Overhead line concrete pole wind damage prediction method considering service state change

Abstract

The invention provides an overhead line concrete pole wind damage prediction method considering service state change, which comprises the following steps: firstly, constructing a full life cycle bearing capacity time-varying model of a concrete pole, and dynamically outputting flexural bearing capacity and shear bearing capacity at any service time point; a foundation soil body state response model is established to evaluate the soil body mechanical performance changed due to heavy rainfall, and pole falling risk dynamic judgment is achieved; meanwhile, electric pole geographic coordinates are integrated to construct a distribution network overhead line topology network, and the typhoon period maximum wind load extreme value of each electric pole is output by combining typhoon wind field space-time evolution data, vector superposition wire and pole body wind loads; the failure probability analysis module is used for constructing a resistance-load random coupling vector in the typhoon disaster damage prediction module, quantizing the pole-level failure risk by adopting a failure probability integral algorithm to generate a visual region failure probability map and outputting a line total failure expected value; according to the method, the comprehensive typhoon disaster damage prediction of the overhead line concrete pole network with the pole service time and the foundation soil body state change can be realized.

Description

Technical Field

[0001] This invention relates to the field of typhoon damage prediction and analysis technology for concrete poles of low-voltage overhead power lines in distribution networks, and in particular to a method for predicting typhoon damage to concrete poles of overhead power lines that considers changes in service status. Specifically, it involves predicting typhoon damage to overhead power lines by analyzing the time-varying performance of the pole structure's bearing capacity and the changes in the mechanical properties of the foundation soil at different moisture contents. Background Technology

[0002] Low-voltage power distribution lines are widely installed using concrete poles. These lines are exposed to the natural environment for a long time and are particularly vulnerable to strong wind loads. When typhoons arrive, they are accompanied by strong winds and heavy rain, which often cause regional pole collapses and line breaks, seriously threatening power supply reliability and public safety.

[0003] Carbonation of concrete, cracking of the protective layer, and corrosion of reinforcing steel can all lead to a significant degradation in structural strength with increasing service life. This results in discrepancies between initial resistance assessments and actual load-bearing capacity, making it difficult to accurately reflect the wind resistance risks of aging power lines. On the other hand, existing analytical methods often neglect or simplify the key influences and dynamic changes of foundation soil properties. The stability of the pole foundation is fundamental to the overall wind resistance, and the mechanical properties of foundation soil, especially saturated sand, silt, or soft clay, are easily weakened by factors such as groundwater level fluctuations and rainwater erosion. This weakening is coupled with the degradation of the structure's own performance, further exacerbating the risk of instability of the power line under extreme wind loads.

[0004] Current wind protection measures for overhead power lines lack assessment of changes in the foundation soil condition and the wind resistance of older poles. They often rely on uniform wind speeds for different areas for reinforcement and retrofitting, which makes it difficult to meet the needs of refined operation and maintenance and proactive defense. How to utilize meteorological forecasts to comprehensively analyze the probability of pole structural failure in order to improve the risk management level of low-voltage overhead power distribution networks has become an urgent problem to be solved. Summary of the Invention

[0005] This invention proposes a method for predicting wind damage to overhead line concrete poles that takes into account changes in service status. This method can achieve comprehensive typhoon damage prediction for overhead line concrete pole networks based on changes in pole service time and foundation soil condition.

[0006] The present invention adopts the following technical solution.

[0007] A method for predicting wind damage to concrete poles for overhead power lines, considering changes in service status, is proposed for typhoon damage prediction. The method first constructs a time-varying model of the full life-cycle bearing capacity of the concrete poles to comprehensively quantify the steel corrosion process (including the years of rust initiation, rust expansion and cracking, and corrosion rate), material strength degradation, deterioration of bond-slip performance between steel and concrete, and concrete cover detachment. It dynamically outputs the flexural and shear bearing capacities at any service time point. Secondly, a soil state response model is established to assess the changes in soil mechanical properties caused by erosion and flooding around the pole foundation due to heavy rainfall. This model is based on the elastic modulus, expansion angle, and other parameters of the soil at different moisture contents. By analyzing changes in internal friction angle, cohesion, and unit weight parameters, a quantitative expression for the horizontal load-displacement of concrete poles under different rainfall amounts is obtained, enabling dynamic assessment of pole collapse risk. Simultaneously, the geographical coordinates of the poles are integrated to construct a distribution network overhead line topology, accurately recording the conductor connection relationships of individual poles, the distribution of neighboring nodes, and span parameters. Furthermore, by combining typhoon wind field spatiotemporal evolution data, the wind loads of the conductors and poles are vector-superimposed to output the maximum wind load extreme value for each pole during the typhoon season. This is used to construct a resistance-load stochastic coupling vector in the typhoon disaster damage prediction module, employing a failure probability integral algorithm to quantify pole-level failure risk, generating a visualized regional failure probability map, and outputting the expected value of the total line failure.

[0008] The prediction method includes the following steps; such as Figure 1 As shown, Step S1: Establish a time-varying model module for the bearing capacity of concrete poles, which is used to calculate the bending and shear bearing capacity of any section of the concrete pole under different service times; Step S2: Establish a quantitative characterization module for soil load displacement under different soil moisture contents to determine the risk of concrete poles collapsing under wind load. Step S3: Establish a recording and characterization module for the connection status of overhead lines, which is used to connect the pole coordinate information into a power distribution network and record the connection information of all conductors on each pole; Step S4: Establish a typhoon wind field model module to record the maximum wind load on each pole of the regional power distribution network; Step S5: Use the pole failure probability calculation module to predict typhoon damage to overhead power lines in the typhoon-affected area.

[0009] like Figure 2 As shown, step S1 includes the following steps; Step S101: Calculate steel reinforcement corrosion; Step S102: Calculate the strength degradation of the reinforcing steel; Step S103: Calculate concrete strength degradation; Step S104: Calculate the degradation of bond-slip properties in reinforced concrete; Step S105: Calculate the damage to the concrete geometric section; Step S106: Calculate the bending and shear bearing capacity of the pole.

[0010] In step S101, the atmospheric environment where the pole is located is described using a corrosion model as follows: In the formula This refers to the number of years it takes for the reinforcing steel to rust. The critical corrosion depth for protective layer cracking; c The thickness of the protective layer; k The carbonization coefficient; For coefficients, when c Less than 28mm, and k When it is greater than 0.8, ; The coefficient representing the influence of carbon dioxide concentration; To consider the positional influence coefficients of the corner and non-corner areas of the components; This is the influence coefficient of the casting surface; To account for the influence coefficient of stress state; The coefficient representing the effect of fly ash replacement amount on carbonization; T The ambient temperature; RH The relative humidity of the environment; This is an estimated value for the compressive strength of concrete. The durability of the concrete protective layer under this atmospheric environment is calculated as follows: The specific corrosion model under marine atmospheric conditions is as follows: ; The durability of the protective coating against rust expansion and cracking under marine atmospheric conditions is as follows: .

[0011] In step S102, the strength degradation of the reinforcing steel is calculated using a time-varying corrosion rate model, specifically as follows: The formula for calculating the strength of corroded steel bars is as follows: ; In step S103, the concrete strength degradation is calculated as follows: The average and standard deviation of concrete strength.

[0012] In step S104, the formula for calculating the degradation of bond-slip properties of reinforced concrete is as follows: Bond stress at the interface of uncorroded reinforced concrete; In step S105, the damage calculation for the concrete geometric section is as follows: Width of soil rust expansion cracks.

[0013] In step S106, the calculation model for the bending bearing capacity of the pole is expressed by the following formula: The ratio factor of height; The calculation model for the shear bearing capacity of utility poles is expressed by the following formula: The angle between the hoop and the axial direction of the component.

[0014] Figure 6 The diagram illustrates the change in the bearing capacity of concrete poles over time according to an embodiment of the present invention. It should be noted that the calculation needs to be repeated until the service time of all poles in the region is covered. Ultimately, the bearing capacity values ​​of different types of poles at different service times will be obtained, and these values ​​will be stored as resistance reference values ​​for subsequent reliability calculations.

[0015] like Figure 3 As shown, step S2 specifically includes the following steps: Step S201: Obtain soil parameters of the environment where the pole to be tested is located; Step S202: Construct a finite element simulation model of the pole-soil interaction; Step S203: Extract the soil load-displacement curve and obtain the corresponding quantitative expression based on the model; determine whether the pole has collapsed by using the pole tilt limit value. The pole tilt is characterized by the displacement of the foundation soil surface, and then the external load when pole collapse occurs is obtained based on the expression. Step S204: Repeat S201, S202, and S203 until all possible soil states under the current typhoon conditions have been traversed. After completing the calculations for all soil moisture states, record the quantitative expression model of load displacement under all states. The simulation software used for the finite element model of the pole-soil interaction includes ABAQUS software; Based on the load-displacement data of the soil-pole interaction, a quantitative expression model is obtained, which is expressed as follows: .

[0016] Figure 7 This paper illustrates a line graph showing the load-displacement of concrete pole bases under different soil moisture contents in one embodiment of the present invention. It should be noted that the calculation needs to be repeated until all possible soil moisture contents under the current typhoon conditions are covered. Ultimately, the external load values ​​corresponding to the collapse of different types of poles under different soil moisture contents will be obtained, and these values ​​will be stored as resistance reference values ​​for subsequent reliability calculations.

[0017] like Figure 4 As shown, the method of step S3 specifically includes: collecting pole coordinate data and using an algorithm to connect the coordinates into a power distribution network, and recording the connection information of all poles, specifically including span (distance between nodes), turning angle (turning angle from node to the next connection point), and direction (direction of the conductor); like Figure 5 As shown, step S4 includes a typhoon wind field calculation module, which calculates and records the maximum wind load and conductor tension on each pole of the regional distribution network at all times based on the connection information in step S3; specifically: In the typhoon wind field calculation module, the typhoon parameters forecast by the meteorological department are input, and the downwind speed and wind direction values ​​of the current area are output. The typhoon parameters include the pressure difference at the typhoon center, the speed of movement of the typhoon center, the angle between the direction of movement of the typhoon center at the time of landfall and the coastline where the landfall point is located, and the latitude and longitude of the typhoon.

[0018] The wind load calculation process is executed by the wind load calculation module, which introduces the amplification effect of fluctuating wind load on the structural response compared to static wind load. This step verifies the accuracy of typhoon wind field simulation by comparing the wind speed power spectrum and the power spectrum of the simulated point in the pulsating wind simulation module, and uses the ratio of the maximum wind vibration response to the average response to reflect the amplification effect. The calculation for static wind load on the pole and conductor is as follows: .

[0019] Figure 8 The diagram illustrates wind speed and direction variations in a simulated typhoon wind field region according to an embodiment of the present invention. It should be noted that the typhoon wind field model can obtain wind speed and direction values ​​for all times when typhoon data is recorded in a given region. Furthermore, the amplification effect of fluctuating wind loads relative to static wind loads on the structural response must be considered. In the fluctuating wind simulation module, the wind speed power spectrum and the power spectrum of the simulated points need to be compared to demonstrate the accuracy of the simulation. The ratio of the maximum wind-induced vibration response to the average response is used to reflect the amplification effect.

[0020] Step S5 includes using the structural failure probability calculation module. In this module, the failure probability is the volume integral of the joint probability density function over the region enclosed by the failure hypersurface, using a random vector. Characterizes the coupling effect between material property variation and load randomness.

[0021] The specific formula for calculating the failure probability is as follows: , In the formula g(X) It is the limit state function. f X (X) It is a vector of random variables X The joint probability density function; The installation and fixing methods for the overhead line concrete poles include direct burial and foundation installation. In this step, the expected failure values ​​of all power poles in the region are statistically analyzed and visualized according to the constructed connection network to obtain the predicted typhoon damage data for overhead lines in that region. Please refer to... Figure 9 This image shows a partial visualization of the failure of a concrete pole connection network according to an embodiment of the present invention. It should be noted that random vectors are used in the pole failure analysis. X=(R,S) In this context, R represents the flexural and shear bearing capacities calculated in step S1. In the pole collapse analysis, the soil displacement limit for determining pole collapse is specified, and a random vector is used. X=(R,S) middle R This refers to the external load value corresponding to the pole collapse displacement limit calculated in step S2. In the analysis of broken pole failure and collapsed pole failure, the random vector... X=(R,S) middle S All of these are the amplified values ​​of the pulsating wind load corresponding to the maximum external load recorded in step S4.

[0022] The forecasting method defines the loads borne by the concrete poles of overhead power lines during their service life as including both static and dynamic loads, in order to focus on disaster damage forecasting under typhoon-dominated conditions. Static loads include the pole's own weight, the permanent weight of the conductors and fittings, Dynamic loads include conductor wind load, pole wind load, and conductor tension, but do not consider icing load, seismic load, or other temporary loads.

[0023] By sequentially performing steps S1, S2, S3, S4, and S5, an assessment of the failure probability of concrete poles under wind load in different states (including different service times, different atmospheric environments, and different soil moisture contents) can be obtained, thereby helping engineers to perform refined operation and maintenance and proactive defense.

[0024] Compared to existing assessment and analysis methods, the advantages of this invention lie in its ability to effectively assess changes in the foundation soil condition due to heavy rain and the varying wind resistance of old power poles under different environments. Based on meteorological forecasts before typhoons, this invention enables rapid analysis of the risk of typhoon failure of power pole structures in the current region and can accurately calculate the failure status of each pole. Different operating conditions can be precisely set according to the service time of the current power poles and changes in the current soil condition, effectively predicting typhoon damage for the failure of distribution network lines after typhoons in different regions, and improving the risk management level of low-voltage overhead distribution lines. Attached Figure Description

[0025] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments: Appendix Figure 1 This is a schematic diagram of the analysis process for the wind damage prediction method of concrete poles for overhead power lines in the distribution network in this embodiment of the invention. Appendix Figure 2 This is a schematic diagram of the implementation process of step S1 in an embodiment of the present invention; Appendix Figure 3 This is a schematic diagram of the implementation process of step S2 in an embodiment of the present invention; Appendix Figure 4 This is a schematic diagram of the implementation process of step S3 in an embodiment of the present invention; Appendix Figure 5 This is a schematic diagram of the implementation process of step S4 in an embodiment of the present invention; Appendix Figure 6 This is a schematic diagram illustrating the time-dependent changes in the bearing capacity of concrete poles and the bending-shear competition in an embodiment of the present invention. Appendix Figure 7 This is a schematic diagram of the load displacement of the concrete pole base under different moisture content states of the foundation soil in an embodiment of the present invention; Appendix Figure 8 This is a schematic diagram of wind speed and direction changes in a typhoon wind field simulation area in an embodiment of the present invention; Appendix Figure 9This is a partial schematic diagram of the failure of the concrete pole connection network in an embodiment of the present invention. Detailed Implementation

[0026] As shown in the figure, a wind damage prediction method for overhead power line concrete poles considering changes in service status is presented for typhoon damage prediction. The method first constructs a time-varying model of the concrete pole's full life-cycle bearing capacity to comprehensively quantify the steel corrosion process (including the number of years since rust initiation, the number of years since rust expansion and cracking, and the corrosion rate), material strength degradation, deterioration of the bond-slip performance between steel and concrete, and concrete cover detachment. It dynamically outputs the flexural and shear bearing capacities at any service time point. Secondly, a soil state response model is established to assess the changes in soil mechanical properties caused by erosion and flooding around the pole foundation due to heavy rainfall. This model is based on the elastic modulus and expansion coefficient of soil at different moisture contents. By analyzing changes in expansion angle, internal friction angle, cohesion, and unit weight parameters, a quantitative expression for the horizontal load-displacement of concrete poles under different rainfall amounts is obtained, enabling dynamic assessment of pole collapse risk. Simultaneously, the geographical coordinates of the poles are integrated to construct a distribution network overhead line topology, accurately recording the conductor connection relationships of individual poles, the distribution of neighboring nodes, and span parameters. Furthermore, by combining typhoon wind field spatiotemporal evolution data, the wind loads of the conductors and poles are vector-superimposed to output the maximum wind load extreme value for each pole during the typhoon season. This is used to construct a resistance-load stochastic coupling vector in the typhoon disaster damage prediction module, employing a failure probability integral algorithm to quantify pole-level failure risk, generating a visualized regional failure probability map, and outputting the expected value of the total line failure.

[0027] The prediction method includes the following steps; such as Figure 1 As shown, Step S1: Establish a time-varying model module for the bearing capacity of concrete poles, which is used to calculate the bending and shear bearing capacity of any section of the concrete pole under different service times; Step S2: Establish a quantitative characterization module for soil load displacement under different soil moisture contents to determine the risk of concrete poles collapsing under wind load. Step S3: Establish a recording and characterization module for the connection status of overhead lines, which is used to connect the pole coordinate information into a power distribution network and record the connection information of all conductors on each pole; Step S4: Establish a typhoon wind field model module to record the maximum wind load on each pole of the regional power distribution network; Step S5: Use the pole failure probability calculation module to predict typhoon damage to overhead power lines in the typhoon-affected area.

[0028] like Figure 2 As shown, step S1 includes the following steps; Step S101: Calculate steel reinforcement corrosion; Step S102: Calculate the strength degradation of the reinforcing steel; Step S103: Calculate concrete strength degradation; Step S104: Calculate the degradation of bond-slip properties in reinforced concrete; Step S105: Calculate the damage to the concrete geometric section; Step S106: Calculate the bending and shear bearing capacity of the pole.

[0029] In step S101, the atmospheric environment where the pole is located is described using a corrosion model as follows: In the formula This refers to the number of years it takes for the reinforcing steel to rust. The critical corrosion depth for protective layer cracking; c The thickness of the protective layer; k The carbonization coefficient; For coefficients, when c Less than 28mm, and k When it is greater than 0.8, ; The coefficient representing the influence of carbon dioxide concentration; To consider the positional influence coefficients of the corner and non-corner areas of the components; This is the influence coefficient of the casting surface; To account for the influence coefficient of stress state; The coefficient representing the effect of fly ash replacement amount on carbonization; T The ambient temperature; RH The relative humidity of the environment; This is an estimated value for the compressive strength of concrete. The durability of the concrete protective layer under this atmospheric environment is calculated as follows: The specific corrosion model under marine atmospheric conditions is as follows: ; The durability of the protective coating against rust expansion and cracking under marine atmospheric conditions is as follows: .

[0030] In step S102, the strength degradation of the reinforcing steel is calculated using a time-varying corrosion rate model, specifically as follows: The formula for calculating the strength of corroded steel bars is as follows: ; In step S103, the concrete strength degradation is calculated as follows: The average and standard deviation of concrete strength.

[0031] In step S104, the formula for calculating the degradation of bond-slip properties of reinforced concrete is as follows: Bond stress at the interface of uncorroded reinforced concrete; In step S105, the damage calculation for the concrete geometric section is as follows: Width of soil rust expansion cracks.

[0032] In step S106, the calculation model for the bending bearing capacity of the pole is expressed by the following formula: The ratio factor of height; The calculation model for the shear bearing capacity of utility poles is expressed by the following formula: The angle between the hoop and the axial direction of the component.

[0033] Figure 6 The diagram illustrates the change in the bearing capacity of concrete poles over time according to an embodiment of the present invention. It should be noted that the calculation needs to be repeated until the service time of all poles in the region is covered. Ultimately, the bearing capacity values ​​of different types of poles at different service times will be obtained, and these values ​​will be stored as resistance reference values ​​for subsequent reliability calculations.

[0034] like Figure 3 As shown, step S2 specifically includes the following steps: Step S201: Obtain soil parameters of the environment where the pole to be tested is located; Step S202: Construct a finite element simulation model of the pole-soil interaction; Step S203: Extract the soil load-displacement curve and obtain the corresponding quantitative expression based on the model; determine whether the pole has collapsed by using the pole tilt limit value. The pole tilt is characterized by the displacement of the foundation soil surface, and then the external load when pole collapse occurs is obtained based on the expression. Step S204: Repeat S201, S202, and S203 until all possible soil states under the current typhoon conditions have been traversed. After completing the calculations for all soil moisture states, record the quantitative expression model of load displacement under all states. The simulation software used for the finite element model of the pole-soil interaction includes ABAQUS software; Based on the load-displacement data of the soil-pole interaction, a quantitative expression model is obtained, which is expressed as follows: .

[0035] Figure 7 This paper illustrates a line graph showing the load-displacement of concrete pole bases under different soil moisture contents in one embodiment of the present invention. It should be noted that the calculation needs to be repeated until all possible soil moisture contents under the current typhoon conditions are covered. Ultimately, the external load values ​​corresponding to the collapse of different types of poles under different soil moisture contents will be obtained, and these values ​​will be stored as resistance reference values ​​for subsequent reliability calculations.

[0036] like Figure 4 As shown, the method of step S3 specifically includes: collecting pole coordinate data and using an algorithm to connect the coordinates into a power distribution network, and recording the connection information of all poles, specifically including span (distance between nodes), turning angle (turning angle from node to the next connection point), and direction (direction of the conductor); like Figure 5 As shown, step S4 includes a typhoon wind field calculation module, which calculates and records the maximum wind load and conductor tension on each pole of the regional distribution network at all times based on the connection information in step S3; specifically: In the typhoon wind field calculation module, the typhoon parameters forecast by the meteorological department are input, and the downwind speed and wind direction values ​​of the current area are output. The typhoon parameters include the pressure difference at the typhoon center, the speed of movement of the typhoon center, the angle between the direction of movement of the typhoon center at the time of landfall and the coastline where the landfall point is located, and the latitude and longitude of the typhoon.

[0037] The wind load calculation process is executed by the wind load calculation module, which introduces the amplification effect of fluctuating wind load on the structural response compared to static wind load. This step verifies the accuracy of typhoon wind field simulation by comparing the wind speed power spectrum and the power spectrum of the simulated point in the pulsating wind simulation module, and uses the ratio of the maximum wind vibration response to the average response to reflect the amplification effect. The calculation for static wind load on the pole and conductor is as follows: .

[0038] Figure 8 The diagram illustrates wind speed and direction variations in a simulated typhoon wind field region according to an embodiment of the present invention. It should be noted that the typhoon wind field model can obtain wind speed and direction values ​​for all times when typhoon data is recorded in a given region. Furthermore, the amplification effect of fluctuating wind loads relative to static wind loads on the structural response must be considered. In the fluctuating wind simulation module, the wind speed power spectrum and the power spectrum of the simulated points need to be compared to demonstrate the accuracy of the simulation. The ratio of the maximum wind-induced vibration response to the average response is used to reflect the amplification effect.

[0039] Step S5 includes using the structural failure probability calculation module. In this module, the failure probability is the volume integral of the joint probability density function over the region enclosed by the failure hypersurface, using a random vector. Characterizes the coupling effect between material property variation and load randomness.

[0040] The specific formula for calculating the failure probability is as follows: , In the formula g(X) It is the limit state function. f X (X) It is a vector of random variables X The joint probability density function; The installation and fixing methods for the overhead line concrete poles include direct burial and foundation installation. In this step, the expected failure values ​​of all power poles in the region are statistically analyzed and visualized according to the constructed connection network to obtain the predicted typhoon damage data for overhead lines in that region. Please refer to... Figure 9 This image shows a partial visualization of the failure of a concrete pole connection network according to an embodiment of the present invention. It should be noted that random vectors are used in the pole failure analysis. X=(R,S) In this context, R represents the flexural and shear bearing capacities calculated in step S1. In the pole collapse analysis, the soil displacement limit for determining pole collapse is specified, and a random vector is used. X=(R,S) middle R This refers to the external load value corresponding to the pole collapse displacement limit calculated in step S2. In the analysis of broken pole failure and collapsed pole failure, the random vector... X=(R,S) middle S All of these are the amplified values ​​of the pulsating wind load corresponding to the maximum external load recorded in step S4.

[0041] The forecasting method defines the loads borne by the concrete poles of overhead power lines during their service life as including both static and dynamic loads, in order to focus on disaster damage forecasting under typhoon-dominated conditions. Static loads include the pole's own weight, the permanent weight of the conductors and fittings, Dynamic loads include conductor wind load, pole wind load, and conductor tension, but do not consider icing load, seismic load, or other temporary loads.

[0042] By sequentially performing steps S1, S2, S3, S4, and S5, an assessment of the failure probability of concrete poles under wind load in different states (including different service times, different atmospheric environments, and different soil moisture contents) can be obtained, thereby helping engineers to perform refined operation and maintenance and proactive defense.

Claims

1. A method for predicting wind damage to concrete poles of overhead power lines considering changes in service status, used for typhoon damage prediction, characterized by: The method first constructs a time-varying model of the full life-cycle bearing capacity of concrete poles to comprehensively quantify the steel corrosion process, material strength degradation, deterioration of bond-slip performance between steel and concrete, and concrete cover detachment, dynamically outputting the flexural and shear bearing capacities at any service time point. Secondly, a soil state response model is established to assess the changes in soil mechanical properties caused by heavy rainfall. Based on the changes in elastic modulus, expansion angle, internal friction angle, cohesion, and unit weight parameters of soil at different moisture contents, a quantitative expression for the horizontal load-displacement of concrete poles under different rainfall amounts is obtained, enabling dynamic judgment of pole collapse risk. Simultaneously, the method integrates the geographical coordinates of the poles to construct a distribution network overhead line topology, combines typhoon wind field spatiotemporal evolution data, and vectorically superimposes the wind loads on the conductors and poles to output the maximum wind load extreme value for each pole during the typhoon period. This value is used to construct a resistance-load random coupling vector in the typhoon disaster prediction module, and a failure probability integral algorithm is used to quantify the pole-level failure risk.

2. The method for predicting wind damage to concrete poles for overhead power lines considering changes in service status as described in claim 1, characterized in that: Includes the following steps; Step S1: Establish a time-varying model module for the bearing capacity of concrete poles, which is used to calculate the bending and shear bearing capacity of any section of the concrete pole under different service times; Step S2: Establish a quantitative characterization module for soil load displacement under different soil moisture contents to determine the risk of concrete poles collapsing under wind load. Step S3: Establish a recording and characterization module for the connection status of overhead lines, which is used to connect the pole coordinate information into a power distribution network and record the connection information of all conductors on each pole; Step S4: Establish a typhoon wind field model module to record the maximum wind load on each pole of the regional power distribution network; Step S5: Use the pole failure probability calculation module to predict typhoon damage to overhead power lines in the typhoon-affected area.

3. The method for predicting wind damage to concrete poles for overhead power lines considering changes in service status as described in claim 1, characterized in that: Step S1 includes the following steps; Step S101: Calculate steel reinforcement corrosion; Step S102: Calculate the strength degradation of the reinforcing steel; Step S103: Calculate concrete strength degradation; Step S104: Calculate the degradation of bond-slip properties in reinforced concrete; Step S105: Calculate the damage to the concrete geometric section; Step S106: Calculate the bending and shear bearing capacity of the pole.

4. The method for predicting wind damage to concrete poles for overhead power lines considering changes in service status as described in claim 3, characterized in that: In step S101, the atmospheric environment where the pole is located is described using a corrosion model as follows: In the formula This refers to the number of years it takes for the reinforcing steel to rust. The critical corrosion depth for protective layer expansion and cracking; c The thickness of the protective layer; k The carbonization coefficient; For coefficients, when c Less than 28mm, and k When it is greater than 0.8, ; The coefficient representing the influence of carbon dioxide concentration; To consider the positional influence coefficients of the corner and non-corner areas of the components; This is the influence coefficient of the casting surface; To account for the influence coefficient of stress state; The coefficient representing the effect of fly ash replacement amount on carbonization; T Ambient temperature; RH The relative humidity of the environment; This is an estimated value for the compressive strength of concrete. The durability of the concrete protective layer under this atmospheric environment is calculated as follows: The specific corrosion model under marine atmospheric conditions is as follows: ； The durability of the protective coating against rust expansion and cracking under marine atmospheric conditions is as follows: 。 5. The method for predicting wind damage to concrete poles for overhead power lines considering changes in service status as described in claim 4, characterized in that: In step S102, the strength degradation of the reinforcing steel is calculated using a time-varying corrosion rate model, specifically as follows: The formula for calculating the strength of corroded steel bars is as follows: ； In step S103, the concrete strength degradation is calculated as follows: The average and standard deviation of concrete strength.

6. The method for predicting wind damage to concrete poles for overhead power lines considering changes in service status as described in claim 5, characterized in that: In step S104, the formula for calculating the degradation of bond-slip properties of reinforced concrete is as follows: Bond stress at the interface of uncorroded reinforced concrete; In step S105, the damage calculation for the concrete geometric section is as follows: Width of soil rust expansion cracks.

7. The method for predicting wind damage to concrete poles for overhead power lines considering changes in service status as described in claim 6, characterized in that: In step S106, the calculation model for the bending bearing capacity of the pole is expressed by the following formula: The ratio factor of height; The calculation model for the shear bearing capacity of utility poles is expressed by the following formula: The angle between the hoop and the axial direction of the component.

8. The method for predicting wind damage to concrete poles for overhead power lines considering changes in service status as described in claim 3, characterized in that: Step S2 specifically includes the following steps: Step S201: Obtain soil parameters of the environment where the pole to be tested is located; Step S202: Construct a finite element simulation model of the pole-soil interaction; Step S203: Extract the soil load-displacement curve and obtain the corresponding quantitative expression based on the model; determine whether the pole has collapsed by using the pole tilt limit value. The pole tilt is characterized by the displacement of the foundation soil surface, and then the external load when pole collapse occurs is obtained based on the expression. Step S204: Repeat S201, S202, and S203 until all possible soil states under the current typhoon conditions have been traversed. After completing the calculations for all soil moisture states, record the quantitative expression model of load displacement under all states. The simulation software used for the finite element model of the pole-soil interaction includes ABAQUS software; Based on the load-displacement data of the soil-pole interaction, a quantitative expression model is obtained, which is expressed as follows: 。 9. The method for predicting wind damage to concrete poles for overhead power lines considering changes in service status as described in claim 3, characterized in that: The method in step S3 specifically includes: collecting pole coordinate data and using an algorithm to connect the coordinates into a power distribution network, and recording the connection information of all poles, specifically including span, angle, and direction; Step S4 includes a typhoon wind field calculation module, which calculates and records the maximum wind load and conductor tension on each pole of the regional distribution network at all times based on the connection information in step S3; specifically: In the typhoon wind field calculation module, the typhoon parameters forecast by the meteorological department are input, and the downwind speed and wind direction values ​​of the current area are output. The typhoon parameters include the pressure difference at the typhoon center, the speed of movement of the typhoon center, the angle between the direction of movement of the typhoon center at the time of landfall and the coastline where the landfall point is located, and the latitude and longitude of the typhoon. The wind load calculation process is executed by the wind load calculation module, which introduces the amplification effect of fluctuating wind load on the structural response compared to static wind load. This step verifies the accuracy of typhoon wind field simulation by comparing the wind speed power spectrum and the power spectrum of the simulated point in the pulsating wind simulation module, and uses the ratio of the maximum wind vibration response to the average response to reflect the amplification effect. The calculation for static wind load on the pole and conductor is as follows: 。 10. The method for predicting wind damage to concrete poles for overhead power lines considering changes in service status as described in claim 9, characterized in that: Step S5 includes using the structural failure probability calculation module. In this module, the failure probability is the volume integral of the joint probability density function over the region enclosed by the failure hypersurface, using a random vector. Characterizing the coupling effect between material property variation and load randomness; The specific calculation formula is as follows: In the formula g(X) It is the limit state function. f X (X) It is a vector of random variables X The joint probability density function; The installation and fixing methods for the overhead line concrete poles include direct burial and foundation installation. The forecasting method defines the loads borne by the concrete poles of overhead power lines during their service life as including both static and dynamic loads, in order to focus on disaster damage forecasting under typhoon-dominated conditions. Static loads include the pole's own weight, the permanent weight of the conductors and fittings, Dynamic loads include conductor wind load, pole wind load, and conductor tension, but do not consider icing load, seismic load, or other temporary loads.

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