Anti-seismic toughness improving structure of in-service steel pier and construction method of anti-seismic toughness improving structure

Abstract

The invention relates to the field of civil engineering and structural seismic resistance, in particular to an in-service steel pier seismic toughness improving structure and a construction method thereof. The method comprises the following steps: obtaining structural health data of an in-service steel pier based on an intelligent sensor network, and carrying out pier aging and stress distribution analysis to obtain a degradation parameter sequence of an old structure; performing comparative analysis on the degradation parameter sequence and new material performance data, generating an optimized new material and old structure connection scheme, and obtaining a cooperative work model of new and old materials; inputting the model into an intelligent feedback adaptive system, and performing construction parameter adjustment based on real-time construction data to generate an optimal construction scheme; based on the connection scheme and the real-time monitoring data, long-term health monitoring is carried out, and a dynamic maintenance strategy sequence is generated. Dynamic adjustment of construction parameters is achieved through the intelligent feedback self-adaption system, seamless connection and cooperative work of new and old materials are ensured, the shock resistance toughness of the in-service steel pier is effectively improved, and the service life of the in-service steel pier is effectively prolonged.

Description

Technical Field

[0001] The present invention belongs to the fields of civil engineering and structural earthquake resistance, and particularly relates to a structure for enhancing the seismic resilience of in-service steel piers and a construction method thereof. Background Art

[0002] With the aging of urban infrastructure and the frequent occurrence of earthquake disasters, many in-service steel piers have significantly degraded in their structural performance and seismic resistance due to factors such as long-term loading, fatigue loads, and environmental corrosion. Therefore, effectively strengthening the seismic resistance and enhancing the resilience of in-service steel piers has become an urgent technical problem to be solved. However, traditional pier strengthening techniques mostly use simple reinforcement with a single material, ignoring the differences in mechanical properties, physical and chemical characteristics, and stress transfer modes between new and old materials, which easily lead to problems such as unstable connections and stress concentration between new and old materials, thus affecting the seismic resistance of the overall structure.

[0003] In response to the above problems, current technical research has gradually introduced high-performance materials (such as ultra-high-performance concrete, shape memory alloys, etc.) and advanced intelligent monitoring systems. By monitoring the stress, deformation, and crack propagation of piers, the construction plan is dynamically adjusted to improve the connection effect between new materials and old structures. However, due to the complex environmental conditions and varying degrees of material aging of in-service steel piers, the collaborative work between new and old materials still faces challenges during actual construction. Existing technologies lack a construction method that can comprehensively consider the health monitoring data of in-service piers, the performance differences between new and old materials, and intelligent feedback regulation, and a systematic solution to achieve seamless connection between new materials and old structures while enhancing the seismic resilience of the overall structure. Summary of the Invention

[0004] The present invention provides a structure for enhancing the seismic resilience of in-service steel piers and a construction method thereof, to solve the problem of how to dynamically adjust construction parameters through an intelligent feedback adaptive system based on the health monitoring data of in-service steel piers and the performance differences between new and old materials, achieve seamless connection and collaborative work between new materials and old structures, and enhance the seismic resilience of in-service steel piers.

[0005] To solve the above technical problems, the present invention provides a structure for enhancing the seismic resilience of in-service steel piers and a construction method thereof, including: Obtaining the structural health data of in-service steel piers based on an intelligent sensing network, and analyzing the pier aging and stress distribution to obtain a sequence of degradation parameters of the old structure; Comparatively analyzing the sequence of degradation parameters and the performance data of new materials to generate an optimized connection plan for new materials and the old structure, and obtaining a collaborative work model of new and old materials; Inputting the collaborative work model into an intelligent feedback adaptive system, adjusting construction parameters based on real-time construction data, and generating an optimal construction plan; Based on the new material connection solution and real-time monitoring data, long-term health monitoring is carried out after construction to generate a sequence of dynamic maintenance strategies.

[0006] Furthermore, the construction method further includes: Obtain the real-time health data of each part of the in-service steel bridge pier through the intelligent sensing network, and transmit data such as stress, deformation, and crack propagation to the cloud processing system; Process and analyze the obtained real-time health data, establish an aging analysis model of the bridge pier, and identify key degradation points and stress concentration areas; According to the analysis results, generate a sequence of degradation parameters of the existing structure, and the sequence of degradation parameters includes the stress values, deformation values, crack lengths, and aging damage degrees of each key part of the bridge pier.

[0007] Furthermore, the construction method further includes: Input the sequence of degradation parameters and the performance data of the new material into the analysis system, and calculate the stress distribution and deformation conditions of the new material under different mechanical conditions; Based on the analysis results, design the connection scheme of the new and old materials, and determine the interface treatment method and the selection of bonding materials; Based on the connection scheme, generate a collaborative working model of the new and old materials, and simulate the stress distribution and deformation conditions of the two under different loads.

[0008] Furthermore, the performance data of the new material includes the elastic modulus, Poisson's ratio, and density of the new material, and the sequence of degradation parameters includes the stress, deformation, crack length, and aging damage degree of the existing structure.

[0009] Furthermore, for the seismic toughness improvement structure of the in-service steel bridge pier and its construction method, the collaborative working model is calculated by the following formula: , Wherein, is the stress distribution at the interface between the new and old materials, is the stress value of the existing material, is the bonding strength, represents the ratio of the elastic moduli of the new and old materials, represents the ratio of the bonding coefficients of the new and old materials.

[0010] Furthermore, the construction method further includes: Import the collaborative working model into the intelligent feedback adaptive system, and calibrate the model according to the real-time construction environment parameters to obtain a calibrated stress distribution model; Through the intelligent feedback system, dynamically adjust the construction parameters according to real-time data, including the laying thickness of the new material, the interface treatment time, and the dosage of the binder. Generate an optimal construction plan based on the calibrated construction parameters.

[0011] Furthermore, the construction environment parameters include temperature, humidity, and material strain.

[0012] Furthermore, the construction method further includes: After the construction is completed, continue to use the intelligent sensing network to monitor the health status of the bridge pier, and collect stress and deformation data at the connection of the new and old materials; Input the monitoring data into the analysis system, evaluate the performance of the new material, and predict potential damage or aging risks according to the data change trend; Generate a dynamic maintenance strategy sequence regularly based on long-term monitoring data.

[0013] Furthermore, the dynamic maintenance strategy sequence includes maintenance time points, maintenance areas, and dynamic reinforcement plans.

[0014] Furthermore, the interface treatment method includes the application of surface modification technology or nano-enhanced materials to enhance the bonding strength of the interface between the new and old materials.

[0015] Furthermore, the intelligent sensing network includes stress sensors, deformation sensors, and crack propagation sensors, and the sensors are arranged at the bottom of the bridge pier, the middle of the column, and the top connection node.

[0016] Furthermore, the optimized connection plan between the new material and the old structure is generated in the following way: Perform finite element calculation and mechanical property comparative analysis on the degradation parameter sequence of the old structure and the new material performance data to obtain the mechanical property difference sequence between the new and old materials, and design the best connection method between the new and old materials based on this sequence.

[0017] Furthermore, the optimized connection plan includes the selection of interface bonding materials, the calculation of bonding strength, and the setting of the laying thickness of the new material.

[0018] Furthermore, the dynamic reinforcement plan includes maintenance strategies such as material reinforcement, re-coating of adhesives, and surface repair.

[0019] Furthermore, the long-term monitoring data includes the maximum stress value, the maximum deformation amount, and the crack propagation length at the joint of the new and old materials.

[0020] The key innovation points of the present invention include: (1) Multi-dimensional structural health monitoring based on an intelligent sensing network: Real-time collect data such as stress, deformation, and crack propagation through sensors arranged at key parts of the bridge pier, and dynamically generate a degradation parameter sequence in combination with cloud computing technology, which has higher real-time performance and accuracy compared with traditional static monitoring methods.

[0021] (2)Construction of the collaborative working model of new and old materials and intelligent regulation of construction parameters: Based on the degradation parameter sequence of the existing structure and the performance data of the new material, a collaborative working model of new and old materials is constructed, and during the construction process, the construction parameters are dynamically adjusted through an intelligent feedback adaptive system to ensure the stress transfer and deformation coordination between the new material and the existing structure.

[0022] (3)Generation of long-term health monitoring and dynamic maintenance strategies: After the construction is completed, the pier is monitored for long-term health using a sensing network, and dynamic maintenance strategies are generated based on the monitoring data to effectively predict potential damage or aging risks and extend the service life of the pier.

[0023] The following are its main beneficial effects: The present invention obtains the structural health data of the in-service steel pier through an intelligent sensing network. Based on a multi-parameter analysis model, it monitors the aging and stress distribution of the pier in real time and generates a degradation parameter sequence of the existing structure. Compared with traditional static health assessment methods, the present invention can dynamically obtain multi-dimensional data such as structural stress, deformation, and crack propagation, improving the accuracy and real-time performance of health monitoring. At the same time, combined with the performance data of the new material, a complex mechanical property comparison calculation model is used to generate a collaborative working model of new and old materials, and the construction parameters are dynamically adjusted through an intelligent feedback adaptive system to ensure the seamless connection between the new material and the existing structure and the coordination of stress transfer. Compared with the disadvantages of stress concentration and poor bonding between materials in traditional construction methods, the present invention can adaptively regulate the material consumption, interface treatment method, and bonding time during construction, effectively improving the construction quality and efficiency and enhancing the overall seismic toughness of the pier. In addition, after the construction is completed, through long-term health monitoring and the formulation of dynamic maintenance strategies, the present invention can timely detect and predict potential structural damage or performance degradation, effectively extend the service life of the pier, reduce maintenance costs, and ensure the safety of the bridge under extreme load conditions. Description of the Drawings

[0024] Figure 1 It is a schematic flow chart of a structure and its construction method for improving the seismic toughness of an in-service steel pier provided by an embodiment of the present application; Figure 2 It is a structural block diagram of a structure and its construction method for improving the seismic toughness of an in-service steel pier provided by an embodiment of the present application. Detailed Embodiments

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs; the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above drawings are intended to cover non-exclusive inclusion. The terms "first", "second", etc. in the specification and claims of this application or the above drawings are used to distinguish different objects and not to describe a specific order.

[0026] Reference herein to "embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of this application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments. Embodiment

[0027] Refer to Figure 1 which is a schematic flow chart of a structure and its construction method for enhancing the seismic resilience of an in-service steel pier provided by an embodiment of the present invention. This process can at least include steps S100 - S400: S100. Obtain the structural health data of the in-service steel pier based on the intelligent sensing network, conduct analysis on the pier aging and stress distribution, and obtain the degradation parameter sequence of the old structure.

[0028] S200. Conduct comparative analysis on the degradation parameter sequence and the new material performance data, generate an optimized connection scheme for the new material and the old structure, and obtain a collaborative working model of the new and old materials.

[0029] S300. Input the collaborative working model into the intelligent feedback adaptive system, adjust the construction parameters based on the real-time construction data, and generate an optimal construction plan.

[0030] S400. Based on the new material connection scheme and the real-time monitoring data, conduct long-term health monitoring after construction, and generate a dynamic maintenance strategy sequence.

[0031] Step S100 at least includes steps S110 - S130: S110. Obtain the real-time health data of each part of the in-service steel pier through the intelligent sensing network.

[0032] The sensors are arranged at the key parts of the structure, including the bottom of the pier, the middle part of the column, and the connection nodes at the top. The sensors are used to collect stress, deformation, crack propagation, and acceleration data of the pier, and transmit the data to the cloud processing system through wireless transmission. Specifically, the stress data collected by the sensors is represented by σ(t), the deformation data is represented by ϵ(t), the crack length data is represented by l(t), and the time t is the data collection time point.

[0033] Furthermore, the sensors , , …, continuously monitor, and the generated stress and deformation sequences are: σ( ), σ( ), …, σ( ) ϵ( ), ϵ( ), …, ϵ( ) The data at each time point includes the multi-dimensional data integration of different key parts of the pier. The data is the basis for subsequent analysis of the pier degradation situation.

[0034] S120. To analyze the real-time data obtained by the sensor network, it is first necessary to establish an aging analysis model of the pier in the cloud computing platform. The model conducts stress-strain curve analysis based on the relationship between pier stress and deformation, and combines the crack propagation data to further analyze the aging degree of the pier. The basic formula for setting the pier aging model is:

[0035] where D(t) represents the aging damage degree of the pier at time t, E represents the elastic modulus of the pier material, and C is the influence coefficient of crack propagation. The stress (t) and the crack length l(t) are collected in real time by the sensor. Through this formula, the aging damage degree of the pier in different time periods can be specifically analyzed.

[0036] Furthermore, conduct a spatial distribution analysis of the aging damage degree D(t) of each part of the pier to identify the key degradation points and stress concentration areas. The areas will be marked as the key parts for reinforcement and treatment. The identified areas should be represented by the position index i, and the stress concentration degree of each part can be expressed as:

[0037] where is the maximum stress value of the i-th part of the pier. The identified high-stress areas will be the key objects for analysis and construction treatment in the subsequent steps.

[0038] S130. Generate a sequence of degradation parameters for the bridge pier based on the analysis results of stress, deformation, crack propagation, and aging damage degree in S120. This sequence includes the stress values, deformation values, and crack propagation conditions of each key part of the bridge pier at each time point The specific form of the sequence of degradation parameters is as follows:

[0039] where P is the sequence of degradation parameters, i represents the index of the key position of the bridge pier, m is the total number of key positions, is the stress at the i-th position, is the deformation at this position, is the crack length, is the aging damage degree.

[0040] The sequence of degradation parameters will be used as input data in the subsequent S200 for comparative analysis with the performance data of new materials to generate a collaborative working model of new and old materials. At the same time, the degradation parameters in S130 will provide a reference basis for determining the construction parts and connection schemes in the subsequent steps.

[0041] Step S200 includes at least steps S210 - S230: S210. Input the sequence of degradation parameters of the existing structure generated in S130 above and the performance data of new materials into the analysis system.

[0042] where, is the elastic modulus of the new material, is the Poisson's ratio, is the density of the new material, and j represents the type of new material.

[0043] Specifically, based on the stress and deformation of the existing structure and the crack length , calculate the stress distribution and deformation of the new material under different mechanical conditions by the finite element method (FEM). The calculation formula is as follows:

[0044] This formula is used to calculate the deformation behavior of the new material under the same stress condition, where and represent the elastic moduli of the new material and the old material respectively, is the stress distribution of the new material at time t.

[0045] Furthermore, compare the mechanical property differences between the new and old materials to generate a sequence of mechanical property comparisons where:

[0046]

[0047]

[0048] The amount of difference will be used for the next step of analysis in order to design the best connection method between the new and old materials.

[0049] S220. Based on the mechanical property comparison sequence C calculated in S210, combined with the physical and chemical characteristics of the new material and the old structure, design the best connection plan. Specifically, the connection plan includes the interface treatment method and the selection of the bonding material. To ensure stress transfer and deformation coordination at the interface between the new and old materials, it is necessary to calculate the best parameters of the interface bonding material. Let the bonding strength be τ, and its calculation formula is:

[0050] Where, is the thickness of the new material, L is the interface length, is the elastic modulus of the new material. Calculate the bonding strength through this formula, and combined with the actual construction conditions, select the optimal bonding agent formula.

[0051] Furthermore, according to the stress distribution and deformation characteristics of the new and old materials, determine the interface treatment method. Understandably, the interface treatment of the new and old materials needs to consider the chemical compatibility between the materials. For example, through surface modification technology or nano-reinforced materials, enhance the bonding strength of the interface to ensure smooth stress transfer at the interface under different load conditions.

[0052] S230. Based on the connection plan designed in S220, further generate a cooperative working model of the new and old materials. Specifically, the cooperative working model simulates the stress distribution and deformation of the new and old materials under different load conditions through finite element analysis. The formula of the cooperative working model is:

[0053] Where, represents the stress distribution at the interface between the new and old materials, and are the bonding coefficients of the new and old materials.

[0054] This model simulates the stress and deformation distributions of the new and old materials under different loads (such as seismic loads, wind loads, etc.), and obtains the cooperative working behavior of the new material and the old structure, providing a reference basis for parameter setting and construction strategies in subsequent construction.

[0055] Furthermore, after the collaborative working model simulation is completed, the analyzed data will be used as the input for the construction stage, especially for setting construction parameters such as the thickness of new materials and the usage amount of adhesives.

[0056] Step S300 includes at least steps S310 - S330: S310. First, the collaborative working model of new and old materials generated in S230 is imported into the intelligent feedback adaptive system. This model describes the collaborative action of new materials and old structures under different stresses and bonding strengths .

[0057] The real - time construction data includes environmental parameters (such as temperature T(t), humidity H(t)) and material strain (t), and this data is collected by on - site sensors and input into the feedback system. Based on this data, the intelligent feedback system will dynamically adjust the parameters of the collaborative working model to calibrate the stress distribution and strain response of new and old materials in the actual construction environment. At this time, the calibrated model becomes:

[0058] where the function f represents the adjustment operation of the system to the construction environment data. This process ensures through iterative optimization that the model can reflect the behavior of new and old materials under real construction conditions, and this model is used to guide the specific parameter adjustment during the construction process.

[0059] S320. According to the model calibrated in S310 , the intelligent feedback system starts to dynamically adjust the construction parameters. Specifically, the system adjusts the following construction parameters according to the difference between the real - time strain data and the calibrated model : 1. The laying thickness of new materials : The system adjusts the laying thickness of new materials according to the real - time strain data to ensure smooth stress transfer between new materials and the old structure. The adjustment formula at this time is:

[0060] where is the initial design thickness, is the adjustment coefficient, is the calibrated strain.

[0061] 2. Interface treatment time : The system adjusts the curing time of the interface bonding material according to the temperature T(t) and humidity H(t) to ensure that the adhesive exerts the maximum bonding strength τ under the best conditions. The adjustment formula is:

[0062] Among them, is the initial interface processing time, is the adjustment coefficient, is the optimal curing temperature of the binder.

[0063] 3. Dosage of the binder : The system adjusts the usage amount of the binder through real-time stress data , ensuring that the interface remains stable under different stress states. The adjustment formula is:

[0064] Among them, is the initial designed dosage, is the adjustment coefficient.

[0065] S330. On the basis of dynamically adjusting construction parameters, the intelligent feedback system generates an optimal construction plan according to real-time feedback data. Through real-time monitoring data (such as , , etc.), the intelligent feedback system evaluates the connection effect of new and old materials, ensuring that the stress transfer and deformation coordination during construction meet the design standards.

[0066] Specifically, the system generates a construction step adjustment plan according to the stress concentration at key nodes, and sets the adjustment of key nodes as:

[0067] When the stress at the key node is close to the design critical stress , the system will automatically adjust the construction steps at this node, increasing or decreasing the material usage amount, adjusting the laying thickness or extending the curing time, ensuring that the seismic toughness of the overall structure reaches the design standard.

[0068] After this series of real-time feedback adjustments, the system finally generates an optimal construction plan, covering specific construction steps such as material usage amount, laying sequence, and key node treatment, ensuring that the connection effect of new and old materials and the seismic capacity of the overall structure meet the design expectations.

[0069] Step S400 includes at least steps S410 - S430: S410. After construction is completed, continue to use the intelligent sensing network deployed in S110 to measure the stress (t) and deformation (t) The data is monitored in real time. The sensing network covers the key parts at the connection between the new material and the old structure, and continuously collects the data at the joint of the new and old materials through the stress, deformation and crack sensors installed at these parts. Specifically, the data collected by the sensors includes:

[0070]

[0071] Among them, and respectively represent the stress and deformation at the i-th monitoring point at the joint, and n represents the number of monitoring points. By continuously collecting the above data, the bonding stability of the new and old materials is monitored to ensure that the connection performance remains stable under different external conditions.

[0072] S420. Input the real-time monitoring data collected in S410 and into the analysis system to further evaluate the performance of the new material. Based on the collaborative working model generated in the S210 and S220 stages, analyze the performance of the new material during actual use, compare it with the theoretical model, and find out the deviation part.

[0073] Set the comparison formula between the monitoring data and the theoretical model as follows:

[0074]

[0075] Among them, and respectively represent the stress and strain models adjusted in S310. By analyzing the difference between the monitoring data and the model data and , the mechanical properties of the new material during long-term use can be evaluated, and its potential damage or aging risk can be further predicted.

[0076] Based on the data change trend, the system analyzes the performance degradation of the material and evaluates the possible structural damage in the future. Using the above trend data, it can be deduced when the material may have a performance drop point \(t_{\text{risk}}\), and this time point is estimated by the following formula:

[0077] Among them, is the start time of monitoring, is the maximum stress difference, is the material degradation rate estimation coefficient. This data is used to further formulate a dynamic maintenance strategy.

[0078] S430. Generate a sequence of dynamic maintenance strategies regularly based on the long-term monitoring data and material performance evaluation results in S420. . The maintenance strategy dynamically adjusts the maintenance and reinforcement plans of the bridge pier according to the degradation rate of the material and the distribution of stress concentration points. The maintenance strategy includes: 1. Maintenance time point : The system calculates the time point of the next maintenance based on the monitoring data. , and this time point is calculated by the aforementioned formula to ensure that maintenance is carried out before the material undergoes severe degradation.

[0079] 2. Selection of maintenance area: By analyzing the stress concentration points , the system preferentially processes high-stress areas to ensure the structural safety of the bridge pier. At this time, the maintenance strategy will include a detailed list of reinforcement areas { , , …, }, where represents the k-th high-stress area.

[0080] 3. Dynamic reinforcement plan: Generate a sequence of reinforcement plans according to the monitoring data , including operations such as material reinforcement, re-coating of adhesives, and surface repair, to ensure the long-term seismic toughness of the bridge pier.

[0081] Thus, the system will regularly evaluate the health status of the bridge pier, continuously optimize the maintenance strategy based on the latest monitoring data, and ensure that the bridge pier remains within the designed seismic toughness standard during long-term use.

[0082] The key innovation points of the present invention include: (1) Multi-dimensional structural health monitoring based on an intelligent sensing network: Real-time data such as stress, deformation, and crack propagation are collected through sensors arranged at key parts of the bridge pier, and a sequence of degradation parameters is dynamically generated in combination with cloud computing technology, which has higher real-time performance and accuracy compared to traditional static monitoring methods.

[0083] (2) Construction of a collaborative working model for new and old materials and intelligent regulation of construction parameters: Based on the sequence of degradation parameters of the existing structure and the performance data of new materials, a collaborative working model for new and old materials is constructed, and the construction parameters are dynamically adjusted through an intelligent feedback adaptive system during the construction process to ensure the stress transfer and deformation coordination between the new materials and the existing structure.

[0084] (3) Generation of long-term health monitoring and dynamic maintenance strategies: After construction, the bridge pier is subjected to long-term health monitoring using the sensing network, and dynamic maintenance strategies are generated based on the monitoring data to effectively predict potential damage or aging risks and extend the service life of the bridge pier.

[0085] The following are its main beneficial effects: The present invention obtains the structural health data of in-service steel bridge piers through an intelligent sensing network. Based on a multi-parameter analysis model, it monitors the aging and stress distribution of the bridge piers in real time and generates a degradation parameter sequence of the existing structure. Compared with traditional static health assessment methods, the present invention can dynamically obtain multi-dimensional data such as structural stress, deformation, and crack propagation, improving the accuracy and real-time performance of health monitoring. At the same time, combining the performance data of new materials, using a complex mechanical property comparison calculation model, it generates a collaborative working model of the new and old materials, and dynamically adjusts the construction parameters through an intelligent feedback adaptive system to ensure seamless connection between the new material and the existing structure and the coordination of stress transfer. Compared with the disadvantages of stress concentration and poor bonding between materials in traditional construction methods, the present invention can adaptively control the material dosage, interface treatment method, and bonding time during construction, effectively improving the construction quality and efficiency and enhancing the overall seismic toughness of the bridge pier. In addition, after the construction is completed, through long-term health monitoring and the formulation of dynamic maintenance strategies, the present invention can timely detect and predict potential structural damage or performance degradation, effectively extend the service life of the bridge pier, reduce maintenance costs, and ensure the safety of the bridge under extreme load conditions.

[0086] Embodiment 2: Figure 2 Shows a structural block diagram of a structure for enhancing the seismic toughness of an in-service steel bridge pier and its construction method according to an embodiment of the present invention. As Figure 2 shown, it may include: Data acquisition and health monitoring module 10 This module is mainly used to collect and monitor real-time data on the health status of in-service steel bridge piers at different stages before, during, and after construction. Module 10 can obtain the health data of the steel bridge pier in real time through sensors for stress, deformation, crack propagation, etc. arranged at key parts of the bridge pier, including material stress σ(t), deformation ϵ(t), and crack length l(t), etc.

[0087] Data acquisition sub-module 101: Used to collect the health data of key parts of the bridge pier, including stress, deformation, crack length, and displacement data at the bottom of the bridge pier, the middle of the column, and the top connection node, and send the data to the cloud processing system through wireless transmission.

[0088] Health monitoring sub-module 102: Preliminarily processes and monitors the collected data, establishes an aging model of the bridge pier, identifies key degradation points and stress concentration areas, and models and evaluates the aging degree of the bridge pier.

[0089] The structural analysis and connection scheme generation module 20, based on the degradation parameter sequence P of the in-service steel bridge pier obtained by module 10 and the performance data M of the new material, conducts a comparative analysis of the mechanical properties of the new and old materials and generates an optimized connection scheme. This module further combines the physical and chemical characteristics of the new material and the old structure to determine the best connection method and interface treatment strategy between the new material and the old structure, ensuring the collaborative work of the new and old materials.

[0090] Structural analysis sub-module 201: Input the degradation parameter sequence of the old structure and the performance data of the new material into the analysis system, and calculate the stress distribution and deformation of the new material under different mechanical conditions.

[0091] Connection scheme generation sub-module 202: Based on the structural analysis results, determine the connection interface treatment method between the new and old materials and the selection of the bonding material, generate a specific connection scheme and output the collaborative work model of the new and old materials.

[0092] The intelligent feedback adaptive system module 30 imports the collaborative work model output by the structural analysis and connection scheme generation module 202 into the intelligent feedback adaptive system, and dynamically adjusts the construction parameters in combination with the real-time data collected during construction. This module can automatically adjust the construction parameters based on real-time construction data, such as temperature, humidity, material strain, etc., and generate an optimal construction scheme.

[0093] Model calibration sub-module 301: Import the collaborative work model into the intelligent feedback adaptive system, calibrate the model according to the real-time construction data, and generate a calibrated model .

[0094] Construction parameter adjustment sub-module 302: Based on the calibrated model , dynamically adjust the construction parameters, including the laying thickness of the new material , the interface treatment time and the dosage of the binder , to ensure the stress transfer and deformation coordination at each node during the construction process.

[0095] The dynamic maintenance and long-term monitoring module 40 is used for long-term health monitoring and maintenance strategy generation after construction. Based on the real-time monitoring data, regularly evaluate the health status of the bridge pier and generate a dynamic maintenance strategy sequence.

[0096] Long-term health monitoring sub-module 401: Continue to use the sensor network in module 10 to collect the stress and deformation data at the connection of the new and old materials, and input the data into the analysis system.

[0097] Maintenance strategy generation sub-module 402: Based on long-term monitoring data, analyze the performance and its changing trends of new and old materials, predict potential damage risks, regularly generate dynamic maintenance strategies, and output maintenance time points, maintenance areas, and specific dynamic reinforcement plans.

[0098] Beneficial effects of the embodiment Through the division of labor and cooperation of the above system structure modules, the present invention can realize data collection, analysis, feedback, and maintenance strategy formulation in each stage before, during, and after the pier reconstruction, effectively improving the seismic resilience of in-service steel piers. The system has the following beneficial effects: 1. Improve construction accuracy and efficiency: The intelligent feedback adaptive system dynamically adjusts construction parameters based on real-time data, generates the optimal construction plan, and ensures the connection effect of new and old materials and the high efficiency of the construction process.

[0099] 2. Ensure long-term use safety: Through long-term health monitoring and the generation of dynamic maintenance strategies, it can effectively predict potential structural damage and material degradation risks and extend the service life of the pier.

[0100] 3. Achieve the collaborative work of new and old materials: Based on the application of mechanical property comparison and interface treatment technology, it can effectively solve the compatibility problem of new and old materials under different stress and deformation conditions, ensure the stable connection performance of new materials and old structures, and improve the seismic capacity of the overall structure.

[0101] Obviously, the above-described embodiments are only a part of the embodiments of the present application, rather than all embodiments. The accompanying drawings show the preferred embodiments of the present application, but do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing the described embodiments is to make the understanding of the disclosure content of the present application more thorough and comprehensive. Although the present application has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions recorded in the foregoing specific embodiments, or perform equivalent replacements for some of the technical features. Any equivalent structures directly or indirectly using the content of the specification and drawings of the present application in other related technical fields are equally within the scope of the patent protection of the present application.

Claims

1. A structure for improving the seismic toughness of an in-service steel bridge pier and a construction method thereof, characterized in that: The following steps are involved: S100, based on the intelligent sensor network, obtain the structural health data of the in-service steel bridge piers, and perform pier aging and stress distribution analysis to obtain the degradation parameter sequence of the old structure; S200, comparing and analyzing the degradation parameter sequence and the new material performance data, generating an optimized connection scheme between the new material and the old structure, and obtaining a collaborative working model of the new and old materials; S300, inputting the collaborative work model into an intelligent feedback adaptive system, adjusting construction parameters based on real-time construction data, and generating an optimal construction plan; S400: Based on the new material connection scheme and real-time monitoring data, long-term health monitoring is performed after construction to generate a dynamic maintenance strategy sequence.

2. The structure for improving the seismic toughness of in-service steel bridge piers and the construction method thereof according to claim 1 is characterized in that: Step S100 includes: S110, obtain real-time health data of various parts of in-service steel bridge piers through intelligent sensor networks, and transmit data such as stress, deformation, crack propagation, etc. to the cloud processing system; S120, process and analyze the acquired real-time health data, establish an aging analysis model for the bridge pier, and identify key degradation points and stress concentration areas; S130. Generate a degradation parameter sequence of the old structure according to the analysis result, wherein the degradation parameter sequence includes stress values, deformation values, crack lengths and aging damage degrees of key parts of the pier.

3. The structure for improving the seismic toughness of in-service steel bridge piers and the construction method thereof according to claim 1 is characterized in that: Step S200 includes: S210, inputting the degradation parameter sequence and the performance data of the new material into an analysis system to calculate the stress distribution and deformation of the new material under different mechanical conditions; S220, based on the analysis results, design a connection scheme for new and old materials, and determine an interface treatment method and bonding material selection; S230. Based on the connection scheme, a collaborative working model of the new and old materials is generated to simulate the stress distribution and deformation of the two under different loads.

4. The structure for improving the seismic toughness of in-service steel bridge piers and the construction method thereof according to claim 3 is characterized in that: The new material performance data includes the elastic modulus, Poisson's ratio and density of the new material, and the degradation parameter sequence includes the stress, deformation, crack length and aging damage degree of the old structure.

5. The structure for improving the seismic toughness of in-service steel bridge piers and the construction method thereof according to claim 3 is characterized in that: The collaborative working model is calculated by the following formula: ， in, is the stress distribution at the interface between the new and old materials, is the stress value of the old material, is the bonding strength, Indicates the ratio of the elastic modulus of the new and old materials, Indicates the bonding coefficient ratio of new and old materials.

6. The structure for improving the seismic toughness of in-service steel bridge piers and the construction method thereof according to claim 1 is characterized in that: Step S300 includes: S310, importing the collaborative work model into an intelligent feedback adaptive system, and calibrating the model according to real-time construction environment parameters to obtain a calibrated stress distribution model; S320, dynamically adjusting construction parameters including the laying thickness of the new material, the interface treatment time and the amount of adhesive according to the real-time data through the intelligent feedback system; S330: Generate an optimal construction plan according to the calibrated construction parameters.

7. The structure for improving the seismic toughness of in-service steel bridge piers and the construction method thereof according to claim 6 is characterized in that: The construction environment parameters include temperature, humidity and material strain.

8. The structure for improving the seismic toughness of in-service steel bridge piers and the construction method thereof according to claim 1 is characterized in that: Step S400 includes: S410. After the construction is completed, the intelligent sensor network will continue to monitor the health of the bridge piers and collect stress and deformation data at the joints between new and old materials; S420, inputting the monitoring data into an analysis system to evaluate the performance of the new material, and predicting potential damage or aging risks based on the data change trend; S430. Regularly generate a dynamic maintenance strategy sequence based on long-term monitoring data.

9. The structure for improving the seismic toughness of in-service steel bridge piers and the construction method thereof according to claim 8, characterized in that: The dynamic maintenance strategy sequence includes maintenance time points, maintenance areas and dynamic reinforcement plans.

10. The structure for improving the seismic toughness of in-service steel bridge piers and the construction method thereof according to claim 3, characterized in that: The interface treatment method includes surface modification technology or application of nano-enhanced materials, which is used to enhance the bonding strength of the interface between new and old materials.

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