Concrete electric pole bearing capacity analysis detection system and method based on multi-dimensional parameters

Abstract

This invention relates to pole bearing capacity testing, specifically to a system and method for analyzing and testing the bearing capacity of concrete poles based on multi-dimensional parameters. The system includes: a benchmark twin model construction module, a multi-dimensional parameter acquisition module, a multi-parameter mapping and model dynamic update module, a multi-condition bearing capacity simulation analysis module, and a result output and scheme verification module. By constructing a three-dimensional finite element benchmark twin model of the pole and combining it with multi-dimensional non-destructive testing data, the system achieves dynamic mapping and updating of the model. Testing data such as concrete strength, steel corrosion degree, crack spatial distribution, and pole deformation angle are used to correct the material properties, damaged structures, and boundary constraints of the benchmark twin model according to their spatial locations. This achieves real-time synchronization between the digital twin model and the actual structural state of the pole. Based on the dynamically updated digital twin model, bearing capacity simulation calculations are performed under normal service conditions and extreme conditions such as typhoons and icing, enabling accurate assessment of the pole's bearing capacity and verification of the safety margin of bearing capacity under extreme conditions.

Description

Technical Field

[0001] This invention relates to pole bearing capacity testing, specifically to a system and method for analyzing and testing the bearing capacity of concrete poles based on multi-dimensional parameters. Background Technology

[0002] Concrete poles are core infrastructure in overhead power transmission and distribution networks, responsible for supporting conductors and transferring loads. They are widely used in the construction of urban and rural power distribution networks, rural power grids, and communication lines. The stability of their structural performance directly affects the operational safety of overhead lines and the continuity of power supply services. They are the most numerous and widely distributed structural support components in the power infrastructure system, and play an irreplaceable fundamental role in ensuring the stable operation of the power system.

[0003] Pole load-bearing capacity analysis and testing is a core technical means for conducting structural condition investigation and mechanical performance evaluation of in-service concrete poles. By testing the material properties, damage state, and service environment parameters of the pole, and combining mechanical calculations, the ultimate load-bearing capacity of the pole can be obtained. This can identify the structural deterioration risk of the pole in a timely manner, providing a quantitative basis for operation and maintenance, defect reinforcement, and equipment replacement. It has important engineering application value for preventing pole collapse and line breakage accidents and reducing potential safety hazards in power grid operation.

[0004] The invention patent application with publication number CN111612885A discloses a digital tower management method and system in a smart power transmission IoT environment. This solution collects tower operation status data through IoT sensing terminals and combines it with a digital tower model to realize online monitoring of tower status and operation and maintenance process control, thus building a basic framework for digital tower operation and maintenance, and enabling centralized and visualized management of tower basic information and operation status.

[0005] However, existing technologies and the aforementioned solutions still have significant limitations. Most solutions utilize digital models statically constructed based on factory design parameters, failing to dynamically update them to reflect structural damage occurring during long-term service, such as concrete strength degradation, steel corrosion, and crack propagation. This makes it difficult to accurately reflect the actual structural condition of the pole. Furthermore, the coupling between load-bearing capacity assessment and the digital twin model is insufficient, preventing the use of dynamically updated digital twin models for load-bearing capacity simulation analysis under extreme conditions. This not only leads to insufficient accuracy in pole load-bearing capacity analysis results but also hinders the provision of reliable digital simulation support for pole disaster risk assessment and reinforcement scheme verification. Therefore, developing a multi-dimensional parameter-based concrete pole load-bearing capacity analysis and testing system and method is of great significance. Summary of the Invention

[0006] (a) Technical problems to be solved To address the aforementioned shortcomings of existing technologies, this invention provides a multi-dimensional parameter-based concrete pole bearing capacity analysis and testing system and method, which can effectively overcome the deficiencies of existing technologies, such as the inability of static models to match the dynamic deterioration state of poles, low coupling between bearing capacity assessment and digital twin models, and lack of digital simulation support for bearing capacity analysis under extreme working conditions.

[0007] (II) Technical Solution To achieve the above objectives, the present invention provides the following technical solution: The concrete pole bearing capacity analysis and testing system based on multi-dimensional parameters includes the following functional modules: The reference twin model construction module retrieves the design parameters, manufacturing process parameters, and basic constraint parameters of the pole to construct a three-dimensional finite element reference twin model of the pole, and sets the initial material properties and boundary constraint conditions. The multi-dimensional parameter acquisition module collects structural damage parameters and service environment parameters of the pole, forming a multi-dimensional detection dataset carrying spatial coordinates. The multi-parameter mapping and dynamic model update module maps the multi-dimensional detection dataset to the corresponding mesh element of the benchmark twin model, corrects the material properties, damage structure and boundary constraints of the benchmark twin model, and generates the updated twin model. The multi-condition bearing capacity simulation analysis module performs multi-condition mechanical simulation solutions based on the updated twin model and outputs the simulation analysis results to the result output and scheme verification module. The results output and scheme verification module outputs the bearing capacity analysis results based on the simulation analysis results, and performs simulation verification of the reinforcement scheme.

[0008] Preferably, the reference twin model construction module performs geometric modeling for the variable cross-section thin-walled reinforcement structure of the annular concrete pole. According to the actual reinforcement scheme of the pole, concrete solid module, ordinary steel bar module, and prestressed steel bar module are established respectively. The unit discretization is completed by using a mapping mesh generation method adapted to the annular variable cross-section thin-walled reinforcement structure. The initial mechanical parameters of concrete and various types of steel bars are configured according to the pole's factory inspection report. The initial prestress value is applied to the prestressed steel bars. The boundary constraint conditions of the foundation part are set according to the pole's embedment depth and foundation type. The initial material properties include initial strength parameters of concrete, such as elastic modulus, compressive strength, tensile strength, and Poisson's ratio, as well as initial mechanical parameters of ordinary steel bars and prestressed steel bars, such as yield strength, elastic modulus, and coefficient of linear expansion. The boundary constraints include lateral soil constraints in the foundation burial depth section and vertical displacement constraints at the bottom end, fully restoring the initial mechanical properties of the pole when it was put into operation at the factory.

[0009] Preferably, the multi-dimensional parameter acquisition module acquires structural damage parameters and service environment parameters of the pole to form a multi-dimensional detection dataset carrying spatial coordinates, including: S11. Divide the pole into multiple inspection sections along its axial direction and conduct non-destructive testing at multiple inspection points on each inspection section. Use the ultrasonic rebound combined method to collect concrete strength data, use the electromagnetic induction method to collect steel corrosion data, and use the image recognition method to collect crack data. S12. Install tilt angle detection devices at the top and middle of the pole to collect the deformation tilt angle data of the pole; S13. Deploy environmental sensing terminals around the utility poles to collect temperature and humidity data and wind load data; S14. After removing outliers and standardizing the format of all collected data, add corresponding spatial coordinates to each group of data to form a multidimensional detection dataset carrying spatial coordinates. The spatial coordinates include the axial height and circumferential angle of the detection point. Each set of data corresponds to a unique spatial position of the pole body, providing reliable position information for the subsequent precise correction of the reference twin model at the unit level.

[0010] Preferably, the multi-parameter mapping and model dynamic update module maps the multi-dimensional detection dataset to the corresponding mesh elements of the baseline twin model, corrects the material properties, damage structure, and boundary constraints of the baseline twin model, and generates an updated twin model, including: S21. Based on the axial height and circumferential angle carried by each group of data in the multidimensional detection dataset, the data are matched with the grid cells of the benchmark twin model in terms of spatial position. The spatial position matching adopts the nearest neighbor cell matching algorithm to ensure that the data of each detection point is accurately mapped to the grid cell with the nearest spatial distance, thereby eliminating the mapping deviation caused by grid discrepancies. S22. Adjust the initial strength parameters of the concrete in the corresponding area according to the concrete strength data, and adjust the initial mechanical parameters of the steel bars in the corresponding area according to the steel bar corrosion data. S23. Calculate the structural damage factor D of the mesh element based on the crack depth d and crack width w in the crack data: ; Where h0 is the wall thickness of the corresponding rod segment, l e α is the characteristic length of the grid element, and α is the weighting coefficient for the influence of crack damage. It is obtained by combining the bending test of the annular thin-walled concrete member with the calibration of concrete fracture mechanics parameters. Corresponding calibration values ​​are used for the grid elements in the tension zone and the grid elements in the compression zone, respectively. Based on the structural damage factor, a damaged structure is introduced for the corresponding mesh element, and the stiffness matrix of the mesh element is updated. S24. Based on the deformation tilt angle data, correct the boundary constraints of the corresponding area's foundation, complete the dynamic correction of the benchmark twin model, and generate the updated twin model. In the process of revising the benchmark twin model, differentiated damage reduction logic is adopted for the tension zone, compression zone, and neutral axis region of the annular variable cross section, so that the stiffness attenuation law of the model matches the actual bending stress characteristics of the pole, and avoids the evaluation results that are too conservative / dangerous due to the uniform reduction method.

[0011] Preferably, when the multi-parameter mapping and model dynamic update module corrects the boundary constraint conditions of the foundation in the corresponding region based on the deformation tilt angle data, it adjusts the temperature stress parameters of the concrete and steel bars in the corresponding region based on the temperature and humidity data, adjusts the lateral wind load parameters of the reference twin model in the corresponding region based on the wind load data, and adjusts the stiffness parameters of the foundation based on the foundation depth parameters of the poles in the reference twin model, so as to incorporate the mechanical effects of temperature and humidity data, wind load data and foundation depth parameters into the correction range of the load conditions and boundary constraint conditions of the reference twin model.

[0012] Preferably, the multi-condition bearing capacity simulation analysis module performs multi-condition mechanical simulation solutions based on the updated twin model, and outputs the simulation analysis results to the result output and scheme verification module, including: S31. Configure load parameters and constraints for normal service conditions and extreme conditions such as typhoons and icing. The lateral wind load parameters are distributed in a gradient along the pole height and are set according to the wind pressure height variation coefficient in the design code of overhead transmission lines. The icing load parameters are applied to the conductor suspension point of the pole and are calculated based on the conductor icing thickness and the conductor nominal cross-section. S32. Call the finite element solver to perform mechanical simulation and solve the pole structure under various working conditions, and obtain the stress distribution data, deformation displacement data and ultimate bending bearing capacity of the pole. S33. Calculate the bearing capacity safety margin γ corresponding to each working condition: ; Among them, M u M represents the ultimate flexural bearing capacity under the corresponding working conditions. s β is the standard design bending moment value under the corresponding working condition, which is determined according to the ratio of the measured load parameters to the standard design load. Under the typhoon working condition, the measured wind load amplitude is combined for correction, and under the icing working condition, the equivalent icing load is combined for correction. S34. Locate the weak points in the structure where stress concentration occurs and the load-bearing capacity safety margin is lower than the preset threshold, and output complete simulation analysis results; In the simulation process of the updated twin model, the bending moment distribution, shear force distribution and deflection curve of the entire pole segment are output simultaneously, which can directly locate the pole segment with weak bearing capacity and the location of dangerous section, providing accurate location guidance for subsequent operation and maintenance.

[0013] Preferably, the multi-condition bearing capacity simulation analysis module calls a finite element solver to perform mechanical simulation solutions on the pole structure under various conditions, obtaining stress distribution data, deformation displacement data, and ultimate bending bearing capacity of the pole, including: The updated twin model was loaded using a progressive incremental loading method, and the changes in concrete strain and steel stress in the tension zone were continuously monitored. The ultimate bearing state was determined based on the structural failure criterion coefficient ψ, which was calculated using the following formula: ; Where, ε c ε is the maximum tensile strain of the concrete in the tension zone. cu The ultimate tensile strain of concrete is determined by the material parameters corresponding to the concrete strength grade, σ. s σ is the maximum tensile stress in the reinforcement of the tension zone. sy The yield strength of the steel reinforcement; When the structural failure judgment coefficient ψ≥1, it is determined that the ultimate bearing state has been reached. The current load value is recorded as the ultimate bending bearing capacity under the corresponding working condition. Under typhoon conditions, the pole top displacement reaches the limit value as a supplementary judgment condition. Under icing conditions, the bending moment at the conductor suspension point reaches the limit value as a supplementary judgment condition. The stress distribution data and deformation displacement data of the pole under the ultimate bending bearing capacity are recorded simultaneously.

[0014] Preferably, the result output and solution verification module has a built-in visualization display unit and a reinforcement solution verification unit; The visualization unit presents the damage distribution, stress distribution, ultimate bending capacity, and risk level information of the pole in the form of cloud maps and numerical lists. The risk level is divided according to the numerical range of the bearing capacity safety margin. The reinforcement scheme verification unit supports inputting reinforcement parameters, including reinforcement material parameters, reinforcement location parameters, and reinforcement structure parameters. After mapping the reinforcement parameters to the updated twin model, the multi-condition bearing capacity simulation analysis module is called again to perform calculations, and the comparison data of ultimate flexural bearing capacity and bearing capacity safety margin before and after reinforcement are output.

[0015] A method for analyzing and testing the bearing capacity of concrete poles based on multidimensional parameters includes the following steps: S1. Obtain the design parameters, manufacturing process parameters, and basic constraint parameters of the pole, construct a three-dimensional finite element reference twin model of the pole, and set the initial material properties and boundary constraint conditions; S2. Collect structural damage parameters and service environment parameters of the poles to form a multidimensional detection dataset carrying spatial coordinates; S3. Map the multidimensional detection dataset to the corresponding mesh element of the baseline twin model, correct the material properties, damage structure and boundary constraints of the baseline twin model, and generate the updated twin model. S4. Based on the updated twin model, perform multi-condition mechanical simulation to obtain the stress distribution data, deformation displacement data, ultimate bending bearing capacity of the pole, and the corresponding simulation analysis results. S5. Output the bearing capacity analysis results based on the simulation analysis results, and verify the reinforcement scheme through simulation.

[0016] Preferably, in S4, multi-condition mechanical simulation is performed based on the updated twin model to obtain the stress distribution data, deformation displacement data, ultimate bending bearing capacity of the pole, and the corresponding simulation analysis results, including: S41. Configure load parameters and constraints for normal service conditions and extreme conditions such as typhoons and icing. The lateral wind load parameters are distributed in a gradient along the pole height and are set according to the wind pressure height variation coefficient in the design code of overhead transmission lines. The icing load parameters are applied to the conductor suspension point of the pole and are calculated based on the conductor icing thickness and the conductor nominal cross-section. S42. Use the finite element method (FEM) solver to perform mechanical simulation of the pole structure under various working conditions, and obtain the stress distribution data, deformation displacement data, and ultimate bending capacity of the pole. Specifically, this includes: The updated twin model was loaded using a progressive incremental loading method, and the changes in concrete strain and steel stress in the tension zone were continuously monitored. The ultimate bearing state was determined based on the structural failure criterion coefficient ψ, which was calculated using the following formula: ; Where, ε c ε is the maximum tensile strain of the concrete in the tension zone. cu The ultimate tensile strain of concrete is determined by the material parameters corresponding to the concrete strength grade, σ. s σ is the maximum tensile stress in the reinforcement of the tension zone. sy The yield strength of the steel reinforcement; When the structural failure judgment coefficient ψ≥1, it is determined that the ultimate bearing state has been reached. The current load value is recorded as the ultimate bending bearing capacity under the corresponding working condition. Under the typhoon working condition, the pole top displacement reaches the limit value as a supplementary judgment condition. Under the icing working condition, the bending moment at the conductor hanging point reaches the limit value as a supplementary judgment condition. The stress distribution data and deformation displacement data of the pole under the ultimate bending bearing capacity are recorded simultaneously. S43. Calculate the bearing capacity safety margin γ corresponding to each working condition: ; Among them, M u M represents the ultimate flexural bearing capacity under the corresponding working conditions. s β is the standard design bending moment value under the corresponding working condition, which is determined according to the ratio of the measured load parameters to the standard design load. Under the typhoon working condition, the measured wind load amplitude is combined for correction, and under the icing working condition, the equivalent icing load is combined for correction. S44. Locate the weak points in the structure where stress concentration occurs and the load-bearing capacity safety margin is lower than the preset threshold, and output complete simulation analysis results; In the simulation process of the updated twin model, the bending moment distribution, shear force distribution and deflection curve of the entire pole segment are output simultaneously, which can directly locate the pole segment with weak bearing capacity and the location of dangerous section, providing accurate location guidance for subsequent operation and maintenance.

[0017] (III) Beneficial Effects Compared with existing technologies, the multi-dimensional parameter-based concrete pole bearing capacity analysis and testing system and method provided by this invention achieves dynamic mapping and updating of the model by constructing a three-dimensional finite element reference twin model of the pole and combining it with multi-dimensional non-destructive testing data. The test data, such as concrete strength, steel corrosion degree, crack spatial distribution, and pole deformation angle, are used to correct the material properties, damage structure, and boundary constraints of the reference twin model according to spatial location, achieving real-time synchronization between the digital twin model and the actual structural state of the pole. Based on this, bearing capacity simulation calculations are carried out under normal service conditions and extreme conditions such as typhoons and icing, relying on the dynamically updated digital twin model. This enables accurate assessment of the pole's bearing capacity and verification of the safety margin of bearing capacity under extreme conditions, effectively improving the accuracy and practical fit of the bearing capacity analysis results. Simultaneously, it provides reliable digital simulation support for pole disaster risk assessment and reinforcement scheme verification, fully ensuring the scientific and effective nature of pole operation and maintenance decisions. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0019] Figure 1 This is a schematic diagram of the working principle of the system of the present invention; Figure 2 This is a schematic flowchart of the method of the present invention; Figure 3 This is a flowchart illustrating the steps of the method of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0021] The multi-dimensional parameter-based concrete pole bearing capacity analysis and testing system uses digital twin technology as its core framework. Addressing the bearing capacity assessment needs of in-service ring-shaped concrete poles, it reconstructs a three-dimensional finite element baseline twin model of the pole to recreate its initial service state. This model integrates structural damage parameters and service environment parameters obtained from on-site non-destructive testing, using a unified spatial coordinate system as the data link to precisely map the test data to the corresponding mesh elements of the baseline twin model. The system dynamically corrects the material properties, damaged structures, and boundary constraints of the baseline twin model, generating an updated twin model that is synchronized in real-time with the actual deterioration state of the pole. Based on this dynamically updated digital twin model, it performs bearing capacity simulation calculations under normal service conditions and extreme conditions such as typhoons and icing. This obtains stress distribution data, deformation displacement data, and ultimate bending bearing capacity of the entire pole segment, calculates the bearing capacity safety margin under each condition, and accurately locates structural weak points. Simultaneously, it supports digital simulation verification and quantitative comparison of different reinforcement schemes, ultimately achieving high-precision assessment of the concrete pole bearing capacity and providing digital support for operation and maintenance decisions.

[0022] The concrete pole bearing capacity analysis and testing system based on multi-dimensional parameters adopts a hierarchical serial data flow architecture. All modules share a unified spatial coordinate reference and data format standard, which ensures the mapping and matching accuracy between the test data and the three-dimensional finite element reference twin model of the pole from the source, and avoids model correction system errors caused by spatial misalignment.

[0023] The following describes the specific functional modules of the concrete pole bearing capacity analysis and testing system based on multidimensional parameters provided by this invention, using concrete poles as examples. Figure 1 (as shown) and technical effects.

[0024] The system includes the following functional modules: The reference twin model construction module retrieves the design parameters, manufacturing process parameters, and basic constraint parameters of the pole to construct a three-dimensional finite element reference twin model of the pole, and sets the initial material properties and boundary constraint conditions. The multi-dimensional parameter acquisition module collects structural damage parameters and service environment parameters of the pole, forming a multi-dimensional detection dataset carrying spatial coordinates. The multi-parameter mapping and dynamic model update module maps the multi-dimensional detection dataset to the corresponding mesh element of the benchmark twin model, corrects the material properties, damage structure and boundary constraints of the benchmark twin model, and generates the updated twin model. The multi-condition bearing capacity simulation analysis module performs multi-condition mechanical simulation solutions based on the updated twin model and outputs the simulation analysis results to the result output and scheme verification module. The results output and scheme verification module outputs the bearing capacity analysis results based on the simulation analysis results, and performs simulation verification of the reinforcement scheme.

[0025] I. Benchmark Twin Model Construction Module The baseline twin model construction module performs geometric modeling for the variable cross-section thin-walled reinforced structure of the annular concrete pole. According to the actual reinforcement scheme of the pole, concrete solid module, ordinary steel bar module, and prestressed steel bar module are established respectively. The element discretization is completed by using a mapping mesh generation method adapted to the annular variable cross-section thin-walled reinforced structure. The initial mechanical parameters of concrete and various types of steel bars are configured according to the pole's factory inspection report. The initial prestress value is applied to the prestressed steel bars. The boundary constraint conditions of the foundation part are set according to the pole's embedment depth and foundation type. Initial material properties include initial strength parameters of concrete, such as elastic modulus, compressive strength, tensile strength, and Poisson's ratio, as well as initial mechanical parameters of ordinary steel bars and prestressed steel bars, such as yield strength, elastic modulus, and coefficient of linear expansion. The boundary constraints include lateral soil constraints for the foundation depth section and vertical displacement constraints at the bottom, fully restoring the initial mechanical properties of the pole when it was put into operation at the factory.

[0026] II. Multidimensional Parameter Acquisition Module The multi-dimensional parameter acquisition module collects structural damage parameters and service environment parameters of the pole, forming a multi-dimensional detection dataset carrying spatial coordinates, including: S11. Divide the pole into multiple inspection sections along its axial direction and conduct non-destructive testing at multiple inspection points on each inspection section. Use the ultrasonic rebound combined method to collect concrete strength data, use the electromagnetic induction method to collect steel corrosion data, and use the image recognition method to collect crack data. S12. Install tilt angle detection devices at the top and middle of the pole to collect the deformation tilt angle data of the pole; S13. Deploy environmental sensing terminals around the utility poles to collect temperature and humidity data and wind load data; S14. After removing outliers and standardizing the format of all collected data, add corresponding spatial coordinates to each group of data to form a multidimensional detection dataset carrying spatial coordinates. The spatial coordinates include the axial height and circumferential angle of the detection point. Each set of data corresponds to a unique spatial position of the pole body, providing reliable position information for the subsequent precise correction of the reference twin model at the unit level.

[0027] III. Multi-parameter mapping and dynamic model update module The multi-parameter mapping and dynamic model update module maps the multi-dimensional detection dataset to the corresponding mesh elements of the baseline twin model, corrects the material properties, damage structure, and boundary constraints of the baseline twin model, and generates an updated twin model, including: S21. Based on the axial height and circumferential angle carried by each group of data in the multidimensional detection dataset, the data are matched with the grid cells of the benchmark twin model in terms of spatial position. The spatial position matching adopts the nearest neighbor cell matching algorithm to ensure that the data of each detection point is accurately mapped to the grid cell with the nearest spatial distance, thereby eliminating the mapping deviation caused by grid discrepancies. S22. Adjust the initial strength parameters of the concrete in the corresponding area according to the concrete strength data, and adjust the initial mechanical parameters of the steel bars in the corresponding area according to the steel bar corrosion data. S23. Calculate the structural damage factor D of the mesh element based on the crack depth d and crack width w in the crack data: ; Where h0 is the wall thickness of the corresponding rod segment, l e α is the characteristic length of the grid element, and α is the weighting coefficient for the influence of crack damage. It is obtained by combining the bending test of the annular thin-walled concrete member with the calibration of concrete fracture mechanics parameters. Corresponding calibration values ​​are used for the grid elements in the tension zone and the grid elements in the compression zone, respectively. Based on the structural damage factor, a damaged structure is introduced for the corresponding mesh element, and the stiffness matrix of the mesh element is updated. S24. Based on the deformation tilt angle data, correct the boundary constraints of the corresponding area's foundation, complete the dynamic correction of the benchmark twin model, and generate the updated twin model. In the process of revising the benchmark twin model, differentiated damage reduction logic is adopted for the tension zone, compression zone, and neutral axis region of the annular variable cross section, so that the stiffness attenuation law of the model matches the actual bending stress characteristics of the pole, and avoids the evaluation results that are too conservative / dangerous due to the uniform reduction method.

[0028] In the technical solution of this application, when the multi-parameter mapping and model dynamic update module corrects the boundary constraint conditions of the foundation parts in the corresponding area based on the deformation tilt angle data, it adjusts the temperature stress parameters of the concrete and steel bars in the corresponding area based on the temperature and humidity data, adjusts the lateral wind load parameters of the reference twin model in the corresponding area based on the wind load data, and adjusts the stiffness parameters of the foundation parts based on the foundation depth parameters of the poles in the reference twin model, so as to incorporate the mechanical effects of temperature and humidity data, wind load data and foundation depth parameters into the correction range of the load conditions and boundary constraint conditions of the reference twin model.

[0029] IV. Multi-condition bearing capacity simulation analysis module The multi-condition bearing capacity simulation analysis module performs multi-condition mechanical simulation solutions based on the updated twin model, and outputs the simulation analysis results to the result output and scheme verification module, including: S31. Configure load parameters and constraints for normal service conditions and extreme conditions such as typhoons and icing. The lateral wind load parameters are distributed in a gradient along the pole height and are set according to the wind pressure height variation coefficient in the design code of overhead transmission lines. The icing load parameters are applied to the conductor suspension point of the pole and are calculated based on the conductor icing thickness and the conductor nominal cross-section. S32. Call the finite element solver to perform mechanical simulation and solve the pole structure under various working conditions, and obtain the stress distribution data, deformation displacement data and ultimate bending bearing capacity of the pole. S33. Calculate the bearing capacity safety margin γ corresponding to each working condition: ; Among them, M u M represents the ultimate flexural bearing capacity under the corresponding working conditions. s β is the standard design bending moment value under the corresponding working condition, which is determined according to the ratio of the measured load parameters to the standard design load. Under the typhoon working condition, the measured wind load amplitude is combined for correction, and under the icing working condition, the equivalent icing load is combined for correction. S34. Locate the weak points in the structure where stress concentration occurs and the load-bearing capacity safety margin is lower than the preset threshold, and output complete simulation analysis results; In the simulation process of the updated twin model, the bending moment distribution, shear force distribution and deflection curve of the entire pole segment are output simultaneously, which can directly locate the pole segment with weak bearing capacity and the location of dangerous section, providing accurate location guidance for subsequent operation and maintenance.

[0030] Specifically, the multi-condition bearing capacity simulation analysis module calls the finite element solver to perform mechanical simulation solutions on the pole structure under various conditions, obtaining stress distribution data, deformation displacement data, and ultimate bending bearing capacity of the pole, including: The updated twin model was loaded using a progressive incremental loading method, and the changes in concrete strain and steel stress in the tension zone were continuously monitored. The ultimate bearing state was determined based on the structural failure criterion coefficient ψ, which was calculated using the following formula: ;

[0031] Where, ε c ε is the maximum tensile strain of the concrete in the tension zone. cu The ultimate tensile strain of concrete is determined by the material parameters corresponding to the concrete strength grade, σ. s σ is the maximum tensile stress in the reinforcement of the tension zone. sy The yield strength of the steel reinforcement; When the structural failure judgment coefficient ψ≥1, it is determined that the ultimate bearing state has been reached. The current load value is recorded as the ultimate bending bearing capacity under the corresponding working condition. Under typhoon conditions, the pole top displacement reaches the limit value as a supplementary judgment condition. Under icing conditions, the bending moment at the conductor suspension point reaches the limit value as a supplementary judgment condition. The stress distribution data and deformation displacement data of the pole under the ultimate bending bearing capacity are recorded simultaneously.

[0032] VI. Results Output and Scheme Verification Module

[0033] The results output and solution verification module includes a built-in visualization unit and a reinforcement solution verification unit.

[0034] The visualization unit presents the damage distribution, stress distribution, ultimate bending capacity, and risk level information of the pole in the form of cloud maps and numerical lists. The risk level is divided according to the numerical range of the bearing capacity safety margin.

[0035] The reinforcement scheme verification unit supports inputting reinforcement parameters, including reinforcement material parameters, reinforcement location parameters, and reinforcement structure parameters. After mapping the reinforcement parameters to the updated twin model, the multi-condition bearing capacity simulation analysis module is called again to perform calculations, and the comparison data of ultimate flexural bearing capacity and bearing capacity safety margin before and after reinforcement are output.

[0036] Building upon the aforementioned multi-dimensional parameter-based concrete pole bearing capacity analysis and testing system, this invention further discloses a multi-dimensional parameter-based concrete pole bearing capacity analysis and testing method. This method uses spatial coordinates as the data association link throughout the process, achieving a one-to-one correspondence between on-site testing data and a digital twin model. The testing and analysis process does not require interruption of the power supply to the line, and the entire bearing capacity analysis can be completed while the pole is operating normally, significantly reducing the impact of testing operations on power supply continuity. Figure 2 and Figure 3 As shown, it includes the following steps:

[0037] S1. Obtain the design parameters, manufacturing process parameters, and basic constraint parameters of the pole, construct a three-dimensional finite element reference twin model of the pole, and set the initial material properties and boundary constraint conditions;

[0038] S2. Collect structural damage parameters and service environment parameters of the poles to form a multidimensional detection dataset carrying spatial coordinates;

[0039] S3. Map the multidimensional detection dataset to the corresponding mesh element of the baseline twin model, correct the material properties, damage structure and boundary constraints of the baseline twin model, and generate the updated twin model.

[0040] S4. Based on the updated twin model, perform multi-condition mechanical simulation to obtain the stress distribution data, deformation displacement data, ultimate bending bearing capacity of the pole, and the corresponding simulation analysis results.

[0041] S5. Output the bearing capacity analysis results based on the simulation analysis results, and verify the reinforcement scheme through simulation.

[0042] Specifically, in S4, multi-condition mechanical simulations are performed based on the updated twin model to obtain stress distribution data, deformation displacement data, ultimate bending capacity, and corresponding simulation analysis results for the pole, including:

[0043] S41. Configure load parameters and constraints for normal service conditions and extreme conditions such as typhoons and icing. The lateral wind load parameters are distributed in a gradient along the pole height and are set according to the wind pressure height variation coefficient in the design code of overhead transmission lines. The icing load parameters are applied to the conductor suspension point of the pole and are calculated based on the conductor icing thickness and the conductor nominal cross-section.

[0044] S42. Use the finite element method (FEM) solver to perform mechanical simulation of the pole structure under various working conditions, and obtain the stress distribution data, deformation displacement data, and ultimate bending capacity of the pole. Specifically, this includes:

[0045] The updated twin model was loaded using a progressive incremental loading method, and the changes in concrete strain and steel stress in the tension zone were continuously monitored. The ultimate bearing state was determined based on the structural failure criterion coefficient ψ, which was calculated using the following formula:

[0046] ;

[0047] Where, ε c ε is the maximum tensile strain of the concrete in the tension zone. cu The ultimate tensile strain of concrete is determined by the material parameters corresponding to the concrete strength grade, σ. s σ is the maximum tensile stress in the reinforcement of the tension zone. sy The yield strength of the steel reinforcement;

[0048] When the structural failure judgment coefficient ψ≥1, it is determined that the ultimate bearing state has been reached. The current load value is recorded as the ultimate bending bearing capacity under the corresponding working condition. Under the typhoon working condition, the pole top displacement reaches the limit value as a supplementary judgment condition. Under the icing working condition, the bending moment at the conductor hanging point reaches the limit value as a supplementary judgment condition. The stress distribution data and deformation displacement data of the pole under the ultimate bending bearing capacity are recorded simultaneously.

[0049] S43. Calculate the bearing capacity safety margin γ corresponding to each working condition:

[0050] ;

[0051] Among them, M u M represents the ultimate flexural bearing capacity under the corresponding working conditions. s β is the standard design bending moment value under the corresponding working condition, which is determined according to the ratio of the measured load parameters to the standard design load. Under the typhoon working condition, the measured wind load amplitude is combined for correction, and under the icing working condition, the equivalent icing load is combined for correction.

[0052] S44. Locate the weak points in the structure where stress concentration occurs and the load-bearing capacity safety margin is lower than the preset threshold, and output complete simulation analysis results;

[0053] In the simulation process of the updated twin model, the bending moment distribution, shear force distribution and deflection curve of the entire pole segment are output simultaneously, which can directly locate the pole segment with weak bearing capacity and the location of dangerous section, providing accurate location guidance for subsequent operation and maintenance.

[0054] To better illustrate the technical solution of this application, a specific embodiment will be described in detail below.

[0055] The concrete pole bearing capacity analysis and testing system based on multi-dimensional parameters used in this embodiment includes a reference twin model construction module, a multi-dimensional parameter acquisition module, a multi-parameter mapping and model dynamic update module, a multi-condition bearing capacity simulation analysis module, and a result output and scheme verification module. The system as a whole adopts a hierarchical serial data flow architecture. All modules share a unified spatial coordinate reference and data format standard. The coordinate reference is based on the center of the bottom section of the pole as the origin, with the axial direction upward along the pole height and the circumferential direction starting from the direction of the conductor suspension point. All test data and model units use the same coordinate system, ensuring the mapping and matching accuracy between test data and finite element model units from the source and avoiding model correction system errors caused by spatial misalignment.

[0056] The test object in this embodiment is a ring-shaped prestressed concrete pole in a 10kV distribution network line. The pole has a total height of 15m, a top diameter of 190mm, a root diameter of 390mm, a cross-sectional wall thickness of 50mm, and a concrete design strength grade of C40. It is equipped with 12 prestressed main bars and spiral ordinary stirrups. The pole foundation is directly buried at a depth of 2m, and the surrounding area is silty clay soil.

[0057] The baseline twin model construction module first retrieves the design drawings, factory inspection reports, and foundation construction records of the pole to be tested, obtaining complete geometric dimensional parameters, reinforcement scheme parameters, prestressing tension parameters, concrete and steel reinforcement mechanical parameters, foundation depth parameters, and foundation form parameters. For the variable cross-section thin-walled reinforced structure of the annular concrete pole, refined geometric modeling is carried out, establishing concrete solid elements, ordinary steel reinforcement elements, and prestressed steel reinforcement elements respectively. The concrete elements use 8-node 3D solid elements, and the steel reinforcement elements use 2-node truss elements. An embedding algorithm is used to embed the steel reinforcement elements into the concrete elements to ensure deformation coordination between the two materials.

[0058] The element discretization was completed by a mapping mesh generation method adapted to the annular thin-walled structure. 75 mesh layers were set along the pole axis, with each layer having a height of 200 mm. 24 elements were divided along the circumferential direction, with each element corresponding to a 15° circumferential angle. Two layers of elements were divided in the wall thickness direction. This method ensures the mesh regularity of the annular thin-walled structure, avoids the impact of distorted elements generated by free mesh on the calculation accuracy, and also takes into account the spatial resolution and overall calculation efficiency of subsequent mapping correction.

[0059] After mesh generation, the initial elastic modulus, compressive strength, tensile strength, and Poisson's ratio parameters of the concrete are configured according to the pole's factory inspection report. The yield strength, elastic modulus, and linear expansion coefficient parameters of ordinary steel bars and prestressed steel bars are also configured. The initial strain method is used to apply corresponding initial prestress values ​​to the prestressed steel bar elements, restoring the prestressed state and initial mechanical properties of the pole at the time of manufacture. Finally, constraint conditions for the foundation are set based on the pole's burial depth and surrounding soil parameters. Nonlinear spring elements are used in the burial section to simulate lateral soil constraints, and vertical displacement and horizontal rotation constraints are set at the bottom, completely restoring the initial mechanical boundaries of the pole during its initial operation. A baseline twin model is generated, and a multi-parameter mapping and model dynamic update module is output.

[0060] The multi-dimensional parameter acquisition module is responsible for collecting and preprocessing on-site test data, forming a multi-dimensional test dataset carrying spatial coordinates. During on-site testing, eight test sections are evenly divided along the pole axis from the root to the tip, with each section spaced approximately 1.8m apart. Eight test points are evenly set along the circumference of each section, completely covering the tension zone, compression zone, and neutral axis region of the cross-section. For each test point, the ultrasonic rebound combined method is used to test the concrete strength. Before testing, the rebound hammer and ultrasonic testing instrument are calibrated on-site. Rebound testing is performed at each point, recording 16 rebound values. After removing extreme values, the average rebound value is calculated. Then, ultrasonic testing is performed, recording the propagation velocity of ultrasonic waves in the concrete. The converted concrete strength value is calculated according to the conversion formula in the current testing specifications. This is then corrected by combining the test angle and the pouring surface to obtain the final concrete strength value.

[0061] An electromagnetic induction rebar corrosion detector was used to scan the rebar segment by segment along its direction, reading the corrosion potential value of each segment. The corrosion level was determined based on the potential value range. Simultaneously, the effective cross-sectional area of ​​the rebar was calculated by combining the rebar diameter data to obtain the corrosion degree data for each segment. A high-definition industrial camera continuously captured surface images along the axial direction of the pole. An image stitching algorithm was used to obtain a panoramic image of the entire pole surface. An edge extraction algorithm was then used to identify crack contours, calculating the length and width of each crack. A binocular stereo vision matching algorithm was used to calculate the crack depth. Simultaneously, the axial position and circumferential angle of each crack were recorded to generate a crack spatial distribution dataset.

[0062] High-precision tilt sensors are installed at the top and half the height of the pole, respectively. These sensors have a measurement accuracy of 0.01° and are mounted on the windward and lateral sides of the pole. They continuously collect data on the lateral and longitudinal deformation tilt angles of the pole at a frequency of once per minute, averaging the data after 30 minutes to obtain the final deformation tilt angle data. Environmental sensing terminals, integrating temperature and humidity sensors and wind speed and direction sensors, are deployed within a 2-meter radius around the pole at a height of 2 meters above the ground. These terminals continuously collect data on air temperature, relative humidity, and real-time wind speed in the service environment, calculating the corresponding wind load value based on wind speed and air density.

[0063] After all data acquisition is completed, the Laida criterion is used to remove outliers from all data, eliminating data that exceeds the reasonable range. Then, all data is standardized into a standard numerical format, and corresponding axial height and circumferential angle spatial coordinates are added to each set of test data. The axial coordinates increase upwards from the pole base, and the circumferential coordinates increase clockwise from 0° in the direction of the conductor crossarm, forming a standardized multidimensional test dataset, which is then output to the multi-parameter mapping and model dynamic update module. For example... Figure 3 As shown, multidimensional parameter acquisition is the second step in the entire detection process, providing comprehensive measured data support for subsequent dynamic model updates.

[0064] After receiving the benchmark twin model and the multidimensional detection dataset, the multi-parameter mapping and dynamic model update module first performs spatial location matching. Based on the axial height and circumferential angle coordinates carried by the detection data, the nearest neighbor element matching algorithm is used to match the spatial locations of each detection parameter with the grid elements of the benchmark twin model. The data at each detection point is automatically mapped to the nearest spatially distant finite element grid element, eliminating the mapping deviation caused by grid discretization, ensuring that the correction parameters of each element correspond to the actual detection data, and avoiding correction errors caused by spatial misalignment.

[0065] After spatial matching is completed, the material property parameters are first corrected. Based on the concrete strength test results, the elastic modulus and strength parameters of the corresponding concrete units are adjusted. For areas where the strength test value is lower than the design value, the elastic modulus and tensile and compressive strength parameters of the units are reduced proportionally. For areas where the strength test value is higher than the design value, the design parameters are maintained to avoid overestimating the actual load-bearing capacity of the structure. Based on the steel corrosion degree test results, the effective cross-sectional area and mechanical property parameters of the corresponding steel reinforcement units are adjusted. The cross-sectional area of ​​the steel reinforcement units is reduced according to the corrosion loss ratio, and the yield strength parameter of the steel reinforcement is reduced simultaneously to restore the actual mechanical properties of the corroded steel reinforcement.

[0066] In the specific implementation of this embodiment, the damage factor is used to characterize the damage degree of the unit in order to correct crack damage. The formula for calculating the damage factor is as follows: Where D is the damage factor of the corresponding mesh element, d is the detected crack depth, h0 is the cross-sectional wall thickness of the corresponding bar segment, w is the detected crack width, and l e α represents the characteristic length of the corresponding mesh element, and α is the weighting coefficient for the impact of crack damage.

[0067] The weighting coefficient α for crack damage was obtained through bending tests on annular thin-walled concrete members combined with calibration of concrete fracture mechanics parameters. The specific calibration process is as follows: Six sets of standard annular thin-walled concrete specimens were fabricated. All specimens used the same concrete mix proportion, wall thickness, and reinforcement scheme as the actual utility poles and were cured to a standard age of 28 days. Standard cracks with different parameters were pre-cast on the surface of each set of specimens. The crack depth was set to different proportions of the wall thickness, and the crack width was set to different levels, covering the range of crack parameters commonly encountered in engineering. Four-point bending tests were conducted on all specimens to simulate the actual bending stress state of the utility pole. During the loading process, the mid-span deflection and loading force values ​​of the specimens were continuously collected to obtain the load-deflection curves of each set of specimens. The initial stiffness of each specimen was calculated based on the initial slope of the curve, and the working stiffness of the cracked specimen was calculated based on the slope of the curve after the crack appeared. Then, the stiffness reduction rate of the specimen corresponding to different crack parameters was obtained.

[0068] Simultaneously, based on the double-K fracture criterion and virtual crack model in concrete fracture mechanics, the theoretical values ​​of stress intensity factor and element stiffness reduction at the crack tip under different crack parameters were calculated, establishing a theoretical correlation between crack parameters and stiffness reduction rate. The stiffness reduction rates of each group of specimens measured in the experiment were substituted into the damage factor calculation formula. Using a linear correspondence between the damage factor value and the element stiffness reduction rate as the fitting objective, the least squares method was employed for data fitting. When the calculated stiffness reduction degree corresponding to the damage factor perfectly matched the experimentally measured value, the corresponding weighting coefficient value was obtained. Since cracks in the tension zone directly reduce the effective tensile area of ​​the section when the annular section is subjected to bending, the attenuation effect on the structural bending stiffness is more significant. Therefore, the weighting coefficient value obtained from fitting the specimens in the tension zone is larger. Cracks in the compression zone mainly affect local compressive performance and have a relatively weaker impact on the overall bending stiffness. Therefore, the weighting coefficient value obtained from fitting the specimens in the compression zone is smaller.

[0069] After calibration, the two types of weight coefficients are stored in the system parameter library. During the model mapping process, the system automatically determines the stress area according to the circumferential position of the unit in the cross section, calls the corresponding weight coefficient to calculate the damage factor, and ensures that the damage correction result conforms to the actual stress characteristics of the pole, avoiding the evaluation result that is too conservative or too dangerous due to the uniform reduction method.

[0070] After calculating the damage factors for all cracked elements, a damage constitutive relation is introduced for the corresponding elements based on the damage factors, and the element stiffness matrix is ​​updated. The reduction in element stiffness is positively correlated with the damage factor value; the larger the damage factor, the greater the reduction in element stiffness, thus restoring the weakening effect of cracks on structural stiffness. After completing the correction of material properties and damage constitutive properties, the boundary constraint conditions of the model are further modified. The angular stiffness of the foundation is back-calculated based on the deformation and tilt angle data of the pole. According to the difference between the tilt angle at the top and middle of the pole and the law of mechanical transmission, the actual constraint stiffness of the foundation is derived, and the stiffness parameters of the foundation constraint spring elements are adjusted to ensure that the deformation characteristics of the model are consistent with the actual deformation state of the solid pole.

[0071] Simultaneously, the temperature stress parameters of concrete and steel reinforcement materials are adjusted based on the collected environmental temperature and humidity data. The difference between the ambient temperature and the design reference temperature is calculated, and the additional stress generated by temperature deformation is introduced, incorporating the temperature effect into the model's calculation range. The initial value of the lateral load on the model is adjusted based on measured wind load data, and the field-measured wind load is input into the model as the reference load, replacing the default design wind load. The stiffness parameters of the foundation constraint elements are adjusted based on the foundation depth parameters in the reference twin model; the greater the depth, the higher the foundation constraint stiffness and the stronger the soil constraint effect. After completing all parameter corrections, an updated twin model that is completely synchronized with the actual service state of the physical pole is generated and output to the multi-condition bearing capacity simulation analysis module.

[0072] After receiving the updated twin model, the multi-condition load-bearing capacity simulation analysis module first configures the load parameters and constraints for various operating conditions. The operating conditions are divided into three categories: normal service load condition, typhoon extreme load condition, and icing extreme load condition. For the normal service condition, conductor tension and conventional wind load are set according to the line's normal operating load. The lateral wind load is distributed in a gradient along the pole height, with the distribution pattern set according to the wind pressure height variation coefficient in the overhead transmission line design specifications; the higher the height, the greater the corresponding wind pressure value, thus replicating the actual wind load distribution characteristics. For the typhoon condition, the wind load amplitude is set according to the 50-year return period disaster standard, and corrected using local measured typhoon data. For the icing condition, the equivalent icing load is calculated based on the design icing thickness, and the icing load is concentrated at the conductor suspension point of the pole, while simultaneously superimposing the wind load at the corresponding wind speed. The load parameters for all operating conditions comply with current engineering design standards, ensuring that the simulation results have engineering applicability and field reference value.

[0073] After configuring the load conditions, the finite element method (FEM) solver was invoked to perform mechanical solutions on the pole structure under each load condition. First, a static linear solution was performed to obtain stress distribution data, deformation displacement data, bending moment distribution data, and shear force distribution data for the entire pole segment under each load condition, initially locating stress concentration points and maximum deformation locations. Then, the ultimate bearing capacity was determined by applying loads to the pole model using a progressively incremental loading method. Initially, a force-controlled mode was used, with each load increment being 1 / 10 of the estimated ultimate load. When the concrete strain in the tension zone reached 80% of the ultimate tensile strain, the mode was switched to displacement control, reducing the loading step size to ensure accurate capture of the structural failure threshold. After each loading stage, tensile strain data for all concrete elements and tensile stress data for all steel reinforcement elements were extracted, and the structural failure criterion coefficient was used to determine the structural state under the current load.

[0074] In the specific implementation of this embodiment, the formula for calculating the structural failure judgment coefficient is as follows: Where ψ is the structural failure criterion, and ε c ε is the maximum tensile strain of the concrete element in the tension zone. cu The ultimate tensile strain of concrete is determined by the material properties corresponding to the concrete strength grade, σ. s σ is the maximum tensile stress of the reinforcing bar element. sy This represents the yield strength of the reinforcing steel.

[0075] When the structural failure criterion coefficient ψ is greater than or equal to 1, the structure is determined to have reached its ultimate bearing capacity. Loading is immediately stopped, and the maximum bending moment at the pole base corresponding to the current load is recorded as the ultimate bending bearing capacity. Simultaneously, the stress and displacement cloud diagrams of the entire pole under that load step are saved. For typhoon conditions, in addition to the strength failure criterion, a serviceability limit state criterion is added. When the lateral displacement at the pole top reaches a set limit value, even if the criterion coefficient does not reach 1, the structure is determined to no longer meet normal service requirements, and the corresponding load is taken as the serviceability limit bearing capacity. For icing conditions, the conductor suspension point is the section with the maximum bending moment of the entire pole. When the bending moment at this section reaches the design limit value, it is simultaneously determined to be in a failure state, ensuring that failure determination under extreme conditions simultaneously considers structural strength safety and line deformation requirements.

[0076] After obtaining the ultimate flexural bearing capacity under each working condition, the bearing capacity safety margin corresponding to each working condition is further calculated. In the specific implementation of this embodiment, the formula for calculating the bearing capacity safety margin is as follows: Where γ is the bearing capacity safety margin under the corresponding working condition, and M u To simulate and solve for the ultimate bending capacity of the pole, M s β represents the standard design bending moment value under the corresponding working condition, and β is the working condition load correction factor.

[0077] The load correction factor β is determined based on the ratio of the measured environmental load data to the standard design load. The specific calculation method is as follows: Based on 10 consecutive years of meteorological observation data from local meteorological stations, the maximum wind speed and maximum icing thickness values ​​for each year are extracted. Statistical analysis is performed using the extreme value type I distribution function to obtain the design values ​​of meteorological parameters for the corresponding return period. For typhoon conditions, the statistically obtained maximum wind speed is converted into a measured wind load value. The ratio of the measured wind load value to the standard design wind load value specified in the code is calculated to obtain the load correction factor for typhoon conditions. For icing conditions, the statistically obtained maximum icing thickness is converted into an equivalent icing load value. The ratio of the equivalent icing load value to the standard design icing load value is calculated to obtain the load correction factor for icing conditions. If the actual local meteorological load is higher than the standard design value, the correction factor is greater than 1, and the corresponding safety margin is reduced accordingly. If the actual meteorological load is lower than the standard design value, the correction factor is less than 1, and the corresponding safety margin is increased accordingly. This ensures that the safety margin assessment can accurately reflect the actual local disaster risk level and avoids assessment deviations caused by uniformly adopting standard design values. Under normal service conditions, the load correction factor is taken as the standard value of 1.0.

[0078] After completing the safety margin calculation, the system automatically locates stress concentration points and structural weak points where the bearing capacity margin is below a set threshold, marks the axial range and circumferential position of the weak segments, and compiles the stress distribution, deformation displacement, ultimate bearing capacity, and safety margin data for the entire segment to form a complete simulation analysis result, which is then output to the result output and scheme verification module. For example... Figure 2 As shown, multi-condition load-bearing capacity simulation calculation is the core part of the entire testing process. After the simulation calculation is completed, the system will determine whether reinforcement scheme verification is required based on the needs.

[0079] The results output and solution verification module includes a built-in visualization unit and a reinforcement solution verification unit. The visualization unit visually presents the stress distribution, damage distribution, and deformation characteristics of the entire pole segment in the form of stress cloud maps, damage cloud maps, and deflection curves. It also lists the ultimate bearing capacity, safety margin, and corresponding risk level for each working condition in numerical form. Risk levels are divided based on the range of the bearing capacity safety margin; the higher the margin value, the lower the risk level. When the margin value is below a set threshold, it is automatically classified as a high-risk level and an early warning is generated. The system can automatically generate standardized inspection and analysis reports. The reports include basic pole information, on-site inspection parameters, simulation analysis results, weak point markings, and targeted maintenance suggestions. The report format conforms to the document specifications of power operation and maintenance departments and can be directly imported into the equipment ledger management system, adapting to the defect closed-loop management workflow.

[0080] The reinforcement scheme verification unit allows maintenance personnel to input parameters for various reinforcement schemes, including the mechanical parameters of the reinforcement materials, the range of reinforcement locations, and the form of the reinforcement structure. Common reinforcement schemes such as carbon fiber cloth bonding, fiberglass cladding, and adding clamps can all be input for verification. After inputting the reinforcement parameters, the system automatically maps them to the current twin model, adds reinforcement units at the corresponding locations, and sets the corresponding material properties and interface bonding constraints. Then, it calls the multi-condition load-bearing capacity simulation analysis module again to complete the load-bearing capacity calculation after reinforcement, outputting a comparison of the ultimate load-bearing capacity before and after reinforcement and changes in safety margin. This quantitatively demonstrates the improvement effect of the reinforcement scheme, helping maintenance personnel compare the cost-effectiveness of different reinforcement schemes and select the optimal one. After completing the reinforcement scheme verification or confirming that no verification is needed, the system outputs the final load-bearing capacity analysis results, completing the entire testing process.

[0081] In summary, this embodiment constructs a digital twin model that is synchronized in real time with the actual service status of the utility pole. By integrating multi-dimensional non-destructive testing data, it achieves unit-level dynamic correction of the model, accurately reproducing structural changes such as material strength decay, steel corrosion and deterioration, and crack propagation damage during the long-term service of the pole. This effectively solves the problem that traditional static models cannot match the dynamic deterioration state of the pole, significantly improving the accuracy and practical relevance of the load-bearing capacity assessment results. Through multi-condition mechanical simulation analysis, it can comprehensively verify the load-bearing capacity and safety margin of the pole under normal service conditions and extreme disasters such as typhoons and icing, accurately locating structural weak points and providing clear directional guidance for pole operation and maintenance and defect remediation. The reinforcement scheme simulation verification function can quantitatively evaluate the performance improvement effect of different reinforcement schemes, providing reliable digital support for operation and maintenance decisions, helping to scientifically formulate operation and maintenance plans, reduce the risk of pole collapse and line breakage accidents, and improve the safety and stability of power distribution network operation. The entire testing process does not require interruption of power supply and can be completed under the normal service status of the pole, significantly reducing the impact of testing operations on power supply continuity, and has good engineering application value and promotion prospects.

[0082] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-dimensional parameter-based concrete pole bearing capacity analysis and testing system, characterized in that: Includes the following functional modules: The reference twin model construction module retrieves the design parameters, manufacturing process parameters, and basic constraint parameters of the pole to construct a three-dimensional finite element reference twin model of the pole, and sets the initial material properties and boundary constraint conditions. The multi-dimensional parameter acquisition module collects structural damage parameters and service environment parameters of the pole, forming a multi-dimensional detection dataset carrying spatial coordinates. The multi-parameter mapping and dynamic model update module maps the multi-dimensional detection dataset to the corresponding mesh element of the benchmark twin model, corrects the material properties, damage structure and boundary constraints of the benchmark twin model, and generates the updated twin model. The multi-condition bearing capacity simulation analysis module performs multi-condition mechanical simulation solutions based on the updated twin model and outputs the simulation analysis results to the result output and scheme verification module. The results output and scheme verification module outputs the bearing capacity analysis results based on the simulation analysis results, and performs simulation verification of the reinforcement scheme.

2. The concrete pole bearing capacity analysis and testing system based on multi-dimensional parameters according to claim 1, characterized in that: The reference twin model construction module performs geometric modeling for the variable cross-section thin-walled reinforcement structure of the annular concrete pole. According to the actual reinforcement scheme of the pole, concrete solid module, ordinary steel bar module, and prestressed steel bar module are established respectively. The element discretization is completed by using a mapping mesh generation method adapted to the annular variable cross-section thin-walled reinforcement structure. The initial mechanical parameters of concrete and various types of steel bars are configured according to the pole's factory inspection report. The initial prestress value is applied to the prestressed steel bars. The boundary constraint conditions of the foundation part are set according to the pole's embedment depth and foundation type. The initial material properties include initial strength parameters of concrete, such as elastic modulus, compressive strength, tensile strength, and Poisson's ratio, as well as initial mechanical parameters of ordinary steel bars and prestressed steel bars, such as yield strength, elastic modulus, and coefficient of linear expansion. The boundary constraints include lateral soil constraints in the foundation burial depth section and vertical displacement constraints at the bottom end, fully restoring the initial mechanical properties of the pole when it was put into operation at the factory.

3. The concrete pole bearing capacity analysis and testing system based on multi-dimensional parameters according to claim 2, characterized in that: The multi-dimensional parameter acquisition module collects structural damage parameters and service environment parameters of the pole, forming a multi-dimensional detection dataset carrying spatial coordinates, including: S11. Divide the pole into multiple inspection sections along its axial direction and conduct non-destructive testing at multiple inspection points on each inspection section. Use the ultrasonic rebound combined method to collect concrete strength data, use the electromagnetic induction method to collect steel corrosion data, and use the image recognition method to collect crack data. S12. Install tilt angle detection devices at the top and middle of the pole to collect the deformation tilt angle data of the pole; S13. Deploy environmental sensing terminals around the utility poles to collect temperature and humidity data and wind load data; S14. After removing outliers and standardizing the format of all collected data, add corresponding spatial coordinates to each group of data to form a multidimensional detection dataset carrying spatial coordinates. The spatial coordinates include the axial height and circumferential angle of the detection point. Each set of data corresponds to a unique spatial position of the pole body, providing reliable position information for the subsequent precise correction of the reference twin model at the unit level.

4. The concrete pole bearing capacity analysis and testing system based on multi-dimensional parameters according to claim 3, characterized in that: The multi-parameter mapping and dynamic model update module maps the multi-dimensional detection dataset to the corresponding mesh elements of the baseline twin model, corrects the material properties, damage structure, and boundary constraints of the baseline twin model, and generates an updated twin model, including: S21. Based on the axial height and circumferential angle carried by each group of data in the multidimensional detection dataset, the data are matched with the grid cells of the benchmark twin model in terms of spatial position. The spatial position matching adopts the nearest neighbor cell matching algorithm to ensure that the data of each detection point is accurately mapped to the grid cell with the nearest spatial distance, thereby eliminating the mapping deviation caused by grid discrepancies. S22. Adjust the initial strength parameters of the concrete in the corresponding area according to the concrete strength data, and adjust the initial mechanical parameters of the steel bars in the corresponding area according to the steel bar corrosion data. S23. Calculate the structural damage factor D of the mesh element based on the crack depth d and crack width w in the crack data: ； Where h0 is the wall thickness of the corresponding rod segment, l e α is the characteristic length of the grid element, and α is the weighting coefficient for the influence of crack damage. It is obtained by combining the bending test of the annular thin-walled concrete member with the calibration of concrete fracture mechanics parameters. Corresponding calibration values ​​are used for the grid elements in the tension zone and the grid elements in the compression zone, respectively. Based on the structural damage factor, a damaged structure is introduced for the corresponding mesh element, and the stiffness matrix of the mesh element is updated. S24. Based on the deformation tilt angle data, correct the boundary constraints of the corresponding area's foundation, complete the dynamic correction of the benchmark twin model, and generate the updated twin model. In the process of revising the benchmark twin model, differentiated damage reduction logic is adopted for the tension zone, compression zone, and neutral axis region of the annular variable cross section, so that the stiffness attenuation law of the model matches the actual bending stress characteristics of the pole, and avoids the evaluation results that are too conservative / dangerous due to the uniform reduction method.

5. The concrete pole bearing capacity analysis and testing system based on multi-dimensional parameters according to claim 4, characterized in that: When the multi-parameter mapping and model dynamic update module corrects the boundary constraints of the foundation in the corresponding region based on the deformation tilt angle data, it adjusts the temperature stress parameters of the concrete and steel bars in the corresponding region based on the temperature and humidity data, adjusts the lateral wind load parameters of the reference twin model in the corresponding region based on the wind load data, and adjusts the stiffness parameters of the foundation based on the foundation depth parameters of the poles in the reference twin model. This is to incorporate the mechanical effects of temperature and humidity data, wind load data, and foundation depth parameters into the correction range of the load conditions and boundary constraints of the reference twin model.

6. The concrete pole bearing capacity analysis and testing system based on multi-dimensional parameters according to claim 4, characterized in that: The multi-condition bearing capacity simulation analysis module performs multi-condition mechanical simulation solutions based on the updated twin model, and outputs the simulation analysis results to the result output and scheme verification module, including: S31. Configure load parameters and constraints for normal service conditions and extreme conditions such as typhoons and icing. The lateral wind load parameters are distributed in a gradient along the pole height and are set according to the wind pressure height variation coefficient in the design code of overhead transmission lines. The icing load parameters are applied to the conductor suspension point of the pole and are calculated based on the conductor icing thickness and the conductor nominal cross-section. S32. Call the finite element solver to perform mechanical simulation and solve the pole structure under various working conditions, and obtain the stress distribution data, deformation displacement data and ultimate bending bearing capacity of the pole. S33. Calculate the bearing capacity safety margin γ corresponding to each working condition: ； Among them, M u M represents the ultimate flexural bearing capacity under the corresponding working conditions. s β is the standard design bending moment value under the corresponding working condition, which is determined according to the ratio of the measured load parameters to the standard design load. Under typhoon conditions, the measured wind load amplitude is combined for correction, and under icing conditions, the equivalent icing load is combined for correction. S34. Locate the weak points in the structure where stress concentration occurs and the load-bearing capacity safety margin is lower than the preset threshold, and output complete simulation analysis results; In the simulation process of the updated twin model, the bending moment distribution, shear force distribution and deflection curve of the entire pole segment are output simultaneously, which can directly locate the pole segment with weak bearing capacity and the location of dangerous section, providing accurate location guidance for subsequent operation and maintenance.

7. The concrete pole bearing capacity analysis and testing system based on multi-dimensional parameters according to claim 6, characterized in that: The multi-condition bearing capacity simulation analysis module calls the finite element solver to perform mechanical simulation solutions on the pole structure under various conditions, obtaining stress distribution data, deformation displacement data, and ultimate bending bearing capacity of the pole, including: The updated twin model was loaded using a progressive incremental loading method, and the changes in concrete strain and steel stress in the tension zone were continuously monitored. The ultimate bearing state was determined based on the structural failure criterion coefficient ψ, which was calculated using the following formula: ； Where, ε c ε is the maximum tensile strain of the concrete in the tension zone. cu The ultimate tensile strain of concrete is determined by the material parameters corresponding to the concrete strength grade, σ. s σ is the maximum tensile stress in the reinforcement of the tension zone. sy The yield strength of the steel reinforcement; When the structural failure judgment coefficient ψ≥1, it is determined that the ultimate bearing state has been reached. The current load value is recorded as the ultimate bending bearing capacity under the corresponding working condition. Under typhoon conditions, the pole top displacement reaches the limit value as a supplementary judgment condition. Under icing conditions, the bending moment at the conductor suspension point reaches the limit value as a supplementary judgment condition. The stress distribution data and deformation displacement data of the pole under the ultimate bending bearing capacity are recorded simultaneously.

8. The concrete pole bearing capacity analysis and testing system based on multi-dimensional parameters according to claim 6, characterized in that: The result output and solution verification module has a built-in visualization display unit and a reinforcement solution verification unit. The visualization unit presents the damage distribution, stress distribution, ultimate bending capacity, and risk level information of the pole in the form of cloud maps and numerical lists. The risk level is divided according to the numerical range of the bearing capacity safety margin. The reinforcement scheme verification unit supports inputting reinforcement parameters, including reinforcement material parameters, reinforcement location parameters, and reinforcement structure parameters. After mapping the reinforcement parameters to the updated twin model, the multi-condition bearing capacity simulation analysis module is called again to perform calculations, and the comparison data of ultimate flexural bearing capacity and bearing capacity safety margin before and after reinforcement are output.

9. A method for analyzing and testing the bearing capacity of concrete poles based on multidimensional parameters, applicable to the multidimensional parameter-based concrete pole bearing capacity analysis and testing system described in claim 1, characterized in that: Includes the following steps: S1. Obtain the design parameters, manufacturing process parameters, and basic constraint parameters of the pole, construct a three-dimensional finite element reference twin model of the pole, and set the initial material properties and boundary constraint conditions; S2. Collect structural damage parameters and service environment parameters of the poles to form a multidimensional detection dataset carrying spatial coordinates; S3. Map the multidimensional detection dataset to the corresponding mesh element of the baseline twin model, correct the material properties, damage structure and boundary constraints of the baseline twin model, and generate the updated twin model. S4. Based on the updated twin model, perform multi-condition mechanical simulation to obtain the stress distribution data, deformation displacement data, ultimate bending bearing capacity of the pole, and the corresponding simulation analysis results. S5. Output the bearing capacity analysis results based on the simulation analysis results, and verify the reinforcement scheme through simulation.

10. The method for analyzing and testing the bearing capacity of concrete poles based on multidimensional parameters according to claim 9, characterized in that: In S4, multi-condition mechanical simulations are performed based on the updated twin model to obtain stress distribution data, deformation and displacement data, ultimate bending capacity, and corresponding simulation analysis results for the pole, including: S41. Configure load parameters and constraints for normal service conditions and extreme conditions such as typhoons and icing. The lateral wind load parameters are distributed in a gradient along the pole height and are set according to the wind pressure height variation coefficient in the design code of overhead transmission lines. The icing load parameters are applied to the conductor suspension point of the pole and are calculated based on the conductor icing thickness and the conductor nominal cross-section. S42. Use the finite element method (FEM) solver to perform mechanical simulation of the pole structure under various working conditions, and obtain the stress distribution data, deformation displacement data, and ultimate bending capacity of the pole. Specifically, this includes: The updated twin model was loaded using a progressive incremental loading method, and the changes in concrete strain and steel stress in the tension zone were continuously monitored. The ultimate bearing state was determined based on the structural failure criterion coefficient ψ, which was calculated using the following formula: ； Where, ε c ε is the maximum tensile strain of the concrete in the tension zone. cu The ultimate tensile strain of concrete is determined by the material parameters corresponding to the concrete strength grade, σ. s σ is the maximum tensile stress in the reinforcement of the tension zone. sy The yield strength of the steel reinforcement; When the structural failure judgment coefficient ψ≥1, it is determined that the ultimate bearing state has been reached. The current load value is recorded as the ultimate bending bearing capacity under the corresponding working condition. Under the typhoon working condition, the pole top displacement reaches the limit value as a supplementary judgment condition. Under the icing working condition, the bending moment at the conductor hanging point reaches the limit value as a supplementary judgment condition. The stress distribution data and deformation displacement data of the pole under the ultimate bending bearing capacity are recorded simultaneously. S43. Calculate the bearing capacity safety margin γ corresponding to each working condition: ； Among them, M u M represents the ultimate flexural bearing capacity under the corresponding working conditions. s β is the standard design bending moment value under the corresponding working condition, which is determined according to the ratio of the measured load parameters to the standard design load. Under typhoon conditions, the measured wind load amplitude is combined for correction, and under icing conditions, the equivalent icing load is combined for correction. S44. Locate the structural weak points where stress concentration occurs and the load-bearing capacity safety margin is lower than the preset threshold, and output complete simulation analysis results; In the simulation process of the updated twin model, the bending moment distribution, shear force distribution and deflection curve of the entire pole segment are output simultaneously, which can directly locate the pole segment with weak bearing capacity and the location of dangerous section, providing accurate location guidance for subsequent operation and maintenance.

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