A self-anchored suspension bridge scale model mechanics simulation and structure monitoring system

Abstract

The application relates to the technical field of bridge engineering structure test, and discloses a self-anchored suspension bridge scale model mechanical simulation and structure monitoring system, which comprises a physical test bed end, a computer-aided simulation end, and simulation modeling modules, tension solution modules, loading simulation modules, monitoring and evaluation modules and damage identification modules arranged in the system. The equivalent model is constructed through the simulation end and the physical assembly is guided, the nonlinear iteration is used to output the bridge tension control coordinate matrix to guide the entity main cable erection and the cable tension, the limit state safety evaluation is carried out by comparing the measured data with the theoretical benchmark data after the load state is established, the structural defects are introduced into the entity model to extract the measured modal parameters, and the element stiffness matrix of the simulation model is corrected in reverse. The application realizes the data interaction and closed-loop correction of computer simulation and physical test, and effectively improves the stress control precision of the complex bridge in the bridge state and the structural damage identification accuracy.

Description

Technical Field

[0001] This invention relates to the field of bridge engineering structural testing technology, specifically to a mechanical simulation and structural monitoring system for a scaled-down model of a self-anchored suspension bridge. Background Technology

[0002] Due to the complex structural stresses of self-anchored suspension bridges, their mechanical behavior during construction and service cannot be accurately assessed solely through theoretical calculations. Therefore, scaled-down model tests have become a crucial means of verifying their structural performance and damage mechanisms. Current conventional research methods typically separate computer numerical simulations from physical physical tests. Single numerical simulations are often based on idealized material properties and boundary condition assumptions, making it difficult to realistically reflect nonlinear deformations, connector slippage, and initial stress errors during construction and assembly, leading to simulation results that deviate from actual engineering conditions. While purely physical scaled-down model tests can intuitively reflect the structural stress phenomena, in complex bridge-building stages such as main cable erection and suspension cable tensioning, the lack of synchronous theoretical coordinate data as a real-time control benchmark often necessitates repeated trial and error based on human experience, making it difficult to achieve high-precision control of the bridge alignment and internal cable forces.

[0003] Based on this, most existing research on structural health monitoring and damage identification remains at the purely theoretical stage, that is, directly extrapolating the damage response of bridges by modifying stiffness parameters in numerical simulation software. This extrapolation method, detached from the physical entity, cannot account for real physical sensor noise, assembly gaps, and environmental interference, making it impossible to effectively verify the reliability of the calculated damage identification indicators in actual engineering applications. If destructive damage tests are conducted directly on the physical model, it is not only costly but also the test process is usually irreversible, making it difficult to conduct repeated comparative verification under multiple working conditions. The long-standing data disconnect between theoretical simulation and physical testing prevents model tests from forming a closed loop of synchronous interaction between virtual and real systems and reverse parameter correction, limiting the accuracy of condition safety assessment and damage prediction for self-anchored suspension bridges. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a mechanical simulation and structural monitoring system for scaled-down models of self-anchored suspension bridges. This system solves the problems of disconnect between theoretical simulation and physical entity data, insufficient accuracy in cable force control after completion, and difficulty in identifying and correcting structural damage in traditional scaled-down model tests of self-anchored suspension bridges.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a mechanical simulation and structural monitoring system for a scaled-down model of a self-anchored suspension bridge, comprising a physical test bed end and a computer-aided simulation end; the computer-aided simulation end includes:

[0006] The simulation modeling module is used to build an equivalent simulation model on the computer-aided simulation end and output assembly control parameters based on the equivalent simulation model to guide the assembly of the scaled physical model on the physical test bed.

[0007] The tensioning solution module is used to iteratively solve the output bridge tensioning control coordinate matrix in the equivalent simulation model. The bridge tensioning control coordinate matrix is ​​used to guide the main cable erection and suspension cable tensioning performed on the scaled physical model.

[0008] The simulation module is loaded, which is used to solve the equivalent simulation model to output theoretical baseline data and output the corresponding equivalent physical load parameters, which are used to establish the loading state on the scaled physical model.

[0009] The monitoring and evaluation module is used to collect measured data of the scaled physical model under load, compare the measured data with theoretical benchmark data, and output the limit state evaluation results.

[0010] The damage identification module is used to extract measured modal parameters after structural defects are introduced into the scaled physical model. The error between the measured modal parameters and the theoretical modal parameters is used as the target to correct the element stiffness matrix of the equivalent simulation model.

[0011] Preferably, the simulation modeling module is specifically used for:

[0012] Obtain the input geometric scale parameters and material constitutive properties to construct an equivalent simulation model. Generate an additional concentrated mass matrix at the beam node of the equivalent simulation model to perform dynamic mass compensation, and apply a weight constraint force vector at the side span base node to set static and dynamic convergence boundary conditions.

[0013] Extract the maximum uplift reaction force generated by the side pier node under the set live load condition, determine the numerical range of the counterweight constraint force vector, and convert the counterweight constraint force vector into the corresponding physical counterweight mass. Combine the geometric scale parameters to generate assembly control parameters, which are used to guide the physical assembly of the scaled physical model at the end of the physical test bed.

[0014] Preferably, the tensioning solution module is specifically used for:

[0015] When iteratively solving the output bridge tension control coordinate matrix in the equivalent simulation model, a pre-biased displacement boundary condition is set at the tower top cable saddle mapping node corresponding to the equivalent simulation model. A jump-type symmetrical tensioning sequence is used to alternately activate the cable element constraint. The tangential stiffness is updated according to the structural deformation state to find the internal and external force equilibrium point. Large displacement nonlinear iterative solution is performed to generate the bridge tension control coordinate matrix.

[0016] The bridge tensioning control coordinate matrix is ​​used to guide the erection of the main cable and tensioning of the suspension cables on the scaled physical model at the end of the physical test bed. Specifically, the tensioning adjustment device on the scaled physical model is repeatedly adjusted according to the bridge tensioning control coordinate matrix at the end of the physical test bed to correct the physical main cable alignment until the main cable coordinate system of the scaled physical model coincides with the bridge tensioning control coordinate matrix, thus completing the physical erection.

[0017] Preferably, the scaled physical model has a sliding saddle assembly installed on the top of the tower at the corresponding tower top saddle mapping node. The sliding saddle assembly includes a saddle base, a support slider embedded in the sliding groove inside the saddle base, and a locking bolt.

[0018] The specific status of the physical installation includes:

[0019] The support slider moves to the predetermined scale position within the groove according to the pre-offset displacement boundary conditions and is fixed by the locking bolts. The suspenders are subjected to corresponding tension according to the bridge tensioning control coordinate matrix.

[0020] Preferably, the loading simulation module is specifically used to: generate a load case matrix including dead load case, static concentrated load case and dynamic moving load case when solving the equivalent simulation model to output theoretical reference data, and perform finite element calculation based on the load case matrix to output the theoretical reference data corresponding to each case; the loading state of the scaled physical model specifically includes: for the static concentrated load case, a solid counterweight with a set mass equivalent is arranged on the top surface of the beam of the scaled physical model;

[0021] For dynamic moving load conditions, dynamic excitation force is applied by a scaled-down test vehicle moving at a constant speed along the longitudinal direction of the main beam.

[0022] Preferably, a sensor network consisting of resistance strain gauges, grating displacement gauges, and through-hole tensile sensors is deployed on the scaled-down physical model.

[0023] When collecting measured data from the scaled physical model under load, the monitoring and evaluation module is specifically used for:

[0024] The measured strain data generated by bending of the main beam section is monitored by resistance strain gauges, the measured horizontal displacement of the tower and the measured vertical deflection of the main beam are monitored by grating displacement gauges, and the measured tension data of the rigging during the stress process is obtained by through-hole tension sensors. The data are then summarized into measured data.

[0025] Preferably, when the monitoring and evaluation module compares the measured data with the theoretical benchmark data and outputs the limit state evaluation results, it is specifically used for:

[0026] The maximum measured strain value is converted into measured extreme stress and compared with the allowable stress of the material to perform the yield test of the main beam material. The maximum measured tension data is compared with the design breaking tensile force to perform the rigging breakage test. The maximum measured vertical deflection is compared with the allowable deflection to perform the structural stiffness assessment.

[0027] When the judgment conditions are met and the comparison error between the measured data and the theoretical benchmark data is within the set allowable threshold range, the limit state assessment result of structural safety is output; where the set allowable threshold range is a tolerance limit determined by comprehensively considering the machining tolerance of the scaled physical model, the discreteness of material properties, and the measurement accuracy of the sensor.

[0028] Preferably, the main beam of the scaled physical model includes steel flange plates longitudinally spliced ​​by high-strength fasteners, and turnbuckles are connected to the bottom of the slings; the state of introducing structural defects is manifested as follows: some high-strength fasteners at the splicing of the main beam segments are loosened or removed, introducing local stiffness degradation properties, and the turnbuckles are screwed in the opposite direction to release the initial tension of a preset proportion, simulating the structural defect of loss of sling tension.

[0029] Preferably, the damage identification module, when extracting measured modal parameters, is specifically used for:

[0030] The dynamic acceleration time history signal of the scaled physical model was acquired under the action of the pulse excitation force applied by the excitation device. The modal parameters of the dynamic acceleration time history signal were identified by the random subspace method. The measured natural frequencies and measured mode shape vectors before and after the introduction of structural defects were extracted as measured modal parameters.

[0031] Preferably, when the damage identification module uses the error between the measured modal parameters and the theoretical modal parameters as the target to reverse-correct the element stiffness matrix of the equivalent simulation model, it is specifically used for:

[0032] The spatial correlation between the baseline modal parameters in the undamaged state and the measured modal parameters after introducing structural defects is calculated using the modal guarantee criterion to determine the damage location. A stiffness reduction coefficient is introduced to adjust the element stiffness matrix of the damaged region and iterative calculation is performed until the relative error between the theoretical natural frequency and the measured natural frequency obtained from the simulation calculation meets the set convergence condition. The updated bridge state parameter matrix is ​​then output. The set convergence condition is determined based on the upper limit of the allowable residual between the theoretically calculated mode and the actual measured mode in optimization theory.

[0033] This invention provides a mechanical simulation and structural monitoring system for a scaled-down model of a self-anchored suspension bridge. It offers the following advantages:

[0034] 1. This invention constructs an equivalent simulation model and outputs the tensioning control coordinate matrix of the completed bridge, thereby guiding the main cable erection and suspension cable tensioning of the scaled-down physical model. Combined with the pre-deflection displacement boundary conditions at the top of the tower and the jump-type symmetrical tensioning sequence, the virtually calculated tensioning stroke parameters can be directly mapped to the tensioning equipment at the end of the physical test bed. This effectively reduces the alignment error of self-anchored suspension bridges during the complex completion stage and improves the consistency between the scaled-down physical model and the design objectives under initial stress.

[0035] 2. This invention establishes a two-way data comparison mechanism under loading conditions by simultaneously executing virtual finite element solutions and equivalent physical loading of the solid model. Using strain gauges, displacement gauges, and tension sensors, the actual response of the solid model under dead load, static concentrated load, and dynamic moving load is obtained. The measured extreme stress, vertical deflection, and rigging tension are compared with theoretical benchmark data, enabling an objective and quantitative determination of the main beam's yielding and rigging failure, thereby improving the reliability of structural safety limit state assessment.

[0036] 3. This invention, at the physical model level, can realistically and quantitatively simulate structural defects such as local stiffness degradation and cable force loss by manipulating high-strength fasteners and turnbuckles. Based on this, by extracting measured modal parameters and using the error between measured and theoretical modal parameters as the target to correct the element stiffness matrix of the simulation model, this closed-loop verification method of introducing physical defects and correcting the virtual model provides realistic physical verification conditions for suspension bridge damage identification algorithms, while simultaneously improving the prediction accuracy of the theoretical model for the actual state of the structure. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the architecture of a scaled-down model mechanical simulation and structural monitoring system for a self-anchored suspension bridge according to an embodiment of the present invention.

[0038] Figure 2 This is a flowchart of a method for mechanical simulation and structural monitoring of a scaled model of a self-anchored suspension bridge according to an embodiment of the present invention.

[0039] Figure 3 This is a comparison distribution diagram of the tension control error of the bridge suspension cables between the experimental group and the control group of this invention;

[0040] Figure 4 This is a schematic diagram of the spatial distribution and damage identification of the main beam measuring point modal guarantee criteria of the present invention. Detailed Implementation

[0041] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] See attached document Figure 1 The present invention provides a mechanical simulation and structural monitoring system for a scaled model of a self-anchored suspension bridge, which may include: a physical test bed end and a computer-aided simulation end that is communicatively connected to the physical test bed end.

[0043] The physical test bed includes a scaled-down physical model of a self-anchored suspension bridge and a sensor network deployed on the physical model. The scaled-down physical model provides the physical and mechanical boundaries and bears the external loading conditions. The sensor network collects the force response data of the physical model under various loading conditions.

[0044] The computer-aided simulation terminal is equipped with a finite element simulation program and a data analysis and processing module. The computer-aided simulation terminal constructs a numerical calculation model equivalent to the physical model, generates assembly control parameters, receives measured data from the sensor network, and performs structural state assessment and inversion correction.

[0045] See attached document Figure 2 This invention provides a method for mechanical simulation and structural monitoring of a scaled-down model of a self-anchored suspension bridge, comprising the following steps:

[0046] The simulation modeling module, computer-aided simulation end, constructs an equivalent simulation model based on the input material constitutive properties and geometric parameters. It adds a mass matrix at the beam node for dynamic compensation, applies a weight constraint force vector at the side span base node to set the static and dynamic convergence boundary conditions, and the solid test bed end synchronously assembles the rigid base, tower pier and equivalent frame main beam according to the scale parameters output by the simulation calculation model.

[0047] The tensioning solution module sets the pre-offset displacement boundary conditions at the cable saddle mapping node at the top of the tower. The system performs large displacement nonlinear iterative solution according to the jump-type symmetrical tensioning sequence and outputs the bridge tensioning control coordinate matrix. The physical test bed adjusts the pre-offset of the sliding cable saddle according to the tensioning control coordinate matrix and performs the main cable erection and suspension cable tensioning to complete the assembly of the bridge state of the physical model.

[0048] The simulation module is loaded, and the computer-aided simulation terminal receives the set static load and dynamic load case matrix, performs finite element solution, and outputs the theoretical reference data of strain field and displacement field of each node. The physical test bed terminal simultaneously applies physical concentrated load or moving load to the corresponding span node to make the physical model enter the loading state.

[0049] The monitoring and evaluation module uses a sensor network to collect real-time data on the measured strain of the main longitudinal beam, the measured vertical deflection of the main beam, the measured displacement of the tower, and the measured tension of the rigging under the load of the physical model. The computer-aided simulation terminal receives the measured data and compares it with the theoretical benchmark data. It then performs the yield test of the main beam material, the structural stiffness assessment, and the rigging breakage assessment, and outputs the structural safety limit state assessment results.

[0050] The damage identification module introduces local stiffness degradation properties into the structure by removing the flange connection fasteners at the ends of specific segments of the main beam on the solid test bed. The sensor network captures the dynamic acceleration response data after stiffness degradation and transmits it to the computer-aided simulation end. The computer-aided simulation end extracts the measured modal parameters and uses the error between the measured modal parameters and the theoretical modal parameters as the objective function to perform reverse iteration to optimize and correct the stiffness reduction coefficient in the unit stiffness matrix, and outputs the damage location calibration results.

[0051] In this embodiment, the simulation modeling module is used to construct a computer numerical calculation model and establish virtual-real mapping boundary conditions, including the physical hardware construction and the finite element parametric modeling on the computer side. Specifically, the simulation modeling module can perform the following steps:

[0052] The computer-aided simulation terminal acquires the material constitutive properties and geometric parameters of the scaled physical model of the self-anchored suspension bridge. In this embodiment, the main beam, piers, bridge deck, and additional counterweights of the scaled physical model are made of carbon structural steel with a yield strength of 235 MPa. The main cable and suspenders are made of stainless steel wire rope. The computer-aided simulation terminal receives the input material constitutive property data, such as elastic modulus, unit weight, and yield strength. For the specific input configuration of material constitutive properties in the finite element software, those skilled in the art can set it according to the needs of conventional mechanical simulation. The above configuration method is well-known in the art and will not be elaborated here.

[0053] The computer-aided simulation terminal performs equivalent mapping of cross-sectional parameters to generate the initial total stiffness matrix of the overall structure. In this embodiment, the main beam of the scaled physical model of the self-anchored suspension bridge is a segmental frame structure, including double longitudinal beams and inner-span crossbeams. In the equivalent simulation model, the spatial cross-sectional dimensions of the double longitudinal beams are equivalently mapped to I-beam elements; the crossbeams and pier sections are equivalently mapped to channel beam elements. Specifically, the principle of equivalent mapping of cross-sectional parameters is to maintain the cross-sectional area and bending moment of inertia of the one-dimensional beam element in the computer simulation model equal to the cross-sectional area and bending moment of inertia of the corresponding three-dimensional component in the scaled physical model, thereby simplifying the calculation scale while ensuring the consistency of mechanical response. Based on the geometric node coordinates and material elastic modulus of the above elements, the computer-aided simulation terminal assembles and generates the initial total stiffness matrix of the overall structure. Initial global stiffness matrix Characterizes the system's initial resistance to deformation before external loads and constraints are applied.

[0054] The computer-aided simulation (CADS) adds mass matrices at the beam nodes and solves the dynamic characteristic equations to perform dynamic mass compensation. Because geometric scaling distorts the mass distribution of the physical model and causes deviations in the natural frequencies during dynamic simulation, additional counterweights are installed at the intervals between the beams of the main beam in the scaled-down physical model. Correspondingly, the CAS configures equivalent additional lumped mass matrices at the beam nodes. Additional lumped mass matrix The numerical values ​​are generated based on the physical mass of the steel plate counterweight with a preset thickness in the physical model. System total mass matrix. From the initial mass matrix of the structure With additional lumped mass matrix The superposition structure satisfies the following equation: ;

[0055] The computer-aided simulation terminal is based on the initial total stiffness matrix. With the total mass matrix of the system Solve the eigenvalue equation for the undamped free vibration of the system: ;

[0056] In the formula, For the system number Circular frequency, This represents the determinant of the matrix being solved. The first-order angular frequency is extracted using a computer-aided simulation. and the first-order angular frequency Converted to the first-order vertical positive symmetric mode frequency of the system The conversion formula is: The system then verified the first-order vertical positive symmetric mode frequencies. Does it meet the set dynamic similarity constraints? The system derives the time similarity ratio based on the preset geometric scaling ratio and dynamic similarity criteria, and converts it by combining the actual natural frequencies of the prototype bridge to determine the frequency range of the target first-order vertical positive symmetric mode shape, so as to ensure that the simulation calculation model is consistent with the dynamic characteristics of the real bridge.

[0057] The computer-aided simulation (CADS) applies a counterweight constraint vector to the end span base nodes, setting static and dynamic convergence boundary conditions. In this embodiment, under live load, the end span nodes of the self-anchored suspension bridge system are prone to uplift divergence. To constrain these boundary conditions, the CAS inputs a downward counterweight constraint vector at the end span base nodes. The numerical range of the counterweight constraint vector is determined by the CAS extracting the maximum uplift reaction force generated by the end span nodes under the set live load condition (i.e., the most unfavorable live load condition), and the specific value is equivalent to the mass of the physical counterweight required to achieve the theoretical maximum uplift reaction force. By applying the counterweight constraint vector, the CAS establishes stable static and dynamic convergence boundaries, preventing node displacement divergence during finite element iterative calculations.

[0058] Based on the scale parameters and physical boundary conditions output by the computer-aided simulation terminal, a scaled-down physical model is simultaneously assembled at the physical test bed end. The scaled-down physical model includes a rigid foundation base, portal piers, and an equivalent frame main beam. In specific implementation, the rigid foundation base is constructed using steel plates and longitudinal and transverse channel steel welded together to form a grid structure. The side span bases have reserved load-bearing areas for placing physical counterweights to resist uplift forces. Both the main piers and side piers are constructed using channel steel to form a portal frame structure and are anchored to the rigid foundation base by fasteners at the bottom, ensuring consistent relative elevations of the pier bases. The equivalent frame main beam is divided into multiple standard beam segments, which are longitudinally spliced ​​together using steel flange plates at the ends and high-strength fasteners. Preferably, the segmental flange splicing structure simulates the construction beam segment joints of a real bridge, while also providing a structural basis for subsequently removing local fasteners to introduce structural stiffness degradation properties. The aforementioned additional counterweights are detachably installed on the top surface of the crossbeams of the equivalent frame main beam using fasteners.

[0059] In this embodiment, the tensioning solution module is used to simulate the nonlinear mechanical process of the construction of a self-anchored suspension bridge and generate theoretical control coordinates to guide the assembly of the physical model. Specifically, the tensioning solution module can perform the following steps:

[0060] The computer-aided simulation (CADS) sets a pre-deflection displacement boundary condition at the cable saddle mapping node at the top of the tower. In this embodiment, the tensioning of the main cable during the construction of a self-anchored suspension bridge will cause tower deformation, so it is necessary to set a pre-deflection at the top of the tower in advance to balance the tension of the main cable. The CAS introduces a sliding degree of freedom in the longitudinal direction at the cable saddle mapping node corresponding to the top of the tower in the simulation model. The system sets the cable saddle pre-deflection displacement boundary condition to slide a preset pre-deflection value in the direction of the side span, that is, inputting a preset pre-deflection displacement boundary with a negative longitudinal displacement in the coordinate system. This preset pre-deflection value is the theoretical displacement of the cable saddle in the longitudinal direction of the bridge, which is pre-calculated iteratively by the CAS based on the horizontal component force balance condition of the main cables on both sides of the main tower under the dead load state of the completed bridge, to ensure that the tower does not generate eccentric bending moment after the bridge is completed. After the sliding is set, the system applies a fixed constraint to the cable saddle mapping node, establishing a static boundary condition equivalent to physical jacking and locking.

[0061] The computer-aided simulation (CADS) performs large-displacement nonlinear iterative solutions using a jump-type symmetrical tensioning sequence, outputting the tensioning control coordinate matrix of the completed bridge. In this embodiment, the cable tensioning of the self-anchored suspension bridge exhibits significant geometrical nonlinear stress characteristics. To ensure the smoothness of the completed bridge alignment and maintain the force balance on both sides of the towers, the CADS sets a specific jump-type symmetrical tensioning sequence. Preferably, the jump-type symmetrical tensioning sequence adopts a jump-cross activation method from the mid-span to both ends. The ordering principle of the above tensioning sequence is: prioritize tensioning the cables at the mid-span and the root of the main tower that have a greater stress and a significant impact on the main beam alignment, and advance symmetrically on both sides alternately to control the peak bending moment of the equivalent frame main beam during construction and maintain the force balance of the portal tower piers. The CADS activates the corresponding cable element constraints in the finite element model sequentially according to the above sequence. Based on the principle of large-displacement nonlinear mechanics, the CADS performs incremental iterative solutions. Specifically, the physical principle of large-displacement nonlinear iterative solution lies in the fact that as the tensile force increases, the geometry of the structure changes significantly, and the system continuously updates the tangential stiffness based on the current deformation state to find the equilibrium point of internal and external forces. The structural nonlinear equilibrium iteration satisfies the following equations: ;

[0062] In the formula, Here is the system tangent stiffness matrix. The vector of unbalanced forces at the nodes. This represents the incremental vector of node displacement. After the iterative calculation converges, the computer-aided simulation terminal outputs a reference coordinate matrix to guide the physical installation. The reference coordinate matrix specifically includes the spatial coordinate matrix of the empty cable during the initial stage of main cable erection and the tension control coordinate matrix of the completed bridge after it reaches force equilibrium.

[0063] The sliding saddle assembly is adjusted at the end of the physical test bed according to the pre-offset displacement boundary conditions. In this embodiment, to reproduce the pre-offset displacement boundary conditions set by the simulation system at the physical entity level, a sliding saddle assembly is installed on the top of the cable tower in the physical model. Specifically, the physical structure of the sliding saddle assembly includes a saddle base, a support slider, and locking bolts. The saddle base is fixedly installed on the top of the portal pier, and the saddle base has grooves distributed along the bridge direction inside. The support slider is embedded in the grooves, and the top of the support slider has a groove for supporting the main cable. Locking bolts are installed through the side of the saddle base. According to the preset pre-offset value output by the simulation, the operator uses a vernier caliper or a high-precision ruler as a position reference to drive the support slider to move within the groove to the predetermined scale position. After the support slider reaches the predetermined scale position, the locking bolts on the side are tightened to completely fix the support slider to the saddle base. The above mechanical structure realizes the accurate simulation of the saddle jacking and anchoring mechanical behavior during the actual bridge construction process by the physical model.

[0064] The physical test bed end executes the main cable erection and suspender tensioning according to the bridge tensioning control coordinate matrix, completing the assembly of the physical model in the bridge-like state. Stainless steel wire rope is used as the main cable at the physical test bed end, laid on the support sliders of the sliding saddle assemblies on both sides. Both ends of the main cable are connected and anchored to the physical anchoring nodes at both ends of the rigid foundation base. The top of the suspender is fixedly connected to the main cable via a cable clamp assembly, and the bottom of the suspender is connected to the crossbeam of the equivalent frame main beam. To precisely adjust the cable force to match the theoretical state output by the computer-aided simulation, a tension adjustment device is connected in series between the bottom of the suspender and the crossbeam. Preferably, the tension adjustment device can be implemented using turnbuckles. The operator applies tension to each suspender gradually by tightening the turnbuckles according to the aforementioned jump-type symmetrical tensioning sequence. During the physical tensioning process, operators use miniature cable force sensors to monitor the actual tension and compare the spatial coordinate matrix of the empty cable with the tensioning control coordinate matrix of the completed bridge. They repeatedly adjust the tensioning device to correct the physical main cable alignment until the main cable coordinate system of the physical model coincides with the tensioning control coordinate matrix of the completed bridge, thus completing the assembly of the self-anchored suspension bridge under the real physical boundary.

[0065] In this embodiment, the loading simulation module is used to synchronously simulate the actual stress state of a self-anchored suspension bridge during operation on both the computer and physical sides, and output theoretical baseline data for subsequent evaluation. Specifically, the loading simulation module can perform the following steps:

[0066] The computer-aided simulation terminal is configured with a load case matrix containing various stress conditions. In this embodiment, to comprehensively simulate the most unfavorable stress state of a self-anchored suspension bridge during actual operation, the load case matrix specifically includes a dead load case, three typical static concentrated load cases, and a dynamic moving load case. The dead load case refers to the structural self-weight state. Specifically, the three typical static concentrated load cases include applying equivalent concentrated loads of a set mass to the mid-span section, quarter-span section, and three-quarter-span section of the main girder. The set mass is determined by analyzing the highest-grade highway live load in the prototype bridge design standard and converting it to the equivalent extreme load of the scaled physical model according to the set geometric similarity ratio and area equivalence principle. In this embodiment, the dynamic moving load case is input into the calculation model with a set moving load time history function to simulate the traffic flow load passing uniformly across the bridge deck.

[0067] The computer-aided simulation (CADS) performs finite element analysis based on a predefined load case matrix, outputting theoretical baseline data for each node. In this embodiment, for static concentrated load cases, the CAS transforms the predefined load cases into corresponding nodal external load vectors. The physical principle of finite element statics analysis lies in the linear elastic equilibrium condition between the internal forces of the structure and the nodal displacements under external loads. The linear elastic static equilibrium equations of the structure satisfy the following formula: ;

[0068] In the formula, This is the initial overall stiffness matrix of the entire structure. This is the nodal external load vector that includes static concentrated load cases. To obtain the structural node displacement vectors, in this embodiment, for the dynamic moving load case, the computer-aided simulation terminal performs transient dynamic time integration to solve the problem. The physical principle of the dynamic solution is that the structure under the action of a moving load not only produces static displacement but also dynamic vibration caused by inertial forces and damping forces. The dynamic equilibrium equations satisfy the following formula: ;

[0069] In the formula, The total mass matrix of the system. Here is the system damping matrix. For the nodal acceleration vector, For the node velocity vector, Let be the nodal displacement vector that varies with time. This represents the moving load vector that varies over time. After the solution is obtained, the computer-aided simulation tool extracts the theoretical displacement and strain values ​​of the nodes for the main beam and tower elements. These theoretical displacement and strain values ​​together constitute the theoretical baseline data. The theoretical baseline data serves as an evaluation reference standard for assessing the safety of the subsequent scaled-down physical model under load.

[0070] Equivalent physical loads are applied to the corresponding span nodes at the end of the physical test bed, causing the scaled physical model to enter a loaded state. In this embodiment, the physical test bed needs to maintain a strict virtual-real correspondence with the simulated working conditions at the computer-aided simulation end. For the concentrated load conditions set at the mid-span, quarter-span, and three-quarter-span sections, the operator places a physical counterweight with an equivalent mass on the top surface of the crossbeam corresponding to the equivalent frame main beam. Preferably, the physical counterweight is a standard cast iron weight to ensure the accuracy of the loaded weight and the stability of the contact surface. In addition to the static concentrated load, a scaled moving test vehicle is configured at the end of the physical test bed. In order to synchronously simulate the dynamic moving load conditions, in actual operation, the operator drives the scaled moving test vehicle to travel at a constant speed along the bridge direction on the equivalent frame main beam, simulating the dynamic excitation force generated by the vehicle on the main beam when traveling on the bridge deck, so that the scaled physical model produces a realistic dynamic force response. The specific traction drive mode of the scaled-down mobile test vehicle can be configured by those skilled in the art according to the requirements of conventional bridge dynamic loading tests. The above settings are well-known technologies in the field and will not be elaborated here.

[0071] In this embodiment, the monitoring and evaluation module is used to acquire the actual physical response data of the physical model during loading, and to evaluate the safety status of the structure based on relevant mechanical judgment conditions. Specifically, the monitoring and evaluation module can perform the following steps:

[0072] A sensor network for acquiring physical model state data is deployed at the end of the physical test bed. In this embodiment, the sensor network specifically consists of resistance strain gauges, grating displacement gauges, and through-hole tension sensors. Operators attach resistance strain gauges to the upper and lower flange surfaces of the mid-span, quarter-span, and three-quarter-span sections of the equivalent frame main beam to monitor the measured strain data generated by bending of the main beam section. Grating displacement gauges are fixedly installed at the top of the portal tower pier and at the bottom of the mid-span of the main beam to monitor the measured horizontal displacement of the tower and the measured vertical deflection of the main beam under load. Through-hole tension sensors are connected in series at the connection point between the bottom of the suspenders and the crossbeam to acquire the measured tension data of the suspenders during the stress process. By arranging the above sensors, a measurement channel for acquiring multi-dimensional physical field deformation and stress state is established at the end of the physical test bed.

[0073] The sensor network collects response data of the physical model under load in real time and transmits it to the computer-aided simulation terminal. In this embodiment, when a static concentrated load or a dynamic moving load is applied to the physical test bed, the aforementioned sensors simultaneously capture the analog electrical signals generated by structural deformation and stress. The data acquisition instrument receives the analog electrical signals in real time and converts them into digital signals, which are then transmitted to the computer-aided simulation terminal through a communication interface. The specific filtering and analog-to-digital conversion methods of the data acquisition instrument can be configured by those skilled in the art according to the requirements of conventional bridge electrical testing experiments. The specific filtering and analog-to-digital conversion methods described above are well-known technologies in the field and will not be elaborated upon here.

[0074] The computer-aided simulation terminal receives measured data and compares it with theoretical benchmark data to perform yield determination of the main beam material. In this embodiment, the computer-aided simulation terminal extracts the maximum measured strain value fed back by the resistance strain gauge under load. Based on the mechanical principles of linear elastic materials, before the structural material enters the plastic yielding stage, the internal stress and surface strain of the material have a linear relationship that is directly proportional. The computer-aided simulation terminal uses Hooke's law to convert the maximum measured strain value into measured extreme stress, and the conversion calculation satisfies the following formula: ;

[0075] In the formula, To measure the extreme stress, The elastic modulus of the material used for the main beam in the physical model (e.g., carbon structural steel) is typically taken as 2.06 × 10⁻⁶. 5 Megapascals This represents the maximum measured strain value. After calculation, the system performs a material yield test, and the test conditions satisfy the following formula: ;

[0076] In the formula, This refers to the allowable stress of the material. The specific value is determined by dividing the material's yield strength (e.g., 235 MPa) by the material safety factor. In this embodiment, based on the stress limitations of the main beam in conventional bridge steel structure design specifications, the material safety factor is taken as 1.5, thereby determining the allowable stress of the material. The specific value limits.

[0077] The computer-aided simulation (CADS) performs rigging failure assessment and structural stiffness evaluation, outputting the structural safety limit state assessment results. In this embodiment, the suspenders of a self-anchored suspension bridge are critical flexible tension members; rigging failure can trigger localized or even systemic continuous failure of the bridge system. The CAS extracts the maximum measured tension data fed back by the through-hole tension sensor and compares it with the design failure tension. The rigging failure assessment condition satisfies the following formula: ;

[0078] In the formula, This represents the maximum measured tension data. This refers to the ultimate breaking tensile strength of the stainless steel wire rope. This refers to the rigging safety factor. In this embodiment, based on the stringent requirements for the tensile safety margin of rigging in the suspension bridge design code, the rigging safety factor is... The value is set between 2.5 and 3.0.

[0079] In addition to stress and cable force, the computer-aided simulation system extracts the maximum measured vertical deflection data of the main girder from the feedback of the grating displacement gauge. Based on the principle of structural stiffness assessment, the vertical deflection of the main girder reflects the overall resistance to deformation of the bridge. The system compares the maximum measured vertical deflection with the allowable deflection, and the judgment condition satisfies the following formula: ;

[0080] In the formula, The maximum measured vertical deflection of the main beam. This refers to the allowable deflection of the main beam. In this embodiment, the allowable deflection of the main beam... It is determined based on one four-hundredth of the bridge span according to the physical model.

[0081] The computer-aided simulation unit integrates the yield test results of the main beam material, the rigging breakage test results, and the structural stiffness assessment results to output a safety limit state assessment result. Specifically, when the measured extreme stress, maximum measured tension data, and maximum measured vertical deflection all satisfy the above-mentioned judgment formula, and the error compared with the theoretical benchmark data output by the loading simulation module is within 10% of the set allowable threshold range, the system outputs an assessment result indicating that the current structural state is safe. Generally, the set allowable threshold range is a tolerance limit determined comprehensively based on the machining tolerance of the scaled physical model, the dispersion of material properties, and the measurement accuracy of the sensors. In this embodiment, preferably, the above-mentioned allowable error threshold range is specifically set to within 10%.

[0082] In this embodiment, the damage identification module is used to simulate the damage state of a real bridge through parameter variations of a physical entity, and to achieve the location and quantitative assessment of damage using dynamic response data. Specifically, the damage identification module can perform the following steps:

[0083] A pre-set structural defect is introduced at the end of the physical test bed to simulate the actual damage conditions of a self-anchored suspension bridge. In this embodiment, common bridge damage during long-term service includes main girder stiffness degradation and cable tension loss. To equivalently simulate these damages on a scaled-down physical model, operators employ mechanical adjustments. Specifically, for main girder stiffness degradation, operators partially loosen or remove high-strength fasteners at the joints of equivalent frame main girder segments, weakening the connection stiffness between flange plates, thereby simulating a reduction in the local cross-sectional stiffness of the main girder. For cable tension loss, operators reverse-tighten the turnbuckles at the bottom of the cable and monitor the process with a through-type tension sensor, releasing a pre-set initial tension ratio to simulate the cable tension decrease caused by cable slack or wire breakage, representing the bridge at a predetermined damage stage. These mechanical adjustments establish controllable physical damage boundary conditions.

[0084] The sensor network collects dynamic response data of the physical model under vibration and extracts modal parameters. In this embodiment, to obtain the dynamic characteristics of the structure before and after damage, a vibration device is configured at the end of the physical test bed. Specifically, the vibration device can be an electromagnetic vibrator or a hammer, applying a pulsed vibration force to the equivalent frame main beam. Under the action of the vibration force, acceleration sensors distributed on the main beam and tower piers capture the dynamic acceleration time history signal of the physical model in real time. The computer-aided simulation terminal receives the above dynamic acceleration time history signal and uses the random subspace method to identify modal parameters of the dynamic acceleration time history signal, extracting the measured natural frequencies and measured mode shape vectors of the physical model before and after damage. For the specific mathematical derivation process of extracting modal parameters using the random subspace method, those skilled in the art can refer to conventional structural dynamics theory for implementation. The above mathematical derivation process is a well-known technology in this field and will not be elaborated here.

[0085] The computer-aided simulation (CADS) constructs damage-sensitive indices and performs damage localization and quantitative assessment. In this embodiment, the CAS compares the baseline modal parameters under undamaged conditions with the measured modal parameters under damaged conditions. Since a single frequency change is not sensitive to local damage, the system uses the modal guarantee criterion as a quantitative indicator for damage localization and assessment. The physical principle of the modal guarantee criterion is to quantify the degree of structural morphological change by calculating the spatial correlation between two mode shape vectors. The more similar the two mode shape vectors are, the closer the calculation result of the modal guarantee criterion is to 1; conversely, if local structural damage causes mode shape distortion, the calculation result will decrease significantly. The calculation of the modal guarantee criterion satisfies the following formula: ;

[0086] In the formula, For the first First-order mode guarantee criterion value, The first one extracted in the undamaged state Measured mode shape vectors of order 1 The first extracted under the damaged state Measured mode shape vectors of order, superscript This represents the vector transpose operation. When the calculated result... When the value is close to 1, it indicates that no significant structural variation has occurred at the corresponding measuring point location; when When the value deviates significantly from 1 and falls below the set judgment threshold, the system determines that structural damage has occurred in the area where the measurement point is located. In this embodiment, the specific value of the judgment threshold is set to 0.90. The value of 0.90 is an engineering tolerance limit determined after comprehensively considering environmental noise interference and accelerometer measurement errors.

[0087] The computer-aided simulation (CADS) terminal performs finite element model correction to achieve synchronous updates of virtual-to-real mapping parameters. In this embodiment, to ensure that the virtual model on the computer terminal can realistically reflect the mechanical state of the damaged physical entity, the CAS terminal uses the measured natural frequencies and measured mode shape vectors as objective functions to inversely correct the local stiffness parameters in the initial finite element model. The physical principle of model correction is based on optimization theory, minimizing the residual between the theoretically calculated modes and the actual measured modes. The system adjusts the element stiffness matrix of the damaged region by introducing stiffness reduction coefficients, continuously performing iterative calculations until the error between the theoretical modal parameters obtained from the simulation calculation and the measured modal parameters meets the convergence condition, and outputs the updated bridge state parameter matrix; wherein, the bridge state parameter matrix includes at least the corrected stiffness reduction coefficients of each element and the calibrated damage location information. The set convergence condition is determined based on the upper limit of the allowable residual between the theoretically calculated modes and the actual measured modes in optimization theory. In this embodiment, preferably, the convergence condition is specifically set as the relative error between the theoretical natural frequency and the measured natural frequency being less than five percent.

[0088] Specific application examples:

[0089] This embodiment uses a scaled-down physical model test of a double-tower self-anchored suspension bridge as an example. The main span of the prototype bridge is 150 meters, and the geometric scale selected for this system is 1:30. The main span of the physical model is set at 5.0 meters, and the side spans are set at 1.5 meters.

[0090] Simulation modeling and assembly stage:

[0091] In the computer-aided simulation, input the constitutive material properties of carbon structural steel: elastic modulus. MPa, yield strength is 235MPa. Based on the principle of scale equivalence, an initial overall stiffness matrix including the main beam, tower piers, and suspension cables is generated. To compensate for the mass distribution distortion caused by the scaling, counterweights are added at the beam nodes, and the system generates an additional lumped mass matrix. And assemble the total mass matrix of the system. Solve the eigenvalue equation for the undamped free vibration of the system: ;

[0092] Extracting the first-order angular frequency The first-order vertical positive symmetric mode frequency was obtained by conversion. Hz, which conforms to the dynamic similarity criterion.

[0093] Subsequently, the physical assembly of the steel frame main beam, portal tower pier, and rigid base was completed at the end of the physical test bed according to the above-mentioned dimensional parameters.

[0094] Tensioning solution and bridge completion stage:

[0095] The system sets a pre-offset value of 12mm for sliding towards the side span at the cable saddle mapping node at the top of the tower. This is based on the set jump-type symmetrical tensioning.

[0096] The sequence is used to perform large-displacement nonlinear iterative solutions on the computer side. The relationship between tangent stiffness and unbalanced forces satisfies: ;

[0097] After iterative convergence, the bridge tension control coordinate matrix is ​​output. The operator on the physical end pushes the support slider of the sliding saddle assembly 12mm towards the side span and locks it. Then, the tension is gradually applied by rotating the turnbuckle in the opposite direction until the physical main cable alignment coincides with the coordinate matrix output by the computer, thus completing the virtual and physical synchronous bridge construction.

[0098] Loading monitoring and status assessment phase

[0099] Static loads were simulated by placing 50kg standard cast iron weights at the quarter-span and mid-span of the main span of the physical model. The maximum measured strain value of the lower flange at mid-span was collected by resistance strain gauges. The system utilizes Hooke's law for extreme stress transformation: ;

[0100] Calculated MPa. The judgment condition is... (Material allowable stress) The pressure (MPa) indicates that the main beam material is in a safe elastic stage. Simultaneously, the maximum measured tension data from the through-hole tension sensor... The measured deflection at mid-span was kN, far below the safety limit for breaking tensile force. The deviation between the measured mid-span deflection and the theoretical deflection was only 4.2% (less than the set tolerance of 10%), and the system output an assessment result indicating that the structure is in a safe state.

[0101] Damage identification and inversion correction stage:

[0102] Operators manually loosened the fasteners of the flange connection at one-quarter of the main span to simulate local stiffness degradation. Under pulsed excitation force, the system acquired acceleration signals and extracted measured damaged modal parameters. The computer then used modal assurance criteria to calculate the extracted modal parameters under the undamaged state. Measured mode shape vector The first extracted from the damaged state Measured mode shape vector Spatial correlation: ;

[0103] Calculations revealed that the MAC value of the local mode shape node corresponding to the damaged area dropped to 0.82 (below the set threshold of 0.90), allowing the system to accurately locate the damage. Subsequently, the system used the measured natural frequencies and mode shapes as targets to reverse-correct the element stiffness matrix reduction coefficients in the simulation model for that region until the error between the theoretical and measured frequencies was less than 5%, thus completing the update of the virtual-real mapping model.

[0104] Experimental Verification and Effect Comparison: Comparative experiments were conducted to verify the differences in practical application effects between the system of this invention and conventional testing methods. The experiments were conducted using a scaled-down physical model of a self-anchored suspension bridge with a main span of 5 meters, divided into groups. The control group used conventional methods, first performing numerical simulation calculations, then tensioning the physical model according to the design drawings; no data interaction or correction was performed between the simulation and physical ends. The experimental group used the system provided by this invention, performing data interaction and correction during the testing process.

[0105] Comparison of bridge completion status control effects (see attached document) Figure 3 After the main cable erection and sling tensioning were completed, the measured tensions of 15 key slings in both the control and experimental groups were recorded. The relative errors between the measured values ​​and the theoretical cable forces were calculated. The results are attached. Figure 3 Appendix Figure 3 This is a two-dimensional line graph. The horizontal axis represents the cable number, and the vertical axis represents the percentage of cable tension error. Dashed lines with square markings represent control group data, solid lines with circular markings represent experimental group data, and the horizontal line in the middle is the 0-degree baseline. (See attached...) Figure 3 It can be seen that the cable force error in the control group fluctuated significantly, with a maximum positive error of 25% and a maximum negative error of 22%. This construction method without interactive correction is prone to causing uneven local stress on the equivalent main beam. The error curve of the experimental group was relatively concentrated near the 0 mark, and the cable force deviation of each suspender remained within ±6.5%. The results show that the tension solution module of this invention can improve the force control accuracy of the physical model in the completed bridge state through interactive calculation iteration and pre-offset compensation.

[0106] Comparison of damage identification effects (see attached document) Figure 4At the flange joints corresponding to measuring points 4 and 7 of the main beam in the physical model, local stiffness degradation damage was simulated by loosening some fasteners. (See attached diagram.) Figure 4 The horizontal axis represents the physical measurement point number, and the vertical axis represents the modal guarantee criterion value calculated from the measured vibration mode vectors before and after damage (the closer the value is to 1, the less damage occurred; the lower the value, the greater the damage). Solid lines with triangle markers connect the measurement point data, and a dashed threshold line is set at the vertical axis of 0.90. (See attached diagram.) Figure 4 The data shows that in areas without predefined damage (such as measurement points 1 to 3, 5 to 6, and 8 to 10), the modal guarantee criterion value is around 1.0, which is higher than the judgment threshold of 0.90. However, at measurement points 4 and 7 with predefined damage, the data decreases, with values ​​dropping to 0.82 and 0.81 respectively, which are lower than the threshold of 0.90.

Claims

1. A mechanical simulation and structural monitoring system for a scaled-down model of a self-anchored suspension bridge, characterized in that, Includes both physical testbed and computer-aided simulation ends; The computer-aided simulation terminal includes: The simulation modeling module is used to construct an equivalent simulation model on the computer-aided simulation terminal and output assembly control parameters based on the equivalent simulation model to guide the assembly of a scaled-down physical model on the physical test bed terminal. The tensioning solution module is used to iteratively solve and output the bridge tensioning control coordinate matrix in the equivalent simulation model. The bridge tensioning control coordinate matrix is ​​used to guide the main cable erection and suspension tensioning of the scaled physical model. The simulation module is loaded, which is used to solve the equivalent simulation model to output theoretical reference data and output the corresponding equivalent physical load parameters, which are used to establish the loading state on the scaled physical model. The monitoring and evaluation module is used to collect measured data of the scaled physical model under the loading state, compare the measured data with the theoretical reference data, and output the limit state evaluation result. The damage identification module is used to extract measured modal parameters after structural defects are introduced into the scaled physical model, and to use the error between the measured modal parameters and the theoretical modal parameters as the target to reverse correct the element stiffness matrix of the equivalent simulation model.

2. The mechanical simulation and structural monitoring system for a scaled model of a self-anchored suspension bridge according to claim 1, characterized in that, The simulation modeling module is specifically used for: The equivalent simulation model is constructed by obtaining the input geometric scale parameters and material constitutive properties. An additional concentrated mass matrix is ​​generated at the beam node of the equivalent simulation model to perform dynamic mass compensation. A compressive constraint force vector is applied at the side span base node to set the static and dynamic convergence boundary conditions. Extract the maximum uplift reaction force generated by the side pier node under the set live load condition, determine the numerical range of the counterweight constraint force vector, and convert the counterweight constraint force vector into the corresponding physical counterweight mass. Combine the geometric scale parameters to generate assembly control parameters, which are used to guide the physical test bed end to complete the physical assembly of the scaled physical model.

3. The mechanical simulation and structural monitoring system for a scaled model of a self-anchored suspension bridge according to claim 1, characterized in that, The tension solving module is specifically used for: When iteratively solving the output bridge tension control coordinate matrix in the equivalent simulation model, a pre-biased displacement boundary condition is set at the tower top cable saddle mapping node corresponding to the equivalent simulation model. A jump-type symmetrical tensioning sequence is used to alternately activate the cable element constraint. The tangential stiffness is updated according to the structural deformation state to find the internal and external force equilibrium point. Large displacement nonlinear iterative solution is performed to generate the bridge tension control coordinate matrix. The bridge tensioning control coordinate matrix is ​​used to guide the physical test bed end to perform main cable erection and suspension tensioning on the scaled physical model. Specifically, the physical test bed end repeatedly adjusts the tensioning adjustment device on the scaled physical model according to the bridge tensioning control coordinate matrix to correct the physical main cable alignment until the main cable coordinate system of the scaled physical model coincides with the bridge tensioning control coordinate matrix, thus completing the physical erection.

4. The mechanical simulation and structural monitoring system for a scaled model of a self-anchored suspension bridge according to claim 3, characterized in that, The scaled-down physical model has a sliding saddle assembly installed on the top of the tower corresponding to the top saddle mapping node. The sliding saddle assembly includes a saddle base, a support slider embedded in the sliding groove inside the saddle base, and a locking bolt. The specific state of the physical erection includes: the support slider moves to a predetermined scale position in the groove according to the pre-offset displacement boundary condition and is fixed by the locking bolt; the sling is subjected to corresponding tension according to the bridge tensioning control coordinate matrix.

5. The mechanical simulation and structural monitoring system for a scaled model of a self-anchored suspension bridge according to claim 1, characterized in that, The loading simulation module is specifically used for: When solving the equivalent simulation model to output theoretical reference data, a load case matrix is ​​generated that includes dead load case, static concentrated load case and dynamic moving load case. Finite element calculation is performed based on the load case matrix to output the theoretical reference data corresponding to each case. The loading states of the scaled physical model specifically include: For the static concentrated load condition, a solid counterweight with an equivalent mass is arranged on the top surface of the beam in the scaled physical model. For the aforementioned dynamic moving load condition, a dynamic excitation force is applied by a scaled-down test vehicle moving at a constant speed along the longitudinal direction of the main beam.

6. The mechanical simulation and structural monitoring system for a scaled model of a self-anchored suspension bridge according to claim 1, characterized in that, The scaled-down physical model is equipped with a sensor network consisting of resistance strain gauges, grating displacement gauges, and through-hole tensile sensors. When collecting measured data from the scaled physical model under the loading state, the monitoring and evaluation module is specifically used for: The measured strain data generated by bending of the main beam section is monitored by the resistance strain gauge, the measured horizontal displacement of the tower and the measured vertical deflection of the main beam are monitored by the grating displacement gauge, and the measured tension data of the rigging during the stress process is obtained by the through-hole tension sensor. The data are then summarized as the measured data.

7. The mechanical simulation and structural monitoring system for a scaled model of a self-anchored suspension bridge according to claim 6, characterized in that, When the monitoring and evaluation module compares the measured data with the theoretical benchmark data and outputs the limit state evaluation result, it is specifically used for: The maximum measured strain value is converted into measured extreme stress and compared with the allowable stress of the material to perform the yield test of the main beam material. The maximum measured tension data is compared with the design breaking tensile force to perform the rigging breakage test. The maximum measured vertical deflection is compared with the allowable deflection to perform the structural stiffness assessment. When the judgment condition is met and the comparison error between the measured data and the theoretical benchmark data is within the set allowable threshold range, the limit state assessment result of the structural state safety is output. The set allowable threshold range is a tolerance limit determined by comprehensively considering the machining tolerances, material property dispersion, and sensor measurement accuracy of the scaled physical model.

8. The mechanical simulation and structural monitoring system for a scaled model of a self-anchored suspension bridge according to claim 1, characterized in that, The main beam of the scaled-down physical model includes steel flange plates longitudinally spliced ​​together by high-strength fasteners, and turnbuckles are connected to the bottom of the slings. The state of introducing structural defects is manifested as follows: The high-strength fasteners at the splicing points of the main beam segments are loosened or removed, introducing local stiffness degradation properties. The turnbuckles are also tightened in the opposite direction to release a preset proportion of the initial tension, simulating the structural defect of loss of cable tension.

9. The mechanical simulation and structural monitoring system for a scaled model of a self-anchored suspension bridge according to claim 1, characterized in that, The damage identification module is specifically used for extracting measured modal parameters as follows: The dynamic acceleration time history signal of the scaled physical model is acquired under the action of the pulse excitation force applied by the excitation device. The modal parameters of the dynamic acceleration time history signal are identified by the random subspace method. The measured natural frequencies and measured mode shape vectors before and after the introduction of the structural defect are extracted as the measured modal parameters.

10. The mechanical simulation and structural monitoring system for a scaled model of a self-anchored suspension bridge according to claim 9, characterized in that, When the damage identification module uses the error between the measured modal parameters and the theoretical modal parameters as a target to reverse-correct the element stiffness matrix of the equivalent simulation model, it is specifically used for: The spatial correlation between the baseline modal parameters in the undamaged state and the measured modal parameters after the introduction of the structural defects is calculated using the modal guarantee criterion to determine the damage location. The stiffness reduction coefficient is introduced to adjust the element stiffness matrix of the damaged area and iterative calculation is performed until the relative error between the theoretical natural frequency and the measured natural frequency obtained by simulation calculation meets the set convergence condition. The updated bridge state parameter matrix is ​​then output. The convergence condition is determined based on the upper limit of the residual between the theoretically calculated mode and the actual measured mode in optimization theory.

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