Suspension bridge steel box girder hoisting method and system

Abstract

According to the suspension bridge steel box girder hoisting method and system, synchronous collection of elevation data and internal force data of multiple hoisting points is achieved by arranging the monitoring module, and full-process intelligent control is formed by combining the steps of filtering fusion, hierarchical decision making and automatic deviation correction. According to the method, the spatial pose change and the stress state of the steel box girder in the hoisting process can be comprehensively captured, and the hoisting precision and safety are improved; by collecting and processing data in real time, the system can quickly respond to external interference (such as wind load or construction load fluctuation), dynamically maintain the balance of a hoisting point and reduce the risk caused by manual intervention lag; the introduction of a preset reference value provides a reliable reference for data comparison, and the judgment accuracy is ensured; and an automatic alarm and adjustment mechanism realizes closed-loop management, ensures the continuous and stable hoisting process, and solves the technical problems of low safety, poor positioning precision and difficulty in meeting the high-standard construction requirement of the large-tonnage steel box girder caused by difficulty in synchronization and coordination of multiple hoisting points in the hoisting process in the prior art.

Description

Technical Field

[0001] This invention belongs to the field of suspension bridge construction technology, specifically relating to a method and system for hoisting steel box girders for suspension bridges. Background Technology

[0002] A suspension bridge is a large-span bridge structure that uses the main cable as the primary load-bearing component, transferring the load of the bridge deck system to the main cable and towers via suspenders. It is characterized by its large span capacity, lightweight structure, and beautiful design, and is widely used in major projects spanning rivers and straits. Steel box girders, a commonly used bridge deck structure in suspension bridges, are constructed from fully welded steel plates forming a closed box section. They offer advantages such as light weight, high torsional stiffness, and good aerodynamic performance, making them a core component ensuring the overall stability of the bridge and the comfort of drivers. During suspension bridge construction, the steel box girder hoisting process refers to the process of lifting prefabricated steel box girder segments, transported to the bridge site in sections, using specialized lifting equipment to the design elevation and connecting them to the suspenders, ultimately assembling them segment by segment to form the overall bridge deck.

[0003] Currently, the hoisting of steel box girders for long-span suspension bridges is mainly carried out using cable-mounted cranes. Among them, the "double-span cable crane with multiple lifting points" synchronous hoisting process is a common method for installing long segments and heavy-duty steel box girders. This method uses two cable-mounted cranes that straddle the main cable to work together and simultaneously lift the same segment of steel box girder through multiple lifting points (usually four or eight points). Compared with the traditional single crane lifting at one or two points, this process can significantly improve the single hoisting capacity, improve the stress state of the beam segment, and increase the installation efficiency.

[0004] However, existing multi-point lifting methods using double-span cable cranes still face significant challenges in practical applications: the synchronization control of multiple lifting points during the lifting process requires extremely high precision. Under the influence of dynamic environmental factors such as wind loads and temperature changes, even slight differences in lifting speed and force at each lifting point can lead to additional internal stress or posture deviations in the beam segment. Existing monitoring methods struggle to accurately capture spatial positional changes at the lifting points, resulting in insufficient control accuracy and poor safety. Furthermore, the coordination of jack control during lifting is poor, and the correction process relies on manual intervention, lacking automation mechanisms, leading to low efficiency and susceptibility to human error. Therefore, existing steel box girder lifting processes still suffer from difficulties in synchronizing and coordinating multiple lifting points, resulting in low safety, poor positioning accuracy, and an inability to meet the high-standard construction requirements of large-tonnage steel box girders. Summary of the Invention

[0005] To address the technical problems in the existing steel box girder hoisting methods described in the background, such as the difficulty in synchronizing and coordinating multiple hoisting points during the hoisting process, resulting in low safety, poor positioning accuracy, and inability to meet the high-standard construction requirements of large-tonnage steel box girders, this invention provides a method and system for hoisting steel box girders for suspension bridges.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for hoisting a steel box girder for a suspension bridge, comprising: S1: Monitoring modules are installed at multiple lifting points of the steel box girder to be lifted, in order to collect elevation and internal force data of each lifting point in real time; S2: Filter and fuse the collected elevation and internal force data of each lifting point to generate fused data; S3: Calculate the synchronization deviation and flatness index of each lifting point based on the fused data, and generate control instructions based on hierarchical decision-making logic; S4: Send the control command to the execution module to control the hydraulic jacks corresponding to each lifting point to perform coordinated actions, so as to achieve dynamic balance between the lifting point elevation and internal force. S5: When the deviation exceeds the safety threshold, an alarm is triggered and automatic adjustment is performed until the hoisting status returns to stability.

[0007] Optionally, in step S2, the filtering process uses a combination algorithm to eliminate environmental interference, and the data fusion integrates elevation and internal force information through a weighted strategy, with the weights dynamically allocated based on signal quality.

[0008] Optionally, the filtering process includes: A combination algorithm of Kalman filtering and wavelet thresholding is used to reduce vibration interference by using a prediction model and residual adjustment for elevation data. A combined algorithm of sliding window averaging and amplitude limiting filtering is used for internal force data to smooth instantaneous fluctuations and remove outliers.

[0009] Optionally, the data fusion is achieved through dynamic weighting, with the weighting coefficients adaptively adjusted according to the quality of the positioning signal. When the positioning signal quality is excellent, elevation data is used first, and when the positioning signal quality is poor, elevation and internal force data are used in a balanced manner.

[0010] Optionally, in step S3, the hierarchical decision logic includes the following priorities: Level 1 Decision: When the internal force at any suspension point exceeds the design safety limit, an emergency stop command is immediately generated and the wire rope locking mechanism is triggered; Secondary decision: Based on the deviation between the average internal force of each lifting point and the measured internal force, the elevation adjustment is calculated through a linear correlation model to generate an internal force compensation command; Three-level decision-making: Based on the deviation between the elevation data of each lifting point and the average elevation, an elevation synchronization command is generated, and plane calibration is achieved by fine-tuning the displacement of the hydraulic jack; Level 4 decision-making: When both internal force and elevation deviation exceed the threshold, Level 2 and Level 3 decisions are executed in tandem to ensure the stability of the adjustment process.

[0011] Optionally, the linear correlation model is calibrated through pre-experimentation, and the model form is F. i =k×Z i +b, i=1,2…n, where F i Z represents the internal force data at the i-th lifting point. i Let represent the elevation data at the i-th lifting point, k be the internal force-elevation coefficient, b be a constant, and n be the number of lifting points.

[0012] Optionally, in step S4, the execution module adopts a master-slave control mechanism, sets the hydraulic jack group as master jack and slave jack, synchronizes the slave jack with the action of the master jack as the reference, and combines a temperature compensation algorithm to correct the influence of hydraulic oil temperature on adjustment accuracy in real time.

[0013] Secondly, the present invention provides a suspension bridge steel box girder hoisting system for implementing the above-described suspension bridge steel box girder hoisting method, comprising: The monitoring module is deployed at each suspension point to collect elevation and internal force data in real time. The data processing module is used to filter, fuse, and calculate deviations in the collected data. The decision-making module is used to generate control instructions based on hierarchical logic; The execution module, including a hydraulic jack assembly, is used to perform coordinated adjustments according to instructions; The alarm module is used to output early warning signals in abnormal situations.

[0014] Optionally, the monitoring module includes a positioning unit and a force sensing unit, both of which are communicatively connected to the data processing module. The positioning unit uses a satellite positioning device to monitor elevation, and the force sensing unit uses a tensile sensor to monitor internal force. Each unit is encapsulated in a protective housing to resist environmental interference.

[0015] Optionally, the execution module includes a hydraulic drive unit and a feedback verification unit. The feedback verification unit collects elevation and internal force data at high frequency, verifies the deviation of the adjustment command execution in real time, and dynamically corrects the opening of the hydraulic flow valve to ensure adjustment accuracy.

[0016] The beneficial effects of this invention are: This invention provides a method and system for hoisting steel box girders for suspension bridges. By deploying monitoring modules, it achieves synchronous acquisition of elevation and internal force data from multiple hoisting points. Combined with filtering and fusion, hierarchical decision-making, and automatic correction steps, it forms a fully intelligent control system. This method can comprehensively capture the spatial orientation changes and stress state of the steel box girder during hoisting, avoiding the limitations of traditional single-parameter monitoring and improving hoisting accuracy and safety. Through real-time data acquisition and processing, the system can quickly respond to external disturbances (such as wind load or construction load fluctuations), dynamically maintain the balance of hoisting points, and reduce the risks caused by delayed manual intervention. The introduction of preset benchmark values ​​provides a reliable reference for data comparison, ensuring accurate judgment. The automatic alarm and adjustment mechanisms achieve closed-loop management, ensuring continuous and stable hoisting processes. This solves the problems of coarse control and low correction efficiency in existing technologies, providing high reliability for suspension bridge construction. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the suspension bridge steel box girder hoisting method in this invention; Figure 2 This is a front view schematic diagram of the suspension bridge steel box girder hoisting system in this invention; Figure 3 This is a side view schematic diagram of the suspension bridge steel box girder hoisting system in this invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of 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. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. 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.

[0019] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0020] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention. It should also be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following figures denote similar items; therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0021] In the description of this invention, it should be understood that the orientation or positional relationship indicated by directional terms such as "front, back, up, down, left, right", "horizontal, vertical, horizontal" and "top, bottom" is generally based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing this invention and simplifying the description. Unless otherwise stated, these directional terms do not indicate or imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on the scope of protection of this invention. The directional terms "inner" and "outer" refer to the inner and outer contours relative to the outline of each component itself.

[0022] For ease of description, spatial relative terms such as "above," "on top of," "on the upper surface of," "above," etc., are used herein to describe the spatial positional relationship of a device or feature as shown in the figures to other devices or features. It should be understood that spatial relative terms are intended to encompass different orientations in use or operation beyond the orientation of the device as described in the figures. For example, if the device in the figures were inverted, a device described as "above" or "on top of" other devices or structures would subsequently be positioned as "below" or "under" other devices or structures. Thus, the exemplary term "above" can include both "above" and "below." The device may also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatial relative descriptions used herein will be interpreted accordingly.

[0023] Example 1 See Figure 1 The diagram illustrates the method for hoisting a steel box girder for a suspension bridge according to the present invention, including: S1: Monitoring modules are installed at multiple lifting points of the steel box girder to be lifted, in order to collect elevation and internal force data of each lifting point in real time; S2: Filter and fuse the collected elevation and internal force data of each lifting point to generate fused data; S3: Calculate the synchronization deviation and flatness index of each lifting point based on the fused data, and generate control instructions based on hierarchical decision-making logic; S4: Send the control command to the execution module to control the hydraulic jacks corresponding to each lifting point to perform coordinated actions, so as to achieve dynamic balance between the lifting point elevation and internal force. S5: When the deviation exceeds the safety threshold, an alarm is triggered and automatic adjustment is performed until the hoisting status returns to stability.

[0024] In this embodiment, a monitoring module is deployed to achieve synchronous acquisition of elevation and internal force data from multiple lifting points. Combined with filtering fusion, hierarchical decision-making, and automatic correction steps, a fully intelligent control system is formed. This method can comprehensively capture the spatial orientation changes and stress state of the steel box girder during the lifting process, avoiding the limitations of traditional single-parameter monitoring and improving lifting accuracy and safety. Through real-time data acquisition and processing, the system can quickly respond to external disturbances (such as wind load or construction load fluctuations), dynamically maintain the balance of lifting points, and reduce the risks caused by the lag in manual intervention. The introduction of preset benchmark values ​​provides a reliable benchmark for data comparison, ensuring accurate judgment. The automatic alarm and adjustment mechanism realizes closed-loop management, ensuring continuous and stable lifting process. This solves the technical problem of existing technologies where multiple lifting points are difficult to synchronize and coordinate, resulting in low safety, poor positioning accuracy, and difficulty in meeting the high-standard construction requirements of large-tonnage steel box girders. This provides a high-reliability guarantee for suspension bridge construction.

[0025] In addition, this method is highly adaptable and can be applied to steel box girders of different tonnages and complex construction environments. By standardizing the process, it reduces the reliance on the experience of operators and improves construction efficiency.

[0026] For example, in step S1, a high-precision Beidou positioning terminal is installed near the connection between the steel cable and the steel box girder at each lifting point. Its sampling frequency is 10 Hz, and at least one Beidou reference station is deployed within 500 meters around the lifting operation area to collect the elevation data of each lifting point in real time using the high-precision Beidou positioning terminal.

[0027] Meanwhile, a column-type tension sensor is installed at the top of the steel cable at each suspension point (near the suspension point of the steel box girder), with a sampling frequency of 20 Hz. The tension sensor is used to collect the internal force data of the steel wire rope at each suspension point in real time.

[0028] Optionally, in step S2 of the present invention, the filtering process uses a combination algorithm to eliminate environmental interference, and the data fusion integrates elevation and internal force information through a weighted strategy, with the weights dynamically allocated based on signal quality.

[0029] In this embodiment, a combination of algorithms and weighting strategies effectively eliminates environmental interference and improves data quality. Specifically, filtering processes target common factors in high-altitude operations such as vibration and electromagnetic noise, employing targeted algorithms to purify the raw data and ensure the authenticity and stability of elevation and internal force information. The weighting strategy dynamically allocates weights based on signal quality, optimizing the data fusion process and avoiding the negative impact of low-quality data on decision-making. This processing method enhances the system's accuracy under harsh conditions (such as strong winds or equipment interference), making the fused data more reflective of the actual lifting status. Simultaneously, the dynamic weight adjustment mechanism adapts to signal fluctuations, ensuring the real-time nature and adaptability of data fusion, providing high-precision input for subsequent hierarchical decision-making, and overcoming the shortcomings of traditional methods such as data susceptibility to interference and inaccurate fusion.

[0030] Optionally, the filtering process in this invention includes: A combination algorithm of Kalman filtering and wavelet thresholding is used to reduce vibration interference by using a prediction model and residual adjustment for elevation data. A combined algorithm of sliding window averaging and amplitude limiting filtering is used for internal force data to smooth instantaneous fluctuations and remove outliers.

[0031] In this embodiment, Kalman filtering combined with wavelet thresholding denoising is used to process elevation data, and sliding window averaging combined with amplitude limiting filtering is used to process internal force data, achieving multi-dimensional noise suppression. Specifically, Kalman filtering utilizes predictive models and residual adjustments to effectively reduce elevation jumps caused by mechanical vibrations or wind speed changes during hoisting, improving data smoothness; wavelet thresholding denoising decomposes high-frequency noise components, retaining useful signals and enhancing the reliability of elevation data; for internal force data, sliding window averaging smooths fluctuations caused by instantaneous impact loads, while amplitude limiting filtering eliminates outputs under sensor malfunctions or abnormal operating conditions, ensuring continuous and stable internal force values. This hierarchical filtering design employs optimal algorithms for different data characteristics, improving overall data accuracy and avoiding the problem of insufficient processing by a single algorithm. This embodiment, through refined noise management, provides clean and reliable input for data fusion and decision-making, significantly improving the system's anti-interference capability.

[0032] Specifically, in this embodiment, a combination algorithm of Kalman filtering and wavelet thresholding is used to reduce vibration interference by adjusting the prediction model and residuals. Kalman filtering: Establishing an elevation prediction model Z bd = Z p + V×Δt(Z p (where v is the elevation at the previous moment, v is the hoisting speed of the lifting point, and Δt is the sampling interval), and the measured value Z is used to measure the elevation at the previous moment. bd The residual between the predicted value and the filter gain is adjusted to reduce elevation jumps caused by sudden vibrations. Wavelet thresholding for noise reduction: The elevation data after Kalman filtering is decomposed, with the number of decomposition layers set to 3, and a threshold is set. (σ is the standard deviation of noise, N is the data length), after removing high-frequency noise components, the processed elevation value Z is obtained. flit ; Tensile force data filtering for internal force data: A combined algorithm of "sliding window + amplitude limiting filtering" is used. Sliding window averaging: Calculate the average value by taking 10 consecutive tensile force data points, with a window sliding step of 1, to smooth the internal force fluctuations caused by instantaneous impact loads; Amplitude limiting filtering: Set a threshold ΔF for the difference between adjacent data points. limit =3kN, when |F i -F i-1 |>ΔF limit In this case, the filtered value from the previous moment is used to replace the current value to avoid data anomalies caused by sensor malfunction.

[0033] Optionally, the data fusion in this invention is achieved through dynamic weighting. The weighting coefficients are adaptively adjusted according to the quality of the positioning signal. When the signal quality is good, elevation data is used first, and when the signal quality is poor, elevation and internal force data are used in a balanced manner.

[0034] In this embodiment, the weighting coefficients are adaptively adjusted based on the positioning signal quality to achieve intelligent integration of elevation and internal force data. When the signal quality is excellent, elevation data is prioritized to fully utilize its spatial positioning accuracy; when the signal quality is poor, elevation and internal force data are used in a balanced manner to compensate for the inadequacy of a single data source. This dynamic strategy ensures that the fused data maintains high representativeness under different operating conditions and avoids decision-making errors caused by signal attenuation or interruption.

[0035] The adaptive adjustment mechanism in this embodiment responds to real-time environmental changes. For example, when the BeiDou signal is affected by weather, the system automatically switches weights to maintain the continuity and accuracy of data fusion. Through flexible weighting, the accuracy and applicability of data fusion are enhanced, providing reliable data support for hoisting control.

[0036] Specifically, in this embodiment, the data fusion process achieved through dynamic weighting is as follows: Elevation data fusion: Combining BeiDou positioning elevation data Z bd Data Z from hydraulic jack displacement sensor jack A dynamic weighting strategy is adopted: Weighted elevation: Z = ω1 × Z flit +ω2×Z jackWhere ω1 + ω2 = 1; ω1 and ω2 are adjusted according to the BeiDou signal quality Q value. Specifically, when Q ≥ 38, ω1 = 0.8 and ω2 = 0.2 are taken to increase the elevation weight; when Q < 38, ω1 = 0.5 and ω2 = 0.5 are taken. At this time, the BeiDou signal is poor, so the elevation data weight is reduced and the internal force data weight is increased.

[0037] The industry-standard classification of BeiDou signal quality Q value is as follows: Excellent (Q≥45): strong signal, no interference; Good (38≤Q<45): moderate signal, slight interference; Poor (Q<38): weak signal, obvious interference.

[0038] Optionally, in step S3 of this invention, the hierarchical decision logic includes the following priorities: Level 1 Decision: When the internal force at any suspension point exceeds the design safety limit, an emergency stop command is immediately generated and the wire rope locking mechanism is triggered; Secondary decision: Based on the deviation between the average internal force of each lifting point and the measured internal force, the elevation adjustment is calculated through a linear correlation model to generate an internal force compensation command; Three-level decision-making: Based on the deviation between the elevation data of each lifting point and the average elevation, an elevation synchronization command is generated, and plane calibration is achieved by fine-tuning the displacement of the hydraulic jack; Level 4 decision-making: When both internal force and elevation deviation exceed the threshold, Level 2 and Level 3 decisions are executed in tandem to ensure the stability of the adjustment process.

[0039] In this embodiment, a hierarchical decision-making process, from Level 1 to Level 4, enables risk classification management and intelligent response. Level 1 decision-making prioritizes the safety of the internal forces at the lifting points, ensuring timely emergency stops to prevent overload accidents. Level 2 decision-making compensates for internal forces based on deviations from the average internal force value, balancing the force through elevation adjustments. Level 3 decision-making focuses on elevation synchronization, fine-tuning the jacks to ensure flatness. Level 4 decision-making coordinates internal force and elevation adjustments to handle complex deviation scenarios. This prioritization design ensures the system can operate smoothly even under multiple risks, addressing safety hazards first, then optimizing accuracy, thus improving decision-making efficiency. The hierarchical logic also reduces unnecessary intervention, avoids system oscillations caused by over-adjustment, ensures stable lifting, and enhances the system's intelligence level through a structured decision-making process, achieving a balance between safety and accuracy.

[0040] Optionally, the linear correlation model in this invention is calibrated through pre-experimentation, and the model form is F. i =k×Z i +b, i=1,2…n, where F i Let Z be the internal force at the i-th suspension point. i Let be the elevation at the i-th lifting point, k be the internal force-elevation coefficient, b be a constant, and n be the number of lifting points.

[0041] In this embodiment, a precise mathematical relationship between the internal force and elevation of the lifting point is established through model parameters calibrated via pre-tests, enabling data-driven coordinated adjustment. The model is simple and practical, facilitating real-time calculations. When the deviation between the measured internal force and the predicted value exceeds the limit, elevation-internal force coordinated adjustment is automatically triggered to quickly correct the imbalance. This correlation mechanism enhances the system's ability to perceive the dynamics of lifting operations, avoiding misjudgments caused by relying on a single parameter. Pre-test calibration ensures that the model adapts to specific engineering conditions, improving prediction accuracy.

[0042] Furthermore, the hierarchical decision-making logic in this embodiment is specifically as follows: Level 1 Decision: The optimal safety level is determined by the internal force of a single sling. When the internal force at any sling exceeds the design safety limit, there exists any F... i >When designing safety limits, an emergency stop command is immediately generated and the oil inlet valve of the hydraulic jack is closed, and the wire rope emergency locking device is triggered.

[0043] Secondary decision-making: The average value of the sling internal force data at each lifting point is used as the decision point. Based on the deviation between the average value of the internal force data at each lifting point and the measured internal force data, when ΔF at any lifting point... i >5%, calculate the elevation adjustment ΔZ=(F) based on the correlation model. avg -F i ) / k, generates "internal force compensation command": F i >F avg At that time, the elevation of the lifting point ΔZ is increased; F i <F avg At that time, the elevation ΔZ of the lifting point is lowered.

[0044] Level 3 decision-making: Using the elevation data of each lifting point as a benchmark, synchronization is performed in the plane. Based on the deviation between the elevation data of each lifting point and the average elevation, an elevation synchronization command is generated. Specifically, if ΔZ i >8mm (and ΔF i If the threshold is less than or equal to 0, generate an "elevation synchronization command": Z i <Z avg At that time, control the extension of the hydraulic jack to raise the elevation of the lifting point; Z i >Z avg When adjusting, shorten the jack to lower the elevation of the lifting point. Adjust the amount ΔZ = 0.5mm-1mm per adjustment to avoid excessive adjustment in a single adjustment that could cause attitude fluctuations.

[0045] Level 4 decision: When both internal force and elevation deviations exceed the threshold, Level 2 and Level 3 decisions are executed in tandem. Specifically, Level 2 decision (internal force equilibrium) is executed first, followed by Level 3 decision (plane synchronization) to ensure the coordinated stability of internal force and elevation during the adjustment process.

[0046] Optionally, in step S4 of the present invention, the execution module adopts a master-slave control mechanism, sets the hydraulic jack group as master jack and slave jack, synchronizes the slave jack with the action of the master jack as the reference, and combines a temperature compensation algorithm to correct the influence of hydraulic oil temperature on the adjustment accuracy in real time.

[0047] In this embodiment, the main jack's reference is used to synchronize the actions of the slave jacks, ensuring coordinated operation of multiple lifting points and avoiding action conflicts. Temperature compensation corrects the impact of hydraulic oil temperature changes on adjustment accuracy in real time, ensuring execution stability. Master-slave control simplifies the control logic and improves execution efficiency; the temperature compensation algorithm dynamically adjusts based on the calibration curve to offset errors caused by ambient temperature fluctuations. This combined design enhances the reliability of the execution module during long-term operation, adapts to high-altitude temperature differences, and ensures the implementation of decision commands through a precise execution mechanism, thereby improving overall system performance.

[0048] Example 2 The present invention also provides a suspension bridge steel box girder hoisting system for implementing the suspension bridge steel box girder hoisting method of Embodiment 1, comprising: The monitoring module is installed at each lifting point of the steel box girder to be hoisted, and is used to collect elevation data and internal force data in real time. The data processing module is used to filter, fuse, and calculate deviations in the collected data. The decision-making module is used to generate control instructions based on hierarchical logic; The execution module, including a hydraulic jack assembly, is used to perform coordinated adjustments according to instructions; The alarm module is used to output early warning signals in abnormal situations.

[0049] In this embodiment, the entire hoisting process is automated through the integration of monitoring, data processing, decision-making, execution, and alarm modules. The modular design facilitates deployment and maintenance, with each module working collaboratively to ensure a closed-loop linkage between data acquisition, processing, decision-making, and execution. The system boasts strong compatibility, adaptable to various hoisting scenarios, and enhances construction flexibility. The alarm module provides timely warnings of anomalies, forming a rapid response mechanism. This embodiment offers a one-stop solution for suspension bridge construction.

[0050] It should be noted that the specific usage process of the suspension bridge steel box girder hoisting system in this embodiment is the same as that of the suspension bridge steel box girder hoisting method in Embodiment 1, so it will not be described again.

[0051] Optionally, the monitoring module in this invention includes a positioning unit and a force sensing unit, both of which are communicatively connected to the data processing module. The positioning unit uses a satellite positioning device to monitor elevation, and the force sensing unit uses a tensile sensor to monitor internal force. Each unit is encapsulated in a protective housing to resist environmental interference.

[0052] In this embodiment, a combination of a positioning unit and a force sensing unit enables reliable acquisition of elevation and internal force data. The satellite positioning device provides precise spatial coordinates, the force sensor accurately captures changes in force, and the protective casing resists environmental interference such as wind, rain, and dust, ensuring continuous data acquisition. Inter-unit communication ensures real-time data transmission and supports efficient system operation.

[0053] Furthermore, the force sensing unit uses a tension sensor, which is connected to each lifting point of the steel box girder to be lifted via the hoisting I-beam.

[0054] Optionally, the execution module in this invention includes a hydraulic drive unit and a feedback verification unit. The feedback verification unit collects elevation and internal force data at high frequency, verifies the deviation of the adjustment command execution in real time, and dynamically corrects the opening of the hydraulic flow valve to ensure adjustment accuracy.

[0055] In this embodiment, high-frequency data acquisition is used to verify command execution deviations in real time and dynamically correct the opening of the hydraulic flow valve to ensure adjustment accuracy. A feedback mechanism ensures consistency between execution and decision-making, avoiding accumulated errors. Dynamic correction of real-time operating condition changes improves system adaptability. This design enhances the accuracy and reliability of the execution module, supporting stable lifting operations. This embodiment optimizes execution performance through closed-loop control, improving overall system performance.

[0056] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0057] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for hoisting a steel box girder for a suspension bridge, characterized in that, include: S1: Monitoring modules are installed at multiple lifting points of the steel box girder to be lifted, in order to collect elevation and internal force data of each lifting point in real time; S2: Filter and fuse the collected elevation and internal force data of each lifting point to generate fused data; S3: Calculate the synchronization deviation and flatness index of each lifting point based on the fused data, and generate control instructions based on hierarchical decision-making logic; S4: Send the control command to the execution module to control the hydraulic jacks corresponding to each lifting point to perform coordinated actions, so as to achieve dynamic balance between the lifting point elevation and internal force. S5: When the deviation exceeds the safety threshold, an alarm is triggered and automatic adjustment is performed until the hoisting status returns to stability.

2. The method for hoisting a steel box girder for a suspension bridge according to claim 1, characterized in that, In step S2, the filtering process uses a combination algorithm to eliminate environmental interference, and the data fusion integrates elevation and internal force information through a weighted strategy, with the weights dynamically allocated based on signal quality.

3. The method for hoisting a steel box girder for a suspension bridge according to claim 2, characterized in that, The filtering process includes: A combination algorithm of Kalman filtering and wavelet thresholding is used to reduce vibration interference by using a prediction model and residual adjustment for elevation data. A combined algorithm of sliding window averaging and amplitude limiting filtering is used for internal force data to smooth instantaneous fluctuations and remove outliers.

4. The method for hoisting a steel box girder for a suspension bridge according to claim 3, characterized in that, The data fusion is achieved through dynamic weighting. The weighting coefficients are adaptively adjusted according to the quality of the positioning signal. When the positioning signal quality is good, elevation data is used first; otherwise, elevation and internal force data are used in a balanced manner.

5. The method for hoisting a steel box girder for a suspension bridge according to claim 1, characterized in that, In step S3, the hierarchical decision-making logic includes the following priorities: Level 1 Decision: When the internal force at any suspension point exceeds the design safety limit, an emergency stop command is immediately generated and the wire rope locking mechanism is triggered; Secondary decision: Based on the deviation between the average internal force of each lifting point and the measured internal force, the elevation adjustment is calculated through a linear correlation model to generate an internal force compensation command; Three-level decision-making: Based on the deviation between the elevation data of each lifting point and the average elevation, an elevation synchronization command is generated, and plane calibration is achieved by fine-tuning the displacement of the hydraulic jack; Level 4 decision-making: When both internal force and elevation deviation exceed the threshold, Level 2 and Level 3 decisions are executed in tandem to ensure the stability of the adjustment process.

6. The method for hoisting a steel box girder for a suspension bridge according to claim 5, characterized in that, The linear correlation model is calibrated through pre-experiments, and the model form is F. i =k×Z i +b, i=1,2…n, where F i Z represents the internal force data at the i-th lifting point. i Let represent the elevation data at the i-th lifting point, k be the internal force-elevation coefficient, b be a constant, and n be the number of lifting points.

7. The method for hoisting a steel box girder for a suspension bridge according to claim 1, characterized in that, In step S4, the execution module adopts a master-slave control mechanism, sets the hydraulic jack group as master jack and slave jack, synchronizes the slave jack with the action of the master jack as the reference, and combines a temperature compensation algorithm to correct the influence of hydraulic oil temperature on adjustment accuracy in real time.

8. A suspension bridge steel box girder hoisting system for implementing the suspension bridge steel box girder hoisting method as described in claims 1 to 7, characterized in that, include: The monitoring module is installed at each lifting point of the steel box girder to be hoisted, and is used to collect elevation data and internal force data in real time. The data processing module is used to filter, fuse, and calculate deviations in the collected data. The decision-making module is used to generate control instructions based on hierarchical logic; The execution module, including a hydraulic jack assembly, is used to perform coordinated adjustments according to instructions; The alarm module is used to output early warning signals in abnormal situations.

9. The suspension bridge steel box girder hoisting system according to claim 8, characterized in that, The monitoring module includes a positioning unit and a force sensing unit, both of which are communicatively connected to the data processing module. The positioning unit uses a satellite positioning device to monitor elevation, and the force sensing unit uses a tensile sensor to monitor internal force. Each unit is encapsulated in a protective housing to resist environmental interference.

10. The suspension bridge steel box girder hoisting system according to claim 8, characterized in that, The execution module includes a hydraulic drive unit and a feedback verification unit. The feedback verification unit collects elevation and internal force data at high frequency, verifies the deviation of the adjustment command execution in real time, and dynamically corrects the opening of the hydraulic flow valve to ensure adjustment accuracy.

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