Pontoon jacking force self-adaptive adjusting system

Abstract

The invention discloses a pontoon jacking force self-adaptive adjusting system, and relates to the technical field of jacking control, the pontoon jacking force self-adaptive adjusting system comprises a pre-processing module, an optimization adjusting module and a control module, after pre-processed data is subjected to fuzzy PID adjustment, a pumping and irrigation system is controlled to change buoyancy by adjusting the water amount of a water tank on a pontoon, parameters of the fuzzy PID controller are adjusted through an invasive weed optimization algorithm, the control module is responded, response data are fed back to the sensor, and then the parameters are adjusted for control optimization; the fuzzy PID control and the invasive weed optimization algorithm are combined, the fuzzy PID solves the control problem of a non-linear and large-lag system, and the invasive weed optimization algorithm enables the system to get rid of dependence on manual experience parameter adjustment, adapt to the complex field environment in real time and dynamically find the optimal control parameter. The three-section error hierarchical control and master-slave cooperative control combined architecture solves the efficiency and precision problems of single-point control and the coordination problem of multi-point synchronization.

Description

Technical Field

[0001] This invention relates to the technical field of jacking control, and more particularly to an adaptive adjustment system for the jacking force of a floating vessel. Background Technology

[0002] In bridge engineering, for the maintenance or renovation of some cross-river and cross-sea bridges, when using floating pontoons to lift the arches of existing bridges, the required lifting force varies at different lifting points due to the inherent inhomogeneity of the bridge structure and the damage caused by long-term service. For example, the arch of an arch bridge has complex stress states in different parts. If the lifting force of the floating pontoon cannot be adaptively adjusted during the lifting process, it may cause localized stress concentration in the arch, resulting in structural damage, and in severe cases, even endangering the safety of the bridge.

[0003] Currently, Chinese invention patent application number CN202311641597.3 discloses a safety assessment method for the overall lifting process of a large segment of a steel-concrete composite arch bridge. The method involves establishing a finite element simulation model of the arch bridge and, based on the model calculation results, determining the lifting points of the cable-connected arch ribs, the key control sections of the arch ribs, and the top structure of the lifting tower as critical locations, and setting assessment points at each location. The method then proceeds to: S2, using a total station and sensors to acquire measured data of structural deformation and stress at the assessment points, and extracting the theoretical deformation and stress values ​​from the assessment points in the model to calculate Dp, Sp, and [the remaining values] as the scores for the first-level safety assessment model of the arch bridge; and S3, combining Dp, Sp, and [the remaining values] to construct the calculation of the second-level safety assessment model of the arch bridge. Formula to obtain the scoring result fp(x) of the secondary safety assessment model; S4, set Dp, Sp and as the first-level control indicators for safety early warning, and fp(x) as the comprehensive safety assessment indicator, establish the comprehensive safety assessment table for arch bridge, realize the systematic and comprehensive safety assessment of the overall lifting process of arch bridge, and ensure the safety and reliability of the construction process; however, traditional methods rely on manual observation and manual operation, which are extremely risky. The biggest problem with using barges and other flexible supports for jacking is synchronization and stability. Traditional methods always rely heavily on experienced operators on site. Indirect economic losses, costly construction accidents and rework caused by waterway closures are also unavoidable, and there are construction problems in complex aquatic environments. Summary of the Invention

[0004] The technical problem solved by this invention is that the parameter adjustment of traditional lifting control in the prior art is difficult. When the initial positioning of the lifting controller is poor in the process of searching for the optimal control strategy, it may converge to a non-optimal solution and may get stuck in a local optimum. Especially when the complexity of the problem itself is high, it may miss the global optimum and cannot solve the complex process of constraints. The lifting control accuracy is low and it is impossible to make precise adjustments to the control link.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a floating hull top lift adaptive adjustment system, comprising a preprocessing module, an optimization adjustment module, and a control module: The preprocessing module is used to construct the finite element model of the arch ring of the arch bridge, and to collect data through sensors and perform data preprocessing. The optimization and adjustment module is used to adjust the pre-processed data using fuzzy PID control, and then control the irrigation system to change the buoyancy by adjusting the water volume in the water tank on the floating pontoon. The parameters of the fuzzy PID controller are adjusted by the invading weed optimization algorithm, the control module responds, and the response data is fed back to the sensor to adjust the parameters for control optimization. The control module is used to perform master-slave collaborative control of each water tank of the floating vessel under the optimal control strategy, and output the optimal control parameters under the current construction conditions.

[0006] Preferably, the preprocessing module includes: The support pressure between the floating vessel's lifting points and the arch ring of the bridge is monitored by pressure sensors. The overall draft, tilt angle, and water tank capacity of the floating vessel are monitored by draft sensors and water tank level sensors. The tilt angle of the arch ring is monitored by inclinometers. The three-dimensional coordinates of key points of the arch ring are collected by a total station robot. The displacement, stress, and attitude of the arch ring are monitored in real time by vibrating wire strain gauges and high-definition cameras. The attitude is the set of three-dimensional coordinates of all key points.

[0007] Preferably, the preprocessing module further includes: A finite element model of the arch ring of the arch bridge is established using MIDAS Civil. The internal force distribution area of ​​the arch ring is obtained based on the finite element model. The internal force distribution area below the preset internal force threshold is extracted. The arch legs and diagonal braces in the internal force distribution area below the preset internal force threshold are reinforced with steel frames. A temporary support system is set up. The temporary support system includes setting a steel frame at the root of the arch leg and transferring the horizontal thrust to the back wall through a sliding beam. Based on the force distribution area within the arch ring of the arch bridge, the arch ring of the arch bridge is controlled in stages by a control module.

[0008] Preferably, the optimization adjustment module includes: The real-time deviation between the actual lifting displacement of the arch ring of the arch bridge and the preset target displacement is calculated. The error type is determined by the principle of fuzzy rule base. The stage where the deviation is greater than the first deviation threshold is set as the large error stage, the stage where the deviation is between the first and second deviation thresholds is set as the small error stage, and the stage where the deviation is less than the second deviation threshold is set as the steady state stage. When the current deviation is in the large error stage, the pumping rate of the main water tank is adjusted first to quickly respond to the deviation. When the current deviation is in the small error stage, cross-coupling control is activated to coordinate the synchronous adjustment of multiple water tanks. When the current deviation is in the steady state stage, fuzzy PID control is used for the second time.

[0009] Preferably, adjusting the parameters of the fuzzy PID controller using an invasive weed optimization algorithm includes: Multiple initial solutions are randomly generated and initialized. Each initial solution represents a combination of PID control factors, which is {Kp, Ki, Kd}. The initial solutions are randomly generated under preset range constraints. The fitness function value for each initial solution is calculated. The fitness function evaluates the control effect using the time response and absolute error integral of the fuzzy PID controller. The mathematical expression of the fitness function is as follows: ; ; in, Let t be the fitness function, and t be time. The difference between the system output and the expected output, For the desired output, This is the actual output, and the unit of error is the same as the unit of the output signal; Set a fitness threshold, select individuals with fitness values ​​less than the fitness threshold corresponding to the initial solutions, and eliminate individuals with poor performance of the initial solutions through natural selection. Update the optimal solutions through multiple iterations, continuously evolve and eventually converge to the optimal solution, which includes the optimal combination of PID control factors.

[0010] Preferably, the optimization adjustment module further includes: During the lifting process, the pressure, tilt angle, displacement, and strain of the arch ring of the arch bridge are monitored in real time. The pressure, tilt angle, displacement, and strain are fed back to the fuzzy PID controller. The feedback data is used as input to adjust the PID adjustment factor to adjust the control strategy of the hydraulic system. The error changes of the control system are monitored in real time, the PID parameters are continuously optimized, the feedback data is updated in real time, and the output data under the best control strategy is output in real time.

[0011] Preferably, the master-slave collaborative control includes: The tank that bears the largest load or has the most critical impact on attitude is designated as the main tank, and the remaining tanks are designated as slave tanks. The water volume adjustment of the slave tanks and the displacement of the corresponding lifting points are tracked within the ±1mm error range of the main tank. The tanks that have the most critical impact on the attitude of the arch bridge include the tank located below the geometric center of the floating vessel or the geometric center of all lifting points, the tank located below the center of gravity of the arch structure where the weight is transferred to the floating vessel, and the main control tank of the pre-designated floating vessel tank group. When the rate of increase of the support pressure at the corresponding lifting point of the water tank exceeds the preset growth threshold, the water adjustment rate of the main water tank is automatically reduced to balance the system load. The loads of the balancing system specifically include: Based on the calculation results of the fuzzy PID algorithm, the control module sends a water injection command to the pumping and irrigation system of the main water tank. After receiving the water injection command, the main water tank begins to inject water, increasing the displacement of the jacking point. The displacement sensor feeds back the real-time displacement data of the main water tank to the control module. The control module uses the real-time displacement data of the main water tank as the target displacement of all slave water tanks and controls the slave water tanks to perform water injection operations based on the target displacement. At the same time, it calculates the displacement error of each slave water tank in real time. The displacement error is the absolute value of the difference between the actual displacement and the target displacement. When the displacement error is greater than a preset error threshold, the control module controls the water injection rate of the pumping and irrigation system of the slave water tanks until the real-time displacement error of the slave water tank is less than the error threshold. When the control module performs synchronous tracking control on all water tanks, it continuously monitors the support pressure at each corresponding lifting point of each water tank and calculates the pressure growth rate, which is the derivative of the support pressure at the lifting point with respect to time. When the control module detects that the pressure increase rate of any water tank exceeds the preset pressure increase threshold, it immediately determines that there is a risk of load imbalance. The control module automatically executes a coverage command, which includes forcibly reducing the water adjustment rate of the main water tank.

[0012] Preferably, the control module includes: A 3D laser scanner is deployed to scan the shape of the arch ring of the arch bridge according to a preset time period to identify abnormal deformation areas. The identification process includes: The three-dimensional laser scanner is automatically started according to the preset time period to perform a comprehensive and high-precision scan of the overall external shape of the arch ring of the arch bridge, generating a three-dimensional point cloud model of the arch ring of the arch bridge. The three-dimensional point cloud model is compared with the previously generated three-dimensional point cloud model to calculate the displacement changes of all points on the structural surface of the arch ring of the arch bridge. Point cloud areas that exceed the preset safety threshold in the change data of all areas are identified as abnormal deformation areas of local settlement. When the control module detects an abnormal deformation area, it issues an audible and visual alarm and a data warning, and automatically starts a local grouting pump connected to a pre-embedded pipe in the abnormal deformation area. The pump injects reinforcing materials such as epoxy resin into structural gaps or weak points through the pipe. A dual PLC control system is configured with master and slave controllers for data synchronization and verification. In the event of a failure in either PLC control system, the master and slave controllers are automatically switched. The switching process includes: The master controller and slave controller perform data synchronization verification simultaneously through a high-speed network. The master controller periodically sends frequency hopping signals to the slave controller and exchanges I / O status and check codes for the frequency hopping signal verification calculation results. If the slave controller does not receive the frequency hopping signal from the master controller within a specified time, or if the received check codes do not match, the slave controller determines that the master controller has failed and immediately takes over all control outputs, becoming the new master controller. Install a locking system consisting of electrically controlled valves and a backup power supply. All electrically controlled valves and dual PLC control systems of the water tanks are connected to the backup power supply. When an unexpected power outage occurs at the construction site, the UPS will respond in milliseconds, instantly switch to battery power, and immediately close all electrically controlled valves to lock the water volume of each water tank.

[0013] Preferably, the control module further includes: The system initiates jacking operations at all jacking points in parallel through a pumping and irrigation system. The optimized fuzzy PID controller adjusts the displacement error in real time. When the displacement error is greater than 2mm, the system automatically triggers an emergency leveling procedure to fine-tune the water volume of a single water tank until the error is less than 1mm. The total station monitors the overall displacement of the arch ring of the arch bridge, and the strain gauge monitors the stress of key sections. The data is uploaded to the host computer for early warning.

[0014] Preferably, the control module further includes: After being lifted to the preset height, the pontoon is unloaded in three stages. After each stage of unloading, residual deformation is monitored, and local grouting is performed to reinforce the support points of the pontoon and the arch ring of the arch bridge.

[0015] The beneficial effects of this invention are as follows: This application combines fuzzy PID control with an invasive weed optimization algorithm to realize an intelligent control system that can self-optimize and self-adapt. Fuzzy PID solves the control problem of nonlinear and large time delay systems, while the invasive weed optimization algorithm frees this system from the dependence on manual experience in parameter tuning, enabling it to adapt to complex field environments in real time and dynamically find the optimal control parameters. A three-stage error hierarchical control architecture combined with master-slave collaborative control was proposed. This architecture solves both the efficiency and accuracy problems of single-point control (hierarchical control) and the coordination problem of multi-point synchronization (master-slave control), making it possible to achieve millimeter-level precise synchronous control of a large and cumbersome multi-point support system. This precision can effectively avoid generating additional torsional and shear stress on the bridge structure during the jacking process, protecting the bridge structure from secondary damage. A comprehensive perception architecture was constructed by integrating a variety of advanced sensing technologies, and this data was truly used for dynamic decision-making. In particular, three-dimensional laser scanning data was used to identify abnormal deformation and trigger automatic grouting, realizing a leap from monitoring and early warning to active intervention and achieving a comprehensive perception-decision-execution-feedback closed loop. Multiple lines of defense were constructed. Dual PLC hot backup, UPS power failure interlocking system, and water tank pressure over-limit linkage speed reduction design are all redundant designs for potentially fatal failure points that may occur in high-risk operations, which is rare in traditional construction schemes. Through automated monitoring, intelligent early warning, and multiple fault-tolerant mechanisms, structural instability or even collapse caused by uneven stress, operational errors, equipment malfunctions, or sudden power outages can be effectively prevented, minimizing human uncertainty and greatly ensuring construction safety. For bridges spanning rivers and seas, environmental factors such as water flow, tides, and waves have a significant impact on construction. This patented adaptive algorithm can compensate for these environmental disturbances in real time, making high-precision jacking operations possible in complex aquatic environments. This greatly expands the applicability of the floating jacking method and solves the construction challenges in complex aquatic environments. Attached Figure Description

[0016] Figure 1 This is a basic flowchart of a floating hull top lift adaptive adjustment system provided in one embodiment of the present invention. Detailed Implementation

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0018] Reference Figure 1 As one embodiment of the present invention, a floating hull top lift adaptive adjustment system is provided, comprising a preprocessing module, an optimization adjustment module, and a control module: The preprocessing module is used to construct the finite element model of the arch ring of the arch bridge, and to collect data through sensors and perform data preprocessing. The optimization and adjustment module is used to adjust the pre-processed data using fuzzy PID control, and then control the irrigation system to change the buoyancy by adjusting the water volume in the water tank on the floating pontoon. The parameters of the fuzzy PID controller are adjusted by the invading weed optimization algorithm, the control module responds, and the response data is fed back to the sensor to adjust the parameters for control optimization. The control module is used to perform master-slave collaborative control of each water tank of the floating vessel under the optimal control strategy, and output the optimal control parameters under the current construction conditions.

[0019] The core implementing mechanism of this solution is one or more modified barges used as jacking floats. The barges are divided into multiple independent water tanks along the longitudinal and transverse directions. Each water tank is equipped with an independent high-power reversible pump, a high-precision liquid level sensor and an electric control valve.

[0020] This application combines fuzzy PID control with an invasive weed optimization algorithm to achieve a self-optimizing and self-adaptive intelligent control system. Fuzzy PID solves the control problem of nonlinear systems with large time delays, while the invasive weed optimization algorithm frees the system from dependence on manual parameter tuning based on experience, enabling it to adapt to complex field environments in real time and dynamically find the optimal control parameters. A three-stage error hierarchical control combined with master-slave cooperative control architecture is proposed. This architecture solves both the efficiency and accuracy problems of single-point control (hierarchical control) and the coordination problem of multi-point synchronization (master-slave control), making it possible to achieve millimeter-level precise synchronous control of a large, cumbersome multi-point support system.

[0021] The preprocessing module includes: The support pressure between the floating vessel's lifting points and the arch ring of the bridge is monitored by pressure sensors. The overall draft, tilt angle, and water tank capacity of the floating vessel are monitored by draft sensors and water tank level sensors. The tilt angle of the arch ring is monitored by inclinometers. The three-dimensional coordinates of key points of the arch ring are collected by a total station robot. The displacement, stress, and attitude of the arch ring are monitored in real time by vibrating wire strain gauges and high-definition cameras. The attitude is the set of three-dimensional coordinates of all key points.

[0022] The physical quantities that need to be monitored are identified, including support pressure, draft, tilt angle, three-dimensional coordinates, and stress. The types of sensors used to achieve these monitoring are specified, including pressure sensors, inclinometers, total stations, and strain gauges, providing comprehensive, multi-dimensional, and high-precision data input for the entire adaptive control system.

[0023] The preprocessing module also includes: A finite element model of the arch ring of the arch bridge was established using MIDAS Civil. Based on the finite element model, the internal force distribution area of ​​the arch ring was obtained. The internal force distribution area below the preset internal force threshold was extracted. The arch legs and diagonal braces in the internal force distribution area below the preset internal force threshold were reinforced with steel frames. A temporary support system was set up. The temporary support system includes setting a steel frame at the root of the arch leg, transferring the horizontal thrust to the back wall through the sliding beam to eliminate the overturning moment, installing temporary steel supports to share the self-weight of the structure and prevent local instability. Based on the distribution area of ​​the internal forces of the arch ring, the arch ring of the arch bridge is controlled in stages by the control module. The number of stages is obtained by manual pre-division.

[0024] This approach introduces pre-planning and reinforcement steps, moving beyond a passive response to proactively identify and reinforce weak points in the bridge before the lifting operation begins. Furthermore, it breaks down the complex lifting process into more manageable, phased tasks, significantly enhancing the proactive safety and controllability of the construction. Pre-reinforcement prevents structural damage caused by stress concentration during lifting. Phased control reduces the difficulty and risk of individual adjustments.

[0025] The optimization and adjustment module includes: The real-time deviation between the actual lifting displacement of the arch ring of the arch bridge and the preset target displacement is calculated. The error type is determined by the principle of fuzzy rule base. The stage where the deviation is greater than the first deviation threshold is set as the large error stage, the stage where the deviation is between the first and second deviation thresholds is set as the small error stage, and the stage where the deviation is less than the second deviation threshold is set as the steady state stage. When the current deviation is in the large error stage, the pumping rate of the main water tank is adjusted first to quickly respond to the deviation. When the current deviation is in the small error stage, cross-coupling control is activated to coordinate the synchronous adjustment of multiple water tanks. When the current deviation is in the steady state stage, fuzzy PID control is used for the second time.

[0026] Activating cross-coupling control includes: multiple water tanks are not synchronized due to pipeline losses and valve characteristics differences. The multiple water tanks include left and right side water tanks and several water tanks that are lifted in sections. Cross-coupling control adjusts the pumping rate of each water tank through a synchronization error coordination method to reduce individual differences. The synchronization error is the difference between the displacement of each water tank and the average displacement. Fuzzy PID control includes: The mathematical expression for fuzzy PID control is: ; in, To control the output, which is the adjustment amount of the pumping rate, This is the system deviation, which represents the difference between the target displacement and the actual displacement. for The first derivative with respect to time t, To reduce the proportionality coefficient, This is the integral coefficient, used to reduce the cumulative effect. The differential coefficient is used to reduce the response to small fluctuations, making the control output smoother and avoiding frequent adjustments due to small deviations, thus ensuring that the system remains stable within ±0.5mm of the target displacement.

[0027] The core control logic of the optimization and adjustment module is explained in detail. It establishes a three-stage hierarchical control strategy, employing different adjustment methods for different deviations, making the control system more intelligent and efficient. It avoids using a single method to handle all situations, achieving a combination of bold and meticulous approaches, ensuring both response speed and final control accuracy and synchronization.

[0028] Adjusting the parameters of the fuzzy PID controller using an optimization algorithm for invasive weeds includes: Multiple initial solutions are randomly generated and initialized. Each initial solution represents a combination of PID control factors, which is {Kp, Ki, Kd}. The initial solutions are randomly generated under preset range constraints. The fitness function value for each initial solution is calculated. The fitness function evaluates the control effect using the time response and absolute error integral of the fuzzy PID controller. The mathematical expression of the fitness function is as follows: ; ; in, Let t be the fitness function, and t be time. The difference between the system output and the expected output, For the desired output, This is the actual output, and the unit of error is the same as the unit of the output signal; Set a fitness threshold, select individuals with fitness values ​​less than the fitness threshold corresponding to the initial solutions, and eliminate individuals with poor performance of the initial solutions through natural selection. Update the optimal solutions through multiple iterations, continuously evolve and eventually converge to the optimal solution, which includes the optimal combination of PID control factors.

[0029] In traditional fuzzy PID control, the adjustment factors Kp, Ki, and Kd are typically adjusted empirically, but this method may not be suitable for complex construction environments. To improve this, an invading weed optimization algorithm is introduced to automatically adjust these adjustment factors, optimizing the adjustment factors Kp, Ki, and Kd of the fuzzy PID controller. This minimizes the system error during the jacking process and ensures the synchronization and stability of the jacking.

[0030] After receiving the sensor data, the optimization and adjustment module calculates the deviation e(t) between the actual displacement and the target displacement of the arch ring of the arch bridge and its rate of change. Based on the magnitude of the deviation e(t), the fuzzy PID controller classifies the execution strategy of the pumping and irrigation system. When the deviation is in the large error stage, the pumping rate of the main water tank should be adjusted first, and a high-power water pump should be used to quickly inject or drain water in order to reduce the displacement deviation as quickly as possible. When the deviation is in the small error stage, the cross-coupling control is activated to coordinate the adjustment of the water volume of multiple water tanks, precisely control the attitude of the floating vessel, and ensure that the arch ring of the arch bridge is raised synchronously and smoothly. When the deviation is in a steady state, fuzzy PID control is used to fine-tune the water volume of each water tank to achieve high-precision position holding.

[0031] Meanwhile, the invading weed optimization algorithm in the background continues to run. It evaluates the quality of the current PID parameters {Kp, Ki, Kd} using a fitness function that includes time-weighted absolute error integrals. By simulating the process of weed reproduction, spread, and competitive elimination, the algorithm continuously searches and updates the PID parameter combination, enabling the control system to adapt to changes in the construction environment and always operate with optimal parameters, ensuring the speed, stability, and accuracy of the jacking process.

[0032] This invention addresses the shortcomings of traditional fuzzy PID controllers, which rely on experience for parameters (Kp, Ki, Kd) and struggle to adapt to complex working conditions. It introduces an invading weed optimization algorithm to automatically and continuously find the optimal combination of PID parameters, achieving true self-adaptation of the control system. Based on real-time feedback, it can autonomously learn and evolve, continuously optimizing its control performance to cope with changes in the construction environment (such as water flow and wind), ensuring that the jacking process is always under optimal control.

[0033] The optimization and adjustment module also includes: During the lifting process, the pressure, tilt angle, displacement, and strain of the arch ring of the arch bridge are monitored in real time. The pressure, tilt angle, displacement, and strain are fed back to the fuzzy PID controller. The feedback data is used as input to adjust the PID adjustment factor to adjust the control strategy of the hydraulic system. The error changes of the control system are monitored in real time, the PID parameters are continuously optimized, the feedback data is updated in real time, and the output data under the best control strategy is output in real time to ensure that the system always maintains the best control state.

[0034] The hydraulic proportional valve adjusts the cylinder speed in real time to optimize the lifting process.

[0035] By introducing an invasive weed optimization algorithm, the adjustment factors (Kp, Ki, Kd) in the fuzzy PID controller can be automatically optimized. This algorithm simulates the invasive behavior of weeds in nature and dynamically adjusts the parameters of the fuzzy PID controller through an adaptive search and selection mechanism, enabling the control system to maintain high efficiency and stability in complex and changing construction environments. Through continuous simulation and optimization, the accuracy, safety, and synchronization of the jacking process are ensured.

[0036] The dynamic closed-loop feedback mechanism of the entire system is clearly defined, emphasizing the process of feeding real-time monitoring data (pressure, displacement) back to the controller, which then continuously optimizes the control strategy based on this feedback, ensuring the system's real-time performance and dynamic optimality. A continuous "monitor-calculate-adjust-remonitor" cycle is described, guaranteeing that the control strategy can respond instantly to any subtle changes in the structure.

[0037] Master-slave collaborative control includes: The tank that bears the largest load or has the most critical impact on attitude is designated as the main tank, and the remaining tanks are designated as slave tanks. The water volume adjustment of the slave tanks and the displacement of the corresponding lifting points are tracked within the ±1mm error range of the main tank. The tanks that have the most critical impact on the attitude of the arch bridge include the tank located below the geometric center of the floating vessel or the geometric center of all lifting points, the tank located below the center of gravity of the arch structure where the weight is transferred to the floating vessel, and the main control tank of the pre-designated floating vessel tank group. When the rate of increase of the support pressure at the corresponding lifting point of the water tank exceeds the preset growth threshold, the water adjustment rate of the main water tank is automatically reduced to balance the system load. The loads of the balancing system specifically include: Based on the calculation results of the fuzzy PID algorithm, the control module sends a water injection command to the pumping and filling system of the main water tank. After receiving the water injection command, the main water tank begins to inject water, increasing the displacement of the jacking point. The displacement sensor feeds back the real-time displacement data of the main water tank to the control module. The control module uses the real-time displacement data of the main water tank as the target displacement of all slave water tanks and controls the slave water tanks to perform water injection operations based on the target displacement. At the same time, it calculates the displacement error of each slave water tank in real time. The displacement error is the absolute value of the difference between the actual displacement and the target displacement. When the displacement error is greater than a preset error threshold, the control module controls the water injection rate of the pumping and filling system of the slave water tanks until the real-time displacement error of the slave water tank is less than the error threshold. The process of balancing the system load is carried out simultaneously and continuously for all slave water tanks to ensure that the entire floating vessel formation is neat and uniform. When the control module performs synchronous tracking control on all water tanks, it continuously monitors the support pressure at each corresponding lifting point of each water tank and calculates the pressure growth rate, which is the derivative of the support pressure at the lifting point with respect to time. When the control module detects that the pressure increase rate of any water tank exceeds the preset pressure increase threshold, it immediately determines that there is a risk of load imbalance. The control module automatically executes a coverage command, which includes forcibly reducing the water adjustment rate of the main water tank, for example, reducing the water pump speed by 50% or pausing it.

[0038] Since all the secondary water tanks follow the main water tank, the entire jacking system will slow down synchronously after the main water tank decelerates. This buys valuable time for structural stress release and redistribution, and also provides a window for engineers to intervene, inspect, and handle problems. Once the abnormal pressure disappears, the system can resume its normal jacking rate.

[0039] In floating vessel lifting operations, the most critical water tank for attitude control refers to the water tank or group of water tanks whose changes in water volume have the most significant and direct impact on the pitch, roll, and overall lifting attitude of the entire floating vessel and the arch it supports. By filling and draining the water tank located below the geometric center of the floating vessel or the geometric center of all lifting points, the most uniform overall lifting or lowering of the entire structure can be achieved, which is most effective for adjusting the overall height. It is like the center point of a tray, from which force is applied most stably. Since the weight distribution of the arch is not absolutely uniform, the pressure on a certain support point will be the greatest. The water tank located below the center of gravity of the floating vessel, where the weight of the arch structure is transferred, is the main part that controls the entire lifting force. This position was accurately calculated through finite element analysis before construction. In the control algorithm, in order to simplify the complex multi-body cooperative motion problem, one or a group of water tanks is designated as the master control unit, and all other water tanks follow and adjust based on its state. This pre-selected master water tank becomes the water tank with the most critical influence on attitude, because any movement of it will trigger the linkage of all other water tanks.

[0040] The ±1mm error band for tracking the displacement of the main water tank by adjusting the water volume of the water tank and the displacement of the corresponding jacking point indicates that the displacement of all jacking points corresponding to the water tank must always be kept within 1 mm of the displacement of the main water tank. The pressure increase threshold is a safety value and also a rate value, which is expressed in kPa / second in this embodiment. It is used to measure the rate of change of the support pressure. If the change is too fast, it usually means that there is a problem with the structure. In this embodiment, there is a problem of jamming or local stress concentration.

[0041] This paper describes the master-slave collaborative control logic for ensuring multiple water tanks work precisely and synchronously as a whole during the lifting process. The core objective is to ensure the arch is lifted smoothly and synchronously, while preventing destructive stresses within the structure due to uneven stress distribution. A master-slave collaborative control architecture for multiple floating vessels or multiple water tanks is defined. By designating a master water tank, other slave water tanks are precisely followed (within ±1mm error range), and a crucial safety interlock mechanism is incorporated: when the pressure in a slave water tank increases too rapidly, the master water tank automatically decelerates, thus synchronizing the entire system's slowdown. This solves the challenge of multi-body synchronous control, ensuring the stability of the entire bridge structure during lifting and preventing torsional or destructive stresses caused by inconsistent displacement at various points. Monitoring the pressure increase rate is a crucial proactive risk avoidance mechanism.

[0042] The control module includes: A 3D laser scanner is deployed to scan the shape of the arch ring of the arch bridge according to a preset time period to identify abnormal deformation areas. The identification process includes: The three-dimensional laser scanner is automatically started according to the preset time period to perform a comprehensive and high-precision scan of the overall external shape of the arch ring of the arch bridge, generating a three-dimensional point cloud model of the arch ring of the arch bridge. The three-dimensional point cloud model is compared with the previously generated three-dimensional point cloud model to calculate the displacement changes of all points on the structural surface of the arch ring of the arch bridge. Point cloud areas that exceed the preset safety threshold in the change data of all areas are identified as abnormal deformation areas of local settlement. When the control module detects an abnormal deformation area, it sends an audible and visual alarm and a data warning to the on-site engineer. It then automatically starts a local grouting pump connected to a pre-embedded pipe in the abnormal deformation area. The pump injects reinforcing materials such as epoxy resin into structural gaps or weak points through the pipe to actively reinforce and fill the gaps and prevent further deformation.

[0043] A dual-PLC control system is set up, with master and slave controllers synchronizing and verifying data. In the event of a failure in either PLC control system, the master and slave controllers automatically switch. They simultaneously run the same control program and receive the same sensor data. The switching process includes: The master controller and slave controller simultaneously perform data synchronization verification via a high-speed network. The master controller periodically sends frequency hopping signals to the slave controller and exchanges I / O status and check codes for the frequency hopping signal verification calculation results. If the slave controller does not receive the frequency hopping signal from the master controller within a specified time, or if the received check code does not match, the slave controller determines that the master controller has failed and immediately takes over all control outputs, becoming the new master controller. Because the data and status of both are synchronized in real time, this switching process is seamless, and the actuators such as pumps and valves on site will not experience any interruptions or erroneous actions, ensuring the continuity of the jacking operation.

[0044] A locking system consisting of electrically controlled valves and a backup power supply is installed. The electrically controlled valves of all water tanks and the dual PLC control system are connected to the backup power supply. When an unexpected power outage occurs at the construction site, the UPS will respond in milliseconds and instantly switch to battery power to ensure that the dual PLC control system and electrically controlled valves will continue to work without power failure. It will also immediately close all electrically controlled valves, lock the water volume in each water tank, and maintain the stability of the pontoon's attitude and lifting force. After the valves are closed, the water volume in each water tank is completely locked, preventing it from flowing out or entering. This freezes the buoyancy, draft, and attitude of the entire pontoon at the moment before the power outage, thus reliably supporting the arch above and preventing it from suddenly falling or becoming unstable due to the power outage, buying time for subsequent handling.

[0045] By combining the flexible lifting characteristics of the floating vessel with the precise adjustment capability of the intelligent control algorithm, the dismantling operation of the arch ring of the arch bridge can be carried out safely, efficiently and smoothly.

[0046] The control module also includes: The system initiates jacking operations at all jacking points in parallel through a pumping and irrigation system. The optimized fuzzy PID controller adjusts the displacement error in real time. When the displacement error is greater than 2mm, the system automatically triggers an emergency leveling procedure to fine-tune the water volume of a single water tank until the error is less than 1mm. The total station monitors the overall displacement of the arch ring of the arch bridge, and the strain gauge monitors the stress of key sections. The data is uploaded to the host computer for early warning.

[0047] It provides clear quantitative indicators and implementation standards for the system's automatic error correction capability, making emergency response more standardized and reliable.

[0048] The control module also includes: After being lifted to the preset height, the structure is unloaded in three stages. After each stage of unloading, residual deformation is monitored, and local grouting is performed to reinforce the support points of the floating vessel and the arch ring of the arch bridge to restore the integrity of the structure.

[0049] The document describes the safe unloading and post-construction procedures for the completion phase of the project. It outlines how staged unloading avoids sudden stress changes and how final grouting reinforcement restores structural integrity. This ensures a complete project from start to finish, guaranteeing safety not only during the jacking process but also at the end of the project, thus forming a closed-loop construction method.

[0050] This application combines fuzzy PID control with an invasive weed optimization algorithm to realize a self-optimizing and self-adaptive intelligent control system. Fuzzy PID solves the control problem of nonlinear and large time delay systems, while the invasive weed optimization algorithm frees the system from dependence on manual experience-based parameter tuning, enabling it to adapt to complex field environments in real time and dynamically find the optimal control parameters. A three-stage error hierarchical control architecture combined with master-slave collaborative control was proposed. This architecture solves both the efficiency and accuracy problems of single-point control (hierarchical control) and the coordination problem of multi-point synchronization (master-slave control), making it possible to achieve millimeter-level precise synchronous control of a large and cumbersome multi-point support system. This precision can effectively avoid generating additional torsional and shear stress on the bridge structure during the jacking process, protecting the bridge structure from secondary damage. A comprehensive perception architecture was constructed by integrating a variety of advanced sensing technologies, and this data was truly used for dynamic decision-making. In particular, three-dimensional laser scanning data was used to identify abnormal deformation and trigger automatic grouting, realizing a leap from monitoring and early warning to active intervention and achieving a comprehensive perception-decision-execution-feedback closed loop. Multiple lines of defense were constructed. Dual PLC hot backup, UPS power failure interlocking system, and water tank pressure over-limit linkage speed reduction design are all redundant designs for potentially fatal failure points that may occur in high-risk operations, which is rare in traditional construction schemes. Through automated monitoring, intelligent early warning, and multiple fault-tolerant mechanisms, structural instability or even collapse caused by uneven stress, operational errors, equipment malfunctions, or sudden power outages can be effectively prevented, minimizing human uncertainty and greatly ensuring construction safety. For bridges spanning rivers and seas, environmental factors such as water flow, tides, and waves have a significant impact on construction. This patented adaptive algorithm can compensate for these environmental disturbances in real time, making high-precision jacking operations possible in complex aquatic environments. This greatly expands the applicability of the floating jacking method and solves the construction challenges in complex aquatic environments.

[0051] In summary, this patent combines advanced intelligent control theory and sensing technology with traditional civil engineering practices, transforming a rough job that relies on experience and luck into a precise, safe, efficient, and intelligent automated project, thus solving the core pain points of large arch bridge water operations.

[0052] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0053] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A floating hull top lift adaptive adjustment system, characterized in that, It includes a preprocessing module, an optimization and adjustment module, and a control module: The preprocessing module is used to construct the finite element model of the arch ring of the arch bridge, and to collect data through sensors and perform data preprocessing. The optimization and adjustment module is used to adjust the pre-processed data using fuzzy PID control, and then control the irrigation system to change the buoyancy by adjusting the water volume in the water tank on the floating pontoon. The parameters of the fuzzy PID controller are adjusted by the invading weed optimization algorithm, the control module responds, and the response data is fed back to the sensor to adjust the parameters for control optimization. The control module is used to perform master-slave collaborative control of each water tank of the floating vessel under the optimal control strategy, and output the optimal control parameters under the current construction conditions.

2. The adaptive adjustment system for the lift of a floating hull as described in claim 1, characterized in that, The preprocessing module includes: The support pressure between the floating vessel's lifting points and the arch ring of the bridge is monitored by pressure sensors. The overall draft, tilt angle, and water tank capacity of the floating vessel are monitored by draft sensors and water tank level sensors. The tilt angle of the arch ring is monitored by inclinometers. The three-dimensional coordinates of key points of the arch ring are collected by a total station robot. The displacement, stress, and attitude of the arch ring are monitored in real time by vibrating wire strain gauges and high-definition cameras. The attitude is the set of three-dimensional coordinates of all key points.

3. The adaptive adjustment system for the lift of a floating hull as described in claim 2, characterized in that, The preprocessing module further includes: A finite element model of the arch ring of the arch bridge is established using MIDAS Civil. The internal force distribution area of ​​the arch ring is obtained based on the finite element model. The internal force distribution area below the preset internal force threshold is extracted. The arch legs and diagonal braces in the internal force distribution area below the preset internal force threshold are reinforced with steel frames. A temporary support system is set up. The temporary support system includes setting a steel frame at the root of the arch leg and transferring the horizontal thrust to the back wall through a sliding beam. Based on the force distribution area within the arch ring of the arch bridge, the arch ring of the arch bridge is controlled in stages by a control module.

4. The adaptive adjustment system for the lift of a floating hull as described in claim 3, characterized in that, The optimization adjustment module includes: The real-time deviation between the actual lifting displacement of the arch ring of the arch bridge and the preset target displacement is calculated. The error type is determined by the principle of fuzzy rule base. The stage where the deviation is greater than the first deviation threshold is set as the large error stage, the stage where the deviation is between the first and second deviation thresholds is set as the small error stage, and the stage where the deviation is less than the second deviation threshold is set as the steady state stage. When the current deviation is in the large error stage, the pumping rate of the main water tank is adjusted first to quickly respond to the deviation. When the current deviation is in the small error stage, cross-coupling control is activated to coordinate the synchronous adjustment of multiple water tanks. When the current deviation is in the steady state stage, fuzzy PID control is used for the second time.

5. The adaptive adjustment system for the lift of a floating hull as described in claim 4, characterized in that, Adjusting the parameters of the fuzzy PID controller using an optimization algorithm for invasive weeds includes: Multiple initial solutions are randomly generated and initialized. Each initial solution represents a combination of PID control factors, which is {Kp, Ki, Kd}. The initial solutions are randomly generated under preset range constraints. The fitness function value for each initial solution is calculated. The fitness function evaluates the control effect using the time response and absolute error integral of the fuzzy PID controller. The mathematical expression of the fitness function is as follows: ； ； in, Let t be the fitness function, and t be time. The difference between the system output and the expected output, For the desired output, This is the actual output, and the unit of error is the same as the unit of the output signal; Set a fitness threshold, select individuals with fitness values ​​less than the fitness threshold corresponding to the initial solutions, and eliminate individuals with poor performance of the initial solutions through natural selection. Update the optimal solutions through multiple iterations, continuously evolve and eventually converge to the optimal solution, which includes the optimal combination of PID control factors.

6. The adaptive adjustment system for the lift of a floating hull as described in claim 5, characterized in that, The optimization adjustment module also includes: During the lifting process, the pressure, tilt angle, displacement, and strain of the arch ring of the arch bridge are monitored in real time. The pressure, tilt angle, displacement, and strain are fed back to the fuzzy PID controller. The feedback data is used as input to adjust the PID adjustment factor to adjust the control strategy of the hydraulic system. The error changes of the control system are monitored in real time, the PID parameters are continuously optimized, the feedback data is updated in real time, and the output data under the best control strategy is output in real time.

7. The adaptive adjustment system for the lift of a floating hull as described in claim 6, characterized in that, Master-slave collaborative control includes: The tank that bears the largest load or has the most critical impact on attitude is designated as the main tank, and the remaining tanks are designated as slave tanks. The water volume adjustment of the slave tanks and the displacement of the corresponding lifting points are tracked within the ±1mm error range of the main tank. The tanks that have the most critical impact on the attitude of the arch bridge include the tank located below the geometric center of the floating vessel or the geometric center of all lifting points, the tank located below the center of gravity of the arch structure where the weight is transferred to the floating vessel, and the main control tank of the pre-designated floating vessel tank group. When the rate of increase of the support pressure at the corresponding lifting point of the water tank exceeds the preset growth threshold, the water adjustment rate of the main water tank is automatically reduced to balance the system load. The loads of the balancing system specifically include: Based on the calculation results of the fuzzy PID algorithm, the control module sends a water injection command to the pumping and irrigation system of the main water tank. After receiving the water injection command, the main water tank begins to inject water, increasing the displacement of the jacking point. The displacement sensor feeds back the real-time displacement data of the main water tank to the control module. The control module uses the real-time displacement data of the main water tank as the target displacement of all slave water tanks and controls the slave water tanks to perform water injection operations based on the target displacement. At the same time, it calculates the displacement error of each slave water tank in real time. The displacement error is the absolute value of the difference between the actual displacement and the target displacement. When the displacement error is greater than a preset error threshold, the control module controls the water injection rate of the pumping and irrigation system of the slave water tanks until the real-time displacement error of the slave water tank is less than the error threshold. When the control module performs synchronous tracking control on all water tanks, it continuously monitors the support pressure at each corresponding lifting point of each water tank and calculates the pressure growth rate, which is the derivative of the support pressure at the lifting point with respect to time. When the control module detects that the pressure increase rate of any water tank exceeds the preset pressure increase threshold, it immediately determines that there is a risk of load imbalance. The control module automatically executes a coverage command, which includes forcibly reducing the water adjustment rate of the main water tank.

8. The adaptive adjustment system for the lift of a floating hull as described in claim 7, characterized in that, The control module includes: A 3D laser scanner is deployed to scan the shape of the arch ring of the arch bridge according to a preset time period to identify abnormal deformation areas. The identification process includes: The three-dimensional laser scanner is automatically started according to the preset time period to perform a comprehensive and high-precision scan of the overall external shape of the arch ring of the arch bridge, generating a three-dimensional point cloud model of the arch ring of the arch bridge. The three-dimensional point cloud model is compared with the previously generated three-dimensional point cloud model to calculate the displacement changes of all points on the structural surface of the arch ring of the arch bridge. Point cloud areas that exceed the preset safety threshold in the change data of all areas are identified as abnormal deformation areas of local settlement. When the control module detects an abnormal deformation area, it issues an audible and visual alarm and a data warning, and automatically starts a local grouting pump connected to a pre-embedded pipe in the abnormal deformation area. The pump injects reinforcing materials such as epoxy resin into structural gaps or weak points through the pipe. A dual PLC control system is configured with master and slave controllers for data synchronization and verification. In the event of a failure in either PLC control system, the master and slave controllers are automatically switched. The switching process includes: The master controller and slave controller perform data synchronization verification simultaneously through a high-speed network. The master controller periodically sends frequency hopping signals to the slave controller and exchanges I / O status and check codes for the frequency hopping signal verification calculation results. If the slave controller does not receive the frequency hopping signal from the master controller within a specified time, or if the received check codes do not match, the slave controller determines that the master controller has failed and immediately takes over all control outputs, becoming the new master controller. Install a locking system consisting of electrically controlled valves and a backup power supply. All electrically controlled valves and dual PLC control systems of the water tanks are connected to the backup power supply. When an unexpected power outage occurs at the construction site, the UPS will respond in milliseconds, instantly switch to battery power, and immediately close all electrically controlled valves to lock the water volume of each water tank.

9. The adaptive adjustment system for the lift of a floating hull as described in claim 8, characterized in that, The control module also includes: The system initiates jacking operations at all jacking points in parallel through a pumping and irrigation system. The optimized fuzzy PID controller adjusts the displacement error in real time. When the displacement error is greater than 2mm, the system automatically triggers an emergency leveling procedure to fine-tune the water volume of a single water tank until the error is less than 1mm. The total station monitors the overall displacement of the arch ring of the arch bridge, and the strain gauge monitors the stress of key sections. The data is uploaded to the host computer for early warning.

10. The adaptive adjustment system for the lift of a floating hull as described in claim 9, characterized in that, The control module also includes: After being lifted to the preset height, the pontoon is unloaded in three stages. After each stage of unloading, residual deformation is monitored, and local grouting is performed to reinforce the support points of the pontoon and the arch ring of the arch bridge.

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