Power transmission tower wind damage vulnerability analysis method based on long-term marine atmospheric corrosion

Abstract

The invention discloses a power transmission tower wind damage vulnerability analysis method based on long-term marine atmospheric corrosion. The method comprises the following steps: step 1, establishing a wind load numerical simulation model; 2, establishing a corrosion depth prediction model of the steel structure in the marine atmospheric environment; 3, establishing a finite element model of the corroded power transmission tower line system; 4, establishing a wind damage vulnerability model of the power transmission line structure; 5, performing push hover analysis on the power transmission tower structures with different service lives considered; and 6, analyzing the wind damage vulnerability of the power transmission tower structure. According to the power transmission tower wind disaster vulnerability analysis method based on long-term marine atmospheric corrosion, by establishing the wind disaster vulnerability curves under different corrosion degrees, the damage probability of the power transmission tower under the wind load effect can be predicted more accurately, a scientific basis is provided for design, maintenance and operation of the power transmission tower, and the method is suitable for popularization and application. And the stability and the safety of the system in a complex marine atmospheric environment are ensured.

Description

Technical Field

[0001] The invention relates to the field of transmission line operation reliability, and in particular to a method for analyzing the wind disaster vulnerability of a transmission tower based on long-term marine atmospheric corrosion. Background Art

[0002] Transmission towers are the core supporting structures in the power transmission process. From early reinforced concrete towers to modern steel structure towers, the transmission capacity has been significantly improved. However, the steel truss structure transmission towers are very susceptible to corrosion in the atmospheric environment due to the combined effects of moisture, oxygen, sulfur dioxide, nitrogen dioxide and chloride ions. As the service time increases, the amount and degree of corrosion of the components gradually increase. The corrosion of steel components will not only cause economic losses, but more importantly, it will lead to the degradation of structural durability and the decrease of bearing capacity, which may eventually cause partial damage or even collapse of the transmission tower.

[0003] Natural wind can be divided into average wind and fluctuating wind, among which fluctuating wind is the main source of wind load randomness. Even under the same wind speed and other conditions, the wind load time history obtained in each simulation will be different. Therefore, the uncertainty of wind load as a random input will significantly affect the results of the wind-induced dynamic response of the transmission tower. Traditional deterministic analysis methods are difficult to comprehensively evaluate the wind resistance of the transmission tower structure. Therefore, a probabilistic method should be used to statistically analyze the wind-induced damage law of the transmission tower structure. Vulnerability analysis is an effective method based on probability. Wind disaster vulnerability refers to the exceedance probability of structural damage under a given intensity of wind load. This method quantitatively describes the wind resistance of the structure from a probabilistic perspective and clarifies the relationship between the probability of structural damage and the intensity of wind load. At present, although the calculation method for the ultimate bearing capacity of structural elastic-plastic wind resistance is not yet mature, there have been many studies on the ultimate bearing capacity of structures under earthquakes and other loads. These analysis methods can provide a reference for the study of the ultimate bearing capacity of structural wind resistance.

[0004] At present, the wind resistance analysis of transmission towers is mainly concentrated in the design stage. However, during the service period, the cross-sectional area of ​​the steel structure transmission tower is reduced and the mechanical properties of the steel are reduced due to corrosion, which will inevitably affect the operational safety of the transmission tower. Therefore, it is necessary to conduct wind vibration response analysis and wind disaster vulnerability analysis on the corroded steel structure transmission tower during service to ensure the stable and safe operation of the transmission tower, prevent the occurrence of tower collapse accidents, and ensure that people's normal life is not affected. Summary of the invention

[0005] The present invention provides a method for analyzing the wind damage vulnerability of transmission towers based on long-term marine atmospheric corrosion. By establishing wind damage vulnerability curves under different corrosion degrees, the destruction probability of transmission towers under wind loads can be more accurately predicted, providing a scientific basis for the design, maintenance and operation of transmission towers, and ensuring their stability and safety in complex marine atmospheric environments.

[0006] The technical solution adopted by the present invention is:

[0007] The wind damage vulnerability analysis method of transmission towers based on long-term marine atmospheric corrosion includes the following steps:

[0008] Step 1: Establish a numerical simulation model for wind load;

[0009] Step 2: Establish a prediction model for the corrosion depth of steel structures in marine atmospheric environment;

[0010] Step 3: Establish the finite element model of the transmission tower line system after corrosion;

[0011] Step 4: Establish a wind disaster vulnerability model for transmission line structures;

[0012] Step 5: Pushover analysis of transmission tower structures considering different service years;

[0013] Step 6: Analyze the wind damage vulnerability of the transmission tower structure.

[0014] In step 1, a wind load numerical simulation model is established, as follows:

[0015] 1.1. The wind speed time series consists of two parts: average wind speed and pulsating wind speed:

[0016]

[0017] In the formula, is the average wind speed; ν(z,t) is the pulsating wind speed;

[0018] The exponential conversion formula is used to simulate and calculate the average wind speed at different heights:

[0019]

[0020] Where α is the ground roughness; z is the height; is the average wind speed at the current height; is the average wind speed at a height of 10m;

[0021] The pulsating wind speed is described by the Kaimal wind speed spectrum proposed by JC Kaimal et al. in the 1970s to describe the frequency spectrum distribution of turbulent wind speed:

[0022]

[0023] In the formula, S v (n) is the power spectrum density of wind speed; f * is the dimensionless Monin coordinate, which is one of the important parameters describing the turbulent structure in the atmospheric boundary layer; n is the pulsating wind frequency; V * is the friction speed or shear speed; is the average velocity at height z above the ground.

[0024] 1.2. Transmission lines are mainly subject to two external forces, namely wind load on conductors and wind load on transmission towers:

[0025] W X =β C α L ·W0·μ Z ·μ SC ·d·L P ·B1·sin 2 θ

[0026] W S =W0·μ Z ·μ S β Z ·B2·A S

[0027]

[0028] Where W X is the standard value of wind load perpendicular to the conductor and ground wire; β C is the wind load adjustment factor of line conductor and ground wire; μ Z is the wind pressure height variation coefficient; μ SC is the body coefficient of the conductor or ground wire; d is the outer diameter of the conductor or ground wire; L P is the horizontal spacing of the tower; θ is the angle between the wind direction and the conductor or ground wire direction; α L is the span reduction coefficient; B1 is the ground wire ice-covered wind load increase coefficient; W S is the standard value of tower wind load; W0 is the standard value of reference wind pressure; V0 is the basic wind speed value; μ S is the component shape coefficient; β Z is the wind vibration coefficient of the tower at height z; B2 is the wind load increase coefficient of the tower component covered with ice; A S is the calculated value of the projected area of ​​the windward component;

[0029] The above formula is given in the "DLT5551-2018 Overhead Transmission Line Load Specifications". This formula is derived from the wind-pressure relationship obtained from the Bernoulli equation. Specifically, the formula for calculating the dynamic pressure of wind is: Where W0 is wind pressure, ρ is air density, and V0 is wind speed. According to the relationship between air density ρ and weight r, we know Where g is the acceleration of gravity, the wind pressure formula is: Under standard conditions (pressure is 1013hPa, temperature is 15℃), air density r=0.01225[kN / m 3 ], the gravitational acceleration at latitude 45° is g = 9.8 [m / s 2 ], the wind pressure formula is:

[0030] The step 2 comprises the following steps:

[0031] S2.1. Consider the relative humidity, temperature, SO 2 Content and Cl - Deposition rate and other factors, according to the relevant specification GB / T 24513.2-2010, the corrosion rate of steel in the first year is:

[0032]

[0033] In the formula, r corr is the average corrosion rate in the first year; RH is the average annual relative humidity; T is the average annual temperature; P d is the annual average SO2 deposition rate; S d The annual average Cl - Deposition rate; f St is the steel correlation coefficient. When T≤10℃, f St =0.150(T-10), otherwise f St =-0.054(T-10).

[0034] S2.2. Based on the corrosion rate of steel in the first year, the prediction model of the corrosion depth of steel structure in marine atmosphere environment is established as follows:

[0035]

[0036] Where, d t is the corrosion depth; t is the exposure time; b is the metal environmental characteristic parameter. In the absence of experimental data, the metal environmental characteristic parameter of steel is taken as 0.523.

[0037] In step 3, the corrosion depth prediction model for steel structure in marine atmosphere environment established in step 2 is combined to select corrosion years of 0, 30, 60, and 90 years, respectively, taking into account uniform corrosion of the entire tower. 30 ,d 60 and d 90, the transmission tower line system is modeled in ANSYS.

[0038] Different tower shapes can be selected for modeling according to local actual conditions. For the L-shaped angle steel unit in the transmission tower model, BEAM188 units are used for simulation during the modeling process, and the cross-sectional shape of the unit is set to simulate the L-shape of the angle steel; the details are as follows:

[0039] In ANSYS software, BEAM188 unit is often used to simulate the angle steel of pole tower. This unit is based on Timoshenko beam theory, takes into account the shear deformation effect, and the cross section remains flat after deformation without distortion. It is suitable for analyzing the angle steel beam structure of pole tower. If the GUI (Graphical User Interface) operation is used to define the BEAM188 unit, it can be found in Figure 1 Or use the LATT command to define it. For details, please consult "ANSYS HELP".

[0040] Overhead conductor is a flexible structure, and LINK10 unit is used to perform finite element modeling, as follows:

[0041] The LINK10 unit is suitable for simulating flexible structures because it has only axial stiffness but no bending stiffness, which is consistent with the physical characteristics of overhead wires. And the LINK10 unit can handle large deformations of overhead wires under wind, ice load or other external forces. For detailed characteristics, please refer to "ANSYS HELP". It is recommended to set it using the command stream method. For specific operations, please refer to "ANSYS HELP".

[0042] The suspension insulator string is composed of multiple transmission insulator segments and can be approximately regarded as a tie rod model, as follows:

[0043] The LINK180 unit can simulate tension, compression and shear behavior, and is suitable for complex suspension insulator structure analysis. For detailed characteristics, please refer to "ANSYS HELP". Figure 2 The LINK180 definition panel is given, which includes two control input options: enter the cross-sectional area in AREA and enter the additional mass in ADDMAS, in kg / m. The GUI does not support the definition of LINK180 compression and tension functions in version 14.0. It can only be defined through command streams. For details, please consult ANSYSHELP.

[0044] The step 4 is specifically as follows:

[0045] The wind damage vulnerability of transmission tower structures is usually expressed by probability values, which refer to the probability of the structure reaching or exceeding a certain limit state under different wind loads. The failure probability can be expressed as:

[0046]

[0047] Where P f is the failure probability; F R (x) is the probability distribution function of the structural resistance; f s (x) is the probability density function of the load effect.

[0048] The wind damage vulnerability function represents the conditional probability that the effects of wind loads of different intensities exceed the structural bearing capacity defined at a specific damage stage. D Exceeding the structural bearing capacity R C The failure probability is:

[0049]

[0050] Due to R C and S D All obey the log-normal distribution, so the probability of structural failure at a specific stage P f It can be further expressed as:

[0051]

[0052] In the formula, is the mean value of the structural bearing capacity; Φ is the probability of structural failure calculated using the log-normal cumulative distribution function. The principle is explained as follows:

[0053] The lognormal distribution is the probability distribution of any random variable whose logarithm is normally distributed. The probability density function of the lognormal distribution is:

[0054]

[0055] In the formula, f X (x) represents the probability density of X taking values ​​near x; β is the overall logarithmic standard deviation; θ is the median;

[0056] The cumulative distribution function is calculated as follows:

[0057]

[0058] The formula is f X (x) is integrated, which can be understood as the probability that X ≤ x; θ is the median; and β is the logarithmic standard deviation.

[0059] The damage of transmission towers is usually closely related to the structural displacement. The wind damage vulnerability function based on the maximum displacement of the tower top is expressed as:

[0060]

[0061] In the formula, m D is the maximum displacement of the top of the transmission tower structure under a given wind load; m C is the mean value of wind resistance C of the structure in different limit states; ln(m D ) represents m D Logarithm, ln(m C ) represents m C Logarithm, lognormal distribution function means that the logarithm of a random variable conforms to the normal distribution. Therefore, in the calculation formula of lognormal distribution, the variable needs to be logarithmized.

[0062] In step 5, the pushover analysis of transmission tower structures with different service lives is considered, as follows:

[0063] Similar to the seismic vulnerability analysis of transmission tower structures, the wind load time history curve in the wind disaster vulnerability problem of transmission tower structures is analogous to the seismic motion curve in the seismic vulnerability analysis; multiple wind load time histories are generated by changing the average wind speed, and transient dynamic analysis of the structure is performed.

[0064] Combined with step 1, the average wind speed value is adjusted incrementally from 30m / s wind speed, 10 groups of wind load time history samples are generated and numbered A1~A10, and the corresponding wind load time history is generated. The transmission tower line system established in step 3 in ANSYS uses a 0° wind direction angle for input, and the displacement change of its transmission tower line system structure is obtained in the software post-processing. According to the displacement change of the transmission tower at different corrosion stages, the quantitative indicators of the transmission tower structure under different limit states are determined.

[0065] In step 6, the wind damage vulnerability of the transmission tower structure is analyzed, and the specific steps are as follows:

[0066] Through the regression analysis of the result data in step 5, the functional relationship between wind speed and structural effect is obtained; the maximum displacement of the top of the transmission tower structure under wind load is m D The relationship between and wind speed v generally follows a power exponential regression relationship. After taking the logarithm of both sides of the power exponent, it can be expressed as:

[0067] lnm D =a+bln(v)

[0068] Where a and b are coefficients, both obtained by regression analysis of the structural IDA result data.

[0069] The probabilistic wind load effect function of the transmission tower structure established in step 5 and the quantitative index limit values ​​of each limit state determined are substituted into the wind disaster vulnerability function in step 4 to obtain the wind disaster vulnerability result of the transmission tower structure. The result can be represented by a wind disaster vulnerability curve, which is a curve with wind speed as the independent variable and the probability of structural damage exceeding a certain limit state as the dependent variable.

[0070] The present invention provides a method for analyzing the wind damage vulnerability of transmission towers based on long-term marine atmospheric corrosion, and the technical effects are as follows:

[0071] 1. In step 1 of the present invention, the average wind speed and the pulsating wind speed can be used to fit the wind speed pulsation at different heights, and the wind load time history at different heights is calculated according to the corresponding specifications;

[0072] 2. In step 2 of the present invention, for the currently studied prediction model of atmospheric corrosion of steel structures, the use of piecewise functions is more suitable for predicting the corrosion of steel structures in long-term service, and the obtained results are more consistent with real data;

[0073] 3. In step 3 of the present invention, the finite element model of the transmission tower line system constructed using the mechanical performance parameters of the corroded rigid structure is more consistent with the actual structural performance of the transmission line in coastal areas;

[0074] 4. In step 4 of the present invention, a wind disaster vulnerability model of the transmission tower line system under different corrosion degrees is established to obtain the performance level of the transmission tower structure under wind load with different corrosion degrees.

[0075] 5. In step 5 of the present invention, a large number of wind load time histories are simulated to perform pushover analysis on transmission tower structures of different service years, so as to provide more practical quantitative indicators for judging wind-induced collapse of transmission tower structures;

[0076] 6. In step 6 of the present invention, by calculating the wind disaster vulnerability curves under different corrosion degrees, the probability of damage of the transmission tower under wind load can be more accurately predicted, providing a scientific basis for the design, maintenance and operation of the transmission tower, and ensuring its stability and safety in a complex marine atmospheric environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

[0078] Figure 1 Define panels for GUI operation of BEAM188 units;

[0079] Figure 2 Define panels for GUI operation of LINK180 units;

[0080] Figure 3 This is a flow chart for wind disaster vulnerability analysis.

[0081] Figure 4 Schematic diagram of the time-varying law of corrosion depth of steel structures.

[0082] Figure 5 Schematic diagram of the finite element model of the transmission tower line system.

[0083] Figure 6 The pushover curve of steel transmission towers with different service years.

[0084] Figure 7 The following is a comparison of the wind disaster vulnerability curves of steel structure transmission towers with different service years.

[0085] Figure 8 Comparison of wind disaster vulnerability curves of steel structure transmission towers under different limit states. DETAILED DESCRIPTION

[0086] A wind damage vulnerability analysis method for transmission towers based on long-term marine atmospheric corrosion. This method focuses on the corrosion effect of the marine atmospheric environment in coastal areas on steel transmission towers, quantitatively describes the wind resistance of the structure from a probability perspective, and determines the relationship between the probability of structural damage and the wind load intensity, such as Figure 3 The specific steps are as follows:

[0087] First, a large number of wind load time-history simulations were performed, and incremental dynamic time-history analysis (IDA) was performed on transmission tower structures of different service years to obtain the effect function under wind load. In addition, the Pushover analysis method was used to analyze these models, obtain the capacity curves of each model, and determine the limit values ​​of the ultimate state of each structure. Based on the above two analysis results, a further wind disaster vulnerability analysis was carried out to establish the wind disaster vulnerability curves of steel structure transmission towers of different service years in a marine atmospheric environment.

[0088] Step 1: Establish a numerical simulation model for wind loads, including:

[0089] 1.1. The wind speed time series consists of two parts: average wind speed and pulsating wind speed:

[0090]

[0091] In the formula, is the average wind speed; ν(z,t) is the pulsating wind speed;

[0092] The exponential conversion formula is used to simulate and calculate the average wind speed at different heights:

[0093]

[0094] Where α is the ground roughness; z is the height; is the average wind speed at the current height; is the average wind speed at a height of 10m;

[0095] The pulsating wind speed is described by the Kaimal wind speed spectrum proposed by JC Kaimal et al. in the 1970s to describe the frequency spectrum distribution of turbulent wind speed:

[0096]

[0097]

[0098] In the formula, S v (n) is the power spectrum density of wind speed; f * is the dimensionless Monin coordinate, which is one of the important parameters describing the turbulent structure in the atmospheric boundary layer; n is the pulsating wind frequency; V * is the friction speed or shear speed; is the average velocity at height z above the ground.

[0099] 1.2. Transmission lines are mainly subject to two external forces, namely wind load on conductors and wind load on transmission towers:

[0100] W X =β C α L ·W0·μ Z ·μ SC ·d·L P ·B1·sin 2 θ

[0101] W S =W0·μ Z ·μ S β Z ·B2·A S

[0102]

[0103] Where W X is the standard value of wind load perpendicular to the conductor and ground wire; β C is the wind load adjustment factor of line conductor and ground wire; μ Z is the wind pressure height variation coefficient; μ SC is the body coefficient of the conductor or ground wire; d is the outer diameter of the conductor or ground wire; L P is the horizontal spacing of the tower; θ is the angle between the wind direction and the conductor or ground wire direction; α L is the span reduction coefficient; B1 is the ground wire ice-covered wind load increase coefficient; W S is the standard value of tower wind load; W0 is the standard value of reference wind pressure; V0 is the basic wind speed value; μS is the component shape coefficient; β Z is the wind vibration coefficient of the tower at height z; B2 is the wind load increase coefficient of the tower component covered with ice; A S Calculated value of the projected area of ​​the windward component.

[0104] Step 2: Establish a prediction model for the corrosion depth of steel structures in marine atmospheric environments:

[0105] S2.1. Consider the relative humidity, temperature, SO 2 Content and Cl - Deposition rate and other factors, according to relevant specifications, the corrosion rate of steel in the first year is:

[0106]

[0107] In the formula, RH is the annual average relative humidity; T is the annual average temperature; P d is the annual average SO2 deposition rate; S d The annual average Cl - Deposition rate; f St is the steel correlation coefficient. When T≤10℃, f St =0.150(T-10), otherwise f St =-0.054(T-10).

[0108] S2.2. The time-varying model of steel corrosion is established based on the first-year corrosion rate of steel as follows:

[0109]

[0110] Where, d t is the corrosion depth; t is the exposure time; r corr is the average corrosion rate in the first year; b is the metal environment characteristic parameter. In the absence of experimental data, the metal environment characteristic parameter of steel is taken as 0.523.

[0111] The present invention is based on the damage of the power transmission lines caused by Typhoon Meranti in Xiamen. Therefore, combined with the climate conditions in Xiamen, the corrosion depth of steel materials that changes with service time is calculated. Figure 4 As shown. Figure 4 It can be seen that with the increase of service life, the corrosion depth of steel gradually increases.

[0112] Step 3: Establish the finite element model of the transmission tower line system after corrosion:

[0113] According to the actual engineering needs, a steel structure transmission tower model with different service life is established. The influence of corrosion is simulated by weakening the cross-sectional size of the component. The present invention only considers the situation of uniform corrosion of the entire tower. According to the steel structure marine atmospheric environment corrosion depth prediction model in step 2, the corrosion depth of the steel structure in the marine atmospheric environment for 30 years, 60 years, and 90 years is calculated, and the original cross-sectional thickness d of each angle steel component of the transmission tower is subtracted from the corrosion depth prediction value d. t , the residual depth of the cross-section of the angle steel components of the transmission tower with different service years is obtained, and the transmission tower line system is modeled in ANSYS based on this parameter. For the L-shaped angle steel unit in the model, the BEAM188 unit is used for simulation during the modeling process, and the cross-sectional shape of the unit is set to simulate the L-shape of the angle steel. The overhead wire is a flexible structure, and the LINK10 unit is used for finite element modeling. The suspension insulator string is composed of multiple transmission insulator pieces, which can be approximately regarded as a pull rod model, and the LINK180 unit model is used. The original uncorroded transmission tower line system model is shown in the figure Figure 5 shown.

[0114] Step 4: Establish a wind disaster vulnerability model for transmission line structures based on uncertainty factors:

[0115] The wind damage vulnerability of transmission tower structures is usually expressed as a probability value, which refers to the probability of the structure reaching or exceeding a certain limit state under different wind loads. The failure probability can be expressed as:

[0116]

[0117] In the formula, F R (x) is the probability distribution function of the structural resistance; f s (x) is the probability density function of the load effect.

[0118] The wind damage vulnerability function represents the conditional probability that the effects of wind loads of different intensities exceed the structural bearing capacity defined at a specific damage stage. D Exceeding the structural bearing capacity R C The failure probability is:

[0119]

[0120] In the formula, R C and S D All obey the log-normal distribution, so the probability of structural failure at a specific stage P f It can be further divided into:

[0121]

[0122] In the formula, is the mean formula of the structural bearing capacity; Φ is the probability of structural failure calculated using the log-normal cumulative distribution function.

[0123] The damage of transmission towers is usually closely related to the structural displacement. The wind damage vulnerability function based on the maximum displacement of the tower top is expressed as:

[0124]

[0125] In the formula, m D is the maximum displacement of the top of the transmission tower structure under a given wind load; m C is the average value of the wind resistance C of the structure in different limit states.

[0126] Step 5: Pushover analysis of transmission tower structures considering different service life:

[0127] The wind load effect of a structure refers to the maximum response caused by the wind load on the structure. Through probabilistic wind load effect analysis, wind load effect parameters (such as the maximum displacement of the top of the transmission tower m) can be established. D ) and wind load (wind speed). Similar to the seismic vulnerability analysis of transmission tower structures, the wind load time history curve in wind disaster vulnerability analysis is similar to the seismic motion curve in seismic vulnerability analysis. By changing the average wind speed to generate multiple wind load time histories, the transient dynamic analysis of the structure is performed:

[0128] (1) Establishing a finite element model: Establishing a finite element model of the transmission tower based on the actual project conditions to ensure that the model can accurately reflect the physical properties and stress conditions of the structure.

[0129] (2) Simulate the fluctuating wind speed time history: Starting from a wind speed of 30 m / s, the average wind speed value is adjusted incrementally to generate 10 sets of wind load time history samples, numbered A1 to A10, and generate the corresponding wind load time history. Use a wind direction angle of 0° for input and perform transient dynamic analysis.

[0130] (3) Regression analysis: Through regression analysis of the simulation results data, the functional relationship between wind speed and structural effect is obtained. The maximum displacement of the top of the transmission tower structure under wind load is m. D The relationship between and wind speed v generally follows a power exponential regression relationship. After taking the logarithm of both sides of the power exponent, it can be expressed as:

[0131] lnm D =a+bln(v)

[0132] Where a and b are coefficients, both obtained by regression analysis of the structural IDA result data.

[0133] According to the above formula, the linear regression analysis of the IDA results is carried out, and the probability demand model of wind load on steel structure transmission towers in marine atmospheric environment when the service life is 0 years, 30 years, 60 years and 90 years is obtained as follows:

[0134]

[0135] Step 6: Analyze the wind damage vulnerability of transmission tower structures:

[0136] Pushover analysis is used to determine the relationship between the wind resistance and structural deformation of transmission tower structures. The maximum displacement of the tower top is selected as the control displacement, and monotonic cyclic loading is used until the maximum displacement of the tower top reaches the target value.

[0137] According to previous disaster cases and related research results on instability failure analysis of transmission towers, the maximum displacement of the top of the transmission tower is m. C As the object of judging the failure form of transmission tower, the specific damage state division and corresponding quantitative criteria are shown in Table 1, where: C / ma Indicates the limit value of severe damage state, m C / co Indicates the limit value of collapse damage.

[0138] Table 1 Definition of damage status

[0139]

[0140]

[0141] ANSYS was used to perform pushover analysis on transmission tower structures with different service years. The lateral loading mode with inverted triangle distribution was adopted to obtain the relationship curve between the base shear force and the top displacement of each transmission tower structure. Finally, the quantitative indicators of corroded transmission towers with different service years under various limit states were determined. When quantifying these limit states, the top displacement of the transmission tower was still selected as the main indicator. The pushover curves of transmission tower structures with different service years are shown in Figure 2. Figure 6 shown.

[0142] from Figure 6 It can be seen that in the initial stage, with the increase of horizontal force, the capacity curve of the transmission tower increases linearly, and the structure is in the elastic stage; after reaching the yield point, although the load increase is small, the displacement of the tower top increases significantly, indicating that the lateral stiffness of the transmission tower is significantly reduced. At this time, it can be considered that the transmission tower structure has entered an unstable state and has been damaged.

[0143] exist Figure 6 It can be seen from the data that the displacement of the transmission towers that have been corroded for 0, 30, 60, and 90 years in the elastic stage is about 0.4 meters, far exceeding the displacement limit specified in the specification. Figure 6It can also be seen that the corresponding limit displacement of the transmission tower at different corrosion stages under its ultimate bearing capacity is about 1.86 meters, which indicates that when the displacement of the top of the transmission tower reaches this limit, the structure will collapse and fail. Based on the above analysis, the quantitative indicators of the corroded transmission tower under different limit states are finally determined, as shown in Table 2.

[0144] Table 2 Quantitative indicators of transmission tower structures under different limit states after corrosion

[0145]

[0146] The probability demand model of wind load on steel transmission towers in marine atmospheric environment obtained in step 5 when the service life is 0, 30, 60 and 90 years is:

[0147]

[0148] As well as the quantitative index limits of each limit state determined, as shown in Table 2, the wind disaster vulnerability function obtained in step 4 is substituted into:

[0149]

[0150] The failure probability formula of the transmission tower structure under the marine atmospheric environment considering the service life is obtained. Taking the service time of 60 years as an example, the failure probability formula is:

[0151]

[0152] The wind damage vulnerability of transmission tower structure is represented by the wind damage vulnerability curve, which takes wind speed as the independent variable and the probability of structural damage exceeding a certain limit state as the dependent variable, such as Figure 7 As shown. Figure 7 It can be seen that for the transmission tower structure with a service life of 0 years, its failure probability increases with the increase of wind speed, the probability of slight damage increases the fastest, and at the same time, there is a possibility of moderate damage, but there is basically no collapse, indicating that it has a high reliability under strong winds.

[0153] In order to more intuitively see the impact of the service life of the structure on the failure probability of each limit state of the structure, Figure 7 The wind disaster vulnerability curve is drawn as Figure 8 In the form of Figure 8 It can be seen that with the increase of service life, the probability of severe damage and collapse of the transmission tower structure at the same wind speed increases. Therefore, it is necessary to consider the influence of corrosion when conducting structural wind resistance analysis.

Claims

1. A wind damage vulnerability analysis method for transmission towers based on long-term marine atmospheric corrosion, characterized by The following steps are involved: Step 1: Establish a numerical simulation model for wind load; Step 2: Establish a prediction model for the corrosion depth of steel structures in marine atmospheric environment; Step 3: Establish the finite element model of the transmission tower line system after corrosion; Step 4: Establish a wind disaster vulnerability model for transmission line structures; Step 5: Pushover analysis of transmission tower structures considering different service years; Step 6: Analyze the wind damage vulnerability of the transmission tower structure.

2. The method for analyzing wind disaster vulnerability of transmission towers based on long-term marine atmospheric corrosion according to claim 1 is characterized in that: In step 1, a wind load numerical simulation model is established, as follows: 1.

1. The wind speed time series consists of two parts: average wind speed and pulsating wind speed: In the formula, is the average wind speed; ν(z,t) is the pulsating wind speed; The exponential conversion formula is used to simulate and calculate the average wind speed at different heights: Where α is the ground roughness; z is the height; is the average wind speed at the current height; is the average wind speed at a height of 10m; The pulsating wind speed is described as follows: In the formula, S v (n) is the power spectrum density of wind speed; f * is the dimensionless Morning coordinate; n is the pulsating wind frequency; V * is the friction speed or shear speed; is the average speed at a height of z above the ground; 1.

2. Transmission lines are subject to two external forces, namely wind loads on conductors and wind loads on transmission towers: W X =b C ·a L ·W0·m Z ·m SC ·d·L P ·B1·sin 2 i W S =W0·m Z ·m S ·b Z ·B2·A S Where W X is the standard value of wind load perpendicular to the conductor and ground wire; β C is the wind load adjustment factor of line conductor and ground wire; μ Z is the wind pressure height variation coefficient; μ SC is the body coefficient of the conductor or ground wire; d is the outer diameter of the conductor or ground wire; L P is the horizontal spacing of the tower; θ is the angle between the wind direction and the conductor or ground wire direction; α L is the span reduction coefficient; B1 is the ground wire ice-covered wind load increase coefficient; W S is the standard value of tower wind load; W0 is the standard value of reference wind pressure; V0 is the basic wind speed value; μ S is the component shape coefficient; β Z is the wind vibration coefficient of the tower at height z; B2 is the wind load increase coefficient of the tower component covered with ice; A S Calculated value of the projected area of ​​the windward component.

3. The method for analyzing the wind damage vulnerability of transmission towers based on long-term marine atmospheric corrosion according to claim 1 is characterized in that: The step 2 comprises the following steps: S2.

1. Consider the relative humidity, temperature, SO 2 Content and Cl - Deposition rate, the corrosion rate of steel in the first year: In the formula, r corr is the average corrosion rate in the first year; RH is the average annual relative humidity; T is the average annual temperature; P d is the annual average SO2 deposition rate; S d The annual average Cl - Deposition rate; f St is the steel correlation coefficient. When T≤10℃, f St =0.150(T-10), otherwise f St =-0.054(T-10); S2.

2. Based on the corrosion rate of steel in the first year, the prediction model of the corrosion depth of steel structure in marine atmosphere environment is established as follows: Where, d t is the corrosion depth; t is the exposure time; b is the metal environment characteristic parameter.

4. The method for analyzing the wind damage vulnerability of transmission towers based on long-term marine atmospheric corrosion according to claim 3 is characterized in that: In step 3, the marine atmospheric environment corrosion depth prediction model for steel structures established in step 2 is combined to select corrosion years of 0, 30, 60, and 90 years, respectively, taking into account uniform corrosion of the entire tower; based on the calculated corrosion depths d0, d 30 ,d 60 and d 90 , the transmission tower line system is modeled in ANSYS, including: Different tower shapes are selected for modeling according to local actual conditions. For the L-shaped angle steel unit in the transmission tower model, BEAM188 units are used for simulation during the modeling process, and the cross-sectional shape of the unit is set to simulate the L-shape of the angle steel. Overhead conductor is a flexible structure, and LINK10 unit is selected for finite element modeling; The suspension insulator string is composed of multiple transmission insulator segments and can be approximately regarded as a tie rod model.

5. The method for analyzing the wind damage vulnerability of transmission towers based on long-term marine atmospheric corrosion according to claim 1 is characterized in that: The step 4 is specifically as follows: The wind damage vulnerability of transmission tower structures is expressed by probability values, which refer to the probability of the structure reaching or exceeding a certain limit state under different wind loads. The failure probability is expressed as: Where P f is the failure probability; F R (x) is the probability distribution function of the structural resistance; f s (x) is the probability density function of the load effect; The wind damage vulnerability function represents the conditional probability that the effects of wind loads of different intensities exceed the structural bearing capacity defined at a specific damage stage; the wind load effect S D Exceeding the structural bearing capacity R C The failure probability is: Due to R C and S D All obey the log-normal distribution, so the probability of structural failure at a specific stage P f Further expressed as: In the formula, is the mean value of the structural bearing capacity; Φ is the probability of structural failure calculated using the log-normal cumulative distribution function; The damage of transmission towers is closely related to structural displacement. The wind damage vulnerability function based on the maximum displacement of the tower top is expressed as: In the formula, m D is the maximum displacement of the top of the transmission tower structure under a given wind load; m C is the average value of the wind resistance C of the structure in different limit states.

6. The method for analyzing the wind damage vulnerability of transmission towers based on long-term marine atmospheric corrosion according to claim 1 is characterized in that: In step 5, the pushover analysis of transmission tower structures with different service lives is considered, as follows: Combined with step 1, the average wind speed value is incrementally adjusted from 30m / s to generate 10 groups of wind load time history samples and numbered A1~A10, and the corresponding wind load time history is generated; the transmission tower line system established in step 3 in ANSYS is input with a 0° wind direction angle, and the displacement change of its transmission tower line system structure is obtained in the software post-processing; according to the displacement change of the transmission tower at different corrosion stages, the quantitative indicators of the transmission tower structure under different limit states are determined.

7. The method for analyzing the wind damage vulnerability of transmission towers based on long-term marine atmospheric corrosion according to claim 1 is characterized in that: In step 6, the wind damage vulnerability of the transmission tower structure is analyzed, and the specific steps are as follows: Through the regression analysis of the result data in step 5, the functional relationship between wind speed and structural effect is obtained; the maximum displacement of the top of the transmission tower structure under wind load is m D The relationship between the wind speed v and the power exponential regression is expressed as follows: lnm D =a+bln(v) In the formula, a and b are coefficients; The probabilistic wind load effect function of the transmission tower structure established in step 5 and the quantitative index limits of each limit state determined are substituted into the wind disaster vulnerability function in step 4 to obtain the wind disaster vulnerability result of the transmission tower structure, which can be represented by a wind disaster vulnerability curve.

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