A method for evaluating the vulnerability of transmission towers to near-fault earthquakes considering environmental erosion

Abstract

The present invention discloses a method for evaluating the vulnerability of transmission towers to near-fault earthquakes, taking environmental erosion into account. The method calculates the corrosion rate of the transmission tower by obtaining atmospheric environmental parameters of the transmission tower, then applies a galvanized coating to the surface of the transmission tower. The corrosion depth of the transmission tower is calculated based on the corrosion rate of the transmission tower. After determining the effective protective life of the galvanized coating, a BP neural network is constructed and trained. A tower-pile-soil-line-time coupled finite element model is then established. The near-field vibration synthesized by the BP neural network is applied to the tower-pile-soil-line-time coupled finite element model to simulate the vulnerability surface of the transmission tower under the combined effects of near-fault earthquakes and atmospheric environmental erosion. Multiple vulnerability surfaces are simulated by changing the model parameters multiple times, and a transmission line damage resistance evaluation formula is established after multi-parameter regression analysis. The present invention enables rapid evaluation of the damage resistance of transmission towers throughout their life cycle, which is beneficial for ensuring the operation and maintenance of transmission towers and has broad application prospects.

Description

Technical Field

[0001] The present invention relates to the technical field of disaster prevention and mitigation and operation and maintenance safety assessment for power transmission and transformation projects, and in particular to a method for assessing the vulnerability of power transmission towers to near-fault earthquakes taking environmental erosion into consideration. Background Art

[0002] Due to the complex nature of climate and topography, transmission lines are inevitably subject to various hazards throughout their lifecycles, including environmental corrosion and earthquakes. When the atmosphere is humid and corrosive gases are present, transmission tower components inevitably corrode. Furthermore, based on past strong earthquakes, it's common for transmission structures to be damaged or even collapse in the face of earthquakes. This is especially true when transmission lines cross or are near active faults, which are more susceptible to more severe seismic responses than those caused by far-field vibrations.

[0003] As transmission lines age, the mechanical properties of transmission tower poles deteriorate due to environmental corrosion, leading to degradation of the overall performance of the tower structure. This reduces the tower's ability to withstand near-site vibrations, posing a serious safety hazard. Therefore, accurately assessing the tower's resistance to near-site vibrations under environmental corrosion over its entire lifecycle is crucial for improving the accuracy of power transmission and transformation project operations and ensuring the safety of transmission and transformation lines. This is of great social significance.

[0004] There have been many studies on the structural performance evaluation of transmission towers in the existing technology, but there are few studies on the performance of transmission towers under near-field vibration in corrosive environments. In addition, the current research on transmission tower corrosion lacks the support of measured data. In the numerical calculation of the seismic response of transmission tower structures, most of the modeling analysis is for a single tower, and the influence of piles, soil, tower, ground wire and material properties around the transmission tower structure is rarely considered. The parameter impact analysis involved is relatively small, and it is impossible to provide fast and accurate information support for transmission tower operation and maintenance. Summary of the Invention

[0005] The present invention aims to address the deficiencies of the prior art and proposes a method for evaluating the vulnerability of transmission towers to near-fault earthquakes taking into account environmental erosion, thereby enabling a rapid assessment of the damage resistance of transmission towers throughout their life cycle.

[0006] The present invention adopts the following technical solutions:

[0007] A method for evaluating the seismic vulnerability of a transmission tower near a fault considering environmental erosion comprises the following steps:

[0008] Step 1: Obtain atmospheric environmental parameters near the transmission tower, determine the comprehensive atmospheric environmental corrosion factor, and calculate the corrosion rate of the transmission tower;

[0009] Step 2: applying a galvanized coating to the surface of the transmission tower components. After the galvanized coating on the surface of the transmission tower components is completely corroded, the corrosion depth of the steel used in the transmission tower components is calculated based on the corrosion rate of the transmission tower to determine the effective protection life of the galvanized coating.

[0010] Step 3: construct a BP neural network, train the BP neural network to synthesize near-field ground motion, and use the trained BP neural network to synthesize the ground motion at any location in the space where the transmission tower is located;

[0011] Step 4: Based on the actual structure of the transmission tower, a finite element analysis model of the transmission tower structure is established using finite element analysis software. The influence of atmospheric erosion on the performance of the transmission tower poles during the entire life cycle of the transmission tower is considered, and a tower-pile-soil-line-time coupled finite element model is established;

[0012] Step 5: Use the trained BP neural network to synthesize seismic waves, apply the synthesized seismic motion to the tower-pile-soil-line-time coupled finite element model, and simulate the vulnerability surface of the transmission tower under the combined effects of near-fault earthquakes and atmospheric erosion.

[0013] Step 6: sequentially change the model parameters of the tower-pile-soil-line-time coupled finite element model, and use the updated tower-pile-soil-line-time coupled finite element model to simulate and obtain the vulnerability surfaces of the transmission tower under the combined effects of multiple near-fault earthquakes and atmospheric erosion, thereby forming a near-field dynamic-atmospheric environment vulnerability surface database. By performing multi-parameter regression analysis on all the transmission tower vulnerability surfaces in the near-field dynamic-atmospheric environment vulnerability surface database, a formula for evaluating the damage resistance performance of the transmission line under the combined effects of the near-field dynamic-atmospheric environment is established, and the transmission line performance evaluation formula is used to quickly evaluate the damage resistance performance of the transmission line under the combined effects of the near-field dynamic-atmospheric environment.

[0014] Preferably, the step 1 specifically includes the following steps:

[0015] Step 1.1: Obtain atmospheric environmental parameters near the transmission tower, including temperature, humidity, sulfur dioxide concentration, chloride ion concentration, and nitrogen dioxide concentration. Determine the annual sunshine duration, annual average temperature, annual average humidity, annual rainfall, annual number of rainy days, and the duration of time with humidity greater than 0.8 in a year. Calculate the wetting factor f1, erosion factor f2, and rainwater acidity factor f3.

[0016] The calculation formula of the wet factor f1 is:

[0017]

[0018] Where f1 is the humidity factor, D1 is the duration of humidity greater than 0.8 in a year, H1 is the annual sunshine duration, is the annual mean temperature;

[0019] The calculation formula of the erosion factor f2 is:

[0020]

[0021] Where f2 is the erosion factor, is the sulfur dioxide concentration, is the chloride ion concentration, is the nitrogen dioxide concentration;

[0022] The calculation formula of the rainwater acidity factor f3 is:

[0023]

[0024] Where f3 is, L is the annual rainfall, D2 is the number of rainy days per year, and PH is the pH value of rainfall.

[0025] Step 1.2: Determine the comprehensive atmospheric corrosion factor based on the wetting factor f1, the erosion factor f2, and the rainwater acidity factor f3, as shown in formula (4):

[0026] N=f1+f2+f3 (4)

[0027] Where N is the comprehensive corrosion factor of atmospheric environment;

[0028] In step 1.3, the corrosion rate of the transmission tower is calculated based on the comprehensive atmospheric corrosion factor and the first-year corrosion rate of the transmission tower steel structure, as shown in formula (5):

[0029] R=A lg N+B (5)

[0030] Where R is the corrosion rate of the transmission tower, in μm / a; A and B are fitting coefficients.

[0031] Preferably, the step 2 specifically includes the following steps:

[0032] Step 2.1: Apply a galvanized coating to the surface of the transmission tower components in accordance with GB / T 13912-2020, “Technical Requirements and Test Methods for Hot-Dip Galvanizing of Metal-Coated Steel Parts.”

[0033] Step 2.2: After the galvanized coating on the surface of the transmission tower component is completely corroded, the corrosion depth of the steel used in the transmission tower component is calculated based on the corrosion rate of the transmission tower;

[0034] When the corrosion rate of the transmission tower is R=50~80μm / a, the corrosion depth of the steel used in the transmission tower components is:

[0035]

[0036] When the corrosion rate of the transmission tower is R=80~200μm / a, the corrosion depth of the steel used in the transmission tower components is:

[0037]

[0038] When the corrosion rate of the transmission tower is R = 200 ~ 700μm / a, the corrosion depth of the steel used in the transmission tower components is:

[0039]

[0040] Where t is the exposure period, in units of a, and is the difference between the service life of the transmission tower and the effective protection period of the galvanized coating;

[0041] Step 2.3, using the relationship between the corrosion depth of the steel used in the transmission tower components and the years of exposure, determine the effective protection life of the galvanized coating based on the corrosion depth of the steel used in the transmission tower components.

[0042] Preferably, in step 2.1, when the thickness of the steel selected for the transmission tower component is greater than 6 mm, the average thickness of the galvanized layer is set to 85 μm; when the thickness of the steel selected for the transmission tower component is greater than 3 mm and not more than 6 mm, the average thickness of the galvanized layer is set to 70 μm; the thickness of the galvanized coating on the surface of the transmission tower component is set according to the minimum coating thickness in GB / T 13912-2020 "Technical Requirements and Test Methods for Hot-Dip Galvanized Layers of Metal-Coated Steel Parts". When the galvanized coating on the surface of the transmission tower component is corroded by 90%, the galvanized coating fails.

[0043] Preferably, the step 3 specifically includes the following steps:

[0044] Step 3.1, constructing a BP neural network, wherein the BP neural network is provided with an input layer, a hidden layer, and an output layer, wherein the hidden layer is provided with multiple neurons, and the input layer and the output layer are connected through neurons;

[0045] Step 3.2: Select multiple near-fault region earthquake records of the same earthquake, obtain multiple ground motions and the spatial coordinates corresponding to the ground motions in each region to form ground motion data samples, and construct a ground motion database;

[0046] Step 3.3: Using the seismic data samples in the seismic database to train the BP neural network, the seismic data samples are input into the BP neural network. The BP neural network uses multivariate empirical mode decomposition to perform signal analysis on the input seismic motion and determine the natural mode corresponding to the seismic motion. The hidden layer in the BP neural network obtains the seismic amplitude based on the natural mode of the seismic motion and transmits it to the output layer, which outputs the amplitude corresponding to the seismic motion.

[0047] In step 3.4, the coordinates of the space where the transmission tower is located are input into the trained BP neural network, and the seismic motion at any position in the space where the transmission tower is located is synthesized using the BP neural network.

[0048] Preferably, the step 4 specifically includes the following steps:

[0049] Step 4.1: Based on the actual structure of the transmission tower, taking into account the soil quality, conductive wires, and pile foundations surrounding the transmission tower, a finite element analysis model of the transmission tower structure is established using finite element analysis software based on a single tower structure. The finite element analysis model of the transmission tower structure adopts a four-wire three-tower structure. The finite element analysis model of the transmission tower structure has three transmission towers, each connected by a conductor with fixed constraints at both ends.

[0050] In step 4.2, the transmission tower at the middle position in the finite element analysis model of the transmission tower structure is taken as the research object. The influence of atmospheric erosion on the performance of the transmission tower poles is considered during the entire life cycle of the transmission tower. Combined with the corrosion depth of the transmission tower components, the effective cross-sectional area of ​​the updated transmission tower poles is calculated, as shown in formula (9):

[0051]

[0052] Where A(t) is the effective cross-sectional area of ​​the transmission tower pole, A(0) is the initial cross-sectional area of ​​the steel, h(0) is the initial cross-sectional thickness of the steel, and D(t) is the corrosion depth of the steel after the galvanized coating is completely corroded.

[0053] In step 4.3, based on the transmission tower structure finite element analysis model and the updated effective cross-sectional area of ​​the transmission tower poles, a tower-pile-soil-line-time coupled finite element model for the entire life cycle of the transmission tower is established.

[0054] Preferably, the step 5 specifically includes the following steps:

[0055] Step 5.1: Perform a static pushover analysis on the transmission tower components using a tower-pile-soil-line-time coupled finite element model to obtain static pushover analysis curves for the transmission tower components. Based on the static pushover analysis curves, determine the damage state of the transmission tower components.

[0056] In step 5.2, the trained BP neural network is used to synthesize seismic waves. The synthesized seismic waves are applied to the tower-pile-soil-line-time coupled finite element model established in step 4. The incremental dynamic analysis method is used to gradually amplify the acceleration of the seismic waves, change the seismic motion and atmospheric corrosion environment, and simulate the response of the tower-pile-soil-line-time coupled finite element model under the combined effects of different seismic motions and atmospheric environments. The probability of the transmission tower structure exceeding the damage limit state under the combined effects of seismic motion and atmospheric environment is determined.

[0057] In step 5.2, the formula for calculating the fragility of the transmission tower structure under the combined effects of earthquake motion and atmospheric environment is:

[0058]

[0059]

[0060] ln(S D )=ln(a)+b ln(IM1)+c ln(IM2) (12)

[0061] Where P is the probability of exceeding the damage limit state, LS is the damage limit state, IM1 is the ground motion, IM2 is the atmospheric erosion, S D is the demand value of the transmission tower structure under the combined effects of earthquake motion and atmospheric erosion, S C is the capacity value of the transmission tower structure under the combined effects of earthquake motion and atmospheric erosion, S D，i is the demand value of the transmission tower structure under the combined action of the i-th earthquake motion and atmospheric erosion, β D|IM is the coefficient of variation, a, b, and c are the fragility fitting parameters of the transmission tower structure;

[0062] In step 5.3, based on the response of the tower-pile-soil-line-time coupled finite element model under seismic waves, determine the vulnerability surface of the transmission tower under the combined action of near-fault earthquakes and atmospheric corrosion. Furthermore, based on the vulnerability surface of the transmission tower under the combined action of near-fault earthquakes and atmospheric corrosion, evaluate the damage resistance of the transmission tower to near-site vibrations.

[0063] Preferably, in step 6, the model parameters include the epicenter distance of the near-fault earthquake, the comprehensive atmospheric environment corrosion factor, the horizontal span, the transmission tower type and the soil type, wherein the transmission tower type includes tension tower, straight tower and terminal tower, and the soil type includes rock, hard soil and soft soil.

[0064] The present invention has the following beneficial effects:

[0065] The present invention realizes a rapid assessment of the vulnerability of transmission tower structures under the combined effects of atmospheric corrosion and near-site vibrations. By collecting environmental data of the transmission tower structure and measured values ​​of steel corrosion, the long-term corrosion degree of the transmission tower is inverted and predicted. A BP neural network is then constructed. The BP neural network is used to synthesize the seismic motion at any position in the space where the transmission tower is located. A tower-pile-soil-line-time coupled finite element model is then established to simulate the vulnerability surface of the transmission tower under the combined effects of near-fault earthquakes and atmospheric erosion. Based on the transmission tower vulnerability surface, the damage resistance of the transmission tower to near-site vibrations under the combined effects of seismic motion and atmospheric erosion is evaluated. This achieves a rapid assessment of the damage resistance of the transmission tower throughout its life cycle, providing support for ensuring the operation and maintenance of the transmission tower. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 Flowchart of a method for evaluating the seismic vulnerability of transmission towers near faults considering environmental erosion.

[0067] Figure 2 This is the curve showing the change of corrosion depth of steel used in transmission tower components over time.

[0068] Figure 3 Schematic diagram of BP neural network structure.

[0069] Figure 4 This is the near-fault seismic wave synthesized by BP neural network.

[0070] Figure 5 This is a structural diagram of the finite element analysis model of the transmission tower structure.

[0071] Figure 6 This is a structural schematic diagram of the transmission tower in the finite element analysis model of the transmission tower structure.

[0072] Figure 7 Figure 2 is the vulnerability surface of the transmission tower-line system at different service lives under the action of atmospheric corrosion and near-site vibration. Figure (a) is the vulnerability surface corresponding to slight damage of the transmission tower-line system under the action of atmospheric corrosion and near-site vibration, Figure (b) is the vulnerability surface corresponding to moderate damage of the transmission tower-line system under the action of atmospheric corrosion and near-site vibration, and Figure (c) is the vulnerability surface corresponding to the collapse state of the transmission tower-line system under the action of atmospheric corrosion and near-site vibration. DETAILED DESCRIPTION

[0073] The following further describes the specific embodiments of the present invention with reference to the accompanying drawings and a transmission tower system of a 220kV high-voltage transmission project as an example:

[0074] Taking the transmission tower system of a 220kV high-voltage transmission project as an example, the transmission towers in the system are 2E2-SZ1 double-circuit ram's horn-shaped transmission towers. The nominal height of the towers is 33m and the total height is 49.7m. The main material is Q345 steel, and the remaining support rods are made of Q235 steel. The horizontal span is set to 350m and the vertical span is set to 480m. The transmission tower system is designed for an ice thickness of 5mm, a maximum temperature of 40°C, and a minimum temperature of -20°C. The insulator model is XWP-100, the suspension string length is 3.3m, the conductor model is LGJ-400 / 35, and the ground wire model is JLB35-150. In this example, the seismic fortification intensity of the area where the transmission tower system is located is 8 degrees, and the design peak earthquake acceleration of the transmission tower system is 0.2g.

[0075] The transmission tower system is evaluated using a transmission tower near-fault earthquake vulnerability assessment method considering environmental erosion proposed in the present invention. Figure 1 As shown, the specific steps include:

[0076] Step 1: Obtain atmospheric environmental parameters near the transmission tower, determine the comprehensive atmospheric environmental corrosion factor, and calculate the corrosion rate of the transmission tower, which specifically includes the following steps:

[0077] Step 1.1: Obtain atmospheric environmental parameters near the transmission tower. These parameters include temperature, humidity, sulfur dioxide concentration, chloride ion concentration, and nitrogen dioxide concentration. Determine the annual sunshine duration, annual average temperature, annual average humidity, annual rainfall, annual number of rainy days, and the duration of time with humidity greater than 0.8 in a year for the environment in which the transmission tower is located.

[0078] In this example, the annual average temperature is 17.9°C, the highest temperature is 39.8°C, the lowest temperature is -0.3°C, the annual average humidity is 81%, the humidity is greater than 0.8 for 5741 hours a year, and the sulfur dioxide concentration is 0.689g / 100cm 2 d. Chloride ion concentration is 0.033 g / 100 cm 2 d. Nitrogen dioxide concentration is 0.051 g / 100 cm 2 d. Calculate the wetting factor f1, erosion factor f2 and rainwater acidity factor f3.

[0079] The calculation formula of the wet factor f1 is:

[0080]

[0081] Where f1 is the humidity factor, D1 is the duration of humidity greater than 0.8 in a year, H1 is the annual sunshine duration, The annual average temperature.

[0082] The calculation formula of the erosion factor f2 is:

[0083]

[0084] Where f2 is the erosion factor, is the sulfur dioxide concentration, is the chloride ion concentration, is the nitrogen dioxide concentration.

[0085] The calculation formula of the rainwater acidity factor f3 is:

[0086]

[0087] Where f3 is, L is the annual rainfall, D2 is the number of rainy days per year, and PH is the pH value of rainfall.

[0088] In step 1.2, the atmospheric environment corrosion comprehensive factor is determined based on the wetting factor f1, the erosion factor f2, and the rainwater acidity factor f3. In this embodiment, the atmospheric environment corrosion comprehensive factor calculated is 1.488.

[0089] The calculation formula for the comprehensive factor of atmospheric corrosion is shown in formula (4):

[0090] N=f1+f2+f3 (4)

[0091] Where N is the comprehensive factor of atmospheric corrosion.

[0092] In step 1.3, based on the comprehensive atmospheric corrosion factor and the first-year corrosion rate of the transmission tower steel structure, since the transmission tower steel structure is made of Q345 main material, the fitting coefficients A = 44.589 and B = 76.553 in formula (4) can be obtained, and the corrosion rate R of the transmission tower is calculated to be 83.7 μm / a.

[0093] Step 2: applying a galvanized coating to the surface of the transmission tower components. After the galvanized coating on the surface of the transmission tower components is completely corroded, the corrosion depth of the steel used in the transmission tower components is calculated based on the corrosion rate of the transmission tower to determine the effective protection life of the galvanized coating. The steps specifically include the following:

[0094] Step 2.1: According to GB / T 13912-2020 "Technical requirements and test methods for hot-dip galvanizing of metal-coated steel parts", a galvanized coating is applied to the surface of the transmission tower components.

[0095] According to GB / T 13912-2020 "Technical requirements and test methods for hot-dip galvanized layers of steel products with metal coatings", when the thickness of the steel used for transmission tower components is greater than 6mm, the average thickness of the galvanized layer is set to 85μm; when the thickness of the steel used for transmission tower components is greater than 3mm and not more than 6mm, the average thickness of the galvanized layer is set to 70μm; the thickness of the galvanized coating on the surface of the transmission tower components is set in accordance with the minimum coating thickness in GB / T 13912-2020 "Technical requirements and test methods for hot-dip galvanized layers of steel products with metal coatings". At the same time, according to the regulations of the Japan Corrosion Protection Association, when the galvanized coating on the surface of the transmission tower component is corroded by 90%, the galvanized coating fails, so the protective effectiveness of the galvanized coating can be calculated using the thickness of the steel.

[0096] In step 2.2, after the galvanized coating on the surface of the transmission tower component is completely corroded, the corrosion depth of the steel used in the transmission tower component is calculated based on the corrosion rate of the transmission tower.

[0097] When the corrosion rate of the transmission tower is R=50~80μm / a, the corrosion depth of the steel used in the transmission tower components is:

[0098]

[0099] When the corrosion rate of the transmission tower is R=80~200μm / a, the corrosion depth of the steel used in the transmission tower components is:

[0100]

[0101] When the corrosion rate of the transmission tower is R = 200 ~ 700μm / a, the corrosion depth of the steel used in the transmission tower components is:

[0102]

[0103] Where t is the exposure period, in units of a, and is the difference between the service life of the transmission tower and the effective protection period of the galvanized coating;

[0104] Step 2.3, using the relationship between the corrosion depth of the steel used in the transmission tower components and the exposure years (i.e. time), as Figure 2 As shown in the figure, the effective protection period of the galvanized coating is determined according to the corrosion depth of the steel used in the transmission tower components.

[0105] Step 3: construct a BP neural network, train the BP neural network to synthesize near-ground ground motion, and use the trained BP neural network to synthesize the ground motion at any position in the space where the transmission tower is located. Specifically, the following steps are included:

[0106] Step 3.1: The near-fault region is the area with the largest earthquake amplitude (i.e., the area with the most severe earthquake). The frequency and duration of earthquake motions vary dramatically over a short spatial interval. Directly using existing earthquake motion data will significantly underestimate the spatial variation effect. Therefore, it is necessary to use artificial intelligence methods to synthesize near-field ground motions by constructing a BP neural network.

[0107] The constructed BP neural network is equipped with input layer, hidden layer and output layer, such as Figure 3 As shown, a plurality of neurons are provided in the hidden layer, and the input layer and the output layer are connected through neurons.

[0108] Step 3.2: Select multiple near-fault area earthquake records of the same earthquake, obtain multiple ground motions and the spatial coordinates corresponding to the ground motions in each area to form ground motion data samples, and construct a ground motion database.

[0109] Step 3.3: Use the seismic data samples in the seismic database to train the BP neural network. Input the seismic data samples into the BP neural network. The BP neural network uses multivariate empirical mode decomposition to perform signal analysis on the input seismic motion and determine the natural mode corresponding to the seismic motion. The hidden layer in the BP neural network obtains the amplitude of the seismic motion according to the natural mode of the seismic motion and transmits it to the output layer. The output layer outputs the amplitude corresponding to the seismic motion.

[0110] In step 3.4, the coordinates of the space where the transmission tower is located are input into the trained BP neural network, and the seismic motion at any position in the space where the transmission tower is located is synthesized using the BP neural network.

[0111] In this embodiment, the PEER earthquake motion database is directly used. The PEER earthquake motion database includes 419 main shock records, and the longitude and latitude and epicenter distance of each main shock record are recorded in detail. The BP neural network constructed by using the earthquake motion database is trained and the trained BP neural network is used to synthesize the artificial seismic waves of the near-fault earthquake at the transmission tower location (1.2 km away from the center of the earthquake source). Figure 4 At the same time, in order to provide stable earthquake motion data for the BP neural network, this embodiment adopts multivariate empirical mode decomposition (MEMD) to perform earthquake motion signal analysis. Multivariate empirical mode decomposition can not only decompose non-stationary signals but also overcome the problem of modal aliasing.

[0112] Step 4: Based on the actual structure of the transmission tower, a finite element analysis model of the transmission tower structure is established using finite element analysis software. The influence of atmospheric erosion on the performance of the transmission tower poles during the entire life cycle of the transmission tower is considered, and a tower-pile-soil-line-time coupled finite element model is established. The specific steps include:

[0113] Step 4.1: Based on the actual structure of the transmission tower, taking into account the soil quality, conductive wires and pile foundations around the transmission tower, a finite element analysis model of the transmission tower structure is established using finite element analysis software based on a single tower structure. The finite element analysis model of the transmission tower structure adopts a four-wire three-tower structure, such as Figure 5 As shown in the figure, there are three transmission towers in the finite element analysis model of the transmission tower structure. Figure 6 As shown, the transmission towers are connected by wires, and both ends of the wires are fixed and constrained.

[0114] In step 4.2, the transmission tower at the middle position in the finite element analysis model of the transmission tower structure is taken as the research object. The influence of atmospheric erosion on the performance of the transmission tower poles is considered during the entire life cycle of the transmission tower. Combined with the corrosion depth of the transmission tower components, the effective cross-sectional area of ​​the updated transmission tower poles is calculated, as shown in formula (9):

[0115]

[0116] Where A(t) is the effective cross-sectional area of ​​the transmission tower pole, A(0) is the initial cross-sectional area of ​​the steel, h(0) is the initial cross-sectional thickness of the steel, and D(t) is the corrosion depth of the steel after the galvanized coating is completely corroded.

[0117] In step 4.3, based on the transmission tower structure finite element analysis model and the updated effective cross-sectional area of ​​the transmission tower poles, a tower-pile-soil-line-time coupled finite element model for the entire life cycle of the transmission tower is established.

[0118] Step 5: Use the trained BP neural network to synthesize seismic waves. Apply the synthesized seismic motion to the tower-pile-soil-line-time coupled finite element model to simulate the vulnerability surface of the transmission tower under the combined effects of near-fault earthquakes and atmospheric erosion. This evaluates the resistance of the transmission tower to near-field vibrations under the combined effects of earthquake motion and atmospheric erosion. This specifically includes the following steps:

[0119] In step 5.1, a static pushover analysis is performed on the transmission tower components using the tower-pile-soil-line-time coupled finite element model to obtain the static pushover analysis curves of the transmission tower components. Based on the static pushover analysis curves of the transmission tower components, the damage state of the transmission tower components is determined.

[0120] In step 5.2, the trained BP neural network is used to synthesize seismic waves. The synthesized seismic waves are applied to the tower-pile-soil-line-time coupled finite element model established in step 4. The incremental dynamic analysis method is used to gradually amplify the acceleration of the seismic waves, change the seismic motion and atmospheric corrosion, and simulate the response of the tower-pile-soil-line-time coupled finite element model under the combined action of different seismic motions and atmospheric environments. The probability of the transmission tower structure exceeding the damage limit state under the combined action of seismic motion and atmospheric environment is calculated, as shown in formulas (10) to (12):

[0121]

[0122]

[0123] ln(S D )=ln(a)+b ln(IM1)+c ln(IM2) (12)

[0124] Where P is the probability of exceeding the damage limit state, LS is the damage limit state, IM1 is the ground motion, IM2 is the atmospheric erosion, S D is the demand value of the transmission tower structure under the combined effects of earthquake motion and atmospheric erosion, S C is the capacity value of the transmission tower structure under the combined effects of earthquake motion and atmospheric erosion, S D，i is the demand value of the transmission tower structure under the combined action of the i-th earthquake motion and atmospheric erosion, β D|IM is the coefficient of variation, and a, b, and c are the fragility fitting parameters of the transmission tower structure.

[0125] In step 5.3, based on the response of the tower-pile-soil-line-time coupled finite element model under seismic waves, determine the vulnerability surface of the transmission tower under the combined action of near-fault earthquakes and atmospheric corrosion. Furthermore, based on the vulnerability surface of the transmission tower under the combined action of near-fault earthquakes and atmospheric corrosion, evaluate the damage resistance of the transmission tower to near-site vibrations.

[0126] Step 6: Change the model parameters of the tower-pile-soil-line-time coupled finite element model. Set the transmission tower type to tension tower, straight tower, and terminal tower in turn. For each type of transmission tower, modify the soil type to rock, hard soil, and soft soil in turn. Set the epicenter distance of the near-fault earthquake to 0-2 km, 2-5 km, 5-10 km, 10-20 km, and greater than 20 km in turn. Set the atmospheric environment corrosion comprehensive factor to 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, and greater than 4.0 in turn. Set the horizontal span to 200 m, 250 m, 300 m, 350 m, 400 m, 450 m, 500 m, 550 m, and 600 m in turn. Use the Monte Carlo numerical simulation method to simulate the response of the tower-pile-soil-line-time coupled finite element model under different model parameter conditions, as shown in the following figure: Figure 7 As shown in the figure, multiple sets of transmission tower vulnerability surfaces are obtained to form a near-field dynamic-atmospheric environment vulnerability surface database. By performing multi-parameter regression analysis on all the transmission tower vulnerability surfaces in the near-field dynamic-atmospheric environment vulnerability surface database, an evaluation formula for the damage resistance of transmission lines under the combined action of the near-field dynamic-atmospheric environment is established. The transmission line performance evaluation formula is used to quickly evaluate the damage resistance of transmission lines under the combined action of the near-field dynamic-atmospheric environment.

[0127] Of course, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by technicians in this technical field within the essential scope of the present invention should also fall within the scope of protection of the present invention.

Claims

1. A method for evaluating the seismic vulnerability of transmission towers near faults considering environmental erosion, characterized in that: The specific steps include: Step 1: Obtain atmospheric environmental parameters near the transmission tower, determine the comprehensive atmospheric environmental corrosion factor, and calculate the corrosion rate of the transmission tower; Step 2: applying a galvanized coating to the surface of the transmission tower components. After the galvanized coating on the surface of the transmission tower components is completely corroded, the corrosion depth of the steel used in the transmission tower components is calculated based on the corrosion rate of the transmission tower to determine the effective protection life of the galvanized coating. Step 3: construct a BP neural network, train the BP neural network to synthesize near-field ground motion, and use the trained BP neural network to synthesize the ground motion at any location in the space where the transmission tower is located; Step 4: Based on the actual structure of the transmission tower, a finite element analysis model of the transmission tower structure is established using finite element analysis software. The influence of atmospheric erosion on the performance of the transmission tower poles during the entire life cycle of the transmission tower is considered, and a tower-pile-soil-line-time coupled finite element model is established; Step 5: Use the trained BP neural network to synthesize seismic waves, apply the synthesized seismic motion to the tower-pile-soil-line-time coupled finite element model, and simulate the vulnerability surface of the transmission tower under the combined effects of near-fault earthquakes and atmospheric erosion. Step 6: sequentially change the model parameters of the tower-pile-soil-line-time coupled finite element model, and use the updated tower-pile-soil-line-time coupled finite element model to simulate and obtain the vulnerability surfaces of the transmission tower under the combined effects of multiple near-fault earthquakes and atmospheric erosion, thereby forming a near-field dynamic-atmospheric environment vulnerability surface database. By performing multi-parameter regression analysis on all the transmission tower vulnerability surfaces in the near-field dynamic-atmospheric environment vulnerability surface database, a formula for evaluating the damage resistance performance of the transmission line under the combined effects of the near-field dynamic-atmospheric environment is established, and the transmission line performance evaluation formula is used to quickly evaluate the damage resistance performance of the transmission line under the combined effects of the near-field dynamic-atmospheric environment.

2. The method for evaluating the near-fault seismic vulnerability of a transmission tower considering environmental erosion according to claim 1, characterized in that: The step 1 specifically includes the following steps: Step 1.1: Obtain atmospheric environmental parameters near the transmission tower, including temperature, humidity, sulfur dioxide concentration, chloride ion concentration, and nitrogen dioxide concentration. Determine the annual sunshine duration, annual average temperature, annual average humidity, annual rainfall, annual number of rainy days, and the duration of time with humidity greater than 0.8 in a year. Calculate the wetting factor f1, erosion factor f2, and rainwater acidity factor f3. The calculation formula of the wet factor f1 is: Where f1 is the humidity factor, D1 is the duration of humidity greater than 0.8 in a year, H1 is the annual sunshine duration, is the annual mean temperature; The calculation formula of the erosion factor f2 is: Where f2 is the erosion factor, is the sulfur dioxide concentration, is the chloride ion concentration, is the nitrogen dioxide concentration; The calculation formula of the rainwater acidity factor f3 is: Where f3 is the rainwater acidity factor, L is the annual rainfall, D2 is the number of rainy days per year, and PH is the pH value of rainfall; Step 1.2: Determine the comprehensive atmospheric corrosion factor based on the wetting factor f1, the erosion factor f2, and the rainwater acidity factor f3, as shown in formula (4): N=f1+f2+f3 (4) Where N is the comprehensive corrosion factor of atmospheric environment; In step 1.3, the corrosion rate of the transmission tower is calculated based on the comprehensive atmospheric corrosion factor and the first-year corrosion rate of the transmission tower steel structure, as shown in formula (5): R=A lg N+B (5) Where R is the corrosion rate of the transmission tower, in μm / a; A and B are fitting coefficients.

3. The method for evaluating the near-fault seismic vulnerability of a transmission tower considering environmental erosion according to claim 2, characterized in that: The step 2 specifically includes the following steps: Step 2.1: Apply a galvanized coating to the surface of the transmission tower components in accordance with GB / T 13912-2020, “Technical Requirements and Test Methods for Hot-Dip Galvanizing of Metal-Coated Steel Parts.” Step 2.2: After the galvanized coating on the surface of the transmission tower component is completely corroded, the corrosion depth of the steel used in the transmission tower component is calculated based on the corrosion rate of the transmission tower; When the corrosion rate of the transmission tower is R=50~80μm / a, the corrosion depth of the steel used in the transmission tower components is: When the corrosion rate of the transmission tower is R=80~200μm / a, the corrosion depth of the steel used in the transmission tower components is: When the corrosion rate of the transmission tower is R = 200 ~ 700μm / a, the corrosion depth of the steel used in the transmission tower components is: Where t is the exposure period, in units of a, and is the difference between the service life of the transmission tower and the effective protection period of the galvanized coating; Step 2.3, using the relationship between the corrosion depth of the steel used in the transmission tower components and the years of exposure, determine the effective protection life of the galvanized coating based on the corrosion depth of the steel used in the transmission tower components.

4. The method for evaluating the near-fault seismic vulnerability of a transmission tower considering environmental erosion according to claim 3, characterized in that: In step 2.1, when the thickness of the steel selected for the transmission tower component is greater than 6 mm, the average thickness of the galvanized layer is set to 85 μm; when the thickness of the steel selected for the transmission tower component is greater than 3 mm and not more than 6 mm, the average thickness of the galvanized layer is set to 70 μm; the thickness of the galvanized coating on the surface of the transmission tower component is set in accordance with the minimum coating thickness in GB / T 13912-2020 "Technical Requirements and Test Methods for Hot-Dip Galvanizing Layers of Metal-Coated Steel Parts". When the galvanized coating on the surface of the transmission tower component is corroded by 90%, the galvanized coating fails.

5. The method for evaluating the near-fault seismic vulnerability of a transmission tower considering environmental erosion according to claim 3, characterized in that: The step 3 specifically includes the following steps: Step 3.1, constructing a BP neural network, wherein the BP neural network is provided with an input layer, a hidden layer, and an output layer, wherein the hidden layer is provided with multiple neurons, and the input layer and the output layer are connected through neurons; Step 3.2: Select multiple near-fault region earthquake records of the same earthquake, obtain multiple ground motions and the spatial coordinates corresponding to the ground motions in each region to form ground motion data samples, and construct a ground motion database; Step 3.3: Using the seismic data samples in the seismic database to train the BP neural network, the seismic data samples are input into the BP neural network. The BP neural network uses multivariate empirical mode decomposition to perform signal analysis on the input seismic motion and determine the natural mode corresponding to the seismic motion. The hidden layer in the BP neural network obtains the seismic amplitude based on the natural mode of the seismic motion and transmits it to the output layer, which outputs the amplitude corresponding to the seismic motion. In step 3.4, the coordinates of the space where the transmission tower is located are input into the trained BP neural network, and the seismic motion at any position in the space where the transmission tower is located is synthesized using the BP neural network.

6. The method for evaluating the near-fault seismic vulnerability of a transmission tower considering environmental erosion according to claim 5, characterized in that: The step 4 specifically includes the following steps: Step 4.1: Based on the actual structure of the transmission tower, taking into account the soil quality, conductive wires, and pile foundations surrounding the transmission tower, a finite element analysis model of the transmission tower structure is established using finite element analysis software based on a single tower structure. The finite element analysis model of the transmission tower structure adopts a four-wire three-tower structure. The finite element analysis model of the transmission tower structure has three transmission towers, each connected by a conductor with fixed constraints at both ends. In step 4.2, the transmission tower at the middle position in the finite element analysis model of the transmission tower structure is taken as the research object. The influence of atmospheric erosion on the performance of the transmission tower poles is considered during the entire life cycle of the transmission tower. Combined with the corrosion depth of the transmission tower components, the effective cross-sectional area of ​​the updated transmission tower poles is calculated, as shown in formula (9): Where A(t) is the effective cross-sectional area of ​​the transmission tower pole, A(0) is the initial cross-sectional area of ​​the steel, h(0) is the initial cross-sectional thickness of the steel, and D(t) is the corrosion depth of the steel after the galvanized coating is completely corroded. In step 4.3, based on the transmission tower structure finite element analysis model and the updated effective cross-sectional area of ​​the transmission tower poles, a tower-pile-soil-line-time coupled finite element model for the entire life cycle of the transmission tower is established.

7. The method for evaluating the near-fault seismic vulnerability of a transmission tower considering environmental erosion according to claim 6, characterized in that: The step 5 specifically includes the following steps: Step 5.1: Perform a static pushover analysis on the transmission tower components using a tower-pile-soil-line-time coupled finite element model to obtain static pushover analysis curves for the transmission tower components. Based on the static pushover analysis curves, determine the damage state of the transmission tower components. In step 5.2, the trained BP neural network is used to synthesize seismic waves. The synthesized seismic waves are applied to the tower-pile-soil-line-time coupled finite element model established in step 4. The incremental dynamic analysis method is used to gradually amplify the acceleration of the seismic waves, change the seismic motion and atmospheric corrosion environment, and simulate the response of the tower-pile-soil-line-time coupled finite element model under the combined effects of different seismic motions and atmospheric environments. The probability of the transmission tower structure exceeding the damage limit state under the combined effects of seismic motion and atmospheric environment is determined. In step 5.2, the formula for calculating the fragility of the transmission tower structure under the combined effects of earthquake motion and atmospheric environment is: ln(S D )=ln(a)+b ln(IM1)+c ln(IM2) (12) Where P is the probability of exceeding the damage limit state, LS is the damage limit state, IM1 is the ground motion, IM2 is the atmospheric erosion, S D is the demand value of the transmission tower structure under the combined effects of earthquake motion and atmospheric erosion, S C is the capacity value of the transmission tower structure under the combined effects of earthquake motion and atmospheric erosion, S D，i is the demand value of the transmission tower structure under the combined action of the i-th earthquake motion and atmospheric erosion, β D|IM is the coefficient of variation, a, b, and c are the fragility fitting parameters of the transmission tower structure; In step 5.3, based on the response of the tower-pile-soil-line-time coupled finite element model under seismic waves, determine the vulnerability surface of the transmission tower under the combined action of near-fault earthquakes and atmospheric corrosion. Furthermore, based on the vulnerability surface of the transmission tower under the combined action of near-fault earthquakes and atmospheric corrosion, evaluate the damage resistance of the transmission tower to near-site vibrations.

8. The method for evaluating the near-fault seismic vulnerability of a transmission tower considering environmental erosion according to claim 1, wherein: In step 6, the model parameters include the epicenter distance of the near-fault earthquake, the comprehensive atmospheric environmental corrosion factor, the horizontal span, the transmission tower type, and the soil type. The transmission tower types include tension towers, straight towers, and terminal towers, and the soil types include rock, hard soil, and soft soil.

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