Stability control and safety construction method for overrun beam and slab high and large formwork supporting system

Abstract

The invention relates to a stability control and safety construction method for a high and large formwork supporting system of an over-limit beam plate, and belongs to the technical field of over-limit beam plate construction. In order to solve the problem that a tall and large formwork supporting system is prone to deformation and instability in the construction process, a full framing with an adjustable base is erected, pre-tightening force is applied to a horizontal rod after a beam plate formwork is installed on the top of a framing body, and a real-time monitoring system is adopted for continuously monitoring framing body deformation, stress and dip angle data. The adjustable base is dynamically adjusted based on monitoring data so as to control the elevation and the perpendicularity, and meanwhile windproof cables are arranged on the periphery of the frame body and regularly checked. According to the method, the overall stability and construction safety of a supporting system can be effectively improved, and the method is suitable for over-limit beam and slab formwork supporting construction of a large-span and high-clearance concrete structure.

Description

Technical Field

[0001] This invention relates to the field of construction technology for super-large beam and slab structures. More specifically, this invention relates to a method for stability control and safe construction of a tall formwork support system for super-large beam and slab structures. Background Technology

[0002] In building construction, the construction of tall formwork support systems for super-large beam-slab structures faces the challenge of stability control. These support systems are prone to deformation and displacement when subjected to construction loads such as concrete pouring, affecting construction accuracy and safety.

[0003] Traditional support systems often employ coupler-type steel pipe scaffolding to erect full-span supports, with simple bases at the bottom of the uprights. Under load, this structure suffers from uneven stress distribution among the uprights, easily leading to uneven settlement. As construction progresses, the deformation of the support system gradually accumulates, potentially resulting in elevation deviations or a decrease in overall stability.

[0004] In existing technologies, monitoring of support systems mainly relies on periodic manual measurements. This method suffers from drawbacks such as long monitoring intervals and discontinuous data, making it difficult to detect sudden deformations in a timely manner. Furthermore, the accuracy of manual measurements is significantly affected by environmental factors and operator skill, failing to meet the precision requirements of monitoring for tall formwork support systems.

[0005] In terms of adjusting the support system, traditional methods often involve manually adjusting the height of the base. This method lacks systematic guidance and often only addresses obvious local deformations, making it difficult to achieve overall coordinated adjustment. Because the uprights of the support system influence each other, local adjustments may cause additional deformations in other parts, creating new imbalances.

[0006] The loads borne by the support system during construction are dynamic, and the theoretical load values ​​differ at different construction stages. Current technologies lack a mechanism for dynamically adjusting monitoring standards according to construction stages, making it difficult to adapt to changing actual working conditions. Furthermore, the stability control measures for the support system under external factors such as wind loads are relatively simple, mainly relying on passive protection methods such as adding diagonal bracing.

[0007] These issues result in insufficient stability control of tall formwork support systems during construction, necessitating improvements in monitoring methods and adjustment mechanisms. Summary of the Invention

[0008] One object of the present invention is to solve at least the above-mentioned problems and to provide at least the advantages that will be described later.

[0009] To achieve these objectives and other advantages according to the present invention, a method for stability control and safe construction of a high-rise beam-slab formwork support system is provided, comprising the following steps: S1. Erect a support frame, the support frame comprising multiple uprights and horizontal bars connected between the uprights, which are erected by fasteners to form a full-span support structure, and the bottom of the uprights is provided with an adjustable base; S2. Install beam and slab templates on the top of the support frame; S3. Apply a preload to the support frame, the preload being applied by a hydraulic tensioning device mounted on the horizontal bar; S4. A real-time monitoring system is used to continuously monitor the deformation, stress and tilt angle of the support frame. The real-time monitoring system includes a sensor unit and a central processing unit. S5. Based on the monitoring data of the real-time monitoring system, the elevation and verticality of the support frame are dynamically adjusted by the adjustable base set at the bottom of the pole; S6. During construction, windproof cables shall be installed around the support frame and regular inspections shall be carried out.

[0010] Preferably, the sensor unit includes a tilt sensor, a pressure sensor, and a displacement sensor. The tilt sensor is disposed at the top and bottom of a specific upright and is used to monitor the verticality of the upright. The pressure sensor is disposed in the adjustable base at the bottom of the upright and is used to monitor the axial pressure borne by the upright. The displacement sensor includes a laser rangefinder, which is disposed on the side of the support frame, with one end fixed to the support frame and the other end fixed to a stable reference point outside the support frame, and is used to monitor the horizontal displacement of the support frame. The data from the sensor unit is transmitted to the central processing unit in real time via a wireless transmission module.

[0011] Preferably, the central processing unit calculates and sets a dynamic alarm threshold based on the monitoring data of the support frame and the current construction stage.

[0012] Preferably, the process by which the central processing unit calculates and sets the dynamic alarm threshold specifically includes: The construction process is divided into multiple stages. In each stage, the central processing unit continuously records the monitoring data of the sensor unit and calculates the statistical characteristic value of the monitoring data in the current stage. The statistical characteristic value of the monitoring data includes at least the mean and standard deviation of the monitoring data. When entering the next construction phase, the central processing unit combines the statistical characteristic values ​​of the previous phase with the expected theoretical load changes in the current phase to calculate the prediction benchmark range of the monitoring data. Based on the predicted baseline range, a dynamic alarm threshold for the current stage is generated.

[0013] Preferably, the expected change in theoretical load at the current stage refers to the theoretical load ratio K at the current stage. The theoretical load ratio at the current stage represents the multiple of the theoretical load at the current stage relative to the theoretical load at the previous stage. The theoretical load at the current stage refers to the design value of the load acting on the support frame at the current construction stage, including the self-weight of the poured concrete, the self-weight of the slab and beam formwork, and the self-weight of the construction personnel and equipment. The theoretical load ratios at each stage of construction are pre-stored in the central processing unit. The calculation method for the prediction benchmark range includes: Call the average value μ of the monitoring data from the previous stage n-1 and standard deviation σ n-1 ; Calculate the predicted mean value μ′ for the current stage based on the theoretical load ratio K for the current stage. n = μ n-1 * K, Predictive Standard Deviation σ′ n = σ n-1 * K; The prediction benchmark range is in μ′ n Centered on β*σ′ n The range is the floating range, and β is the safety factor.

[0014] Preferably, the hydraulic tensioning device is used to symmetrically tension multiple horizontal bars, and the pressure sensor is used to monitor the distribution of preload in real time to ensure uniformity.

[0015] Preferably, each adjustable base is provided with an actuator, which is communicatively connected to the central processing unit to receive adjustment commands and drive the adjustable base to adjust its elevation and verticality. The central processing unit is also used to analyze the monitoring data in real time. When the monitoring data exceeds the dynamic alarm threshold, it calculates the required adjustment amount and direction of the adjustable base at the bottom of each pole, and sends the adjustment command containing the adjustment amount and direction to the actuator via wireless or wired transmission.

[0016] Preferably, the process by which the central processing unit calculates the required adjustment amount and direction for the adjustable base at the bottom of each pole specifically includes: Acquire tilt sensor data for a specific upright, calculate the relative tilt angle Δθ between its top and bottom, and the overall horizontal displacement D of the support frame as monitored by the displacement sensor; Based on the tilt angle Δθ and the pole height H, calculate the theoretical horizontal offset δ = H ×sin(Δθ) at the top of the pole; Combining the theoretical horizontal offset δ and the overall horizontal displacement D, a weighted summation method is used to calculate the comprehensive offset assessment value E = a · δ + b · D; where a is the local deformation weight coefficient, b is the overall deformation weight coefficient, and a + b = 1; the theoretical horizontal offset δ reflects the local deformation of the upright itself, and the overall horizontal displacement D reflects the overall deformation of the support frame. The comprehensive offset assessment value is compared with the dynamic alarm threshold of the current stage. If it exceeds the threshold, the adjustment amount calculation is initiated. The adjustment amount is calculated based on the comprehensive offset assessment value. The adjustment amount L = α × (|comprehensive offset assessment value| - dynamic alarm threshold), where α is a preset adjustment coefficient and the adjustment direction is the direction that counteracts the offset shown by the comprehensive offset assessment value.

[0017] Preferably, the process by which the central processing unit calculates the required adjustment amount and direction for the adjustable base at the bottom of each pole specifically includes: Acquire tilt sensor data for a specific upright, calculate the relative tilt angle Δθ between its top and bottom, and the overall horizontal displacement D of the support frame as monitored by the displacement sensor; Based on the tilt angle Δθ and the pole height H, calculate the theoretical horizontal offset δ = H ×sin(Δθ) at the top of the pole; Combining the theoretical horizontal offset δ and the overall horizontal displacement D, a weighted summation method is used to calculate the comprehensive offset assessment value E = a · δ + b · D; where a is the local deformation weight coefficient, b is the overall deformation weight coefficient, and a + b = 1; the theoretical horizontal offset δ reflects the local deformation of the upright itself, and the overall horizontal displacement D reflects the overall deformation of the support frame. Mark all poles whose comprehensive offset assessment value E exceeds the dynamic alarm threshold as poles to be adjusted, forming a set of poles to be adjusted Ω; The primary optimization objective is to minimize the comprehensive offset evaluation value E of all uprights in the set of uprights to be adjusted Ω, and the secondary optimization objective is to minimize the sum of squares of the adjustment values ​​of all uprights, so as to limit the overall adjustment range. Based on the system influence matrix M, an optimal set of upright adjustment instructions that can restore the stability of the entire support frame is calculated. The optimal set of pole adjustment instructions is synchronously sent to the corresponding actuators, driving multiple adjustable bases to coordinate their actions according to the optimized scheme.

[0018] Preferably, the system influence matrix M is obtained through any of the following methods: a) Finite element numerical simulation method: Before construction, a finite element model is established based on the design drawings of the support frame. By applying a unit displacement to the bottom of each upright in the model in sequence and calculating the displacement response of the top of all uprights, a complete system influence matrix M is constructed. b) System identification method: After the support frame is erected and the sensors are installed, multiple uprights are selected on site as excitation points in sequence, and their actuators are controlled to generate a small test displacement. At the same time, the response data of all sensors are recorded. Based on the ratio of the response data to the test displacement, the system influence matrix M is calculated and fitted.

[0019] This invention offers at least the following advantages: By constructing a support frame with an adjustable base and applying pre-tensioning force, it provides a stable working platform for the construction of large-scale beams and slabs. The full-span support structure formed by vertical and horizontal bars effectively distributes construction loads and reduces localized stress concentration. The application of pre-tensioning force enhances the overall rigidity of the frame, creating favorable conditions for subsequent construction processes. A real-time monitoring system continuously monitors the deformation, stress, and tilt angle of the support frame, enabling timely understanding of structural changes. Multi-dimensional data is collected by sensor units, and alarm thresholds are dynamically set by the central processing unit, achieving a quantitative assessment of the support system's stability. This monitoring method provides a reliable basis for early warning. Based on the monitoring data, the elevation and verticality of the support frame are dynamically adjusted via the adjustable base, proactively correcting structural deformation. The system calculates a comprehensive offset assessment and generates optimization adjustment instructions, achieving closed-loop control of the support system. Combined with auxiliary measures such as windproof cables, a complete stability control scheme is formed, improving the construction safety and reliability of the high-rise formwork support system.

[0020] Other advantages, objectives and features of the present invention will become apparent in part from the following description, and in part from those skilled in the art through study and practice of the invention. Detailed Implementation

[0021] The present invention will be further described in detail below with reference to embodiments, so that those skilled in the art can implement it based on the description.

[0022] This invention provides a method for stability control and safe construction of a high-rise beam and slab formwork support system, comprising the following steps: S1. Erect a support frame, the support frame comprising multiple uprights and horizontal bars connected between the uprights, which are erected by fasteners to form a full-span support structure, and the bottom of the uprights is provided with an adjustable base; S2. Install beam and slab templates on the top of the support frame; S3. Apply a preload to the support frame, the preload being applied by a hydraulic tensioning device mounted on the horizontal bar; S4. A real-time monitoring system is used to continuously monitor the deformation, stress and tilt angle of the support frame. The real-time monitoring system includes a sensor unit and a central processing unit. S5. Based on the monitoring data of the real-time monitoring system, the elevation and verticality of the support frame are dynamically adjusted by the adjustable base set at the bottom of the pole; S6. During construction, windproof cables shall be installed around the support frame and regular inspections shall be carried out.

[0023] Specifically, when erecting the support frame, uprights and horizontal bars can be assembled into a full-span support structure using fastener-type connectors. The spacing between the uprights can be selected as 1.2 meters, 1.5 meters, or 1.8 meters according to the design load, and the step distance of the horizontal bars can be selected as 1.5 meters, 1.8 meters, or 2.0 meters to adapt to different load requirements. Adjustable bases can be installed at the bottom of the uprights, with an adjustment range of 100 mm to 300 mm to compensate for uneven foundations. The support frame material can be Q235 carbon structural steel or high-strength aluminum alloy to ensure sufficient strength and durability. The assembly positions of the uprights and horizontal bars should be located in the load-bearing areas of the building structure, with the uprights standing vertically on the foundation and the horizontal bars connecting the uprights horizontally to form a grid structure. When installing beam and slab formwork on top of the support frame, plywood or steel formwork can be used, with a formwork thickness of 15 mm, 18 mm, or 20 mm. The formwork is fixed to the support frame with nails or bolts.

[0024] The process of erecting a support frame includes first positioning the uprights, then installing horizontal bars layer by layer and securing them with fasteners, and finally adjusting the adjustable base to level the frame. When installing beam and slab formwork, first lay the formwork on top of the frame, then check the flatness of the formwork and secure it. The erection of the support frame can refer to the Safety Technical Specifications for Construction Scaffolding, and load tests should be conducted to ensure stability. Test methods include applying static loads and measuring deformation. The test object can be a formwork support system on an actual construction site, and performance can be evaluated by measuring upright settlement and horizontal displacement.

[0025] When applying preload, a hydraulic tensioning device can be installed on the horizontal bar. The working pressure of the hydraulic tensioning device can be selected as 10 MPa, 15 MPa, or 20 MPa. The preload magnitude can be calculated and set according to the design load and the spacing and number of uprights, for example, 50 kN, 100 kN, or 150 kN, to ensure the overall rigidity of the support system. The hydraulic tensioning device may include a hydraulic pump and a tensioning cylinder, connected by a high-pressure hose. The assembly position is located in the middle or end of the horizontal bar, arranged symmetrically. The material for applying the preload can be high-strength steel strand or hydraulic oil to ensure the stability and reliability of the tensioning process. The preload setting method can be calculated based on the design load of the support frame, and the force value is monitored in real time by a pressure sensor to ensure uniform distribution.

[0026] The process of applying pretensioning force involves starting the hydraulic pump, which causes the tensioning cylinder to apply tension to the horizontal bar, maintaining stability once the set pressure is reached. Pressure sensors monitor the force values ​​at various points; if the deviation exceeds 5%, the tensioning sequence or pressure is adjusted. Functional testing can be conducted by simulating construction loads, using a hydraulic testing machine to verify the accuracy and durability of the tensioning device. The test object can be a model of the formwork support system, and the effectiveness is evaluated by measuring the deformation of the frame after pretensioning.

[0027] The real-time monitoring system can include sensor units and a central processing unit. Sensor units can be tilt sensors, pressure sensors, and displacement sensors. Tilt sensors typically achieve an accuracy of 0.1, 0.2, or 0.5 degrees in construction site environments, with protective measures to reduce environmental interference. Pressure sensors can have measuring ranges of 0-200 kN, 0-500 kN, or 0-1000 kN. Displacement sensors can be laser rangefinders, with measuring ranges of 0-100 mm, 0-200 mm, or 0-500 mm. Tilt sensors are mounted at the top and bottom of the upright, pressure sensors are mounted in adjustable bases at the bottom of the upright, and displacement sensors are mounted on the side of the support frame, with one end fixed to the frame and the other end fixed to an external reference point. The central processing unit can be an industrial computer or an embedded controller, receiving data via a wireless transmission module. During dynamic adjustment, the adjustment accuracy of the adjustable base can be selected as 1 mm, 2 mm or 5 mm. The alarm threshold can be set according to the monitoring data and design load. For example, the displacement alarm threshold can be uniformly set to 10 mm, 15 mm or 20 mm, and dynamically adjusted based on the design load and construction stage.

[0028] The real-time monitoring process involves sensors continuously collecting data, which is then wirelessly transmitted to a central processing unit (CPU). The CPU analyzes the data and calculates dynamic alarm thresholds. If the data exceeds the threshold, the CPU sends a command to the actuator of the adjustable base, driving the base to adjust its elevation and verticality. The dynamic alarm threshold is set based on construction phases, such as foundation, pouring, and curing stages. The threshold is updated for each stage based on theoretical load changes. Functional testing can be conducted through simulated load experiments, using the data acquisition system to verify monitoring accuracy and adjust response time. The experimental object can be the actual support system in construction, and the thresholds are optimized by statistically analyzing the mean and standard deviation of the monitoring data.

[0029] When installing windproof cables, steel wire ropes or nylon ropes can be used, with diameters of 8 mm, 10 mm, or 12 mm, and breaking strengths of 50 kN, 80 kN, or 100 kN. The cables are installed around the perimeter of the support frame, connected via ground anchors or fixed points, with angles between the cables and the ground of 30, 45, or 60 degrees. Regular inspections can include visual checks and the use of measuring tools, with frequency options including daily, weekly, or monthly, adjusted according to construction progress and environmental conditions. The windproof cables can be made of galvanized steel wire or high-strength polymers to ensure corrosion resistance and durability.

[0030] The process of setting up windproof cables includes first determining the location of the anchor points, then installing the cables and adjusting the tension, and finally checking the reliability of the connections. During regular inspections, construction personnel check the cable tension, scaffold deformation, and the condition of the connectors, and record the inspection results. Functional testing can be conducted through wind load simulation experiments, using a wind turbine to apply wind force and measuring the scaffold response. The test object can be an outdoor construction site, and the windproof effect can be evaluated through environmental monitoring data.

[0031] In the above technical solution, by erecting a support frame and installing beam and slab formwork on top, a stable full-span support structure can be formed, providing a reliable foundation for subsequent construction. The uprights and horizontal bars are connected by fasteners, and the adjustable base helps to adapt to different foundation conditions and reduce the risk of uneven settlement. This structural design ensures that the support system distributes loads evenly, reducing the possibility of localized deformation. Applying preload and continuous monitoring through a real-time monitoring system allows for timely identification of deformation and stress changes in the support frame. A hydraulic tensioning device applies preload symmetrically, and combined with sensor data, ensures uniform force distribution and improves overall rigidity. Dynamic adjustment of elevation and verticality helps maintain structural balance and prevents cumulative errors from affecting construction quality. Installing wind-resistant cables and conducting regular inspections enhances the stability of the support system in the external environment. The cables are fixed around the frame and connected to ground anchors, effectively dispersing wind loads and reducing the risk of overturning. Regular inspections facilitate early detection of potential problems, such as loose connections or worn cables, allowing for timely maintenance and extending service life.

[0032] Furthermore, the sensor unit includes a tilt sensor, a pressure sensor, and a displacement sensor. The tilt sensor is installed at the top and bottom of a specific upright, referring to a critical load-bearing upright, such as an upright at a corner, mid-span, or in a load-concentrated area, and is used to monitor the verticality of the upright. The pressure sensor is installed in the adjustable base at the bottom of the upright and is used to monitor the axial pressure borne by the upright. The displacement sensor includes a laser rangefinder, which is installed on the side of the support frame, with one end fixed to the support frame and the other end fixed to a stable reference point outside the support frame, and is used to monitor the horizontal displacement of the support frame. The data from the sensor unit is transmitted to the central processing unit in real time via a wireless transmission module.

[0033] Specifically, the sensor unit may include a tilt sensor, a pressure sensor, and a displacement sensor. The tilt sensor can be configured with an accuracy of 0.1, 0.2, or 0.5 degrees to detect angle changes; the pressure sensor can have a range of 0-200 kN, 0-500 kN, or 0-1000 kN to adapt to different load conditions; the displacement sensor can be a laser rangefinder with a measurement range of 0-100 mm, 0-200 mm, or 0-500 mm and a resolution of 0.1 mm. These sensors can be commercially available digital tilt sensors, strain gauge pressure sensors, and infrared laser rangefinders, and the housing material can be aluminum alloy or engineering plastics to ensure lightweight and durability. The sensor unit is connected via internal circuitry. The operation process includes automatic data acquisition after power supply and signal output via analog-to-digital conversion.

[0034] The sensor unit's parameters can be set through calibration procedures, such as using standard angle blocks and a press, to ensure accurate measurements. Functional testing can be conducted in a laboratory environment, mounting the sensor on a simulated frame, applying known loads and displacements, and recording the output values ​​for comparison with actual values. The test object can be a small support frame model, collecting data through repeated tests, and performing statistical analyses such as calculating the mean error and standard deviation to verify sensor reliability. The raw materials for the sensor unit can be sourced from electronic component suppliers to ensure compliance with industry standards.

[0035] Tilt sensors can be installed at the top and bottom of specific uprights, with the assembly location chosen at the end flange or connecting node of the upright, and fixed with bolts. Pressure sensors can be installed inside the adjustable base at the bottom of the upright, assembled between the base and the contact surface of the upright, and connected by threads. Displacement sensors can be laser rangefinders, installed on the side of the support frame, with one end fixed to the crossbar of the frame by a bracket, and the other end fixed to a stable reference point outside the frame, such as a ground anchor or independent support. The installation height of these sensors can be selected as 1 meter, 2 meters, or 3 meters above the ground to accommodate changes in the height of the frame. The sensor materials can be stainless steel or galvanized steel to resist environmental corrosion.

[0036] The sensor setup process includes first locating the installation point, then fixing the sensor and connecting the wiring, and finally calibrating the initial values. For example, an inclination sensor simultaneously collects angle data at the top and bottom of the pole, and calculates the relative tilt by comparison; a pressure sensor monitors changes in base pressure in real time; and a displacement sensor measures horizontal distance via laser reflection. Functional testing can be conducted on-site by artificially applying small displacements or loads to observe the consistency between the sensor response time and the data. The test object can be the actual support frame in construction, using a total station or level as a reference for data comparison and error analysis.

[0037] Data from the sensor unit can be transmitted to the central processing unit in real time via a wireless transmission module. The wireless transmission module can be a Wi-Fi module, Bluetooth module, or 4G / 5G module, with a transmission distance of 100 meters, 500 meters, or 1000 meters, and a data transmission rate of 10kbps, 50kbps, or 100kbps to ensure real-time performance. The module's operating frequency can be 2.4GHz or 5GHz, and a low-power mode can be selected to extend battery life. The wireless transmission module can be integrated inside the sensor unit or used as an external device, connecting via a serial port or USB interface. The installation location should be in a cool, well-ventilated area of ​​the mounting frame, avoiding direct sunlight and rain. The module material can be flame-retardant plastic or a metal casing to ensure durability.

[0038] The wireless transmission process involves sensors collecting data, which is then packaged by the built-in processor and transmitted by the wireless module to the central processing unit using a specific protocol. The central processing unit receives, parses, and stores the data. Parameter settings include setting the transmission interval, such as once per second or every five seconds, and signal strength thresholds, such as -70dBm, -80dBm, or -90dBm, to ensure stable connections. Functional testing can be conducted in simulated interference environments, such as testing data packet loss rate when multiple wireless devices coexist, and using a network analyzer to evaluate transmission performance. The experimental subject can be a field-deployed sensor network; long-term monitoring of data can statistically analyze transmission success rate and latency to optimize network configuration.

[0039] The aforementioned technical solution utilizes a sensor unit comprised of tilt sensors, pressure sensors, and displacement sensors to comprehensively monitor the deformation, stress, and tilt changes of the support frame. These sensors provide multi-dimensional data to help identify the structural condition and ensure monitoring coverage of key parameters. The sensor unit's operation includes automatic signal acquisition and conversion, providing reliable input for subsequent analysis. Placing sensors at the top and bottom of the uprights, inside the adjustable base, and on the sides of the support frame accurately reflects the local and overall deformation of the support system. This arrangement reduces monitoring blind spots and improves data representativeness. Fixed installation and calibration of the sensors ensure long-term stable operation, enhancing the timeliness and accuracy of early warnings. Real-time transmission of sensor data to the central processing unit via a wireless transmission module enables remote monitoring, reducing on-site wiring requirements. Wireless transmission supports flexible deployment and adapts to complex construction environments. The stable and reliable data transmission process contributes to improved efficiency and response speed in construction management.

[0040] Furthermore, the central processing unit calculates and sets dynamic alarm thresholds based on the monitoring data of the support frame and the current construction stage.

[0041] In one embodiment, the process by which the central processing unit calculates and sets the dynamic alarm threshold specifically includes: The construction process is divided into multiple stages. In each stage, the central processing unit continuously records the monitoring data of the sensor unit and calculates the statistical characteristic value of the monitoring data in the current stage. The statistical characteristic value of the monitoring data includes at least the mean and standard deviation of the monitoring data. When entering the next construction phase, the central processing unit combines the statistical characteristic values ​​of the previous phase with the expected theoretical load changes in the current phase to calculate the prediction benchmark range of the monitoring data. Based on the predicted baseline range, a dynamic alarm threshold for the current stage is generated.

[0042] In one embodiment, the expected change in theoretical load at the current stage refers to the theoretical load ratio K at the current stage. The theoretical load ratio at the current stage represents the multiple of the theoretical load at the current stage relative to the theoretical load at the previous stage. The theoretical load at the current stage refers to the design value of the load acting on the support frame at the current construction stage, including the self-weight of the poured concrete, the self-weight of the slab beam formwork, and the self-weight of the construction personnel and equipment. The theoretical load ratios at each construction stage are pre-stored in the central processing unit based on design calculations and similar engineering experience, and are calibrated according to the actual working conditions during construction. The calculation method for the prediction benchmark range includes: Call the average value μ of the monitoring data from the previous stage n-1 and standard deviation σ n-1 ; Calculate the predicted mean value μ′ for the current stage based on the theoretical load ratio K for the current stage. n = μ n-1 * K, Predictive Standard Deviation σ′ n = σ n-1 * K; The prediction benchmark range is in μ′ n Centered on β*σ′ n The range is the floating range, and β is the safety factor, which is calibrated based on the structural safety level and engineering experience, and is usually taken as 1.5 to 2.5.

[0043] Specifically, the central processing unit first divides the construction process into multiple consecutive stages, including the foundation construction stage, the formwork installation stage, and the concrete pouring stage. The duration of each stage can be set to 24 hours, 48 ​​hours, or 72 hours according to the actual needs of the project. The central processing unit can be equipped with industrial-grade computer equipment, data acquisition cards, and storage modules, with storage capacities of 512GB or 1TB. These devices can be installed in a control box on the construction site and connected to the sensor network via a waterproof junction box.

[0044] During operation, the sensor unit continuously collects monitoring data at each construction stage, including parameters such as pole tilt angle, base pressure, and scaffold displacement. The data acquisition frequency can be set to once per minute, once every 5 minutes, or once every 10 minutes. The central processing unit calculates the statistical characteristics of these data in real time, including the arithmetic mean and standard deviation. The calculation process uses a sliding window method, and the window size can be set to 30 minutes, 60 minutes, or 120 minutes. The central processing unit stores these statistical characteristics along with the raw data on the local hard drive and simultaneously backs them up to a cloud server via the network.

[0045] Upon entering a new construction phase, the central processing unit automatically retrieves the pre-stored theoretical load ratio K, which can be 1.2, 1.5, or 2.0. The central processing unit then combines this with statistical characteristic values ​​from the previous phase, including the mean μ. n-1 and standard deviation σ n-1 Calculate the current forecast baseline range. The specific calculation process includes: forecast mean μ′ n = μ n-1 * K, Predictive Standard Deviation σ′ n = σ n-1 * K. The safety factor β used by the central processing unit can be selected as 1.5, 2.0, or 2.5, and is used to generate the predicted mean μ′. n Centered on, the floating range is β×σ′ n The prediction range.

[0046] Based on the calculated prediction baseline range, the central processing unit automatically generates dynamic alarm thresholds. These thresholds can be set as the upper and lower limits of the prediction range; for example, the displacement alarm threshold can be uniformly set to 10 mm, 15 mm, or 20 mm, dynamically adjusted based on the design load and construction stage. The threshold update timing can be set to automatic updates at the beginning of each stage, or triggered updates based on the rate of change of the monitored data. The central processing unit also sets up a two-level alarm mechanism, activating a higher-level alarm when the monitored data exceeds the threshold multiple times consecutively.

[0047] To ensure system reliability, functional testing is required during implementation. Testing can be conducted in a simulated construction environment, using a hydraulic loading device to simulate load changes at different construction stages. During testing, the system's response time, calculation accuracy, and threshold adaptability are recorded. Experimental data can be analyzed using statistical methods, including calculating confidence intervals and hypothesis testing, to verify the effectiveness of the dynamic alarm threshold. In practical applications, the central processing unit can also continuously optimize the theoretical load ratio and safety factor settings based on historical engineering data.

[0048] In the above technical solution, by dividing the construction process into multiple stages and continuously recording monitoring data, it can better adapt to load changes under different construction conditions. This staged management allows the monitoring system to adjust its early warning strategy according to the actual progress, improving its sensitivity to changes in structural state. The central processing unit automatically calculates statistical characteristic values ​​within each stage, providing a data basis for threshold setting. By calculating the statistical characteristic values ​​of the monitoring data, including the mean and standard deviation, the actual state of the support system can be objectively reflected. This data-driven approach reduces the influence of subjective judgment, making alarm thresholds more scientifically based. The central processing unit continuously updates the statistical characteristic values, ensuring that threshold calculations are always based on the latest data, improving the accuracy of early warnings. By combining the statistical characteristic values ​​of the previous stage with the theoretical load changes of the current stage to generate dynamic alarm thresholds, adaptive adjustment of the early warning standard can be achieved. This method considers the expected changes in load during the construction process, allowing the alarm threshold to be automatically updated with each construction stage. The dynamic threshold generation mechanism improves the monitoring system's ability to identify abnormal situations and enhances the safety of the construction process.

[0049] Furthermore, the hydraulic tensioning device is used to symmetrically tension multiple horizontal bars, and the pressure sensor is used to monitor the distribution of preload in real time to ensure uniformity.

[0050] Specifically, the hydraulic tensioning device can be composed of an electric hydraulic pump and a tensioning cylinder. The rated working pressure can be selected from 10 MPa, 15 MPa, or 20 MPa, and the output force range can be selected from 50 kN to 200 kN. The piston diameter of the tensioning cylinder can be selected from 50 mm, 80 mm, or 100 mm, and the stroke can be selected from 100 mm, 150 mm, or 200 mm. The device can be made of high-strength alloy steel cylinder body and wear-resistant seals to ensure durability. The hydraulic tensioning device can be symmetrically arranged at the middle or end of the horizontal bar and connected to the horizontal bar through a special clamp. The clamp can be an adjustable steel clamp, ensuring full contact with the bar surface during assembly.

[0051] During operation, the hydraulic pump generates pressurized oil to push the piston of the tensioning cylinder, applying preload to the horizontal bar. The system pressure can be displayed in real time via a pressure gauge with a selectable range of 0-25 MPa and an accuracy class of 0.5 or 1.0. Parameter setting involves calculating the required oil pressure based on the designed preload value and setting the target pressure via a pressure regulating valve. Functional testing can be conducted on a test bench, using a standard force gauge to verify the correspondence between the output force and the pressure gauge reading. Horizontal bars of different diameters can be selected as test objects, and pressure stability data can be recorded through multiple tensioning tests.

[0052] Symmetrical tensioning can be performed radially from the center of the support frame or sequentially along a diagonal. Tensioning points can be arranged symmetrically at 4, 6, or 8 points, with a spacing of 2, 3, or 4 meters between adjacent points. A synchronous control system can be used, with a control accuracy of ±2%, ±3%, or ±5%. The synchronous control unit can be installed on the hydraulic pump station and connected to each tensioning cylinder via cables. The control unit can be made of engineering plastic housing and copper circuit boards, with a protection rating of IP54 or IP65.

[0053] During operation, the operator initiates the synchronization control program, and each tensioning cylinder moves synchronously according to a preset sequence and speed. The system monitors the pressure values ​​at each point to ensure that the difference does not exceed a set threshold, such as 5%, 8%, or 10%. Pressure data is transmitted to the control unit in real time, and the oil supply to the corresponding cylinder is automatically adjusted when uneven pressure is detected. Parameter setting methods include setting the tensioning sequence, synchronization accuracy threshold, and pressure holding time. Functional testing can be conducted by arranging multiple tensioning points on the test frame, using high-precision pressure sensors to monitor the force values ​​at each point, and calculating the uniformity of the force distribution.

[0054] A resistance strain gauge pressure sensor can be used to monitor the preload distribution. The sensor range can be selected from 0-100 kN, 0-200 kN, or 0-500 kN, and the accuracy can be selected from 0.5%FS, 1.0%FS, or 1.5%FS. The sensor can be installed in an adjustable base at the bottom of the pole or directly integrated into the tensioning fixture. The sensor signal is transmitted to a data acquisition unit via a shielded cable. The sampling frequency of the acquisition unit can be selected from 10Hz, 50Hz, or 100Hz. Stainless steel elastomers and gold-plated contact points can be used for the sensor material to ensure long-term stability.

[0055] During operation, the pressure sensor monitors the force values ​​at each tensioning point in real time, and the data acquisition instrument continuously records and calculates the standard deviation and range of the force value distribution. The monitoring system sets a force uniformity threshold, such as a force value difference at each point not exceeding 10%, 15%, or 20% of the average value. When the threshold is exceeded, the system issues an alarm and indicates the tensioning point location that needs adjustment. Parameter setting methods include calibrating the sensor zero point and setting the alarm threshold. Functional testing can be conducted in a calibration laboratory, using a standard press to apply known force values ​​to verify the sensor measurement accuracy and system responsiveness.

[0056] In the above technical solution, by using a hydraulic tensioning device to symmetrically tension the horizontal bars, the preload can be evenly distributed throughout the support frame. This symmetrical force application method helps maintain the force balance of the frame and avoids excessive local stress. During the tensioning process, the control system keeps all points synchronized, improving the coordination of the force application process.

[0057] By using pressure sensors to monitor the preload distribution in real time, uneven force distribution can be detected promptly. The monitoring system continuously collects data from each tensioning point and automatically issues a warning when the detected force difference exceeds a set threshold. This real-time feedback mechanism provides a basis for adjusting the tensioning operation, ensuring that the preload meets design requirements.

[0058] By combining symmetrical tensioning with real-time monitoring, the overall stiffness and stability of the support frame can be effectively improved. Uniform preload distribution enables all components of the frame to work collaboratively, reducing the risk of deformation. This technical feature provides a more reliable structural foundation for subsequent construction procedures, helping to ensure construction safety.

[0059] Furthermore, each adjustable base is provided with an actuator, which is communicatively connected to the central processing unit and is used to receive adjustment commands and drive the adjustable base to adjust its elevation and verticality. The central processing unit is also used to analyze the monitoring data in real time. When the monitoring data exceeds the dynamic alarm threshold, it calculates the required adjustment amount and direction of the adjustable base at the bottom of each pole, and sends the adjustment command containing the adjustment amount and direction to the actuator via wireless or wired transmission.

[0060] In one embodiment, the process by which the central processing unit calculates the required adjustment amount and direction for the adjustable base at the bottom of each pole specifically includes: Acquire tilt sensor data for a specific upright, calculate the relative tilt angle Δθ between its top and bottom, and the overall horizontal displacement D of the support frame as monitored by the displacement sensor; Based on the tilt angle Δθ and the pole height H, calculate the theoretical horizontal offset δ = H ×sin(Δθ) at the top of the pole; Combining the theoretical horizontal offset δ and the overall horizontal displacement D, a weighted summation method is used to calculate the comprehensive offset assessment value E = a · δ + b · D; where a is the local deformation weight coefficient, b is the overall deformation weight coefficient, and a + b = 1. The weight coefficients a and b are determined based on structural analysis and experimental data, such as through finite element simulation or field testing calibration; the theoretical horizontal offset δ reflects the local deformation of the upright itself, and the overall horizontal displacement D reflects the overall deformation of the support frame; The comprehensive offset assessment value is compared with the dynamic alarm threshold of the current stage. If it exceeds the threshold, the adjustment amount calculation is initiated. The adjustment amount is calculated based on the comprehensive offset assessment value. The adjustment amount L = α × (|comprehensive offset assessment value| - dynamic alarm threshold), where α is a preset adjustment coefficient and the adjustment direction is the direction that counteracts the offset shown by the comprehensive offset assessment value.

[0061] Specifically, each adjustable base can be equipped with an actuator, which can be a stepper motor or a servo motor, with an output torque selectable at 5 Nm, 10 Nm, or 15 Nm, and an adjustment accuracy of 0.1 mm, 0.2 mm, or 0.5 mm. The actuator is connected to the base's adjusting screw via a gearbox, and its mounting position is located on the side or bottom of the adjustable base. The actuator can be made of an aluminum alloy shell and steel transmission components. The actuator communicates with the central processing unit via an RS485 wired interface or a wireless transmission module, with a transmission distance selectable at 100 meters, 200 meters, or 500 meters.

[0062] During operation, the actuator remains in standby mode, receiving adjustment commands from the central processing unit. After command parsing, the motor drives the adjusting screw to rotate, achieving precise lifting and lowering of the base. Parameter setting methods include establishing the correspondence between the motor's control pulses and the displacement. Functional testing can be conducted on an experimental platform, using displacement sensors to measure the consistency between the actual displacement and the command requirements. Multiple adjustable bases can be selected for the experiment, and their accuracy in responding to commands and repeatability can be statistically analyzed.

[0063] The central processing unit (CPU) analyzes monitoring data from the sensor units in real time. When the monitoring data exceeds the dynamic alarm threshold, it automatically initiates an adjustment command calculation program. The data analysis cycle can be selected once per second, once every 5 seconds, or once every 10 seconds. The CPU can be an industrial computer with a processor frequency of 2.0GHz, 2.5GHz, or 3.0GHz, and a memory capacity of 8GB, 16GB, or 32GB. This unit is installed in a control box at the construction site and connects to all actuators via a communication network.

[0064] During operation, the central processing unit continuously compares the monitored data with the current dynamic alarm threshold. Once the data exceeds the limit, it immediately calculates the required adjustment amount and direction for the adjustable base at the bottom of each pole according to a preset algorithm. After calculation, the unit sends a command containing the specific adjustment parameters to the corresponding actuator via wireless or wired transmission. Parameter setting methods include setting the alarm threshold and coefficients for the adjustment algorithm. Functional testing can be performed by simulating an out-of-limit data stream to verify the central processing unit's response time and accuracy throughout the entire process from analysis to command transmission.

[0065] The central processing unit acquires tilt sensor data from the top and bottom of specific uprights, calculates their relative tilt angle Δθ, and the angle measurement accuracy can be selected as 0.01 degrees, 0.02 degrees, or 0.05 degrees. Simultaneously, it acquires the overall horizontal displacement D of the support frame monitored by displacement sensors, with a displacement measurement range selectable as 0-50 mm, 0-100 mm, or 0-200 mm. This sensor data is transmitted to the central processing unit in real time via a wireless transmission module.

[0066] During operation, the central processing unit performs differential calculations on the received tilt angle data to obtain the bending trend of the pole. Displacement data is read directly. Based on the tilt angle Δθ and the pole height H (the height value can be preset to 3 meters, 5 meters, or 8 meters), the theoretical horizontal offset δ = H × sin(Δθ) at the top of the pole is calculated. The parameter setting method includes pre-storing the height values ​​of each pole in the central processing unit. Functional testing can compare the results with those from external measuring equipment such as a total station to verify the accuracy of the theoretical horizontal offset calculation.

[0067] The central processing unit (CPU) combines the theoretical horizontal offset δ with the overall horizontal displacement D, and calculates the comprehensive offset assessment E = a · δ + b · D ​​using a weighted summation method. The weighting coefficients a (local deformation weight) and b (overall deformation weight) can be selected as 0.3, 0.5, or 0.7, respectively, satisfying a + b = 1. These weighting coefficients are determined based on structural analysis and experimental data, such as through finite element simulation or field testing. The calculation unit utilizes the CPU's built-in arithmetic logic unit, and its processing speed can be selected as 1 GHz, 1.5 GHz, or 2.0 GHz.

[0068] During operation, the central processing unit calls preset weighting coefficients to fuse the two offsets, obtaining a comprehensive stability assessment index. Subsequently, the comprehensive offset assessment value E is compared in real time with the current dynamic alarm threshold (e.g., 8 mm, 10 mm, or 12 mm). Parameter setting methods include setting and adjusting the weighting coefficients through a software interface. Functional testing can simulate different deformation modes to verify whether the comprehensive assessment value can effectively characterize the actual stability state of the frame.

[0069] When the overall offset assessment value E exceeds the dynamic alarm threshold, the central processing unit initiates adjustment calculation. The formula for calculating the adjustment value L is L = α × (|E| - dynamic alarm threshold), and the adjustment coefficient α can be selected as 0.5, 1.0, or 1.5. The adjustment direction is the direction that counteracts the offset indicated by the overall offset assessment value E. For example, if E represents a northward offset, then the adjustment direction is southward.

[0070] During operation, the central processing unit first determines the direction of the offset, and then calculates the specific adjustment amount L based on the magnitude of the exceedance. The final generated adjustment instruction includes two key parameters: "adjustment amount L" and "adjustment direction," and specifies the target actuator. Parameter setting methods include setting the adjustment coefficient α and the direction judgment rule. Functional testing can simulate different exceedance scenarios to check whether the calculated adjustment amount and direction conform to the expected correction logic.

[0071] In the above technical solution, by establishing a communication connection between the actuator and the central processing unit, remote dynamic adjustment of the support frame's elevation and verticality can be achieved. When the monitored data exceeds the alarm threshold, the central processing unit automatically sends adjustment instructions to the actuator, reducing the delay of manual intervention. This automated adjustment method helps maintain the stability of the support frame. By comprehensively calculating the tilt angle of the uprights and the overall displacement of the frame, the deformation of the support system can be more comprehensively assessed. A weighted method is used to calculate the comprehensive offset assessment, taking into account the influence of both local and overall deformation. The adjustment amount and direction are calculated based on the assessment results, making the adjustment operation more targeted. By setting clear adjustment amount calculation formulas and direction judgment rules, clear operating instructions can be provided to the actuator. The calculation of the adjustment amount considers the difference between the actual offset and the threshold, ensuring that the adjustment range matches the degree of deformation. This adjustment method helps the support frame gradually restore a stable state and prevents over-adjustment.

[0072] In another embodiment, the process by which the central processing unit calculates the required adjustment amount and direction for the adjustable base at the bottom of each pole specifically includes: Acquire tilt sensor data for a specific upright, calculate the relative tilt angle Δθ between its top and bottom, and the overall horizontal displacement D of the support frame as monitored by the displacement sensor; Based on the tilt angle Δθ and the pole height H, calculate the theoretical horizontal offset δ = H ×sin(Δθ) at the top of the pole; Combining the theoretical horizontal offset δ and the overall horizontal displacement D, a weighted summation method is used to calculate the comprehensive offset assessment value E = a · δ + b · D; where a is the local deformation weight coefficient, b is the overall deformation weight coefficient, and a + b = 1. The weight coefficients a and b are determined based on structural analysis and experimental data; the theoretical horizontal offset δ reflects the local deformation of the upright itself, and the overall horizontal displacement D reflects the overall deformation of the support frame. Mark all poles whose comprehensive offset assessment value E exceeds the dynamic alarm threshold as poles to be adjusted, forming a set of poles to be adjusted Ω; The primary optimization objective is to minimize the comprehensive offset evaluation value E of all uprights in the set of uprights to be adjusted Ω, and the secondary optimization objective is to minimize the sum of squares of the adjustment values ​​of all uprights, so as to limit the overall adjustment range. Based on the system influence matrix M, an optimal set of upright adjustment instructions that can restore the stability of the entire support frame is calculated. The term "optimal" means minimizing the secondary objective while satisfying the primary objective. The optimal set of pole adjustment instructions is synchronously sent to the corresponding actuators, driving multiple adjustable bases to coordinate their actions according to the optimized scheme.

[0073] Specifically, the central processing unit marks all poles whose comprehensive offset assessment value E exceeds the dynamic alarm threshold as poles requiring adjustment, forming a set Ω of poles to be adjusted. The dynamic alarm threshold can be set to 8 mm, 10 mm, or 12 mm depending on the construction stage. The marking conditions can be selected as immediate marking upon exceeding the threshold, or marking after 3 or 5 consecutive exceedances of the threshold. The central processing unit can be equipped with a data filtering module, with a processing speed selectable at 1 GHz, 1.5 GHz, or 2.0 GHz. This module is integrated inside the central processing unit and connected to the computing unit via an internal bus.

[0074] During operation, the central processing unit compares the comprehensive offset assessment value E of each pole with the current threshold in real time. When the marking conditions are met, the pole number is added to the set Ω. The system continuously updates the set content and records the number of times and the magnitude of each pole exceeds the limit. Parameter setting methods include setting the marking conditions and the set update frequency. Functional testing can verify the accuracy of the set formation by inputting exceedance data with different distributions. The experimental object can be a simulated support frame model, and the response time and accuracy of the set formation can be statistically analyzed.

[0075] The central processing unit (CPU) prioritizes minimizing the comprehensive offset evaluation value E of all uprights in the set Ω to be adjusted, with minimizing the sum of squared adjustments of all uprights as a secondary optimization objective. The optimization calculation can employ linear programming or quadratic programming algorithms, and the weight of the primary objective can be selected as 0.7, 0.8, or 0.9. The required computational accuracy can reach 0.01 mm, 0.02 mm, or 0.05 mm. The CPU can be equipped with an optimization calculation module, which can be built based on a mathematical coprocessor, with a floating-point operation speed selectable at 1 billion operations per second, 5 billion operations per second, or 10 billion operations per second.

[0076] During operation, the optimization calculation module reads data from the set of poles to be adjusted, Ω, constructs an optimization model based on the system influence matrix M, and uses a quadratic programming algorithm to solve for the optimal adjustment amount. The calculation process includes constructing the objective function, setting constraints, and solving the optimization problem. Parameter setting methods include setting optimization weights, convergence accuracy, and the number of iterations. Functional testing can verify the algorithm's accuracy using a standard optimization test function. Experimental subjects can be pole sets of different sizes, and the optimization effect can be verified by comparing with the theoretical optimal solution.

[0077] Based on the system influence matrix M, the central processing unit calculates an optimal set of pole adjustment instructions. The instruction set includes the adjustment amount and direction for each pole to be adjusted, with adjustment accuracy reaching 0.1 mm, 0.2 mm, or 0.5 mm. The central processing unit can be equipped with an instruction generation module, which can be built based on a programmable logic controller (PLC) and has a selectable response time of 50 ms, 100 ms, or 200 ms. The instruction generation module is installed inside the central processing unit and connects to the actuator via an output interface.

[0078] During operation, the instruction generation module receives the optimization calculation results and converts them into an instruction format recognizable by the actuators. The instruction set is synchronously sent to all corresponding actuators via a communication network, driving multiple adjustable bases to coordinate actions according to the optimized scheme. Parameter setting methods include setting the instruction format, communication protocol, and synchronization timing. Functional testing can verify the accuracy and synchronization of the instruction set by simulating the collaborative work of multiple actuators. The experimental object can be an actual support frame, recording the synchronization error and adjustment effect during the adjustment process.

[0079] In the above technical solution, by establishing a communication connection between the actuator and the central processing unit, remote dynamic adjustment of the support frame's elevation and verticality can be achieved. When the monitored data exceeds the alarm threshold, the central processing unit automatically calculates the adjustment parameters and sends instructions to the actuator, reducing the time consumed by manual measurement. This closed-loop control method helps maintain the support frame within the allowable deformation range. By establishing a set of uprights to be adjusted and setting optimization goals, the coordinated adjustment of multiple uprights can be systematically handled. Minimizing the comprehensive offset assessment is the primary goal, while controlling the overall adjustment amplitude, which helps avoid new imbalances caused by excessive adjustment of individual uprights. This optimization strategy considers the mechanical characteristics of the support frame as a whole system. Calculating the optimal adjustment instruction set based on the system influence matrix can more accurately predict the impact of adjustment measures on the overall structure. By synchronously driving multiple adjustable bases to coordinate their actions according to the optimized scheme, the recovery process of the support frame is made more stable and orderly. This coordinated adjustment method helps improve the efficiency and reliability of the support system's stability recovery.

[0080] The system influence matrix M is obtained through any of the following methods: a) Finite element numerical simulation method: Before construction, a finite element model is established based on the design drawings of the support frame. By applying a unit displacement to the bottom of each upright in the model in sequence and calculating the displacement response of the top of all uprights, a complete system influence matrix M is constructed. This method has been verified by engineering and is applicable to conventional support systems. Specifically, before construction, a finite element model is established based on the design drawings of the support frame. The model accuracy can be selected as 1 mm, 2 mm, or 5 mm. A unit displacement is applied sequentially to the bottom of each upright in the model, with the unit displacement amount also selected as 1 mm, 2 mm, or 5 mm, and the displacement response at the top of all uprights is calculated. General-purpose finite element analysis software can be used, with the number of calculation nodes selected as 100,000, 500,000, or 1,000,000. A high-performance computer can be used, with the number of processor cores selected as 32, 64, or 128.

[0081] During the process, a complete finite element model of the support frame was established, including uprights, horizontal bars, and connectors. A unit displacement in the Z-direction was applied sequentially to the bottom of each upright, and the X, Y, and Z-direction displacement responses at the top of all uprights were recorded, forming the system influence matrix M. Parameter setting methods included setting material parameters, boundary conditions, and convergence criteria. Functional testing can verify the accuracy of the finite element calculations using a simplified model. Typical support frame structures can be selected as experimental subjects, and the reliability of the finite element model can be verified by comparing it with theoretical solutions.

[0082] b) System identification method: After the support frame is erected and the sensors are installed, multiple uprights are selected as excitation points on site in sequence, and their actuators are controlled to generate a small test displacement, with the test displacement ranging from 1 to 5 mm. At the same time, the response data of all sensors are recorded. Based on the ratio of the response data to the test displacement, the system influence matrix M is calculated and fitted. This method is based on on-site measurements and is more in line with actual working conditions.

[0083] After the support frame is erected and the sensors are installed, multiple uprights are selected sequentially on-site as excitation points. The number of excitation points can be 5%, 10%, or 20% of the total number of uprights, and the test displacement can be 1 mm, 2 mm, or 3 mm. The actuator is controlled to generate a small test displacement, and the response data of all sensors are recorded simultaneously. A dynamic signal analyzer can be used as the data acquisition system, with a sampling frequency of 100Hz, 200Hz, or 500Hz, and a channel count of 32, 64, or 128 channels.

[0084] During operation, test displacements are sequentially applied to the selected excitation points on the uprights, while simultaneously recording the response data from the sensors on all uprights. Based on the ratio of the response data to the test displacement, the complete system influence matrix M is fitted using the least squares method. Parameter setting methods include setting the test displacement magnitude, sampling frequency, and fitting algorithm parameters. Functional testing can verify the accuracy of system identification using a simplified structure with known characteristics. The experimental object can be an actual erected support frame, and the effectiveness of system identification can be verified by comparing the finite element results.

[0085] In the above technical solutions, the system influence matrix is ​​obtained through finite element numerical simulation, enabling the understanding of the mechanical properties of the support frame before construction. This method establishes a computational model based on design drawings and obtains the mutual influence relationships between the uprights through simulation analysis. Obtaining the system influence matrix in advance helps optimize the design of the adjustment scheme and provides a theoretical basis for stability control during construction. Obtaining the system influence matrix through system identification reflects the actual mechanical behavior of the erected support frame. This method involves direct on-site testing, obtaining system characteristics through fitting measured data, and considering the influence of actual factors such as material properties and connection status. The system influence matrix based on measured data is more realistic and helps improve the accuracy of adjustment and control. The two methods for obtaining the system influence matrix complement each other, and the appropriate method can be selected according to the actual engineering situation. The finite element method is suitable for the pre-construction scheme demonstration stage, while the system identification method is suitable for the on-site calibration stage after the frame is erected. This flexible acquisition method enhances the adaptability and practicality of the support system stability control method.

[0086] Although embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details and embodiments shown and described herein.

Claims

1. A method for stability control and safe construction of a high-rise beam and slab formwork support system, characterized in that, Includes the following steps: S1. Erect a support frame, the support frame comprising multiple uprights and horizontal bars connected between the uprights, which are erected by fasteners to form a full-span support structure, and the bottom of the uprights is provided with an adjustable base; S2. Install beam and slab templates on the top of the support frame; S3. Apply a preload to the support frame, the preload being applied by a hydraulic tensioning device mounted on the horizontal bar; S4. A real-time monitoring system is used to continuously monitor the deformation, stress and tilt angle of the support frame. The real-time monitoring system includes a sensor unit and a central processing unit. S5. Based on the monitoring data of the real-time monitoring system, the elevation and verticality of the support frame are dynamically adjusted by the adjustable base set at the bottom of the pole; S6. During construction, windproof cables shall be installed around the support frame and regular inspections shall be carried out.

2. The method for stability control and safe construction of the high-rise formwork support system for super-large beams and slabs as described in claim 1, characterized in that, The sensor unit includes a tilt sensor, a pressure sensor, and a displacement sensor. The tilt sensor is installed at the top and bottom of a specific upright to monitor the verticality of the upright. The pressure sensor is installed in the adjustable base at the bottom of the upright to monitor the axial pressure borne by the upright. The displacement sensor includes a laser rangefinder, which is installed on the side of the support frame, with one end fixed to the support frame and the other end fixed to a stable reference point outside the support frame, to monitor the horizontal displacement of the support frame. The data from the sensor unit is transmitted to the central processing unit in real time via a wireless transmission module.

3. The method for stability control and safe construction of the high-rise formwork support system for super-large beams and slabs as described in claim 2, characterized in that, The central processing unit calculates and sets dynamic alarm thresholds based on the monitoring data of the support frame and the current construction stage.

4. The method for stability control and safe construction of the high-rise formwork support system for super-large beams and slabs as described in claim 3, characterized in that, The process by which the central processing unit calculates and sets the dynamic alarm threshold specifically includes: The construction process is divided into multiple stages. In each stage, the central processing unit continuously records the monitoring data of the sensor unit and calculates the statistical characteristic value of the monitoring data in the current stage. The statistical characteristic value of the monitoring data includes at least the mean and standard deviation of the monitoring data. When entering the next construction phase, the central processing unit combines the statistical characteristic values ​​of the previous phase with the expected theoretical load changes in the current phase to calculate the prediction benchmark range of the monitoring data. Based on the predicted baseline range, a dynamic alarm threshold for the current stage is generated.

5. The method for stability control and safe construction of the high-rise formwork support system for super-large beams and slabs as described in claim 4, characterized in that, The expected change in theoretical load at the current stage refers to the theoretical load ratio K at the current stage. The theoretical load ratio at the current stage represents the multiple of the theoretical load at the current stage relative to the theoretical load at the previous stage. The theoretical load at the current stage refers to the design value of the load acting on the support frame at the current construction stage, including the self-weight of the poured concrete, the self-weight of the slab and beam formwork, and the self-weight of the construction personnel and equipment. The theoretical load ratios at each stage of construction are pre-stored in the central processing unit. The calculation method for the prediction benchmark range includes: Call the average value μ of the monitoring data from the previous stage n-1 and standard deviation σ n-1 ; Calculate the predicted mean value μ′ for the current stage based on the theoretical load ratio K for the current stage. n = μ n-1 * K, Predictive Standard Deviation σ′ n = σ n-1 * K; The prediction benchmark range is in μ′ n Centered on β*σ′ n The range is the floating range, and β is the safety factor.

6. The method for stability control and safe construction of the high-rise formwork support system for super-large beams and slabs as described in claim 2, characterized in that, The hydraulic tensioning device is used to symmetrically tension multiple horizontal bars, and the pressure sensor is used to monitor the distribution of preload in real time to ensure uniformity.

7. The method for stability control and safe construction of the high-rise formwork support system for super-large beams and slabs as described in claim 3, characterized in that, Each adjustable base is equipped with an actuator, which is communicatively connected to the central processing unit to receive adjustment commands and drive the adjustable base to adjust its elevation and verticality. The central processing unit is also used to analyze the monitoring data in real time. When the monitoring data exceeds the dynamic alarm threshold, it calculates the required adjustment amount and direction of the adjustable base at the bottom of each pole, and sends the adjustment command containing the adjustment amount and direction to the actuator via wireless or wired transmission.

8. The method for stability control and safe construction of the high-rise formwork support system for super-large beams and slabs as described in claim 7, characterized in that, The process by which the central processing unit calculates the required adjustment amount and direction for the adjustable base at the bottom of each pole specifically includes: Acquire tilt sensor data for a specific upright, calculate the relative tilt angle Δθ between its top and bottom, and the overall horizontal displacement D of the support frame as monitored by the displacement sensor; Based on the tilt angle Δθ and the pole height H, calculate the theoretical horizontal offset δ = H × sin(Δθ) at the top of the pole; Combining the theoretical horizontal offset δ and the overall horizontal displacement D, a weighted summation method is used to calculate the comprehensive offset assessment value E = a · δ + b · D; where a is the local deformation weight coefficient, b is the overall deformation weight coefficient, and a + b = 1; the theoretical horizontal offset δ reflects the local deformation of the upright itself, and the overall horizontal displacement D reflects the overall deformation of the support frame. The comprehensive offset assessment value is compared with the dynamic alarm threshold of the current stage. If it exceeds the threshold, the adjustment amount calculation is initiated. The adjustment amount is calculated based on the comprehensive offset assessment value. The adjustment amount L = α × (|comprehensive offset assessment value| - dynamic alarm threshold), where α is a preset adjustment coefficient and the adjustment direction is the direction that counteracts the offset shown by the comprehensive offset assessment value.

9. The method for stability control and safe construction of the high-rise formwork support system for super-large beams and slabs as described in claim 7, characterized in that, The process by which the central processing unit calculates the required adjustment amount and direction for the adjustable base at the bottom of each pole specifically includes: Acquire tilt sensor data for a specific upright, calculate the relative tilt angle Δθ between its top and bottom, and the overall horizontal displacement D of the support frame as monitored by the displacement sensor; Based on the tilt angle Δθ and the pole height H, calculate the theoretical horizontal offset δ = H × sin(Δθ) at the top of the pole; Combining the theoretical horizontal offset δ and the overall horizontal displacement D, a weighted summation method is used to calculate the comprehensive offset assessment value E = a · δ + b · D; where a is the local deformation weight coefficient, b is the overall deformation weight coefficient, and a + b = 1; the theoretical horizontal offset δ reflects the local deformation of the upright itself, and the overall horizontal displacement D reflects the overall deformation of the support frame. Mark all poles whose comprehensive offset assessment value E exceeds the dynamic alarm threshold as poles to be adjusted, forming a set of poles to be adjusted Ω; The primary optimization objective is to minimize the comprehensive offset evaluation value E of all uprights in the set of uprights to be adjusted Ω, and the secondary optimization objective is to minimize the sum of squares of the adjustment values ​​of all uprights, so as to limit the overall adjustment range. Based on the system influence matrix M, an optimal set of upright adjustment instructions that can restore the stability of the entire support frame is calculated. The optimal set of pole adjustment instructions is synchronously sent to the corresponding actuators, driving multiple adjustable bases to coordinate their actions according to the optimized scheme.

10. The method for stability control and safe construction of the high-rise formwork support system for super-large beams and slabs as described in claim 9, characterized in that, The system influence matrix M is obtained through any of the following methods: a) Finite element numerical simulation method: Before construction, a finite element model is established based on the design drawings of the support frame. By applying a unit displacement to the bottom of each upright in the model in sequence and calculating the displacement response of the top of all uprights, a complete system influence matrix M is constructed. b) System identification method: After the support frame is erected and the sensors are installed, multiple uprights are selected on site as excitation points in sequence, and their actuators are controlled to generate a small test displacement. At the same time, the response data of all sensors are recorded. Based on the ratio of the response data to the test displacement, the system influence matrix M is calculated and fitted.