Modular support system and monitoring system for bridge demolition

Abstract

The application discloses a module type support system and monitoring system for bridge demolition, constructs a pole space arrangement scheme by collecting bridge span, beam section, material strength and other parameters, calls a pole bearing capacity calculation model to obtain stress data, generates dynamic monitoring data in combination with a structure health index evaluation model, adjusts support system parameters accordingly, and repeatedly operates until segmented beam body demolition is completed. The system extends the bearing capacity calculation and health evaluation model, introduces an innovative formula related to bridge parameters, refines the sub-steps of support calculation, health evaluation and parameter adjustment, and includes six related units such as parameter collection, pole arrangement generation and model operation, so as to realize dynamic adaptation and accurate monitoring of the support system and the structure state in the bridge demolition process.

Description

Technical Field

[0001] This invention relates to the field of bridge demolition, and in particular to a modular support system and monitoring system for bridge demolition. Background Technology

[0002] In the process of upgrading and renovating transportation infrastructure, a large number of old bridges face demolition. Such operations require addressing issues such as dynamic load transfer during beam segmentation, structural stress redistribution, and safety control under complex conditions. Bridge structures vary significantly in span, beam cross-sectional shape, service life, and material properties. During demolition, the support system must adapt to the structural characteristics at different stages, while simultaneously monitoring the structural health status in real time to mitigate the risk of collapse. Traditional support methods rely heavily on experience-based design, and monitoring methods lack dynamic linkage with the support system, making it difficult to meet the safety and accuracy requirements of complex bridge demolition operations. Therefore, there is an urgent need to construct a modular support and monitoring system that integrates pole bearing capacity calculation and structural health assessment.

[0003] In existing technologies, the calculation of the support pole bearing capacity does not fully integrate the specific parameters of the bridge. It only uses a general mechanical model for calculation, without considering the influence of the bridge's own characteristics, such as beam cross-sectional dimensions, concrete strength, reinforcement configuration, and service wear, on the support stress. This leads to deviations between the calculation results and the actual stress state, making it impossible to accurately guide the design of the support system. At the same time, there is a disconnect between the structural health index evaluation and the adjustment of the support system. The health evaluation relies on only a single monitoring data and does not establish a dynamic correlation with the pole stress data. This makes it impossible to feed the evaluation results back to the support parameter adjustment process in a timely manner, making it difficult to achieve real-time adaptation of the support system to the structural characteristics of the bridge during the demolition stage, affecting the safety and efficiency of the demolition operation. Summary of the Invention

[0004] In order to overcome the shortcomings and deficiencies of the existing technology, the present invention provides a modular support system and monitoring system for bridge demolition.

[0005] The technical solution adopted in this invention is a modular support system for bridge demolition, comprising the following steps:

[0006] S1. Collect the structural geometric parameters of the parts to be supported within the bridge demolition area, and import the structural geometric parameters into the preset parameter storage unit for classification and labeling;

[0007] S2. Based on the parameters collected in S1, construct a spatial arrangement scheme for the uprights in the modular support system. This scheme needs to be combined with the sequence of beam segmentation during bridge demolition to determine the longitudinal spacing, transverse spacing, and coordinates of the contact point between the top of the upright and the bottom of the beam. At the same time, it is necessary to clarify the layout angle and node connection method of the transverse connecting members between adjacent uprights.

[0008] S3. Based on the pole layout parameters determined in S2, call the pole bearing capacity calculation model, input the elastic modulus, moment of inertia, design value of compressive strength, pole height, foundation bottom reaction coefficient, wind load direction and magnitude, and temperature change range of the pole material, and obtain the axial force, bending moment and shear force distribution data of the pole under vertical load, horizontal load and combined load through model calculation;

[0009] S4. Simultaneously start the structural health index evaluation model, associate the original bridge structural parameters collected in S1 with the pole stress data calculated in S3, and generate a dynamic monitoring data sequence of stress transfer coefficient, structural deformation rate and damage evolution trend of the support system and beam contact interface during bridge demolition through the built-in analysis module of the model.

[0010] S5. Based on the dynamic monitoring data sequence output by S4, adjust the real-time control parameters of the modular support system. This adjustment process involves the displacement of the fine-tuning device at the top of the pole, the preload of the lateral stabilizing support, the working pressure of the hydraulic jack, and the overall stiffness matching coefficient of the support system, so that the stress state of the support system is dynamically adapted to the structural characteristics of the bridge beam during the dismantling stage.

[0011] S6. Repeat steps S3 to S5 until the current segment of the beam is completely detached from the original structure and transferred to the designated area during the bridge demolition operation. Then reset the support system and monitoring parameters for the next segment of the beam.

[0012] Furthermore, the pole bearing capacity calculation model described in S3 includes a formula for calculating the stable bearing capacity of the pole under eccentric compression, which is: Where, N u φ represents the stable bearing capacity of the pole, f represents the stability coefficient of the pole, and f represents the stable bearing capacity of the pole. c A represents the design value of the axial compressive strength of the concrete in the upright. s Let represent the cross-sectional area of ​​the upright, e0 represent the eccentricity of the axial force of the upright about the centroid of the cross-section, r represent the radius of gyration of the cross-section, and λ represent the slenderness ratio of the upright. Simultaneously, in conjunction with the bridge parameters in S1, this model also introduces the impact load influence coefficient k during beam cutting. i k i With bridge concrete design strength grade f cu，k and cutting speed v c The relationship is and k i Multiply by the calculated axial force of the pole to correct the stress state of the pole under impact load.

[0013] Furthermore, the structural health index evaluation model described in S4 includes a formula for calculating the structural health index HI, which is: Where α1, α2, and α3 represent the weighting coefficients for stress, deformation, and damage, respectively, and α1 + α2 + α3 = 1, σ max σ represents the maximum stress value at the interface between the support system and the beam. lim The value represents the ultimate stress of the interface material, Δl represents the cumulative deformation of the beam under supported conditions, l0 represents the original calculated length of the beam, and n d n represents the number of structural damage points detected. t This represents the total number of monitoring points; the model also correlates the bridge's service life t in S1 with the rate of change of HI as a function of t. It reflects the characteristics of the decline in the health status of the original bridge structure during the demolition process.

[0014] Furthermore, the adjustment process in S5 also includes a coupled analysis based on the upright bearing capacity calculation model and the structural health index evaluation model. When the structural health index HI is lower than a preset threshold, an upright support stiffness enhancement mechanism is triggered. This mechanism changes the elastic modulus E of the adjustable support at the top of the upright. a Achieve, E a The adjustment formula is E a =E a0 ·(1+β·(HI0―HI)), where E a0 Let represent the initial elastic modulus of the support, β represent the stiffness adjustment coefficient, and HI0 represent the preset health index threshold. Simultaneously, considering the bridge beam section height h and the column spacing s, the effective range for adjusting the support elastic modulus is determined as follows: Furthermore, the adjustment range is expanded when h / s > 1.2, and narrowed when h / s > 1.2.

[0015] Furthermore, the pole bearing capacity calculation model in S3 also includes a modified formula that considers uneven settlement of the pole foundation. This modified formula is: N′ u =N u (1―γ·Δs), where N′ u The value of γ represents the corrected stability bearing capacity of the upright, γ represents the settlement influence coefficient, and Δs represents the settlement difference of the upright foundation relative to adjacent uprights. The value of γ is related to the type of bridge foundation. When the bridge has a pile foundation, γ = 0.025; when the bridge has an enlarged foundation, γ = 0.04. Furthermore, the calculation of Δs needs to be combined with the bridge span length L in S1. Calculate, where θ represents the foundation tilt angle.

[0016] Furthermore, the structural health index evaluation model in S4 also includes a dynamic update mechanism. This mechanism uses the vibration frequency change Δf during bridge demolition to correct the health index in real time. The correction formula is as follows: Where HI′ represents the corrected health index, δ represents the frequency influence coefficient, and f0 represents the natural vibration frequency of the original bridge structure; the value of δ is related to the moment of inertia I of the bridge beam section, specifically as follows: Furthermore, Δf is obtained by a vibration sensor installed at the top of the pole, and the sampling frequency is consistent with the time step of the pole force calculation in S3.

[0017] Furthermore, S3 includes the following sub-steps:

[0018] S31. Extract the physical and mechanical parameters of the pole material from the parameter storage unit. These parameters include the yield strength, Poisson's ratio, cross-sectional area moment, and ultimate elongation of the steel used in the pole. At the same time, retrieve the pole spatial arrangement coordinate data determined in S2, convert the above parameters into a numerical format that the pole bearing capacity calculation model can recognize, and match them sequentially according to the pole numbering order.

[0019] S32. Set the load conditions, which include the uniformly distributed load generated by the self-weight of the bridge beam, the concentrated load generated by the cutting operation, the horizontal thrust caused by the wind load, and the temperature stress generated by the temperature change. According to the location of the different load types, decompose them into vertical and horizontal components acting on the top of the pole.

[0020] S33. Input the parameters transformed in S31 and the load data decomposed in S32 into the column bearing capacity calculation model, start the iterative calculation process of the model, and gradually update the stress state of the column at different heights during the calculation until the axial force, bending moment and shear force data output by the model converge within the preset error range.

[0021] S34. Expand the dimensions of the pole stress data output by the model, converting the one-dimensional force data into a three-dimensional stress cloud map. This cloud map can intuitively display the stress concentration area of ​​the pole in the length direction and mark the parts where the stress value exceeds the material design strength and their corresponding coordinate information.

[0022] Furthermore, S4 includes the following sub-steps:

[0023] S41. Activate the data source interface of the structural health index evaluation model. This interface establishes a two-way data transmission channel with the parameter storage unit in S1 and the calculation result output unit in S3. Through the interface protocol, the original structural parameters of the bridge and the force data of the poles are time-stamped to ensure that the data input to the model are consistent in the time dimension.

[0024] S42. The analysis module inside the model performs layered processing on the synchronized dataset. The first layer processes the relationship between the strength of bridge concrete and the degree of steel corrosion. The second layer processes the mapping relationship between the axial force of the pole and the deformation of the beam. The third layer processes the correspondence between the rate of load change and the degree of structural damage. Each layer generates an independent intermediate data matrix.

[0025] S43. Call the built-in weight allocation algorithm of the model and assign corresponding weight values ​​to the intermediate data matrices of each layer generated in S42 according to the different stages of bridge demolition. Specifically, increase the weight of the beam self-weight parameter in the initial stage of cutting, increase the weight of the pole stress data in the middle stage of cutting, and increase the weight of the deformation rate data in the later stage of cutting.

[0026] S44. Integrate the intermediate data after weighted processing at each layer, and generate the real-time value and change curve of the structural health index through the core of the model's calculation. The horizontal axis of the curve is the demolition operation time, the vertical axis is the health index value, and the feature points on the curve correspond to the calibration state of the interaction between the support system and the beam.

[0027] Furthermore, S5 includes the following sub-steps:

[0028] S51. Receive the dynamic monitoring data sequence output by S4, identify abnormal data points in the sequence, and identify them based on the deviation between the data point and its adjacent data points exceeding a set threshold range. For the identified abnormal data points, use linear interpolation to supplement them to ensure the continuity and integrity of the data sequence.

[0029] S52. Based on the complete data sequence, determine the adjustment priority of each adjustable component in the modular support system. The priority ranking criteria are: the adjustment of the displacement of the top of the pole takes priority over the adjustment of the preload of the transverse support, the adjustment of the hydraulic jack pressure takes priority over the adjustment of the stiffness matching coefficient, and the adjustment priority is dynamically updated as the position of the bridge beam cutting section changes.

[0030] S53. According to the priority determined in S52, send an adjustment instruction to the corresponding actuator. The instruction includes the specific adjustment value, adjustment direction and adjustment speed. The adjustment value is calculated based on the deviation between the pole force data and the health index. The adjustment direction is determined based on the trend of structural deformation. The adjustment speed is adapted to the rate of change of the data sequence.

[0031] S54. After the actuator completes the adjustment operation, the real-time status parameters of the support system are collected, the parameters are compared with the target parameters in the adjustment command, the percentage of deviation between the two is calculated, and the percentage of deviation is fed back to the parameter storage unit as a reference for the next adjustment.

[0032] A modular monitoring system for bridge demolition includes the following units:

[0033] The parameter acquisition and classification labeling unit is connected to the bridge structure testing equipment via a wired data transmission link and is used to receive and process various bridge parameters.

[0034] The pole spatial arrangement parameter generation unit has its input end connected to the output end of the parameter acquisition and classification labeling unit via a data bus, and its output end connected to the support system control unit.

[0035] The calculation unit for the pole bearing capacity calculation model interacts with the pole spatial arrangement parameter generation unit through a wireless communication module, and integrates a force analysis submodule.

[0036] The structural health index evaluation model calculation unit is connected to the parameter acquisition and classification labeling unit and the pole bearing capacity calculation model calculation unit via optical fiber transmission lines, and has the function of data synchronization processing.

[0037] The real-time parameter adjustment unit of the support system is connected to the signal output of the structural health index evaluation model calculation unit, and the execution component is connected to the mechanical structure of the modular support system.

[0038] The data storage and iterative optimization unit is connected to the pole bearing capacity calculation model calculation unit, the structural health index evaluation model calculation unit, and the support system real-time parameter adjustment unit through a bidirectional data interface. It is used to store historical data and provide iterative basis for each unit.

[0039] Beneficial Effects: This invention proposes a modular support system and monitoring system for bridge demolition. By comprehensively integrating specific parameters such as bridge span, beam cross-sectional dimensions, concrete strength, reinforcement configuration, and service life into the column bearing capacity calculation model, it overcomes the deviation problem caused by existing technologies that only use general mechanical models for column bearing capacity calculation without considering the bridge's own characteristics. This makes the axial force, bending moment, and other stress data of the column under vertical loads, horizontal loads, and combined loads more closely match the actual stress state of the bridge during the demolition stage, providing a precise basis for the design of the support system. Simultaneously, through the dynamic correlation between the structural health index evaluation model and the column stress data, the original bridge structural parameters, column stress data, and real-time monitoring data are processed hierarchically and weighted, achieving real-time linkage between the health index and support system adjustments. This overcomes the defect of existing technologies where health evaluation and support adjustment are disconnected, ensuring that adjustments to parameters such as column top displacement, lateral support preload, and hydraulic jack pressure in the support system can promptly adapt to changes in the structural characteristics of the bridge beam during the demolition process. In addition, the dynamic adjustment mechanism of the modular support system and the collaborative work of multiple units have enabled full-process adaptation from parameter acquisition, stress calculation, health assessment to support adjustment, which has improved the safety and accuracy of bridge demolition operations, effectively avoided the risk of structural collapse, and improved the efficiency of demolition operations. Attached Figure Description

[0040] Figure 1 This is a flowchart of the supporting system of the present invention;

[0041] Figure 2 This is a diagram showing the system unit composition of the present invention. Detailed Implementation

[0042] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0043] like Figure 1 As shown, a modular support system for bridge demolition includes the following steps:

[0044] S1. Collect the structural geometric parameters of the parts to be supported within the bridge demolition area. These parameters include the bridge span length, beam section height, web thickness, flange width, concrete design strength grade, steel reinforcement density, original structure service life, and cumulative number of traffic loads. Import these parameters into a preset parameter storage unit for classification and labeling.

[0045] Specifically, S1 is the foundational data acquisition stage for the entire modular support system and monitoring system. The bridge parameters acquired directly determine the accuracy of subsequent pole arrangement, load-bearing capacity calculations, and health assessments. The technical parameters involved cover three categories: structural geometry, material properties, and service status. Among the structural geometry parameters, the bridge span length determines the overall span adaptability of the support system; the beam section height, web thickness, and flange width affect the stress distribution at the top of the poles. Among the material property parameters, the concrete design strength grade and steel reinforcement density relate to the stress transfer characteristics at the pole-beam interface. Service life and the cumulative number of traffic loads reflect the aging degree and potential damage status of the bridge structure. Comprehensive acquisition of these parameters provides a data benchmark for subsequent steps and is a prerequisite for achieving dynamic matching of the support system with the structural characteristics during the bridge demolition phase.

[0046] During implementation, a professional testing team equipped with high-precision testing equipment must be organized to enter the bridge demolition area. For the bridge span length, a total station is used to conduct multi-point measurements and take the average value. Beam cross-section parameters are obtained by acquiring a three-dimensional model using laser scanning technology, extracting data such as web thickness and flange width. The concrete design strength grade is tested at different locations on the beam using a rebound hammer at least 30 times and recorded. Reinforcement density is measured every 50 centimeters along the longitudinal direction of the beam using a rebar detector. Service life is retrieved from the bridge construction archives, and the cumulative number of traffic loads is calculated from past traffic flow monitoring data. After data collection, all parameters are imported into the parameter storage unit according to the classification standard of "geometric parameters - material parameters - service parameters." Each parameter is marked with its corresponding acquisition location, time, and testing equipment number to ensure traceability of the data source for subsequent retrieval.

[0047] S2. Based on the parameters collected in S1, construct a spatial arrangement scheme for the uprights in the modular support system. This scheme needs to be combined with the sequence of beam segmentation during bridge demolition to determine the longitudinal spacing, transverse spacing, and coordinates of the contact point between the top of the upright and the bottom of the beam. At the same time, it is necessary to clarify the layout angle and node connection method of the transverse connecting members between adjacent uprights.

[0048] Specifically, S2 transforms the abstract parameters collected by S1 into a concrete spatial layout scheme for the support system, which is a crucial step connecting data acquisition and structural stress analysis. This step requires comprehensive consideration of the order in which the bridge beams are cut into segments during demolition, as different cutting sequences will lead to differences in the distribution of beam loads on the support system. The determination of the longitudinal spacing and transverse spacing of the uprights must match the self-weight distribution characteristics of the beams, and the coordinates of the contact points between the top of the uprights and the bottom surface of the beams must avoid weak points in the beams (such as areas with concentrated cracks). The arrangement angle and node connection method of the transverse connecting members between adjacent uprights directly affect the overall stability of the support system. The quality of implementation of this step determines whether the support system can bear the load evenly during the beam cutting process and avoid excessive local stress leading to structural instability.

[0049] During implementation, the bridge span length and beam section height in S1 are first used to preliminarily divide the beam into segments, determining the cutting sequence from the mid-span to both ends or from both ends to the mid-span. For each segment, the lateral spacing of the uprights is determined based on the width of the beam flange, ensuring that the top of the uprights covers the effective load-bearing area of ​​the flange. The longitudinal spacing of the uprights is calculated based on the beam's self-weight and concrete strength grade, typically reducing the spacing in areas with higher self-weight and increasing it in areas with lower self-weight. A three-dimensional model of the beam is constructed using BIM technology, marking the coordinates of the contact points between the top of the uprights and the bottom of the beam. These contact points must be located near the neutral axis of the beam section to reduce eccentric stress. Lateral connecting members are arranged at 45-degree or 60-degree angles. The connection method is selected based on the upright material: bolted or welded. Bolted connections are suitable for scenarios requiring frequent adjustments, while welding is suitable for areas with stable loads. All parameters are entered into the support system design module for digital archiving.

[0050] S3. Based on the pole layout parameters determined in S2, call the pole bearing capacity calculation model, input the elastic modulus, moment of inertia, design value of compressive strength, pole height, foundation bottom reaction coefficient, wind load direction and magnitude, and temperature change range of the pole material, and obtain the axial force, bending moment and shear force distribution data of the pole under vertical load, horizontal load and combined load through model calculation;

[0051] Specifically, S3 is the process of accurately assessing the mechanical properties of the uprights in the support system. It combines the physical parameters of the uprights with external load conditions through an upright bearing capacity calculation model, quantitatively analyzing the bearing capacity of the uprights under various stress states. The input elastic modulus and moment of inertia of the upright material determine the stiffness characteristics of the uprights; the design value of the compressive strength and the upright height are related to the uprights' resistance to failure; the foundation bottom reaction coefficient reflects the interaction between the uprights and the foundation; and wind load and temperature changes are environmental load factors that cannot be ignored. The axial force, bending moment, and shear force distribution data output in this step are the core basis for determining whether the uprights meet the safety support requirements, providing a mechanical analysis foundation for subsequent parameter adjustments of the support system.

[0052] During implementation, first retrieve the pole arrangement parameters determined by S2 from the parameter storage unit, including the number of poles, spacing, and height. Then, supplement the input with the specific parameters of the pole material: such as the elastic modulus being 2.1 × 10⁻⁶. 5 MPa, the section moment of inertia is calculated based on the pole diameter, and the design compressive strength is determined according to the pole concrete grade. The foundation bottom reaction coefficient is obtained from geological survey data, the wind load magnitude is referenced to the basic wind pressure value of the bridge location and converted in conjunction with the demolition operation height, and the temperature variation range is taken from the extreme temperature difference values ​​of the same period in the local area over the past 3 years. After inputting these parameters into the pole bearing capacity calculation model, the model first calculates the axial force of the pole under the vertical load (beam self-weight), then superimposes the bending moment generated by the horizontal load (wind load), and finally calculates the shear force distribution based on the pole height and section dimensions. During the calculation process, the model automatically identifies the critical section location of the pole (usually in the middle of the pole or at the connection with the transverse connecting members) and outputs the maximum axial force, bending moment, and shear force values ​​at that location. These data are transmitted to the structural health index evaluation model in real time.

[0053] S4. Simultaneously start the structural health index evaluation model, associate the original bridge structural parameters collected in S1 with the pole stress data calculated in S3, and generate a dynamic monitoring data sequence of stress transfer coefficient, structural deformation rate and damage evolution trend of the support system and beam contact interface during bridge demolition through the built-in analysis module of the model.

[0054] Specifically, S4 uses a structural health index evaluation model to dynamically monitor the overall structural condition of a bridge during demolition. Its core lies in establishing the correlation between the original structural parameters of the bridge and the stress data of the support system. The original structural parameters (such as concrete strength, steel reinforcement density, and service life) reflect the load-bearing potential and damage foundation of the beam itself, while the stress data of the supports (axial force, bending moment, and shear force) reflects the response state of the support system to loads. The combined analysis of these two parameters provides a more comprehensive assessment of the structure's safety status during the demolition phase. The generated stress transfer coefficient reflects the force transfer efficiency between the support system and the beam, the structural deformation rate indicates the trend of beam stability changes, and the damage evolution trend provides a basis for predicting potential risks. These three types of data together constitute the decision-making basis for adjusting the support system.

[0055] During implementation, the model first synchronously receives the original bridge structural parameters from S1 and the anchor stress data from S3 via a data interface, aligning the data in the time dimension to ensure that the beam state and support stress correspond at the same moment. For the calculation of the stress transfer coefficient, the model compares the design strength grade of the beam concrete with the contact stress at the top of the anchor, and corrects for the uniformity of stress transfer by incorporating the reinforcement density. The calculation of the structural deformation rate is correlated with the bridge's service life and the cumulative number of traffic loads; beams with longer service lives and more load cycles have a lower threshold for deformation rate. Damage evolution trend analysis continuously monitors the micro-strain changes at the contact points between the beam and the anchor, combining this with the beam cross-sectional height and web thickness to determine if there are signs of damage extending inwards. All analysis results are output in real-time as a dynamic data sequence, updated every 5 minutes to ensure timely capture of changes in the structural state.

[0056] S5. Based on the dynamic monitoring data sequence output by S4, adjust the real-time control parameters of the modular support system. This adjustment process involves the displacement of the fine-tuning device at the top of the pole, the preload of the lateral stabilizing support, the working pressure of the hydraulic jack, and the overall stiffness matching coefficient of the support system, so that the stress state of the support system is dynamically adapted to the structural characteristics of the bridge beam during the dismantling stage.

[0057] Specifically, S5 adjusts the support parameters to ensure the stress state of the support system matches the structural characteristics of the bridge beam during the demolition phase, a key control method to guarantee the safety of the demolition operation. The displacement adjustment of the fine-tuning device at the top of the support pole compensates for minor settlement during beam cutting; the preload adjustment of the lateral stabilizing support enhances the overall lateral resistance of the support system; the adjustment of the hydraulic jack's working pressure directly controls the support system's bearing capacity on the beam; and the adjustment of the stiffness matching coefficient ensures that the stiffness of the support system is coordinated with the stiffness of the beam, avoiding additional stress caused by stiffness mismatch. This step transforms the support system from a static design to a dynamic response system, effectively coping with various uncertain loads and structural changes during bridge demolition.

[0058] During implementation, the control system first analyzes the dynamic monitoring data sequence output by S4. When the stress transfer coefficient is lower than the set range, the fine-tuning device at the top of the upright is activated. The displacement is adjusted according to the beam cross-section height, typically 0.5 mm for every 10 cm of beam height. The adjustment is made vertically to ensure uniform stress distribution at the contact interface. When the structural deformation rate exceeds the warning value, the preload of the lateral stabilizing support is increased. The magnitude of the preload is determined based on the flange width, with an additional 5 kN of preload for every meter of flange width. The adjustment process is completed in three stages, with a 3-minute interval between each stage to avoid impact loads. The working pressure adjustment of the hydraulic jack is linked to the upright axial force data. For every 10% increase in axial force, the working pressure increases by 8%, maintaining pressure fluctuations within ±2%. The stiffness matching coefficient is adjusted according to the concrete design strength grade. The stiffness matching coefficient for C50 and above concrete is increased by 15%, while that for C30 and below it is decreased by 10%. All adjustment operations are executed by the automatic control system. After adjustment, continuous monitoring is performed for 30 minutes to confirm structural stability before proceeding to the next round of adjustments.

[0059] S6. Repeat steps S3 to S5 until the current segment of the beam is completely detached from the original structure and transferred to the designated area during the bridge demolition operation. Then reset the support system and monitoring parameters for the next segment of the beam.

[0060] Specifically, S6 continuously monitors and dynamically adjusts the entire bridge demolition process by repeating operations S3 to S5, ensuring that the demolition of each beam segment is carried out in a safe and controllable manner. Bridge demolition operations are phased, and the structural parameters, load conditions, and demolition environment of each beam segment may differ. Therefore, it is necessary to provide targeted support calculations, health assessments, and parameter adjustments for each beam segment through repeated cycles. This step enables the system to operate continuously, adapting to the demolition needs of different beam segments and ensuring the overall safety and efficiency of the bridge demolition project.

[0061] During implementation, the cyclic control system first sets the criteria for determining the completion of demolition of the current segment of the beam: the connection between the beam and the original structure must be completely cut and separated, and the center of gravity of the beam must have been completely transferred to the support system. Once the criteria are met, the control system signals to stop operations S3 to S5 for the current segment and initiates the beam transfer device to slowly move the segment to the designated area. During the transfer, the stress changes in the support system are continuously monitored to ensure that the support system does not experience excessive rebound after the load is removed. Subsequently, the system automatically calls up the parameters for the next segment of the beam, including the span length, beam cross-sectional dimensions, and concrete strength grade. Based on these new parameters, the parameter thresholds of the upright bearing capacity calculation model and the structural health index evaluation model are reinitialized, and the basic parameters of the upright spatial arrangement scheme, such as longitudinal spacing and transverse spacing, are adjusted. After completing the setting of the support system and monitoring parameters for the new segment, the cyclic operation of S3 to S5 is restarted until all segment beams are demolished. Throughout the entire cycle, the parameter adjustment records for each segment are automatically archived, providing data reference for subsequent projects.

[0062] Preferably, the pole bearing capacity calculation model in S3 includes a formula for calculating the stable bearing capacity of the pole under eccentric compression, which is: Where, N u φ represents the stable bearing capacity of the pole, f represents the stability coefficient of the pole, and f represents the stable bearing capacity of the pole. c A represents the design value of the axial compressive strength of the concrete in the upright. s Let represent the cross-sectional area of ​​the upright, e0 represent the eccentricity of the axial force of the upright about the centroid of the cross-section, r represent the radius of gyration of the cross-section, and λ represent the slenderness ratio of the upright. Simultaneously, in conjunction with the bridge parameters in S1, this model also introduces the impact load influence coefficient k during beam cutting. i k i With bridge concrete design strength grade f cu，k and cutting speed v c The relationship is and k i Multiply by the calculated axial force of the pole to correct the stress state of the pole under impact load.

[0063] Specifically, the load-bearing capacity of the upright under eccentric compression is accurately assessed through the calculation formula of the upright stability bearing capacity. The upright stability coefficient is directly related to the slenderness ratio of the upright, which is determined by the upright height and the radius of gyration of the cross section. The radius of gyration of the cross section is related to the cross-sectional area and cross-sectional shape of the upright. The design value of the axial compressive strength of the upright concrete needs to be determined in combination with the actual grade of the concrete used for the upright, while the eccentricity is calculated from the relative position of the point of application of the axial force of the upright and the centroid of the cross section. Meanwhile, the proposal introduces an impact load influence coefficient, which is closely related to the bridge concrete design strength grade and beam cutting speed. The concrete design strength grade needs to be determined based on the original bridge structure concrete parameters collected in S1, and the cutting speed is set according to the performance of the cutting equipment in the demolition operation plan. During implementation, the impact load influence coefficient is first calculated using the above parameters, and then multiplied by the calculated axial force of the pole. This corrects the influence of the impact load on the stress state of the pole during the cutting process, making the calculation of the pole bearing capacity more consistent with the actual working conditions during bridge demolition, and ensuring that the calculation results can accurately reflect the stable bearing capacity of the pole under the combined action of eccentric pressure and impact load.

[0064] Preferably, the structural health index evaluation model in S4 includes a formula for calculating the structural health index HI, which is: Where α1, α2, and α3 represent the weighting coefficients for stress, deformation, and damage, respectively, and α1 + α2 + α3 = 1, σ max σ represents the maximum stress value at the interface between the support system and the beam. lim The value represents the ultimate stress of the interface material, Δl represents the cumulative deformation of the beam under supported conditions, l0 represents the original calculated length of the beam, and n d n represents the number of structural damage points detected. t This represents the total number of monitoring points; the model also correlates the bridge's service life t in S1 with the rate of change of HI as a function of t. It reflects the characteristics of the decline in the health status of the original bridge structure during the demolition process.

[0065] Specifically, the constructed health index calculation formula integrates key parameters such as the maximum stress at the interface between the support system and the beam, the ultimate stress of the interface material, the cumulative deformation of the beam, the original calculated length of the beam, the number of structural damage points, and the total number of monitoring points. The maximum stress is collected in real time by stress sensors installed at the interface; the ultimate stress is determined based on the physical performance parameters of the interface material; the cumulative deformation is measured by displacement monitoring equipment placed at key locations on the beam; the original calculated length is determined based on the bridge span and beam segment dimensions collected in S1; and the number of damage points is identified through visual inspection equipment and stress mutation analysis. Simultaneously, the model incorporates the bridge's service life into the analysis, reflecting the health degradation characteristics of the original structure during demolition by calculating the rate of change of the health index with the service life. During implementation, the above parameters are collected synchronously and input into the model. An initial value of the health index is obtained through weight allocation, and then the rate of change is calculated in conjunction with the service life data. This dynamically assesses the collaborative working status of the original bridge structure and the support system, providing a quantitative basis for safety control during demolition operations.

[0066] Preferably, the adjustment process in S5 also includes a coupled analysis based on the upright bearing capacity calculation model and the structural health index evaluation model. When the structural health index HI is lower than a preset threshold, an upright support stiffness enhancement mechanism is triggered. This mechanism changes the elastic modulus E of the adjustable support at the top of the upright. a Achieve, E a The adjustment formula is E a =E a0 ·(1+β·(HI0―HI)), where E a0 Let E represent the initial elastic modulus of the support, β represent the stiffness adjustment coefficient, and HI0 represent the preset health index threshold. Simultaneously, considering the bridge beam section height h and the column spacing s, the effective range for adjusting the support elastic modulus is determined to be E. a ∈[0.8E a0 1.5E a0 Furthermore, the adjustment range is expanded when h / s > 1.2, and narrowed when h / s > 1.2.

[0067] Specifically, a mechanism for enhancing the stiffness of support poles based on a structural health index is proposed. The core of this mechanism is to adapt to changes in the health index by adjusting the elastic modulus of the adjustable bearing at the top of the pole. The initial elastic modulus of the bearing is determined by the mechanical properties of the material used in the bearing. The stiffness adjustment coefficient is set according to the structural type and adjustment range of the bearing. The preset health index threshold is determined based on the safety level of the bridge structure and the risk assessment results during the demolition phase. Simultaneously, this mechanism dynamically adjusts the effective range of the elastic modulus by combining the ratio of the bridge beam section height to the pole spacing. When the ratio is greater than 1.2, it indicates a concentrated load distribution on the beam, requiring an expansion of the elastic modulus adjustment range to enhance support adaptability; conversely, the range is narrowed. In implementation, the required elastic modulus adjustment is first calculated using the difference between the health index output by S4 and the preset threshold. Then, the adjustment boundary is determined based on the beam section height and pole spacing. Subsequently, a command is sent to the bearing adjustment mechanism to complete the elastic modulus adjustment, ensuring real-time matching between support stiffness and structural health status.

[0068] Preferably, the calculation model for the bearing capacity of the uprights in S3 also includes a correction formula that considers uneven settlement of the upright foundation. The correction formula is: N′ u =N u ·(1―γ·Δs), where, N′ u The value of γ represents the corrected stability bearing capacity of the upright, γ represents the settlement influence coefficient, and Δs represents the settlement difference of the upright foundation relative to adjacent uprights. The value of γ is related to the type of bridge foundation. When the bridge has a pile foundation, γ = 0.025; when the bridge has an enlarged foundation, γ = 0.04. Furthermore, the calculation of Δs needs to be combined with the bridge span length L in S1. Calculate, where θ represents the foundation tilt angle.

[0069] Specifically, a correction mechanism for uneven settlement of the pole foundation is added. The settlement influence coefficient in the correction formula is determined according to the bridge foundation type. When the bridge has a pile foundation, the coefficient is 0.025 because the piles have strong bearing capacity and relatively small settlement. When it is an enlarged foundation, the coefficient is 0.04 because the foundation has a large bearing area and high settlement sensitivity. The settlement difference is calculated by combining the bridge span length and foundation tilt angle collected in S1. The span length directly affects the overall deformation of the foundation, and the tilt angle is measured by an inclination sensor installed at the bottom of the foundation. In implementation, the bridge foundation type is first determined by geological survey data to select the corresponding settlement influence coefficient. Then, the foundation tilt angle is measured and the settlement difference is calculated in combination with the span length. Subsequently, the original pole stable bearing capacity is multiplied by (1 minus the product of the settlement influence coefficient and the settlement difference) to obtain the corrected bearing capacity value. This reflects the weakening effect of uneven foundation settlement on the pole bearing capacity, making the calculation results more consistent with the actual stress environment.

[0070] Preferably, the structural health index evaluation model in S4 also includes a dynamic update mechanism. This mechanism uses the vibration frequency change Δf during bridge demolition to correct the health index in real time. The correction formula is as follows: Where HI′ represents the corrected health index, δ represents the frequency influence coefficient, and f0 represents the natural vibration frequency of the original bridge structure; the value of δ is related to the moment of inertia I of the bridge beam section, specifically as follows: Furthermore, Δf is obtained by a vibration sensor installed at the top of the pole, and the sampling frequency is consistent with the time step of the pole force calculation in S3.

[0071] Specifically, the S4 structural health index evaluation model incorporates a dynamic update mechanism. This mechanism corrects the health index by incorporating the vibration frequency change during bridge demolition. The vibration frequency change is collected by vibration sensors installed at the top of the uprights, with the collection frequency consistent with the time step of the upright force calculation in S3, ensuring data synchronization over time. The frequency influence coefficient is related to the moment of inertia of the bridge beam section. The moment of inertia is calculated from parameters such as the beam section height, width, and web thickness collected in S1. A larger moment of inertia indicates higher beam stiffness, resulting in a correspondingly larger frequency influence coefficient, specifically determined by multiplying the square root of the moment of inertia by 0.015. In implementation, vibration frequency data during beam demolition is collected in real-time using vibration sensors, and the difference between this data and the original structure's inherent vibration frequency is calculated. The frequency influence coefficient is then calculated using the beam section moment of inertia. Subsequently, the product of this coefficient and the frequency change rate is incorporated into the health index correction calculation, resulting in a real-time updated health index. This allows the evaluation results to promptly reflect the impact of vibration loads on the structural health status, improving the model's adaptability to dynamic conditions.

[0072] Preferably, S3 includes the following sub-steps:

[0073] S31. Extract the physical and mechanical parameters of the pole material from the parameter storage unit. These parameters include the yield strength, Poisson's ratio, cross-sectional area moment, and ultimate elongation of the steel used in the pole. At the same time, retrieve the pole spatial arrangement coordinate data determined in S2, convert the above parameters into a numerical format that the pole bearing capacity calculation model can recognize, and match them sequentially according to the pole numbering order.

[0074] S32. Set the load conditions, which include the uniformly distributed load generated by the self-weight of the bridge beam, the concentrated load generated by the cutting operation, the horizontal thrust caused by the wind load, and the temperature stress generated by the temperature change. According to the location of the different load types, decompose them into vertical and horizontal components acting on the top of the pole.

[0075] S33. Input the parameters transformed in S31 and the load data decomposed in S32 into the column bearing capacity calculation model, start the iterative calculation process of the model, and gradually update the stress state of the column at different heights during the calculation until the axial force, bending moment and shear force data output by the model converge within the preset error range.

[0076] S34. Expand the dimensions of the pole stress data output by the model, converting the one-dimensional force data into a three-dimensional stress cloud map. This cloud map can intuitively display the stress concentration area of ​​the pole in the length direction and mark the parts where the stress value exceeds the material design strength and their corresponding coordinate information.

[0077] Preferably, S4 includes the following sub-steps:

[0078] S41. Activate the data source interface of the structural health index evaluation model. This interface establishes a two-way data transmission channel with the parameter storage unit in S1 and the calculation result output unit in S3. Through the interface protocol, the original structural parameters of the bridge and the force data of the poles are time-stamped to ensure that the data input to the model are consistent in the time dimension.

[0079] S42. The analysis module inside the model performs layered processing on the synchronized dataset. The first layer processes the relationship between the strength of bridge concrete and the degree of steel corrosion. The second layer processes the mapping relationship between the axial force of the pole and the deformation of the beam. The third layer processes the correspondence between the rate of load change and the degree of structural damage. Each layer generates an independent intermediate data matrix.

[0080] S43. Call the built-in weight allocation algorithm of the model and assign corresponding weight values ​​to the intermediate data matrices of each layer generated in S42 according to the different stages of bridge demolition. Specifically, increase the weight of the beam self-weight parameter in the initial stage of cutting, increase the weight of the pole stress data in the middle stage of cutting, and increase the weight of the deformation rate data in the later stage of cutting.

[0081] S44. Integrate the intermediate data after weighted processing at each layer, and generate the real-time value and change curve of the structural health index through the core of the model's calculation. The horizontal axis of the curve is the demolition operation time, the vertical axis is the health index value, and the feature points on the curve correspond to the calibration state of the interaction between the support system and the beam.

[0082] Preferably, S5 includes the following sub-steps:

[0083] S51. Receive the dynamic monitoring data sequence output by S4, identify abnormal data points in the sequence, and identify them based on the deviation between the data point and its adjacent data points exceeding a set threshold range. For the identified abnormal data points, use linear interpolation to supplement them to ensure the continuity and integrity of the data sequence.

[0084] S52. Based on the complete data sequence, determine the adjustment priority of each adjustable component in the modular support system. The priority ranking criteria are: the adjustment of the displacement of the top of the pole takes priority over the adjustment of the preload of the transverse support, the adjustment of the hydraulic jack pressure takes priority over the adjustment of the stiffness matching coefficient, and the adjustment priority is dynamically updated as the position of the bridge beam cutting section changes.

[0085] S53. According to the priority determined in S52, send an adjustment instruction to the corresponding actuator. The instruction includes the specific adjustment value, adjustment direction and adjustment speed. The adjustment value is calculated based on the deviation between the pole force data and the health index. The adjustment direction is determined based on the trend of structural deformation. The adjustment speed is adapted to the rate of change of the data sequence.

[0086] S54. After the actuator completes the adjustment operation, the real-time status parameters of the support system are collected, the parameters are compared with the target parameters in the adjustment command, the percentage of deviation between the two is calculated, and the percentage of deviation is fed back to the parameter storage unit as a reference for the next adjustment.

[0087] like Figure 2 As shown, a modular monitoring system for bridge demolition includes the following units:

[0088] The parameter acquisition and classification labeling unit is connected to the bridge structure testing equipment via a wired data transmission link and is used to receive and process various bridge parameters.

[0089] The pole spatial arrangement parameter generation unit has its input end connected to the output end of the parameter acquisition and classification labeling unit via a data bus, and its output end connected to the support system control unit.

[0090] The calculation unit for the pole bearing capacity calculation model interacts with the pole spatial arrangement parameter generation unit through a wireless communication module, and integrates a force analysis submodule.

[0091] The structural health index evaluation model calculation unit is connected to the parameter acquisition and classification labeling unit and the pole bearing capacity calculation model calculation unit via optical fiber transmission lines, and has the function of data synchronization processing.

[0092] The real-time parameter adjustment unit of the support system is connected to the signal output of the structural health index evaluation model calculation unit, and the execution component is connected to the mechanical structure of the modular support system.

[0093] The data storage and iterative optimization unit is connected to the pole bearing capacity calculation model calculation unit, the structural health index evaluation model calculation unit, and the support system real-time parameter adjustment unit through a bidirectional data interface. It is used to store historical data and provide iterative basis for each unit.

[0094] A modular support system and monitoring system for bridge demolition effectively overcomes the shortcomings of existing technologies where the calculation of the support pole's bearing capacity is divorced from the bridge's characteristics by deeply integrating the calculation model of the pole's bearing capacity with various specific parameters of the bridge. In the process of calculating the support pole's bearing capacity, it comprehensively incorporates parameters such as the bridge's span length, beam cross-sectional dimensions, concrete strength grade, and steel reinforcement density, enabling the calculation model to accurately reflect the stress characteristics of different bridge structures during the demolition stage. By dynamically calling the calculation logic that includes bridge parameters, it achieves accurate calculation of data such as axial force and bending moment of the support pole under vertical loads, horizontal loads, and combined loads, avoiding calculation deviations caused by general models, ensuring that the support pole design is neither redundant nor insufficient, and adapting to the complex stress requirements during bridge demolition.

[0095] This application addresses the disconnect between health assessment and support adjustment in existing technologies by constructing a dynamic linkage mechanism between a structural health index evaluation model and support system adjustments. The model correlates the original bridge structural parameters with the stress data of the supports in real time. The generated structural health index not only includes information such as stress transfer coefficient and deformation rate but also updates dynamically as the bridge demolition progresses. Based on changes in the health index, the system can automatically trigger adjustments to the support system parameters, including the displacement of the support tops and the preload of the lateral supports. This ensures that the stress state of the support system remains in real-time compatible with the structural characteristics during the beam demolition stage, guaranteeing that the health assessment results directly guide support adjustments and achieving close synergy between the two.

[0096] Furthermore, the modular design and multi-step collaborative mechanism of this application further enhance overall performance. Through iterative cycles from S3 to S5, combined with continuous optimization of pole bearing capacity calculation and health index evaluation, it can adapt to the dynamic changes of bridge segment dismantling. Each unit achieves efficient data flow through complex connections, ensuring seamless integration of parameter acquisition, model calculation, and adjustment execution. This design not only enhances the system's adaptability to different bridge structures but also improves the accuracy of support and monitoring through detailed step-by-step operation procedures (such as the step-by-step execution of S3 to S5), comprehensively ensuring the safety and stability of the bridge dismantling process.

[0097] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," "link," and "fix" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0098] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various equivalent changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A modular support system for bridge demolition, characterized in that, Includes the following steps: S1. Collect the structural geometric parameters of the parts to be supported within the bridge demolition area, and import the structural geometric parameters into the preset parameter storage unit for classification and labeling; S2. Based on the parameters collected in S1, construct a spatial arrangement scheme for the uprights in the modular support system. This scheme needs to be combined with the sequence of beam segmentation during bridge demolition to determine the longitudinal spacing, transverse spacing, and coordinates of the contact point between the top of the upright and the bottom of the beam. At the same time, it is necessary to clarify the layout angle and node connection method of the transverse connecting members between adjacent uprights. S3. Based on the pole layout parameters determined in S2, call the pole bearing capacity calculation model, input the elastic modulus, moment of inertia, design value of compressive strength, pole height, foundation bottom reaction coefficient, wind load direction and magnitude, and temperature change range of the pole material, and obtain the axial force, bending moment and shear force distribution data of the pole under vertical load, horizontal load and combined load through model calculation; S4. Simultaneously start the structural health index evaluation model, associate the original bridge structural parameters collected in S1 with the pole stress data calculated in S3, and generate a dynamic monitoring data sequence of stress transfer coefficient, structural deformation rate and damage evolution trend of the support system and beam contact interface during bridge demolition through the built-in analysis module of the model. S5. Based on the dynamic monitoring data sequence output by S4, adjust the real-time control parameters of the modular support system. This adjustment process involves the displacement of the fine-tuning device at the top of the pole, the preload of the lateral stabilizing support, the working pressure of the hydraulic jack, and the overall stiffness matching coefficient of the support system, so that the stress state of the support system is dynamically adapted to the structural characteristics of the bridge beam during the dismantling stage. S6. Repeat steps S3 to S5 until the current segment of the beam is completely detached from the original structure and transferred to the designated area during the bridge demolition operation. Then reset the support system and monitoring parameters for the next segment of the beam.

2. The modular support system for bridge demolition according to claim 1, characterized in that, The upright bearing capacity calculation model described in S3 includes a formula for calculating the stable bearing capacity of the upright under eccentric compression. This formula is: Where, N u φ represents the stable bearing capacity of the pole, f represents the stability coefficient of the pole, and f represents the stable bearing capacity of the pole. c A represents the design value of the axial compressive strength of the concrete in the upright. s Let represent the cross-sectional area of ​​the upright, e0 represent the eccentricity of the axial force of the upright about the centroid of the cross-section, r represent the radius of gyration of the cross-section, and λ represent the slenderness ratio of the upright. Simultaneously, in conjunction with the bridge parameters in S1, this model also introduces the impact load influence coefficient k during beam cutting. i k i With bridge concrete design strength grade f cu，k and cutting speed v c The relationship is and k i Multiply by the calculated axial force of the pole to correct the stress state of the pole under impact load.

3. The modular support system for bridge demolition according to claim 1, characterized in that, The structural health index evaluation model described in S4 includes a formula for calculating the structural health index HI, which is as follows: Where α1, α2, and α3 represent the weighting coefficients for stress, deformation, and damage, respectively, and α1 + α2 + α3 = 1, σ max σ represents the maximum stress value at the interface between the support system and the beam. lim The value represents the ultimate stress of the interface material, Δl represents the cumulative deformation of the beam under supported conditions, l0 represents the original calculated length of the beam, and n d n represents the number of structural damage points detected. t This represents the total number of monitoring points; the model also correlates the bridge's service life t in S1 with the rate of change of HI as a function of t. It reflects the characteristics of the decline in the health status of the original bridge structure during the demolition process.

4. The modular support system for bridge demolition according to claim 1, characterized in that, The adjustment process in S5 also includes a coupled analysis based on the upright bearing capacity calculation model and the structural health index evaluation model. When the structural health index HI is lower than a preset threshold, an upright support stiffness enhancement mechanism is triggered. This mechanism changes the elastic modulus E of the adjustable support at the top of the upright. a Achieve, E a The adjustment formula is E a =E a0 ·(1+β·(HI0―HI)), where E a0 Let E represent the initial elastic modulus of the support, β represent the stiffness adjustment coefficient, and HI0 represent the preset health index threshold. Simultaneously, considering the bridge beam section height h and the column spacing s, the effective range for adjusting the support elastic modulus is determined to be E. a ∈[0.8E a0 1.5E a0 Furthermore, the adjustment range is expanded when h / s > 1.2, and narrowed when h / s > 1.

2.

5. A modular support system for bridge demolition according to claim 1, characterized in that, The upright bearing capacity calculation model in S3 also includes a correction formula that considers uneven settlement of the upright foundation. This correction formula is: N′ u =N u ·(1―γ·ΔS), where, N′ u The value of γ represents the corrected stability bearing capacity of the upright, γ represents the settlement influence coefficient, and Δs represents the settlement difference of the upright foundation relative to adjacent uprights. The value of γ is related to the type of bridge foundation. When the bridge has a pile foundation, γ = 0.025; when the bridge has an enlarged foundation, γ = 0.

04. Furthermore, the calculation of Δs needs to be combined with the bridge span length L in S1. Calculate, where θ represents the foundation tilt angle.

6. A modular support system for bridge demolition according to claim 1, characterized in that, The structural health index evaluation model in S4 also includes a dynamic update mechanism. This mechanism uses the vibration frequency change Δf during bridge demolition to correct the health index in real time. The correction formula is as follows: Where HI′ represents the corrected health index, δ represents the frequency influence coefficient, and f0 represents the natural vibration frequency of the original bridge structure; the value of δ is related to the moment of inertia I of the bridge beam section, specifically as follows: and The data was collected by a vibration sensor installed at the top of the pole, and the sampling frequency was consistent with the time step of the pole force calculation in S3.

7. A modular support system for bridge demolition according to claim 1, characterized in that, S3 includes the following steps: S31. Extract the physical and mechanical parameters of the pole material from the parameter storage unit. These parameters include the yield strength, Poisson's ratio, cross-sectional area moment, and ultimate elongation of the steel used in the pole. At the same time, retrieve the pole spatial arrangement coordinate data determined in S2, convert the above parameters into a numerical format that the pole bearing capacity calculation model can recognize, and match them sequentially according to the pole numbering order. S32. Set the load conditions, which include the uniformly distributed load generated by the self-weight of the bridge beam, the concentrated load generated by the cutting operation, the horizontal thrust caused by the wind load, and the temperature stress generated by the temperature change. According to the location of the different load types, decompose them into vertical and horizontal components acting on the top of the pole. S33. Input the parameters transformed in S31 and the load data decomposed in S32 into the column bearing capacity calculation model, start the iterative calculation process of the model, and gradually update the stress state of the column at different heights during the calculation until the axial force, bending moment and shear force data output by the model converge within the preset error range. S34. Expand the dimensions of the pole stress data output by the model, converting the one-dimensional force data into a three-dimensional stress cloud map. This cloud map can intuitively display the stress concentration area of ​​the pole in the length direction and mark the parts where the stress value exceeds the material design strength and their corresponding coordinate information.

8. A modular support system for bridge demolition according to claim 1, characterized in that, S4 includes the following steps: S41. Activate the data source interface of the structural health index evaluation model. This interface establishes a two-way data transmission channel with the parameter storage unit in S1 and the calculation result output unit in S3. Through the interface protocol, the original structural parameters of the bridge and the force data of the poles are time-stamped to ensure that the data input to the model are consistent in the time dimension. S42. The analysis module inside the model performs layered processing on the synchronized dataset. The first layer processes the relationship between the strength of bridge concrete and the degree of steel corrosion. The second layer processes the mapping relationship between the axial force of the pole and the deformation of the beam. The third layer processes the correspondence between the rate of load change and the degree of structural damage. Each layer generates an independent intermediate data matrix. S43. Call the built-in weight allocation algorithm of the model and assign corresponding weight values ​​to the intermediate data matrices of each layer generated in S42 according to the different stages of bridge demolition. Specifically, increase the weight of the beam self-weight parameter in the initial stage of cutting, increase the weight of the pole stress data in the middle stage of cutting, and increase the weight of the deformation rate data in the later stage of cutting. S44. Integrate the intermediate data after weighted processing at each layer, and generate the real-time value and change curve of the structural health index through the core of the model's calculation. The horizontal axis of the curve is the demolition operation time, the vertical axis is the health index value, and the feature points on the curve correspond to the calibration state of the interaction between the support system and the beam.

9. A modular support system for bridge demolition according to claim 1, characterized in that, S5 includes the following steps: S51. Receive the dynamic monitoring data sequence output by S4, identify abnormal data points in the sequence, and identify them based on the deviation between the data point and its adjacent data points exceeding a set threshold range. For the identified abnormal data points, use linear interpolation to supplement them to ensure the continuity and integrity of the data sequence. S52. Based on the complete data sequence, determine the adjustment priority of each adjustable component in the modular support system. The priority ranking criteria are: the adjustment of the displacement of the top of the pole takes priority over the adjustment of the preload of the transverse support, the adjustment of the hydraulic jack pressure takes priority over the adjustment of the stiffness matching coefficient, and the adjustment priority is dynamically updated as the position of the bridge beam cutting section changes. S53. According to the priority determined in S52, send an adjustment instruction to the corresponding actuator. The instruction includes the specific adjustment value, adjustment direction and adjustment speed. The adjustment value is calculated based on the deviation between the pole force data and the health index. The adjustment direction is determined based on the trend of structural deformation. The adjustment speed is adapted to the rate of change of the data sequence. S54. After the actuator completes the adjustment operation, the real-time status parameters of the support system are collected, the parameters are compared with the target parameters in the adjustment command, the percentage of deviation between the two is calculated, and the percentage of deviation is fed back to the parameter storage unit as a reference for the next adjustment.

10. A modular support system for bridge demolition according to any one of claims 1-9, characterized in that, This system is implemented through a modular monitoring system for bridge demolition, comprising the following units: The parameter acquisition and classification labeling unit is connected to the bridge structure testing equipment via a wired data transmission link and is used to receive and process various bridge parameters. The pole spatial arrangement parameter generation unit has its input end connected to the output end of the parameter acquisition and classification labeling unit via a data bus, and its output end connected to the support system control unit. The calculation unit for the pole bearing capacity calculation model interacts with the pole spatial arrangement parameter generation unit through a wireless communication module, and integrates a force analysis submodule. The structural health index evaluation model calculation unit is connected to the parameter acquisition and classification labeling unit and the pole bearing capacity calculation model calculation unit via optical fiber transmission lines, and has the function of data synchronization processing. The real-time parameter adjustment unit of the support system is connected to the signal output of the structural health index evaluation model calculation unit, and the execution component is connected to the mechanical structure of the modular support system. The data storage and iterative optimization unit is connected to the pole bearing capacity calculation model calculation unit, the structural health index evaluation model calculation unit, and the support system real-time parameter adjustment unit through a bidirectional data interface. It is used to store historical data and provide iterative basis for each unit.

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