Accurate hoisting construction method for dynamic-static fused steel shell pier

Abstract

The invention relates to the technical field of civil construction engineering construction, in particular to a dynamic-static fusion steel shell pier precise hoisting construction method which comprises the following steps: collecting basic parameters of a steel shell pier; establishing a statics model to determine an optimal lifting point; deploying a monitoring system linked with the crane; carrying out grading trial hoisting to collect dynamic data; fusing actual measurement and simulation data to optimize hoisting parameters; hoisting and regulating in real time according to optimized parameters; and in-place calibration and stress re-checking are completed. According to the method, continuous optimization of the hoisting process is realized through closed-loop fusion of dynamic and static mechanical data. A prediction-verification-regulation closed loop is formed by establishing a statics prediction and dynamics actual measurement fusion mechanism, the problem that a traditional hoisting theory is disjointed from reality is effectively solved, the steel shell pier hoisting process control precision and structural safety are remarkably improved, the construction risk caused by parameter mismatching is reduced, and the construction efficiency is improved. And reliable technical support is provided for precise hoisting of the large steel structure.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of civil engineering construction, and particularly relates to a dynamic-statics integrated steel shell pier precise hoisting construction method. BACKGROUND

[0002] As the core load-bearing structure of large infrastructure projects such as bridges and ocean engineering, the precision and safety of the hoisting construction of the steel shell pier directly determine the overall quality and service life of the project. The existing steel shell pier hoisting construction mostly relies on single statics simulation or empirical hoisting parameter setting, lacks dynamic consideration of the dynamic factors in the actual hoisting process, and does not form a whole-process linkage mechanism of basic data, theoretical simulation, actual measurement optimization and dynamic control, resulting in deviation between the hoisting scheme and the actual working condition, and difficulty in precisely matching the structural characteristics and stress requirements of the steel shell pier.

[0003] Because the traditional construction method does not realize the deep integration of dynamic-statics data, the initial parameters such as the hoisting point arrangement and the sling configuration determined by statics analysis cannot effectively adapt to the dynamic changes such as stress fluctuation and vibration interference in the hoisting process, which easily causes problems such as uneven stress and attitude tilt, not only affecting the installation deviation control precision of the steel shell pier, but also possibly causing structural damage, seriously threatening the construction safety and engineering quality. SUMMARY

[0004] In order to make up for the above shortcomings, the present application provides a dynamic-statics integrated steel shell pier precise hoisting construction method, aiming to improve the problems of uneven stress, attitude tilt, hoisting precision and safety caused by the lack of dynamic-statics whole-process linkage of technology and the mismatch between hoisting parameters and actual working conditions.

[0005] The present application provides the following technical scheme, a dynamic-statics integrated steel shell pier precise hoisting construction method, comprising the following steps: S1, steel shell pier basic parameter acquisition: acquiring the steel shell pier structure size data, material density data, gravity center coordinate data, design hoisting load limit value data and installation reference coordinate data by using a measuring device; S2, statics modeling analysis: inputting the basic parameters collected in step S1 into a finite element analysis system, establishing a steel shell pier statics model, and calculating the hoisting point arrangement scheme and sling configuration parameters; S3, monitoring system deployment: based on the hoisting point arrangement scheme and stress analysis results of step S2, deploying stress sensors, vibration sensors and load sensors at the corresponding positions of the steel shell pier, and establishing data connection between the sensor network and the crane control system; S4, hoisting system configuration: according to the hoisting point arrangement scheme and sling configuration parameters of step S2, selecting and debugging the hoisting system, and completing the control calibration of the sensor system and the crane; S5, trial hoisting data collection: the hoisting system configured in step S4 performs a hierarchical trial hoisting, and the monitoring system deployed in step S3 collects steel shell pier stress data, vibration data and load data to form a dynamic measured data set; S6, data fusion optimization: comparing and analyzing the dynamic measured data of step S5 with the statics analysis results of step S2, the optimized hoisting control parameters are calculated through a parameter correction algorithm; S7, precise hoisting implementation: according to the hoisting control parameters optimized in step S6, the formal hoisting is performed, and the hoisting state data is collected in real time through the monitoring system to dynamically adjust the hoisting process; S8, calibration control: the steel shell pier is hoisted to the preset position, and the installation attitude is adjusted based on the real-time monitoring data to control the installation deviation within the allowable range; S9, fixed state review: the steel shell pier is temporarily fixed, and the stress state data after fixing is collected through the monitoring system to verify the structural safety; S10, hoisting quality confirmation: the hoisting quality acceptance is completed by comprehensively considering the calibration results of step S8 and the stress review results of step S9.

[0006] By adopting the above technical scheme: through the whole-process closed-loop design of dynamic-statics fusion, the collaborative guarantee of hoisting precision, real-time control and structural safety is realized: first, the statics model is established based on the steel shell pier foundation parameters to determine the hoisting point and initial scheme of the sling, then the dynamic measured data is collected through hierarchical trial hoisting, the hoisting control parameters are optimized through deviation analysis and parameter correction algorithm, the precise linkage of theoretical simulation and actual working condition is realized, and the problems of uneven structure stress and attitude tilt caused by foundation data deviation and unreasonable hoisting parameters are effectively avoided; secondly, based on the statics analysis results, a real-time monitoring network is constructed by deploying multiple types of sensors, stress and vibration data are received in real time during hoisting and dynamically adjusted in speed and attitude, and the installation deviation is strictly controlled within the allowable range through the linkage of measuring instruments and crane control system during the positioning stage; finally, through the stress state review after temporary fixing and full-dimensional quality acceptance, a safety management closed loop of fixing, monitoring, verification and acceptance is formed, and when the requirements are not met, the installation attitude is adjusted to comprehensively guarantee the precision, stability, structural safety and construction quality reliability of the steel shell pier hoisting.

[0007] Preferably, in step S1, the measuring equipment includes a laser three-dimensional scanner, a density tester and a gravity testing platform, the laser three-dimensional scanner collects structure size data, the density tester obtains material density data, and the gravity testing platform measures gravity coordinate data, and all the basic parameters are transmitted to the finite element analysis system of step S2.

[0008] Preferably, in step S2, the static modeling analysis includes establishing multiple lifting point arrangement schemes, calculating stress distribution data and deformation data under each scheme through finite element analysis, selecting the optimal scheme to determine the lifting point position coordinates and sling parameters, and outputting them to steps S3 and S4.

[0009] Preferably, in step S3, the monitoring system deployment includes deploying stress sensors in the lifting point area, vibration sensors in the structural key points, and load sensors at the hook. All sensors are connected to the crane control system through a data transmission network, and the sensor configuration parameters are fed back to step S4.

[0010] Preferably, in step S4, the hoisting system configuration includes verifying the crane's lifting capacity according to the hoisting point layout scheme, selecting sling specifications according to the sling configuration parameters, and after completing the equipment debugging, linking and calibrating the sensor system with the crane control system, and updating the calibration data to the monitoring system.

[0011] Preferably, in step S5, the trial lifting data acquisition includes lifting the steel shell pier in stages, collecting stress stability data, vibration characteristic data, and actual load data during each stage pause, forming a dynamic measured dataset that is transmitted to step S6.

[0012] Preferably, in step S6, the data fusion optimization includes establishing a deviation analysis model between measured data and simulated data, correcting the sling tension parameters and hoisting speed parameters based on the deviation calculation results, and generating an optimized hoisting control parameter set which is then transmitted to the crane control system.

[0013] Preferably, in step S7, the precise hoisting implementation includes receiving sensor data from the monitoring system in real time, automatically adjusting the hoisting speed when the data approaches a set threshold, correcting the hoisting posture through the crane control system, and transmitting the adjusted status data to step S8 in real time.

[0014] Preferably, in step S8, the positioning calibration control includes using a measuring instrument to monitor the position data of the steel shell pier in real time, comparing it with the installation reference coordinates, controlling the installation deviation through fine-tuning operations, and finally outputting the position data to steps S9 and S10.

[0015] Preferably, in step S9, the fixed state verification includes collecting stress distribution data after temporary fixation, comparing and verifying it with the static safety threshold, and returning to S8 for readjustment when the stress state does not meet the requirements. The stress data that has passed the verification is output to step S10.

[0016] The present invention has the following beneficial effects: 1. In this invention, a closed-loop design integrating dynamics and statics is used to first collect the foundation parameters of the steel shell pier to establish a static model and determine the initial scheme. Then, dynamic measured data are collected through graded trial lifting. The lifting control parameters are optimized through deviation analysis and parameter correction algorithms to achieve precise linkage between theoretical simulation and actual working conditions. This effectively avoids the problems of uneven structural stress and tilting caused by deviations in foundation data and unreasonable lifting parameters, and significantly improves the accuracy and safety of lifting construction.

[0017] 2. In this invention, a real-time monitoring network is constructed by deploying multiple types of sensors based on the results of static analysis. During the hoisting process, data such as stress, vibration, and position are received in real time. The hoisting speed and attitude are dynamically adjusted in combination with preset thresholds. During the positioning stage, the installation deviation of the steel shell pier is strictly controlled within the allowable range through the linkage of measuring instruments and the crane control system, ensuring the accuracy and stability of the installation attitude.

[0018] 3. In this invention, the stress state is checked after temporary fixation, and the stress data of the support points and key sections are collected and compared with the static safety threshold. If the requirements are not met, the positioning posture is adjusted. Finally, the positioning calibration results and stress check results are combined to carry out full-dimensional quality acceptance, forming a safety control closed loop of fixing, monitoring, verification and acceptance, which fully ensures the structural safety and construction quality reliability of the steel shell pier after hoisting. Attached Figure Description

[0019] Figure 1 This is a flowchart of a method for precise hoisting and construction of steel shell piers that integrates dynamic and static mechanics, as proposed in this invention. Detailed Implementation

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] This invention provides a method for precise hoisting and construction of steel shell piers that integrates dynamic and static principles, such as... Figure 1 As shown, it includes the following steps: S1. Steel shell pier foundation parameter acquisition: The steel shell pier structural dimension data, material density data, center of gravity coordinate data, design hoisting load limit data and installation reference coordinate data are acquired using measuring equipment; Furthermore, the measuring equipment includes a laser 3D scanner, a density meter, and a center of gravity testing platform. The laser 3D scanner collects structural dimension data, the density meter acquires material density data, and the center of gravity testing platform measures the center of gravity coordinate data. All basic parameters are transmitted to the finite element analysis system in step S2.

[0022] Specifically, comprehensive foundation parameters of the steel shell pier are acquired using specialized measuring equipment. This provides a unified and accurate data benchmark for subsequent static modeling, dynamic monitoring, and hoisting parameter optimization, preventing the failure of dynamic-static fusion analysis due to deviations in foundation data and ensuring the accuracy and safety of hoisting construction from the outset. The measuring equipment selected in this step is based on the characteristics of the large size and strong structural integrity of the steel shell pier. Among them, the laser 3D scanner, density meter, and center of gravity testing platform form a collaborative acquisition system. The acquisition process and data purpose of each device are clearly defined and interconnected.

[0023] The laser 3D scanner is used to collect structural dimensional data of the steel shell pier. During implementation, 3-4 reference control points are first set up around the steel shell pier to ensure that the scanning coverage is complete without blind spots. For a large-diameter steel shell pier with a diameter of φ8m and a height of 12m, a measurement section is set up every 2m along the height direction. Data from 36 measuring points are collected evenly around each section. The scanner records the three-dimensional coordinates of each measuring point through the laser ranging principle. The data processing software on the device is used to fit and generate a geometric model of the steel shell pier, directly outputting key dimensional parameters such as outer diameter, wall thickness, height, and end face flatness. This data serves as the geometric basis for the S2 finite element analysis system to build a three-dimensional static model. If the dimensional data error exceeds ±0.1mm / m, it will cause the stress distribution calculation deviation after modeling to exceed 5%. Therefore, multiple scans are required to verify the data accuracy.

[0024] A density meter is used to obtain the material density data of the steel shell pier. During implementation, three standard samples (100mm × 100mm × 10mm) are cut from the steel shell pier's base material. After removing the oxide layer from the sample surface, the sample volume V is measured using the water displacement method (unit: m³). The sample mass m is measured using an electronic balance (unit: kg). The density of a single sample is calculated using the density formula ρ = m / V. The average density of the three samples is taken as the material density data ρ of the steel shell pier. For example, if the masses of the three samples are 7.85kg, 7.83kg, and 7.87kg respectively, and the volume of each sample is 1 × 10⁻³ m³, then the average density ρ = 7850kg / m³. This data will be used in S2 modeling to calculate the self-weight load G of the steel shell pier: G = ρ × V. 总 V 总 The total weight of the steel shell pier measured by the laser 3D scanner is G, and it needs to be mutually verified with the total weight G_total measured by the center of gravity test platform, with a deviation of ≤1%, so as to provide accurate load input for static analysis.

[0025] The center of gravity testing platform is used to measure the coordinate data of the center of gravity of the steel shell pier. During implementation, the steel shell pier is placed horizontally on three symmetrically arranged weighing sensors on the platform. The sensor spacing is half the diameter of the steel shell pier. First, the forces G1, G2, and G3 at the three support points are measured using the sensors (unit: N); the total weight Gtotal = G1 + G2 + G3. Then, a two-dimensional coordinate system is established with the platform center as the origin, and the coordinates of the three sensors are recorded as (x1, y1), (x2, y2), and (x3, y3) (unit: m). The horizontal coordinate of the center of gravity (x1, y1), (x2, y2), and (x3, y3) is derived based on the principle of torque balance. c ,y c The formula is as follows: x c =(G1x1+G2x2+G3x3) / G_total; y c =(G1y1+G2y2+G3y3) / G_total The steel shell pier is then rotated 90°, and the above measurement process is repeated to obtain the vertical coordinate zc of the center of gravity. Finally, the complete coordinates of the center of gravity (x) are output. c ,y c ,z c This coordinate data will be directly input into the S2 finite element analysis system to locate the center of gravity loading position of the model. It is the core basis for determining the optimal arrangement of the lifting points. If the center of gravity coordinate deviation exceeds 50mm, it will lead to uneven force distribution at the lifting points and cause the steel shell pier to tilt during the lifting process.

[0026] The design hoisting load limit data and installation reference coordinate data are extracted from the construction design documents. The design hoisting load limit needs to be determined in conjunction with the self-weight G total of the steel shell pier and the hoisting dynamic load coefficient, where the hoisting dynamic load coefficient is taken as 1.2, that is, the design hoisting load limit F limit = 1.2 × G total, which is used to set the load boundary conditions when modeling S2 and to select the hoisting equipment in S4. The installation reference coordinate data is based on the measurement control points on the construction site, which clarifies the center coordinates (x0, y0, z0) and allowable deviation values ​​of the steel shell pier after it is in place, such as horizontal deviation ≤ 2mm / m and vertical deviation ≤ 3mm / m, to provide a reference benchmark for the S8 positioning calibration.

[0027] All collected structural dimension data, material density data, center of gravity coordinate data, design hoisting load limit data, and installation reference coordinate data are integrated into a standardized basic parameter dataset through a data interface. After being formatted according to GB / T50315 Construction Engineering Surveying Specification, the dataset is transmitted in real time to the finite element analysis system in step S2 via a wireless transmission module. This ensures that the input data for subsequent static modeling is completely matched with the actual working conditions of the steel shell pier. The implementation effect of this step directly determines the reliability of the dynamic-static fusion analysis. For example, in a bridge project, the center of gravity coordinate measurement error of a φ6m steel shell pier was controlled within 30mm through the data collected in this step, providing accurate data support for subsequent hoisting point optimization and dynamic control, and ultimately controlling the hoisting positioning deviation within 80% of the design allowable value.

[0028] S2. Static Modeling and Analysis: Input the basic parameters collected in step S1 into the finite element analysis system, establish a static model of the steel shell pier, and calculate the lifting point layout scheme and sling configuration parameters. Furthermore, the static modeling analysis includes establishing multiple lifting point arrangement schemes, calculating stress distribution data and deformation data under each scheme through finite element analysis, selecting the optimal scheme to determine the lifting point position coordinates and sling parameters, and outputting the results to steps S3 and S4.

[0029] Specifically, the core objective of step S2 is to construct a static model of the steel shell pier based on the standardized basic parameter dataset of step S1 through finite element analysis, quantify the mechanical response of different lifting point arrangement schemes, select the optimal scheme, and output the lifting point coordinates and sling parameters, so as to provide accurate mechanical data support for sensor deployment in S3 and equipment debugging in S4.

[0030] First, the structural dimensions, material density ρ, and centroid coordinates (x) collected by S1 are analyzed. c ,y c ,z c The lifting load limit F, material elastic modulus E, Poisson's ratio μ, allowable stress [σ], and other parameters are directly input into the finite element analysis system to generate a three-dimensional geometric model. Detailed modeling is performed on key areas such as the lifting point region and abrupt changes in cross-section, with a geometric accuracy error ≤0.5%. In the model's material properties, density ρ is used to calculate the self-weight load G. 模 =ρ×V 模 V 模 The volume of the model is calculated, with a total deviation of V from step S1 ≤ 1%. E and μ are used as core parameters for stress and deformation calculation, and [σ] is used as the strength criterion. Subsequently, solid elements are used to generate the mesh, with a mesh size of 50 mm for the lifting points and stress-sensitive areas, and 100-150 mm for other areas, with an element distortion rate ≤ 5%. A vertically downward self-weight load G is applied based on the centroid coordinates, and a vertically upward lifting load is applied according to the F limit to complete the boundary condition setting.

[0031] Design 3-5 lifting point layout schemes, including symmetrical layouts of 2, 3, and 4 points, covering different numbers of lifting points and circumferential distribution angles to ensure comprehensive selection. The lifting point height is 1.5-2.0m from the top of the steel shell pier. Calculate the initial coordinates of the lifting points for each scheme based on the center coordinates and radius of the steel shell pier (S1). Calculate using the finite element method of elasticity through a finite element analysis system. The core equation is [K]{u}={F}, where [K] is the overall stiffness matrix, related to the S1 structural dimensions and E; {u} is the nodal displacement vector; and {F} is the load vector, including the G-mode and F-limit. Then, σ=D[B]{u} is used to derive the maximum principal stress σ. max The maximum deflection w is calculated by combining the displacement vector. max Output the stress distribution data and deformation data for each scheme.

[0032] The optimal solution was selected based on the principles of meeting strength requirements, minimizing deformation, and ensuring balanced stress: σ was eliminated. max For schemes with >[σ], select w from the remaining schemes. max The optimal solution is one where the minimum stress difference at each lifting point is ≤10%. Based on this optimal solution, the coordinates of the lifting points are determined. The initial length of the slings is calculated according to the lifting point coordinates and the preset position of the crane hook. The initial angle and initial tension distribution of the slings are set according to the stress results at the lifting points, with the tension difference between each sling ≤10%.

[0033] Finally, the coordinate data of the suspension point position is output to S3 for precise sensor deployment; the initial values ​​of the initial length, angle, and tension distribution of the sling are output to S4 as the basis for equipment adaptation and debugging. Reverse verification is performed using the basic parameters of S1. During verification, the Vtotal and Gtotal of S1 are substituted into the model to verify that the deviation between the Gmodel and Gtotal is ≤1%, and the deviation between the Vmodel and Vtotal is ≤1%, ensuring the optimal solution σ0. max ≤[σ]、w max The design allowable deflection lays the theoretical foundation for precise hoisting based on the integration of dynamic and static mechanics.

[0034] S3. Monitoring System Deployment: Based on the lifting point layout scheme and stress analysis results in step S2, stress sensors, vibration sensors and load sensors are deployed at the corresponding positions of the steel shell pier, and a sensor network is established to connect with the data of the crane control system. Furthermore, the monitoring system deployment includes deploying stress sensors in the lifting point area, vibration sensors in key structural points, and load sensors at the hook. All sensors are connected to the crane control system via a data transmission network, and sensor configuration parameters are fed back to step S4.

[0035] Specifically, based on the lifting point coordinates and stress-sensitive area data output by S2, multiple types of sensors are precisely deployed and a real-time data link is established with the crane control system. This provides stable data transmission support for subsequent trial lifting data acquisition and dynamic control. At the same time, the sensor configuration parameters are fed back to S4 to ensure the linkage and adaptation between the lifting equipment and the monitoring system.

[0036] First, based on the coordinates of the lifting points determined in S2, 4-6 strain gauge stress sensors are evenly deployed circumferentially in a section 50-100mm below each lifting point. The deployment positions avoid the weld seam area, ensuring that the sensor's contact with the steel shell pier surface is ≥95%. The sensor range is set to 1.5 times the maximum stress value of the lifting point calculated in S2, with a resolution ≤1με, for real-time acquisition of stress data in the lifting point area. Combining the stress distribution and deformation data in S2, one triaxial vibration sensor is deployed at each of the key structural points such as the top, middle, and bottom center of the steel shell pier. The range is ±5g, and the frequency response range is 0.1-1000Hz, to accurately capture vibration acceleration data during the lifting process.

[0037] A high-precision load sensor is fixed at the crane hook. The sensor's accuracy class is no less than 0.1, and its range is twice the design lifting load limit F of S1. It directly collects actual lifting load data to ensure load monitoring covers the entire lifting process. All sensor configuration parameters, including range, resolution, deployment location coordinates, signal output method, signal sampling rate, and data transmission protocol type, are integrated into a unified sensor configuration dataset and fed back to S4 in real time as the basis for the linkage calibration between the lifting equipment and the sensors.

[0038] Subsequently, a wireless data transmission network was established using industrial-grade LoRa transmission modules. This network established bidirectional data connections between all sensors and the crane control system, setting the data acquisition frequency to 200Hz and the transmission latency to ≤100ms. Data encryption and fault tolerance mechanisms were also configured to ensure data transmission stability. After network construction, connectivity tests were conducted to verify that real-time data from stress sensors, vibration sensors, and load sensors could be synchronously transmitted to the crane control system, and that control system commands could be fed back to the sensor acquisition modules via the network, forming a real-time data link for acquisition, transmission, and reception.

[0039] After final deployment, output the sensor deployment location details, data transmission network parameters, and linkage status confirmation results. The confirmation results must include verification records showing a sensor communication success rate of ≥99.9% and a measured data transmission delay of ≤100ms. The sensor deployment location details are used for data analysis and positioning during S7 dynamic control. The data transmission network parameters ensure real-time data interaction during subsequent hoisting. The linkage status confirmation results provide the prerequisites for S4 equipment adaptation and debugging, ensuring that the monitoring system and the crane control system form a closed-loop response.

[0040] S4. Lifting System Configuration: Based on the lifting point layout plan and sling configuration parameters in step S2, select and configure crane equipment and debug the lifting system, and complete the control calibration of the sensor system and the crane. Furthermore, the hoisting system configuration includes verifying the crane's lifting capacity according to the hoisting point layout plan, selecting sling specifications according to the sling configuration parameters, and after completing the equipment debugging, linking and calibrating the sensor system with the crane control system, and updating the calibration data to the monitoring system.

[0041] Specifically, based on the lifting point layout scheme of S2, the sling configuration parameters, and the sensor configuration dataset of S3, the selection of lifting equipment, system debugging and linkage calibration are completed, and a collaborative control mechanism between the monitoring system and the crane is established to provide equipment and control guarantees for subsequent precise lifting. The calibration data is updated back to the monitoring system to form a closed loop.

[0042] First, based on the lifting point layout scheme of S2 and the design lifting load limit F limit of S1, verify and select the crane equipment: the rated load of the crane must be no less than 1.5 times the F limit, and the lifting height and working radius must cover the space requirements of the lifting point layout. Based on the lifting point height of S2 and the construction site layout, the crane's luffing and slewing accuracy is checked. The luffing accuracy is ≤5mm / ° and the slewing accuracy is ≤3mm / ° to ensure that the requirements for precise control of the lifting posture are met.

[0043] Based on the sling configuration parameters of S2, including initial length, initial angle, and initial tension distribution, select the corresponding slings and lifting devices: High-strength steel wire ropes are selected for the slings, with the diameter determined by calculating the initial maximum tension value of the slings in S2, based on the GB / T8918-2018 national standard for steel wire ropes, combined with a safety factor ≥5. The sling length is selected with an initial length deviation of ≤50mm from S2. The lifting device angle adjustment range must match the initial angle of S2, with an allowable adjustment error ≤1°. Matching lifting lugs suitable for the lifting points are selected, with a bearing capacity not less than twice the initial tension value of a single lifting point, ensuring a reliable connection between the slings and the steel shell pier lifting points.

[0044] After completing the equipment selection, the hoisting system is debugged: Start the crane, adjust the boom posture according to the lifting point position coordinates of S2, and precisely connect the slings and lifting lugs. Fine-tune the sling length and the angle between the lifting device and the lifting device through the crane control system so that the tension of each sling initially matches the initial value of the tension distribution of S2, where the tension deviation is ≤10%; at the same time, test the smoothness of the crane's lifting, luffing, and slewing movements, and set an initial threshold of 0.3-0.8m / min for the lifting speed to ensure that the equipment operates without abnormal vibration.

[0045] Subsequently, based on the sensor configuration dataset of S3, including range, signal output mode, and deployment location, the linkage calibration between the sensor system and the crane control system was carried out: real-time data from load sensors, stress sensors, and vibration sensors were connected to the crane control system, and a calibration benchmark was set. Using the initial tension distribution value of S2 as the standard, the crane load control module was adjusted so that the response error between the measured value of the load sensor and the set value of the control system was ≤ ±0.5%; using the maximum stress value of the lifting point of S2 as a reference, the linkage logic between the stress sensor data and the crane lifting speed was calibrated; using 0.5g as the vibration safety threshold as a benchmark, the trigger response of the vibration sensor data and the crane pause / adjustment command was calibrated.

[0046] After calibration, the calibration data, including response error values, trigger threshold parameters, and control logic parameters, will be promptly updated to the monitoring system of S3. Simultaneously, the matching parameters for sensor data acquisition and control system command feedback will be updated to ensure a closed-loop response between the monitoring data and the crane control actions. Finally, a hoisting system configuration confirmation result will be output, including equipment model, sling specifications, and calibration error report. This configuration confirmation result provides the basis for equipment operation during the S5 trial hoisting, while the calibration error report serves as a reference for error correction during subsequent S6 data fusion optimization. The report clearly defines the linkage error values ​​of each sensor and control system, providing error compensation data for S6 deviation analysis and ensuring reliable collaboration between the hoisting system and the monitoring system.

[0047] S5. Trial Lifting Data Acquisition: Perform graded trial lifting using the lifting system configured in step S4, and collect stress data, vibration data, and load data of the steel shell pier using the monitoring system deployed in step S3 to form a dynamic measured dataset. Furthermore, the data acquisition for the trial lifting includes lifting the steel shell pier in stages, collecting stress stability data, vibration characteristic data, and actual load data during each stage pause, forming a dynamic measured dataset that is transmitted to step S6.

[0048] Specifically, based on the hoisting system configured in S4 and the monitoring system deployed in S3, the dynamic response of the steel shell pier is triggered by graded trial hoisting, and multi-dimensional measured data is accurately collected to form a dynamic measured dataset, providing direct input basis for the dynamic-static data fusion optimization in S6.

[0049] First, the S4 hoisting system, after configuration, is started, and a trial hoisting is performed according to the process of graded lifting, phased pauses, and data acquisition: In the initial stage, the steel shell pier is lifted to a height of 0.5m at a speed of ≤0.3m / min, paused for 2 minutes, and after the stress and vibration state of the structure stabilizes, stress stability data of the lifting point area is collected through the stress sensor of S3, structural vibration characteristic data is collected through the vibration sensor, and actual load data of the initial stage is collected through the load sensor; then, the lifting continues at the same speed to a height of 1m, and the pause and data acquisition process is repeated, focusing on collecting dynamic transition data when the load of the slings changes; finally, the pier is lifted to a preset height of 1.5-2m, paused for 3 minutes, and stress stability value, vibration attenuation data, and full-range actual load data of the structure in a static state are collected.

[0050] Throughout the trial lifting process, the monitoring system synchronously recorded data at the 200Hz acquisition frequency set in S3. Stress data was accurate to 1με, vibration data retained the three-dimensional acceleration components along the x / y / z axes, and load data was accurate to 0.1kN. All acquired data were categorized and labeled according to lifting stage, acquisition time, data type, and numerical format. For each pause point in the lifting stage, data stability needed to be confirmed, specifically, stress fluctuation ≤5% and vibration acceleration ≤0.1g within 10 consecutive seconds, ensuring that stable data accounted for ≥90% to avoid data distortion caused by dynamic interference.

[0051] After data acquisition, all stress stability data, vibration characteristic data, and actual load data are integrated into a standardized dynamic measured dataset via the S3 wireless data transmission network and synchronously transmitted to the S6 data analysis module. A trial lifting data acquisition report is also output, specifying the completeness of data acquisition at each stage (≥95% completeness, ≤5% invalid data), and whether the data accuracy meets the S3 sensor configuration requirements. The report also includes analysis of data anomalies such as vibration interference and temporary sensor inaccuracies, providing a reference for S6 data preprocessing. This report provides a basis for judging data reliability for S6 data fusion optimization, ensuring that subsequent parameter corrections are based on real and valid dynamic measured data, achieving direct data linkage between trial lifting data and fusion optimization.

[0052] S6. Data Fusion and Optimization: The dynamic measured data from step S5 is compared and analyzed with the static analysis results from step S2. The optimized hoisting control parameters are calculated using a parameter correction algorithm. Furthermore, the data fusion optimization includes establishing a deviation analysis model between measured data and simulated data, correcting the sling tension parameters and hoisting speed parameters based on the deviation calculation results, and generating an optimized hoisting control parameter set which is then transmitted to the crane control system.

[0053] Specifically, based on the dynamic measured dataset output by S5 and the static analysis results of S2, the dynamic-static data are deeply integrated through deviation modeling and parameter correction algorithms to generate an optimized set of hoisting control parameters. This provides the core control basis for the dynamic regulation of precise hoisting in S7 and forms a data closed loop of simulation-measurement-correction.

[0054] First, data preprocessing is performed: the dynamic measured dataset of S5 is extracted and classified into lifting point stress data, lifting load data, and vibration characteristic data. It is then compared with the corresponding dimension data in the static analysis results of S2, including the simulated lifting point stress value σ modulus, the simulated lifting load value F modulus, and the simulated deformation-related vibration reference value. The data is matched one by one according to the nodes with the same working conditions, including lifting height and static state. Invalid outliers in the measured data are removed, that is, data that deviate from the mean by three times the standard deviation. Before removal, outlier judgment is performed by the Laida criterion to ensure that the removal logic is rigorous and to ensure the consistency and reliability of the comparison data.

[0055] A deviation analysis model is established, employing a linear deviation model. The least squares method is used to fit the deviation trend between measured and simulated values, improving the accuracy of deviation calculation and quantifying the degree of deviation between measured and simulated data. The core calculation utilizes the relative deviation formula. Where δ represents the percentage relative deviation of data in a certain dimension, Xactual represents the measured dynamic value of S5, including the measured value of lifting point stress σactual and the measured value of lifting load Factual, and Xmodel represents the static simulation value of S2, corresponding to σmodel and Fmodel. This formula is based on the logic of using simulation values ​​as the benchmark and measured values ​​as the basis for correction, directly reflecting the difference between the theoretical model and the actual working conditions. The relative deviation of lifting point stress δσ and the relative deviation of lifting load δF are calculated separately, and a deviation judgment threshold is set: δ not exceeding 5% is considered acceptable, and δ exceeding 5% is considered an excessive deviation requiring significant correction.

[0056] Based on the deviation analysis results, a parameter correction algorithm is initiated to correct the hoisting control parameters in multiple dimensions: The tension parameter correction is based on the initial tension distribution value Tinitial of S2, and the tension correction coefficient kT is calculated by combining the relative stress deviation δσ at each suspension point. The formula is as follows: kT=1-δσ×k 安全 Where k 安全 A safety correction factor, set to 0.8, is used to prevent over-correction that could lead to excessive stress. The corrected sling tension value T 优 =T 初 ×kT. If the δσ of a certain suspension point exceeds 5%, an additional stress equalization correction term is added: T 优 =T 优 ×(σ 模 / σ实 This ensures that the stress deviation at each lifting point does not exceed 3%, and finally outputs the optimized cable tension distribution matrix, which includes the specific tension value for each lifting point; Lifting speed parameter correction: Combining the vibration characteristic data of S5, i.e., the peak vibration acceleration aactual, with the vibration reference value amodulo of S2, calculate the vibration deviation δa = |am| 实 -a 模 | / a 模 ×100%, if δa exceeds 10%, then the hoisting speed is corrected according to the ratio of a_actual to the safe vibration threshold of 0.5g: V 优 =V 初 ×(0.5g / a 实 ), where V_initial is the initial threshold of the lifting speed set by S4, specifically ranging from 0.3 to 0.8 m / min. After correction, it ensures that a_actual does not exceed 0.4g during the hoisting process, balancing hoisting efficiency and structural stability.

[0057] After the corrections are completed, the optimized sling tension distribution matrix, lifting speed threshold, and attitude correction trigger threshold are integrated. The attitude correction trigger threshold is determined by combining the S2 static safety threshold and the extreme values ​​of the S5 measured data to ensure its rationality. Based on a stress deviation of 3% and a vibration acceleration of 0.4g, a standardized lifting control parameter set is formed, which is transmitted in real time to the crane control system via a data transmission network as the core command for S7 precise lifting dynamic control. Simultaneously, parameter correction coefficients, including kT and V, are... 优 / V 初 The deviation analysis results are fed back to the static model of S2 to update the simulation parameters and improve the accuracy of subsequent analyses, forming a data closed loop. The final output is a data fusion and optimization report, which clarifies the basis for the correction of each parameter, the comparison values ​​before and after optimization, and the results of the determination of the effectiveness of the control parameters. The deviation is considered qualified if it does not exceed 3%, ensuring that the optimized control parameters not only conform to the actual working conditions but also meet the structural safety requirements.

[0058] S7. Precise hoisting implementation: Perform formal hoisting according to the hoisting control parameters optimized in step S6, and collect hoisting status data in real time through the monitoring system to dynamically adjust the hoisting process; Furthermore, the precise hoisting implementation includes receiving sensor data from the monitoring system in real time, automatically adjusting the hoisting speed when the data approaches a set threshold, correcting the hoisting posture through the crane control system, and transmitting the adjusted status data to step S8 in real time.

[0059] Specifically, based on the optimized hoisting control parameters output in step S6 and the monitoring system deployed in step S3, the formal hoisting is executed and dynamic closed-loop control is achieved to ensure that the steel shell pier is accurately positioned according to the preset trajectory, while providing real-time and continuous hoisting status data support for the positioning calibration in step S8.

[0060] First, the crane control system is activated, and the optimized lifting control parameters from step S6 are invoked, including the sling tension distribution matrix, lifting speed threshold, and attitude correction trigger threshold. The formal lifting operation then begins according to the preset lifting path. In the initial stage, the steel shell pier is smoothly lifted at the optimized lifting speed threshold. Simultaneously, the boom attitude is adjusted through the crane control system to ensure that the initial lifting attitude of the steel shell pier is consistent with the lifting point layout scheme in step S2 and the installation reference coordinates in step S1, thus ensuring that the sling tension is evenly distributed and meets the optimized parameter requirements during the lifting process.

[0061] Throughout the hoisting process, the monitoring system in step S3 collects hoisting status data in real time at a frequency of 200Hz, including stress data in the hoisting point area, structural vibration acceleration data, actual hoisting load data, and real-time attitude data of the steel shell pier. The real-time attitude data of the steel shell pier is calculated by combining the three-dimensional coordinate data collected by the sensors with the Euler angle transformation algorithm, and is synchronously transmitted to the crane control system through a wireless transmission network, forming a real-time response link of acquisition, transmission, analysis, and adjustment.

[0062] The crane control system receives and analyzes monitoring data in real time, continuously comparing it with the thresholds set in S6: when the monitored stress data at the lifting point approaches the value corresponding to the stress deviation of 3% in the attitude correction trigger threshold, the system automatically reduces the lifting speed by 10% to 20% while maintaining stable sling tension; when the vibration acceleration data approaches the 0.4g in the attitude correction trigger threshold, the system pauses the lifting action, fine-tunes the tension of each sling based on the sling tension distribution matrix optimized in S6, and resumes lifting after the vibration acceleration decays to below 0.1g; when the real-time attitude data deviates from the initial attitude corresponding to the installation reference coordinates in step S1, the lifting attitude is corrected in coordination through the crane's luffing and slewing actions. The correction range is determined according to the ratio of the real-time attitude deviation to the allowable deviation value in working S1, ensuring that the attitude deviation gradually decreases.

[0063] After all dynamic adjustment actions are executed, the crane control system records the adjusted lifting status data in real time, including the adjusted speed, tension, attitude parameters and corresponding monitoring data. This data is then synchronously transmitted to step S8 via the data transmission network, providing a dynamic adjustment basis for subsequent positioning calibration. At the same time, the adjustment records are fed back to the monitoring system in step S3, updating the key monitoring areas for data acquisition. This ensures accurate capture of possible stress and vibration changes after adjustment, forming a dynamic control closed loop for the lifting process. The control closed loop response time is ≤500ms, ensuring the timeliness of the adjustment actions.

[0064] Throughout the entire precision hoisting process, the hoisting action was kept continuous and stable to avoid sudden starts and stops that could cause abrupt changes in structural stress. All adjustments were automatically executed based on the comparison results of measured data and preset thresholds to ensure the accuracy and timeliness of the control. Ultimately, the steel shell pier was smoothly hoisted above the preset installation area, laying the foundation for the positioning calibration in step S8.

[0065] S8. Positioning and calibration control: The steel shell pier is hoisted to the preset position, and the installation posture is adjusted based on real-time monitoring data to control the installation deviation within the allowable range; Furthermore, the positioning calibration control includes using measuring instruments to monitor the position data of the steel shell pier in real time, comparing it with the installation reference coordinates, controlling the installation deviation through fine-tuning operations, and finally outputting the position data to steps S9 and S10.

[0066] Specifically, based on the adjusted hoisting status data transmitted by S7, the installation reference coordinates and allowable deviation values ​​of S1, the steel shell pier is accurately positioned through real-time measurement and dynamic fine-tuning, and the installation deviation is controlled within the design requirements. At the same time, the final position data is output to provide core basis for temporary fixing by S9 and quality acceptance by S10.

[0067] First, the steel shell pier is lifted to 500mm above the preset installation area using the precise lifting action of S7. The crane control system calls the real-time attitude data transmitted by S7 to initially adjust the attitude of the boom so that the center of the steel shell pier is roughly aligned with the installation reference coordinates set by S1, and maintains the stability of the lifting state to create conditions for subsequent calibration.

[0068] A laser plumb line and an electronic level are deployed as the core measuring instruments. The laser plumb line is set up at the measurement control point on the construction site to monitor the verticality data of the steel shell pier in real time. The accuracy level of the laser plumb line is no less than level 2, and the measurement error is ≤0.5mm / m. The electronic level is installed on the top end face of the steel shell pier to collect levelness data in real time. The accuracy of the electronic level is ≤0.01mm / m. At the same time, the center coordinate data of the steel shell pier is collected through a laser rangefinder. All measuring instruments work synchronously at a collection frequency of 100Hz. The measurement data is transmitted to the crane control system in real time through the data transmission network, forming a data complementarity with the S3 monitoring system.

[0069] The crane control system will compare the real-time verticality data, horizontality data, and center coordinate data with the installation reference coordinates and allowable deviation values ​​of S1 one by one, and calculate the deviation values ​​of each: the verticality deviation is determined by the vertical offset between the top and bottom centers of the steel shell pier; the horizontality deviation is calculated by the elevation difference between different measuring points on the top end face; the center coordinate deviation is obtained by the difference between the measured center coordinates and the installation reference coordinates; the measured center coordinates are obtained by calculating the mean value of the three-dimensional coordinate data collected by the laser rangefinder, and the sampling number is ≥10 times to ensure coordinate accuracy.

[0070] Based on the calculated deviation values, dynamic fine-tuning operations are initiated: if the verticality deviation exceeds 3mm / m, it is corrected through the coordinated adjustment of the crane's slewing action and sling tension, with each adjustment controlled at 30% of the deviation value; if the horizontal deviation exceeds 2mm / m, the height difference of the steel shell pier is fine-tuned through the crane's lifting action to gradually eliminate the end face tilt; if the center coordinate deviation exceeds the design allowable range, the horizontal position of the steel shell pier is precisely adjusted through the crane's luffing action. After each fine-tuning operation is completed, the measuring instrument immediately re-collects position data and transmits it to the control system, comparing it again with the installation reference coordinates until all deviations meet the design requirements.

[0071] During the calibration process, the measuring instruments and the crane control system are linked in real time. All fine-tuning actions are executed precisely based on the measured deviation data to avoid blind adjustments that could lead to increased deviations. When the verticality deviation does not exceed 3 mm / m, the horizontality deviation does not exceed 2 mm / m, and the center coordinate deviation does not exceed the design allowable range, the steel shell pier is confirmed to be in place and calibrated successfully. The crane control system then locks the current lifting posture to maintain the stability of the steel shell pier.

[0072] Finally, the verticality, horizontality, and center coordinate data of the calibrated steel shell pier are integrated into a standardized final position dataset via a data transmission network. This dataset is output in a format consistent with the S1 installation reference coordinates to avoid coordinate system deviations and is simultaneously output to S9 and S10. This dataset provides a basis for the placement of support points for the temporary fixing of S9, ensuring that the support structure accurately matches the actual positioning posture of the steel shell pier. Simultaneously, it serves as a core criterion for quality acceptance in S10, ensuring that the acceptance results are consistent with the actual installation state, forming a data closed loop between positioning calibration and subsequent processes.

[0073] S9. Fixed State Verification: Temporary fixation is implemented on the in-place steel shell pier, and stress state data after fixation is collected through the monitoring system to verify the structural safety; Furthermore, the fixed state verification includes collecting stress distribution data after temporary fixation, comparing and verifying it with the static safety threshold, and returning to S8 for readjustment when the stress state does not meet the requirements. The stress data that passes the verification is output to step S10.

[0074] Specifically, based on the final location dataset output by S8, the static safety threshold of S2, and the monitoring system of S3, the temporary fixing and stress state verification of the steel shell pier are completed, the safety of the structure after fixing is verified, a closed-loop control of fixing, monitoring, and verification is formed, and core stress state data are provided for the quality acceptance of S10.

[0075] First, based on the final location dataset of S8, including the final verticality, horizontality, and center coordinates of the steel shell pier, a temporary fixed support point layout scheme was determined. Hydraulic supports were uniformly arranged along the circumference of the steel shell pier, with a spacing of no more than 2 meters between supports. The support points were precisely aligned with the stress optimization area on the outer wall of the steel shell pier. The stress optimization area is the region where the stress is ≤ 60% of the allowable stress in the S2 static analysis, ensuring the safety of the support points. This area was determined based on the static stress distribution data of S2, ensuring that the support force can effectively distribute the structural load. The initial support force of the supports was set according to the static analysis results of S2. The initial support force was calculated using linear interpolation based on the stress distribution data of S2, ensuring that the support force matched the structural stress. The hydraulic control system was activated to gradually apply the support force, maintaining a uniform loading rate during the application process to avoid stress fluctuations in the steel shell pier caused by sudden changes in support force.

[0076] After temporary fixation is completed, the stress sensor system deployed in S3 is activated to continuously collect stress distribution data of the steel shell pier at a sampling frequency of 200Hz. The system focuses on collecting stress values ​​in the lifting point area, the support point contact area, and the central stress-bearing section. Simultaneously, structural vibration acceleration data is collected to assist in determining stability. All collected stress distribution data is transmitted in real time to the crane control system via a wireless transmission network and integrated with the data from the S3 monitoring system to form a post-fixation stress state dataset.

[0077] The crane control system compares the stress values ​​at each measuring point in the fixed stress state dataset with the static safety threshold set in S2. The static safety threshold is 80% of the allowable stress of the steel shell pier material. If the stress value at a measuring point exceeds the static safety threshold, and the exceedance is within 10%, the support force is adjusted first; if it exceeds 10% or more, the system returns to S8 to adjust the positioning posture. Alternatively, if the stress difference between measuring points exceeds 10%, the stress state is determined to be unsafe, and the support force adjustment procedure is immediately initiated. Simultaneously, an adjustment command is sent to the positioning calibration module in S8 via the data transmission network. The system then returns to S8 to readjust the positioning posture of the steel shell pier. After adjustment, the temporary fixing and stress acquisition process is executed again until the stress state meets the requirements.

[0078] If the stress values ​​at all measuring points do not exceed the static safety threshold, and the stress distribution at each measuring point is uniform with a stress difference not exceeding 10%, the fixed state verification is deemed passed. The crane control system locks the support force of the hydraulic support components to maintain the stability of the temporary fixed structure. Simultaneously, it integrates the verified stress distribution data, support force parameters, and stability judgment results into a fixed state verification dataset, which is then output to S10 in real time via a data transmission network. This dataset provides the core basis for determining the structural fixed safety for S10 quality acceptance, ensuring that the acceptance results comprehensively reflect the actual mechanical state of the steel shell pier after fixation, forming a data closed loop between the fixed state verification and quality acceptance.

[0079] S10. Confirmation of hoisting quality: Based on the results of the positioning calibration in step S8 and the stress verification in step S9, the hoisting quality is accepted.

[0080] Specifically, by combining the positioning calibration results of S8 with the stress verification results of S9, a comprehensive quality assessment of the hoisting is completed according to the preset acceptance standards, forming a standardized quality acceptance report. This provides a legal basis for subsequent permanent fixing and project handover, while simultaneously closing the loop of the entire dynamic-static integrated hoisting construction process.

[0081] First, the quality acceptance system is activated. The final position dataset output by S8 and the fixed state verification dataset output by S9 are retrieved synchronously through the data transmission network. The two types of data are classified and integrated according to three dimensions: positioning accuracy, stress safety, and fixation reliability, to form a complete hoisting quality verification dataset, ensuring that the acceptance data fully covers the installation posture and structural mechanical state.

[0082] Conduct positioning accuracy acceptance: Extract the verticality data, horizontality data, and center coordinate data from the final position dataset and compare them with the allowable deviation values ​​set in S1. If the verticality deviation does not exceed 3mm / m, the horizontality deviation does not exceed 2mm / m, and the center coordinate deviation does not exceed the design allowable range, the positioning accuracy is deemed qualified. If any deviation exceeds the allowable range, immediately initiate the rework process, return to S8 to re-execute the positioning calibration, and resubmit the data for acceptance after calibration until the positioning accuracy meets the standard.

[0083] Conduct structural stress safety acceptance: Extract stress distribution data, stress difference, and support force parameters from each measuring point in the fixed state verification dataset, and compare them with the static safety threshold and stress equalization requirements set in S2. If the stress values ​​at all measuring points do not exceed the static safety threshold and the stress distribution is uniform, the stress safety is deemed qualified; if there are cases of excessive stress or uneven distribution, return to S9 to adjust the temporary fixed support force or return to S8 to fine-tune the positioning posture, and re-complete the fixation and stress verification before conducting the acceptance again.

[0084] Conduct temporary fixation reliability acceptance: Verify the stability of the support force parameters in the S9 fixation status verification dataset, the requirement that the support force stability fluctuation is ≤5% for 30 seconds, the compliance of the support structure layout, and the structural vibration acceleration data. If all three indicators meet the requirements, the temporary fixation reliability is deemed qualified. If there are excessive fluctuations in support force, non-compliant layout, or excessive vibration, the temporary fixation structure must be rectified, and the fixation status verification must be carried out again. After rectification, stress distribution data must be re-collected to ensure that the stress state meets the requirements before submitting for acceptance, until acceptance is passed.

[0085] After all three dimensions of acceptance are passed, the hoisting quality is comprehensively judged to meet the standards. The quality acceptance system automatically generates a standardized hoisting quality acceptance report, which includes positioning accuracy test data and judgment results, stress safety verification data and judgment results, temporary fixation reliability verification records, and comprehensive quality assessment conclusions. The final position dataset of S8 and the fixation status verification dataset of S9 are attached as appendices.

[0086] The hoisting quality acceptance report is simultaneously archived in the project management system and transmitted to the subsequent permanent fixing construction process. This provides accurate data support for the optimization of the permanent fixing scheme and the adjustment of the construction process, ensuring seamless connection between the permanent fixing construction and the hoisting quality status, and ultimately completing the entire closed loop of the precise hoisting construction of the dynamic-static integrated steel shell pier.

[0087] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for precise hoisting and construction of steel shell piers integrating dynamic and static mechanics, characterized in that, Includes the following steps: S1. Steel shell pier foundation parameter acquisition: The steel shell pier structural dimension data, material density data, center of gravity coordinate data, design hoisting load limit data and installation reference coordinate data are acquired using measuring equipment; S2. Static Modeling and Analysis: Input the basic parameters collected in step S1 into the finite element analysis system, establish a static model of the steel shell pier, and calculate the lifting point layout scheme and sling configuration parameters. S3. Monitoring System Deployment: Based on the lifting point layout scheme and stress analysis results in step S2, stress sensors, vibration sensors and load sensors are deployed at the corresponding positions of the steel shell pier, and a sensor network is established to connect with the data of the crane control system. S4. Lifting System Configuration: Based on the lifting point layout plan and sling configuration parameters in step S2, select and configure crane equipment and debug the lifting system, and complete the control calibration of the sensor system and the crane. S5. Trial Lifting Data Acquisition: Perform graded trial lifting using the lifting system configured in step S4, and collect stress data, vibration data, and load data of the steel shell pier using the monitoring system deployed in step S3 to form a dynamic measured dataset. S6. Data Fusion and Optimization: The dynamic measured data from step S5 is compared and analyzed with the static analysis results from step S2. The optimized hoisting control parameters are calculated using a parameter correction algorithm. S7. Precise hoisting implementation: Perform formal hoisting according to the hoisting control parameters optimized in step S6, and collect hoisting status data in real time through the monitoring system to dynamically adjust the hoisting process; S8. Positioning and calibration control: The steel shell pier is hoisted to the preset position, and the installation posture is adjusted based on real-time monitoring data to control the installation deviation within the allowable range; S9. Fixed State Verification: Temporary fixation is implemented on the in-place steel shell pier, and stress state data after fixation is collected through the monitoring system to verify the structural safety; S10. Lifting quality confirmation: Based on the placement calibration results of step S8 and the stress verification results of step S9, the lifting quality acceptance is completed.

2. The method for precise hoisting and construction of steel shell piers integrating dynamic and static mechanics as described in claim 1, characterized in that, In step S1, the measuring equipment includes a laser 3D scanner, a density meter, and a center of gravity testing platform. The laser 3D scanner collects structural dimension data, the density meter acquires material density data, and the center of gravity testing platform measures the center of gravity coordinate data. All basic parameters are transmitted to the finite element analysis system in step S2.

3. The method for precise hoisting and construction of steel shell piers integrating dynamic and static mechanics as described in claim 1, characterized in that, In step S2, the static modeling analysis includes establishing multiple lifting point arrangement schemes, calculating stress distribution data and deformation data under each scheme through finite element analysis, selecting the optimal scheme to determine the lifting point position coordinates and sling parameters, and outputting them to steps S3 and S4.

4. The method for precise hoisting and construction of steel shell piers integrating dynamic and static mechanics according to claim 1, characterized in that, In step S3, the deployment of the monitoring system includes deploying stress sensors in the lifting point area, vibration sensors in key structural points, and load sensors at the hook. All sensors are connected to the crane control system through a data transmission network, and the sensor configuration parameters are fed back to step S4.

5. The method for precise hoisting and construction of steel shell piers integrating dynamic and static mechanics according to claim 1, characterized in that, In step S4, the hoisting system configuration includes verifying the crane's lifting capacity according to the hoisting point layout plan, selecting sling specifications according to the sling configuration parameters, and after completing the equipment debugging, linking and calibrating the sensor system with the crane control system, and updating the calibration data to the monitoring system.

6. The method for precise hoisting and construction of steel shell piers integrating dynamic and static mechanics according to claim 1, characterized in that, In step S5, the data acquisition for the trial lifting includes lifting the steel shell pier in stages, collecting stress stability data, vibration characteristic data, and actual load data during each stage pause, forming a dynamic measured dataset that is then transmitted to step S6.

7. The method for precise hoisting and construction of steel shell piers integrating dynamic and static mechanics according to claim 1, characterized in that, In step S6, the data fusion optimization includes establishing a deviation analysis model between measured data and simulated data, correcting the sling tension parameters and hoisting speed parameters based on the deviation calculation results, and generating an optimized hoisting control parameter set which is then transmitted to the crane control system.

8. The method for precise hoisting and construction of steel shell piers integrating dynamic and static mechanics according to claim 1, characterized in that, In step S7, the precise hoisting implementation includes receiving sensor data from the monitoring system in real time, automatically adjusting the hoisting speed when the data approaches a set threshold, correcting the hoisting posture through the crane control system, and transmitting the adjusted status data to step S8 in real time.

9. The method for precise hoisting and construction of a steel shell pier integrating dynamic and static mechanics according to claim 1, characterized in that, In step S8, the positioning calibration control includes using measuring instruments to monitor the position data of the steel shell pier in real time, comparing it with the installation reference coordinates, controlling the installation deviation through fine-tuning operations, and finally outputting the position data to steps S9 and S10.

10. The method for precise hoisting and construction of a steel shell pier integrating dynamic and static mechanics according to claim 1, characterized in that, In step S9, the fixed state verification includes collecting stress distribution data after temporary fixation, comparing and verifying it with the static safety threshold, and returning to S8 for readjustment when the stress state does not meet the requirements. The stress data that passes the verification is output to step S10.

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