Fault diagnosis method, system and storage medium for a wind power blade connector

Abstract

The present invention provides a fault diagnosis method, system and storage medium for a wind turbine blade connecting member. The method includes the following steps: measuring axial stress data of the wind turbine blade connecting member in a wind turbine through a sensor; obtaining operation data of a wind turbine in the wind turbine; determining a stress data screening condition based on the operation data; screening at least two target axial stress data of different time periods from the axial stress data according to the stress data screening condition; calculating stress data difference values of the wind turbine blade connecting member in each of the time periods based on the target axial stress data; and analyzing a fault type of the wind turbine blade connecting member according to a change characteristic of the stress data difference values in all the time periods. The present invention has the effect of being able to diagnose faults of the wind turbine blade connecting member in a timely and accurate manner.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind turbines, and particularly relates to a fault diagnosis method, system and storage medium for a wind power blade connector. Background Art

[0002] Wind power generation is an important way to large-scale utilize renewable new energy. With the rapid development of the global wind power industry, the installed scale and single-unit capacity of wind turbines are also continuously expanding. The wind power blades in a wind turbine are the core components for capturing wind energy. The wind power blades are connected to the wind turbine hub through wind power blade connectors. During the operation of the wind turbine, the connectors play a crucial role. If the connector breaks during the normal operation of the unit, there will be abnormal noises in the unit or the broken part of the connector will smash and damage the pitch control cabinet, resulting in related communication failures in the pitch system, and then the unit will recognize the pitch communication failure and shut down. If the faulty connector is not maintained and replaced in time, the blades of the unit will be damaged or broken, which can easily lead to the failure or damage of the wind turbine.

[0003] The stress conditions of the wind power blade connectors during the operation of the wind turbine are complex and changeable. Therefore, real-time monitoring and fault diagnosis of wind power blade connectors under complex working conditions have very important practical significance. At present, for the fault diagnosis of the connectors at the connection between the blades and the hub of a wind power generation unit, the method of manual regular inspection is usually adopted. Technicians conduct regular inspections every six months and visually observe whether the connectors are broken or damaged. However, the method of manual regular inspection not only requires a lot of manpower, but also can only observe the condition of the connectors with the naked eye. If there are no problems on the surface of the connectors, but there are cracks inside, it is very difficult to diagnose the faults, resulting in inaccurate diagnosis results. Summary of the Invention

[0004] The present invention provides a fault diagnosis method, system and storage medium for a wind power blade connector to solve the problem of inaccurate diagnosis results when manually diagnosing wind power blade connectors.

[0005] In a first aspect, the present invention provides a fault diagnosis method for a wind power blade connector, and the method includes the following steps:

[0006] Measure the axial stress data of the wind power blade connector in the wind turbine through a sensor;

[0007] Obtain the operation data of the wind turbine in the wind turbine;

[0008] Determine the stress data screening conditions based on the operation data;

[0009] Screen out the target axial stress data for at least two different time periods from the axial stress data according to the stress data screening conditions;

[0010] Based on the target axial stress data, calculate the stress data difference values of the wind turbine blade connectors in each of the time periods;

[0011] Analyze and obtain the fault types of the wind turbine blade connectors according to the change characteristics of the stress data difference values in all the time periods.

[0012] Optionally, the operating data includes tangential wind speed, pitch angle, rotation frequency, and rotation period.

[0013] Optionally, the determining the stress data screening conditions based on the operating data includes the following steps:

[0014] Determine the minimum time period length of the screening time period according to the rotation period, and the minimum time period length is greater than or equal to the rotation period;

[0015] Combine the average wind speed of the tangential wind speed and the pitch angle in the screening time period to determine the working condition screening conditions, and the working condition screening conditions are that the average wind speed and the pitch angle in all the screening time periods are the same;

[0016] Calculate the data screening frequency based on the rotation frequency;

[0017] Combine the minimum time period length, the working condition screening conditions, and the data screening frequency to determine the stress data screening conditions.

[0018] Optionally, the stress data difference values include static load stress difference value, dynamic load stress average difference value, dynamic load stress amplitude difference value, and dynamic load stress frequency difference value.

[0019] Optionally, the wind turbine blade connectors include fastening connectors, hub connectors, and blade connectors. The analyzing and obtaining the fault types of the wind turbine blade connectors according to the change characteristics of the stress data difference values in all the time periods includes the following steps:

[0020] Judge whether the static load stress difference value changes;

[0021] If the static load stress difference value remains unchanged, then judge whether the dynamic load stress frequency difference value changes;

[0022] If the dynamic load stress frequency difference value remains unchanged, then judge whether both the dynamic load stress average difference value and the dynamic load stress amplitude difference value are the same as the static load stress difference value;

[0023] If both the average difference value of the dynamic load stress and the difference value of the dynamic load stress amplitude are the same as the static load stress difference value, it is determined that the fault type of the wind turbine blade connector is damage to the blade connector.

[0024] Optionally, the method further includes the following steps:

[0025] If the static load stress difference value changes, it is determined whether the static load stress difference value decreases;

[0026] If the static load stress difference value decreases, it is determined whether the static load stress difference value is 0;

[0027] If the static load stress difference value is not 0, it is determined whether both the average difference value of the dynamic load stress and the difference value of the dynamic load stress amplitude decrease;

[0028] If both the average difference value of the dynamic load stress and the difference value of the dynamic load stress amplitude decrease, it is determined whether the dynamic load stress frequency difference value changes;

[0029] If the dynamic load stress difference value remains unchanged, it is determined that the fault type is damage to the blade connector or damage to the fastening connector.

[0030] Optionally, the method further includes the following steps:

[0031] If the static load stress difference value is 0, it is determined whether the average difference value of the dynamic load stress, the difference value of the dynamic load stress amplitude, and the dynamic load stress frequency difference value are all 0;

[0032] If the average difference value of the dynamic load stress, the difference value of the dynamic load stress amplitude, and the dynamic load stress frequency difference value are all 0, it is determined that the fault type is damage to the hub connector.

[0033] Optionally, the sensor is an ultrasonic sensor, a resistive strain sensor, or a fiber Bragg grating strain sensor.

[0034] In a second aspect, the present invention further provides a fault diagnosis system for a wind turbine blade connector, the system including:

[0035] A stress data acquisition module, configured to measure the axial stress data of the wind turbine blade connector in the wind turbine through a sensor;

[0036] An operating data acquisition module, configured to acquire the operating data of the wind turbine in the wind turbine;

[0037] A condition generation module, configured to determine stress data screening conditions according to the operating data;

[0038] A data screening module, configured to screen out target axial stress data of at least two different time periods from the axial stress data according to the stress data screening condition;

[0039] A difference value calculation module, configured to calculate the stress data difference value of the wind turbine blade connector in each of the time periods according to the target axial stress data;

[0040] A fault diagnosis module, configured to analyze and obtain the fault type of the wind turbine blade connector according to the change characteristics of the stress data difference value in all the time periods.

[0041] In a third aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0042] The beneficial effects of the present invention are:

[0043] First, the axial stress data of the wind turbine blade connector in the wind turbine is measured by a sensor, and then the operation data of the wind turbine in the wind turbine is obtained, and the stress data screening condition is determined based on the operation data. The stress data screening condition can be used to screen out the target axial stress data of different time periods but with the same operating conditions from the axial stress data. Thus, the stress data difference value is calculated according to the target axial stress data in different time periods, and finally the fault type of the wind turbine blade connector is analyzed and diagnosed according to the change characteristics of the stress data difference value. Compared with the manual fault diagnosis method, it can not only save manpower, but also has higher efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic flowchart of a fault diagnosis method for a wind turbine blade connector in one embodiment of the present application.

[0045] Figure 2 It is a schematic cross-sectional view of a wind turbine blade connector in one embodiment of the present application.

[0046] Figure 3 It is a system structure diagram of a fault diagnosis system for a wind turbine blade connector in one embodiment of the present application.

[0047] DESCRIPTION OF THE REFERENCE NUMERALS:

[0048] 1, sensor; 2, fastening connector; 3, hub connector; 4, blade connector; 5, blade structural member; 6, hub structural member. DETAILED DESCRIPTION

[0049] The present invention discloses a fault diagnosis method for a wind turbine blade connector.

[0050] Reference Figure 1 , the fault diagnosis method of the wind turbine blade connector specifically includes the following steps:

[0051] S101. Measure the axial stress data of the wind turbine blade connector in the wind turbine through sensors.

[0052] Among them, through stress measurement sensors in the forms of acoustic emission, strain gauges, and optical conduction, the axial stress data of the wind turbine blade connector in the wind turbine are measured in real time, and the change of the time-continuous axial stress data is used as the basis for judging the connector fault. Among them, the sensor corresponding to the acoustic emission form is an ultrasonic sensor, the sensor corresponding to the strain gauge form is usually a resistive strain sensor, and the sensor corresponding to the optical conduction form is usually a fiber Bragg grating strain sensor. The sensor collects the strain data of the wind turbine blade connector, and then converts it into the axial stress data of the axial stress received by the connector according to the calibration test of the connector.

[0053] S102. Obtain the operation data of the wind turbine in the wind turbine.

[0054] Among them, all the operation data of the wind turbine are stored in the storage module of the control center, and the operation data can be called from the storage module. The operation data includes the tangential wind speed, pitch angle, rotation frequency, and rotation period. The tangential wind speed refers to the flow rate of the wind in front of the wind turbine, that is, the wind speed when the wind passes through the leading edge of the wind turbine. The power generation capacity of the wind turbine has a great relationship with the tangential wind speed. Therefore, in the site selection and design of the wind turbine, the tangential wind speed is a very important parameter.

[0055] The pitch angle of the wind turbine blade refers to the rotation angle of the wind turbine blade relative to its axis, which is used to adjust the incoming and outgoing wind angles of the blade to control the amount of wind captured by the blade. When the pitch angle of the wind turbine blade increases, the area of the blade facing the wind becomes larger, thereby improving the wind energy conversion efficiency; conversely, when the pitch angle decreases, the area of the blade facing the wind becomes smaller, thereby reducing the wind energy conversion efficiency, and at the same time, the rotation speed of the wind turbine can be reduced to protect the safety of the wind turbine.

[0056] The rotation frequency of the wind turbine refers to the number of rotations per second, with the unit of Hz (Hertz), and can also be expressed in RPM (revolutions per minute). The higher the rotation frequency, the greater the power generation capacity of the wind turbine. The rotation period refers to the time required for the wind turbine to complete one rotation, usually expressed in seconds (s). The relationship between the rotation period and the rotation frequency is: rotation period = 1 / rotation frequency. For example, if the rotation frequency of the wind turbine is 1 Hz, then its rotation period is 1 second. The shorter the rotation period, the higher the power generation efficiency of the wind turbine.

[0057] S103. Determine the stress data screening conditions based on the operation data.

[0058] Among them, since the sensor can continuously measure the wind turbine blade connectors and obtain time - continuous axial stress data, which can be stored in real - time after software processing. If all the data is used for fault analysis, the efficiency of fault analysis will be greatly reduced, and the analysis result is also easily interfered by irrelevant data, thus leading to a decrease in the accuracy of fault diagnosis. Therefore, in order to improve the analysis efficiency and accuracy of fault diagnosis, it is necessary to select appropriate data from a large amount of axial stress data for analysis. The stress data screening conditions for axial stress data can be determined according to the operation data of the wind turbine.

[0059] S104. Screen out the target axial stress data of at least two different time periods from the axial stress data according to the stress data screening conditions.

[0060] Among them, to ensure the accuracy and reliability of fault diagnosis, the target axial stress data in different time periods but under the same working conditions can be screened out according to the stress data screening conditions, so as to analyze the force change of the wind turbine blade connectors based on the target axial stress data in different time periods, providing a basis for the fault diagnosis of the wind turbine blade connectors.

[0061] S105. Calculate the stress data difference values of the wind turbine blade connectors in each time period based on the target axial stress data.

[0062] Among them, the stress data difference values include the static load stress difference value, the average dynamic load stress difference value, the dynamic load stress amplitude difference value, and the dynamic load stress frequency difference value. The static load stress difference value is the absolute value of the difference between the stress values in different time periods when the wind turbine blade is in a static state. The average dynamic load stress difference value is the absolute value of the difference between the average stress values in different time periods when the wind turbine blade is in a moving state. The dynamic load stress amplitude difference value is the absolute value of the difference between the maximum and minimum stress values in a time period when the wind turbine blade is in a moving state. The dynamic load stress frequency difference value is the absolute value of the difference between the stress fluctuation period values in different time periods when the wind turbine blade is in a moving state. The stress fluctuation is generated by the rotation of the blade and is in the same period as the blade rotation period.

[0063] S106. Analyze and obtain the fault type of the wind turbine blade connectors according to the change characteristics of the stress data difference values in all time periods.

[0064] The implementation principle of this embodiment is:

[0065] Axial stress data of the wind turbine blade connector is measured by a sensor. Then, the operation data of the wind turbine in the wind power generator is obtained, and stress data screening conditions are determined based on the operation data. The stress data screening conditions can be used to screen out target axial stress data with the same operating conditions but in different time periods from the axial stress data. Thus, the stress data difference value is calculated based on the target axial stress data in different time periods, and finally, the fault type of the wind turbine blade connector is analyzed and diagnosed according to the change characteristics of the stress data difference value. Compared with the manual fault diagnosis method, it can not only save manpower, but also has higher efficiency and accuracy.

[0066] In one implementation manner, step S103, that is, determining the stress data screening conditions based on the operation data, specifically includes the following steps:

[0067] Determine the minimum time period length of the screening time period according to the rotation period, and the minimum time period length is greater than or equal to the rotation period;

[0068] Combine the average wind speed of the tangential wind speed and the pitch angle within the screening time period to determine the working condition screening conditions, and the working condition screening conditions are that the average wind speed and the pitch angle are the same within all screening time periods;

[0069] Calculate the data screening frequency based on the rotation frequency;

[0070] Combine the minimum time period length, the working condition screening conditions and the data screening frequency to determine the stress data screening conditions.

[0071] In this implementation manner, the stress change period of the wind turbine blade connector is the same as the period of one rotation of the blade, and the period of one rotation of the blade is the same as the rotation period of the wind turbine. Therefore, for the comprehensiveness of data during the data screening process, the minimum time period length of the screening time period during data screening should be greater than or equal to the rotation period. The significance of screening axial stress data in multiple different time periods is to conduct multi-time period data comparison to diagnose faults based on the comparison results. Therefore, it is necessary to ensure that the background conditions of different time periods are the same, that is, the working condition screening conditions need to be met. The data screening frequency can be calculated by F = f / 6, where F is the data screening frequency and f is the rotation frequency. At this time, the data screening frequency is the minimum value, and the data screening frequency can also be other values, but it must satisfy F≥f / 6.

[0072] In one implementation manner, referring to Figure 2 , the wind turbine blade connector includes a fastening connector, a hub connector and a blade connector. The blade connector is embedded inside the blade structural member, and the fastening connector passes through the hub structural member and is threadedly connected to the blade connector, so that the hub structural member and the blade structural member are tightly connected, and the hub connector plays a reinforcing role.

[0073] In this embodiment, step S106, that is, analyzing the fault type of the wind turbine blade connector based on the variation characteristics of the stress data difference value in all time periods, specifically includes the following steps:

[0074] Judge whether the static load stress difference value changes;

[0075] If the static load stress difference value remains unchanged, then judge whether the dynamic load stress frequency difference value changes;

[0076] If the dynamic load stress frequency difference value remains unchanged, then judge whether both the dynamic load stress average difference value and the dynamic load stress amplitude difference value are the same as the static load stress difference value;

[0077] If both the dynamic load stress average difference value and the dynamic load stress amplitude difference value are the same as the static load stress difference value, then determine that the fault type of the wind turbine blade connector is damage to the blade connector.

[0078] In this embodiment, through the above fault judgment conditions, it can be concluded that if the static load stress difference value and the dynamic load stress frequency difference value do not change in multiple different time periods under the same working conditions, and both the dynamic load stress average difference value and the dynamic load stress amplitude difference value are the same as the static load stress difference value, then it can be determined that the wind turbine blade connector has a fault, and the fault type is damage to the blade connector. The specific damage situation is that the blade connector is disengaged from the blade structural member. In this embodiment, if the judgment result of judging whether the static load stress difference value changes is that the static load stress difference value changes, then continue to execute the following steps:

[0079] Judge whether the static load stress difference value decreases;

[0080] If the static load stress difference value decreases, then judge whether the static load stress difference value is 0;

[0081] If the static load stress difference value is not 0, then judge whether both the dynamic load stress average difference value and the dynamic load stress amplitude difference value decrease;

[0082] If both the dynamic load stress average difference value and the dynamic load stress amplitude difference value decrease, then judge whether the dynamic load stress frequency difference value changes;

[0083] If the dynamic load stress difference value remains unchanged, then determine that the fault type is damage to the blade connector or damage to the fastening connector.

[0084] In this embodiment, based on the above fault judgment conditions, it can be concluded that the static load stress difference value shows a decreasing change in multiple different time periods under the same working conditions, but does not decrease to 0. The average dynamic load stress difference value and the amplitude dynamic load stress difference value also show decreasing changes in multiple different time periods under the same working conditions, while the dynamic load stress frequency difference value remains unchanged. Then, it can be determined that a fault has occurred in the wind turbine blade connection component, and the fault type is damage to the blade connection component or damage to the fastening connection component. If the blade connection component is damaged, the specific damage condition is that the blade connection component cracks in the direction perpendicular to the axial direction. If the fastening connection component is damaged, the specific damage condition is that the connection part between the fastening connection component and the blade connection component breaks, and / or the connection part between the fastening connection component and the hub connection component breaks. In this embodiment, if the judgment result of whether the static load stress difference value is 0 is that the static load stress difference value is 0, then continue to execute the following steps:

[0085] Judge whether the average dynamic load stress difference value, the amplitude dynamic load stress difference value, and the frequency dynamic load stress difference value are all 0;

[0086] If the average dynamic load stress difference value, the amplitude dynamic load stress difference value, and the frequency dynamic load stress difference value are all 0, then determine that the fault type is damage to the hub connection component.

[0087] In this embodiment, based on the above fault judgment conditions, it can be concluded that the static load stress difference value, the average dynamic load stress difference value, the amplitude dynamic load stress difference value, and the frequency dynamic load stress difference value are all 0. Then, it can be determined that a fault has occurred in the wind turbine blade connection component, and the fault type is damage to the hub connection component. The specific damage condition is that the hub connection component breaks axially.

[0088] The present invention also discloses a fault diagnosis system for a wind turbine blade connection component. The system includes:

[0089] A stress data acquisition module, configured to measure the axial stress data of the wind turbine blade connection component in the wind turbine through a sensor;

[0090] An operating data acquisition module, configured to acquire the operating data of the wind turbine in the wind turbine;

[0091] A condition generation module, configured to determine the stress data screening conditions according to the operating data;

[0092] A data screening module, configured to screen out at least two target axial stress data in different time periods from the axial stress data according to the stress data screening conditions;

[0093] A difference value calculation module, configured to calculate the stress data difference value of the wind turbine blade connection component in each time period according to the target axial stress data;

[0094] A fault diagnosis module, which is used to analyze and obtain the fault type of the wind turbine blade connector according to the change characteristics of the stress data difference value in all time periods.

[0095] The implementation principle of this embodiment is as follows:

[0096] Through program retrieval, the axial stress data of the wind turbine blade connector in the wind turbine can be measured by sensors first, and then the operation data of the wind turbine in the wind turbine can be obtained, and the stress data screening conditions can be determined based on the operation data. The stress data screening conditions can be used to screen out the target axial stress data with the same operating conditions in different time periods from the axial stress data. Thus, the stress data difference value can be calculated according to the target axial stress data in different time periods, and finally the fault type of the wind turbine blade connector can be analyzed and diagnosed according to the change characteristics of the stress data difference value. Compared with the manual fault diagnosis method, it can not only save manpower, but also has higher efficiency and accuracy.

[0097] The present invention also discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the fault diagnosis method for the wind turbine blade connector in the above embodiment are implemented.

[0098] The implementation principle of this embodiment is as follows:

[0099] Through program retrieval, the axial stress data of the wind turbine blade connector in the wind turbine can be measured by sensors first, and then the operation data of the wind turbine in the wind turbine can be obtained, and the stress data screening conditions can be determined based on the operation data. The stress data screening conditions can be used to screen out the target axial stress data with the same operating conditions in different time periods from the axial stress data. Thus, the stress data difference value can be calculated according to the target axial stress data in different time periods, and finally the fault type of the wind turbine blade connector can be analyzed and diagnosed according to the change characteristics of the stress data difference value. Compared with the manual fault diagnosis method, it can not only save manpower, but also has higher efficiency and accuracy.

[0100] Those of ordinary skill in the art should understand that the discussion of any above embodiment is only exemplary, and is not intended to imply that the protection scope of the present application is limited to these examples; under the idea of the present application, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations in different aspects of one or more embodiments in the present application as above. For the sake of brevity, they are not provided in detail.

[0101] One or more embodiments in the present application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the present application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of one or more embodiments in the present application shall be included within the protection scope of the present application.

Claims

1. A fault diagnosis method for a wind turbine blade connector, characterized in that, It includes the following steps: Measure the axial stress data of the wind turbine blade connector in the wind turbine through a sensor; Obtain the operation data of the wind turbine in the wind turbine; Determine the stress data screening conditions based on the operation data; Screen out the target axial stress data of at least two different time periods from the axial stress data according to the stress data screening conditions; Calculate the stress data difference values of the wind turbine blade connector in each of the time periods based on the target axial stress data; Analyze and obtain the fault type of the wind turbine blade connector according to the change characteristics of the stress data difference values in all the time periods; The operation data includes tangential wind speed, pitch angle, rotation frequency and rotation period; The determining the stress data screening conditions based on the operation data includes the following steps: Determine the minimum time period length of the screening time period according to the rotation period, and the minimum time period length is greater than or equal to the rotation period; Combine the average wind speed of the tangential wind speed and the pitch angle in the screening time period to determine the working condition screening conditions, and the working condition screening conditions are that the average wind speed and the pitch angle in all the screening time periods are the same; Calculate the data screening frequency based on the rotation frequency; Combine the minimum time period length, the working condition screening conditions and the data screening frequency to determine the stress data screening conditions.

2. The fault diagnosis method for a wind turbine blade connector according to claim 1, characterized in that, The stress data difference values include static load stress difference value, dynamic load stress average difference value, dynamic load stress amplitude difference value and dynamic load stress frequency difference value.

3. The fault diagnosis method for a wind turbine blade connector according to claim 2, characterized in that, The wind turbine blade connector includes a fastening connector, a hub connector and a blade connector. The analyzing and obtaining the fault type of the wind turbine blade connector according to the change characteristics of the stress data difference values in all the time periods includes the following steps: Judge whether the static load stress difference value changes; If the static load stress difference value does not change, then judge whether the dynamic load stress frequency difference value changes; If the dynamic load stress frequency difference value does not change, then judge whether both the dynamic load stress average difference value and the dynamic load stress amplitude difference value are the same as the static load stress difference value; If both the dynamic load stress average difference value and the dynamic load stress amplitude difference value are the same as the static load stress difference value, then determine that the fault type of the wind turbine blade connector is damage of the blade connector.

4. The fault diagnosis method for a wind turbine blade connector according to claim 3, characterized in that, The method further includes the following steps: If the static load stress difference value changes, then judge whether the static load stress difference value decreases; If the static load stress difference value decreases, then judge whether the static load stress difference value is 0; If the static load stress difference value is not 0, then judge whether both the dynamic load stress average difference value and the dynamic load stress amplitude difference value decrease; If both the dynamic load stress average difference value and the dynamic load stress amplitude difference value decrease, then judge whether the dynamic load stress frequency difference value changes; If the dynamic load stress difference value does not change, then determine that the fault type is damage of the blade connector or damage of the fastening connector.

5. The fault diagnosis method for a wind turbine blade connector according to claim 4, characterized in that, The method further includes the following steps: If the static load stress difference value is 0, determine whether the average dynamic load stress difference value, the dynamic load stress amplitude difference value, and the dynamic load stress frequency difference value are all 0; If the average dynamic load stress difference value, the dynamic load stress amplitude difference value, and the dynamic load stress frequency difference value are all 0, determine that the fault type is damage to the hub connector.

6. The fault diagnosis method for a wind turbine blade connector according to claim 1, characterized in that, The sensor is an ultrasonic sensor, a resistive strain sensor, or a fiber Bragg grating strain sensor.

7. A fault diagnosis system for a wind turbine blade connector, which is used to implement the fault diagnosis method for the wind turbine blade connector according to any one of claims 1-6, characterized in that, The system includes: A stress data acquisition module for measuring axial stress data of a wind turbine blade connector in a wind turbine through a sensor; An operating data acquisition module for acquiring operating data of a wind turbine in the wind turbine; A condition generation module for determining stress data screening conditions according to the operating data; A data screening module for screening at least two target axial stress data of different time periods from the axial stress data according to the stress data screening conditions; A difference value calculation module for calculating stress data difference values of the wind turbine blade connector in each of the time periods according to the target axial stress data; A fault diagnosis module for analyzing the fault type of the wind turbine blade connector according to the change characteristics of the stress data difference values in all the time periods.

8. A computer-readable storage medium, on which a computer program is stored, characterized in that, When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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