Self-balancing type capping beam construction structure and capping beam construction method

Abstract

The invention provides a self-balancing type capping beam construction structure and a capping beam construction method, and belongs to the technical field, the self-balancing type capping beam construction structure comprises a capping beam plate, the capping beam plate comprises a supporting steel frame, a walkway plate and a bottom frame, the walkway plate is laid on the upper surface of the supporting steel frame, the bottom frame is arranged below the supporting steel frame, and a balancing assembly is arranged between the bottom frame and the supporting steel frame; the balance assembly comprises a cylinder barrel, a plurality of telescopic rods and mounting blocks, the sizes of the telescopic rods are sequentially decreased, the cylinder barrel is arranged outside the telescopic rod on the outermost side in a sleeving mode, the mounting blocks are arranged at the ends of the cylinder barrel and the telescopic rods, and the self-balance control system is used for monitoring the use balance state of the bent cap structure and controlling the balance assembly to conduct automatic balance adjustment according to the balance state. The problems that in the construction process, a platform is prone to balance, and balance adjusting efficiency is low and adjusting is not timely due to traditional manual observation are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of bridge construction, and in particular, relates to a self-balancing cap beam construction structure and a cap beam construction method. Background Art

[0002] The cap beam, as the upper structure of the bridge, is a key component connecting the bridge piers and the bridge deck. It not only bears various loads from the bridge deck, but also plays an important role in dispersing the load and ensuring the overall stability of the bridge. The construction quality of the cap beam is directly related to the safety performance, service life and driving comfort of the bridge.

[0003] In the traditional cap beam construction process, scaffolding boards are usually used to temporarily block the gap between the bottom formwork and the construction platform, or the gap is not blocked directly. During the cap beam construction process, due to the continuous change of load, the platform is prone to imbalance. Traditional balance adjustment methods often rely on manual observation and experience judgment, with low adjustment efficiency and poor precision. Untimely or inaccurate balance adjustment will increase safety hazards during the construction process and may even cause construction accidents. Due to the existence of balance problems, the construction process often requires frequent suspension and adjustment, which greatly reduces the construction efficiency. To this end, a self-balancing cap beam construction structure and a cap beam construction method are designed. Summary of the invention

[0004] The embodiments of the present invention provide a self-balancing cap beam construction structure and a cap beam construction method, which solve the problem that the platform is prone to balance problems during the construction process and the problem that traditional balance adjustment through manual observation leads to low efficiency and untimely adjustment.

[0005] In view of the above problems, the technical solution proposed by the present invention is:

[0006] The present invention provides a self-balancing cap beam construction structure, comprising a cap beam plate, wherein the cap beam plate comprises a supporting steel frame, a walkway plate and a base frame, wherein the walkway plate is laid on the upper surface of the supporting steel frame, and the base frame is arranged below the supporting steel frame;

[0007] A balancing assembly, the balancing assembly is arranged between the base frame and the supporting steel frame, the balancing assembly comprises a cylinder, a plurality of telescopic rods of decreasing sizes and a mounting block, the cylinder is sleeved outside the outermost telescopic rod, and the ends of the cylinder and the telescopic rod are both provided with mounting blocks;

[0008] A self-balancing control system is used to monitor the balance state of the cap beam structure and control the balance component to perform automatic balance adjustment according to the balance state.

[0009] As a preferred technical solution of the present invention, it further includes an adjustment component, the adjustment component is arranged outside the support steel frame, the adjustment component includes a motor, a rotating shaft and a folding plate, the rotating shaft is arranged at the output end of the motor, the output end of the motor is in transmission connection with the rotating shaft, mounting plates are screwed at both ends of the rotating shaft and on one side of the motor, the mounting plates are bolted to the chassis, and the rotating shaft is bolted to the bottom side of the folding plate.

[0010] As a preferred technical solution of the present invention, the support steel frame is bolted to the walkway plate, a guardrail is welded on the upper surface of the walkway plate, pier connection holes are formed on the surfaces of the walkway plate, the support steel frame and the chassis, and connection hoops are arranged in the connection holes for connection. At least two of the balance components are arranged at the four corners of the bottom of the support steel frame, and the balance components in the same group are arranged obliquely and designed in a triangle with the chassis.

[0011] As a preferred technical solution of the present invention, a hydraulic pump, an oil cylinder and a motor are arranged inside the cylinder barrel. The output end of the motor is connected to the input end of the hydraulic pump through a coupling. The hydraulic pump is communicated with the piston cavity of the oil cylinder through a hydraulic pipeline. The telescopic rod is fixed on the piston of the oil cylinder. Connection blocks are arranged between the mounting block and the telescopic rod and the cylinder barrel. The connection blocks are screwed to the telescopic rod and the cylinder barrel. The connection blocks are rotatably connected to the mounting block. A motor is embedded on one side of the mounting block, and the output shaft of the motor is screwed to the connection block. The mounting block is bolted to the support steel frame and the chassis respectively.

[0012] As a preferred technical solution of the present invention, the self-balancing control system includes a data acquisition module, and the data acquisition module uses sensors to collect the usage status data of the capping beam structure;

[0013] A data fusion module, the data fusion module uses a weight fusion algorithm to assign weights to the data from each sensor and perform fusion;

[0014] A data dimensionality reduction module, the data dimensionality reduction module uses a variational autoencoder to perform dimensionality reduction processing on the fused high-dimensional sensor data;

[0015] A collaborative prediction module, the collaborative prediction module selects a suitable prediction model according to the data characteristics of the data acquisition module, establishes a prediction model, and uses a reinforcement learning algorithm to optimize the prediction model;

[0016] A control module, the control module is used to perform sliding mode control on the low-dimensional data output by the variational autoencoder.

[0017] As a preferred technical solution of the present invention, the detailed content of the collaborative prediction by the collaborative prediction module is as follows:

[0018] Step a: Establish a dynamic model of the bent cap structure. According to the dynamic model and the features extracted by the variational autoencoder, establish a prediction model for state prediction.

[0019] Step b: Design a reinforcement learning algorithm to learn the optimization strategy in the prediction model. Use historical monitoring data to train the reinforcement learning model, set the initial parameters of the model, set the training parameters, and update the parameters of the reinforcement learning model through iterative optimization to improve the control strategy.

[0020] Step c: Use the low-dimensional features extracted by the variational autoencoder to fuse with real-time data to form a complete input vector. Input the fused input vector into the prediction model to predict the future state and optimize the control input.

[0021] Step d: Integrate the learned reinforcement learning strategy into the prediction model framework for real-time prediction and optimal control. Apply the optimized control input to the self-balancing control system for precise control.

[0022] As a preferred technical solution of the present invention, the detailed content of the sliding mode control by the control module is as follows:

[0023] Step 1: Establish a dynamic model of the bent cap structure. According to the dynamic model and the low-dimensional data output by the variational autoencoder, design a suitable sliding surface equation, usually s(x) = 0, where x is the system state vector, including the low-dimensional features output by the variational autoencoder.

[0024] Step 2: Design an equivalent control law, which is obtained by solving the derivative of s(x) = 0 and setting it equal to zero, and a switching control law for overcoming system uncertainties and external disturbances. The switching control law usually includes the sign function sign(s). Combine the equivalent control law and the switching control law to form a comprehensive control law, which is used as the input of the actual control system.

[0025] Step 3: Verify the control effect of the sliding mode control in the simulation environment and adjust the parameters until the performance requirements are met.

[0026] Step 4: Take the low-dimensional features extracted by the variational autoencoder as the real-time state and input them into the sliding mode variable structure controller, and make necessary adjustments and optimizations. According to the actual test results, further optimize the parameters and structure of the variational autoencoder and the sliding mode control.

[0027] On the other hand, a construction method for the bent cap of a self-balancing bent cap construction structure includes the following steps:

[0028] S1. Assemble the cover beam slab according to the design scheme of the cover beam structure. Install the underframe, balance assembly, support steel frame, walkway board, and adjustment assembly on the pier in sequence. Set up steel strands between the underframe and the support steel frame for strengthened connection. Install sensors at the joints to monitor the cover beam slab and provide raw data for subsequent processing.

[0029] S2. Collect sensor data and perform preprocessing. Use a variational autoencoder to obtain low-dimensional features, and combine with a dynamic model to establish a prediction model. Based on the future state and current state output by the prediction model, design the sliding surface equation and control law of the sliding mode controller, providing key information input for subsequent steps.

[0030] S3. Establish a reinforcement learning model to learn and optimize the control strategy based on historical data and real-time feedback, and adjust the control strategy according to real-time feedback.

[0031] S4. Evaluate the performance of the sliding mode controller according to the actual control effect, adjust the parameters of the sliding mode controller according to the evaluation results, and continuously perform parameter adjustment and structural optimization until balance is achieved to complete the construction of the cover beam.

[0032] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0033] (1) Through the multi-point inclined triangle layout of the balance assembly, the design of the hydraulic telescopic rod and the motor, the present invention enhances the structural stability and the balance adjustment accuracy, adapts to complex environments. Through the multi-functional design of the folding plate of the adjustment assembly, it integrates the functions of increasing the usable area, facilitating transportation, and providing safety protection, with high space utilization rate and strong practicability, improving the equipment performance and construction efficiency, and reducing safety risks and costs.

[0034] (2) By designing a self-balancing control system, the present invention can adjust the balance assembly in real time to avoid structural deformation. By combining the variational autoencoder and the dynamic model, an efficient prediction model is established to provide reliable information for the control strategy. The sliding mode controller and the reinforcement learning complement each other, enhancing the control adaptability and robustness, improving the construction safety, efficiency, and economy, reducing rework and maintenance, providing strong technical support for the construction and long-term operation of the cover beam structure, and realizing efficient, intelligent, and stable control.

[0035] The above description is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly, it can be implemented according to the content of the specification. And in order to make the above and other objects, features, and advantages of the present invention more obvious and understandable, the following specifically illustrates the specific embodiments of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a structural schematic diagram of a self-balancing cover beam construction structure disclosed by the present invention;

[0037] Figure 2 It is a schematic structural diagram of a balance component of a self - balancing bent cap construction structure disclosed by the present invention;

[0038] Figure 3 It is a schematic structural diagram of an adjustment component of a self - balancing bent cap construction structure disclosed by the present invention;

[0039] Figure 4 It is an installation schematic diagram of a self - balancing bent cap construction structure and a bridge pier disclosed by the present invention;

[0040] Figure 5 It is a block diagram of a self - balancing control system of a self - balancing bent cap construction structure disclosed by the present invention;

[0041] Figure 6 It is a schematic flow diagram of a bent cap construction method of a self - balancing bent cap construction structure disclosed by the present invention;

[0042] Explanation of reference numerals: 100, bent cap slab; 101, support steel frame; 102, walkway slab; 103, guardrail; 104, chassis;

[0043] 200, balance component; 201, cylinder barrel; 202, telescopic rod; 203, mounting block; 204, connecting block;

[0044] 300, adjustment component; 301, motor; 302, rotating shaft; 303, folding plate; 304, mounting plate;

[0045] 400, self - balancing control system; 401, data acquisition module; 402, data fusion module; 403, data dimensionality reduction module; 404, collaborative prediction module; 405, control module; 406, delay compensation module; 500, bridge pier. Detailed implementation manners

[0046] To make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0047] Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0048] It should be noted that like reference numerals and letters refer to like items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0049] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0050] In addition, the terms "first" and "second" are only used for descriptive purposes and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined.

[0051] Embodiment 1

[0052] Referring to the attached Figures 1-5 As shown, the present invention provides a technical solution: a self - balancing capping beam construction structure, including a capping beam slab 100. The capping beam slab 100 includes a support steel frame 101, a walkway slab 102, and a bottom frame 104. The walkway slab 102 is laid on the upper surface of the support steel frame 101, and the bottom frame 104 is arranged below the support steel frame 101;

[0053] A balance assembly 200 is arranged between the bottom frame 104 and the support steel frame 101. The balance assembly 200 includes a cylinder barrel 201, several telescopic rods 202 with gradually decreasing sizes, and mounting blocks 203. The cylinder barrel 201 is sleeved outside the outermost telescopic rod 202, and mounting blocks 203 are arranged at the ends of both the cylinder barrel 201 and the telescopic rods 202;

[0054] Adjusting assembly 300 is arranged outside the support steel frame 101. The adjusting assembly 300 includes a motor 301, a rotating shaft 302 and a folding plate 303. The rotating shaft 302 is arranged at the output end of the motor 301, and the output end of the motor 301 is in transmission connection with the rotating shaft 302. Mounting plates 304 are screwed to both ends of the rotating shaft 302 and one side of the motor 301. The mounting plates 304 are bolted to the chassis 104. The rotating shaft 302 and the motor 301 are fixed on the chassis 104 through the mounting plates 304, providing a stable support point for the rotation of the rotating shaft 302 and ensuring the accuracy and reliability of the rotational movement. The rotating shaft 302 is bolted to the bottom side of the folding plate 303. By driving the rotating shaft 302 to rotate through the motor 301, the folding plate 303 is driven to change its angle, enabling precise attitude control of the folding plate 303. Through the angle adjustment of the folding plate 303, the usable area of the cover beam plate 100 can be increased when the folding plate 303 is horizontal with the walkway plate 102. Through the unfolding of the folding plate 303, the space that was originally unavailable or difficult to utilize is effectively expanded. When vertically folded, it is convenient for transportation and is used as a guardrail during use. During the construction of the cover beam, workers need to perform various operations on the walkway plate 102, posing certain safety risks such as personnel falling. The folding plate 303, as a guardrail, can effectively prevent accidental falls of personnel and ensure the safety of construction workers. At the same time, since the folding plate 303 is fixed to the rotating shaft 302 through connection means such as bolts, it has a certain strength and stability and can withstand a certain impact force, meeting the safety requirements during the use of the guardrail;

[0055] Self-balancing control system 400 is used to monitor the usage balance state of the cover beam structure and control the balance assembly 200 to perform automatic balance adjustment according to the balance state.

[0056] The embodiments of the present invention are also implemented through the following technical solutions.

[0057] In the embodiments of the present invention, the support steel frame 101 is bolted to the walkway plate 102. A guardrail 103 is welded to the upper surface of the walkway plate 102. Pier connection holes are provided on the surfaces of the walkway plate 102, the support steel frame 101 and the chassis 104. Connection hoops are arranged in the connection holes for connection. The cover beam plate 100 is installed on the pier 500 through the connection hoops. At least two balance assemblies 200 are arranged at the four corners of the bottom of the support steel frame 101. The balance assemblies 200 in the same group are inclined and designed in a triangular shape with the chassis 104. The cover beam plate 100 is balanced and adjusted through the balance assemblies 200 at the four corners.

[0058] In an embodiment of the present invention, a hydraulic pump, an oil cylinder, and a motor 301 are disposed inside the cylinder barrel 201. The output end of the motor 301 is connected to the input end of the hydraulic pump through a coupling. The rotational motion of the motor 301 is transmitted to the hydraulic pump through this connection. The hydraulic pump is communicated with the piston chamber of the oil cylinder through a hydraulic pipeline. The pressure oil generated by the hydraulic pump is transported to the piston chamber of the oil cylinder through the hydraulic pipeline. The acting force of the hydraulic oil pushes the piston inside the oil cylinder to move, thereby realizing the extension or retraction of the telescopic rod 202. The telescopic rod 202 is fixed to the piston of the oil cylinder. When the hydraulic oil pushes the piston to move, the telescopic rod 202 extends or retracts accordingly. The telescopic rod 202 can be a multi-stage structure to achieve a greater stroke. Connecting blocks 204 are provided between the mounting block 203 and both the telescopic rod 202 and the cylinder barrel 201. The connecting blocks 204 are screwed to the telescopic rod 202 and the cylinder barrel 201. The connecting blocks 204 are rotatably connected to the mounting block 203. The mounting block 203 is connected to the cylinder barrel 201 and the telescopic rod 202 through the connecting blocks. A motor is embedded on one side of the mounting block 203. The output shaft of the motor is screwed to the connecting block 204. By controlling the rotation of the connecting block connected thereto by the motor, the motor can drive the telescopic rod 202 and the cylinder barrel 201 to perform fine adjustment by rotating the connecting block 204, thereby realizing the precise control of the angle of the balance assembly 200. The mounting block 203 is respectively bolted to the support steel frame 101 and the bottom frame 104. The connection between the balance assembly 200 and the cover slab 100 is realized through the mounting block 203.

[0059] Specifically, the layout mode of the balance assembly 200 can form a stable support structure and at the same time provide multiple fulcrums and adjustment directions for balance adjustment. In the initial state, the telescopic rods 202 of the balance assemblies 200 are in appropriate telescopic positions, so that a relative balance is maintained between the support steel frame 101 and the bottom frame 104. At this time, the hydraulic system components such as the hydraulic pump, the oil cylinder, and the motor 301 are in a standby state. The length of the telescopic rod 202 is fixed, and the balance assembly 200 provides a stable supporting force for the support steel frame 101. When the self-balancing control system 400 receives the signal fed back by the sensor, it judges the inclination direction and degree of the support steel frame 101, as well as the position and adjustment amount of the balance assembly 200 that needs to be adjusted. Then, the self-balancing control system 400 issues an adjustment instruction to the corresponding balance assembly 200 according to the analysis result. After receiving the instruction of the self-balancing control system 400, the motor 301 starts to work. Its output end drives the hydraulic pump to rotate through a coupling. The hydraulic pump sucks the hydraulic oil from the fuel tank, pressurizes it, and transports it to the piston chamber of the oil cylinder through the hydraulic pipeline. Under the action of the pressure oil, the piston inside the oil cylinder moves, driving the telescopic rod 202 to extend or retract. The telescopic movement of the telescopic rod 202 changes the length of the balance assembly 200, thereby adjusting the relative position between the support steel frame 101 and the bottom frame 104.

[0060] Since multiple balance components 200 are provided at the four bottom corners of the support steel frame 101, during the balance adjustment process, the multiple balance components 200 will work together according to the instructions of the control system. For example, when the support steel frame 101 tilts to one side, the telescopic rods 202 of the balance components 200 on that side will extend to increase the support height on that side; while the telescopic rods 202 of the balance components 200 on the other side will retract to reduce the support height on that side. Through the coordinated adjustment of the multiple balance components 200, the support steel frame 101 gradually returns to the balanced state.

[0061] In an embodiment of the present invention, the self-balancing control system 400 includes a data acquisition module 401. The data acquisition module 401 uses sensors to collect the usage status data of the capping beam structure, including high-precision inclinometers, strain gauges, laser displacement sensors, pressure sensors, etc.;

[0062] A data fusion module 402. The data fusion module 402 uses a weight fusion algorithm to assign weights to the data from each sensor and perform fusion;

[0063] Specific fusion steps: According to the selected weight assignment basis, use the entropy weight method to calculate the entropy value of the sensor data to determine its weight. The smaller the entropy value, the more important the data, and the greater the weight. Multiply the data of each sensor by its corresponding weight, and then perform a summation or averaging operation to obtain the fused result;

[0064] A data dimensionality reduction module 403. The data dimensionality reduction module 403 uses a variational autoencoder to perform dimensionality reduction processing on the fused high-dimensional sensor data and outputs simpler data to provide simple data input for subsequent processing;

[0065] Specific dimensionality reduction steps: Design the network structure of the variational autoencoder, including the number of layers and neurons of the encoder and decoder. Input the fused data for training the encoder model. Reconstruct the data through the decoder. The encoder outputs the mean and variance of the variables to obtain the latent variables. The decoder trains the model by minimizing the reconstruction error and the difference between the distribution of the latent variables and the normal distribution during the reconstruction of the original data from the latent variables. Input real-time data into the trained encoder. The encoder outputs the mean and variance of the latent variables. According to the mean and variance output by the encoder, perform a sampling operation to obtain the latent variables. The sampled latent variables are the low-dimensional feature representations of the original data, and this feature represents the key information of the original data in the low-dimensional space;

[0066] A collaborative prediction module 404. The collaborative prediction module 404 selects a suitable prediction model according to the data characteristics of the data acquisition module 401, and establishes a prediction model, such as a linear model, a non-linear model, or a neural network model, and uses a reinforcement learning algorithm to optimize the prediction model;

[0067] A control module 405, which is used to perform sliding mode control on the low-dimensional data output by the variational autoencoder;

[0068] A delay compensation module 406, which is used to eliminate the influence of the execution lag of the balance component 200 on the control stability. The specific operation is as follows: embed a time-delay transfer function e in the prediction model -TS , where T is the time-delay time constant, and the value of T is updated in real time through an online identification method to adapt to the dynamic changes of the system. Based on the sensor data, predict the magnitude and direction of the wind load disturbance, generate a reverse control amount to offset the influence of the wind load disturbance on the system, superimpose the control instruction output by the prediction model and the reverse control amount, generate a compensated control instruction, ensure the real-time and accuracy of the control instruction, optimize the system response. Through the delay compensation module, the control stability and anti-disturbance ability of the hydraulic system can be improved, and the safe operation of the system in a complex environment can be ensured.

[0069] For example, assume that the IMU monitors that the wind load disturbance is F, the direction is θ, the prediction model outputs a control instruction u, and the time-delay transfer function is e -2S , the reverse control amount is -kF, where k is the compensation coefficient, and the compensated control instruction is u m = u - kF;

[0070] In the embodiment of the present invention, the detailed content of the collaborative prediction by the collaborative prediction module 404 is as follows:

[0071] Step a: Use a mechanical model software to establish a dynamic model of the bent cap structure. According to the dynamic model and the features extracted by the variational autoencoder, establish a prediction model, define the model inputs (such as variational autoencoder features, historical states, etc.) and outputs (future state predictions), perform state predictions, and conduct conventional verification and optimization on the model;

[0072] Step b: Design a reinforcement learning algorithm to learn the optimization strategy in the prediction model, such as deep Q network, policy gradient, etc. Define the state space, action space, and reward function of the reinforcement learning. The state space includes the current state of the construction platform (such as load, displacement, speed, etc.) and the future state output by the prediction model. The action space includes the control instructions of the construction platform, such as adjusting the hydraulic system, the rotation speed of the motor 301, etc. The reward function is set according to the control objectives of the construction platform, such as stability, efficiency, etc. Use historical monitoring data to train the reinforcement learning model, set the initial parameters of the model, such as the weights and biases of the neural network, set the training parameters, such as batch size, number of iterations, exploration rate (determining the frequency at which the model tries new actions), etc. Through iterative optimization, update the parameters of the reinforcement learning model and improve the control strategy;

[0073] Step c: The low-dimensional features extracted by the variational autoencoder are fused with real-time data to form a complete input vector. The fused input vector is input into the prediction model to predict the future state, providing prior knowledge for the prediction model and optimizing the control input.

[0074] Step d: Integrate the learned reinforcement learning strategy into the prediction model framework for real-time prediction and optimal control. Apply the optimized control input to the self-balancing control system 400 for precise control.

[0075] In the embodiment of the present invention, the detailed content of the sliding mode control performed by the control module 405 is as follows:

[0076] Step 1: Establish the dynamic model of the bent cap structure. According to the dynamic model and the low-dimensional data output by the variational autoencoder, design a suitable sliding surface equation, usually s(x) = 0, where x is the system state vector, including the low-dimensional features output by the variational autoencoder, to ensure that the sliding surface equation satisfies the desired dynamic characteristics, such as asymptotic stability, fast response, etc.

[0077] Step 2: Design the equivalent control law to keep the system moving on the sliding surface. The equivalent control law is obtained by solving the derivative of s(x) = 0 and setting it equal to zero, and the switching control law is used to overcome system uncertainties and external disturbances to ensure that the system state can quickly reach the sliding surface. The switching control law usually includes the sign function sign(s) to achieve fast response and robustness, ensuring that the system state can quickly reach and stay on the sliding surface. Combine the equivalent control law and the switching control law to form a comprehensive control law, which is used as the input of the actual control system.

[0078] Step 3: Verify the control effect of the sliding mode control in the simulation environment. Integrate the variational autoencoder and the sliding mode control in the simulation environment, use the low-dimensional features output by the variational autoencoder as the input of the sliding mode control, conduct simulation experiments, observe the dynamic response of the system under the sliding mode control, record key performance indicators, such as rise time, overshoot, settling time, etc., and adjust the parameters until the performance requirements, such as fast response, small overshoot, stability margin, etc., are met to improve the control performance of the system.

[0079] Step 4: Input the low-dimensional features extracted by the variational autoencoder as the real-time state into the sliding mode variable structure controller, and make necessary adjustments and optimizations. According to the actual test results, further optimize the parameters and structure of the variational autoencoder and the sliding mode control.

[0080] Embodiment 2

[0081] Refer to the attached Figure 6 As shown in the figure, another bent cap construction method for the self-balancing bent cap construction structure provided by the embodiment of the present invention includes the following steps:

[0082] S1. Assemble the capping beam slab 100 according to the design scheme of the capping beam structure. Install the underframe 104, balance assembly 200, support steel frame 101, walkway slab 102, and adjustment assembly 300 on the pier 500 in sequence. Adopt the segmented pouring method. First, pour the two ends of the capping beam, and then pour the middle part. During the pouring process, use the self-balancing control system 400 to adjust the balance assembly 200 in real time to keep the capping beam balanced. Set steel strands between the underframe 104 and the support steel frame 101 to strengthen the connection. Install sensors at the joints to monitor the capping beam slab 100 and provide raw data for subsequent processing;

[0083] S2. Collect sensor data and perform preprocessing, such as denoising, normalization, etc. Use the variational autoencoder to obtain low-dimensional features, and combine with the dynamic model to establish a prediction model. The prediction model is used to estimate the future state and provide information for the control strategy. Based on the future state and the current state output by the prediction model, design the sliding surface equation and control law of the sliding mode controller, providing key information input for the subsequent steps;

[0084] S3. Reinforcement learning is used to optimize the parameters of the sliding mode controller. Establish a reinforcement learning model to learn and optimize the control strategy according to historical data and real-time feedback. Adjust the control strategy according to real-time feedback to improve the control effect. Regularly retrain the prediction model and the reinforcement learning model with newly collected data;

[0085] S4. Evaluate the performance of the sliding mode controller according to the actual control effect. Adjust the parameters of the sliding mode controller, such as the gain coefficient, switching gain, etc., to optimize the control effect. If the parameter adjustment cannot meet the requirements, consider optimizing the structure of the sliding mode controller, such as improving the sliding surface design, introducing an adaptive mechanism, etc., to form an iterative optimization closed loop, continuously perform parameter adjustment and structure optimization, and finally feedback to the real-time monitoring and self-balancing control system 400 in S1 to ensure long-term stable balance control until balance is achieved and the construction of the capping beam is completed.

[0086] Self-balancing adjustment example: The sensor monitors that the inclination angle of the capping beam construction structure is 5 degrees, and the inclination speed is 0.1 degree / second. The variational autoencoder extracts the feature f. The prediction model predicts that the future inclination angle is 6 degrees, and the inclination speed is 0.3 degree / second. The sliding surface value s(x) = 5 + 2 * 0.1 = 5.2. Assume that the equivalent control law is -2, and the switching control law is k * sign(s(x)) = 3 * sign(5.2) = 3. The comprehensive control law is -2 + 3 = 1. Then, convert 1 into a drive instruction for the balance assembly 200. For example, the control input 1 corresponds to increasing the pressure by 10 units or the rotation speed by 100 revolutions per minute. For every 10 units increase in pressure, the balance assembly 200 extends 0.5 cm. The height adjustment value corresponding to the control input 1 is 0.5 cm.

[0087] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

[0088] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process can be rearranged without departing from the protection scope of the present disclosure. The appended method claims present the elements of the various steps in an exemplary order and are not intended to be limited to the specific order or hierarchy.

[0089] In the above detailed description, various features are combined in a single embodiment to simplify the present disclosure. This method of disclosure should not be interpreted as reflecting an intention that the embodiments of the claimed subject matter require more features than those expressly recited in each claim. On the contrary, as reflected in the appended claims, the present invention lies in a state less than all the features of the disclosed single embodiment. Therefore, the appended claims are hereby expressly incorporated into the detailed description, where each claim stands alone as a separate preferred embodiment of the present invention.

[0090] Those skilled in the art should also understand that the various illustrative logical blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments herein can be implemented as electronic hardware, computer software, or a combination thereof. To clearly illustrate the interchangeability of hardware and software, the above description of various illustrative components, blocks, modules, circuits, and steps has been generally described in terms of their functions. Whether such a function is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Skilled artisans can implement the described functions in a flexible manner for each specific application, but such implementation decisions should not be construed as departing from the protection scope of the present disclosure.

[0091] The steps of the methods or algorithms described in connection with the embodiments of this specification may be embodied directly as hardware, software modules executed by a processor, or a combination thereof. The software modules may be located in a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium well known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be an integral part of the processor. The processor and the storage medium may be located in an ASIC. The ASIC may be located in a user terminal. Of course, the processor and the storage medium may also exist as discrete components in the user terminal.

[0092] For a software implementation, the techniques described in this application may be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. These software codes may be stored in a memory unit and executed by a processor. The memory unit may be implemented within the processor or outside the processor, and in the latter case, it is coupled to the processor in a communicative manner by various means, which are well known in the art.

[0093] The foregoing description includes examples of one or more embodiments. Of course, it is not possible to describe all possible combinations of components or methods for the purpose of describing the above embodiments, but those of ordinary skill in the art should recognize that various embodiments may be further combined and arranged. Accordingly, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims. In addition, with respect to the term "comprising" used in the specification or claims, this term is inclusive in a manner similar to the term "including" as interpreted when used as a transitional word in a claim. Further, any use of the term "or" in the claims or specification is intended to mean "non-exclusive or".

Claims

1. A self-balancing cap beam construction structure, characterized in that: The invention comprises a cap beam plate (100), wherein the cap beam plate (100) comprises a supporting steel frame (101), a walkway plate (102) and a base frame (104), wherein the walkway plate (102) is laid on the upper surface of the supporting steel frame (101), and the base frame (104) is arranged below the supporting steel frame (101); A balancing assembly (200), the balancing assembly (200) being arranged between the base frame (104) and the supporting steel frame (101), the balancing assembly (200) comprising a cylinder (201), a plurality of telescopic rods (202) of decreasing sizes, and a mounting block (203), the cylinder (201) being sleeved outside the outermost telescopic rod (202), and the ends of the cylinder (201) and the telescopic rod (202) being provided with mounting blocks (203); A self-balancing control system (400) controls the balancing assembly (200) to perform automatic balancing adjustment according to the balancing state of the cap beam structure.

2. A self-balancing cap beam construction structure according to claim 1, characterized in that: The invention also comprises an adjustment component (300), wherein the adjustment component (300) is arranged on the outer side of the supporting steel frame (101), and the adjustment component (300) comprises a motor (301), a rotating shaft (302) and a folding plate (303), wherein the rotating shaft (302) is arranged at the output end of the motor (301), and the output end of the motor (301) is transmission-connected with the rotating shaft (302), and both ends of the rotating shaft (302) and one side of the motor (301) are screw-connected with a mounting plate (304), and the mounting plate (304) is bolt-connected with the base frame (104), and the rotating shaft (302) is bolt-connected with the bottom side of the folding plate (303).

3. A self-balancing cap beam construction structure according to claim 2, characterized in that: The supporting steel frame (101) is bolted to the walkway plate (102); a guardrail (103) is welded to the upper surface of the walkway plate (102); pier connection holes are provided on the surfaces of the walkway plate (102), the supporting steel frame (101) and the base frame (104); connection hoops are provided in the connection holes for connection; at least two balancing assemblies (200) are provided at the four bottom corners of the supporting steel frame (101); the balancing assemblies (200) in the same group are tilted and designed to be triangular with the base frame (104).

4. A self-balancing cap beam construction structure according to claim 3, characterized in that: A hydraulic pump, an oil cylinder and a motor (301) are arranged inside the cylinder barrel (201); the output end of the motor (301) is connected to the input end of the hydraulic pump through a coupling; the hydraulic pump is connected to the piston chamber of the oil cylinder through a hydraulic pipeline; the telescopic rod (202) is fixed on the piston of the oil cylinder; a connecting block (204) is arranged between the mounting block (203), the telescopic rod (202) and the cylinder barrel (201); the connecting block (204) is screw-connected to the telescopic rod (202) and the cylinder barrel (201); the connecting block (204) is rotatably connected to the mounting block (203); a motor is embedded in one side of the mounting block (203); the output shaft of the motor is screw-connected to the connecting block (204); the mounting block (203) is respectively bolt-connected to the supporting steel frame (101) and the base frame (104).

5. A self-balancing cap beam construction structure according to claim 4, characterized in that: The self-balancing control system (400) comprises a data acquisition module (401), wherein the data acquisition module (401) collects usage status data of the cap beam structure using sensors; A data fusion module (402), wherein the data fusion module (402) uses a weight fusion algorithm to assign weights to the data from each sensor and fuse them; A data dimension reduction module (403), wherein the data dimension reduction module (403) uses a variational autoencoder to perform dimension reduction processing on the fused high-order sensor data; A collaborative prediction module (404), wherein the collaborative prediction module (404) selects a suitable prediction model according to the data characteristics of the data acquisition module (401), establishes the prediction model, and optimizes the prediction model using a reinforcement learning algorithm; A control module (405), wherein the control module (405) is used to perform sliding mode control on the low-dimensional data output by the variational autoencoder.

6. A self-balancing cap beam construction structure according to claim 5, characterized in that: The collaborative prediction module (404) performs collaborative prediction in detail as follows: Step a, establishing a dynamic model of the cap beam structure, and establishing a prediction model based on the dynamic model and features extracted by the variational autoencoder to perform state prediction; Step b, designing a reinforcement learning algorithm to learn the optimization strategy in the prediction model, using historical monitoring data to train the reinforcement learning model, setting the initial parameters of the model, setting the training parameters, updating the parameters of the reinforcement learning model through iterative optimization, and improving the control strategy; Step c, using the low-dimensional features extracted by the variational autoencoder and the real-time data to fuse to form a complete input vector, and inputting the fused input vector into the prediction model to predict the future state and optimize the control input; Step d, integrating the learned reinforcement learning strategy into the prediction model framework, performing real-time prediction and optimization control, and applying the optimized control input to the self-balancing control system (400) for precise control.

7. A self-balancing cap beam construction structure according to claim 6, characterized in that: The details of the sliding mode control performed by the control module (405) are as follows: Step 1: Establish a dynamic model of the cap beam structure, and design a suitable sliding surface equation based on the dynamic model and the low-dimensional data output by the variational autoencoder, which is usually s(x)=0, where x is the system state vector, including the low-dimensional features output by the variational autoencoder; Step 2: Design an equivalent control law. The equivalent control law is obtained by solving the inverse of s(x)=0 and setting it equal to zero, as well as a switching control law, which is used to overcome system uncertainty and external disturbances. The switching control law usually includes a sign function sign(s). The equivalent control law and the switching control law are combined to form a comprehensive control law. The comprehensive control law is used as the input of the actual control system. Step 3: Verify the control effect of sliding mode control in a simulation environment and adjust the parameters until the performance requirements are met; Step 4: Input the low-dimensional features extracted by the variational autoencoder into the sliding mode variable structure controller as the real-time state, and make necessary adjustments and optimizations. According to the actual test results, further optimize the parameters and structure of the variational autoencoder and sliding mode control.

8. A cap beam construction method of a self-balancing cap beam construction structure, applied to a self-balancing cap beam construction structure according to any one of claims 1 to 7, characterized in that: The following steps are involved: S1, assembling the cap beam plate (100) according to the design scheme of the cap beam structure, sequentially installing the base frame (104), the balance assembly (200), the supporting steel frame (101), the walkway plate (102) and the adjustment assembly (300) on the pier (500), and setting a steel strand reinforcement connection between the base frame (104) and the supporting steel frame (101), installing sensors at the nodes to monitor the cap beam plate (100), and providing raw data for subsequent processing; S2, collects sensor data, performs preprocessing, uses variational autoencoders to obtain low-dimensional features, and builds a prediction model based on the future state and current state output by the prediction model. The sliding surface equation and control law of the sliding mode controller are designed to provide key information input for subsequent steps; S3, establish a reinforcement learning model to learn and optimize the control strategy based on historical data and real-time feedback, and adjust the control strategy based on real-time feedback; S4, evaluate the performance of the sliding mode controller according to the actual control effect, adjust the parameters of the sliding mode controller according to the evaluation results, and continue to adjust the parameters and optimize the structure until a balance is achieved and the construction of the cap beam is completed.

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