A method for controlling axial force of servo steel support

Abstract

The present invention provides a method for controlling the axial force of a servo steel support, comprising the following steps: establishing a finite element numerical calculation model, wherein the finite element numerical calculation model is used to calculate the deformation of a servo-supported foundation pit retaining structure and divide the foundation pit excavation process into multiple excavation steps; establishing optimization constraints, wherein the optimization constraints are based on the excavation steps and foundation pit environmental protection requirements and construction safety requirements; based on the optimization constraints and a genetic algorithm, jointly iteratively solving the finite element numerical technology model and the genetic algorithm to calculate the optimal axial force value of each excavation step; and using the optimal axial force value of each excavation step for the hydraulic servo compensation amount of each excavation step.

Description

Technical Field

[0001] The invention relates to the field of servo steel support axial force design in soft soil deep foundation pit engineering, and mainly relates to a servo steel support axial force control method. Background Art

[0002] With the rapid development of urban construction, the scale and depth of foundation pit excavations in engineering projects are increasing. At the same time, the complex surrounding environment has led to increasingly stringent requirements for controlling foundation pit deformation. In recent years, the steel support axial force servo system has been widely used in deep foundation pit projects with high environmental protection requirements by dynamically controlling axial force, compensating for the axial force loss experienced by traditional steel supports.

[0003] Chinese patent CN108052782B proposes a method for determining the axial force of a servo steel support system, using maximum displacement as the control objective. This method establishes a planar model of the elastic foundation beam and the control equilibrium equation for the servo system's elastic foundation beam. By modifying the stiffness matrix and the resultant force matrix, the deformation and internal forces corresponding to the modified axial force are calculated. Through repeated trial and error calculations, the final optimized axial force value is obtained.

[0004] However, in practical application, this method has certain problems. First, it ignores the specific excavation process and simply simplifies it as a static equilibrium problem. It does not consider factors such as the excavation depth of the excavation step, which is not conducive to fine-grained control of the deformation of the retaining structure. Second, controlling only the displacement of a single support is also not conducive to considering the systematic relationship between the support systems. Summary of the Invention

[0005] The embodiment of the present application solves the problem in the prior art of not considering the dynamic construction factors of step-by-step excavation of foundation pits and step-by-step support by providing a method for controlling the axial force of a servo steel support, realizes quantitative and refined control of the deformation of the retaining structure, and provides a reasonable control scheme for the practical application of the steel support axial force servo system.

[0006] The present invention provides a method for controlling the axial force of a servo steel support, comprising the following steps:

[0007] S1) establishing a finite element numerical calculation model, wherein the finite element numerical calculation model is used to calculate the deformation of the servo-supported foundation pit retaining structure and divide the foundation pit excavation process into multiple excavation steps;

[0008] S2) establishing optimization constraints, wherein the optimization constraints are based on the excavation steps and foundation pit environmental protection requirements and construction safety requirements;

[0009] S3) performing a joint iterative solution on the finite element numerical technology model and the genetic algorithm based on the optimization constraints and the genetic algorithm to calculate the optimal axial force value for each excavation step;

[0010] S4) Using the optimal axial force value of each excavation step as the hydraulic servo compensation amount of each excavation step.

[0011] Preferably, in the method for controlling the servo steel support axial force, step S1 further comprises:

[0012] Establish finite element model of servo steel support foundation pit;

[0013] Establish the finite element model of foundation pit retaining structure;

[0014] Establish a finite element model of the soil in the pit;

[0015] Establish finite element models of ordinary steel support, concrete base steel support and servo steel support.

[0016] Preferably, in the control method of the servo steel support axial force, the optimization constraint condition calculation expression is:

[0017]

[0018] Wherein, f(x) is the function to be optimized, and the optimization function takes the minimum maximum deformation value of the maintenance structure as the optimization goal;

[0019] The independent variable xi is the design axial force of the servo steel support at each excavation step;

[0020] U max is the maximum deformation value of the surrounding structure;

[0021] F max The maximum axial force that can be sustained without losing stability, based on the support material, length, and constraints at both ends;

[0022] U a To determine the maximum allowable horizontal deformation of the retaining structure based on the excavation depth and foundation pit environmental protection requirements.

[0023] Preferably, in the control method of the servo steel support axial force, the genetic algorithm includes a convergence criterion, and the convergence criterion is achieved by setting the maximum number of generations, the maximum calculation time, and the individual fitness variance.

[0024] Preferably, in the method for controlling the servo steel support axial force, step S3 further comprises:

[0025] S31) generating an initial population, wherein the initial population is a plurality of randomly generated groups of design axial force values ​​of the servo steel supports including each of the excavation steps;

[0026] S32) Substituting the initial population into the finite element numerical calculation model, calculating the deformation results of the enclosure structure under different design axial force combination values, and selecting the optimal result of the enclosure structure deformation results under the different design axial force combination values ​​as the global optimal individual;

[0027] S33) applying the genetic algorithm to the initial population to obtain a progeny population, wherein the progeny population is a plurality of sets of design axial force values ​​of the servo steel supports for each excavation step regenerated under the optimization constraint condition, substituting each axial force combination value of the progeny population into a finite element model to calculate deformation, selecting the optimal individual in the progeny based on the deformation result, and updating the globally optimal individual;

[0028] S34) Repeatedly execute S33, continuously generate new offspring populations, and continuously update the globally optimal individuals until the termination condition of the convergence criterion is met, and then output the result as the globally optimal individual.

[0029] Preferably, in the method for controlling the servo steel support axial force, the individual fitness variance is set to be less than 0.01.

[0030] Preferably, in the method for controlling the servo steel support axial force, the genetic algorithm is written using MATLAB.

[0031] Preferably, in the method for controlling the axial force of the servo steel support, the finite element model of the servo steel support adopts a composite boundary condition of nonlinear spring elements and variable concentrated forces to simulate the support under different excavation steps.

[0032] The embodiment of the present application further provides a servo steel support axial force device, comprising:

[0033] a memory for storing instructions executable by a processor;

[0034] The processor is used to execute the instructions to implement the control method of the servo steel support axial force.

[0035] An embodiment of the present application further provides a computer-readable storage medium, characterized in that a computer program is stored on the storage medium, and when the computer program is executed by a processor, the method for controlling the servo steel support axial force is implemented.

[0036] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0037] 1. By establishing a finite element numerical calculation model and dividing the foundation pit excavation process into multiple excavation steps, precise control of multiple excavation step data is achieved.

[0038] 2. The use of genetic algorithm and finite element numerical calculation model iterative calculation method makes the calculation process more simplified and automated. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 Flowchart of a method for controlling the axial force of a servo steel support according to an embodiment of the present invention;

[0040] Figure 2 A flowchart of a combined calculation of a servo steel support axial force design method according to an embodiment of the present invention;

[0041] Figure 3A and Figure 3B Schematic diagram of a physical model of a servo steel support axial force design method according to an embodiment of the present invention;

[0042] Figure 4 is a schematic diagram of a three-dimensional numerical model according to an embodiment of the present invention;

[0043] Figure 5 Schematic diagram of excavation steps according to an embodiment of the present invention;

[0044] Figure 6 is a schematic diagram of excavation steps according to an embodiment of the present invention;

[0045] Figure 7 Schematic diagram of the convergence process of the genetic algorithm according to an embodiment of the present invention.

[0046] Reference numerals:

[0047] Finite element numerical calculation model-100;

[0048] Foundation pit retaining structure-10;

[0049] Beam-10A;

[0050] Soil in the pit -11;

[0051] Soil spring unit-11A;

[0052] Ordinary steel support-12;

[0053] Concrete steel support 13;

[0054] Spring unit 12A;

[0055] Servo steel support-14;

[0056] Nonlinear spring unit 13A;

[0057] Variable Concentration Force-14A;

[0058] Consider the soil pressure outside the pit -15A;

[0059] Axial force applying equipment-15. DETAILED DESCRIPTION

[0060] The detailed features and advantages of the present invention are described in detail below in the specific embodiments, and the content is sufficient to enable any person skilled in the art to understand the technical content of the present invention and implement it accordingly. Based on the description, claims, and drawings disclosed in this specification, those skilled in the art can easily understand the relevant purposes and advantages of the present invention.

[0061] In order to solve the problems in the background technology, the present invention proposes a method for controlling the axial force of a servo steel support. Figure 1 , which shows a flow chart of a method according to an embodiment of the present invention, as shown in Figure 1 As shown, the present invention proposes a method for controlling the axial force of a servo steel support, comprising the following steps:

[0062] S1) establishing a finite element numerical calculation model 100, wherein the finite element numerical calculation model 100 is used to calculate the deformation of the servo-supported foundation pit retaining structure and divide the foundation pit excavation process into multiple excavation steps;

[0063] S2) establishing optimization constraints, wherein the optimization constraints are based on the excavation steps and foundation pit environmental protection requirements and construction safety requirements;

[0064] S3) performing a joint iterative solution on the finite element numerical technology model and the genetic algorithm based on the optimization constraints and the genetic algorithm to calculate the optimal axial force value for each excavation step;

[0065] S4) Using the optimal axial force value of each excavation step as the hydraulic servo compensation amount of each excavation step.

[0066] Figure 2 The following is a flowchart of a combined operation of a servo steel support axial force control method according to an embodiment of the present invention. Figure 2 The specific steps of the method for controlling the servo steel support axial force proposed by the present invention are further described.

[0067] Step S1: establishing a finite element numerical calculation model 100, wherein the finite element numerical calculation model 100 is used to calculate the deformation of the servo-supported foundation pit retaining structure and divide the foundation pit excavation process into multiple excavation steps.

[0068] Figure 3BThis is a schematic diagram of a finite element numerical calculation model 100. The finite element numerical calculation model 100 is mainly used to calculate the deformation of the retaining structure under a certain design. The foundation pit excavation process is divided into multiple excavation steps, and the composite boundary conditions of nonlinear spring units 13A and variable concentrated forces 14A are used to simulate the servo steel supports under different excavation steps. At the same time, the model ignores the vertical compression deformation of the foundation pit retaining structure 10. The horizontal base coefficient of the soil spring unit 11A in the pit changes linearly along the depth direction. At the same time, it is assumed that during the active axial force compensation process, the compression deformation of the support is absorbed by the axial force application equipment, which has no effect on the horizontal displacement of the retaining structure.

[0069] Establishing the finite element numerical calculation model further includes:

[0070] Establish the finite element model of servo steel support foundation pit P;

[0071] Establish the finite element model of foundation pit retaining structure 10;

[0072] Establish a finite element model of the soil in the pit;

[0073] Finite element models of ordinary steel support 12, base concrete steel support 13 and servo steel support 14 are established.

[0074] like Figure 3A As shown in the figure, it is a simplified schematic diagram of the calculation model and physical model of the plane. Figure 3A and Figure 3B As shown, the foundation pit excavation process is divided into multiple excavation steps. By determining the calculation parameters such as support stiffness and soil spring stiffness, a servo steel support foundation pit P finite element model is established; the foundation pit retaining structure 10 is simulated by a beam 10A with a certain stiffness; the soil 11 in the pit is simulated by a soil spring unit 11A; the ordinary steel support 12 and the concrete steel support 13 are both simulated by a spring unit 12A; the servo steel support 14 uses a composite boundary condition of a nonlinear spring unit 13A and a variable concentrated force 14A to simulate the support under different excavation steps. Since the axial force of the servo steel support 14 changes with the excavation, the soil can be approximately regarded as a quasi-static state, and the static earth pressure theory is used to consider the effect of the earth pressure 15A outside the pit. At the same time, it is assumed that during the active compensation of the axial force, the compressive deformation of the support is absorbed by the axial force application device 15, which has no effect on the horizontal displacement of the foundation pit retaining structure 10.

[0075] Step S2: establishing optimization constraints, wherein the optimization constraints are based on the excavation steps and foundation pit environmental protection requirements and construction safety requirements.

[0076] The optimization constraint is used to limit the characteristics of the axial force combination value. The optimization constraint is: the design axial force of the servo steel support 14 in each excavation step is used as the independent variable xi, and in each excavation step, the maximum horizontal deformation allowable value U of the enclosure structure is determined according to the excavation depth and the foundation pit environmental protection requirements. a , so that under the action of the optimized design axial force, the maximum deformation value U of the enclosure structure max Less than the specified value; at the same time, according to the material, length, and constraints at both ends of the support, calculate the maximum axial force F that the support can withstand without losing stability. max , ensuring that the optimized design axial force does not cause vertical or lateral instability in the servo steel support 14, thereby improving construction safety. The specific values ​​of each parameter in the constraint conditions are determined based on the actual project design and the importance coefficient of the foundation pit project.

[0077] The mathematical model calculation expression of the above optimization constraints can be expressed as:

[0078]

[0079] Wherein, f(x) is the function to be optimized, and the optimization function takes the minimum maximum deformation value of the maintenance structure as the optimization goal;

[0080] The independent variable xi is the design axial force of the servo steel support 14 at each excavation step;

[0081] U max is the maximum deformation value of the surrounding structure;

[0082] F max The maximum axial force that can be sustained without losing stability, based on the support material, length, and constraints at both ends;

[0083] U a To determine the maximum allowable horizontal deformation of the retaining structure based on the excavation depth and foundation pit environmental protection requirements.

[0084] Step S3: Based on the optimization constraints and the genetic algorithm, the finite element numerical technology model and the genetic algorithm are jointly iteratively solved to calculate the optimal axial force value of each excavation step.

[0085] Wherein, the step S3 further includes:

[0086] S31) generating an initial population, wherein the initial population is a plurality of randomly generated groups of design axial force values ​​of the servo steel supports 14 for each of the excavation steps;

[0087] A certain number of design axial force parameters are randomly generated as the initial population and encoded using a binary method. Each individual in the initial population includes the design axial force values ​​of all servo steel supports 14 at each excavation step.

[0088] S32) Substituting the initial population into the finite element numerical calculation model, calculating the deformation results of the enclosure structure under different design axial force combination values, and selecting the optimal result of the enclosure structure deformation results under the different design axial force combination values ​​as the global optimal individual;

[0089] In one embodiment, the axial force design values ​​in the initial population are substituted into ABAQUS to calculate the deformation of the enclosure structure under the corresponding design axial force.

[0090] S33) applying the genetic algorithm to the initial population to obtain a progeny population, wherein the progeny population is a plurality of sets of design axial force values ​​of the servo steel supports for each excavation step regenerated under the optimization constraint condition, substituting each axial force combination value of the progeny population into a finite element model to calculate deformation, selecting the optimal individual in the progeny based on the deformation result, and updating the globally optimal individual;

[0091] In one embodiment, a program is written in MATLAB, and the deformation calculation results are input into a genetic algorithm. The fitness function is calculated respectively. After genetic operations such as crossover and mutation, an offspring population is obtained. The various axial force combinations of the offspring population are substituted into ABAQUS to calculate the deformation of the enclosure structure under the corresponding design axial force. The best individual in the offspring is selected based on the deformation results, and the globally optimal individual is updated.

[0092] S34) Repeatedly execute S33, continuously generate new offspring populations, and continuously update the globally optimal individuals until the termination condition of the convergence criterion is met, and then output the result as the globally optimal individual.

[0093] The offspring population is continuously substituted into ABAQUS to calculate the deformation of the enclosure structure, and the iteration process continues until the genetic algorithm converges. The genetic algorithm includes a convergence criterion, which is usually achieved by setting a maximum number of generations, a maximum calculation time, a constraint function error, or an individual fitness variance. The termination condition used by the algorithm is that the constraint function error is less than 0.01 or the individual fitness variance is less than 0.01.

[0094] Step S4: Using the optimal axial force value of each excavation step as the hydraulic servo compensation amount of each excavation step.

[0095] After the optimal axial force value data of each excavation step is determined by genetic algorithm, it is used to control the hydraulic servo compensation amount of each excavation step, thereby achieving precise control of the steel support axial force servo system.

[0096] In one embodiment, a servo steel support axial force device is further provided, comprising:

[0097] a memory for storing instructions executable by a processor;

[0098] The processor is used to execute the instructions to implement the control method of the servo steel support axial force as described above.

[0099] In one embodiment, a computer-readable storage medium is further provided, wherein a computer program is stored on the storage medium, and when the computer program is executed by a processor, the method for controlling the servo steel support axial force as described above is implemented.

[0100] like Figures 4 to 7 As shown, it is a specific technical implementation process for realizing the preferred embodiment of this application.

[0101] like Figure 4 As shown, according to the actual working conditions, a finite element three-dimensional model is established. In this embodiment, ABAQUS is preferably used to establish the finite element three-dimensional model, and the distributed force is used to simulate the unbalanced earth pressure. By taking advantage of the finite element model, a spatial three-dimensional model can be constructed instead of just a two-dimensional plane model. Figure 5 As shown, F11, F12, F21, F13, F22 and F31 are the forces applied to divide the foundation pit excavation process into multiple excavation steps, and generate a finite element model file. In this embodiment, the inp file is preferably used, and the servo support axis force of the file is set to 0.

[0102] According to the genetic algorithm code, this embodiment preferably uses MATLAB to write the genetic algorithm code, and determines the upper limit F of the axial force adjustment according to the cross-sectional form of the servo support and the material yield limit. u An initial mid-range is randomly generated from 0 to Fu. The initial population is the initial values ​​of the servo axial forces of different servo supports at each excavation stage. The inp file is called in the genetic algorithm to obtain the wall deformation under the first data table. The deformation data is saved by reading the dat file generated by the finite element calculation.

[0103] A second data table is generated using a genetic algorithm. The finite element 3D model is then used to generate a new inp file based on the second data table. The wall deformation results generated from the first and second data tables are compared, and the preferred wall deformation result is selected as the preferred deformation result and axial force design value, which is then compared with subsequent calculation results.

[0104] like Figure 6 and Figure 7 As shown in FIG, the genetic algorithm continuously generates new axial force combination values, i.e., a new data table. The optimal deformation results and axial force design values, i.e., the data table, are continuously updated until the genetic algorithm converges and the final optimized axial force design value data table is obtained.

[0105] The embodiment of the present application solves the problem in the prior art of not considering the dynamic construction factors of step-by-step excavation of foundation pits and step-by-step support by providing a method for controlling the axial force of a servo steel support, realizes quantitative and refined control of the deformation of the retaining structure, and provides a reasonable control scheme for the practical application of the steel support axial force servo system.

[0106] As used in this application and the claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" are not intended to refer to the singular but may include the plural. Generally speaking, the terms "comprises" and "include" only indicate the inclusion of the steps and elements specifically identified, and these steps and elements do not constitute an exclusive list. A method or apparatus may also include other steps or elements.

[0107] Those skilled in the art will appreciate that information, signals, and data may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips cited throughout the foregoing description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0108] Those skilled in the art will further appreciate that the various illustrative logic blocks, modules, circuits, and algorithmic steps described in conjunction with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or a combination of the two. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps are generally described above in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. A skilled person may implement the described functionality in different ways for each specific application, but such implementation decisions should not be interpreted as resulting in a departure from the scope of the present invention.

[0109] The various illustrative logic modules and circuits described in conjunction with the embodiments disclosed herein may be implemented or executed using a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

[0110] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read and write information from / to the storage medium. In an alternative, the storage medium may be integrated into the processor. The processor and storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and storage medium may reside in a user terminal as discrete components.

[0111] In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted via a computer-readable medium as one or more instructions or codes. Computer-readable media include both computer storage media and communication media, including any media that facilitates the transfer of a computer program from one location to another. A storage medium may be any available medium that can be accessed by a computer. By way of example and not limitation, such computer-readable media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is also properly referred to as a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwaves, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwaves are included in the definition of medium. As used herein, disk and disc include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, where disks typically reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0112] The above embodiments are provided to persons familiar with the art for implementing or using the present invention. Personnel familiar with the art may make various modifications or changes to the above embodiments without departing from the inventive concept of the present invention. Therefore, the scope of protection of the present invention is not limited to the above embodiments, but should be the maximum scope of the innovative features mentioned in the claims.

Claims

1. A method for controlling the axial force of a servo steel support, characterized in that: The following steps are involved: S1) establishing a finite element numerical calculation model, wherein the finite element numerical calculation model is used to calculate the deformation of the servo-supported foundation pit retaining structure and divide the foundation pit excavation process into multiple excavation steps; S2) establishing optimization constraints, wherein the optimization constraints are based on the excavation steps and foundation pit environmental protection requirements and construction safety requirements; S3) performing a joint iterative solution on the finite element numerical calculation model and the genetic algorithm based on the optimization constraint conditions and the genetic algorithm to calculate the optimal axial force value for each excavation step; S4) using the optimal axial force value of each excavation step as the hydraulic servo compensation amount of each excavation step; Wherein, the step S3 further includes: S31) generating an initial population, wherein the initial population is a plurality of randomly generated groups of design axial force values ​​of the servo steel supports including each of the excavation steps; S32) Substituting the initial population into the finite element numerical calculation model, calculating the deformation results of the enclosure structure under different design axial force combination values, and selecting the optimal result of the enclosure structure deformation results under the different design axial force combination values ​​as the global optimal individual; S33) applying the genetic algorithm to the initial population to obtain a progeny population, wherein the progeny population is a plurality of sets of design axial force values ​​of the servo steel supports for each excavation step regenerated under the optimization constraint condition, substituting each axial force combination value of the progeny population into a finite element model to calculate deformation, selecting the optimal individual in the progeny based on the deformation result, and updating the globally optimal individual; S34) Repeatedly execute S33, continuously generate new offspring populations, and continuously update the globally optimal individuals until the termination condition of the convergence criterion is met, and then output the result as the globally optimal individual.

2. The method for controlling the servo steel support axial force according to claim 1, characterized in that: The step S1 further comprises: Establish finite element model of servo steel support foundation pit; Establish the finite element model of foundation pit retaining structure; Establish a finite element model of the soil in the pit; Establish finite element models of ordinary steel support, concrete base steel support and servo steel support.

3. The method for controlling the servo steel support axial force according to claim 1, characterized in that: The genetic algorithm includes a convergence criterion, which is achieved by setting a maximum number of generations, a maximum calculation time, and an individual fitness variance.

4. The method for controlling the servo steel support axial force according to claim 3, characterized in that: The individual fitness variance is set to be less than 0.

01.

5. The method for controlling the servo steel support axial force according to claim 1, characterized in that: The genetic algorithm is written in MATLAB.

6. The method for controlling the servo steel support axial force according to claim 2, characterized in that: The servo steel support finite element model adopts composite boundary conditions of nonlinear spring elements and variable concentrated forces to simulate the support under different excavation steps.

7. A servo steel support axial force device, characterized in that: include: a memory for storing instructions executable by a processor; A processor is used to execute the instructions to implement the servo steel support axial force control method according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by the processor, the method for controlling the servo steel support axial force according to any one of claims 1 to 6 is implemented.

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