Method, system and equipment for monitoring abnormal operation state of wind turbine generator and medium

Abstract

The invention discloses a wind turbine generator abnormal operation state monitoring method, system and device and a medium, mainly relates to the technical field of wind turbine generator monitoring, and is used for solving the problem that the damage of a wind turbine generator cannot be effectively identified when the damage degree of the wind turbine generator is not serious in the existing scheme. Comprising the following steps: fitting to generate a standard wind speed-variable pitch position curve within a preset time period according to a wind speed and a variable pitch position in standard second-level acquisition data; when the wind turbine generator runs, acquiring effective second-level acquisition data from the real-time second-level acquisition data; storing the wind speed and the variable pitch position in the effective second-level acquisition data into a preset edge computing system; when the number of the wind speed and the variable pitch position in the preset edge calculation system reaches a preset fitting number, fitting to generate an actual wind speed-variable pitch position curve; and the deviation degree between the actual wind speed-variable pitch position curve and the standard wind speed-variable pitch position curve is compared, and when the deviation degree is larger than a preset deviation threshold value, a preset deviation degree warning program is started.

Description

Technical Field

[0001] The present application relates to the technical field of wind turbine monitoring, and in particular to a method, system, equipment and medium for monitoring abnormal operation status of a wind turbine. Background Art

[0002] Wind turbines will inevitably have abnormal damages such as blade material degradation, blade damage, and transmission chain problems due to long-term operation in complex environments. These problems may have a negative impact on the performance and reliability of wind turbines. However, when wind turbines are operating with problems, their operating characteristics are not obvious and difficult to identify effectively, which often causes more serious accidents of wind turbines. In order to identify the abnormal state of wind turbine blades as early as possible and nip safety accidents in the bud, wind turbines must be given the ability to autonomously and quickly identify abnormal states.

[0003] The existing means of monitoring abnormal conditions of wind turbines are mainly vibration monitoring, temperature monitoring, voltage and current monitoring, noise monitoring, etc. However, when faults such as material performance degradation of wind turbine blades, minor damage to blades, and minor damage to transmission chain components occur, these means are often unable to effectively identify them because the degree of damage is not serious. The operating status characteristics of early damaged units are not obvious and are often easily overlooked. After the unit runs with a fault for too long, the blade damage is aggravated, which may cause serious accidents.

[0004] Therefore, there is an urgent need for a method, system, device and medium for monitoring the abnormal operation status of a wind turbine generator set to solve the problem that existing solutions cannot effectively identify wind turbine generator set damage when the degree of damage to the wind turbine generator set is not serious. Summary of the invention

[0005] In view of the above-mentioned deficiencies in the prior art, the present application provides a method, system, device and medium for monitoring the abnormal operation status of a wind turbine generator set, so as to solve the problem that the existing solutions cannot effectively identify wind turbine generator set damage when the degree of damage to the wind turbine generator set is not serious.

[0006] In a first aspect, the present application provides a method for monitoring abnormal operation status of a wind turbine generator set, the method comprising: The second-level collected data related to the wind turbine in the preset time period is exported from the monitoring and data acquisition database; wherein the second-level collected data at least includes: wind speed, pitch position, power, power setting, and yaw error; based on power, power setting, and yaw error, the second-level collected data in the power-limited state and the yaw error greater than the preset yaw threshold are removed from all the second-level collected data to obtain the standard second-level collected data; according to the wind speed and pitch position in the standard second-level collected data, the standard wind speed-pitch position curve in the preset time period is fitted and generated; when the wind turbine is running, the wind speed-pitch position curve is calculated in real time. Acquire the second-level collected data of the wind turbine, and based on the power, power setting, and yaw error, obtain the effective second-level collected data from the real-time second-level collected data; store the wind speed and pitch position in the effective second-level collected data in the preset edge computing system; when the number of wind speeds and pitch positions in the preset edge computing system reaches the preset fitting number, fit and generate the actual wind speed-pitch position curve; compare the deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve, and when the deviation is greater than the preset deviation threshold, start the preset deviation alarm program.

[0007] The abnormal operation state monitoring method of a wind turbine provided in the embodiment of the present application obtains wind turbine operation data from a monitoring and data acquisition database, and screens and calculates the data; obtains a standard wind speed-pitch position curve; extracts wind turbine operation data in real time when the wind turbine is running, and screens and calculates the data, retaining the wind speed and pitch position data under normal power generation conditions of the wind turbine; obtains the actual wind speed-pitch position curve; by comparing the degree of deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve, and setting an alarm threshold, the abnormal operation state of the wind turbine is discovered in time, which can ensure the safe and stable operation of the unit and reduce potential failures and losses. The problem that the existing solution cannot effectively identify wind turbine damage when the damage to the wind turbine is not serious is solved.

[0008] In one implementation of the present application, based on power, power setting, and yaw error, the second-level collected data in the power-limited state and the second-level collected data with a yaw error greater than a preset yaw threshold are removed from all the second-level collected data to obtain standard second-level collected data, specifically including: Calculate whether the difference between the power setting and the power minus the power is greater than the preset difference. If it is greater than the preset difference, it indicates a power-limited state, and remove the second-level collected data in the power-limited state. At the same time, remove the second-level collected data with a yaw error greater than the preset yaw threshold to obtain standard second-level collected data.

[0009] In one implementation of the present application, a standard wind speed-pitch position curve within a preset time period is fitted and generated according to the wind speed and pitch position in the standard second-level collected data, specifically including: The wind speed data is divided into bins according to preset intervals to obtain the wind speed intervals, wind speed interval boundaries and pitch positions falling into different wind speed intervals; the average values ​​of the pitch positions in different wind speed intervals are respectively obtained, and the wind speed interval boundaries are used as the horizontal coordinate and the average value of the pitch position is used as the vertical coordinate to generate a standard wind speed-pitch position curve.

[0010] In one implementation of the present application, the wind speed and pitch position in the effective second-level collected data are stored in a preset edge computing system, specifically including: An empty array wind speed array and a pitch position array with a fixed length of m are created through a preset edge computing system; the preset edge computing system fills the wind speed array and the pitch position array in sequence according to the wind speed and pitch position in the received valid second-level collected data until the wind speed array and the pitch position array are filled.

[0011] In one implementation of the present application, comparing the deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve specifically includes: The deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve is compared by using the curve inflection point and difference method.

[0012] In one implementation of the present application, when the deviation is greater than a preset deviation threshold, a preset deviation alarm procedure is initiated, specifically including: The preset alarm information is displayed on the preset human-machine display interface; at the same time, a power limit instruction is issued to the wind turbine generator set, so that the wind turbine generator set operates according to the power setting value in the power limit instruction.

[0013] In one implementation of the present application, the real-time second-level collected data includes at least: wind speed, pitch position, power, power setting, and yaw error; based on the power, power setting, and yaw error, effective second-level collected data is obtained from the real-time second-level collected data, specifically including: calculating whether the difference between the power setting and the power in the real-time second-level collected data is greater than a preset difference, and when it is greater than the preset difference, it indicates a power-limited state, and the real-time second-level collected data in the power-limited state is removed; at the same time, the real-time second-level collected data with a yaw error greater than a preset yaw threshold is removed to obtain effective second-level collected data.

[0014] In a second aspect, the present application provides a system for monitoring abnormal operation status of a wind turbine generator set, the system comprising: The export module is used to export the second-level collected data related to the wind turbine in a preset time period from the monitoring and data acquisition database; wherein the second-level collected data at least includes: wind speed, pitch position, power, power setting, and yaw error; the standard curve acquisition module is used to remove the second-level collected data in the power-limited state and the yaw error greater than the preset yaw threshold from all the second-level collected data based on power, power setting, and yaw error, and obtain standard second-level collected data; according to the wind speed and pitch position in the standard second-level collected data, a standard wind speed-pitch position curve in a preset time period is fitted and generated; the real-time data storage module is used to store data in the wind turbine During operation, the second-level collected data of the wind turbine is obtained in real time, and based on the power, power setting, and yaw error, the effective second-level collected data is obtained from the real-time second-level collected data; the wind speed and pitch position in the effective second-level collected data are stored in the preset edge computing system; the real-time curve acquisition module is used to fit and generate the actual wind speed-pitch position curve when the number of wind speeds and pitch positions in the preset edge computing system reaches the preset fitting number; the comparison module is used to compare the deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve. When the deviation is greater than the preset deviation threshold, the preset deviation alarm program is started.

[0015] In a third aspect, the present application provides a device for monitoring abnormal operation status of a wind turbine, the device comprising: A processor; and a memory having executable codes stored thereon, wherein when the executable codes are executed, the processor executes any one of the above-mentioned methods for monitoring abnormal operation status of a wind turbine.

[0016] In a fourth aspect, the present application provides a non-volatile computer storage medium having computer instructions stored thereon, which, when executed, implement a method for monitoring abnormal operation status of a wind turbine as described in any one of the above items.

[0017] Those skilled in the art can understand that the present application has at least the following beneficial effects: The embodiment of the present application provides a method, system, device and medium for monitoring the abnormal operation status of a wind turbine, which obtains the operation data of the wind turbine from the monitoring and data acquisition database, and screens and calculates the data; obtains the standard wind speed-pitch position curve; extracts the operation data of the wind turbine in real time when the wind turbine is running, and screens and calculates the data, retains the wind speed and pitch position data under normal power generation conditions of the wind turbine; obtains the actual wind speed-pitch position curve; by comparing the deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve, and setting an alarm threshold, the abnormal operation status of the wind turbine is discovered in time, which can ensure the safe and stable operation of the unit and reduce potential failures and losses. The problem that the existing solution cannot effectively identify the damage of the wind turbine when the damage degree of the wind turbine is not serious is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Some embodiments of the present disclosure are described below with reference to the accompanying drawings, in which: Figure 1 It is a flow chart of a method for monitoring abnormal operation status of a wind turbine set provided in an embodiment of the present application.

[0019] Figure 2 It is a schematic diagram of the internal structure of a wind turbine abnormal operation status monitoring system provided in an embodiment of the present application.

[0020] Figure 3 It is a schematic diagram of the internal structure of a wind turbine abnormal operation status monitoring device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] It should be understood by those skilled in the art that the embodiments described below are only preferred embodiments of the present disclosure, and do not mean that the present disclosure can only be implemented through the preferred embodiments. The preferred embodiments are only used to explain the technical principles of the present disclosure, and are not used to limit the protection scope of the present disclosure. Based on the preferred embodiments provided by the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work should still fall within the protection scope of the present disclosure.

[0022] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0023] The technical solution proposed in the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0024] The embodiment provides a method for monitoring abnormal operation status of a wind turbine generator set. Figure 1 As shown, the method provided in the embodiment of the present application mainly includes the following steps: Step 110: Export the second-level collected data related to the wind turbine generator set within a preset time period from the monitoring and data collection database.

[0025] It should be noted that the data collected at the second level includes at least: wind speed, pitch position, power, power setting, and yaw error.

[0026] The monitoring and data acquisition database may be a database involved in a SCADA (Supervisory Control And Data Acquisition) system.

[0027] Step 120: Based on power, power setting, and yaw error, remove the second-level collected data in a power-limited state and with a yaw error greater than a preset yaw threshold from all the second-level collected data to obtain standard second-level collected data.

[0028] This step can be specifically as follows: Calculate whether the difference between the power setting and the power reduction is greater than the preset difference. If it is greater than the preset difference, it indicates a power limit state, and remove the second-level collected data of the power limit state; for example, ;in, Indicates power setting, Indicates power, the preset difference can be .

[0029] At the same time, the second-level acquisition data with a yaw error greater than a preset yaw threshold is removed to obtain standard second-level acquisition data.

[0030] For example, the yaw error can be obtained by: ;in To measure wind direction, is the cabin position, the preset yaw threshold can be .

[0031] Step 130: According to the wind speed and pitch position in the standard second-level collected data, a standard wind speed-pitch position curve within a preset time period is generated by fitting.

[0032] This step can be specifically as follows: The wind speed data is binned into intervals according to preset intervals to obtain wind speed intervals, wind speed interval boundaries, and pitch positions falling into different wind speed intervals; The average values ​​of the pitch position in different wind speed ranges are obtained respectively, and the wind speed range boundary is used as the horizontal coordinate and the average value of the pitch position is used as the vertical coordinate to generate a standard wind speed-pitch position curve.

[0033] As an example, The wind speed data is binned into intervals of 0.2 m / s, and the corresponding pitch positions fall into different intervals. The average values ​​of the pitch positions in different intervals are obtained respectively. A fitted standard wind speed-pitch position curve is drawn with the wind speed interval boundary as the horizontal coordinate and the pitch position average value as the vertical coordinate.

[0034] Step 140: When the wind turbine is running, the second-level collected data of the wind turbine is obtained in real time, and based on the power, power setting, and yaw error, effective second-level collected data is obtained from the real-time second-level collected data; the wind speed and pitch position in the effective second-level collected data are stored in a preset edge computing system.

[0035] It should be noted that the real-time, second-level data collection includes at least: wind speed, pitch position, power, power setting, yaw error; based on power, power setting, yaw error.

[0036] Based on the power, power setting, and yaw error, the specific scheme for obtaining effective second-level collected data from the real-time second-level collected data is similar to step 120, and can be specifically: Calculate whether the difference between the power setting and the power reduction in the real-time second-level collected data is greater than the preset difference. If it is greater than the preset difference (the preset difference can be ) indicates a power-limited state, and the real-time second-level collected data of the power-limited state is removed; at the same time, the yaw error greater than the preset yaw threshold (the preset yaw threshold can be ) to collect data in real time at the second level and obtain effective data collected at the second level.

[0037] In step 140, the wind speed and pitch position in the effective second-level collected data are stored in a preset edge computing system, which may be: An empty array wind speed array and a pitch position array with a fixed length of m are created through a preset edge computing system; the preset edge computing system fills the wind speed array and the pitch position array in sequence according to the wind speed and pitch position in the received valid second-level collected data until the wind speed array and the pitch position array are filled.

[0038] For example, the preset edge computing system sets the wind speed array and the pitch position array. First, create an empty array with a fixed length of m. , When the main control system transmits data, each time the data is stored , , until the array is filled.

[0039] The wind speed array is updated as follows: ; ; ; …….

[0040] The pitch position array is updated as follows: ; ; ; …….

[0041] Step 150: When the number of wind speeds and pitch positions in the preset edge computing system reaches a preset fitting number, an actual wind speed-pitch position curve is generated by fitting.

[0042] It should be noted that the specific scheme for fitting and generating the actual wind speed-pitch position curve is consistent with step 130, and will not be elaborated in this application.

[0043] Step 160 : comparing the deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve, and when the deviation is greater than a preset deviation threshold, starting a preset deviation alarm procedure.

[0044] In this step, the deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve is compared, which can be specifically: The deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve is compared by using the curve inflection point and difference method.

[0045] As an example, the deviation includes a first deviation threshold and a second first deviation threshold. A mathematical method or a graphical method is used to identify the wind speed inflection point corresponding to the pitch position from 0 to pitch retraction on the actual wind speed-pitch position curve and compare it numerically with the wind speed inflection point of the standard wind speed-pitch position curve. When the difference is greater than the preset first deviation threshold, the preset deviation alarm program is started and displayed in the human-computer interaction interface, and a power limit instruction is issued to put the wind turbine into a safe control mode; at the same time, the wind speed-pitch position is calculated. The pitch position corresponding to each wind speed interval in the actual wind speed-pitch position curve is compared numerically with the pitch position corresponding to the same wind speed interval in the standard wind speed-pitch position curve. When the difference is greater than the preset second deviation threshold, the preset deviation alarm program is started and displayed in the human-computer interaction interface, and a power limit instruction is issued to put the wind turbine into a safe control mode.

[0046] When the deviation is greater than the preset deviation threshold, the preset deviation alarm procedure is started, which can be specifically as follows: The preset alarm information is displayed on the preset human-machine display interface; at the same time, a power limit instruction is issued to the wind turbine generator set, so that the wind turbine generator set operates according to the power setting value in the power limit instruction.

[0047] In addition, this application Figure 2 A wind turbine abnormal operation status monitoring system is provided in an embodiment of the present application. Figure 2 As shown, the system provided in the embodiment of the present application mainly includes: The export module 210 is used to export the second-level collected data related to the wind turbine generator set within a preset time period from the monitoring and data collection database.

[0048] Among them, the data collected at the second level includes at least: wind speed, pitch position, power, power setting, and yaw error.

[0049] The standard curve acquisition module 220 is used to remove the second-level acquisition data in the limited power state and the second-level acquisition data with a yaw error greater than a preset yaw threshold from all the second-level acquisition data based on power, power setting, and yaw error, and obtain standard second-level acquisition data; according to the wind speed and pitch position in the standard second-level acquisition data, a standard wind speed-pitch position curve within a preset time period is fitted and generated.

[0050] The real-time data storage module 230 is used to obtain the second-level collected data of the wind turbine in real time when the wind turbine is running, and obtain effective second-level collected data from the real-time second-level collected data based on power, power setting, and yaw error; and store the wind speed and pitch position in the effective second-level collected data in a preset edge computing system.

[0051] The real-time curve acquisition module 240 is used to fit and generate an actual wind speed-pitch position curve when the number of wind speeds and pitch positions in the preset edge computing system reaches a preset fitting number.

[0052] The comparison module 250 is used to compare the deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve, and when the deviation is greater than a preset deviation threshold, a preset deviation alarm program is started.

[0053] The above is a method embodiment of the present application. Based on the same inventive concept, the present application embodiment also provides a wind turbine abnormal operation state monitoring device. Figure 3 As shown, the device includes: a processor; and a memory, on which executable codes are stored. When the executable codes are executed, the processor executes a method for monitoring abnormal operation status of a wind turbine generator set as described in the above embodiment.

[0054] Specifically, the server side exports the second-level collected data related to the wind turbine in a preset time period from the monitoring and data acquisition database; wherein the second-level collected data at least includes: wind speed, pitch position, power, power setting, and yaw error; based on power, power setting, and yaw error, the second-level collected data in the power-limited state and the yaw error greater than the preset yaw threshold are removed from all the second-level collected data to obtain standard second-level collected data; based on the wind speed and pitch position in the standard second-level collected data, a standard wind speed-pitch position curve in a preset time period is fitted and generated; during the operation of the wind turbine When the wind turbine is in operation, the second-level data collected by the wind turbine is obtained in real time, and the effective second-level data collected is obtained from the real-time second-level data based on the power, power setting and yaw error; the wind speed and pitch position in the effective second-level data are stored in the preset edge computing system; when the number of wind speeds and pitch positions in the preset edge computing system reaches the preset fitting number, the actual wind speed-pitch position curve is generated by fitting; the deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve is compared, and when the deviation is greater than the preset deviation threshold, the preset deviation alarm program is started.

[0055] In addition, an embodiment of the present application further provides a non-volatile computer storage medium on which executable instructions are stored. When the executable instructions are executed, a method for monitoring the abnormal operation status of a wind turbine generator set as described above is implemented.

[0056] So far, the technical solutions of the present disclosure have been described in combination with the above multiple embodiments, but it is easy for those skilled in the art to understand that the protection scope of the present disclosure is not limited to these specific embodiments. Without departing from the technical principles of the present disclosure, those skilled in the art can split and combine the technical solutions in the above-mentioned various embodiments, and can also make equivalent changes or replacements to the relevant technical features. Any changes, equivalent replacements, improvements, etc. made within the technical concept and / or technical principle of the present disclosure will fall within the protection scope of the present disclosure.

Claims

1. A method for monitoring abnormal operation status of a wind turbine generator set, characterized in that: The method comprises: Exporting the second-level collected data related to the wind turbine in a preset time period from the monitoring and data acquisition database; wherein the second-level collected data at least includes: wind speed, pitch position, power, power setting, and yaw error; Based on power, power setting, and yaw error, the second-level collected data in the power-limited state and with yaw errors greater than a preset yaw threshold are removed from all the second-level collected data to obtain standard second-level collected data; According to the wind speed and pitch position in the standard second-level collected data, a standard wind speed-pitch position curve within a preset time period is fitted and generated; When the wind turbine is running, the wind turbine's second-level data is acquired in real time, and effective second-level data is acquired from the real-time second-level data based on power, power setting, and yaw error; the wind speed and pitch position in the effective second-level data are stored in the preset edge computing system; When the number of wind speeds and pitch positions in the preset edge computing system reaches the preset fitting number, an actual wind speed-pitch position curve is generated by fitting; The deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve is compared. When the deviation is greater than a preset deviation threshold, a preset deviation alarm program is started.

2. The method for monitoring abnormal operation status of a wind turbine according to claim 1, characterized in that: Based on power, power setting, and yaw error, the second-level collected data in the power-limited state and with yaw error greater than the preset yaw threshold are removed from all the second-level collected data to obtain standard second-level collected data, including: Calculate whether the difference between the power setting and the power reduction is greater than a preset difference. If it is greater than the preset difference, it indicates a power limit state, and remove the second-level collected data of the power limit state; At the same time, the second-level acquisition data with a yaw error greater than a preset yaw threshold is removed to obtain standard second-level acquisition data.

3. The method for monitoring abnormal operation status of a wind turbine according to claim 1, characterized in that: According to the wind speed and pitch position in the standard second-level collected data, a standard wind speed-pitch position curve within a preset time period is generated by fitting, specifically including: The wind speed data is binned into intervals according to preset intervals to obtain wind speed intervals, wind speed interval boundaries, and pitch positions falling into different wind speed intervals; The average values ​​of the pitch position in different wind speed ranges are obtained respectively, and the wind speed range boundary is used as the horizontal coordinate and the average value of the pitch position is used as the vertical coordinate to generate a standard wind speed-pitch position curve.

4. The method for monitoring abnormal operation status of a wind turbine according to claim 1, characterized in that: The wind speed and pitch position in the effective second-level collected data are stored in the preset edge computing system, including: Create an empty array wind speed array and a pitch position array with a fixed length of m through a preset edge computing system; The preset edge computing system fills the wind speed array and the pitch position array in sequence according to the wind speed and pitch position in the received valid second-level collected data until the wind speed array and the pitch position array are filled.

5. The method for monitoring abnormal operation status of a wind turbine according to claim 1, characterized in that: Compare the deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve, including: The deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve is compared by using the curve inflection point and difference method.

6. The method for monitoring abnormal operation status of a wind turbine generator set according to claim 1, characterized in that: When the deviation is greater than the preset deviation threshold, the preset deviation alarm procedure is initiated, including: Display preset alarm information on the preset human-machine display interface; At the same time, a power limit instruction is sent to the wind turbine generator set so that the wind turbine generator set operates according to the power setting value in the power limit instruction.

7. The method for monitoring abnormal operation status of a wind turbine generator set according to claim 1, characterized in that: Real-time, second-level data collection includes at least: wind speed, pitch position, power, power setting, and yaw error; Based on power, power setting, and yaw error, obtain effective second-level collection data from real-time second-level collection data, including: Calculate whether the difference between the power setting and the power reduction in the real-time second-level collected data is greater than a preset difference. If it is greater than the preset difference, it indicates a power-limited state, and remove the real-time second-level collected data in the power-limited state. At the same time, the real-time second-level collected data with yaw errors greater than the preset yaw threshold is removed to obtain effective second-level collected data.

8. A wind turbine abnormal operation status monitoring system, characterized in that: The system comprises: An export module is used to export the second-level collected data related to the wind turbine in a preset time period from the monitoring and data acquisition database; wherein the second-level collected data at least includes: wind speed, pitch position, power, power setting, and yaw error; The standard curve acquisition module is used to remove the second-level acquisition data in the power-limited state and the second-level acquisition data with a yaw error greater than a preset yaw threshold from all the second-level acquisition data based on power, power setting, and yaw error, and obtain standard second-level acquisition data; according to the wind speed and pitch position in the standard second-level acquisition data, a standard wind speed-pitch position curve within a preset time period is fitted and generated; The real-time data storage module is used to obtain the second-level collected data of the wind turbine in real time when the wind turbine is running, and obtain the effective second-level collected data from the real-time second-level collected data based on power, power setting, and yaw error; and store the wind speed and pitch position in the effective second-level collected data in the preset edge computing system; A real-time curve acquisition module is used to fit and generate an actual wind speed-pitch position curve when the number of wind speeds and pitch positions in the preset edge computing system reaches a preset fitting number; The comparison module is used to compare the deviation between the actual wind speed-pitch position curve and the standard wind speed-pitch position curve. When the deviation is greater than a preset deviation threshold, a preset deviation alarm program is started.

9. A wind turbine abnormal operation status monitoring device, characterized in that: The device comprises: processor; and a memory having executable codes stored thereon, which, when the executable codes are executed, enable the processor to execute a method for monitoring abnormal operation status of a wind turbine set as claimed in any one of claims 1 to 7.

10. A non-volatile computer storage medium, characterized in that: Computer instructions are stored thereon, and when the computer instructions are executed, a method for monitoring abnormal operation status of a wind turbine set as described in any one of claims 1 to 7 is implemented.

Images