Jig frame device of prestressed steel cover beam and adjusting method

Abstract

The invention relates to the field of bridge manufacturing and transportation, and discloses a jig frame device of a prestressed steel cover beam and an adjusting method.The jig frame device comprises a plurality of supporting units, the multiple supporting units are in communication connection with a control unit, each supporting unit comprises a supporting part and a vertical supporting structure, and the supporting parts are connected to the vertical supporting structures in a vertically adjustable mode; the displacement detection assemblies are installed on the corresponding supporting units. The pressure detection assembly is arranged on the supporting part and feeds back a pressure signal to the control unit; and based on a preset optimization algorithm model, the control unit calculates the target adjustment amount for adjusting each supporting part by taking the linear error minimization of the steel cover beam and the pressure balance of each supporting point as optimization targets when the plurality of supporting units cooperatively support. The method has the beneficial effects that the linear precision of the steel cover beam is improved, the forming quality is effectively guaranteed, all supporting points are evenly stressed, local overload or instability is avoided, the construction safety and structural reliability are improved, and the construction efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of bridge manufacturing and transportation, and specifically to a prestressed steel cap beam jig and adjustment method. Background Technology

[0002] In the manufacturing process of large steel structures such as prestressed steel cap beams, the jig serves as a key tool for support and positioning, and its accuracy and adaptability directly affect the linear quality of the components and construction efficiency.

[0003] Existing support frame devices generally have the following defects: First, the structure is fixed and the height is not adjustable, making it impossible to dynamically respond to height changes caused by welding deformation, structural weight, or design changes. This can easily lead to deviations in the elevation of the support points, requiring repeated rework and correction. Second, the adjustment process relies on manual operation and experience-based judgment, making it difficult to achieve coordinated optimization control of multiple support points. Especially in the construction of complex alignments or large-span cap beams, it is difficult to simultaneously consider alignment accuracy, support stability, and construction efficiency, thus hindering the development of bridge manufacturing towards intelligence and lean manufacturing. Summary of the Invention

[0004] The technical problem this invention aims to solve is that current methods for adjusting prestressed steel cap beams rely heavily on manual experience and judgment, making it difficult to achieve coordinated and optimized control of multiple support points. This is especially true in the construction of complex or large-span cap beams, where it is difficult to simultaneously ensure alignment accuracy, support stability, and construction efficiency. The purpose of this invention is to provide a prestressed steel cap beam frame device and adjustment method that improves the alignment accuracy of the steel cap beam, effectively ensures the forming quality, ensures uniform stress on each support point, avoids local overload or instability, enhances construction safety and structural reliability, and improves construction efficiency.

[0005] This invention is achieved through the following technical solution:

[0006] A prestressed steel cap beam support frame device includes multiple support units, each communicatively connected to a control unit for vertically supporting the steel cap beam at multiple locations. Each support unit includes a support portion and a vertical support structure, the support portion being vertically adjustable and connected to the vertical support structure. A displacement detection component is installed on the corresponding support unit, feeding back the real-time height signal of the support portion to the control unit. A pressure detection component is installed on the support portion, used to detect the load on the corresponding support unit in real time and feeding back the pressure signal to the control unit. The control unit, based on a preset optimization algorithm model, calculates the target adjustment amount for each support portion, with the optimization objectives of minimizing the linear error of the steel cap beam when multiple support units work together and balancing the pressure at each support point.

[0007] The beneficial effects of this invention are that, by employing a collaborative control system composed of multiple independently adjustable support units, integrated displacement and pressure detection components, and a control unit with a built-in optimization algorithm, the system receives precise data support through the independently adjustable structure of each support unit and dual-channel sensors. The control unit, by real-time fusion of height and pressure data from all support points and running an optimization algorithm aimed at minimizing linear error and achieving pressure balance, can automatically calculate the globally optimal adjustment scheme, replacing manual trial and error and experience-based judgment. This improves the linear accuracy of the steel cap beam, effectively ensuring forming quality. Furthermore, through the coordinated control of force and position, the stress on each support point is uniform, avoiding local overload or instability, improving construction safety and structural reliability, and significantly reducing the time spent on repeated measurements and adjustments, thus significantly improving construction efficiency. It is particularly suitable for the manufacture of cap beams under complex conditions such as large spans and variable curvatures.

[0008] In some embodiments, each support unit further includes a base plate connected to the base frame. A column is connected to the upper end of the base plate, forming the vertical support structure. A mounting base is installed at the upper end of the column. The support portion includes a stud, and the mounting base has a threaded through hole. The stud engages with the threaded through hole and can move along the inner hole of the column. By setting up a support unit structure including a base plate, column, mounting base, and stud, overall stability is ensured. The column serves as a rigid support body, while the engagement of the stud with the threaded pair of the mounting base enables stepless and precise mechanical adjustment of the support height, replacing the drawbacks of the traditional welded fixed base frame which is not adjustable. This provides a reliable execution end for subsequent algorithm-based intelligent collaborative leveling.

[0009] In some embodiments, the pressure detection assembly includes a cylindrical pressure sensor and a mounting plate. The mounting plate is connected to the top of the stud, and the cylindrical pressure sensor is connected to the top of the mounting plate. A protective sleeve is also installed on the top of the mounting plate. The cylindrical pressure sensor is located inside the protective sleeve, and a buffer pad is provided at the top of the protective sleeve, contacting the top of the cylindrical pressure sensor. By directly connecting the cylindrical pressure sensor to the top of the stud via the mounting plate, and supplemented by the protective sleeve and buffer pad, the sensor can directly and accurately measure the load of the steel cap beam borne by the support, and the measured value is almost unaffected by mechanical structural deformation. The protective sleeve effectively isolates welding sparks, dust, and other on-site contamination, while the buffer pad avoids impact damage during the installation of the upper components, ensuring high accuracy and high reliability of pressure signal acquisition.

[0010] In some embodiments, the displacement detection assembly includes a magnetostrictive displacement sensor and a magnetic ring. The magnetostrictive displacement sensor is fixedly installed vertically in the lower section of the inner hole of the column, and the magnetic ring is sleeved on the end of the stud away from the support portion. By fixing the magnetostrictive displacement sensor inside the column and sleeve the magnetic ring on the stud, the sensor can accurately measure the absolute displacement of the stud (i.e., the support portion) in a non-contact manner in a fully enclosed clean environment. The inner hole of the column is cleverly utilized as a protective space to avoid magnetic interference and physical collisions at the construction site, enabling real-time monitoring of the support height.

[0011] In some embodiments, a locking nut is further included, which engages with the stud and abuts against the upper end of the mounting base. By providing a locking nut that engages with the stud and abuts against the upper end of the mounting base, a strong locking force can be generated by tightening the locking nut after the stud has been rotated and adjusted to the target height, effectively preventing the stud from rotating or settling due to vibration or load changes.

[0012] In some embodiments, a wrench portion is further included, which is disposed on the upper section of the stud and is in the shape of a polygonal plate. The polygonal plate-shaped wrench portion disposed on the upper section of the stud provides a convenient and efficient force application interface for height adjustment by manual intervention or in the absence of power drive.

[0013] The present invention also provides an adjustment method, implemented based on the prestressed steel cap beam jig device, comprising the following steps:

[0014] Data acquisition steps: Pressure data of each support unit is acquired in real time using cylindrical pressure sensors and magnetostrictive displacement sensors in each support unit. and altitude data ;

[0015] Optimization calculation steps: The control unit uses the collected pressure data and altitude data As the initial state input to the algorithm, based on the pre-stored target design alignment of the steel cap beam, the optimization algorithm is run to minimize the predicted alignment deviation and optimize the predicted pressure distribution, thereby solving for the target height adjustment amount of each support point that maximizes the overall optimization objective. ;

[0016] Adjustment execution steps: Adjust the amount based on the calculated target height. The control unit outputs adjustment instruction information to adjust the studs in each support unit so that the support part is adjusted to the corresponding target height;

[0017] Closed-loop verification steps: After the adjustment execution step is executed, return to the data acquisition step to re-acquire data, and repeat the optimization calculation step and adjustment execution step until the current height data is obtained. The deviation between the actual alignment and the target design alignment, and the current pressure data at each support point. The balance of all components meets the preset accuracy requirements. This transforms the frame adjustment from an open-loop operation relying on manual experience to a data-driven intelligent closed-loop control. By collecting data from the entire site in real time, using algorithms for global optimization, precise execution, and feedback verification, it systematically solves the problem of difficulty in coordinating multiple support points, achieving the optimal balance between alignment accuracy, support stability, and construction efficiency. Furthermore, closed-loop verification ensures that the final result strictly conforms to the design tolerance. Optimization calculations based on global information avoid repeated local adjustments, significantly improving work efficiency and first-pass yield.

[0018] In some embodiments, the optimization algorithm in the optimization calculation step is a genetic algorithm, which includes the following steps:

[0019] S1. Adjust the target height of each support component. As an optimization variable, and using the current pressure data and current altitude data As initial input, set the number of iterations for the genetic algorithm and the number of individuals to be solved in each generation of the population;

[0020] S2. Establish a height adjustment optimization configuration model, which includes an objective function and overall constraints, wherein the objective function is:

[0021] ;

[0022] in, This is the linear error function. For pressure equilibrium function, To adjust the efficiency function, For line type precision weights, To support stable weights, Weighted by construction efficiency. , and All of them were constructed such that smaller values ​​were considered better;

[0023] S3, Target height adjustment for each support component Encoding is performed to obtain the encoded value of the individual to be solved. Based on the overall constraints, an initial population is randomly generated from several individuals to be solved, which is called the parent population. The individuals to be solved in the parent population are called parent individuals. The encoded value of each parent individual includes the target height adjustment amount of each support. ;

[0024] S4. Input the encoding values ​​of each individual in the parent population into the height adjustment simulation system to perform height simulation, and obtain the set of actual height values ​​that each support needs to be adjusted. The set of actual height values ​​is the simulation result of the height adjustment simulation.

[0025] S5. Calculate the objective function value of each individual in the parent population based on each simulation result, and then calculate and sort the fitness value of each individual in the parent population based on the fitness function.

[0026] S6. Save the top M parent individuals with the largest fitness values ​​in the parent population. Select parent individuals from all parent individuals other than the top M parent individuals with the largest fitness values ​​through a roulette wheel and perform crossover and mutation operations to obtain offspring individuals. Calculate the fitness values ​​of the offspring individuals after crossover and mutation and sort them. Reinsert the offspring individuals into the parent population according to their fitness values. Select a set number of individuals to be solved to form a new parent population. Then return to S4.

[0027] S7. Repeat S4-S6 until the required number of iterations is reached or the objective function value is within a specified threshold range. The resulting parent population is the feasible solution set, and the parent individuals in the parent population are the feasible individuals. By encoding the height adjustment amount as a chromosome, constructing an objective function that includes linear error and pressure balance, and using a population evolution mechanism for iterative optimization, the algorithm can efficiently search for the globally optimal or suboptimal set of adjustment amounts from a large number of candidate solutions. This replaces the inefficient traditional trial-and-error adjustment mode that relies on human experience. In particular, by establishing a simulation system for pre-evaluation of solutions, the algorithm can predict and quantitatively compare the adjustment effects in advance, significantly improving the scientificity and reliability of multi-support point collaborative optimization in complex linear scenarios.

[0028] In some embodiments, in step S2 It is 0.5. It is 0.3. The value is 0.2. This ensures that the optimization process prioritizes line accuracy (50%) while also considering support stability (30%) and construction efficiency (20%). This allows the genetic algorithm to follow scientific decision-making principles when searching for the optimal solution, rationally allocating support loads and controlling adjustment costs while ensuring the forming accuracy of the steel cap beam. This avoids the problem of optimization results deviating from actual engineering needs due to improper weight settings, and improves the operability and engineering applicability of the optimization results.

[0029] In some embodiments, the fitness function is: .

[0030] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0031] 1. By setting up a support unit structure including a base plate, columns, mounting base and studs, the overall stability is ensured. The columns serve as the main rigid support, while the threaded pair between the studs and the mounting base enables stepless and precise mechanical adjustment of the support height, replacing the drawbacks of the traditional welded fixed jig that is not adjustable.

[0032] 2. By encoding the height adjustment amount as a chromosome, constructing an objective function that includes linear error and pressure balance, and using a population evolution mechanism for iterative optimization, the algorithm can efficiently search for the globally optimal or suboptimal set of adjustment amounts from a large number of candidate solutions. This replaces the inefficient traditional trial-and-error adjustment mode that relies on human experience. In particular, by establishing a simulation system for pre-evaluation of the solution, the algorithm can predict and quantitatively compare the adjustment effect in advance, significantly improving the scientificity and reliability of multi-support point collaborative optimization in complex linear scenarios. Attached Figure Description

[0033] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0034] Figure 1 This is a structural diagram of the device in this invention;

[0035] Figure 2 This is a schematic diagram of the installation of the device and the herringbone slope cap beam in this invention.

[0036] The attached diagram shows the markings and corresponding component names:

[0037] Support unit 100, base plate 10, column 11, connecting plate 111, magnetostrictive displacement sensor 20, magnetic ring 21, stud 30, wrench part 31, locking nut 40, protective sleeve 50, mounting plate 51, column pressure sensor 52, buffer pad 53, mounting base 60, and cover beam 70. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0039] Throughout this specification, references to "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with that embodiment or example is included in at least one embodiment of the invention. Therefore, the phrases "an embodiment," "an example," "an example," or "an example" appearing in various places throughout the specification do not necessarily refer to the same embodiment or example. Furthermore, specific features, structures, or characteristics can be combined in one or more embodiments or examples in any suitable combination and / or sub-combination. Moreover, those skilled in the art will understand that the illustrations provided herein are for illustrative purposes and are not necessarily drawn to scale. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0040] In the description of this invention, the terms "front", "rear", "left", "right", "up", "down", "vertical", "horizontal", "high", "low", "inner", and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting the scope of protection of this invention.

[0041] The terms "first," "second," etc., used in this invention are merely for clarity of description and are not intended to limit any order or emphasize importance. Furthermore, the term "connection" as used herein, unless otherwise specified, can refer to a direct connection or an indirect connection via other components.

[0042] Example

[0043] like Figure 1 and Figure 2 As shown, this embodiment 1 provides a prestressed steel cap beam frame device, including multiple support units 100, which are communicatively connected to a control unit for vertically supporting the steel cap beam 70 at multiple locations. Each support unit includes a support portion and a vertical support structure, with the support portion being vertically adjustable and connected to the vertical support structure. A displacement detection component is installed on the corresponding support unit to feed back the height signal of the support portion monitored in real time to the control unit. A pressure detection component is installed on the support portion to detect the load on the corresponding support unit in real time and feed back the pressure signal to the control unit. The control unit, based on a preset optimization algorithm model, calculates the target adjustment amount for adjusting each support portion, with the optimization objectives being minimizing the linear error of the steel cap beam when multiple support units work together and balancing the pressure at each support point.

[0044] See Figure 1 Each support unit further includes a base plate 10 connected to the base frame. A column 11 is connected to the upper end of the base plate 10, forming the vertical support structure. A mounting base 60 is installed at the upper end of the column 11. The support includes a stud 30, and the mounting base 60 has a threaded through hole. The stud 30 engages with the threaded through hole and can move along the inner hole of the column 11. By setting up a support unit structure including the base plate 10, column 11, mounting base 60, and stud 30, overall stability is ensured. The column 11 serves as a rigid support body, while the engagement of the threaded pair between the stud 30 and the mounting base 60 enables stepless and precise mechanical adjustment of the support height, replacing the drawbacks of the traditional welded fixed frame which is not adjustable. This provides a reliable execution end for subsequent algorithm-based intelligent collaborative leveling.

[0045] See Figure 1 The pressure detection assembly includes a cylindrical pressure sensor 52 and a mounting plate 51. The mounting plate 51 is connected to the top of the stud 30, and the cylindrical pressure sensor 52 is connected to the top of the mounting plate 51. A protective sleeve 50 is also installed on the top of the mounting plate 51. The cylindrical pressure sensor 52 is located inside the protective sleeve 50, and a buffer pad 53 is provided on the top of the protective sleeve 50, which contacts the top of the cylindrical pressure sensor 52. By directly connecting the cylindrical pressure sensor 52 to the top of the stud 30 via the mounting plate 51, and supplemented by the protective sleeve 50 and the buffer pad 53, the sensor can directly and accurately measure the load of the steel cap beam borne by the support, and the measured value is almost unaffected by mechanical structural deformation. The protective sleeve 50 effectively isolates welding sparks, dust, and other on-site contamination, while the buffer pad 53 avoids impact damage during the installation of the upper components, ensuring high accuracy and high reliability of pressure signal acquisition.

[0046] Specifically, the buffer pad 53 is made of polyurethane elastomer, and the elastic modulus can be adjusted according to the formula. It can effectively absorb the impact energy when the upper components (such as the bottom plate 10 of the cover beam or temporary pressure block) are installed, and protect the lower column pressure sensor 52 from instantaneous overload impact.

[0047] See Figure 1The displacement detection assembly includes a magnetostrictive displacement sensor 20 and a magnetic ring 21. The magnetostrictive displacement sensor 20 is fixedly installed vertically in the lower section of the inner hole of the column 11, and the magnetic ring 21 is sleeved on the end of the stud 30 away from the support. By fixing the magnetostrictive displacement sensor 20 inside the column 11 and sleeve the magnetic ring 21 on the stud 30, the sensor can accurately measure the absolute displacement of the stud 30 (i.e., the support) in a non-contact manner in a fully enclosed clean environment. The inner hole of the column 11 is cleverly utilized as a protective space to avoid magnetic interference and physical collisions at the construction site, enabling real-time monitoring of the support height.

[0048] See Figure 1 It also includes a locking nut 40, which engages with the stud 30 and abuts against the upper end of the mounting base 60. By providing a locking nut 40 that engages with the stud 30 and abuts against the upper end of the mounting base 60, a strong locking force can be generated by tightening the locking nut 40 after the stud 30 has been rotated and adjusted to the target height, effectively preventing the stud 30 from rotating or settling due to vibration or load changes.

[0049] See Figure 1 It also includes a wrench part 31, which is disposed on the upper section of the stud 30 and is in the shape of a polygonal plate. The polygonal plate-shaped wrench part 31 disposed on the upper section of the stud 30 provides a convenient and efficient force application interface for height adjustment by manual intervention or in the absence of power drive.

[0050] See Figure 1 The column 11 is in the shape of a circular tube, and a connecting plate 111 is provided on the inner side of the column 11. The magnetostrictive displacement sensor 20 is mounted on the connecting plate 111.

[0051] Example 2

[0052] This embodiment 2 provides an adjustment method based on the prestressed steel cap beam jig device, including the following steps:

[0053] Data acquisition steps: Pressure data of each support unit 100 is acquired in real time using the cylindrical pressure sensor 52 and the magnetostrictive displacement sensor 20. and altitude data ;

[0054] Optimization calculation steps: The control unit uses the collected pressure data and altitude data As the initial state input to the algorithm, based on the pre-stored target design alignment of the steel cap beam, the optimization algorithm is run to minimize the predicted alignment deviation and optimize the predicted pressure distribution, thereby solving for the target height adjustment amount of each support point that maximizes the overall optimization objective. ;

[0055] Adjustment execution steps: Adjust the amount based on the calculated target height. The control unit outputs adjustment instruction information to adjust the studs in each support unit so that the support part is adjusted to the corresponding target height;

[0056] Closed-loop verification steps: After the adjustment execution step is executed, return to the data acquisition step to re-acquire data, and repeat the optimization calculation step and adjustment execution step until the current height data is obtained. The deviation between the actual alignment and the target design alignment, and the current pressure data at each support point. The balance of all components meets the preset accuracy requirements. This transforms the frame adjustment from an open-loop operation relying on manual experience to a data-driven intelligent closed-loop control. By collecting data from the entire site in real time, using algorithms for global optimization, precise execution, and feedback verification, it systematically solves the problem of difficulty in coordinating multiple support points, achieving the optimal balance between alignment accuracy, support stability, and construction efficiency. Furthermore, closed-loop verification ensures that the final result strictly conforms to the design tolerance. Optimization calculations based on global information avoid repeated local adjustments, significantly improving work efficiency and first-pass yield.

[0057] Specifically, the optimization algorithm in the optimization calculation step is a genetic algorithm, which includes the following steps:

[0058] S1. Adjust the target height of each support component. As an optimization variable, and using the current pressure data and current altitude data As initial input, set the number of iterations for the genetic algorithm and the number of individuals to be solved in each generation of the population; The value ranges from -300mm to +300mm.

[0059] S2. Establish a height adjustment optimization configuration model, which includes an objective function and overall constraints, wherein the objective function is:

[0060] ;

[0061] in, This is the linear error function. For pressure equilibrium function, To adjust the efficiency function, For line type precision weights, To support stable weights, Weighted by construction efficiency. , and All of them were constructed such that smaller values ​​were considered better;

[0062] The formula for calculating the linearity error function is as follows:

[0063] ;

[0064] in, : at the j-th detection position At this location, the predicted height is based on the adjusted support points. The actual predicted line shape value is obtained through interpolation (such as cubic splines). In the same location The target design line shape value at the location (pre-stored in the system), M: the total number of detection points selected along the length of the steel cap beam.

[0065] The formula for calculating the pressure equilibrium function is as follows:

[0066] ;

[0067] in, : No. The predicted pressure value after adjustment of each support point. Its calculation can be based on a simplified mechanical model: ,in This is the current measured pressure. For the first The equivalent support stiffness of each support point (which can be obtained through calibration). For adjustment amount. : The average predicted pressure across all N support points. N: The total number of support points.

[0068] The formula for calculating the adjustment efficiency function is as follows:

[0069] ;

[0070] in, : No. The target height adjustment amount (decision variable) for each support point. N: Total number of support points.

[0071] S3, Target height adjustment for each support component Encoding is performed to obtain the encoded value of the individual to be solved. Based on the overall constraints, an initial population is randomly generated from several individuals to be solved, which is called the parent population. The individuals to be solved in the parent population are called parent individuals. The encoded value of each parent individual includes the target height adjustment amount of each support. ;

[0072] S4. Input the encoding values ​​of each individual in the parent population into the height adjustment simulation system to perform height simulation, and obtain the set of actual height values ​​that each support needs to be adjusted. The set of actual height values ​​is the simulation result of the height adjustment simulation.

[0073] Including individual fitness assessment: For each individual in the parent population, perform the following calculations: (a) decode its encoded value to obtain the set of target height adjustment values ​​it represents. (b) Predictive calculation: based on the above And the current height data as the initial input. and current pressure data ,calculate:

[0074] Predicted height of each support point ;

[0075] Based on all Predicted alignment of steel cap beams;

[0076] based on and Based on the preset support stiffness parameters, the predicted pressure distribution is calculated. (c) Objective function calculation: Calculate the line shape error value based on the deviation between the predicted line shape and the target design line shape. According to the predicted pressure distribution , Calculate the pressure equalization value (For example, the variance of pressure values); according to Calculate the regulation efficiency value Then calculate the objective function value of the individual. (d) Fitness value transformation: Based on the objective function value F, the fitness function calculates its fitness value. ;

[0077] S5. Calculate the objective function value of each individual in the parent population based on each simulation result, and then calculate and sort the fitness value of each individual in the parent population based on the fitness function.

[0078] Genetic evolutionary operations: based on the fitness values ​​of all individuals. The parent population is subjected to selection, crossover, and mutation operations to generate the offspring population.

[0079] S6. Save the top M parent individuals with the largest fitness values ​​in the parent population. Select parent individuals from all parent individuals other than the top M parent individuals with the largest fitness values ​​through a roulette wheel and perform crossover and mutation operations to obtain offspring individuals. Calculate the fitness values ​​of the offspring individuals after crossover and mutation and sort them. Reinsert the offspring individuals into the parent population according to their fitness values. Select a set number of individuals to be solved to form a new parent population. Then return to S4.

[0080] S7. Repeat S4-S6 until the required number of iterations is reached or the objective function value is within a specified threshold range. The resulting parent population is the feasible solution set, and the parent individuals in the parent population are the feasible individuals. By encoding the height adjustment amount as a chromosome, constructing an objective function that includes linear error and pressure balance, and using a population evolution mechanism for iterative optimization, the algorithm can efficiently search for the globally optimal or suboptimal set of adjustment amounts from a large number of candidate solutions. This replaces the inefficient traditional trial-and-error adjustment mode that relies on human experience. In particular, by establishing a simulation system for pre-evaluation of solutions, the algorithm can predict and quantitatively compare the adjustment effects in advance, significantly improving the scientificity and reliability of multi-support point collaborative optimization in complex linear scenarios.

[0081] In some embodiments, in step S2 It is 0.5. It is 0.3. The value is 0.2. This ensures that the optimization process prioritizes line accuracy (50%) while also considering support stability (30%) and construction efficiency (20%). This allows the genetic algorithm to follow scientific decision-making principles when searching for the optimal solution, rationally allocating support loads and controlling adjustment costs while ensuring the forming accuracy of the steel cap beam. This avoids the problem of optimization results deviating from actual engineering needs due to improper weight settings, and improves the operability and engineering applicability of the optimization results.

[0082] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A prestressed steel cap beam frame device, characterized in that, include: Multiple support units, each communicatively connected to a control unit, are used to vertically support the steel cap beam at multiple locations. Each support unit includes a support part and a vertical support structure, wherein the support part is vertically adjustable and connected to the vertical support structure. The displacement detection component is installed on the corresponding support unit and feeds back the height signal of the support part monitored in real time to the control unit; A pressure detection component is disposed on the support portion for real-time detection of the load on the corresponding support unit and feeding back the pressure signal to the control unit; The control unit, based on a preset optimization algorithm model, calculates the target adjustment amount for each of the support components, with the optimization objectives being to minimize the linear error of the steel cap beam and to balance the pressure at each support point when multiple support units work together.

2. The prestressed steel cap beam frame device according to claim 1, characterized in that, Each of the support units also includes a base plate connected to the base plate. The upper end of the base plate is connected to a column, which constitutes the vertical support structure. A mounting base is installed at the upper end of the column. The support part includes a stud, and the mounting base is provided with a threaded through hole. The stud engages with the threaded through hole and can move along the inner hole of the column.

3. The prestressed steel cap beam frame device according to claim 2, characterized in that, The pressure detection assembly includes a cylindrical pressure sensor and a mounting plate. The mounting plate is connected to the top of the stud, and the cylindrical pressure sensor is connected to the top of the mounting plate. A protective sleeve is also installed on the top of the mounting plate. The cylindrical pressure sensor is located inside the protective sleeve. A buffer pad is provided on the top of the protective sleeve, and the buffer pad is in contact with the top of the cylindrical pressure sensor.

4. The prestressed steel cap beam frame device according to claim 2, characterized in that, The displacement detection assembly includes a magnetostrictive displacement sensor and a magnetic ring. The magnetostrictive displacement sensor is fixedly installed vertically in the lower section of the inner hole of the column, and the magnetic ring is sleeved on the end of the stud away from the support.

5. The prestressed steel cap beam formwork device according to claim 2, characterized in that, It also includes a locking nut, which is screwed into the stud and abuts against the upper end of the mounting base.

6. The prestressed steel cap beam formwork device according to claim 2, characterized in that, It also includes a wrench part, which is disposed on the upper section of the stud and is in the shape of a polygonal plate.

7. An adjustment method, characterized in that, The implementation of the prestressed steel cap beam frame device according to any one of claims 1-6 includes the following steps: Data acquisition steps: Pressure data of each support unit is acquired in real time using cylindrical pressure sensors and magnetostrictive displacement sensors in each support unit. and altitude data ; Optimization calculation steps: The control unit uses the collected pressure data and altitude data As the initial state input to the algorithm, based on the pre-stored target design alignment of the steel cap beam, the optimization algorithm is run to minimize the predicted alignment deviation and optimize the predicted pressure distribution, thereby solving for the target height adjustment amount of each support point that maximizes the overall optimization objective. ; Adjustment execution steps: Adjust the amount based on the calculated target height. The control unit outputs adjustment instruction information to adjust the studs in each support unit so that the support part is adjusted to the corresponding target height; Closed-loop verification steps: After the adjustment execution step is executed, return to the data acquisition step to re-acquire data, and repeat the optimization calculation step and adjustment execution step until the current height data is obtained. The deviation between the actual alignment and the target design alignment, and the current pressure data at each support point. The balance of all components meets the preset accuracy requirements.

8. The adjustment method according to claim 7, characterized in that, The optimization algorithm in the optimization calculation step is a genetic algorithm, which includes the following steps: S1. Adjust the target height of each support component. As an optimization variable, and using the current pressure data and current altitude data As initial input, set the number of iterations for the genetic algorithm and the number of individuals to be solved in each generation of the population; S2. Establish a height adjustment optimization configuration model, which includes an objective function and overall constraints, wherein the objective function is: ； in, This is the linear error function. For pressure equilibrium function, To adjust the efficiency function, For line type precision weights, To support stable weights, Weighted by construction efficiency. , and All of them were constructed such that smaller values ​​were considered better; S3, Target height adjustment for each support component Encoding is performed to obtain the encoded value of the individual to be solved. Based on the overall constraints, an initial population is randomly generated from several individuals to be solved, which is called the parent population. The individuals to be solved in the parent population are called parent individuals. The encoded value of each parent individual includes the target height adjustment amount of each support. ; S4. Input the encoding values ​​of each individual in the parent population into the height adjustment simulation system to perform height simulation, and obtain the set of actual height values ​​that each support needs to be adjusted. The set of actual height values ​​is the simulation result of the height adjustment simulation. S5. Calculate the objective function value of each individual in the parent population based on each simulation result, and then calculate and sort the fitness value of each individual in the parent population based on the fitness function. S6. Save the top M parent individuals with the largest fitness values ​​in the parent population. Select parent individuals from all parent individuals other than the top M parent individuals with the largest fitness values ​​through a roulette wheel and perform crossover and mutation operations to obtain offspring individuals. Calculate the fitness values ​​of the offspring individuals after crossover and mutation and sort them. Reinsert the offspring individuals into the parent population according to their fitness values. Select a set number of individuals to be solved to form a new parent population. Then return to S4. S7. Repeat S4-S6 until the number of iterations is reached or the objective function value is within the specified threshold range. The resulting parent population is the feasible solution set, and the parent individuals in the parent population are the feasible individuals.

9. The adjustment method according to claim 8, characterized in that, In step S2 It is 0.

5. It is 0.

3. It is 0.

2.

10. The adjustment method according to claim 8, characterized in that, The fitness function is: .

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