoretical position of the structure. This method ignores the influence of various dynamic factors in the construction process, such as temperature change, construction load and the like, resulting in a large deviation between the prediction result and the actual situation.

[0003] In the related art, the large-span steel structure installation position control ignores the dynamic factors in the construction process, resulting in a large deviation between the prediction result and the actual situation. SUMMARY

[0004] The present application provides a large-span steel structure installation position intelligent control method, which extracts the design position parameters in the design drawing, establishes a calculation and analysis model of the overall structure state, obtains the predicted position after completion through construction simulation, calculates the position difference between the design position and the predicted position, adjusts the installation position parameters of the rods according to the difference, performs construction simulation iteration until the position difference meets the requirements, monitors the actual position parameters of each rod in real time during the construction process, and performs real-time construction simulation iteration adjustment to obtain a revised construction scheme, and controls the installation position of the large-span steel structure based on the revised construction scheme, so as to comprehensively consider various dynamic factors in the construction process, accurately predict the actual position of the structure, adjust in real time according to the prediction result, and ensure the installation accuracy of the structure.

[0005] The application provides a large-span steel structure installation position intelligent control method, including: extracting design position parameters of each rod of the steel structure in design drawings; establishing a calculation and analysis model of the overall structure state of the large-span steel structure according to the design position parameters; based on the calculation and analysis model, construction simulation is performed to obtain a predicted position after completion; the design position is extracted from the design drawings, and a position difference between the design position and the predicted position is calculated; the installation position parameters of the rod are adjusted according to the position difference, construction simulation iteration is performed until the position difference is less than or equal to a position deviation threshold, and a construction scheme is obtained; according to the construction scheme, on-site construction is performed, actual position parameters of each rod in the construction process are obtained through real-time monitoring, real-time construction simulation is performed according to the actual position parameters, a real-time position after completion is predicted, real-time construction simulation iteration adjustment of the installation position parameters is performed according to a real-time position difference between the real-time position and the design position, and a corrected construction scheme is obtained; and the installation position of the large-span steel structure is controlled based on the corrected construction scheme.

[0006] In a possible implementation, the design position parameters include coordinates, angles and structure sizes of the rod.

[0007] In a possible implementation, the calculation and analysis model of the overall structure state of the large-span steel structure is established according to the design position parameters, and the following processing is performed: the self-weight of the rod is calculated and obtained according to the structure size; the additional load applied in the installation process is obtained according to a preset installation process, and the additional load includes a construction equipment load, a temporary support load and an environmental load; and the calculation and analysis model of the overall structure state of the large-span steel structure is established according to the design position parameters, the self-weight and the additional load.

[0008] In a possible implementation, the construction simulation is performed based on the calculation and analysis model to obtain the predicted position after completion, and the following processing is performed: the construction process analysis is performed based on the calculation and analysis model to predict a construction completion position; and the usage state analysis is performed based on the construction completion position to obtain a predicted position of the structure after completion under preset usage load and preset non-resistant load.

[0009] In a possible implementation, the construction process analysis is performed based on the calculation and analysis model to predict the construction completion position, and the following processing is performed: the construction sequence position influence analysis, the construction operation position influence analysis and the construction additional load position influence analysis are performed based on the calculation and analysis model to predict a construction position change; and the stress distribution position influence analysis is performed according to the construction position change to predict the construction completion position.

[0010] In a possible implementation, the installation position parameter of the rod is adjusted according to the position difference value, construction simulation iteration is performed until the position difference value is less than or equal to the position deviation threshold, a construction scheme is obtained, and the following processing is performed: the adjustment step and the adjustment direction are determined according to the position difference value; the design position parameter is adjusted according to the adjustment step and the adjustment direction, to obtain an updated position parameter; construction simulation is performed according to the updated position parameter, and an updated position difference value is obtained; if the updated position difference value is greater than the position deviation threshold, iterative adjustment of the installation position parameter is performed until the updated position difference value is less than or equal to the position deviation threshold, to obtain the construction scheme.

[0011] In a possible implementation, the adjustment step and the adjustment direction are determined according to the position difference value, and the following processing is performed: historical position difference values and corresponding optimal adjustment steps and optimal adjustment directions are collected, a training data set is constructed according to the corresponding relationship of the historical data; the training data set is used to train a neural network, to obtain an adjustment strategy model; and the position difference value is input into the adjustment strategy model, to output the adjustment step and the adjustment direction.

[0012] In a possible implementation, the training data set is used to train a neural network, to obtain an adjustment strategy model, and the following processing is performed: historical position difference values are extracted from the training data set, and a historical position difference value vector is generated; the historical position difference value vector is converted into a historical position difference value matrix; and the training data set updated according to the historical position difference value matrix is input into a pre-trained convolutional neural network for transfer learning training, to obtain the adjustment strategy model.

[0013] The large-span steel structure installation position intelligent control method provided in the present application first extracts design position parameters of each rod of the steel structure in design drawings, then establishes a calculation and analysis model of the overall structure state of the large-span steel structure according to the design position parameters, then performs construction simulation based on the calculation and analysis model, obtains a predicted position after completion, then extracts a design position from the design drawings, calculates a position difference value between the design position and the predicted position, adjusts the installation position parameter of the rod according to the position difference value, performs construction simulation iteration until the position difference value is less than or equal to a position deviation threshold, obtains a construction scheme, then performs on-site construction according to the construction scheme, real-time monitoring is performed to obtain actual position parameters of each rod in the construction process, real-time construction simulation is performed according to the actual position parameters, a real-time position after completion is predicted, real-time construction simulation iteration adjustment of the installation position parameter is performed according to a real-time position difference value between the real-time position and the design position, to obtain a corrected construction scheme, and finally the installation position control of the large-span steel structure is performed based on the corrected construction scheme, so that various dynamic factors in the construction process are comprehensively considered, the actual position of the structure is accurately predicted, real-time adjustment is performed according to the prediction result, and the technical effect of ensuring the installation precision of the structure is achieved. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings of the embodiments of the present application will be briefly introduced below. In the present application, flowcharts are used to illustrate the operations performed by the method according to the embodiments of the present application. It should be understood that the foregoing or the following operations are not necessarily performed in sequence. On the contrary, various steps can be processed in reverse order or simultaneously according to needs. Meanwhile, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0015] Figure 1 A flowchart of the intelligent control method of the installation configuration of the long-span steel structure provided by the embodiments of the present application is shown.

[0016] Figure 2 A flowchart of obtaining a construction scheme in the intelligent control method of the installation configuration of the long-span steel structure provided by the embodiments of the present application is shown. DETAILED DESCRIPTION

[0017] The foregoing description is only a summary of the technical solutions of the present application. In order to more clearly understand the technical means of the present application, the embodiments of the present application can be implemented according to the content of the description, and in order to make the above and other purposes, characteristics and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described.

[0018] In order to make the purposes, technical solutions and advantages of the present application more clear, the following will further describe the present application in combination with the drawings, and the described embodiments should not be regarded as limiting the present application. All other embodiments obtained by those skilled in the art without making creative efforts belong to the scope of protection of the present application.

[0019] In the following description, "some embodiments" are described, which describe a subset of all possible embodiments, but it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. The terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or server including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as understood by those skilled in the art in the technical field to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application.

[0020] The embodiments of the present application provide an intelligent control method of installation configuration of a long-span steel structure, as shown in Figure 1 the method comprises:

[0021] Step S100, extract the design configuration parameters of each member of the steel structure in the design drawing.

[0022] Specifically, through computer-aided design (CAD) software or building information modeling (BIM) technology, the geometric dimensions, position coordinates, cross-section characteristics and other design configuration parameters of each member of the steel structure are extracted one by one from the design drawing by using the measurement tool or attribute query function of the software, and are arranged into an electronic table or database form for subsequent analysis and calculation.

[0023] In one possible implementation, step S100 further includes step S110, and the design configuration parameters include the coordinates, rotation angles and structural dimensions of the members. Specifically, the position of a member in space is determined by its coordinates, which are defined in three-dimensional space and include values in X, Y and Z directions. In CAD or BIM software, these coordinate values can be obtained by selecting the member and viewing its attributes. The rotation angle describes the rotation angle of the member relative to its initial position or reference direction, and is expressed in degrees (°) or radians (rad). The structural dimensions include the length, width, height (or diameter for circular cross-section) and other geometric parameters of the member. These dimensions determine the physical properties and load-carrying capacity of the member. In CAD or BIM software, these dimension values can be obtained by using the measurement tool or attribute query function. This implementation ensures the accuracy and reliability of the subsequent calculation and analysis model by extracting the design configuration parameters such as the coordinates, rotation angles and structural dimensions of the members. By accurately extracting these parameters, the as-built configuration of the long-span steel structure can be more effectively predicted, and real-time adjustments can be made during the construction process to ensure that the final structure meets the design requirements.

[0024] Step S200, according to the design configuration parameters, establish a calculation and analysis model of the overall structural state of the long-span steel structure.

[0025] Specifically, the extracted member parameters are input into finite element analysis (FEA) software such as ANSYS, SAP2000, etc., the physical and mechanical properties of the material are defined, the boundary conditions and load conditions are set, and the overall structural state calculation and analysis model of the long-span steel structure is established.

[0026] In one possible implementation, according to the design configuration parameters, a calculation and analysis model of the overall structural state of the long-span steel structure is established, and step S200 further includes step S210 of calculating the self-weight of the member according to the structural dimensions. Specifically, according to the extracted structural dimensions (such as length, cross-sectional area, wall thickness, etc.) of the member, combined with the density of the steel used, the mass of each member is calculated.

[0027] At step S220, according to the preset installation process, the additional load applied in the installation process is obtained, and the additional load includes a construction equipment load, a temporary support load, and an environmental load. Specifically, according to the preset installation process, the additional load (in the installation process, in addition to the self weight of the rod, other external forces acting on the structure) involved in each construction stage is listed in detail, and the load is derived from the weight of the construction equipment (such as a crane, a sling, etc.), the weight of the temporary support structure (such as a scaffold, a support frame, etc.), and the influence of environmental factors (such as wind load, snow load, temperature stress, etc.). The size of the load is estimated by referring to relevant design specifications or standards. For example, for wind load, local meteorological data can be consulted, and wind load calculation formula is used to estimate according to wind speed and wind direction.

[0028] At step S230, a calculation and analysis model of the overall structure state of the long-span steel structure is established according to the design shape parameter, the self weight, and the additional load. Specifically, the obtained design shape parameter, the self weight of the rod, and the additional load are taken as input data, and a calculation and analysis model of the overall structure state of the long-span steel structure is established by using a structure analysis software (such as ANSYS, SAP2000, etc.). The software can automatically calculate key parameters such as internal force distribution, deformation, and stability of the structure according to the information. This implementation provides accurate structure state information and analysis tools by establishing a calculation and analysis model, and can perform virtual testing and optimization design on the structure before construction to reduce risks and uncertainties in the construction process.

[0029] At step S300, construction simulation is performed based on the calculation and analysis model to obtain a predicted shape after completion.

[0030] Specifically, the construction process of the long-span steel structure is simulated by using the construction simulation function of the finite element analysis software, including hoisting, sliding, lifting, jacking, and other construction technologies, the rod installation, load application, and deformation in each construction stage are simulated, and finally the predicted shape after completion is obtained, that is, the predicted shape is the expected geometric shape and position of the long-span steel structure after completion calculated by the construction simulation software.

[0031] In one possible implementation, based on the calculation and analysis model, construction simulation is performed to obtain a predicted shape after completion, and step S300 further includes step S310 of performing construction process analysis based on the calculation and analysis model to predict a construction completion shape. Specifically, the construction process is divided into multiple construction stages, and each stage corresponds to a certain construction step or change of construction conditions. The finite element analysis or structural dynamics analysis is performed step by step for each stage to simulate the deformation and stress of the steel structure in each stage. The predicted shape after completion (construction completion shape) is obtained by accumulating the deformations of the stages.

[0032] At step S320, based on the construction completion configuration, a use state analysis is performed to obtain a predicted configuration of the structure under a preset use load and a preset non-resistive load after completion. Specifically, various load conditions that the structure may encounter during the use stage are determined, including regular use loads (regular loads borne by the structure during use, such as floor live loads, equipment loads, etc.) and non-resistive loads (extreme or unpredictable loads that the structure may encounter, such as wind loads, snow loads, and earthquake loads under extreme weather conditions, etc.). These loads are applied to the construction completion configuration to perform finite element analysis or structural dynamics analysis, to obtain the deformation and stress conditions of the structure under these loads, and to obtain the predicted configuration. This implementation predicts the configuration after completion of the construction process through construction process analysis, and performs use state analysis based on the configuration, to evaluate the configuration change of the structure during long-term use, which helps to optimize the construction scheme and ensure the quality and safety of the structure.

[0033] In a possible implementation, based on the calculation analysis model, construction process analysis is performed to predict the construction completion configuration, and step S310 further includes step S311, based on the calculation analysis model, construction sequence configuration influence analysis, construction operation configuration influence analysis, and construction additional load configuration influence analysis are performed to predict the construction configuration change. Specifically, the construction process is divided into multiple stages, each stage corresponding to a certain construction step. Through finite element analysis, the influence of each construction step on the structure configuration is simulated, and these influences are accumulated to predict the configuration change of the entire construction process. For example, which members are installed first, which members are installed later, and how the installation sequence of each member affects the overall structure configuration. The influence of specific operations in the construction process, such as welding, bolt connection, etc., on the structure configuration is analyzed. These operations may cause local deformation or stress concentration of the structure, and the influences are evaluated through finite element analysis. The influence of additional loads applied during the construction process, such as the weight of construction equipment, the arrangement of temporary supports, and environmental factors (such as wind load, temperature change) on the structure configuration is analyzed, and these additional loads may cause additional deformation of the structure, which is predicted through finite element analysis.

[0034] At step S312, stress distribution configuration influence analysis is performed according to the construction configuration change to predict the construction completion configuration. Specifically, based on the construction configuration change predicted in step S311, stress distribution analysis is performed, including evaluating the stress state of each member and node, and how these stress states change as the construction process progresses. Through finite element analysis, the stress distribution and configuration state after construction completion are predicted. This implementation gradually and deeply analyzes the configuration change during the construction process through finite element analysis, improving the accuracy of configuration prediction.

[0035] Step S400: Extract the design configuration from the design drawings and calculate the configuration difference between the design configuration and the predicted configuration.

[0036] Specifically, the design configuration is extracted from the design drawings using CAD or BIM software. The comparison tools in the software or scripts are used to compare the coordinate values ​​or shape differences between the design configuration and the predicted configuration at various key points or in the overall shape. The configuration difference is calculated, which refers to the difference between the design configuration and the predicted configuration.

[0037] Step S500: Adjust the installation configuration parameters of the members according to the configuration difference value, and perform construction simulation iteration until the configuration difference value is less than or equal to the configuration deviation threshold to obtain the construction plan.

[0038] Specifically, based on the configuration difference, the installation configuration parameters of the members in the model, such as the initial position and tilt angle, are adjusted. Then, the construction process of the large-span steel structure is simulated again using finite element analysis software or real-time construction simulation software to obtain a new predicted configuration. The new predicted configuration is then compared with the design configuration to obtain a new configuration difference. This process is repeated until the configuration difference is less than or equal to the configuration deviation threshold (the allowable configuration difference range; adjustments are required if the value exceeds this range, such as ±5mm), thus obtaining a construction scheme that meets the requirements.

[0039] like Figure 2 As shown, in one possible implementation, the installation configuration parameters of the member are adjusted according to the configuration difference value, and construction simulation iterations are performed until the configuration difference value is less than or equal to the configuration deviation threshold to obtain a construction plan. Step S500 further includes step S510, determining the adjustment step size and adjustment direction based on the configuration difference value. Specifically, the gradient (i.e., derivative or partial derivative) of the configuration difference value relative to the design configuration parameters is calculated, which indicates the direction and rate of error change with the design parameters. The adjustment step size for each step is determined according to the magnitude and direction of the gradient, as well as a preset learning rate (or step size factor). The adjustment direction is determined by the sign of the gradient; a negative gradient indicates the direction of error reduction.

[0040] Step S520: Adjust the design configuration parameters according to the adjustment step size and the adjustment direction to obtain updated configuration parameters. Specifically, multiply the current design configuration parameters by the adjustment step size and the adjustment direction to obtain the updated design configuration parameters.

[0041] Step S530: Perform construction simulation based on the updated configuration parameters and obtain the updated configuration difference value. Specifically, use finite element analysis or other structural analysis methods to simulate based on the updated design configuration parameters. After the simulation is completed, calculate the configuration difference value between the new predicted configuration and the design configuration.

[0042] Step S540, if the updated shape difference value is greater than the shape deviation threshold, iterative adjustment of the installation shape parameters is performed until the updated shape difference value is less than or equal to the shape deviation threshold, and a construction scheme is obtained. Specifically, the updated shape difference value is compared with the preset shape deviation threshold. If the updated shape difference value is less than or equal to the shape deviation threshold, it is considered that a satisfactory result has been converged, the iteration is stopped, the updated shape parameter corresponding to the updated shape difference value is obtained, and the updated shape parameter is taken as the construction scheme for subsequent processing and installation of each member. If the updated shape difference value is greater than the shape deviation threshold, the process returns to step S510, and the design shape parameter is iteratively adjusted until the updated shape difference value is less than or equal to the shape deviation threshold, and the corresponding construction scheme is obtained. This implementation ensures that the installation shape of the long-span steel structure is as close as possible to the design shape, thereby meeting the engineering requirements, through iterative adjustment.

[0043] In a possible implementation, the adjustment step and the adjustment direction are determined according to the shape difference value. Step S510 further includes step S511 of collecting historical shape difference values and corresponding optimal adjustment steps and optimal adjustment directions, and constructing a training data set according to the corresponding relationship of the historical data. Specifically, data is collected from past projects, including the shape difference value at each iteration, the adjustment step and the adjustment direction taken, and whether these adjustments result in a decrease in the shape difference value. The adjustment step and the adjustment direction that result in a significant decrease in the shape difference value are selected as the optimal solution to form the training data set.

[0044] Step S512, the training data set is used to train the neural network to obtain an adjustment strategy model. Specifically, a neural network architecture is selected, such as a multi-layer perceptron (MLP), a convolutional neural network (CNN), or a recurrent neural network (RNN). The training data set is input into the neural network, and the weights and biases of the neural network are adjusted through a backpropagation algorithm until the performance of the model on the validation set reaches a satisfactory level. During the training process, the performance of the model on the validation set is periodically evaluated to prevent overfitting.

[0045] Step S513, the shape difference value is input into the adjustment strategy model, and the adjustment step and the adjustment direction are output. Specifically, the shape difference value in the current iteration is input as input data into the trained adjustment strategy model, and the model outputs the predicted adjustment step and the adjustment direction according to the input shape difference value. According to the output of the model, the design shape parameter is adjusted, and the iteration process is continued. This implementation uses a neural network to predict the adjustment step and the adjustment direction. The neural network can automatically learn the rules in the historical data and guide future adjustments according to these rules, thereby improving the accuracy and efficiency of determining the adjustment step and the adjustment direction.

[0046] In a possible implementation, the neural network is trained by using the training data set to obtain an adjustment strategy model, and step S512 further includes the following step S5121: extracting historical position difference values from the training data set and generating a historical position difference value vector. Specifically, all data records containing position difference values are filtered from the historical data set. The extracted position difference values are converted into vector form. If the position difference value is a multi-dimensional data (for example, containing difference values in X, Y and Z directions), each position difference value can be converted into a three-dimensional vector. If the position difference value is one-dimensional data, it is directly converted into a one-dimensional vector. In order to improve the training efficiency and performance of the model, the data is standardized to scale the data to a suitable range (such as between 0 and 1) and eliminate the dimensional differences between different features.

[0047] Step S5122: converting the historical position difference value vector into a historical position difference value matrix. Specifically, a plurality of historical position difference value vectors are spliced into a large matrix in a certain order, each row representing a data record (that is, a historical position difference value vector), and each column representing a feature (that is, a certain dimension of the position difference value). If the number of position difference values in the data set is insufficient to form a large enough matrix, the size of the matrix is expanded by using data enhancement techniques such as data replication, data interpolation and the like.

[0048] Step S5123: inputting the training data set updated according to the historical position difference value matrix into a pre-trained convolutional neural network for transfer learning training to obtain an adjustment strategy model. Specifically, a pre-trained convolutional neural network that performs well on similar tasks is selected as a feature extractor. For example, a VGG, ResNet or the like model pre-trained on an image classification task can be selected. A new fully connected layer is added to the pre-trained model as an output layer for predicting the adjustment step and the adjustment direction. Then, the updated training data set is used for fine-tuning the model. During the fine-tuning process, some parameters of the pre-trained model can be frozen to reduce the amount of calculation and speed up the training process. This implementation extracts the position difference values from the historical data set and converts them into vector and matrix forms, which can be conveniently used for neural network training. By using the transfer learning technology and using the pre-trained convolutional neural network as a feature extractor, the learning process of the adjustment strategy model is accelerated and the prediction accuracy is improved.

[0049] Step S600: performing site construction according to the construction scheme, monitoring and obtaining actual position parameters of each member in the construction process in real time, performing real-time construction simulation according to the actual position parameters, predicting a real-time position after completion, performing real-time construction simulation iterative adjustment of the installation position parameters according to real-time position difference values between the real-time position and the design position, and obtaining a revised construction scheme.

[0050] Specifically, according to the construction scheme, actual construction is carried out, in the construction process, the actual position parameters of each rod are monitored in real time by using monitoring equipment such as sensors, laser range finders, total stations and the like, and are input into the real-time construction simulation software. The software adjusts the calculation and analysis model in real time according to the monitoring data, predicts the real-time position after completion, and compares with the design position. If the difference between the real-time position and the design position is greater than the position deviation threshold, the installation position parameters of the rods are adjusted, and real-time construction simulation iterative adjustment is carried out until the difference between the real-time position is less than or equal to the position deviation threshold, and a corrected construction scheme is obtained, the corrected construction scheme being the installation position parameters corresponding to the real-time position difference less than or equal to the position deviation threshold.

[0051] Step S700, based on the corrected construction scheme, installation position control of the long-span steel structure is carried out.

[0052] Specifically, according to the corrected construction scheme, on-site construction is organized. In the construction process, the actual construction situation is tracked and fed back in real time by using monitoring equipment, and it is ensured that the installation position of each rod meets the design requirements. If deviation is found, real-time adjustment is carried out to ensure that the position of the overall structure meets the design requirements. The embodiment of the application extracts the design position parameters in the design drawings to establish a calculation and analysis model of the overall structure state, carries out construction simulation to obtain the predicted position after completion, calculates the position difference between the design position and the predicted position, adjusts the installation position parameters of the rods according to the difference, and carries out construction simulation iteration until the position difference meets the requirements. In the construction process, the actual position parameters of each rod are monitored in real time, and real-time construction simulation iterative adjustment is carried out to obtain a corrected construction scheme. Based on the corrected construction scheme, installation position control of the long-span steel structure is carried out, and the like technical means are adopted, which achieves the technical effects of accurately predicting the actual position of the structure in the comprehensive construction process, adjusting in real time according to the prediction results, and ensuring the installation accuracy of the structure.

[0053] The above specific embodiments do not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps described in the present application can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or can be advantageous.

Claims

1. A method for intelligent control of installation configuration of a large-span steel structure, characterized in that, The method comprises: extracting design configuration parameters of each bar of a steel structure in design drawings; establishing a calculation and analysis model of the overall structure state of the large-span steel structure according to the design configuration parameters; based on the calculation and analysis model, construction simulation is performed to obtain a predicted configuration after completion; extracting the design configuration from the design drawings, and calculating a configuration difference between the design configuration and the predicted configuration; adjusting the installation configuration parameters of the bars according to the configuration difference, and performing iterative construction simulation until the configuration difference is less than or equal to a configuration deviation threshold to obtain a construction scheme; based on the construction scheme, the installation configuration of the large-span steel structure is controlled; adjusting the installation configuration parameters of the bars according to the configuration difference, and performing iterative construction simulation until the configuration difference is less than or equal to a configuration deviation threshold to obtain a construction scheme, comprising: determining an adjustment step and an adjustment direction according to the configuration difference; adjusting the design configuration parameters according to the adjustment step and the adjustment direction to obtain updated configuration parameters; performing construction simulation according to the updated configuration parameters and obtaining an updated configuration difference; if the updated configuration difference is greater than the configuration deviation threshold, iteratively adjusting the installation configuration parameters until the updated configuration difference is less than or equal to the configuration deviation threshold to obtain a construction scheme; determining an adjustment step and an adjustment direction according to the configuration difference, comprising: collecting historical configuration differences and corresponding optimal adjustment steps and optimal adjustment directions, and constructing a training data set according to the corresponding relationship of the historical data; training a neural network using the training data set to obtain an adjustment strategy model; inputting the configuration difference into the adjustment strategy model to output an adjustment step and an adjustment direction; training a neural network using the training data set to obtain an adjustment strategy model, comprising: extracting historical configuration differences from the training data set and generating a historical configuration difference vector; converting the historical configuration difference vector into a historical configuration difference matrix; inputting the training data set updated according to the historical configuration difference matrix into a pre-trained convolutional neural network for transfer learning training to obtain an adjustment strategy model. The design configuration parameters include the coordinates, angles and structural dimensions of the bars.

2. The method of claim 1, wherein the method comprises: According to the design configuration parameters, a calculation and analysis model of the overall structure state of the large-span steel structure is established, comprising:

3. The method of claim 2, wherein the method further comprises: calculating and obtaining the self-weight of the bars according to the structural dimensions; obtaining the applied additional load in the installation process according to a preset installation process, the additional load including construction equipment load, temporary support load and environmental load; establishing a calculation and analysis model of the overall structure state of the large-span steel structure according to the design configuration parameters, the self-weight and the additional load. Based on the calculation and analysis model, construction simulation is performed to obtain a predicted configuration after completion, comprising:

4. The method of claim 1, wherein the method further comprises: ​ Based on the calculation analysis model, construction process analysis is performed to predict a construction completion configuration; Based on the construction completion configuration, usage state analysis is performed to obtain a predicted configuration of the structure after completion under preset usage load and preset non-resistant load.

5. The method of claim 4, wherein the method further comprises: Based on the calculation analysis model, construction process analysis is performed to predict a construction completion configuration, including: Based on the calculation analysis model, construction sequence configuration influence analysis, construction operation configuration influence analysis, and construction additional load configuration influence analysis are performed to predict construction configuration changes; According to the construction configuration changes, stress distribution configuration influence analysis is performed to predict a construction completion configuration.

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