Fan tower drum reliability evaluation method and system, electronic equipment and medium

Abstract

The invention belongs to the technical field of wind power generation, and relates to a fan tower reliability evaluation method and system, electronic equipment and a medium, and the method comprises the steps: obtaining a weather fatigue accumulated damage coefficient according to different weather data information; obtaining a load coefficient based on the load stress and a preset allowable stress; the inclination is collected in real time through an inclination angle sensor, and according to the inclination and a preset inclination threshold value, an inclination coefficient is obtained through normalization processing; obtaining the service time and the design life of the fan tower, and obtaining a life attenuation coefficient based on the service time and the design life; and obtaining the reliability according to the weather fatigue accumulated damage coefficient, the load coefficient, the inclination coefficient, the life attenuation coefficient, a preset weather fatigue accumulated damage weight, a load weight, an inclination weight and a life attenuation weight. According to the method, the reliability is obtained through the weather fatigue accumulated damage coefficient, the load coefficient, the inclination coefficient and the life attenuation coefficient, and the problem of low reliability evaluation accuracy of the existing fan tower is solved.

Description

Technical Field

[0001] This invention relates to the field of wind power generation technology, and specifically discloses a method, system, electronic equipment and medium for assessing the reliability of wind turbine towers. Background Technology

[0002] As a key load-bearing structure supporting the entire wind turbine generator, the long-term safe and stable operation of the wind turbine tower is crucial. During its service life, the reliability of the wind turbine tower is affected by various factors, such as extreme weather (strong winds, snow, lightning, and heavy rain), load stress, tilt, and service time. Currently, the monitoring of the reliability of existing wind turbine towers mainly relies on periodic macroscopic inspections or the installation of strain gauges on the tower. This method suffers from limited data types, lacks multi-dimensional data fusion analysis and evaluation, and is prone to false alarms or omissions, resulting in low accuracy in reliability assessment. Summary of the Invention

[0003] The purpose of this invention is to provide a method, system, electronic equipment, and medium for assessing the reliability of wind turbine towers, thereby solving the problem of low accuracy in existing wind turbine tower reliability assessments.

[0004] The specific solution of the present invention is as follows:

[0005] A method for assessing the reliability of wind turbine towers includes:

[0006] Obtain different weather data information, and obtain the cumulative damage coefficient of weather fatigue based on the different weather data information;

[0007] The load stress is collected in real time by a fiber optic strain sensor, and the load coefficient is obtained based on the load stress and the preset allowable stress.

[0008] The tilt angle is collected in real time by a tilt sensor, and the tilt coefficient is obtained by normalization based on the tilt angle and a preset tilt threshold.

[0009] Obtain the service time and design life of the wind turbine tower, and derive the life decay coefficient based on the service time and design life;

[0010] The reliability is obtained based on the cumulative damage coefficient due to weather fatigue, the load coefficient, the tilt coefficient, the life decay coefficient, and the preset weights for cumulative damage due to weather fatigue, the load weight, the tilt weight, and the life decay weight.

[0011] Preferably, the cumulative damage coefficient of weather fatigue is obtained based on different weather data information, including:

[0012] Different weather data include instantaneous wind speed, snow and ice coverage, number of lightning strikes, and rainfall;

[0013] A three-dimensional model of the wind turbine tower was constructed, and the fatigue life of the wind turbine tower under different weather conditions was obtained through a finite element simulation model based on the three-dimensional model of the wind turbine tower.

[0014] Based on instantaneous wind speed, snow and ice coverage, lightning frequency, rainfall, and fatigue life under different weather conditions, the cumulative damage coefficient of weather fatigue is obtained and updated.

[0015] Preferably, the cumulative damage coefficient due to weather fatigue includes:

[0016] Fatigue life under different weather conditions includes fatigue life under strong winds, snow and ice, lightning, and heavy rain.

[0017] The fatigue cycles of wind speed, snow and ice coverage, lightning strikes per unit time, and rainfall were obtained based on instantaneous wind speed, snow and ice coverage, lightning strikes per unit time, and rainfall, respectively.

[0018] Based on the fatigue life of strong winds, snow and ice, lightning, heavy rain, snow and ice fatigue cycles, wind speed fatigue cycles, lightning fatigue cycles, and rainfall fatigue cycles, the cumulative fatigue damage coefficient of weather is obtained through a fatigue cumulative damage model.

[0019] Preferably, the number of wind speed fatigue cycles is obtained, including:

[0020] Instantaneous wind speed and effective wind speed duration are collected in real time using an ultrasonic anemometer. The instantaneous wind speed is compared with a preset wind speed threshold. When the instantaneous wind speed is greater than the wind speed threshold, the number of wind speed fatigue cycles is obtained based on the instantaneous wind speed, effective wind speed duration, and a preset wind speed fatigue cycle coefficient. When the instantaneous wind speed is less than or equal to the wind speed threshold, there is no number of wind speed fatigue cycles.

[0021] Preferably, the formula for calculating the tilt coefficient is:

[0022] ,

[0023] in, The tilt coefficient; Indicates the degree of inclination; is the tilt threshold; n is the preset correction coefficient.

[0024] The preferred formula for calculating reliability is:

[0025] ,

[0026] in, For reliability; The cumulative damage coefficient due to weather fatigue; For load factor; The tilt coefficient; This is the lifetime degradation coefficient; Weighting of accumulated damage due to weather fatigue; For load weights; For skewed weights; Weighted by lifetime decay; .

[0027] Preferably, it also includes the step of generating a reliability level based on the reliability level and issuing maintenance warnings based on the reliability level, specifically including:

[0028] When the reliability is greater than the first threshold, the reliability level is the first level, and the system will operate normally and be continuously monitored.

[0029] When the reliability is less than or equal to the first threshold and greater than the second threshold, the reliability level is the second level, and the system will operate normally and conduct regular checks and warnings.

[0030] When the reliability is less than or equal to the second threshold and greater than the third threshold, the reliability level is the third level. In this case, monitoring should be strengthened and preparations for maintenance and early warning should be made.

[0031] When the reliability is less than or equal to the third threshold and greater than the fourth threshold, the reliability level is the fourth level, then power operation is restricted and a planned maintenance warning is issued.

[0032] When the reliability is less than or equal to the fourth threshold, the reliability level is the fifth level, and an emergency shutdown is initiated for immediate inspection and early warning.

[0033] This invention also relates to a wind turbine tower reliability assessment system, used in the aforementioned wind turbine tower reliability assessment method, comprising:

[0034] The data acquisition module is used to collect real-time data on instantaneous wind speed, snow and ice coverage, lightning strikes, rainfall, load stress, and tilt.

[0035] The weather fatigue cumulative damage coefficient generation module is used to obtain the weather fatigue cumulative damage coefficient based on different weather data information;

[0036] The load factor generation module is used to obtain the load factor based on the load stress and the preset allowable stress.

[0037] The tilt coefficient generation module is used to obtain the tilt coefficient through normalization based on the tilt degree and a preset tilt threshold.

[0038] The service attenuation coefficient generation module is used to obtain the service time and design life of the wind turbine tower, and to obtain the service attenuation coefficient based on the service time and design life.

[0039] The reliability generation module is used to obtain the reliability based on the weather fatigue cumulative damage coefficient, load coefficient, tilt coefficient, life decay coefficient, and preset weather fatigue cumulative damage weight, load weight, tilt weight and life decay weight.

[0040] The reliability level and maintenance early warning generation module is used to generate reliability levels based on reliability and to issue maintenance early warnings based on the reliability levels.

[0041] The present invention also relates to an electronic device, comprising: a processor and a memory; the memory for storing executable instructions of the processor, the processor being configured to execute the aforementioned wind turbine tower reliability assessment method by executing the executable instructions.

[0042] The present invention also relates to a computer storage medium storing a computer program, which, when executed by a processor, implements the aforementioned method for assessing the reliability of wind turbine towers.

[0043] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0044] 1. By using weather fatigue cumulative damage coefficient, load coefficient, tilt coefficient, and life decay coefficient to obtain reliability, the multi-source data of wind turbine tower reliability is fully integrated, which greatly reduces false alarms and missed alarms, improves the accuracy of reliability assessment, and effectively improves safety and operating efficiency.

[0045] 2. By generating reliability levels based on reliability and issuing maintenance warnings based on these reliability levels, managers can quickly and intuitively grasp the safety status of wind turbine towers, carry out maintenance effectively and promptly, improve response speed, ensure safe operation, and enhance management level. Attached Figure Description

[0046] Figure 1 This is a flowchart of a wind turbine tower reliability assessment method according to an embodiment of the present invention.

[0047] Figure 2 This is a flowchart illustrating the process of obtaining the cumulative damage coefficient due to weather fatigue in an embodiment of the present invention.

[0048] Figure 3 This is a block diagram of a wind turbine tower reliability assessment system according to an embodiment of the present invention. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0050] A method for assessing the reliability of wind turbine towers, such as Figure 1 As shown, it includes the following steps:

[0051] S1. Obtain different weather data information and obtain the cumulative damage coefficient of weather fatigue based on the different weather data information;

[0052] S11. Obtain the dimensions of the wind turbine tower and the connection relationships of each component. Based on the dimensions of the wind turbine tower and the connection relationships of each component, construct a three-dimensional model of the wind turbine tower. Based on the three-dimensional model of the wind turbine tower, obtain the fatigue life of the wind turbine tower under different weather conditions through a finite element simulation model.

[0053] Different weather conditions include windy weather, snowy weather, thunderstorms, and heavy rain.

[0054] Fatigue life under different weather conditions, including fatigue life under strong winds Fatigue life of ice and snow Lightning fatigue life Fatigue life during heavy rain .

[0055] S12. Based on real-time collected instantaneous wind speed, snow and ice coverage, lightning strikes, rainfall, and fatigue life under different weather conditions, the cumulative damage coefficient of weather fatigue is obtained and updated.

[0056] The cumulative damage coefficient due to weather fatigue is obtained, such as Figure 2 As shown, it specifically includes:

[0057] S121. Collect instantaneous wind speed and effective wind speed duration, and obtain the number of wind speed fatigue cycles based on instantaneous wind speed, effective wind speed duration and preset wind speed fatigue cycle coefficient;

[0058] Instantaneous wind speed and effective wind speed duration are collected in real time using an ultrasonic anemometer installed on the wind turbine tower. A wind speed fatigue cycle coefficient is set based on the material of the wind turbine tower. The instantaneous wind speed is compared with a preset wind speed threshold. When the instantaneous wind speed is greater than the wind speed threshold, it indicates that the wind speed has an impact on the wind turbine tower. The number of wind speed fatigue cycles is then obtained based on the instantaneous wind speed, effective wind speed duration, and wind speed fatigue cycle coefficient. When the instantaneous wind speed is less than or equal to the wind speed threshold, it indicates that the wind speed has no impact on the wind turbine tower. Therefore, there is no number of wind speed fatigue cycles.

[0059] The formula for calculating the number of wind speed fatigue cycles is:

[0060] ,

[0061] in, This represents the number of wind speed fatigue cycles. The wind speed fatigue cycle coefficient; Instantaneous wind speed, in m / s; The effective wind speed duration is expressed in hours (h).

[0062] S122. Collect the ice and snow cover thickness and coverage duration, and obtain the number of ice and snow fatigue cycles based on the instantaneous wind speed, ice and snow cover thickness, coverage duration and preset ice and snow fatigue coefficient.

[0063] The thickness and duration of ice and snow cover are collected in real time by microwave icing sensors installed on the wind turbine tower. An ice and snow fatigue coefficient is set based on the increased load on the wind turbine tower caused by the ice and snow. The formula for calculating the number of ice and snow fatigue cycles is as follows:

[0064] ,

[0065] in, This represents the current number of ice and snow fatigue cycles. The fatigue coefficient for ice and snow; This refers to the thickness of the snow and ice cover, expressed in cm. Coverage duration, in hours (h); Instantaneous wind speed, in m / s.

[0066] S123. Collect the number of lightning strikes and the peak lightning current per unit time, and obtain the number of lightning fatigue cycles based on the collected number of lightning strikes, the peak lightning current and the preset lightning fatigue coefficient.

[0067] The lightning fatigue cycle count is calculated by real-time data collection of the number of lightning strikes and peak lightning current per unit time using a lightning locator installed on the wind turbine tower.

[0068] ,

[0069] in, This represents the number of lightning fatigue cycles. This refers to the lightning fatigue coefficient. The number of lightning strikes per unit time; This represents the peak lightning current, measured in kA.

[0070] S124. Collect rainfall and rainfall duration, and obtain the number of rainfall fatigue cycles based on rainfall, rainfall duration, and rainfall fatigue coefficient;

[0071] Rainfall and duration are collected in real time by a laser raindrop spectrometer installed on the wind turbine tower. A rainfall fatigue coefficient is set based on the principle that rainwater corrosion accelerates weld fatigue. The rainfall is compared with a preset rainfall threshold. When the rainfall is greater than the threshold, it indicates that the rainfall has an impact on the wind turbine tower. The number of rainfall fatigue cycles is then calculated based on the rainfall, duration, and rainfall fatigue coefficient. When the rainfall is less than or equal to the threshold, it indicates that the rainfall has no impact on the wind turbine tower. In this case, no rainfall fatigue cycle count is calculated.

[0072] The formula for calculating the number of rainfall fatigue cycles is:

[0073] ,

[0074] in, This represents the current number of rainfall fatigue cycles. The fatigue coefficient is determined by rainfall. Rainfall amount, in mm; The duration of rainfall is expressed in hours (h).

[0075] S125. Based on the fatigue life of strong winds, snow and ice, lightning, rainstorms, wind speed fatigue cycles, snow and ice fatigue cycles, lightning fatigue cycles, and rainfall fatigue cycles, the cumulative fatigue damage coefficient of weather is obtained through a fatigue cumulative damage model.

[0076] The formula for calculating the cumulative damage coefficient due to weather fatigue is:

[0077] ,

[0078] in, The cumulative damage coefficient due to weather fatigue; For fatigue life under strong winds; For ice and snow fatigue life; Lightning fatigue life; For fatigue life due to heavy rain; This represents the number of wind speed fatigue cycles. This represents the number of cycles of fatigue caused by ice and snow. This represents the number of lightning fatigue cycles. This refers to the number of rainfall fatigue cycles; The preset wind speed weight; The preset ice and snow weights; The preset lightning weight; The preset rainfall weights; .

[0079] The wind speed weight represents the influence of wind speed on the cumulative damage coefficient of weather fatigue. Generally, wind speed has a significant impact on the cumulative damage coefficient of weather fatigue, so the wind speed weight can be 0.6-0.7. The snow and ice weight represents the influence of snow and ice on the cumulative damage coefficient of weather fatigue. Generally, snow and ice have a moderate impact on the cumulative damage coefficient of weather fatigue, so the snow and ice weight is lower than the wind speed weight, and the snow and ice weight can be 0.2-0.25. The lightning weight represents the influence of lightning on the cumulative damage coefficient of weather fatigue. Generally, lightning has a slightly lower impact on the cumulative damage coefficient of weather fatigue, so the lightning weight is lower than the snow and ice weight, and the lightning weight can be 0.5-0.1. The rainfall weight represents the influence of rainfall on the cumulative damage coefficient of weather fatigue. Generally, rainfall has a very low impact on the cumulative damage coefficient of weather fatigue, so the rainfall weight is lower than the lightning weight, and the rainfall weight can be less than 0.5. The weights of wind speed, snow and ice, lightning, and rainfall can be adjusted according to the region where the wind turbine tower is located. For example, in high-altitude, snowy areas, the snow and ice weight is increased.

[0080] The higher the cumulative damage coefficient due to weather fatigue, the greater the damage to the wind turbine tower caused by the weather.

[0081] The updated formula for the cumulative damage coefficient due to weather fatigue is:

[0082] ,

[0083] in, The updated cumulative damage coefficient for weather fatigue; For fatigue life under strong winds; For ice and snow fatigue life; Lightning fatigue life; For fatigue life due to heavy rain; This represents the number of wind speed fatigue cycles before the update. This represents the number of ice and snow fatigue cycles before the update. This represents the number of lightning fatigue cycles before the update. This represents the number of rainfall fatigue cycles before the update. This represents the current number of fatigue cycles at wind speed. This represents the current number of ice and snow fatigue cycles. This represents the current number of lightning fatigue cycles. This represents the current number of rainfall fatigue cycles; Weighted by wind speed; Weighting for ice and snow; Lightning weight; The weight is determined by rainfall.

[0084] By accumulating fatigue damage under extreme weather conditions such as strong winds, snow, lightning, and heavy rain, the cumulative weather fatigue damage coefficient is obtained, and the fusion of multiple extreme weather data can effectively improve the accuracy of wind turbine tower reliability assessment. By iteratively updating the cumulative weather fatigue damage coefficient, the cumulative damage can be quantified.

[0085] S2. Load stress is collected in real time by fiber optic strain sensor, and load coefficient is obtained based on load stress and preset allowable stress.

[0086] Since the load capacity of the wind turbine tower exceeds its yield strength, it will cause the wind turbine tower to crack or even break directly, resulting in a safety accident, it is necessary to monitor the load stress in real time.

[0087] The load stress is monitored in real time by fiber optic strain sensors installed on the wind turbine tower, and the load coefficient is obtained based on the load stress and the preset allowable stress.

[0088] The formula for calculating the load factor is:

[0089] ,

[0090] in, For load factor, For load stress, Allowable stress.

[0091] S3. The tilt angle is collected in real time by the tilt sensor, and the tilt coefficient is obtained by normalization based on the tilt angle and the preset tilt threshold.

[0092] If the tilt of the wind turbine tower is too large, exceeding the designed tilt threshold, it will reduce the stability of the wind turbine tower, causing the wind turbine on the tower to become unbalanced and fall off. Therefore, it is necessary to monitor the tilt of the wind turbine tower in real time to ensure its stability.

[0093] The tilt angle is monitored in real time by tilt sensors installed on the wind turbine tower. The tilt coefficient is obtained by normalization based on the tilt angle and a preset tilt threshold.

[0094] The formula for calculating the tilt coefficient is:

[0095] ,

[0096] in, The tilt coefficient; Indicates the degree of inclination; is the tilt threshold; n is the preset correction coefficient, usually 2.

[0097] S4. Obtain the service time and design life of the wind turbine tower. Based on the service time and design life, obtain the life decay coefficient. The formula for calculating the life decay coefficient is:

[0098] ,

[0099] in, This is the lifespan degradation coefficient. For service time, For design lifespan.

[0100] As wind turbine towers age, their material properties gradually degrade, structural strength decreases, and even if the surface appears intact, they may not provide sufficient support for the wind turbine, potentially leading to collapse or component falls. This can affect safety and operational efficiency, thus necessitating monitoring of the service life of wind turbine towers.

[0101] S5. The reliability is obtained based on the weather fatigue cumulative damage coefficient, load coefficient, tilt coefficient, life decay coefficient, and the preset weather fatigue cumulative damage weight, load weight, tilt weight and life decay weight.

[0102] The formula for calculating reliability is:

[0103] ,

[0104] in, For reliability; The cumulative damage coefficient due to weather fatigue; For load factor; The tilt coefficient; This is the lifetime degradation coefficient; Weighting of accumulated damage due to weather fatigue; For load weights; For skewed weights; Weighted by lifetime decay; .

[0105] Weather fatigue cumulative damage weight is the weight of the influence of weather fatigue cumulative damage coefficient on reliability; load weight is the weight of the influence of load on reliability; tilt weight is the weight of the influence of tilt coefficient on reliability; and lifetime decay weight is the weight of the influence of lifetime decay coefficient on reliability.

[0106] By using weather fatigue cumulative damage coefficient, load coefficient, tilt coefficient, and life decay coefficient to obtain reliability, the multi-source data on wind turbine tower reliability is fully integrated, which greatly reduces false alarms and missed alarms, improves the accuracy of reliability assessment, and effectively improves safety and operational efficiency.

[0107] S6. Generate reliability levels based on reliability and conduct maintenance warnings based on the reliability levels.

[0108] When the reliability is greater than the first threshold, the reliability level is Level 1, which indicates extremely high reliability. In this case, the system will operate normally and be continuously monitored. The first threshold is 0.9.

[0109] When the reliability is less than or equal to the first threshold and greater than the second threshold, the reliability level is the second level. The second level indicates high reliability, so the system will operate normally and undergo regular checks and warnings. The second threshold is 0.8.

[0110] When the reliability is less than or equal to the second threshold and greater than the third threshold, the reliability level is the third level, which indicates moderate reliability. In this case, monitoring should be strengthened and maintenance and early warning should be prepared. The third threshold is 0.7.

[0111] When the reliability is less than or equal to the third threshold and greater than the fourth threshold, the reliability level is the fourth level. The fourth level indicates low reliability, so power operation is limited and a planned maintenance warning is issued; the fourth threshold is 0.6.

[0112] When the reliability is less than or equal to the fourth threshold, the reliability level is the fifth level. The fifth level indicates extremely low reliability, so an emergency shutdown is required, and immediate maintenance and early warning are initiated.

[0113] By generating reliability levels based on reliability and issuing maintenance warnings based on these reliability levels, managers can quickly and intuitively grasp the safety status of wind turbine towers, carry out maintenance effectively and promptly, improve response speed, ensure safe operation, and enhance management level.

[0114] This invention also relates to a wind turbine tower reliability assessment system, used in the aforementioned wind turbine tower reliability assessment method, such as... Figure 3 As shown, it includes:

[0115] The data acquisition module is used to collect data in real time, such as instantaneous wind speed, snow and ice coverage, lightning strike frequency, rainfall, load stress, and tilt.

[0116] The weather fatigue cumulative damage coefficient generation module is used to acquire different weather data information and obtain the weather fatigue cumulative damage coefficient based on the different weather data information.

[0117] The weather fatigue cumulative damage coefficient generation module includes a fatigue life generation unit under different weather conditions and a weather fatigue cumulative damage coefficient generation unit. The fatigue life generation unit under different weather conditions is used to construct a three-dimensional model of the wind turbine tower and obtain the fatigue life of the wind turbine tower under different weather conditions through a finite element simulation model based on the three-dimensional model of the wind turbine tower. The weather fatigue cumulative damage coefficient generation unit is used to obtain the weather fatigue cumulative damage coefficient based on real-time collected instantaneous wind speed, snow and ice coverage, lightning frequency, rainfall, and fatigue life under different weather conditions, and at the same time update the weather fatigue cumulative damage coefficient.

[0118] The load factor generation module is used to obtain the load factor based on the load stress and the preset allowable stress.

[0119] The tilt coefficient generation module is used to obtain the tilt coefficient through normalization based on the tilt degree and a preset tilt threshold.

[0120] The service attenuation coefficient generation module is used to obtain the service time and design life of the wind turbine tower, and to obtain the service attenuation coefficient based on the service time and design life.

[0121] The reliability generation module is used to obtain the reliability based on the weather fatigue cumulative damage coefficient, load coefficient, tilt coefficient, life decay coefficient, and preset weather fatigue cumulative damage weight, load weight, tilt weight, and life decay weight.

[0122] The reliability level and maintenance early warning generation module is used to generate reliability levels based on reliability and to issue maintenance early warnings based on the reliability levels.

[0123] The present invention also relates to an electronic device, comprising: a processor and a memory; the memory for storing executable instructions of the processor, the processor being configured to execute the aforementioned wind turbine tower reliability assessment method by executing the executable instructions.

[0124] The present invention also relates to a computer storage medium storing a computer program, which, when executed by a processor, implements the aforementioned method for assessing the reliability of wind turbine towers.

[0125] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for assessing the reliability of wind turbine towers, characterized in that, include: Obtain different weather data information, and obtain the cumulative damage coefficient of weather fatigue based on the different weather data information; The load stress is collected in real time by a fiber optic strain sensor, and the load coefficient is obtained based on the load stress and the preset allowable stress. The tilt angle is collected in real time by a tilt sensor, and the tilt coefficient is obtained by normalization based on the tilt angle and a preset tilt threshold. Obtain the service time and design life of the wind turbine tower, and derive the life decay coefficient based on the service time and design life; The reliability is obtained based on the cumulative damage coefficient due to weather fatigue, the load coefficient, the tilt coefficient, the life decay coefficient, and the preset weights for cumulative damage due to weather fatigue, the load weight, the tilt weight, and the life decay weight.

2. The method for assessing the reliability of a wind turbine tower according to claim 1, characterized in that, The method of obtaining the cumulative damage coefficient of weather fatigue based on different weather data information includes: The various weather data include instantaneous wind speed, snow and ice coverage, number of lightning strikes, and rainfall. A three-dimensional model of the wind turbine tower was constructed, and the fatigue life of the wind turbine tower under different weather conditions was obtained through a finite element simulation model based on the three-dimensional model of the wind turbine tower. Based on instantaneous wind speed, snow and ice coverage, lightning frequency, rainfall, and fatigue life under different weather conditions, the cumulative damage coefficient of weather fatigue is obtained and updated.

3. The method for assessing the reliability of a wind turbine tower according to claim 2, characterized in that, The obtained cumulative damage coefficient due to weather fatigue includes: The fatigue life under different weather conditions includes fatigue life under strong winds, snow and ice, lightning, and heavy rain. The fatigue cycles of wind speed, snow and ice coverage, lightning strikes per unit time, and rainfall were obtained based on instantaneous wind speed, snow and ice coverage, lightning strikes per unit time, and rainfall, respectively. Based on the fatigue life of strong winds, snow and ice, lightning, heavy rain, snow and ice fatigue cycles, wind speed fatigue cycles, lightning fatigue cycles, and rainfall fatigue cycles, the cumulative fatigue damage coefficient of weather is obtained through a fatigue cumulative damage model.

4. The method for assessing the reliability of a wind turbine tower according to claim 3, characterized in that, The number of wind speed fatigue cycles obtained includes: Instantaneous wind speed and effective wind speed duration are collected in real time using an ultrasonic anemometer. The instantaneous wind speed is compared with a preset wind speed threshold. When the instantaneous wind speed is greater than the wind speed threshold, the number of wind speed fatigue cycles is obtained based on the instantaneous wind speed, effective wind speed duration, and a preset wind speed fatigue cycle coefficient. When the instantaneous wind speed is less than or equal to the wind speed threshold, there is no number of wind speed fatigue cycles.

5. The method for assessing the reliability of a wind turbine tower according to claim 1, characterized in that, The formula for calculating the tilt coefficient is: , in, The tilt coefficient; Indicates the degree of inclination; is the tilt threshold; n is the preset correction coefficient.

6. The method for assessing the reliability of a wind turbine tower according to claim 1, characterized in that, The formula for calculating the reliability is: , in, For reliability; The cumulative damage coefficient due to weather fatigue; For load factor; The tilt coefficient; This is the lifetime degradation coefficient; Weighting of accumulated damage due to weather fatigue; For load weights; For skewed weights; Weighted by lifetime decay; .

7. The method for assessing the reliability of a wind turbine tower according to claim 1, characterized in that, It also includes the steps of generating reliability levels based on reliability and issuing maintenance warnings based on the reliability levels, specifically including: When the reliability is greater than the first threshold, the reliability level is the first level, and the system will operate normally and be continuously monitored. When the reliability is less than or equal to the first threshold and greater than the second threshold, the reliability level is the second level, and the system will operate normally and conduct regular checks and warnings. When the reliability is less than or equal to the second threshold and greater than the third threshold, the reliability level is the third level. In this case, monitoring should be strengthened and preparations for maintenance and early warning should be made. When the reliability is less than or equal to the third threshold and greater than the fourth threshold, the reliability level is the fourth level, then power operation is restricted and a planned maintenance warning is issued. When the reliability is less than or equal to the fourth threshold, the reliability level is the fifth level, and an emergency shutdown is initiated for immediate inspection and early warning.

8. A wind turbine tower reliability assessment system, characterized in that, A method for assessing the reliability of a wind turbine tower as described in any one of claims 1-7, comprising: The data acquisition module is used to collect real-time data on instantaneous wind speed, snow and ice coverage, lightning strikes, rainfall, load stress, and tilt. The weather fatigue cumulative damage coefficient generation module is used to obtain the weather fatigue cumulative damage coefficient based on different weather data information; The load factor generation module is used to obtain the load factor based on the load stress and the preset allowable stress. The tilt coefficient generation module is used to obtain the tilt coefficient through normalization based on the tilt degree and a preset tilt threshold. The service attenuation coefficient generation module is used to obtain the service time and design life of the wind turbine tower, and to obtain the service attenuation coefficient based on the service time and design life. The reliability generation module is used to obtain the reliability based on the weather fatigue cumulative damage coefficient, load coefficient, tilt coefficient, life decay coefficient, and preset weather fatigue cumulative damage weight, load weight, tilt weight and life decay weight. The reliability level and maintenance early warning generation module is used to generate reliability levels based on reliability and to issue maintenance early warnings based on the reliability levels.

9. An electronic device, characterized in that, include: Processor and memory; The memory is used to store executable instructions of the processor, which is configured to execute the wind turbine tower reliability assessment method according to any one of claims 1-7 by executing the executable instructions.

10. A computer storage medium, characterized in that: The computer storage medium stores a computer program, which, when executed by a processor, implements a wind turbine tower reliability assessment method according to any one of claims 1-7.

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