A detection method and related device for a wind turbine

Abstract

Embodiments of the present application disclose a detection method and related device for a wind driven generator, which can obtain running data of the wind driven generator in a preset time period, and then determine comprehensive data corresponding to the wind driven generator according to the running data. The comprehensive data can reflect a continuous running state of the wind driven generator in the preset time period. When the comprehensive data exceeds a first data threshold, it can be determined that the wind driven generator continuously runs in an abnormal state to a certain extent, although the running data does not exceed a second data threshold corresponding to a fault, but the fatigue load of the wind driven generator is increased, and the service life of the wind driven generator is reduced. Therefore, in response to the comprehensive data exceeding the first data threshold, a processing device can generate first alarm information corresponding to the wind driven generator, so that the problem that the wind driven generator is damaged due to working in an unhealthy running state can be avoided to a certain extent.

Description

Technical Field

[0001] This application relates to the field of wind power generation technology, and in particular to a testing method and related apparatus for wind turbines. Background Technology

[0002] Wind power generation is a major energy supply method among new energy sources. In order to maintain the stable operation of wind turbines, relevant personnel will set alarm thresholds for wind turbines. Once the operating parameters of the wind turbine exceed the threshold, an alarm will be triggered, thereby realizing the detection of the operating status of the wind turbine.

[0003] However, this method of wind turbine detection can only issue relatively accurate alarms for data that exceeds the alarm threshold, and cannot analyze data that does not exceed the alarm threshold, thus making it difficult to effectively detect wind turbines. Summary of the Invention

[0004] To address the aforementioned technical issues, this application provides a detection method for wind turbines. The processing equipment can analyze the overall operating status of the wind turbine over a period of time. When the continuous operating status within that period corresponds to relatively abnormal data, an alarm can be triggered even if the data threshold for a fault alarm has not been reached, in order to prevent the generator from continuously operating in a relatively abnormal state and causing wear and tear on the generator.

[0005] The embodiments of this application disclose the following technical solutions:

[0006] In a first aspect, embodiments of this application disclose a detection method for wind turbine generators, the method comprising:

[0007] Obtain the operating data of the wind turbine within a preset time period;

[0008] The comprehensive data corresponding to the wind turbine is determined based on the operating data, and the comprehensive data is used to reflect the continuous operating status of the wind turbine during the preset time period;

[0009] In response to the comprehensive data exceeding a first data threshold, a first alarm message corresponding to the wind turbine is generated. The first alarm message is used to identify that the wind turbine is in an abnormal operating state during the preset time period. The first data threshold is less than a second data threshold, and the second data threshold is used to determine whether the wind turbine has malfunctioned.

[0010] In one possible implementation, the method further includes:

[0011] In response to the operating data exceeding a second data threshold, a second alarm message corresponding to the wind turbine is generated, wherein the first data threshold is less than the second data threshold, and the second alarm message is used to identify that the wind turbine has an operational fault.

[0012] In one possible implementation, the operating data is blade angle data, and determining the comprehensive data corresponding to the wind turbine based on the operating data includes:

[0013] Based on the blade angle data, determine the minimum blade angle fluctuation amplitude, blade angle fluctuation period, average blade angle fluctuation period, blade angle dominant frequency, and blade angle dominant frequency amplitude corresponding to the wind turbine.

[0014] The first data threshold includes a propeller angle main frequency amplitude threshold, a propeller angle period interval fluctuation difference threshold, and a propeller angle fluctuation amplitude threshold. The step of generating a first alarm message corresponding to the wind turbine in response to the comprehensive data exceeding the first data threshold includes:

[0015] In response to the fact that the blade angle main frequency is greater than the first-order frequency of the tower corresponding to the wind turbine, and the amplitude of the blade angle main frequency is greater than the blade angle main frequency amplitude threshold, a first alarm message corresponding to the wind turbine is generated.

[0016] Alternatively, in response to multiple propeller angle fluctuation cycles within the preset time period satisfying the propeller angle cycle interval fluctuation difference threshold, and the minimum propeller angle fluctuation amplitude being greater than the propeller angle fluctuation amplitude, a first alarm message corresponding to the wind turbine is generated.

[0017] In one possible implementation, the operating data is rotational speed data, and determining the comprehensive data corresponding to the wind turbine based on the operating data includes:

[0018] Based on the rotational speed data, determine the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the average value of the rotational speed fluctuation period, the main rotational speed frequency, and the amplitude of the main rotational speed frequency for the wind turbine.

[0019] The first data threshold includes a rotational speed frequency amplitude threshold, a rotational speed cycle interval fluctuation difference threshold, and a rotational speed fluctuation amplitude threshold. The step of generating a first alarm message corresponding to the wind turbine in response to the comprehensive data exceeding the first data threshold includes:

[0020] In response to the fact that the main frequency of the rotational speed is greater than the first-order frequency of the tower corresponding to the wind turbine, and the amplitude of the main frequency of the rotational speed is greater than the amplitude threshold of the main frequency of the rotational speed, a first alarm message corresponding to the wind turbine is generated.

[0021] Alternatively, in response to multiple speed fluctuation cycles within the preset time period satisfying the speed cycle interval fluctuation difference threshold, and the minimum speed fluctuation amplitude being greater than the speed fluctuation amplitude, a first alarm message corresponding to the wind turbine is generated.

[0022] In one possible implementation, the method further includes:

[0023] The inherent mode frequencies in the rotational speed signal are filtered out. These inherent mode frequencies are generated based on the vibrations during the operation of the wind turbine.

[0024] The step of determining the minimum value of the speed fluctuation amplitude, the speed fluctuation period, the average value of the speed fluctuation period, the main speed frequency, and the main speed frequency amplitude of the wind turbine based on the speed data includes:

[0025] Based on the filtered rotational speed data, the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the average value of the rotational speed fluctuation period, the main rotational speed frequency, and the amplitude of the main rotational speed frequency are determined for the wind turbine.

[0026] In one possible implementation, the method further includes:

[0027] The running data is then filtered.

[0028] The step of determining the comprehensive data corresponding to the wind turbine based on the operating data includes:

[0029] Based on the filtered operating data, the comprehensive data corresponding to the wind turbine is determined.

[0030] Secondly, embodiments of this application disclose a detection device for wind turbine generators, the device comprising an acquisition unit, a determination unit, and a first response unit:

[0031] The acquisition unit is used to acquire the operating data of the wind turbine within a preset time period;

[0032] The determining unit is used to determine the comprehensive data corresponding to the wind turbine based on the operating data. The comprehensive data is used to reflect the continuous operating status of the wind turbine within the preset time period.

[0033] The first response unit is used to generate a first alarm message corresponding to the wind turbine in response to the comprehensive data exceeding a first data threshold. The first alarm message is used to identify that the wind turbine is in an abnormal operating state during the preset time period. The first data threshold is less than a second data threshold, and the second data threshold is used to determine whether the wind turbine has malfunctioned.

[0034] In one possible implementation, the device further includes a second response unit:

[0035] The second response unit is used to generate a second alarm message corresponding to the wind turbine in response to the operating data exceeding a second data threshold. The first data threshold is less than the second data threshold, and the second alarm message is used to identify that the wind turbine has an operating fault.

[0036] In one possible implementation, the operating data is paddle angle data, and the determining unit is specifically used for:

[0037] Based on the blade angle data, determine the minimum blade angle fluctuation amplitude, blade angle fluctuation period, average blade angle fluctuation period, blade angle dominant frequency, and blade angle dominant frequency amplitude corresponding to the wind turbine.

[0038] The first data threshold includes the propeller angle main frequency amplitude threshold, the propeller angle period interval fluctuation difference threshold, and the propeller angle fluctuation amplitude threshold. The first response unit is specifically used for:

[0039] In response to the fact that the blade angle main frequency is greater than the first-order frequency of the tower corresponding to the wind turbine, and the amplitude of the blade angle main frequency is greater than the blade angle main frequency amplitude threshold, a first alarm message corresponding to the wind turbine is generated.

[0040] Alternatively, in response to multiple propeller angle fluctuation cycles within the preset time period satisfying the propeller angle cycle interval fluctuation difference threshold, and the minimum propeller angle fluctuation amplitude being greater than the propeller angle fluctuation amplitude, a first alarm message corresponding to the wind turbine is generated.

[0041] In one possible implementation, the operating data is rotational speed data, and the determining unit is specifically used for:

[0042] Based on the rotational speed data, determine the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the average value of the rotational speed fluctuation period, the main rotational speed frequency, and the amplitude of the main rotational speed frequency for the wind turbine.

[0043] The first data threshold includes the main frequency amplitude threshold, the speed cycle interval fluctuation difference threshold, and the speed fluctuation amplitude threshold. The first response unit is specifically used for:

[0044] In response to the fact that the main frequency of the rotational speed is greater than the first-order frequency of the tower corresponding to the wind turbine, and the amplitude of the main frequency of the rotational speed is greater than the amplitude threshold of the main frequency of the rotational speed, a first alarm message corresponding to the wind turbine is generated.

[0045] Alternatively, in response to multiple speed fluctuation cycles within the preset time period satisfying the speed cycle interval fluctuation difference threshold, and the minimum speed fluctuation amplitude being greater than the speed fluctuation amplitude, a first alarm message corresponding to the wind turbine is generated.

[0046] In one possible implementation, the device further includes a first filtering unit:

[0047] The first filtering unit is used to filter out the inherent mode frequencies in the rotation speed signal, which are generated based on the vibrations during the operation of the wind turbine.

[0048] The determining unit is specifically used for:

[0049] Based on the filtered rotational speed data, the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the average value of the rotational speed fluctuation period, the main rotational speed frequency, and the amplitude of the main rotational speed frequency are determined for the wind turbine.

[0050] In one possible implementation, the device further includes a second filtering unit:

[0051] The second filtering unit is used to filter the running data;

[0052] The determining unit is specifically used for:

[0053] Based on the filtered operating data, the comprehensive data corresponding to the wind turbine is determined.

[0054] Thirdly, embodiments of this application disclose a computer-readable storage medium in which, when the instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor performs the detection method for a wind turbine as described in any of the first aspects.

[0055] Fourthly, embodiments of this application disclose a computer device, including:

[0056] At least one processor;

[0057] At least one memory that stores computer-executable instructions.

[0058] Wherein, when the computer device executes instructions, the at least one processor performs the detection method for a wind turbine as described in any of the first aspects.

[0059] In one possible implementation, the computer device is located in the controller of the wind farm.

[0060] As can be seen from the above technical solution, during testing, the operating data of the wind turbine within a preset time period can be acquired. Then, based on this operating data, comprehensive data corresponding to the wind turbine can be determined. This comprehensive data reflects the continuous operating status of the wind turbine within the preset time period. When the comprehensive data exceeds a first data threshold, it indicates to some extent that the wind turbine is continuously operating in a state with abnormal data. In this operating state, although the operating data does not exceed the second data threshold corresponding to a fault, it will cause increased fatigue load on the wind turbine unit, reducing the unit's service life. Therefore, in response to the comprehensive data exceeding the first data threshold, the processing equipment can generate a first alarm message corresponding to the wind turbine. This first alarm message is used to identify that the wind turbine is in an abnormal state within the preset time period. The first data threshold is less than the second data threshold, which is used to determine whether the wind turbine has a fault. Thus, through this method, in addition to identifying whether the generator is faulty, it is also possible to further detect whether the wind turbine is in an unhealthy operating state, thereby preventing the wind turbine from being damaged due to unhealthy operating conditions to a certain extent. Attached Figure Description

[0061] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0062] Figure 1 A flowchart illustrating a detection method for a wind turbine generator provided in this application embodiment;

[0063] Figure 2 A detection method and schematic diagram for a wind turbine generator are provided for embodiments of this application;

[0064] Figure 3 A detection method and schematic diagram for a wind turbine generator are provided for embodiments of this application;

[0065] Figure 4 A detection method and schematic diagram for a wind turbine generator are provided for embodiments of this application;

[0066] Figure 5 A detection method and schematic diagram for a wind turbine generator are provided for embodiments of this application;

[0067] Figure 6 This is a schematic diagram illustrating a detection method based on paddle angle data, provided as an embodiment of this application.

[0068] Figure 7 A schematic diagram illustrating detection based on rotational speed data, provided as an embodiment of this application;

[0069] Figure 8 This is a structural block diagram of a testing device for a wind turbine provided in an embodiment of this application. Detailed Implementation

[0070] The embodiments of this application will now be described with reference to the accompanying drawings.

[0071] Currently, there are no solutions for identifying and protecting against control system oscillations in wind turbine generators. Existing over-acceleration fault protection, over-power fault protection, and rotor overspeed protection only provide protection when the control system oscillations are abnormally severe, i.e., the acceleration amplitude, power, and speed exceed the fault protection threshold. During normal operation, control system oscillations can cause relatively large acceleration amplitudes and fluctuations in speed, power, and pitch angle, but these may not reach the above fault standards. Long-term operation of the unit under these conditions will increase fatigue loads and reduce the unit's service life.

[0072] To address the aforementioned technical issues, this application provides a detection method for wind turbines. The processing equipment can analyze the overall operating status of the wind turbine over a period of time. When the continuous operating status within that period corresponds to relatively abnormal data, an alarm can be triggered even if the data threshold for a fault alarm has not been reached, in order to prevent the generator from continuously operating in a relatively abnormal state and causing wear and tear on the generator.

[0073] Understandably, this method can be applied to processing devices capable of wind turbine detection, such as terminal devices or servers with motion control functions. This method can be executed independently by the terminal device or server, or it can be applied in network scenarios where the terminal device and server communicate, executing in cooperation. The terminal device can be a computer, mobile phone, or similar device. The server can be an application server or a web server; in actual deployment, this server can be a standalone server or a cluster server.

[0074] Next, with reference to the accompanying drawings, a testing method for wind turbines provided in this application will be described.

[0075] See Figure 1 , Figure 1 A flowchart of a detection method for a wind turbine provided in this application embodiment, the method comprising:

[0076] S101: Obtain the operating data of the wind turbine within a preset time period.

[0077] The preset time period can be set based on the operating characteristics of the wind turbine, such as 60 seconds; the operating data is used to reflect the corresponding operating status of the wind turbine, such as speed data, blade angle data, etc., and there are no restrictions here.

[0078] S102: Determine the comprehensive data corresponding to the wind turbine based on the operating data.

[0079] This comprehensive data is used to reflect the continuous operating status of the wind turbine within a preset time period. The continuous operating status refers to the operating status of the wind turbine with little change during continuous operation within the preset time period. This continuous operating status can reflect the overall operating characteristics of the wind turbine within the preset time period.

[0080] S103: In response to the comprehensive data exceeding the first data threshold, generate the first alarm information corresponding to the wind turbine.

[0081] To prevent wind turbines from operating in an unhealthy state for extended periods, the processing equipment can set two types of thresholds for the wind turbines: a first data threshold and a second data threshold. The first data threshold is used to determine whether the wind turbine is operating in an abnormal state, while the second data threshold is used to determine whether the wind turbine has malfunctioned. The first data threshold is lower than the second data threshold.

[0082] During wind turbine testing, the processing equipment can determine whether the wind turbine has malfunctioned based on the second data threshold. In response to the operating data exceeding the second data threshold, the processing equipment can generate a second alarm message corresponding to the wind turbine, which indicates that the wind turbine has experienced an operational malfunction.

[0083] On the other hand, even if the operating data does not exceed the second data threshold, the processing device can still determine whether the wind turbine is in an abnormal operating state based on the first data threshold and the comprehensive data. If the comprehensive data exceeds the first data threshold, indicating that the wind turbine has been operating in a relatively abnormal state during the target time period, the processing device can generate a first alarm message corresponding to the wind turbine. This first alarm message is used to identify that the wind turbine is in an abnormal operating state during the preset time period.

[0084] As can be seen from the above technical solution, during testing, the operating data of the wind turbine within a preset time period can be acquired. Then, based on this operating data, comprehensive data corresponding to the wind turbine can be determined. This comprehensive data reflects the continuous operating status of the wind turbine within the preset time period. When the comprehensive data exceeds a first data threshold, it indicates to some extent that the wind turbine is continuously operating in a state with abnormal data. In this operating state, although the operating data does not exceed the second data threshold corresponding to a fault, it will cause increased fatigue load on the wind turbine unit, reducing the unit's service life. Therefore, in response to the comprehensive data exceeding the first data threshold, the processing equipment can generate a first alarm message corresponding to the wind turbine. This first alarm message is used to identify that the wind turbine is in an abnormal state within the preset time period. The first data threshold is less than the second data threshold, which is used to determine whether the wind turbine has a fault. Thus, through this method, in addition to identifying whether the generator is faulty, it is also possible to further detect whether the wind turbine is in an unhealthy operating state, thereby preventing the wind turbine from being damaged due to unhealthy operating conditions to a certain extent.

[0085] The methods used by the processing equipment to detect different types of operational data may vary. The following sections will provide a detailed introduction to different types of operational data.

[0086] In one possible implementation, the operational data can be propeller angle data. When determining the comprehensive data, the processing equipment can determine the minimum propeller angle fluctuation amplitude, propeller angle fluctuation period, average propeller angle fluctuation period, propeller angle dominant frequency, and propeller angle dominant frequency amplitude corresponding to the wind turbine based on the propeller angle data. Here, the fluctuation amplitude refers to the difference between the peaks and troughs in the propeller angle data waveform, and the interval between peaks is the fluctuation period. Figure 2 As shown. The finite difference method can be used to find the peaks and troughs of a graph, thereby determining relevant data. The dominant frequency refers to the predominant frequency, such as... Figure 3 As shown.

[0087] In this implementation, the first data threshold may include a blade angle dominant frequency amplitude threshold, a blade angle period interval fluctuation difference threshold, and a blade angle fluctuation amplitude threshold. If the blade angle dominant frequency is greater than the first-order frequency of the tower corresponding to the wind turbine, and the blade angle dominant frequency amplitude is greater than the blade angle dominant frequency amplitude threshold, it indicates that the operating parameters of the wind turbine are abnormal during the target time period, and the processing device can generate a first alarm message corresponding to the wind turbine. Alternatively, if multiple blade angle fluctuation cycles within a preset time period meet the blade angle period interval fluctuation difference threshold, and the minimum blade angle fluctuation amplitude is greater than the blade angle fluctuation amplitude, it also proves that the wind turbine's operating status is abnormal during the target time period, and the processing device can similarly generate a first alarm message corresponding to the wind turbine. The first-order frequency of the tower is an inherent parameter of the wind turbine and can be set by relevant personnel during the construction of the wind turbine.

[0088] In another possible implementation, the operating data can be rotational speed data. The processing equipment can determine, based on the rotational speed data, the minimum amplitude of the rotational speed fluctuation, the period of rotational speed fluctuation, the average period of rotational speed fluctuation, the dominant frequency of rotational speed, and the amplitude of the dominant frequency of rotational speed for the wind turbine. The rotational speed waveform can be as follows: Figure 4 As shown, the rotational speed and main frequency can be as follows: Figure 5 As shown. In this implementation, the first data threshold may include a rotational speed frequency amplitude threshold, a rotational speed cycle interval fluctuation difference threshold, and a rotational speed fluctuation amplitude threshold. During detection, in response to the rotational speed frequency being greater than the first-order frequency of the tower corresponding to the wind turbine, and the rotational speed frequency amplitude being greater than the rotational speed frequency amplitude threshold, the processing device can generate a first alarm message corresponding to the wind turbine; or, in response to multiple rotational speed fluctuation cycles within the preset time period all satisfying the rotational speed cycle interval fluctuation difference threshold, and the minimum value of the rotational speed fluctuation amplitude being greater than the rotational speed fluctuation amplitude, the processing device can generate a first alarm message corresponding to the wind turbine.

[0089] It is understandable that during the operation of a wind turbine, due to environmental factors such as wind and rotor rotation, the wind turbine itself may generate vibrations, which can affect the speed data collected by the processing equipment. Therefore, in one possible implementation, to further improve the accuracy of detection, the processing equipment can filter out the inherent modal frequencies (IMFs) in the speed signal. These IMFs are generated based on the vibrations generated during wind turbine operation. Based on the filtered speed data, the processing equipment can determine the minimum amplitude of the speed fluctuation, the period of the speed fluctuation, the average period of the speed fluctuation, the dominant speed frequency, and the amplitude of the dominant speed frequency for the wind turbine, thereby eliminating the influence of wind turbine vibration on the speed data and improving the accuracy of wind turbine detection.

[0090] Furthermore, to further improve data accuracy, in one possible implementation, the processing equipment can also filter the operational data to remove noise and other interference, thereby improving the reliability of the operational data. Based on the filtered operational data, the processing equipment can determine the comprehensive data corresponding to the wind turbine, further improving detection accuracy.

[0091] For example, such as Figure 6 As shown, Figure 6 This is a schematic diagram illustrating detection based on propeller angle data, provided in an embodiment of this application. The processing device can acquire propeller angle data via a propeller angle measurement unit, such as a rotary encoder installed in a pitch control system. A propeller angle filtering unit performs low-pass filtering to improve the accuracy of the main frequency and time-domain period calculations. Then, a Fast Fourier Transform algorithm can be used to calculate the main frequency and amplitude, and the peaks and troughs are identified using a difference method. The difference between the peak and trough values ​​is the fluctuation amplitude, and the interval between peaks is the fluctuation period. The processing device can acquire the propeller angle signal fed back from the propeller angle measurement unit in real time as propeller angle data. The threshold values ​​can be set as follows:

[0092] m - the threshold value of the main frequency amplitude, can be taken in the range of 0.2 to 5. The lower the value, the higher the sensitivity of the algorithm to oscillation identification, but the accuracy is relatively lower than when the value is higher. It needs to be adjusted according to the actual control characteristics of the unit.

[0093] n - number of propeller angle fluctuation cycles, the reference value range is >4. The lower the value, the higher the sensitivity of the algorithm to oscillation identification, but the accuracy is relatively lower than when the value is higher. It needs to be adjusted according to the actual unit control characteristics.

[0094] The threshold value for k-period interval fluctuation difference can be taken from 0.1 to 0.2. A higher value means that the algorithm is more sensitive to oscillations, but the accuracy is relatively lower when the value is lower. It needs to be adjusted according to the actual unit control characteristics.

[0095] The threshold value for y-paddle angle fluctuation amplitude can be taken from 0.2 to 10. The lower the value, the higher the sensitivity of the algorithm to oscillation identification, but the accuracy is relatively lower than when the value is higher. It needs to be adjusted according to the actual unit control characteristics.

[0096] like Figure 6 As shown, after the corresponding conditions are met, the processing equipment can generate a propeller angle vibration warning (i.e., the first alarm information) to notify the wind turbine that abnormal vibration has occurred in the propeller angle dimension.

[0097] See Figure 7 , Figure 7This is a schematic diagram illustrating a detection method based on rotational speed data, provided in an embodiment of this application. The processing device measures the rotational speed using a speed measurement unit integrated in the generator converter, and then performs low-pass filtering to improve the accuracy of the main frequency and time-domain period calculations. The rotational speed signal (i.e., rotational speed data) originates from the rotational speed measurement source. The generator's inherent modal frequencies must be filtered out from the measured rotational speed signal before it can be applied to generator control; otherwise, the generator's inherent modal frequencies will couple into the control speed, causing further excitation by the control system and leading to oscillations. The processing device can use a fast Fourier transform algorithm to calculate the main frequency and amplitude, and use a difference method to find the peaks and troughs. The difference between the peak and trough values ​​is the fluctuation amplitude, and the interval between peaks is the fluctuation period. The processing device can acquire the rotational speed signal fed back by the speed measurement unit in real time. The threshold values ​​used for rotational speed detection are as follows:

[0098] m - the threshold value of the main frequency amplitude, can be taken in the range of 0.2 to 4. A lower value means that the algorithm is more sensitive to oscillations, but the accuracy is relatively lower than that when the value is higher. It needs to be adjusted according to the actual control characteristics of the unit.

[0099] n - the number of speed fluctuation cycles, can be taken as a reference value of >4. The lower the value, the higher the sensitivity of the algorithm to oscillation identification, but the accuracy is relatively lower than when the value is higher. It needs to be adjusted according to the actual unit control characteristics.

[0100] The threshold value for k-period interval fluctuation difference can be taken from 0.1 to 0.2. A higher value means that the algorithm is more sensitive to oscillations, but the accuracy is relatively lower when the value is lower. It needs to be adjusted according to the actual unit control characteristics.

[0101] The threshold value for the y-speed fluctuation difference coefficient can be taken from 0.7 to 0.9, but needs to be adjusted according to the actual control characteristics of the unit.

[0102] r - the difference coefficient of the main frequency amplitude of speed fluctuation, can be taken in the range of 0.7 to 0.9, and needs to be adjusted according to the actual control characteristics of the unit.

[0103] By employing the above methods, when a wind turbine generator unit is operating in a sub-healthy state due to control system oscillations, but the severity is not enough to cause other derivative faults, this unstable state can be identified and warned in a timely manner, ensuring the unit's lifespan. Simultaneously, through diverse threshold determinations, the processing equipment can further diagnose the root causes of control system oscillations, improving the unit's self-diagnostic capabilities and reducing overall lifecycle maintenance costs.

[0104] Based on the detection method for wind turbines provided in the above embodiments, this application also provides a detection device for wind turbines. (See attached document.) Figure 8 , Figure 8 A structural block diagram of a detection device 800 for a wind turbine generator provided in this application embodiment is shown. The device includes an acquisition unit 801, a determination unit 802, and a first response unit 803.

[0105] The acquisition unit 801 is used to acquire the operating data of the wind turbine within a preset time period.

[0106] The determining unit 802 is used to determine the comprehensive data corresponding to the wind turbine based on the operating data. The comprehensive data is used to reflect the continuous operating status of the wind turbine during the preset time period.

[0107] The first response unit 803 is used to generate a first alarm message corresponding to the wind turbine in response to the comprehensive data exceeding a first data threshold. The first alarm message is used to identify that the wind turbine is in an abnormal operating state during the preset time period. The first data threshold is less than a second data threshold, and the second data threshold is used to determine whether the wind turbine has malfunctioned.

[0108] In one possible implementation, the device further includes a second response unit:

[0109] The second response unit is used to generate a second alarm message corresponding to the wind turbine in response to the operating data exceeding a second data threshold. The first data threshold is less than the second data threshold, and the second alarm message is used to identify that the wind turbine has an operating fault.

[0110] In one possible implementation, the operating data is paddle angle data, and the determining unit 802 is specifically used for:

[0111] Based on the blade angle data, determine the minimum blade angle fluctuation amplitude, blade angle fluctuation period, average blade angle fluctuation period, blade angle dominant frequency, and blade angle dominant frequency amplitude corresponding to the wind turbine.

[0112] The first data thresholds include the propeller angle main frequency amplitude threshold, the propeller angle period interval fluctuation difference threshold, and the propeller angle fluctuation amplitude threshold. The first response unit 803 is specifically used for:

[0113] In response to the fact that the blade angle main frequency is greater than the first-order frequency of the tower corresponding to the wind turbine, and the amplitude of the blade angle main frequency is greater than the blade angle main frequency amplitude threshold, a first alarm message corresponding to the wind turbine is generated.

[0114] Alternatively, in response to multiple propeller angle fluctuation cycles within the preset time period satisfying the propeller angle cycle interval fluctuation difference threshold, and the minimum propeller angle fluctuation amplitude being greater than the propeller angle fluctuation amplitude, a first alarm message corresponding to the wind turbine is generated.

[0115] In one possible implementation, the operating data is rotational speed data, and the determining unit 802 is specifically used for:

[0116] Based on the rotational speed data, determine the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the average value of the rotational speed fluctuation period, the main rotational speed frequency, and the amplitude of the main rotational speed frequency for the wind turbine.

[0117] The first data threshold includes the main frequency amplitude threshold, the speed cycle interval fluctuation difference threshold, and the speed fluctuation amplitude threshold. The first response unit 803 is specifically used for:

[0118] In response to the fact that the main frequency of the rotational speed is greater than the first-order frequency of the tower corresponding to the wind turbine, and the amplitude of the main frequency of the rotational speed is greater than the amplitude threshold of the main frequency of the rotational speed, a first alarm message corresponding to the wind turbine is generated.

[0119] Alternatively, in response to multiple speed fluctuation cycles within the preset time period satisfying the speed cycle interval fluctuation difference threshold, and the minimum speed fluctuation amplitude being greater than the speed fluctuation amplitude, a first alarm message corresponding to the wind turbine is generated.

[0120] In one possible implementation, the device further includes a first filtering unit:

[0121] The first filtering unit is used to filter out the inherent mode frequencies in the rotation speed signal, which are generated based on the vibrations during the operation of the wind turbine.

[0122] The determining unit 802 is specifically used for:

[0123] Based on the filtered rotational speed data, the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the average value of the rotational speed fluctuation period, the main rotational speed frequency, and the amplitude of the main rotational speed frequency are determined for the wind turbine.

[0124] In one possible implementation, the device further includes a second filtering unit:

[0125] The second filtering unit is used to filter the running data;

[0126] The determining unit 802 is specifically used for:

[0127] Based on the filtered operating data, the comprehensive data corresponding to the wind turbine is determined.

[0128] This application also provides a computer-readable storage medium, wherein when the instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor performs the detection method for a wind turbine described in any of the above embodiments.

[0129] This application also provides a computer device, including:

[0130] At least one processor;

[0131] At least one memory that stores computer-executable instructions.

[0132] When the computer device executes instructions, the at least one processor performs the detection method for wind turbines described in any of the above embodiments.

[0133] In one possible implementation, the computer device is located in the controller of the wind farm.

[0134] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium can be at least one of the following media: read-only memory (ROM), RAM, magnetic disk, or optical disk, etc., and other media capable of storing program code.

[0135] It should be noted that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for the device and system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiments. The device and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of the solution in this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0136] The above description is merely one specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A testing method for wind turbine generators, characterized in that, The method includes: Obtain the operating data of the wind turbine within a preset time period; The comprehensive data corresponding to the wind turbine is determined based on the operating data, and the comprehensive data is used to reflect the continuous operating status of the wind turbine during the preset time period; In response to the comprehensive data exceeding a first data threshold, a first alarm message corresponding to the wind turbine is generated. The first alarm message is used to identify that the wind turbine is in an abnormal operating state during the preset time period. The first data threshold is less than a second data threshold, and the second data threshold is used to determine whether the wind turbine has a fault. The operating data is blade angle data, and determining the comprehensive data corresponding to the wind turbine based on the operating data includes: Based on the blade angle data, determine the minimum blade angle fluctuation amplitude, blade angle fluctuation period, average blade angle fluctuation period, blade angle dominant frequency, and blade angle dominant frequency amplitude corresponding to the wind turbine. The first data threshold includes a propeller angle dominant frequency amplitude threshold, a propeller angle period interval fluctuation difference threshold, and a propeller angle fluctuation amplitude threshold. The step of generating a first alarm message corresponding to the wind turbine in response to the comprehensive data exceeding the first data threshold includes: In response to the fact that the blade angle dominant frequency is greater than the first-order frequency of the tower corresponding to the wind turbine, and the amplitude of the blade angle dominant frequency is greater than the blade angle dominant frequency amplitude threshold, a first alarm message corresponding to the wind turbine is generated. Alternatively, in response to multiple propeller angle fluctuation cycles within the preset time period satisfying the propeller angle cycle interval fluctuation difference threshold, and the minimum propeller angle fluctuation amplitude being greater than the propeller angle fluctuation amplitude, a first alarm message corresponding to the wind turbine is generated. Alternatively, the operating data may be rotational speed data, and determining the comprehensive data corresponding to the wind turbine based on the operating data includes: Based on the rotational speed data, determine the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the average value of the rotational speed fluctuation period, the main rotational speed frequency, and the amplitude of the main rotational speed frequency for the wind turbine. The first data threshold includes a rotational speed frequency amplitude threshold, a rotational speed cycle interval fluctuation difference threshold, and a rotational speed fluctuation amplitude threshold. The step of generating a first alarm message corresponding to the wind turbine in response to the comprehensive data exceeding the first data threshold includes: In response to the fact that the main frequency of the rotational speed is greater than the first-order frequency of the tower corresponding to the wind turbine, and the amplitude of the main frequency of the rotational speed is greater than the amplitude threshold of the main frequency of the rotational speed, a first alarm message corresponding to the wind turbine is generated. Alternatively, in response to multiple speed fluctuation cycles within the preset time period satisfying the speed cycle interval fluctuation difference threshold, and the minimum speed fluctuation amplitude being greater than the speed fluctuation amplitude, a first alarm message corresponding to the wind turbine is generated.

2. The method according to claim 1, characterized in that, The method further includes: In response to the operating data exceeding a second data threshold, a second alarm message corresponding to the wind turbine is generated, wherein the first data threshold is less than the second data threshold, and the second alarm message is used to identify that the wind turbine has an operating fault.

3. The method according to claim 1, characterized in that, The method further includes: The inherent modal frequencies in the rotational speed data are filtered out. These inherent modal frequencies are generated based on the vibrations during the operation of the wind turbine. The step of determining the minimum value of the speed fluctuation amplitude, the speed fluctuation period, the average value of the speed fluctuation period, the main speed frequency, and the main speed frequency amplitude of the wind turbine based on the speed data includes: Based on the filtered rotational speed data, the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the average value of the rotational speed fluctuation period, the main rotational speed frequency, and the amplitude of the main rotational speed frequency are determined for the wind turbine.

4. The method according to claim 1, characterized in that, The method further includes: The running data is then filtered. The step of determining the comprehensive data corresponding to the wind turbine based on the operating data includes: Based on the filtered operating data, the comprehensive data corresponding to the wind turbine is determined.

5. A testing device for wind turbine generators, characterized in that, The device includes an acquisition unit, a determination unit, and a first response unit: The acquisition unit is used to acquire the operating data of the wind turbine within a preset time period; The determining unit is used to determine the comprehensive data corresponding to the wind turbine based on the operating data. The comprehensive data is used to reflect the continuous operating status of the wind turbine within the preset time period. The first response unit is used to generate a first alarm message corresponding to the wind turbine in response to the comprehensive data exceeding a first data threshold. The first alarm message is used to identify that the wind turbine is in an abnormal operating state during the preset time period. The first data threshold is less than a second data threshold, and the second data threshold is used to determine whether the wind turbine has a fault. The operating data is blade angle data, and determining the comprehensive data corresponding to the wind turbine based on the operating data includes: Based on the blade angle data, determine the minimum blade angle fluctuation amplitude, blade angle fluctuation period, average blade angle fluctuation period, blade angle dominant frequency, and blade angle dominant frequency amplitude corresponding to the wind turbine. The first data threshold includes a propeller angle dominant frequency amplitude threshold, a propeller angle period interval fluctuation difference threshold, and a propeller angle fluctuation amplitude threshold. The step of generating a first alarm message corresponding to the wind turbine in response to the comprehensive data exceeding the first data threshold includes: In response to the fact that the blade angle dominant frequency is greater than the first-order frequency of the tower corresponding to the wind turbine, and the amplitude of the blade angle dominant frequency is greater than the blade angle dominant frequency amplitude threshold, a first alarm message corresponding to the wind turbine is generated. Alternatively, in response to multiple propeller angle fluctuation cycles within the preset time period satisfying the propeller angle cycle interval fluctuation difference threshold, and the minimum propeller angle fluctuation amplitude being greater than the propeller angle fluctuation amplitude, a first alarm message corresponding to the wind turbine is generated. Alternatively, the operating data may be rotational speed data, and determining the comprehensive data corresponding to the wind turbine based on the operating data includes: Based on the rotational speed data, determine the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the average value of the rotational speed fluctuation period, the main rotational speed frequency, and the amplitude of the main rotational speed frequency for the wind turbine. The first data threshold includes a rotational speed frequency amplitude threshold, a rotational speed cycle interval fluctuation difference threshold, and a rotational speed fluctuation amplitude threshold. The step of generating a first alarm message corresponding to the wind turbine in response to the comprehensive data exceeding the first data threshold includes: In response to the fact that the main frequency of the rotational speed is greater than the first-order frequency of the tower corresponding to the wind turbine, and the amplitude of the main frequency of the rotational speed is greater than the amplitude threshold of the main frequency of the rotational speed, a first alarm message corresponding to the wind turbine is generated. Alternatively, in response to multiple speed fluctuation cycles within the preset time period satisfying the speed cycle interval fluctuation difference threshold, and the minimum speed fluctuation amplitude being greater than the speed fluctuation amplitude, a first alarm message corresponding to the wind turbine is generated.

6. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor performs the detection method for a wind turbine as described in any one of claims 1-4.

7. A computer device, characterized in that, include: At least one processor; At least one memory that stores computer-executable instructions. Wherein, when the computer device executes instructions, the at least one processor performs the detection method for a wind turbine as described in any one of claims 1-4.

8. The computer device according to claim 7, characterized in that, The computer equipment is installed in the controller of the wind farm.

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