A method for predicting and controlling construction deformation of multi-tower connected structures based on digital twins

Abstract

The present invention discloses a method for predicting and controlling the construction deformation of a multi-tower connected structure based on digital twins, including: establishing a finite element analysis model for towers and multi-tower connected structures, deducing the stress and deformation state under the full construction cycle and adjusting the construction strategy; constructing a digital twin model based on the architectural parameters measured during the construction cycle of each tower; establishing an ARMA model and using the inverse function prediction method to predict the settlement data value of the tower; adjusting the construction strategy in real time based on the prediction results; analyzing the positions of the preset installation points of the connected structures on each tower, and taking preset control measures to control the construction according to the analysis results, and finally completing the installation of the connected structure. The present invention can realize the modeling analysis of the construction cycle of the multi-tower connected structure construction, and assist engineers in real-time control of the construction method during the construction cycle, so that the connected structure can be accurately erected between multiple towers as expected.

Description

Technical Field

[0001] The present invention belongs to the technical field of building construction, and specifically relates to a construction deformation prediction and control method for a multi-tower connected structure based on digital twins. Background Art

[0002] The multi-tower conjoined structure is a common complex structure in modern high-rise buildings. It consists of multiple towers connected at different heights by one or more conjoined structures, which not only provides a unique architectural aesthetic, but also increases the use function of the building. The design and construction of this structure faces many technical challenges, mainly because of the complex force characteristics of the structure, which requires comprehensive consideration of the mutual influence and collaborative work between the towers and the stiffness and strength of the overall structure.

[0003] During the design and construction process, the safety factors of the structure must be taken into account, including the redundant design of the structure and the safety measures during the construction process. In addition, the multi-tower structure also needs to adapt to the environment in which it is located, including geological conditions, climatic factors, etc., to ensure the long-term stability and durability of the structure.

[0004] Therefore, during the construction process, the multi-tower connected structure needs to precisely control the construction accuracy of the towers and the connected structure to ensure the stability and safety of the structure. This requires engineers to consider many factors throughout the entire design-construction process to accurately adjust the construction strategy, which is undoubtedly a huge challenge for engineers. Summary of the invention

[0005] In view of this, the present invention proposes a method for predicting and controlling the construction deformation of a multi-tower connected structure based on digital twins. The present invention can realize modeling and analysis of the construction period of the multi-tower connected structure, and assist engineers to perform real-time regulation of the construction method within the construction period, so that the connected structure can be accurately erected between multiple towers as expected.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] The present invention provides a method for predicting and controlling the construction deformation of a multi-tower connected structure based on digital twins, comprising:

[0008] Step S1: Establish a finite element analysis model for towers and multi-tower connected structures, and adjust the construction strategy according to the deduction results of the stress and deformation states under the full construction cycle;

[0009] Step S2: constructing a digital twin model based on the building parameters measured during the construction period of each tower;

[0010] Step S3, based on the digital twin model, using Eviews software to establish an ARMA model and use the inverse function prediction method to predict the settlement data value of the tower;

[0011] Step S4: adjusting the construction strategy in real time based on the prediction results;

[0012] Step S5: After the construction of the towers is completed, the positions of the preset installation points of the connected structures on each tower are analyzed, and according to the analysis results, preset control measures are taken to control the construction, and finally the installation of the connected structures is completed.

[0013] Preferably, step S1 comprises:

[0014] Determine the design models and design parameters corresponding to all towers with pre-installed installation points of connected structures;

[0015] Import the design model into the finite element analysis software and determine the structural size and shape of the tower based on the design model;

[0016] Define the physical properties of various materials in the model according to the design parameters, where the physical properties include elastic modulus, Poisson's ratio, mass, and density;

[0017] Divide the geometric model into a finite number of small units, where the small units include one-dimensional rods, two-dimensional shell elements or three-dimensional solid elements;

[0018] Apply actual constraints and loads to the model to simulate various working conditions of the tower in the real world, and use finite element software to calculate the model to obtain the stress, strain and displacement response of the structure under given loads;

[0019] The results of these calculations led to the development and adjustment of construction strategies to achieve target performance for all towers, including material properties, foundation design depth, pile optimization, structural reinforcement, and construction sequence and timing.

[0020] Preferably, step S2 comprises:

[0021] The sensors installed on the towers collect the building parameters, settlement observation data, load changes, and ambient temperature and humidity of each tower during the construction period, and obtain the building material data corresponding to each position on the tower during the construction period;

[0022] According to the current construction progress of the tower, the current overall structure of the constructed part of the tower is obtained by interception based on the finite element analysis model of the tower;

[0023] A digital twin model of the tower is constructed based on the current overall structure and the collected building parameters, settlement observation data, load changes, ambient temperature and humidity, and building material data.

[0024] Preferably, step S3 includes:

[0025] Based on the digital twin model, the ARMA model is established using Eviews software:

[0026]

[0027] in, It indicates the settlement data value of the tower measured when the tower construction is completed to the tth floor above the ground. represents the autoregressive parameter, represents the sliding average parameter, It represents the influencing item in the tower settlement process when the tower construction is completed to t floors above the ground;

[0028]

[0029] in, It indicates the total weight of the tower when the construction of the tower is completed to the tth floor above the ground. Indicates the total weight of additional construction materials and equipment necessary for the construction of the tower, as known from the building materials data, Indicates the preset correction factor, Indicates the rigidity coefficient of the base soil;

[0030] when When it is 0, the ARMA model is determined to be an n-order autoregressive model, and the model variant is:

[0031]

[0032] when When it is 0, the ARMA model is determined to be an m-order moving average model, and the model variant is:

[0033]

[0034] According to the building material data, the total weight of the construction materials on the tower except the building structure is calculated and determined as the second type of load;

[0035] For the settlement data value sequence formed by the model, the ADF test method is used to test its stability based on the observation results during the construction process, and the non-stationary settlement data value sequence is tested after differential processing;

[0036] The minimum information criterion method is used to optimize the model, and the maximum likelihood estimation method is used to estimate the autoregressive parameters and moving average parameters in the optimized model;

[0037] The model's residual sequence is tested to see if it is a white noise sequence to determine the model's adaptability. If it is suitable, the inverse function prediction method is used to predict the model and obtain the total settlement data value when the tower construction is completed.

[0038] Preferably, step S4 comprises:

[0039] The settlement of each tower is estimated based on the prediction results, and the axial compression of the tower is determined based on the deduction results of the stress and deformation state of the finite element analysis model during the entire construction period;

[0040] Based on the finite element analysis model, simulate the stress effect of the vertical deformation of the four sides of the connected structure and determine the allowable difference value of the design ;

[0041] By adjusting the construction sequence of each tower, compensating for elevation, and raising the height of some floors, the vertical elevation difference between the pre-installed installation point of the connected structure and the tower is reduced. ;

[0042] Regularly monitor the tower settlement and compression of each floor according to the actual construction progress, and determine the vertical elevation difference of the floor elevation control points in the connection range between the tower and the connected structure ;

[0043] The finite element analysis model was modified according to the monitoring results to predict the subsequent settlement and axial compression of each tower and obtain the vertical elevation difference value. ;

[0044] When connecting the tower and the conjoined structure, the elevation difference should be minimized by fine-tuning the elevation between the buttresses. .

[0045] Preferably, step S5 comprises:

[0046] After the construction of the towers is completed, the various sensor data installed on each tower and the historical position data of each preset installation point of the connected structure on the horizontal plane are obtained;

[0047] Update the digital twin model based on sensor data and historical position data of pre-set installation points on the horizontal plane;

[0048] Based on the digital twin model, the lateral deformation law of the tower under the combined effects of different wind loads and temperatures, as well as the horizontal displacement difference between each preset installation point and its corresponding design position point are determined;

[0049] For the digital twin model, the finite element analysis method is used to establish the overall connection model between the aerial conjoined structure and the tower, and the influence of the horizontal displacement difference on the force of the conjoined model is analyzed and determined;

[0050] When the increase in the local internal force of the connected structure is less than 5%, it is determined to have no effect;

[0051] When the local internal force increase value of the connected structure is between 5% and 10%, local reinforcement measures shall be taken;

[0052] When the local internal force increase of the connected structure exceeds 10%, precise control measures should be taken.

[0053] Preferably, the precise control measure is to precisely adjust the relative horizontal configuration between the towers, and the specific methods include:

[0054] Measure the changing pattern of the preset installation points and the area they enclose to determine the closing time of the connected structure;

[0055] Lift the connected structure between multiple towers to the connection height represented by the preset installation point position;

[0056] Temporarily connect the raised joint structure to the tower at the time of closing;

[0057] Adjust the temporary horizontal adjustable support system by comparing the measured horizontal displacement with the design value;

[0058] After the adjustment is completed, the connected structure and the tower are formally connected.

[0059] The present invention has achieved at least the following beneficial effects:

[0060] 1. Through the present invention, it is possible to implement modeling and analysis of the construction period of a multi-tower connected structure, and to implement real-time regulation of the construction method within the construction period, so that the connected structure can be accurately erected between multiple towers as expected.

[0061] 2. The vertical elevation difference is obtained by predicting the subsequent settlement and axial compression of each tower. When connecting the tower and the connected structure, the elevation difference can be reduced as much as possible by fine-tuning the elevation between the butt brackets. This can significantly improve the construction accuracy and ensure the stability and service life of the structure.

[0062] Other advantages, objectives and features of the present invention will be described in the following description and will be apparent to those skilled in the art to some extent, or those skilled in the art may be taught from the practice of the present invention. The objectives and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to make the purpose, technical solution and beneficial effects of the present invention clearer, the present invention provides the following drawings for illustration:

[0064] Figure 1 It is a flowchart of the steps of a method for predicting and controlling the construction deformation of a multi-tower connected structure based on digital twins in an embodiment of the present invention;

[0065] Figure 2 It is a structural schematic diagram of a multi-tower connected structure in an embodiment of the present invention. DETAILED DESCRIPTION

[0066] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0067] The invention provides a method for predicting and controlling the construction deformation of a multi-tower connected structure based on digital twins, referring to Figure 1 ,include:

[0068] Step S1: Establish a finite element analysis model for towers and multi-tower connected structures, and adjust the construction strategy according to the deduction results of the stress and deformation states under the full construction cycle;

[0069] Step S2: constructing a digital twin model based on the building parameters measured during the construction period of each tower;

[0070] Step S3, based on the digital twin model, using Eviews software to establish an ARMA model and use the inverse function prediction method to predict the settlement data value of the tower;

[0071] Step S4: adjusting the construction strategy in real time based on the prediction results;

[0072] Step S5: After the construction of the towers is completed, the positions of the preset installation points of the connected structures on each tower are analyzed, and according to the analysis results, preset control measures are taken to control the construction, and finally the installation of the connected structures is completed.

[0073] The working principle and beneficial effects of the above technical solution are as follows: by establishing a finite element analysis model and a digital twin model, the stress and deformation state of the tower and the connected structure during the entire construction cycle can be accurately simulated. This simulation enables the construction team to predict potential structural responses and risks, thereby adjusting the construction strategy in advance, reducing uncertainty and potential safety risks during the construction process, and evaluating and optimizing the long-term performance of the building through continuous monitoring and prediction of the digital twin model. Using EViews software and ARMA model for settlement prediction, the construction team can adjust the construction plan in real time according to the prediction results. For example, if the prediction shows that the settlement of a tower may exceed the safety range, the construction team can prioritize the allocation of resources for foundation reinforcement or take other preventive measures. This can improve the efficiency of resource use and reduce the cost increase caused by construction delays. After the construction of the tower is completed, the precise installation of the connected structure can be ensured by analyzing the location of the preset installation points of the connected structure on the tower and taking preset control measures for construction control. This method can reduce errors and rework during the installation process, improve construction efficiency, and also ensure the stability and service life of the connected structure. The present invention can realize modeling and analysis of the construction period of the multi-tower connected structure, and realize real-time regulation of the construction method within the construction period, so that the connected structure can be accurately erected between the multiple towers as expected.

[0074] In a preferred embodiment, step S1 comprises:

[0075] Determine the design models and design parameters corresponding to all towers with pre-installed installation points of connected structures;

[0076] Import the design model into the finite element analysis software and determine the structural size and shape of the tower based on the design model;

[0077] Define the physical properties of various materials in the model according to the design parameters, where the physical properties include elastic modulus, Poisson's ratio, mass, and density;

[0078] Divide the geometric model into a finite number of small units, where the small units include one-dimensional rods, two-dimensional shell elements or three-dimensional solid elements;

[0079] Apply actual constraints and loads to the model to simulate various working conditions of the tower in the real world, and use finite element software to calculate the model to obtain the stress, strain and displacement response of the structure under given loads;

[0080] The results of these calculations led to the development and adjustment of construction strategies to achieve target performance for all towers, including material properties, foundation design depth, pile optimization, structural reinforcement, and construction sequence and timing.

[0081] The working principle and beneficial effects of the above technical solution are as follows: by importing the design model into the finite element analysis software and defining the physical properties of the material, the structural size and shape of the tower can be accurately simulated. This simulation enables the effectiveness of the design to be verified before construction, and the stress and deformation of the structure in the real world to be predicted, thereby ensuring the accuracy and safety of the design. The stress, strain and displacement response data obtained by the finite element analysis can be used to guide the formulation and adjustment of the tower construction strategy. For example, if the analysis results show that stress concentration is in certain areas, the construction material properties can be adjusted or structural reinforcement measures can be added to improve the bearing capacity of these areas. This data-based decision-making process helps to optimize the use of tower construction resources and improve construction efficiency. By applying actual constraints and loads to the model, various working conditions of the tower in the real world can be simulated, including extreme weather, earthquakes, etc. This helps to predict and evaluate the offset state of the tower during long-term use and ensure the stress state of the connected structure.

[0082] In a preferred embodiment, step S2 comprises:

[0083] The sensors installed on the towers collect the building parameters, settlement observation data, load changes, and ambient temperature and humidity of each tower during the construction period, and obtain the building material data corresponding to each position on the tower during the construction period;

[0084] According to the current construction progress of the tower, the current overall structure of the constructed part of the tower is obtained by interception based on the finite element analysis model of the tower;

[0085] A digital twin model of the tower is constructed based on the current overall structure and the collected building parameters, settlement observation data, load changes, ambient temperature and humidity, and building material data.

[0086] The working principle and beneficial effects of the above technical solution are as follows: by setting sensors on the tower to collect building parameters and environmental data, more accurate real-time data can be obtained, including settlement observation data, load changes, and ambient temperature and humidity. By using the finite element analysis model to intercept the current overall structure of the constructed part of the tower, the construction progress can be simulated and predicted more accurately. This method helps to discover potential structural problems and make timely adjustments, thereby optimizing construction quality and progress. Constructing a digital twin model, combined with actual building parameters and environmental data, can more realistically simulate the behavior of the tower and predict its performance in future use. It helps to take preventive measures to reduce possible future maintenance costs and enhance the safety and life of the structure.

[0087] In a preferred embodiment, step S3 comprises:

[0088] Based on the digital twin model, the ARMA model is established using Eviews software:

[0089]

[0090] in, It indicates the settlement data value of the tower measured when the tower construction is completed to the tth floor above the ground. represents the autoregressive parameter, represents the sliding average parameter, It represents the influencing item in the tower settlement process when the tower construction is completed to t floors above the ground;

[0091]

[0092] in, It indicates the total weight of the tower when the construction of the tower is completed to the tth floor above the ground. Indicates the total weight of additional construction materials and equipment necessary for the construction of the tower, as known from the building materials data, Indicates the preset correction factor, Indicates the rigidity coefficient of the base soil;

[0093] when When it is 0, the ARMA model is determined to be an n-order autoregressive model, and the model variant is:

[0094]

[0095] when When it is 0, the ARMA model is determined to be an m-order moving average model, and the model variant is:

[0096]

[0097] According to the building material data, the total weight of the construction materials on the tower except the building structure is calculated and determined as the second type of load;

[0098] For the settlement data value sequence formed by the model, the ADF test method is used to test its stability based on the observation results during the construction process, and the non-stationary settlement data value sequence is tested after differential processing;

[0099] The minimum information criterion method is used to optimize the model, and the maximum likelihood estimation method is used to estimate the autoregressive parameters and moving average parameters in the optimized model;

[0100] The model's residual sequence is tested to see if it is a white noise sequence to determine the model's adaptability. If it is suitable, the inverse function prediction method is used to predict the model and obtain the total settlement data value when the tower construction is completed.

[0101] The working principle and beneficial effects of the above technical solution are as follows: by establishing an ARMA model to predict the tower settlement data, future settlement can be estimated more accurately. The model takes into account the autoregressive parameters and sliding average parameters of the tower, as well as the influencing items in the construction process, such as the total weight of the tower and the rigidity coefficient of the base soil, thereby improving the accuracy and reliability of the prediction. Using the settlement prediction value obtained by the inverse function prediction method, the construction team can adjust the construction strategy in real time, such as changing the construction materials, optimizing the foundation design depth, or adjusting the pile foundation design. This real-time adjustment helps to ensure the stability and safety of the tower while reducing potential costs and delays caused by settlement problems. The stability and applicability of the model can be ensured by testing the stationarity of the settlement data value sequence through the ADF test method and optimizing the model using the minimum information criterion method. This helps to better manage risks and potential errors in the construction process, predict and prevent possible engineering problems, and thus improve the management level of the entire construction project.

[0102] In a preferred embodiment, referring to Figure 2 , step S4 comprises:

[0103] The settlement of each tower is estimated based on the prediction results, and the axial compression of the tower is determined based on the deduction results of the stress and deformation state of the finite element analysis model during the entire construction period;

[0104] Based on the finite element analysis model, simulate the stress effect of the vertical deformation of the four sides of the connected structure and determine the allowable difference value of the design ;

[0105] By adjusting the construction sequence of each tower, compensating for elevation, and raising the height of some floors, the vertical elevation difference between the pre-installed installation point of the connected structure and the tower is reduced. ;

[0106] Regularly monitor the tower settlement and compression of each floor according to the actual construction progress, and determine the vertical elevation difference of the floor elevation control points in the connection range between the tower and the connected structure ;

[0107] The finite element analysis model was modified according to the monitoring results to predict the subsequent settlement and axial compression of each tower and obtain the vertical elevation difference value. ;

[0108] When connecting the tower and the conjoined structure, the elevation difference should be minimized by fine-tuning the elevation between the buttresses. .

[0109] The working principle and beneficial effects of the above technical solution are as follows: the axial compression and design allowable difference of the tower can be determined by accurate estimation based on the prediction results and deduction of the finite element analysis model. This helps to take into account possible settlement and deformation in the future at the design stage, so as to take measures in advance to ensure the stability and safety of the structure. By adjusting the construction sequence, elevation compensation and local floor height, the vertical elevation difference between the preset installation point and the tower can be effectively reduced. This adjustment helps to reduce the difficulty of construction, improve construction efficiency, and ensure the smooth connection between the connected structure and the tower. Regularly monitoring the settlement of the tower and the compression of the floor can determine the vertical elevation difference in real time, and the finite element analysis model can be corrected according to the monitoring results. This dynamic monitoring and adjustment mechanism helps to ensure the accuracy and quality of the construction process, and timely discover and solve possible problems. By predicting the subsequent settlement and axial compression of each tower to obtain the vertical elevation difference, and by fine-tuning the elevation between the butt brackets when connecting the tower and the connected structure, the difference elevation can be reduced as much as possible, which can significantly improve the construction accuracy and ensure the stability and service life of the structure.

[0110] In a preferred embodiment, step S5 comprises:

[0111] After the construction of the towers is completed, the various sensor data installed on each tower and the historical position data of each preset installation point of the connected structure on the horizontal plane are obtained;

[0112] Update the digital twin model based on sensor data and historical position data of pre-set installation points on the horizontal plane;

[0113] Based on the digital twin model, the lateral deformation law of the tower under different wind loads and temperatures, as well as the horizontal displacement difference between each preset installation point and its corresponding design position point are determined;

[0114] For the digital twin model, the finite element analysis method is used to establish the overall connection model between the aerial conjoined structure and the tower, and the influence of the horizontal displacement difference on the force of the conjoined model is analyzed and determined;

[0115] When the increase in the local internal force of the connected structure is less than 5%, it is determined to have no effect;

[0116] When the local internal force increase value of the connected structure is between 5% and 10%, local reinforcement measures shall be taken;

[0117] When the local internal force increase of the connected structure exceeds 10%, precise control measures should be taken.

[0118] The working principle and beneficial effects of the above technical solution are as follows: by obtaining a variety of sensor data and historical position data of the preset installation points after the completion of the tower construction, the digital twin model can be updated in real time. This update enables the model to reflect the latest state of the actual structure, so that under the combined action of different wind loads and temperatures, the lateral deformation law of the tower and the horizontal displacement difference of the preset installation points can be accurately predicted, thereby enhancing the adaptability and safety of the structure. By using the digital twin model to analyze the overall connection model between the connected structure and the tower, the influence of the horizontal displacement difference on the force of the connected structure can be evaluated. This analysis helps to make more reasonable decisions during the design and construction stages, such as whether reinforcement or control measures are needed, thereby optimizing the design and construction of the connected structure. Different response measures are taken according to the different ranges of the local internal force increase of the connected structure. This hierarchical response strategy makes the construction quality control more accurate and ensures the reliability of the structure under various working conditions. For example, when the local internal force increase is less than 5%, it can be considered that the impact is not significant; when the increase is between 5% and 10%, local reinforcement measures can be taken; when the increase exceeds 10%, more precise control measures are required. Through precise analysis and prediction, unnecessary over-design and reinforcement can be avoided, thus saving materials and costs and improving construction efficiency.

[0119] In a preferred embodiment, the precise control measure is to precisely adjust the relative horizontal configuration between the towers, and the specific method includes:

[0120] Measure the changing pattern of the preset installation points and the area they enclose to determine the closing time of the connected structure;

[0121] Lift the connected structure between multiple towers to the connection height represented by the preset installation point position;

[0122] Temporarily connect the raised joint structure to the tower at the time of closing;

[0123] Adjust the temporary horizontal adjustable support system by comparing the measured horizontal displacement with the design value;

[0124] After the adjustment is completed, the connected structure and the tower are formally connected.

[0125] The working principle and beneficial effects of the above technical solution are as follows: by measuring the changing rules of the preset installation points and the areas enclosed by them, the closing time of the connected structure can be accurately determined. This precise timing selection helps to ensure that the relative horizontal position between the towers is adjusted more accurately, thereby improving the accuracy and overall stability of the structural docking. Temporarily connecting the lifted connected structure to the tower at the time of closing and adjusting the temporary horizontal adjustable support system can ensure that the structure is fine-tuned and verified before the formal connection. This step helps to ensure safety and reliability during the construction process and prevent accidents caused by structural deviations. Through precise control measures, the construction process can be optimized while ensuring structural safety. By lifting the connected structure as a whole and making temporary connections, the time and risk of high-altitude operations can be reduced, while improving construction efficiency.

[0126] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the scope defined by the claims of the present invention.

Claims

1. A method for predicting and controlling the construction deformation of a multi-tower connected structure based on digital twins, characterized in that: include: Step S1: Establish a finite element analysis model for towers and multi-tower connected structures, and adjust the construction strategy according to the deduction results of the stress and deformation states under the full construction cycle; Step S2: constructing a digital twin model based on the building parameters measured during the construction period of each tower; Step S3, based on the digital twin model, using Eviews software to establish an ARMA model and use the inverse function prediction method to predict the settlement data value of the tower; Step S4: adjusting the construction strategy in real time based on the prediction results; Step S5: After the construction of the towers is completed, the positions of the preset installation points of the connected structures on each tower are analyzed, and according to the analysis results, preset control measures are taken to control the construction, and finally the installation of the connected structures is completed; The step S3 comprises: Based on the digital twin model, the ARMA model is established using Eviews software: in, It indicates the settlement data value of the tower measured when the tower construction is completed to the tth floor above the ground. represents the autoregressive parameter, represents the sliding average parameter, It represents the influencing item in the tower settlement process when the tower construction is completed to t floors above the ground; in, It indicates the total weight of the tower when the construction of the tower is completed to the tth floor above the ground. Indicates the total weight of additional construction materials and equipment necessary for the construction of the tower, as known from the building materials data, Indicates the preset correction factor, Indicates the rigidity coefficient of the base soil; when When it is 0, the ARMA model is determined to be an n-order autoregressive model, and the model variant is: when When it is 0, the ARMA model is determined to be an m-order moving average model, and the model variant is: According to the building material data, the total weight of the construction materials on the tower except the building structure is calculated and determined as the second type of load; For the settlement data value sequence formed by the model, the ADF test method is used to test its stability based on the observation results during the construction process, and the non-stationary settlement data value sequence is tested after differential processing; The minimum information criterion method is used to optimize the model, and the maximum likelihood estimation method is used to estimate the autoregressive parameters and moving average parameters in the optimized model; The model's residual sequence is tested to see if it is a white noise sequence to determine the model's adaptability. If it is suitable, the inverse function prediction method is used to predict the model and obtain the total settlement data value when the tower construction is completed.

2. According to the method for predicting and controlling the construction deformation of a multi-tower connected structure based on digital twinning according to claim 1, it is characterized in that: The step S1 comprises: Determine the design models and design parameters corresponding to all towers with pre-installed installation points of connected structures; Import the design model into the finite element analysis software and determine the structural size and shape of the tower based on the design model; Define the physical properties of various materials in the model according to the design parameters, where the physical properties include elastic modulus, Poisson's ratio, mass, and density; Divide the geometric model into a finite number of small units, where the small units include one-dimensional rods, two-dimensional shell elements or three-dimensional solid elements; Apply actual constraints and loads to the model to simulate various working conditions of the tower in the real world, and use finite element software to calculate the model to obtain the stress, strain and displacement response of the structure under given loads; The results of these calculations led to the development and adjustment of construction strategies to achieve target performance for all towers, including material properties, foundation design depth, pile optimization, structural reinforcement, and construction sequence and timing.

3. According to the method of construction deformation prediction and control of multi-tower connected structure based on digital twinning in claim 1, it is characterized in that: The step S2 comprises: The sensors installed on the towers collect the building parameters, settlement observation data, load changes, and ambient temperature and humidity of each tower during the construction period, and obtain the building material data corresponding to each position on the tower during the construction period; According to the current construction progress of the tower, the current overall structure of the constructed part of the tower is obtained by interception based on the finite element analysis model of the tower; A digital twin model of the tower is constructed based on the current overall structure and the collected building parameters, settlement observation data, load changes, ambient temperature and humidity, and building material data.

4. The method for predicting and controlling the construction deformation of a multi-tower connected structure based on digital twin according to claim 1 is characterized in that: The step S4 comprises: The settlement of each tower is estimated based on the prediction results, and the axial compression of the tower is determined based on the deduction results of the stress and deformation state of the finite element analysis model during the entire construction period; Based on the finite element analysis model, simulate the stress effect of the vertical deformation of the four sides of the connected structure and determine the allowable difference value of the design ; By adjusting the construction sequence of each tower, compensating for elevation, and raising the height of some floors, the vertical elevation difference between the pre-installed installation point of the connected structure and the tower is reduced. ; Regularly monitor the tower settlement and compression of each floor according to the actual construction progress, and determine the vertical elevation difference of the floor elevation control points in the connection range between the tower and the connected structure ; The finite element analysis model was modified according to the monitoring results to predict the subsequent settlement and axial compression of each tower and obtain the vertical elevation difference value. ; When connecting the tower and the conjoined structure, the elevation difference should be minimized by fine-tuning the elevation between the buttresses. .

5. The method for predicting and controlling the construction deformation of a multi-tower connected structure based on digital twin according to claim 1 is characterized in that: The step S5 comprises: After the construction of the towers is completed, the various sensor data installed on each tower and the historical position data of each preset installation point of the connected structure on the horizontal plane are obtained; Update the digital twin model based on sensor data and historical position data of pre-set installation points on the horizontal plane; Based on the digital twin model, the lateral deformation law of the tower under different wind loads and temperatures, as well as the horizontal displacement difference between each preset installation point and its corresponding design position point are determined; For the digital twin model, the finite element analysis method is used to establish the overall connection model between the aerial conjoined structure and the tower, and the influence of the horizontal displacement difference on the force of the conjoined model is analyzed and determined; When the increase in the local internal force of the connected structure is less than 5%, it is determined to have no effect; When the local internal force increase value of the connected structure is between 5% and 10%, local reinforcement measures shall be taken; When the local internal force increase of the connected structure exceeds 10%, precise control measures should be taken.

6. The method for predicting and controlling the construction deformation of a multi-tower connected structure based on digital twin according to claim 5 is characterized in that: Precise control measures include precise adjustment of the relative horizontal position between towers, including: Measure the changing pattern of the preset installation points and the area they enclose to determine the closing time of the connected structure; Lift the connected structure between multiple towers to the connection height represented by the preset installation point position; Temporarily connect the raised joint structure to the tower at the time of closing; Adjust the temporary horizontal adjustable support system by comparing the measured horizontal displacement with the design value; After the adjustment is completed, the connected structure and the tower are formally connected.

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