An intelligent construction management and control platform system for super high-rise buildings and a construction method

Abstract

The application relates to an ultra-high-rise building intelligent construction management and control platform system and a construction method, which comprises an intelligent sensing layer, a plurality of sensor terminals are configured in the intelligent sensing layer, and the intelligent sensing layer is used for collecting structural state data, environmental data, equipment operation data and construction process data in real time; a data fusion and hub layer is used for receiving and processing data from the plurality of sensors, generating a unified data stream with a time stamp and a spatial coordinate, and automatically identifying a key construction event node through data analysis; a digital twin and model layer is used for constructing a digital twin body which is synchronously updated with a physical structure, and performing short-term construction simulation prediction based on a current twin body state; an intelligent analysis and decision layer is used for generating a construction adjustment strategy according to a simulation prediction result, and establishing an associated early warning model in combination with multidimensional data; a collaborative execution and interaction layer is used for pushing a decision instruction to an execution equipment on a construction site, and collecting execution feedback data to optimize subsequent prediction and decision.

Description

Technical Field

[0001] This invention belongs to the field of building construction technology, and specifically relates to an intelligent construction management and control platform system and construction method for super high-rise buildings. Background Technology

[0002] The construction of super high-rise buildings, especially those employing a core-frame hybrid structural system, is a complex dynamic systems engineering project. The core construction challenge lies in the time-varying nature of the structural system and the incoordination of deformation. Due to significant differences in material properties, stiffness formation time, and construction progress between the core (usually a steel or steel-concrete composite structure) and the outer frame (mostly reinforced concrete), continuous and constantly changing vertical deformation differences will occur between them during construction. If these deformation differences are not controlled, they will lead to difficulties in installing subsequent connecting components (such as floor beams and outrigger trusses) and generate additional secondary stresses that are difficult to eliminate, seriously affecting structural safety and forming accuracy.

[0003] Currently, the management and control measures for this challenge still have significant shortcomings. First, monitoring data is fragmented and analysis is lagging. Strain gauges, inclinometers, total stations, and other sensors deployed on-site operate independently, generating massive amounts of data scattered across different systems, lacking unified aggregation and real-time correlation analysis. Managers cannot intuitively and instantly grasp the overall deformation and stress fields of the entire building. Second, construction decisions rely on experience and static simulations. Traditional construction simulations are mostly conducted before construction, based on theoretical assumptions, and cannot be corrected or predicted in real time based on dynamic changes such as concrete shrinkage and creep, and actual loads at the construction site. Decisions regarding key processes (such as the welding closure time of the outrigger truss and the pre-adjusted elevation of the outer frame) are largely based on experience, lacking data support. Third, coordination among various construction subsystems is difficult. Processes such as steel platform climbing, tower crane operation, concrete pouring, and surveying and setting out influence each other, making it difficult for traditional management models to achieve dynamic scheduling and risk pre-control based on real-time structural conditions.

[0004] Therefore, how to provide an intelligent construction management and control platform system and construction method for super high-rise buildings is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] This invention provides an intelligent construction management and control platform system and construction method for super high-rise buildings. It constructs an intelligent construction management and control platform that integrates perception, twin, decision-making and control. It can integrate multi-source data, map the construction status in real time, and intelligently drive construction decisions and adjustments into a global management and control system. It not only realizes the visualization of the construction status, but also makes the construction process predictable, optimizable and controllable.

[0006] To solve the above technical problems, the present invention includes the following technical solutions:

[0007] A smart construction management and control platform system for super high-rise buildings includes:

[0008] The intelligent sensing layer is equipped with a variety of sensor terminals for real-time collection of structural status data, environmental data, equipment operation data, and construction process data;

[0009] The data fusion and central layer is communicatively connected to the intelligent sensing layer. It is used to receive and process data from multiple sensors, generate a unified data stream with timestamps and spatial coordinates, and automatically identify key construction event nodes through data analysis.

[0010] The digital twin and model layer, which is connected to the data fusion and central layer, is used to construct a digital twin that is updated synchronously with the physical structure, and to perform short-term construction simulation prediction based on the current state of the twin.

[0011] The intelligent analysis and decision-making layer communicates with the digital twin and model layer to generate construction adjustment strategies based on simulation prediction results and establish a correlation early warning model by combining multi-dimensional data.

[0012] The collaborative execution and interaction layer communicates with the intelligent analysis and decision-making layer to push decision instructions to the execution equipment at the construction site and collect execution feedback data to optimize subsequent predictions and decisions.

[0013] Furthermore, the intelligent sensing layer includes:

[0014] Static levels and GPS / BeiDou monitoring stations are installed at key locations in the core tube and outer frame columns to measure vertical deformation and absolute settlement.

[0015] Inclinometers and three-dimensional laser scanning targets, located on the outside of the structure, are used to monitor the overall tilt and sway.

[0016] Vibrating wire strain gauges or fiber optic grating sensors installed on critical load-bearing components are used to monitor stress changes during construction.

[0017] Load sensors and inclinometers integrated into the hydraulic climbing steel platform are used to monitor load and attitude;

[0018] The operation monitoring instrument installed on tower cranes and concrete pumping equipment is used to collect equipment operating status, lifting weight and position data;

[0019] Wireless temperature, humidity, and strength sensors deployed at concrete pouring sites are used to monitor the development of concrete performance.

[0020] Anemometers and thermometers are installed on the floor to record environmental loads.

[0021] Furthermore, the data fusion and central layer also includes an automatic construction event identification engine, which automatically marks key construction nodes by detecting abrupt changes in strain and deformation data.

[0022] Furthermore, the digital twin and model layer is equipped with a lightweight online simulation engine, which uses the current state of the twin as the initial condition to quickly simulate and predict the construction process within the next 24 to 72 hours.

[0023] Furthermore, the intelligent analysis and decision-making layer includes:

[0024] The deformation difference active coordination module is used to calculate the optimal pre-adjusted elevation before the template is erected and send it to the layout robot;

[0025] The intelligent scheduling module for multi-tower crane clusters is used to optimize the operation path and sequence of tower cranes based on structural stress monitoring data;

[0026] The outrigger truss closure intelligent recommendation module is used to dynamically recommend the closure timing based on the deformation difference rate and additional stress.

[0027] The present invention also provides a construction method using the aforementioned intelligent construction management and control platform system for super high-rise buildings, comprising the following steps:

[0028] Step S1: Construct a digital twin platform with a five-layer logical architecture covering the entire construction process;

[0029] Step S2: Based on real-time monitoring data, drive the synchronous evolution of the digital twin model and automatically identify construction events;

[0030] Step S3: Using an online simulation and prediction engine, with the current twin state as the initial condition and combined with the short-term construction plan, simulate and predict the structural response of the future construction cycle;

[0031] Step S4: If the prediction result exceeds the safety threshold, the intelligent decision layer generates specific parameter control instructions including the elevation pre-adjustment value and the equipment scheduling plan;

[0032] Step S5: Push the control command to the on-site execution terminal for construction adjustments, and feed back the adjusted measured data to the system to update the twin model and prediction algorithm.

[0033] Furthermore, the automatic identification of construction events in step S2 includes: automatically marking the completion of core tube climbing formwork and key construction nodes of concrete pouring by analyzing abrupt changes in strain and deformation data, and using them as initial boundary conditions for simulation calculations.

[0034] Furthermore, the short-term construction plan in step S3 includes at least the number of core tube construction layers, the number of outer frame construction layers, and material stacking loads for the next 24 to 72 hours.

[0035] Furthermore, the control commands in step S4 include: a command to pre-adjust the elevation of the outer frame template for cases where the deformation difference between the core tube and the outer frame exceeds the limit, or a prompt for the recommended closing timing for the installation of the outrigger truss.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0037] The intelligent construction management and control platform system and construction method for super high-rise buildings provided by this invention constructs an integrated intelligent construction management and control platform encompassing perception, twin data, decision-making, and control. This platform integrates multi-source data, maps construction status in real time, and intelligently drives construction decisions and adjustments—a comprehensive management and control system. It not only visualizes the construction status but also enables the construction process to be predictable, optimizable, and controllable. It has the following advantages:

[0038] (1) Realize real-time holographic perception and fusion of structural response and construction status: Unify access and integrate multi-dimensional monitoring data such as deformation, stress, and settlement of the core tube and outer frame, as well as real-time working conditions such as construction machinery and environmental loads, to build a comprehensive and dynamic digital image of the construction site.

[0039] (2) Establish a deformation collaborative intelligent decision-making mechanism based on digital twins: Create a deformation collaborative intelligent decision-making mechanism based on digital twins. Through real-time data-driven and short-term prediction, provide quantitative basis for key decisions such as optimizing the number of layers in the core tube for advanced construction, the optimal closing sequence of the outrigger truss, and the dynamic pre-adjustment of the elevation of the outer frame.

[0040] (3) Construct a data-driven adaptive control closed loop for construction process: Transform intelligent decision-making results into executable construction instructions, dynamically guide surveying and setting out, operation of steel platforms and large equipment, concrete pouring rhythm, etc., realize the active adaptation and coordination of construction process to structural deformation state, and ensure construction safety and accuracy. Attached Figure Description

[0041] Figure 1 This is a flowchart illustrating an intelligent construction management and control platform system and construction method for super high-rise buildings according to an embodiment of the present invention. Detailed Implementation

[0042] The following detailed description, in conjunction with specific embodiments, provides a further detailed explanation of the intelligent construction management and control platform system and construction method for super high-rise buildings provided by the present invention. The advantages and features of the present invention will become clearer from the following description.

[0043] The following details the structural composition of the intelligent construction management and control platform system for super high-rise buildings of the present invention.

[0044] Example 1

[0045] The following describes the structure of the intelligent construction management and control platform system for super high-rise buildings provided by this invention, with reference to specific embodiments. A hardware and software system integrating IoT, BIM, finite element analysis, and big data analytics technologies is provided. A digital twin is constructed, and an intelligent management and control closed loop is formed around it. This construction management and control platform system adopts a five-layer logical architecture to ensure seamless connection throughout the entire chain from data acquisition to intelligent control.

[0046] A smart construction management and control platform system for super high-rise buildings includes:

[0047] The intelligent sensing layer is equipped with various sensor terminals for real-time acquisition of structural status data, environmental data, equipment operation data, and construction process data. This layer consists of a sensor network deployed across the structure and environment, along with intelligent device terminals. Static levels and GPS / BeiDou monitoring stations are deployed on key floors of the core tube and outer frame columns to measure vertical deformation and absolute settlement in real time. Inclinometers and 3D laser scanning targets are deployed on the outer side of the structure to monitor overall tilt and sway. Vibrating wire strain gauges or fiber optic sensors are installed on key load-bearing components such as the core tube shear walls, outer frame columns, and outrigger truss chords and web members to monitor stress changes during construction in real time. Load sensors and inclinometers are integrated into the hydraulic climbing steel platform to monitor its load-bearing capacity and attitude in real time. Equipment operation monitoring instruments are installed on tower cranes and concrete pumping equipment to collect data on operating status, load, and location in real time. Wireless temperature, humidity, and strength sensors are deployed at concrete pouring points to monitor concrete performance development. Anemometers and thermometers are deployed on floors to record environmental loads.

[0048] The data fusion and central layer, communicating with the intelligent sensing layer, receives and processes data from multiple sensors, generating a unified data stream with timestamps and spatial coordinates. It automatically identifies key construction event nodes through data analysis. Specifically, it establishes a unified benchmark, assigning precise time and three-dimensional spatial coordinates to all sensing data. Through an edge computing gateway and a unified data interface, it cleans, aligns, and standardizes multi-source, heterogeneous real-time streaming data. A built-in automatic construction event identification engine automatically marks key construction nodes, such as the completion of core tube formwork climbing or the completion of concrete pouring for a specific floor, by analyzing abrupt changes in strain and deformation data.

[0049] The digital twin and model layer, connected to the data fusion and central layer, is used to construct a digital twin that is synchronously updated with the physical structure and to perform short-term construction simulation predictions based on the current twin state. Using a high-precision BIM model from the design phase as the framework, data from the perception layer is fused in real time. Measured deformation values ​​are assigned to corresponding BIM components, causing the model to deform; stress monitoring values ​​are mapped to color cloud maps on the model components, enabling visualization of the structural internal force field. An online simulation and prediction engine is established, integrating a lightweight finite element analysis kernel. This engine uses the current twin state as initial conditions, inputs the future short-term construction plan and loads (e.g., the next three floors of the core tube construction), and quickly simulates and predicts the deformation development and deformation difference of the core tube and outer frame over the next 24-72 hours, and assesses the additional stress on connecting components such as outrigger trusses.

[0050] The intelligent analysis and decision-making layer, communicating with the digital twin and model layer, is used to generate construction adjustment strategies based on simulation prediction results and establish a correlation early warning model based on multi-dimensional data. Specifically, based on the prediction engine's results, if it is determined that the future deformation difference will exceed the allowable threshold (e.g., 5mm), the algorithm will automatically generate adjustment suggestions, such as suggesting adjusting the number of advanced construction layers of the core tube from 6 to 5, or suggesting a +3mm pre-lift of the Nth layer elevation of the outer frame. A multi-index correlation early warning model is established by combining real-time stress, equipment load, and environmental data. For example, when a rapid and continuous increase in stress is detected in a member of the outrigger truss, coupled with increased wind speed, the system will conduct a comprehensive risk assessment and issue a graded early warning.

[0051] The collaborative execution and interaction layer, communicating with the intelligent analysis and decision-making layer, is used to push decision-making instructions to the execution equipment on the construction site and collect execution feedback data to optimize subsequent predictions and decisions. Specifically, it provides managers with a holographic view of the building, enabling them to view real-time data, prediction curves, and early warning information at any location. Decision-making instructions (such as adjusted elevation preset values ​​and optimized tower crane scheduling schemes) are accurately pushed to the mobile terminals of surveying teams and equipment operators. Execution results can be fed back into the system, forming a closed loop.

[0052] This embodiment also provides a construction method using the aforementioned intelligent construction management and control platform system for super high-rise buildings, specifically including the following steps:

[0053] Step S1: Construct a digital twin platform with a five-layer logical architecture covering the entire construction process;

[0054] Step S2: Based on real-time monitoring data, drive the synchronous evolution of the digital twin model and automatically identify construction events;

[0055] Step S3: Using an online simulation and prediction engine, with the current twin state as the initial condition and combined with the short-term construction plan, simulate and predict the structural response of the future construction cycle;

[0056] Step S4: If the prediction result exceeds the safety threshold, the intelligent decision layer generates specific parameter control instructions including the elevation pre-adjustment value and the equipment scheduling plan;

[0057] Step S5: Push the control command to the on-site execution terminal for construction adjustments, and feed back the adjusted measured data to the system to update the twin model and prediction algorithm.

[0058] In this embodiment, more preferably, the automatic identification of construction events in step S2 includes: automatically marking the completion of core tube climbing formwork and key construction nodes of concrete pouring by analyzing abrupt changes in strain and deformation data, and using them as initial boundary conditions for simulation calculation.

[0059] In this embodiment, more preferably, the short-term construction plan in step S3 includes at least the number of core tube construction layers, the number of outer frame construction layers, and the material stacking load for the next 24 to 72 hours.

[0060] In this embodiment, more preferably, the control commands in step S4 include: a command to pre-adjust the elevation of the outer frame template for cases where the deformation difference between the core tube and the outer frame exceeds the limit, or a prompt for the recommended closing timing for the installation of the outrigger truss.

[0061] In particular, this construction management and control platform system is deeply integrated into the construction cycle of standard floors in super high-rise buildings. The following example, using the typical working condition of "core tube leading - outer frame following", illustrates its intelligent management and control process:

[0062] Phase 1: Core tube construction and steel platform lifting

[0063] The system intelligently inputs load and tilt data for the steel platform, as well as strain and temperature data for the newly poured core tube section. The platform monitors the stability of the steel platform in real time, immediately issuing alarms in case of overload or uneven loading. Simultaneously, based on the measured strain and temperature of the newly poured concrete, the online simulation engine dynamically corrects the parameters of the concrete shrinkage and creep model, making subsequent predictions more accurate. Based on the corrected model, the platform predicts the elastic deformation and shrinkage deformation of the core tube over the next three days, providing advanced data preparation for the upcoming outer frame construction.

[0064] Phase Two: Coordination and Control of External Frame Construction and Deformation Difference

[0065] Input real-time settlement and vertical deformation data of the outer frame columns; ambient temperature and humidity. The platform calculates and visualizes the deformation difference curves between the core tube and the outer frame on each floor in real time. A high-level alarm is triggered when the value approaches a threshold. Before the formwork of each outer frame is erected, the platform uses an online simulation engine, combined with the latest core tube data, to predict the final deformation difference after the concrete pouring of that floor's outer frame reaches its strength. If the predicted deformation difference exceeds the standard, the deformation collaborative decision-making algorithm automatically calculates the optimal pre-adjustment elevation value for the outer frame formwork on that floor. This command, along with the 3D positioning coordinates, is sent directly to the surveyor's intelligent total station or layout robot. After construction, the pre-adjustment effect is verified through measured data, and the data is fed back to the system to optimize the pre-adjustment algorithm for subsequent floors.

[0066] Phase Three: Construction of Key Nodes such as the Outrigger Truss Layer

[0067] The platform inputs stress and strain data for the outrigger truss members throughout the entire process of hoisting, temporary fixing, and final welding closure. It monitors stress changes in the truss members in real time using dynamic curves and contour maps, comparing these changes with the simulated safety stress envelope. The platform continuously analyzes the rate of change of deformation difference between the core tube and the outer frame. When the system determines that the deformation is relatively stable and the additional stress in the members is low, it automatically indicates the recommended time for the final welding closure of the outrigger truss, changing the previous reliance on fixed construction steps or experience-based judgment.

[0068] Phase Four: Large-scale equipment coordination and resource scheduling

[0069] Input the real-time position, lifting weight, and slewing angle of multiple tower cranes; material requirements planning. The platform integrates an AI tower crane group control algorithm, which dynamically plans the optimal lifting path and scheduling sequence based on real-time lifting requirements, tower crane operating conditions, and structural stress monitoring data (to avoid local overload caused by heavy lifting), reducing waiting time and improving efficiency.

[0070] The above examples are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. The above embodiments only illustrate several implementations of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this patent should be determined by the appended claims.

Claims

1. A smart construction management and control platform system for super high-rise buildings, characterized in that, include: The intelligent sensing layer is equipped with a variety of sensor terminals for real-time collection of structural status data, environmental data, equipment operation data, and construction process data; The data fusion and central layer is communicatively connected to the intelligent sensing layer. It is used to receive and process data from multiple sensors, generate a unified data stream with timestamps and spatial coordinates, and automatically identify key construction event nodes through data analysis. The digital twin and model layer, which is connected to the data fusion and central layer, is used to construct a digital twin that is updated synchronously with the physical structure, and to perform short-term construction simulation prediction based on the current state of the twin. The intelligent analysis and decision-making layer communicates with the digital twin and model layer to generate construction adjustment strategies based on simulation prediction results and establish a correlation early warning model by combining multi-dimensional data. The collaborative execution and interaction layer communicates with the intelligent analysis and decision-making layer to push decision instructions to the execution equipment at the construction site and collect execution feedback data to optimize subsequent predictions and decisions.

2. The intelligent construction management and control platform system for super high-rise buildings according to claim 1, characterized in that, The intelligent sensing layer includes: Static levels and GPS / BeiDou monitoring stations are installed at key locations in the core tube and outer frame columns to measure vertical deformation and absolute settlement. Inclinometers and three-dimensional laser scanning targets, located on the outside of the structure, are used to monitor the overall tilt and sway. Vibrating wire strain gauges or fiber optic grating sensors installed on critical load-bearing components are used to monitor stress changes during construction. Load sensors and inclinometers integrated into the hydraulic climbing steel platform are used to monitor load and attitude; The operation monitoring instrument installed on tower cranes and concrete pumping equipment is used to collect equipment operating status, lifting weight and position data; Wireless temperature, humidity, and strength sensors deployed at concrete pouring sites are used to monitor the development of concrete performance. Anemometers and thermometers are installed on the floor to record environmental loads.

3. The intelligent construction management and control platform system for super high-rise buildings according to claim 2, characterized in that, The data fusion and central layer also includes an automatic construction event identification engine, which automatically marks key construction nodes by detecting abrupt changes in strain and deformation data.

4. The intelligent construction management and control platform system for super high-rise buildings according to claim 3, characterized in that, The digital twin and model layer is equipped with a lightweight online simulation engine. The lightweight online simulation engine uses the current state of the twin as the initial condition to quickly simulate and predict the construction process in the next 24 to 72 hours.

5. The intelligent construction management and control platform system for super high-rise buildings according to claim 4, characterized in that, The intelligent analysis and decision-making layer includes: The deformation difference active coordination module is used to calculate the optimal pre-adjusted elevation before the template is erected and send it to the layout robot; The intelligent scheduling module for multi-tower crane clusters is used to optimize the operation path and sequence of tower cranes based on structural stress monitoring data; The outrigger truss closure intelligent recommendation module is used to dynamically recommend the closure timing based on the deformation difference rate and additional stress.

6. A construction method using the intelligent construction management and control platform system for super high-rise buildings as described in any one of claims 1 to 5, characterized in that, Includes the following steps: Step S1: Construct a digital twin platform with a five-layer logical architecture covering the entire construction process; Step S2: Based on real-time monitoring data, drive the synchronous evolution of the digital twin model and automatically identify construction events; Step S3: Using an online simulation and prediction engine, with the current twin state as the initial condition and combined with the short-term construction plan, simulate and predict the structural response of the future construction cycle; Step S4: If the prediction result exceeds the safety threshold, the intelligent decision layer generates specific parameter control instructions including the elevation pre-adjustment value and the equipment scheduling plan; Step S5: Push the control command to the on-site execution terminal for construction adjustments, and feed back the adjusted measured data to the system to update the twin model and prediction algorithm.

7. The construction method according to claim 6, characterized in that, The automatic identification of construction events in step S2 includes: automatically marking the completion of core tube climbing formwork and key construction nodes of concrete pouring by analyzing abrupt changes in strain and deformation data, and using them as initial boundary conditions for simulation calculations.

8. The construction method according to claim 6, characterized in that, The short-term construction plan in step S3 includes at least the number of core tube construction layers, the number of outer frame construction layers, and the material stacking load for the next 24 to 72 hours.

9. The construction method according to claim 6, characterized in that, The control commands in step S4 include: a command to pre-adjust the elevation of the outer frame template for cases where the deformation difference between the core tube and the outer frame exceeds the limit, or a prompt for the recommended closing timing for the installation of the outrigger truss.

Images