Large-span bridge horizontal rotation stress model construction method based on numerical simulation

Abstract

The invention relates to the technical field of bridge swivel data processing, in particular to a large-span bridge horizontal swivel stress model construction method based on numerical simulation, and the method comprises the steps: constructing a large-span bridge horizontal swivel stress initial model based on obtained target bridge information; performing stage division on each simulation rotation; determining the swivel trend important influence degree of each preset detection point under each preset detection dimension in each target stage of each simulated swivel; adjusting the simulation sampling frequency of the preset detection point under the preset detection dimension in the target stage of the simulation swivel; and constructing a large-span bridge horizontal swivel stress target model based on the large-span bridge horizontal swivel stress initial model and the target sampling frequencies of different preset detection points under different preset detection dimensions in different target stages of different simulated swivel. According to the method, different target sampling frequencies are adaptively set, and the construction accuracy of the horizontal rotation stress model of the large-span bridge is improved.

Description

Technical Field

[0001] The invention relates to the technical field of bridge rotation data processing, and in particular to a method for constructing a force model of a large-span bridge horizontal rotation based on numerical simulation. Background Art

[0002] The horizontal rotation construction method of bridges is a method suitable for the construction of large-span bridges. After the prefabricated bridge components are formed (cast or spliced) at a non-design axis position, they are moved to the designed bridge position by rotation to complete the bridge installation. Before installation, numerical simulation is usually used to simulate the mechanical response of the bridge during the rotation process, including the force, displacement, and stress distribution of each part of the bridge, and to test the changes under different rotation angles, so as to predict the performance of the structure and possible problems.

[0003] During the simulation of the force model of a large-span bridge, it is necessary to fully consider the situations that may be encountered during the actual rotation of the bridge in order to accurately predict the behavior of the bridge during the rotation process and ensure the safety and stability of the bridge during construction and use. However, in the construction of the force model of the horizontal rotation of a large-span bridge based on numerical simulation, the existing methods often model all parts of the large-span bridge indiscriminately, that is, they often use a fixed sampling frequency to model different positions of the large-span bridge. As a result, the results obtained in the simulation process of the force model of the large-span bridge may not accurately predict the stress concentration, time-varying characteristics of the friction coefficient, and dynamic deformation response at some positions during the rotation process, resulting in poor accuracy in the construction of the force model of the horizontal rotation of the large-span bridge. Summary of the invention

[0004] In order to solve the technical problem of poor accuracy in constructing a horizontal rotation force model of a large-span bridge, the present invention proposes a method for constructing a horizontal rotation force model of a large-span bridge based on numerical simulation.

[0005] In a first aspect, the present invention provides a method for constructing a force model of a large-span bridge horizontal rotation based on numerical simulation, the method comprising: Based on the acquired target bridge information, an initial force model of the horizontal rotation of the long-span bridge is constructed, and the bridge rotation simulation is performed to obtain the bridge simulation records corresponding to each simulated rotation; According to the bridge rotation angular velocity in the bridge simulation record corresponding to each simulated rotation, each simulated rotation is divided into stages to obtain a preset number of target stages; Determine the rotation trend importance of each preset detection point in each preset detection dimension in each target stage of each simulated rotation according to the simulated dimension data of each preset detection point in each preset detection dimension in each target stage of each simulated rotation; If the rotation trend important influence degree of the preset detection point in the preset detection dimension at the target stage of the simulated rotation is greater than the preset important influence threshold, the simulation sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation is adjusted to obtain the target sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation; Based on the initial force model of horizontal rotation of large-span bridges and the target sampling frequencies of different preset detection points under different preset detection dimensions at different target stages of different simulated rotations, a target force model of horizontal rotation of large-span bridges is constructed.

[0006] In combination with the first aspect above, in a possible implementation, each simulated rotation is divided into stages according to the bridge rotation angular velocity in the bridge simulation record corresponding to each simulated rotation to obtain a preset number of target stages, including: Determine any simulated rotation as a marked simulated rotation, and form a marked rotation angular velocity sequence with all bridge rotation angular velocities in the bridge simulation record corresponding to the marked simulated rotation; Determine the maximum value in the marked rotation angular velocity sequence as the marked maximum value, and select the marked maximum value greater than or equal to the marked representative angular velocity from all the marked maximum values ​​as the candidate maximum value, wherein the marked representative angular velocity is the average of all the bridge rotation angular velocities in the marked rotation angular velocity sequence; Every two candidate maxima form a maximum value group, and based on the candidate maximum value distribution between the corresponding positions of the two candidate maxima in each maximum value group in the marked rotation angular velocity sequence, determine the stage division confidence corresponding to each maximum value group; Select the maximum value group with the largest confidence in the corresponding stage division from all the maximum value groups as the target maximum value group; The marked rotation angular velocity sequence is segmented using two candidate maxima in the target maximum group as segmentation points to obtain a preset number of subsequences, and the time period corresponding to each subsequence is recorded as a target stage to obtain a preset number of target stages.

[0007] In combination with the first aspect, in a possible implementation, determining the stage division confidence corresponding to each maximum value group based on the candidate maximum value distribution between two candidate maximum values ​​in each maximum value group at corresponding positions in the marked rotation angular velocity sequence includes: Determine any maximum value group as a marked maximum value group, and form a reference maximum value sequence with all candidate maximum values ​​of the marked maximum value group between corresponding positions in the marked rotation angular velocity sequence, wherein the reference maximum value sequence includes the marked maximum value group; Based on the absolute value of the difference between adjacent candidate maxima in the reference maximum sequence and the duration between the simulated sampling moments corresponding to two candidate maxima in the marked maximum group, the confidence level of the stage division corresponding to the marked maximum group is determined.

[0008] In combination with the first aspect above, in a possible implementation manner, the formula corresponding to the stage division confidence corresponding to the marked maximum value group is: ;in, Q is the confidence level of the stage division corresponding to the marked maximum value group; is the normalization function; It is the absolute value function; is the simulated sampling time corresponding to the first candidate maximum in the marked maximum group; is the simulated sampling time corresponding to the second candidate maximum in the marked maximum group; is a natural exponential function; A is the number of candidate maxima in the reference maximum sequence; a is the sequence number of the candidate maximum value in the reference maximum value sequence; is the first a Candidate maxima; is the first a +1 candidate maximum.

[0009] In combination with the first aspect above, in a possible implementation, determining the rotation trend importance influence degree of each preset detection point in each preset detection dimension in each target stage of each simulated rotation according to the simulated dimension data of each preset detection point in each preset detection dimension in each target stage of each simulated rotation includes: Determine any preset detection point as a marked detection point, and select a preset detection point that detects the same part as the marked detection point from all preset detection points as a reference detection point; Determine any target phase as a marking phase, determine any preset detection dimension as a marking detection dimension, and determine any simulated rotation as a marking simulated rotation; Determine the range of all simulation dimension data of the mark detection point in the mark detection dimension in the marking stage of the mark simulation rotor as the target difference value of the mark detection point in the mark detection dimension in the marking stage of the mark simulation rotor; Determine the range of all simulated dimensional data of each reference detection point in the mark detection dimension at the mark stage of the mark simulation rotor as a target difference value of each reference detection point in the mark detection dimension at the mark stage of the mark simulation rotor; Determine the monitoring attention degree of the mark detection point in the mark detection dimension at the marking stage of the mark simulation rotor according to the target difference value of the mark detection point in the mark detection dimension at the marking stage of the mark simulation rotor and the target difference values ​​of all reference detection points in the mark detection dimension at the marking stage of the mark simulation rotor; According to the monitoring attention and target difference value of the mark detection point in the mark detection dimension during the marking phase of the mark simulation rotation, the important influence of the rotation trend of the mark detection point in the mark detection dimension during the marking phase of the mark simulation rotation is determined, wherein the monitoring attention and target difference value are positively correlated with the important influence of the rotation trend.

[0010] In combination with the first aspect above, in a possible implementation manner, determining the monitoring attention of the mark detection point in the mark detection dimension at the marking stage of the mark simulation rotor according to the target difference value of the mark detection point in the mark detection dimension at the marking stage of the mark simulation rotor and the target difference values ​​of all reference detection points in the mark detection dimension at the marking stage of the mark simulation rotor includes: Determine the average of the target difference values ​​of all reference detection points in the mark detection dimension at the mark stage of the mark simulation rotor as the reference difference value of the mark detection point in the mark detection dimension at the mark stage of the mark simulation rotor; The ratio of the target difference value and the reference difference value of the mark detection point in the mark detection dimension during the marking phase of the mark simulation rotor is normalized to obtain the monitoring attention degree of the mark detection point in the mark detection dimension during the marking phase of the mark simulation rotor.

[0011] In combination with the first aspect above, in a possible implementation manner, the adjusting the simulated sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation to obtain the target sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation includes: Determine the maximum value of all simulated dimension data of the preset detection point in the preset detection dimension at the target stage of the simulated rotation as a data reference value; The simulated sampling frequency of the preset detection point under the preset detection dimension within the preset time period in the target phase of the simulated rotation is adjusted to the maximum, and a simulated dimension data sequence under the maximum sampling frequency within the preset time period is obtained, which is recorded as the simulated dimension data sequence of the preset detection point under the preset detection dimension within the preset time period in the target phase of the simulated rotation; Determine the critical data capture degree of the preset detection point in the preset detection dimension at the target stage of the simulated rotation according to the data reference value and the simulated dimension data sequence of the preset detection point in the preset detection dimension within the preset time period at the target stage of the simulated rotation; According to the critical data capture degree of the preset detection point in the preset detection dimension in the target stage of the simulated rotation and the initial simulation sampling frequency, the target sampling frequency of the preset detection point in the preset detection dimension in the target stage of the simulated rotation is determined.

[0012] In combination with the first aspect above, in a possible implementation manner, determining the critical data capture degree of the preset detection point in the preset detection dimension at the target stage of the simulated rotation according to the data reference value and the simulated dimension data sequence of the preset detection point in the preset detection dimension within a preset time period in the target stage of the simulated rotation includes: Determine the simulation dimension data sequence of the preset detection point under the preset detection dimension within the preset time period in the target stage of the simulated rotation as the target simulation dimension data sequence; Filter out simulated dimensional data greater than or equal to a data reference value from the target simulated dimensional data sequence as reference dimensional data; According to the amount of reference dimension data, the critical data capture degree of the preset detection point in the preset detection dimension at the target stage of the simulated rotation is determined, wherein the amount of reference dimension data is positively correlated with the critical data capture degree.

[0013] In combination with the first aspect above, in a possible implementation manner, the formula corresponding to the target sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation is: ;in, G is the target sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation; h is the initial simulation sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation; ZM is the maximum sampling frequency that can be achieved; H It is the critical data capture degree of the preset detection point under the preset detection dimension at the target stage of the simulated rotation.

[0014] In combination with the first aspect above, in a possible implementation, the target model of the horizontal rotation force of the long-span bridge is constructed based on the initial model of the horizontal rotation force of the long-span bridge and the target sampling frequencies of different preset detection points under different preset detection dimensions at different target stages of different simulated rotations, including: The simulation sampling frequencies of different preset detection points in the initial force model of horizontal rotation of large-span bridges under different preset detection dimensions at different target stages of different simulated rotations are updated to their corresponding target sampling frequencies, and the updated initial force model of horizontal rotation of large-span bridges is determined as the target force model of horizontal rotation of large-span bridges.

[0015] In a second aspect, the present invention provides a system for constructing a force model of a horizontal rotation of a large-span bridge based on numerical simulation, the system comprising: A simulation module is constructed to construct an initial force model of a large-span bridge horizontal rotation based on the acquired target bridge information, and to perform bridge rotation simulation to obtain bridge simulation records corresponding to each simulated rotation; A stage division module is used to divide each simulated rotation into stages according to the bridge rotation angular velocity in the bridge simulation record corresponding to each simulated rotation, and obtain a preset number of target stages; A rotation trend importance influence determination module, used to determine the rotation trend importance influence of each preset detection point in each preset detection dimension at each target stage of each simulated rotation according to the simulated dimension data of each preset detection point in each preset detection dimension at each target stage of each simulated rotation; A sampling frequency adjustment module is used to adjust the simulation sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation if the rotation trend important influence degree of the preset detection point in the preset detection dimension at the target stage of the simulated rotation is greater than the preset important influence threshold, so as to obtain the target sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation; The model building module is used to build a target model of the horizontal rotation of a large-span bridge based on the initial model of the horizontal rotation of the large-span bridge and the target sampling frequencies of different preset detection points under different preset detection dimensions at different target stages of different simulated rotations.

[0016] In a third aspect, a server is provided, comprising a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, so that the device executes the method in the first aspect or any possible implementation of the first aspect.

[0017] In a fourth aspect, a computer program product is provided, comprising: a computer program code, which, when executed on a computer, enables the computer to execute the method in the first aspect or any possible implementation of the first aspect.

[0018] In a fifth aspect, a computer-readable storage medium is provided, which stores a computer program code. When the computer program code runs on a computer, the computer executes the method in the above-mentioned first aspect or any possible implementation manner of the first aspect.

[0019] The present invention has the following beneficial effects: The method for constructing a force model of a horizontal rotation of a large-span bridge based on numerical simulation of the present invention adaptively sets different target sampling frequencies, solves the technical problem of poor accuracy in constructing a force model of a horizontal rotation of a large-span bridge, and improves the accuracy of constructing a force model of a horizontal rotation of a large-span bridge. When constructing a target force model of a horizontal rotation of a large-span bridge, the present invention comprehensively considers the influence of different detection points on the rotation of the bridge, thereby quantifying the important influence of each preset detection point on the rotation trend under each preset detection dimension under each target stage of each simulated rotation, and realizes adaptive adjustment of the simulation sampling frequencies of different preset detection points under different preset detection dimensions under different target stages of different simulated rotations, thereby realizing adaptive modeling of different parts of the large-span bridge, and further improving the accuracy of the final construction of the force model of the horizontal rotation of the large-span bridge. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 It is a flow chart of the method for constructing a force model of a large-span bridge horizontal rotation based on numerical simulation of the present invention; Figure 2 It is a schematic diagram of the composition structure of the system for constructing a horizontal rotation force model of a large-span bridge based on numerical simulation of the present invention; Figure 3 The figure is a schematic diagram of the structure of a computer device of the present invention. DETAILED DESCRIPTION

[0022] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the technical solutions proposed by the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0023] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0024] refer to Figure 1 , shows the process of some embodiments of the method for constructing a horizontal rotation force model of a large-span bridge based on numerical simulation according to the present invention. The method for constructing a horizontal rotation force model of a large-span bridge based on numerical simulation includes the following steps: Step S1, based on the acquired target bridge information, construct an initial stress model of the horizontal rotation of the large-span bridge, and perform a bridge rotation simulation to obtain a bridge simulation record corresponding to each simulated rotation.

[0025] Among them, the target bridge information may be information related to the long-span bridge to be detected. For example, the target bridge information may include but is not limited to: the geometric dimensions and spatial positions of the bridge main beam, the geometric dimensions and spatial positions of the bridge piers, the geometric dimensions and spatial positions of the bearings, the geometric dimensions and spatial positions of the rotating mechanism, the mechanical parameters of the concrete, the mechanical parameters of the steel bars, the static load and the dynamic load. The long-span bridge to be detected may be a long-span bridge to be subjected to rotation simulation. A long-span bridge refers to a bridge that spans a large space, usually across geographical obstacles such as deep valleys, rivers or bays, and the main span length of these bridges is usually more than 100 meters. The initial force model of the horizontal rotation of the long-span bridge may be a force model of the horizontal rotation of the long-span bridge obtained by initial construction based on the target bridge information. The force model of the horizontal rotation of the long-span bridge refers to the study of the effects of various forces on the bridge during the rotation process of the long-span bridge through the mechanical analysis of the bridge. The simulated rotation may be a simulated rotation process obtained by simulating the rotation of the bridge using the initial force model of the horizontal rotation of the long-span bridge. The bridge simulation record corresponding to the simulated rotation may characterize the situation related to the simulated rotation. The bridge simulation record may include but is not limited to: the bridge rotation angular velocity during the simulated rotation process. The bridge rotation angular velocity may represent the angular change rate of the bridge rotation.

[0026] It should be noted that in the simulation process of the horizontal rotation of a large-span bridge, it is necessary to fully consider the possible risks that may occur during the actual rotation process, such as uneven stress on the bridge structure, equipment failure or incoordination, bridge deformation or tilt, etc. The simulation is used to determine the structural stability of the bridge rotation, the adaptability of the turntable equipment, the feasibility of the rotation plan, etc., to fully understand the rotation status of the bridge under different rotation angles and loads, and avoid unnecessary risks in actual operations.

[0027] As an example, this step may include the following steps: The first step is to obtain the target bridge information.

[0028] For example, geometric data, material parameters, load data, unit type, boundary constraints, load conditions and historical large-span bridge rotation records can be obtained to form the target bridge information. Among them, the method for obtaining geometric data can be: collecting the geometric dimensions, spatial positions and connection relationships of key parts such as bridge main beams, piers, supports, and rotation mechanisms, and high-precision data must be obtained based on design drawings or three-dimensional laser scanning technology. The rotation mechanism can be a ball joint. The method for obtaining material parameters can be: inputting mechanical parameters such as elastic modulus, Poisson's ratio, yield strength, etc. of materials such as concrete and steel bars, and national standards or laboratory measured data must be used to ensure the accuracy of the parameters. The method for obtaining load data can be: collecting static loads, dynamic loads, temporary loads during rotation, and special conditions. Among them, static loads can include but are not limited to: dead weight and second-stage dead loads. Dynamic loads can include but are not limited to: vehicle and wind loads. Temporary loads can be unbalanced moments. Special conditions can be earthquakes. The method for obtaining unit types can be: collecting beam units, shell units, and special units. Beam elements can be used to simulate linear structures such as main beams and piers, and cross-sectional shapes and reinforcement information need to be obtained. The cross-sectional shape can be box-shaped or T-shaped. Shell elements, also known as solid elements, can be used in complex parts such as bridge decks and ball joints to capture local stress distribution. Special elements can be, but are not limited to, gap elements and spring elements. Gap elements can simulate bearing sliding, and spring elements simulate pile-soil interaction. The method for obtaining boundary constraints can be: setting degree of freedom constraints according to actual support conditions, such as fixed bearings restricting all displacements and movable bearings only allowing longitudinal sliding. Load conditions can include: rotation stage and environmental load. In the rotation stage, rotation traction, unbalanced torque and temporary counterweight can be applied to dynamically simulate time-varying loads under changes in rotation angles. Environmental loads can consider the effects of wind loads (pulsating wind simulation) and temperature gradient effects (thermal expansion coefficient) on the structure. The historical long-span bridge rotation records can be used as a reference to obtain the maximum rotation angle and the minimum rotation angle, so as to determine the rotation angle range of the long-span bridge during simulation; and different load data can be obtained to determine the number of load interferences that can be selected for simulation.

[0029] The second step is to construct an initial force model of the horizontal rotation of the large-span bridge based on the target bridge information.

[0030] For example, a three-dimensional finite element model of the bridge can be constructed by software tools according to the target bridge information, and the model constructed at this time is recorded as the initial force model of the horizontal rotation of the long-span bridge. The software tools may include but are not limited to: ANSYS, MIDAS and SOFiSTiK.

[0031] It should be noted that finite element software such as ANSYS, MIDAS, SOFiSTiK, etc. can be used to establish a three-dimensional model. The main beam and piers are discretized using beam units or solid units. The rotation mechanism needs to be modeled in a refined manner, considering the nonlinear behavior of contact. The rotation mechanism may include but is not limited to: ball joints.

[0032] The third step is to simulate the bridge rotation through the initial force model of the horizontal rotation of the large-span bridge, record the angular velocity of the bridge rotation during each simulated rotation, and form a bridge simulation record corresponding to each simulated rotation.

[0033] Step S2, dividing each simulated rotation into stages according to the bridge rotation angular velocity in the bridge simulation record corresponding to each simulated rotation, and obtaining a preset number of target stages.

[0034] Among them, the preset number can be a pre-set number, which can be 3. The three target stages can be: a starting stage, an intermediate stage and an ending stage in sequence.

[0035] It should be noted that during the bridge rotation process, when the bridge starts to rotate, due to the large static friction of the bridge, it needs to overcome the static friction before it can start to move, so the speed at this stage is often relatively slow. The speed at this time is often relatively low because a large force is required to overcome the friction; when the bridge starts to rotate and enters a stable rotation state, the speed usually remains relatively stable. This is the main stage in the bridge rotation process, and the rotating equipment pushes the bridge at a relatively constant speed; near the end of the rotation process, the speed of the bridge usually slows down, especially when approaching the final positioning point, the speed will gradually decrease, because at this time, fine adjustments are often required to ensure the accurate positioning of the bridge. Because during the bridge rotation process, the middle stage of the bridge rotation is a stage where the speed is relatively stable, so the speed stability period can be selected for the bridge rotation angular velocity record, and the corresponding time stage can be divided into the middle stage of the bridge rotation, so that the time stages before and after it are the starting stage and the ending stage respectively.

[0036] As an example, this step may include the following steps: In the first step, any simulated rotation is determined as a marked simulated rotation, and all bridge rotation angular velocities in the bridge simulation record corresponding to the marked simulated rotation are combined into a marked rotation angular velocity sequence.

[0037] The marked rotation angular velocity sequence may be a time series.

[0038] In the second step, the maximum value in the above-mentioned marked rotation angular velocity sequence is determined as the marked maximum value, and the marked maximum value greater than or equal to the marked representative angular velocity is screened out from all the marked maximum values ​​as the candidate maximum values.

[0039] The marked representative angular velocity may be the average of all bridge rotation angular velocities in the marked rotation angular velocity sequence.

[0040] The third step is to form a maximum value group with every two candidate maxima, and based on the candidate maximum value distribution between the corresponding positions of the two candidate maxima in each maximum value group in the marked rotation angular velocity sequence, determine the stage division confidence corresponding to each maximum value group, which may include the following sub-steps: In the first sub-step, any maximum value group is determined as a marked maximum value group, and all candidate maximum values ​​of the marked maximum value group between corresponding positions in the marked rotation angular velocity sequence constitute a reference maximum value sequence.

[0041] Among them, the reference maximum value sequence can include a marked maximum value group.

[0042] For example, if the marked maximum value group includes: the second candidate maximum value and the sixth candidate maximum value, and the candidate maximum values ​​in the marked rotation angular velocity sequence are: the first candidate maximum value, the second candidate maximum value, the third candidate maximum value, the fourth candidate maximum value, the fifth candidate maximum value, the sixth candidate maximum value, the seventh candidate maximum value and the eighth candidate maximum value, then the reference maximum value sequence constructed at this time can be {second candidate maximum value, third candidate maximum value, fourth candidate maximum value, fifth candidate maximum value, sixth candidate maximum value}.

[0043] The second sub-step is to determine the stage division confidence corresponding to the above-mentioned marked maximum value group based on the absolute value of the difference between adjacent candidate maxima in the above-mentioned reference maximum value sequence and the duration between the simulated sampling moments corresponding to two candidate maxima in the above-mentioned marked maximum value group.

[0044] The simulation sampling time may be a sampling time in the simulation rotation process. The simulation sampling time corresponding to the candidate maximum value may be a sampling time when the candidate maximum value is collected in the simulation rotation process.

[0045] For example, the formula for determining the confidence level of the stage division corresponding to the marked maximum value group can be: ;in, Q is the confidence level of the stage division corresponding to the marked maximum value group. is a normalization function. It is the absolute value function. is the simulated sampling time corresponding to the first candidate maximum in the marked maximum group. is the simulated sampling time corresponding to the second candidate maximum in the marked maximum group. is a natural exponential function. A is the number of candidate maxima in the reference maximum sequence. a is the sequence number of the candidate maximum in the reference maximum sequence. is the first a Candidate maximum values. is the first a +1 candidate maximum.

[0046] It should be noted that the middle stage is the main stage of the bridge rotation, and its corresponding duration is often longer. When the value is larger, it often means that the time between the simulated sampling moments corresponding to the two candidate maxima in the marked maximum value group is longer, which often means that the stage corresponding to the marked maximum value group is longer, which often means that the simulated sampling moments corresponding to the two candidate maxima in the marked maximum value group are more likely to be the endpoint moments of the intermediate stage. The smaller it is, the more similar the maximum values ​​between the two candidate maximum values ​​in the marked maximum value group are, the more similar the angular velocities of the bridge rotation in the corresponding stage of the marked maximum value group are, the smoother the bridge rotation in the corresponding stage of the marked maximum value group is, and the more likely the simulation sampling time corresponding to the two candidate maximum values ​​in the marked maximum value group is to be the endpoint time of the intermediate stage. Therefore, when Q The larger it is, the more likely it is that the simulated sampling moments corresponding to the two candidate maxima in the marked maximum group are the endpoint moments of the intermediate stage.

[0047] The fourth step is to select the maximum value group with the largest corresponding stage division confidence from all maximum value groups as the target maximum value group.

[0048] The fifth step is to use the two candidate maxima in the above target maximum group as segmentation points to segment the marked rotation angular velocity sequence to obtain a preset number of subsequences, that is, 3 subsequences, and record the time period corresponding to each subsequence as the target stage, and obtain a preset number of target stages, that is, 3 target stages, which can be recorded as the starting stage, the middle stage and the ending stage respectively.

[0049] Step S3, determining the rotation trend importance of each preset detection point in each preset detection dimension at each target stage of each simulated rotation according to the simulated dimension data of each preset detection point in each preset detection dimension at each target stage of each simulated rotation.

[0050] Among them, the preset detection point can be a preset position point for state monitoring. The number of preset detection points can be preset. Multiple preset detection points can be installed in the same part so that they are located at different positions of the same part. For example, the preset detection points can be but are not limited to: support leg axial force measurement points, hinge stress measurement points, traction force, traction length monitoring points, main beam axis monitoring points, main beam elevation monitoring points, rotation angle, angular velocity, center axis inclination measurement points and tower axis monitoring points. The preset detection dimension can be a dimension related to the simulated rotation corresponding to the data collected through the preset detection point. The simulated dimensional data under the preset detection dimension can be the preset detection dimension data collected by the preset detection point during the simulated rotation process. For example, taking the support leg axial force measurement point as an example, the various preset detection dimensions under the support leg axial force measurement point can be the axial force dimension, lateral force dimension, bending moment dimension, torque dimension and shear force dimension, respectively, and the simulated dimensional data under these preset detection dimensions can be axial force, lateral force, bending moment, torque and shear force, respectively.

[0051] It should be noted that in the process of bridge rotation, there are often different key and critical parts when the rotation is in different stages. For example, the key and critical parts can be but not limited to: ball joints, V-shaped pier support structures and cantilever ends. The selection of these key parts usually depends on factors such as the way the bridge rotates, the rotation angle and the type of equipment used, and these parts involve the rotation accuracy, stability, equipment reliability and control of mechanical requirements during the construction process of the bridge. Here, the bridge rotation will involve relevant monitoring data of the support system, traction system and turntable attitude to reflect the relevant data performance during the rotation process, and the support system monitoring parameters should include turntable settlement, slideway line shape, support foot and slideway gap, turntable stress, auxiliary support stress, etc.; traction system monitoring parameters should include traction force, traction length, traction speed, etc.; rotation attitude monitoring parameters should include rotation inclination, rotation angle, rotation angular velocity, relative elevation difference between the cantilever ends on both sides of the rotation structure, beam axis, pier tower verticality, etc. Therefore, multiple detection points can be set at multiple locations in the support system, traction system and rotation attitude monitoring process.

[0052] As an example, this step may include the following steps: In the first step, any preset detection point is determined as a marked detection point, and a preset detection point that detects the same part as the marked detection point is selected from all preset detection points as a reference detection point.

[0053] In the second step, any target phase is determined as a marking phase, any preset detection dimension is determined as a marking detection dimension, and any simulated rotation is determined as a marking simulated rotation.

[0054] In the third step, the extreme difference of all simulation dimensional data of the above-mentioned mark detection point in the above-mentioned mark detection dimension in the above-mentioned mark stage of the above-mentioned mark simulation rotation is determined as the target difference value of the above-mentioned mark detection point in the above-mentioned mark detection dimension in the above-mentioned mark stage of the above-mentioned mark simulation rotation.

[0055] In the fourth step, the extreme difference of all simulation dimension data of each reference detection point in the above-mentioned mark detection dimension in the above-mentioned mark stage of the above-mentioned mark simulation rotation is determined as the target difference value of each reference detection point in the above-mentioned mark detection dimension in the above-mentioned mark stage of the above-mentioned mark simulation rotation.

[0056] The fifth step, according to the target difference value of the mark detection point in the mark detection dimension in the mark phase of the mark simulation rotation, and the target difference values ​​of all reference detection points in the mark detection dimension in the mark phase of the mark simulation rotation, determines the monitoring attention of the mark detection point in the mark detection dimension in the mark phase of the mark simulation rotation, which may include the following sub-steps: In the first sub-step, the average of the target difference values ​​of all reference detection points in the above-mentioned mark detection dimension in the above-mentioned mark phase of the above-mentioned mark simulation rotation is determined as the reference difference value of the above-mentioned mark detection points in the above-mentioned mark detection dimension in the above-mentioned mark phase of the above-mentioned mark simulation rotation.

[0057] In the second sub-step, normalize the ratio of the target difference value and the reference difference value of the mark detection point in the mark detection dimension during the mark phase of the mark simulation rotation, and obtain the monitoring attention degree of the mark detection point in the mark detection dimension during the mark phase of the mark simulation rotation.

[0058] For example, the formula for determining the monitoring attention of the mark detection point in the mark detection dimension during the mark phase of the mark simulation rotation can be: ;in, B It is the monitoring attention of the marking detection point in the marking detection dimension during the marking phase of the marking simulation rotation. is a normalization function. d is the target difference value of the mark detection point in the mark detection dimension during the mark phase of the mark simulation rotation. D It is the reference difference value of the mark detection point in the mark detection dimension during the marking phase of the mark simulation rotation.

[0059] It should be noted that when B When it is larger, it often means that the data fluctuation of the marking detection point in the marking stage of the marking simulation rotation under the marking detection dimension is greater than the data fluctuation of most reference detection points in the marking stage of the marking simulation rotation under the marking detection dimension. It often means that the data fluctuation of the marking detection point in the marking stage of the marking simulation rotation under the marking detection dimension is more important, and it often means that the monitoring attention level of the marking detection point in the marking stage of the marking simulation rotation under the marking detection dimension should be higher.

[0060] The sixth step is to determine the important influence of the rotation trend of the above-mentioned mark detection point in the above-mentioned mark detection dimension at the above-mentioned mark stage of the above-mentioned mark simulation rotation according to the monitoring attention and target difference value of the above-mentioned mark detection point in the above-mentioned mark detection dimension at the above-mentioned mark stage of the above-mentioned mark simulation rotation.

[0061] Among them, both the monitoring attention and the target difference value can be positively correlated with the important influence of the rotation trend.

[0062] For example, the formula corresponding to the important influence of the rotation trend of the mark detection point in the mark detection dimension in the marking stage of the mark simulation rotation can be: ;in, w It is the important influence of the marking detection point on the rotation trend in the marking detection dimension during the marking phase of the marking simulation rotation. is a normalization function. B It is the monitoring attention of the marking detection point in the marking detection dimension during the marking phase of the marking simulation rotation. d is the target difference value of the mark detection point in the mark detection dimension during the mark phase of the mark simulation rotation.

[0063] It should be noted that when B When it is larger, it often means that the data fluctuation of the marking detection point in the marking stage of the marking simulation rotation under the marking detection dimension is greater than the data fluctuation of the marking detection dimension of most reference detection points in the marking stage of the marking simulation rotation, which often means that the monitoring attention level of the marking detection point in the marking stage of the marking simulation rotation under the marking detection dimension should be higher. d When it is larger, it often means that the data fluctuation of the marking detection point in the marking stage of the marking simulation rotation under the marking detection dimension is greater, and it often means that the data fluctuation of the marking detection point in the marking stage of the marking simulation rotation under the marking detection dimension is more important, and it often means that the monitoring attention of the marking detection point in the marking stage of the marking simulation rotation under the marking detection dimension should be higher. Therefore, when wThe larger it is, the higher the monitoring attention of the marking detection point should be in the marking detection dimension during the marking phase of the marking simulation rotation.

[0064] Step S4, if the important influence degree of the rotation trend of the preset detection point under the preset detection dimension at the target stage of the simulated rotation is greater than the preset important influence threshold, then the simulation sampling frequency of the preset detection point under the preset detection dimension at the target stage of the simulated rotation is adjusted to obtain the target sampling frequency of the preset detection point under the preset detection dimension at the target stage of the simulated rotation.

[0065] The preset important influence threshold may be a preset threshold, which may be 0.6. The simulation sampling frequency under the preset detection dimension may be the sampling frequency of data under the preset detection dimension during the simulation rotation process, which may be manually set.

[0066] As an example, this step may include the following steps: In the first step, the maximum value of all simulation dimension data of the preset detection point under the preset detection dimension in the target stage of the simulated rotation is determined as the data reference value.

[0067] In the second step, the simulation sampling frequency of the preset detection point under the preset detection dimension within the preset time period in the target phase of the simulated rotation is adjusted to the maximum, and a simulation dimension data sequence under the maximum sampling frequency within the preset time period is obtained, which is recorded as the simulation dimension data sequence of the preset detection point under the preset detection dimension within the preset time period in the target phase of the simulated rotation.

[0068] Among them, the preset time period may be a pre-set time period, and its corresponding duration may be less than the duration corresponding to the target stage. For example, if the duration corresponding to the preset time period is half of the duration corresponding to the target stage, the preset time period in the target stage may be the first half of the target stage. The maximum sampling frequency may be the maximum sampling frequency that the corresponding sampling device can reach. The simulation dimension data sequence at the maximum sampling frequency may include: simulation dimension data under the preset detection dimension collected at the maximum sampling frequency. The simulation dimension data sequence may be a time series.

[0069] The third step is to determine the critical data capture degree of the preset detection point in the preset detection dimension at the target stage of the simulated rotation according to the data reference value and the simulated dimension data sequence of the preset detection point in the preset detection dimension within the preset time period in the target stage of the simulated rotation, which may include the following sub-steps: In the first sub-step, a simulation dimensional data sequence of the preset detection point under the preset detection dimension within a preset time period in the target phase of the simulated rotation is determined as a target simulation dimensional data sequence.

[0070] The second sub-step is to select simulated dimensional data greater than or equal to the data reference value from the above target simulated dimensional data sequence as reference dimensional data.

[0071] The third sub-step is to determine the critical data capture degree of the preset detection point in the preset detection dimension at the target stage of the simulated rotation according to the amount of reference dimension data.

[0072] Among them, the amount of reference dimension data can be positively correlated with the critical data capture degree.

[0073] For example, the formula corresponding to the critical data capture degree of the preset detection point in the preset detection dimension at the target stage of the simulated rotation may be: ;in, H It is the critical data capture degree of the preset detection point under the preset detection dimension at the target stage of the simulated rotation. n is the number of reference dimension data. N is the number of simulated dimension data in the target simulated dimension data sequence.

[0074] It should be noted that the reference dimension data can, to a certain extent, characterize the abnormal data captured after the refined modeling. Among them, the modeling after increasing the sampling frequency is equivalent to the refined modeling. H The larger it is, the more reference dimension data there are, which often means that more abnormal situations are captured after detailed modeling. It often means that the corresponding sampling frequency should be increased in the subsequent construction of the final large-span bridge horizontal rotation force model to achieve detailed modeling.

[0075] The fourth step is to determine the target sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation based on the critical data capture degree and the initial simulation sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation.

[0076] The initial simulation sampling frequency may be the sampling frequency at the preset detection dimension during the simulated rotation process, that is, the sampling frequency that has not been adjusted.

[0077] For example, the formula for determining the target sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation may be: ;in, G is the target sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation. hIt is the initial simulation sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation. ZM is the maximum achievable sampling frequency. H It is the critical data capture degree of the preset detection point under the preset detection dimension at the target stage of the simulated rotation.

[0078] It should be noted that when H The larger the value is, the more reference dimension data there is, which means that more abnormal situations are captured after detailed modeling. This means that the corresponding sampling frequency should be increased when constructing the final large-span bridge horizontal rotation force model in order to achieve detailed modeling. G The sampling frequency required for the preset detection point after refined modeling under the preset detection dimension at the target stage of the simulated rotation can be represented.

[0079] Step S5, constructing a target force model of the horizontal rotation of the large-span bridge based on the initial force model of the horizontal rotation of the large-span bridge and the target sampling frequencies of different preset detection points under different preset detection dimensions at different target stages of different simulated rotations.

[0080] Among them, the target force model of the horizontal rotation of the large-span bridge is the final constructed force model of the horizontal rotation of the large-span bridge.

[0081] As an example, the simulation sampling frequencies of different preset detection points in the initial force model of horizontal rotation of large-span bridges under different preset detection dimensions at different target stages of simulated rotation can be updated to their corresponding target sampling frequencies, and the updated initial force model of horizontal rotation of large-span bridges can be determined as the target force model of horizontal rotation of large-span bridges.

[0082] It should be noted that the embodiment of the present invention can divide the historical bridge rotation simulation records into different stages of the rotation process summary, and analyze the key parts existing in different stages based on the different stages, so as to understand the corresponding key parts in each stage of the rotation, and to carry out refined modeling of these key parts in the actual modeling process, so as to fully monitor various emergencies that may be encountered in the actual rotation process, and replace the data measured during the actual rotation with the corresponding simulation data, so as to improve the construction of the model.

[0083] refer to Figure 2Based on the same inventive concept as the above method embodiment, the present invention provides a system for constructing a horizontal rotation force model of a large-span bridge based on numerical simulation, the system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the above computer program is executed by the processor, the steps of implementing the method for constructing a horizontal rotation force model of a large-span bridge based on numerical simulation may specifically include: A simulation module 201 is constructed to construct an initial force model of a large-span bridge horizontal rotation based on the acquired target bridge information, and to perform bridge rotation simulation to obtain a bridge simulation record corresponding to each simulated rotation; The stage division module 202 is used to divide each simulated rotation into stages according to the bridge rotation angular velocity in the bridge simulation record corresponding to each simulated rotation, and obtain a preset number of target stages; The rotation trend importance influence determination module 203 is used to determine the rotation trend importance influence of each preset detection point in each preset detection dimension in each target stage of each simulated rotation according to the simulated dimension data of each preset detection point in each preset detection dimension in each target stage of each simulated rotation; The sampling frequency adjustment module 204 is used to adjust the simulation sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation if the rotation trend important influence degree of the preset detection point in the preset detection dimension at the target stage of the simulated rotation is greater than the preset important influence threshold, so as to obtain the target sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation; The model building module 205 is used to build a target model of the horizontal rotation of a large-span bridge based on the initial model of the horizontal rotation of the large-span bridge and the target sampling frequencies of different preset detection points under different preset detection dimensions at different target stages of different simulated rotations.

[0084] Figure 3 is a schematic diagram of the structure of a computer device provided by an embodiment of the present invention. Figure 3 As shown, the computer device 300 includes: a memory 301, a processor 302, and a computer program 303 stored in the memory 301 and running on the processor 302, wherein when the processor 302 executes the computer program 303, the computer device can execute any of the aforementioned methods for constructing a horizontal rotation force model of a large-span bridge based on numerical simulation.

[0085] Based on the same inventive concept as the above method embodiment, the present invention provides a server, including a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, so that the device executes any of the above methods for constructing a force model of a horizontal rotation of a large-span bridge based on numerical simulation.

[0086] Based on the same inventive concept as the above-mentioned method embodiment, the present invention provides a computer program product, which includes: computer program code, when the computer program code runs on a computer, enables the computer to execute any one of the above-mentioned methods for constructing a horizontal rotation force model of a large-span bridge based on numerical simulation.

[0087] Based on the same inventive concept as the above-mentioned method embodiment, the present invention provides a computer-readable storage medium, which stores a computer program code. When the computer program code runs on a computer, the computer executes any one of the above-mentioned methods for constructing a horizontal rotation force model of a large-span bridge based on numerical simulation.

[0088] In summary, when constructing the target force model of the horizontal rotation of a large-span bridge, the present invention comprehensively considers the influence of different detection points on the rotation of the bridge, thereby quantifying the important influence of each preset detection point on the rotation trend under each preset detection dimension at each target stage of each simulated rotation, and realizes adaptive adjustment of the simulation sampling frequency of different preset detection points under different preset detection dimensions at different target stages of different simulated rotations, thereby realizing adaptive modeling of different parts of the large-span bridge, and further improving the accuracy of the final construction of the horizontal rotation force model of the large-span bridge.

[0089] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features can be replaced by equivalents. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for constructing a force model of a large-span bridge horizontal rotation based on numerical simulation, characterized in that: The following steps are involved: Based on the acquired target bridge information, an initial force model of the horizontal rotation of the long-span bridge is constructed, and the bridge rotation simulation is performed to obtain the bridge simulation records corresponding to each simulated rotation; According to the bridge rotation angular velocity in the bridge simulation record corresponding to each simulated rotation, each simulated rotation is divided into stages to obtain a preset number of target stages; Determine the rotation trend importance of each preset detection point in each preset detection dimension in each target stage of each simulated rotation according to the simulated dimension data of each preset detection point in each preset detection dimension in each target stage of each simulated rotation; If the rotation trend important influence degree of the preset detection point in the preset detection dimension at the target stage of the simulated rotation is greater than the preset important influence threshold, the simulation sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation is adjusted to obtain the target sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation; Based on the initial force model of horizontal rotation of large-span bridges and the target sampling frequencies of different preset detection points under different preset detection dimensions at different target stages of different simulated rotations, a target force model of horizontal rotation of large-span bridges is constructed.

2. According to the method for constructing a force model of a large-span bridge horizontal rotation based on numerical simulation according to claim 1, it is characterized in that: The method divides each simulated rotation into stages according to the bridge rotation angular velocity in the bridge simulation record corresponding to each simulated rotation, and obtains a preset number of target stages, including: Determine any simulated rotation as a marked simulated rotation, and form a marked rotation angular velocity sequence with all bridge rotation angular velocities in the bridge simulation record corresponding to the marked simulated rotation; Determine the maximum value in the marked rotation angular velocity sequence as the marked maximum value, and select the marked maximum value greater than or equal to the marked representative angular velocity from all the marked maximum values ​​as the candidate maximum value, wherein the marked representative angular velocity is the average of all the bridge rotation angular velocities in the marked rotation angular velocity sequence; Every two candidate maxima form a maximum value group, and based on the candidate maximum value distribution between the corresponding positions of the two candidate maxima in each maximum value group in the marked rotation angular velocity sequence, determine the stage division confidence corresponding to each maximum value group; Select the maximum value group with the largest confidence in the corresponding stage division from all the maximum value groups as the target maximum value group; The marked rotation angular velocity sequence is segmented using two candidate maxima in the target maximum group as segmentation points to obtain a preset number of subsequences, and the time period corresponding to each subsequence is recorded as a target stage to obtain a preset number of target stages.

3. The method for constructing a force model of a large-span bridge horizontal rotation based on numerical simulation according to claim 2 is characterized in that: The step of determining the stage division confidence corresponding to each maximum value group based on the candidate maximum value distribution between the corresponding positions of two candidate maximum values ​​in each maximum value group in the marked rotation angular velocity sequence comprises: Determine any maximum value group as a marked maximum value group, and form a reference maximum value sequence with all candidate maximum values ​​of the marked maximum value group between corresponding positions in the marked rotation angular velocity sequence, wherein the reference maximum value sequence includes the marked maximum value group; Based on the absolute value of the difference between adjacent candidate maxima in the reference maximum sequence and the duration between the simulated sampling moments corresponding to two candidate maxima in the marked maximum group, the confidence level of the stage division corresponding to the marked maximum group is determined.

4. The method for constructing a force model of a large-span bridge horizontal rotation based on numerical simulation according to claim 3 is characterized in that: The formula for the confidence level of the stage division corresponding to the marked maximum value group is: ;in, Q is the confidence level of the stage division corresponding to the marked maximum value group; is the normalization function; It is the absolute value function; is the simulated sampling time corresponding to the first candidate maximum in the marked maximum group; is the simulated sampling time corresponding to the second candidate maximum in the marked maximum group; is a natural exponential function; A is the number of candidate maxima in the reference maximum sequence; a is the sequence number of the candidate maximum value in the reference maximum value sequence; is the first a Candidate maxima; is the first a +1 candidate maximum.

5. The method for constructing a force model of a large-span bridge horizontal rotation based on numerical simulation according to claim 1 is characterized in that: The determining, according to the simulated dimension data of each preset detection point in each preset detection dimension in each target stage of each simulated rotation, the rotation trend importance influence degree of each preset detection point in each preset detection dimension in each target stage of each simulated rotation comprises: Determine any preset detection point as a marked detection point, and select a preset detection point that detects the same part as the marked detection point from all preset detection points as a reference detection point; Determine any target phase as a marking phase, determine any preset detection dimension as a marking detection dimension, and determine any simulated rotation as a marking simulated rotation; Determine the range of all simulation dimension data of the mark detection point in the mark detection dimension in the marking stage of the mark simulation rotor as the target difference value of the mark detection point in the mark detection dimension in the marking stage of the mark simulation rotor; Determine the range of all simulated dimensional data of each reference detection point in the mark detection dimension at the mark stage of the mark simulation rotor as a target difference value of each reference detection point in the mark detection dimension at the mark stage of the mark simulation rotor; Determine the monitoring attention degree of the mark detection point in the mark detection dimension at the marking stage of the mark simulation rotor according to the target difference value of the mark detection point in the mark detection dimension at the marking stage of the mark simulation rotor and the target difference values ​​of all reference detection points in the mark detection dimension at the marking stage of the mark simulation rotor; According to the monitoring attention and target difference value of the mark detection point in the mark detection dimension during the marking phase of the mark simulation rotation, the important influence of the rotation trend of the mark detection point in the mark detection dimension during the marking phase of the mark simulation rotation is determined, wherein the monitoring attention and target difference value are positively correlated with the important influence of the rotation trend.

6. The method for constructing a force model of a large-span bridge horizontal rotation based on numerical simulation according to claim 5 is characterized in that: The step of determining the monitoring attention of the mark detection point in the mark detection dimension at the mark stage of the mark simulation rotor according to the target difference value of the mark detection point in the mark detection dimension at the mark stage of the mark simulation rotor and the target difference values ​​of all reference detection points in the mark detection dimension at the mark stage of the mark simulation rotor comprises: Determine the average of the target difference values ​​of all reference detection points in the mark detection dimension at the mark stage of the mark simulation rotor as the reference difference value of the mark detection point in the mark detection dimension at the mark stage of the mark simulation rotor; The ratio of the target difference value and the reference difference value of the mark detection point in the mark detection dimension during the marking phase of the mark simulation rotor is normalized to obtain the monitoring attention degree of the mark detection point in the mark detection dimension during the marking phase of the mark simulation rotor.

7. The method for constructing a force model of a large-span bridge horizontal rotation based on numerical simulation according to claim 1 is characterized in that: The step of adjusting the simulated sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation to obtain the target sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation includes: Determine the maximum value of all simulated dimension data of the preset detection point in the preset detection dimension at the target stage of the simulated rotation as a data reference value; The simulated sampling frequency of the preset detection point under the preset detection dimension within the preset time period in the target phase of the simulated rotation is adjusted to the maximum, and a simulated dimension data sequence under the maximum sampling frequency within the preset time period is obtained, which is recorded as the simulated dimension data sequence of the preset detection point under the preset detection dimension within the preset time period in the target phase of the simulated rotation; Determine the critical data capture degree of the preset detection point in the preset detection dimension at the target stage of the simulated rotation according to the data reference value and the simulated dimension data sequence of the preset detection point in the preset detection dimension within the preset time period at the target stage of the simulated rotation; According to the critical data capture degree of the preset detection point in the preset detection dimension in the target stage of the simulated rotation and the initial simulation sampling frequency, the target sampling frequency of the preset detection point in the preset detection dimension in the target stage of the simulated rotation is determined.

8. The method for constructing a force model of a large-span bridge horizontal rotation based on numerical simulation according to claim 7 is characterized in that: The step of determining the critical data capture degree of the preset detection point in the preset detection dimension at the target stage of the simulated rotation body according to the data reference value and the simulated dimension data sequence of the preset detection point in the preset detection dimension within the preset time period at the target stage of the simulated rotation body comprises: Determine the simulation dimension data sequence of the preset detection point under the preset detection dimension within the preset time period in the target stage of the simulated rotation as the target simulation dimension data sequence; Filter out simulated dimensional data greater than or equal to a data reference value from the target simulated dimensional data sequence as reference dimensional data; According to the amount of reference dimension data, the critical data capture degree of the preset detection point in the preset detection dimension at the target stage of the simulated rotation is determined, wherein the amount of reference dimension data is positively correlated with the critical data capture degree.

9. The method for constructing a force model of a large-span bridge horizontal rotation based on numerical simulation according to claim 7, characterized in that: The formula corresponding to the target sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation is: ;in, G is the target sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation; h is the initial simulation sampling frequency of the preset detection point in the preset detection dimension at the target stage of the simulated rotation; ZM is the maximum sampling frequency that can be achieved; H It is the critical data capture degree of the preset detection point under the preset detection dimension at the target stage of the simulated rotation.

10. The method for constructing a force model of a large-span bridge horizontal rotation based on numerical simulation according to claim 1, characterized in that: The method of constructing a target model of horizontal rotation force of a large-span bridge based on the initial model of horizontal rotation force of the large-span bridge and the target sampling frequencies of different preset detection points under different preset detection dimensions at different target stages of different simulated rotations includes: The simulation sampling frequencies of different preset detection points in the initial force model of horizontal rotation of large-span bridges under different preset detection dimensions at different target stages of different simulated rotations are updated to their corresponding target sampling frequencies, and the updated initial force model of horizontal rotation of large-span bridges is determined as the target force model of horizontal rotation of large-span bridges.

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