Method and device for detecting icing state of wind turbine generator system

Abstract

Provided are a method and device for detecting icing state of a wind turbine. The method comprises: obtaining measurement data and control rotation speed data of the wind turbine within a first preset time length, wherein the measurement data comprises measurement rotation speed data or measurement vibration data, and the control rotation speed data is rotation speed data used for unit control; performing frequency spectrum feature analysis on the measurement data and the control rotation speed data to obtain a frequency corresponding to a maximum frequency spectrum amplitude of the measurement data and a frequency spectrum amplitude of the control rotation speed data in a specific frequency band, wherein the specific frequency band is a frequency band in which an impeller modal frequency is located; and determining whether a blade of the wind turbine is in an icing state based on the frequency corresponding to the maximum frequency spectrum amplitude of the measurement data and the frequency spectrum amplitude of the control rotation speed data in the specific frequency band.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of wind power generation in general, and more particularly, to a method and device for detecting icing state of a wind turbine. BACKGROUND

[0002] Icing of blades in winter or spring is a common phenomenon for wind turbines (hereinafter, also referred to as a turbine). With the increase of large-capacity, long and flexible blades, the industry has paid more and more attention to the harm of blade icing or serious frosting, and hopes to detect the blade icing state as soon as possible and accurately to stop the turbine in time.

[0003] However, due to the large surface area of the blade (the surface area of a 70-meter-long blade reaches more than 500 square meters), after the blade is iced, whether a heating device or an ice monitoring sensor is installed, the cost is very high to achieve the ideal effect, which makes it impossible to practically promote and apply the hardware devices for deicing or detecting icing. SUMMARY

[0004] An exemplary embodiment of the present disclosure provides a method and device for detecting icing state of a wind turbine, which can automatically detect whether the blade is iced in time and effectively without installing hardware devices.

[0005] According to a first aspect of an embodiment of the present disclosure, a method for detecting icing state of a wind turbine is provided, the method comprising: obtaining measurement data and control rotation speed data of the wind turbine within a first preset time length, wherein the measurement data comprises measurement rotation speed data or measurement vibration data, and the control rotation speed data is rotation speed data used for turbine control; performing frequency spectrum feature analysis on the measurement data and the control rotation speed data to obtain a frequency corresponding to a maximum value of a frequency spectrum amplitude of the measurement data and a frequency spectrum amplitude of the control rotation speed data in a specific frequency band, wherein the specific frequency band is a frequency band in which an impeller modal frequency is located; and determining whether a blade of the wind turbine is in an icing state based on the frequency corresponding to the maximum value of the frequency spectrum amplitude of the measurement data and the frequency spectrum amplitude of the control rotation speed data in the specific frequency band.

[0006] Optionally, the step of determining whether the blade is in the icing state based on the frequency corresponding to the maximum spectral amplitude of the measurement data and the spectral amplitude of the control rotation speed data in the specific frequency band comprises: determining whether the maximum spectral amplitude of the measurement data is greater than a first amplitude threshold; in response to the maximum spectral amplitude being greater than the first amplitude threshold, determining whether the frequency corresponding to the maximum spectral amplitude of the measurement data is in the specific frequency band; and in response to the frequency corresponding to the maximum spectral amplitude of the measurement data being in the specific frequency band, determining whether the blade is in the icing state based on the spectral amplitude of the control rotation speed data in the specific frequency band.

[0007] Optionally, the step of determining whether the blade is in the icing state based on the spectral amplitude of the control rotation speed data in the specific frequency band comprises: determining whether a maximum spectral amplitude of the control rotation speed data in the specific frequency band is less than a second amplitude threshold, wherein the second amplitude threshold is less than the first amplitude threshold; and in response to the maximum spectral amplitude of the control rotation speed data in the specific frequency band being less than the second amplitude threshold, performing the following steps N times: controlling the pitch angle to increase by a preset amplitude, and controlling the pitch angle to return to the pitch angle before the increase after a second preset time length from the start of the increase of the pitch angle; determining whether the blade is in the icing state based on the change in the measurement data caused by each increase in the pitch angle; wherein N is an integer greater than 1.

[0008] Optionally, the step of determining whether the blade is in the icing state based on the change in the measurement data caused by each increase in the pitch angle comprises: determining whether a rotation speed increase value of a maximum rotation speed measurement data after each increase in the pitch angle relative to the rotation speed measurement data before the increase in the pitch angle is greater than a first preset threshold; and in response to the proportion of the number of times of the increase in the pitch angle corresponding to the rotation speed increase value being greater than the first preset threshold to N exceeding a preset proportion, determining that the blade is in the icing state.

[0009] Optionally, the step of determining whether the blade is in the icing state based on the change in the measurement data caused by each increase in the pitch angle comprises: determining whether a vibration reduction value of a maximum vibration measurement data after each increase in the pitch angle relative to the vibration measurement data before the increase in the pitch angle is greater than a second preset threshold; and in response to the proportion of the number of times of the increase in the pitch angle corresponding to the vibration reduction value being greater than the second preset threshold to N exceeding a preset proportion, determining that the blade is in the icing state.

[0010] Optionally, the detection method further comprises: in response to the blade being in the icing state, controlling the wind turbine generator set to shut down.

[0011] Optionally, the step of obtaining the measurement data and the control rotation speed data of the wind turbine within the first preset time length comprises: in a case that the wind turbine is in a power generation state, determining whether an average value of an ambient temperature of the wind turbine within a third preset time length is less than a first temperature threshold value and an average value of an ambient humidity within the third preset time length is greater than a humidity threshold value; and in response to the average value of the ambient temperature within the third preset time length being less than the first temperature threshold value and the average value of the ambient humidity within the third preset time length being greater than the humidity threshold value, obtaining the measurement data and the control rotation speed data of the wind turbine within the first preset time length.

[0012] Optionally, the detection method further comprises: in a case that the wind turbine is in a shutdown state due to icing of the blades, determining whether an average value of an ambient temperature of the wind turbine within a fourth preset time length is greater than a second temperature threshold value and an average value of a wind speed within a fifth preset time length is greater than a wind speed threshold value; and in response to the average value of the ambient temperature within the fourth preset time length being greater than the second temperature threshold value and the average value of the wind speed within the fifth preset time length being greater than the wind speed threshold value, controlling the wind turbine to dynamically open the blades so that the measurement rotation speed data of the wind turbine approaches a first rotation speed threshold value; obtaining measurement data of the wind turbine within a sixth preset time length, and determining whether to control the wind turbine to enter a power generation mode based on a spectral amplitude of the measurement data within the sixth preset time length in the specific frequency band.

[0013] Optionally, the step of determining whether to control the wind turbine to enter the power generation mode based on the spectral amplitude of the measurement data within the sixth preset time length in the specific frequency band comprises: in response to an average value of the measurement rotation speed data within the sixth preset time length being greater than a second rotation speed threshold value, determining whether a maximum value of the spectral amplitude of the measurement rotation speed data within the sixth preset time length in the specific frequency band is less than a third amplitude threshold value; and in response to the maximum value of the spectral amplitude of the measurement rotation speed data within the sixth preset time length in the specific frequency band being less than the third amplitude threshold value, controlling the wind turbine to enter the power generation mode; wherein the second rotation speed threshold value is less than the first rotation speed threshold value.

[0014] Optionally, the detection method further comprises: in response to the maximum value of the spectral amplitude of the measurement rotation speed data within the sixth preset time length in the specific frequency band being greater than or equal to the third amplitude threshold value, controlling the wind turbine to continue to be in the shutdown state.

[0015] Optionally, the detection method further comprises: in response to the average of the measured rotational speed data in the sixth preset time period being less than or equal to the second rotational speed threshold, determining whether the cumulative time period at the minimum pitch angle has reached a seventh preset time period; in response to the cumulative time period at the minimum pitch angle having reached the seventh preset time period, controlling the wind turbine generator set to continue to be stopped; and in response to the cumulative time period at the minimum pitch angle not having reached the seventh preset time period, returning to perform the step of controlling the wind turbine generator set to dynamically open the pitch.

[0016] According to a second aspect of the embodiments of the present disclosure, a detection device for icing state of a wind turbine generator set is provided, the detection device comprising: a data acquisition unit configured to acquire measured data and control rotational speed data of the wind turbine generator set in a first preset time period, wherein the measured data comprises measured rotational speed data or measured vibration data, and the control rotational speed data is rotational speed data used for unit control; a frequency spectrum feature analysis unit configured to perform frequency spectrum feature analysis on the measured data and the control rotational speed data to obtain a frequency corresponding to a maximum frequency spectrum amplitude of the measured data and a frequency spectrum amplitude of the control rotational speed data in a specific frequency band, wherein the specific frequency band is a frequency band in which an impeller modal frequency is located; and an icing identification unit configured to determine whether a blade of the wind turbine generator set is in an icing state based on the frequency corresponding to the maximum frequency spectrum amplitude of the measured data and the frequency spectrum amplitude of the control rotational speed data in the specific frequency band.

[0017] Optionally, the icing identification unit is configured to: determine whether the maximum frequency spectrum amplitude of the measured data is greater than a first amplitude threshold; in response to the maximum frequency spectrum amplitude being greater than the first amplitude threshold, determine whether the frequency corresponding to the maximum frequency spectrum amplitude of the measured data is in the specific frequency band; and in response to the frequency corresponding to the maximum frequency spectrum amplitude of the measured data being in the specific frequency band, determine whether the blade is in the icing state based on the frequency spectrum amplitude of the control rotational speed data in the specific frequency band.

[0018] Optionally, the icing identification unit is configured to: determine whether a maximum frequency spectrum amplitude of the control rotational speed data in the specific frequency band is less than a second amplitude threshold, wherein the second amplitude threshold is less than the first amplitude threshold; and in response to the maximum frequency spectrum amplitude of the control rotational speed data in the specific frequency band being less than the second amplitude threshold, perform the following steps N times: control the pitch angle to increase by a preset amplitude, and control the pitch angle to return to the pitch angle before the increase after the pitch angle has been increased for a second preset time period; and determine whether the blade is in the icing state based on changes in the measured data caused by each increase in the pitch angle; wherein N is an integer greater than 1.

[0019] Optionally, the icing identification unit is configured to: determine whether a maximum value of the rotation speed measurement data after each increase in the pitch angle is greater than a first preset threshold value than a rotation speed increase value of the rotation speed measurement data before the increase in the pitch angle; and determine that the blade is in the icing state in response to a proportion of the number of times of increasing the pitch angle corresponding to the rotation speed increase value being greater than the first preset threshold value exceeding a preset proportion.

[0020] Optionally, the icing identification unit is configured to: determine whether a maximum value of the vibration measurement data after each increase in the pitch angle is greater than a second preset threshold value than a vibration decrease value of the vibration measurement data before the increase in the pitch angle; and determine that the blade is in the icing state in response to a proportion of the number of times of increasing the pitch angle corresponding to the vibration decrease value being greater than the second preset threshold value exceeding a preset proportion.

[0021] Optionally, the detection device further comprises a shutdown control unit configured to control the wind turbine generator set to shut down in response to the blade being in the icing state.

[0022] Optionally, the data acquisition unit is configured to: determine whether an average value of the ambient temperature of the wind turbine generator set within a third preset time period is less than a first temperature threshold value and an average value of the ambient humidity within the third preset time period is greater than a humidity threshold value in a case where the wind turbine generator set is in a power generation state; and acquire the measurement data and the control rotation speed data of the wind turbine generator set within the first preset time period in response to the average value of the ambient temperature within the third preset time period being less than the first temperature threshold value and the average value of the ambient humidity being greater than the humidity threshold value.

[0023] Optionally, the icing identification unit is further configured to: determine whether an average value of the ambient temperature of the wind turbine generator set within a fourth preset time period is greater than a second temperature threshold value and an average value of the wind speed within a fifth preset time period is greater than a wind speed threshold value in a case where the wind turbine generator set is in a shutdown state due to icing of the blade; control the wind turbine generator set to dynamically pitch in response to the average value of the ambient temperature within the fourth preset time period being greater than the second temperature threshold value and the average value of the wind speed within the fifth preset time period being greater than the wind speed threshold value, so that the measurement rotation speed data of the wind turbine generator set approaches a first rotation speed threshold value; acquire measurement data of the wind turbine generator set within a sixth preset time period, and determine whether to control the wind turbine generator set to enter a power generation mode based on a spectral amplitude value of the measurement data within the sixth preset time period in the specific frequency band.

[0024] Optionally, the icing identification unit is configured to: in response to the average of the measured rotation speed data in the sixth preset time period being greater than a second rotation speed threshold, determine whether a maximum spectral amplitude of the measured rotation speed data in the specific frequency band in the sixth preset time period is less than a third amplitude threshold; and in response to the maximum spectral amplitude of the measured rotation speed data in the specific frequency band in the sixth preset time period being less than the third amplitude threshold, control the wind turbine generator set to enter a power generation mode; wherein the second rotation speed threshold is less than the first rotation speed threshold.

[0025] Optionally, the icing identification unit is further configured to: in response to the maximum spectral amplitude of the measured rotation speed data in the specific frequency band in the sixth preset time period being greater than or equal to the third amplitude threshold, control the wind turbine generator set to continue to be stopped.

[0026] Optionally, the icing identification unit is further configured to: in response to the average of the measured rotation speed data in the sixth preset time period being less than or equal to the second rotation speed threshold, determine whether an accumulated time period at the minimum pitch angle has reached a seventh preset time period; in response to the accumulated time period at the minimum pitch angle having reached the seventh preset time period, control the wind turbine generator set to continue to be stopped; and in response to the accumulated time period at the minimum pitch angle not having reached the seventh preset time period, return to perform the step of controlling the wind turbine generator set to dynamically open the pitch.

[0027] According to a third aspect of the embodiments of the present disclosure, a computer readable storage medium storing a computer program is provided, when the computer program is executed by a processor, the processor is caused to perform the method for detecting an icing state of a wind turbine generator set as described above.

[0028] According to a fourth aspect of the embodiments of the present disclosure, an electronic device is provided, the electronic device comprising: a processor; and a memory storing a computer program, when the computer program is executed by the processor, the processor is caused to perform the method for detecting an icing state of a wind turbine generator set as described above.

[0029] The method and device for detecting an icing state of a wind turbine generator set according to the exemplary embodiments of the present disclosure can timely and effectively automatically detect whether the blades are iced, without the need to install hardware devices. In addition, after the blades are stopped due to icing, the method and device can automatically detect whether the blade icing has melted and whether the start condition is reached, so as to achieve a state of unmanned operation, improve operation and maintenance efficiency, and reduce power generation loss.

[0030] Additional aspects and / or advantages of the general inventive concept will be set forth in part in the description which follows, and in part will be obvious from the description, or can be learned by practice of the general inventive concept. BRIEF DESCRIPTION OF DRAWINGS

[0031] The above and other objects and features of the present disclosure exemplary embodiments will become more apparent from the following description of the embodiments when taken in conjunction with the accompanying drawings, which together illustrate:

[0032] Figure 1 A flowchart illustrating a method of detecting an icing state of a wind turbine generator system according to an exemplary embodiment of the present disclosure is shown;

[0033] Figure 2 A flowchart illustrating a method of determining whether a blade is in an icing state according to an exemplary embodiment of the present disclosure is shown;

[0034] Figure 3 A flowchart illustrating a method of determining whether a blade is in an icing state based on a spectral amplitude of control rotational speed data in a specific frequency band according to an exemplary embodiment of the present disclosure is shown;

[0035] Figure 4 A flowchart illustrating a method of determining whether to control a wind turbine generator system to enter a power generation mode according to an exemplary embodiment of the present disclosure is shown;

[0036] Figure 5 A flowchart illustrating a method of detecting an icing state of a wind turbine generator system according to another exemplary embodiment of the present disclosure is shown;

[0037] Figure 6 A flowchart illustrating a method of determining whether to control a wind turbine generator system to enter a power generation mode according to another exemplary embodiment of the present disclosure is shown;

[0038] Figure 7 A block diagram illustrating a configuration of a device for detecting an icing state of a wind turbine generator system according to an exemplary embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0039] Reference will now be made in detail embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to like elements throughout. The embodiments herein will be described in sufficient detail by explaining exemplary embodiments thereof generally, but to which it is to be understood that the application is not limited.

[0040] It is to be understood that the terms "first", "second", and the like, used in the description and the claims of the present disclosure as well as the above description of the drawings merely specify the names of important features and do not limit their positions or the order in which they are used. It is to be understood that the terms so used are interchangeable under appropriate circumstances. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present disclosure. Instead, they are merely examples of apparatuses and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0041] It should be noted that "at least one of" in the present disclosure means that the following three cases are included: (1) any one of the items; (2) a combination of any multiple of the items; (3) all of the items. For example, "including at least one of A and B" includes the following three cases: (1) including A; (2) including B; (3) including A and B.

[0042] Figure 1 A flowchart of a method for detecting icing state of a wind turbine generator set according to an example embodiment of the present disclosure is shown.

[0043] As an example, the method for detecting icing state of a wind turbine generator set according to an example embodiment of the present disclosure can be executed by an electronic device with data processing capability, for example, the electronic device can be a terminal (such as a personal notebook, a desktop computer, etc.), or a server (such as a standalone server, a server cluster, a cloud platform, etc.). In addition, it can also be executed by a wind turbine generator set (for example, a central controller of the wind turbine generator set), or a wind farm controller.

[0044] Referring to Figure 1 In step S101, measurement data and control speed data of the wind turbine generator set in a first preset time length are obtained.

[0045] The measurement data includes measurement speed data or measurement vibration data.

[0046] As an example, the measurement speed data is measured rotor speed data.

[0047] As an example, the measurement vibration data is measured rotor vibration data or nacelle vibration data. For example, the rotor vibration data can include but is not limited to rotor acceleration data. The nacelle vibration data can include but is not limited to nacelle acceleration data.

[0048] It should be understood that the measurement data can be obtained in various appropriate ways. As an example, the measurement data can be obtained from SCADA and / or the unit's own PLC or sensors. For example, the measurement speed data can be obtained from a sensor for measuring speed. For example, the measurement vibration data can be obtained from an acceleration sensor installed on the tower or the blade.

[0049] The control speed data is speed data used for unit control. For example, the control speed data can be obtained by filtering the measurement speed data. For example, the control speed data can be speed data used for pitch control and / or torque control.

[0050] As an example, the measurement data and the control speed data of the wind turbine in a first preset time period can be acquired. It should be understood that the first preset time period can be set according to engineering experience, actual conditions and specific requirements, for example, the value of the first preset time period can be between 30s-120s.

[0051] As an example, step S101 can be performed when the wind turbine is in the power generation state.

[0052] As an example, when the wind turbine is in the power generation state, it can be determined whether the average of the ambient temperature of the wind turbine in a third preset time period is less than a first temperature threshold value and whether the average of the ambient humidity in the third preset time period is greater than a humidity threshold value; in response to the average of the ambient temperature in the third preset time period being less than the first temperature threshold value and the average of the ambient humidity being greater than the humidity threshold value, step S101 is performed.

[0053] It should be understood that the third preset time period, the first temperature threshold value and the humidity threshold value can be set according to engineering experience, actual conditions and specific requirements, for example, the value of the first temperature threshold value can be 3 degrees, and the value of the humidity threshold value can be greater than 50%.

[0054] When identifying icing of the blade in the power generation state, the present disclosure considers that icing of the blade requires certain meteorological conditions, so the ambient temperature and humidity are limited to prevent false triggering of icing protection, for example, if the stall caused by high temperature and low air density also produces similar characteristics to icing.

[0055] In step S102, the measurement data and the control speed data are analyzed for spectral features to obtain the frequency corresponding to the maximum spectral amplitude of the measurement data and the spectral amplitude of the control speed data in a specific frequency band.

[0056] The specific frequency band is a frequency band in which the impeller modal frequency is located. As an example, the specific frequency band can be: impeller modal frequency*(1-b)~impeller modal frequency*(1+b). For example, the value of b can be set according to engineering experience, actual conditions and specific requirements, for example, the value of b can be in the range of 0.02-0.05.

[0057] As an example, the impeller modal frequency can include but is not limited to the in-plane modal frequency of the impeller, for example, specifically can include but is not limited to at least one of the following: the first-order in-plane modal frequency of the impeller, the second-order in-plane modal frequency of the impeller, the third-order in-plane modal frequency of the impeller.

[0058] The in-plane modal frequency of the impeller can be understood as the modal frequency of the impeller in the impeller rotation plane, i.e., the modal frequency in the direction of rotation of the impeller, rather than the modal frequency in the direction perpendicular to the impeller rotation plane.

[0059] As an example, the way of performing the spectral feature analysis on the measurement data and the control rotation speed data can include, but is not limited to, a fast Fourier transform. As an example, the measurement data in the first preset time length constitutes a time series (for example, a plurality of measurement rotation speed values in the first preset time length constitute a time series, and the interval time of adjacent measurement rotation speed values is the same, that is, the sampling period of the measurement rotation speed values), and the fast Fourier transform is performed on the time series to obtain a corresponding frequency spectrum, the horizontal axis of the frequency spectrum represents the frequency (unit: Hz), and the vertical axis represents the amplitude value corresponding to the frequency value. As an example, the control rotation speed data in the first preset time length constitutes a time series (for example, a plurality of control rotation speed values in the first preset time length constitute a time series, and the interval time of adjacent control rotation speed values is the same), and the fast Fourier transform is performed on the time series to obtain a corresponding frequency spectrum.

[0060] In step S103, whether the blade of the wind turbine generator is in an icing state is determined based on the frequency corresponding to the maximum spectral amplitude of the measurement data, and the spectral amplitude of the control rotation speed data in the specific frequency band.

[0061] The exemplary embodiments of step S103 will be described below in conjunction with Figure 2 , which will not be expanded here.

[0062] In addition, as an example, the method for detecting the icing state of the wind turbine generator according to the exemplary embodiments of the present disclosure can further include: in response to the blade being in the icing state, controlling the wind turbine generator to shut down.

[0063] According to the exemplary embodiments of the present disclosure, considering the feature that the in-plane modal frequency of the long and flexible blade is abnormally prominent after icing, a blade icing detection method based on the in-plane modal frequency amplitude of the blade is proposed, which can determine whether the blade of the wind turbine generator is in an icing state in a timely, convenient and effective manner based on the spectral features of the measurement data and the control data. Even if the wind turbine generator still reaches the rated power and the rated rotation speed in the early icing stage, the icing of the blade can still be detected in a timely manner and the wind turbine generator can be shut down in a timely manner for protection. Moreover, no additional hardware devices need to be installed.

[0064] The existing scheme generally determines whether the blade is iced according to the operation data of the unit, determines whether the blade is iced, and stops the protection. When the ice is artificially observed or subjectively considered to be melted, the unit is restarted. If the unit can be successfully started, power generation is performed. If the unit cannot be successfully started, the unit is artificially continued to be waited for. At present, whether the blade is iced is determined according to two categories of wind speed and power, and mismatching of rotational speed, and attack angle exceeding the normal operation range of the unit. However, there are certain limitations in determining whether the blade is iced by determining the matching of wind speed and power and rotational speed. First, the wind speed has a precision problem. The anemometer is installed behind the impeller and is affected by the rotation of the impeller. The air density affects the wind energy density, and the measurement point cannot truly reflect the actual equivalent wind speed of the entire impeller plane. The wind energy is proportional to the cube of the wind speed. Considering the accuracy of the wind speed, in order to accurately determine whether the blade is iced, the warning protection shutdown is only performed when the icing is relatively serious in actual application. At the same time, under the condition of blade icing, the anemometer may also be iced or jammed, causing the actual wind speed to be unable to be displayed. When the detected wind speed deviates greatly from the actual wind speed, the blade icing cannot be accurately detected. Similarly, the attack angle detection method also detects whether the blade is iced by comparing the positional relationship between the wind speed and the pitch angle with the design. Similarly, there are problems of deviation caused by the fact that the wind speed detection cannot well represent the actual equivalent wind speed of the impeller or the fact that the anemometer is iced, and limitations. The icing state detection method of the wind turbine generator set according to the example of the present disclosure does not have the problem that the measurement deviation or the measurement distortion caused by icing of the anemometer itself cannot determine or cannot timely determine whether the blade is iced.

[0065] In addition, as an example, the icing state detection method of the wind turbine generator set according to the example of the present disclosure can further include: in a case where the wind turbine generator set is in a shutdown state due to blade icing, determining whether to control the wind turbine generator set to enter a power generation mode. The example of the example embodiment will be described below in conjunction with Figure 4 , which will not be expanded here.

[0066] According to the example embodiment of the present disclosure, the blade icing shutdown can also be used to automatically detect whether the blade icing has melted and whether the blade can reach the start condition, so as to achieve the purpose of unmanned maintenance. The blade icing shutdown has the function of automatically detecting the ice melting state and automatically starting the operation during the waiting process, so as to achieve the state of unmanned operation, improve the operation and maintenance efficiency, and reduce the loss of power generation.

[0067] Figure 2 A flowchart of a method for determining whether a blade is in an icing state according to an example embodiment of the present disclosure is shown.

[0068] Referring to Figure 2 , in step S201, it is determined whether the maximum value of the spectrum amplitude of the measurement data is greater than a first amplitude threshold.

[0069] In step S202, in response to the maximum spectral amplitude of the measurement data being greater than the first amplitude threshold, it is determined whether the frequency corresponding to the maximum spectral amplitude of the measurement data is in the specific frequency band.

[0070] In step S203, in response to the frequency corresponding to the maximum spectral amplitude of the measurement data being in the specific frequency band, it is determined whether the blade is in the icing state based on the spectral amplitude of the control rotational speed data in the specific frequency band. Exemplary embodiments of step S203 will be described below in conjunction with Figure 3

[0071] It should be understood that the first amplitude threshold can be set according to engineering experience, actual conditions and specific requirements, for example, when the measurement data is the measurement rotational speed data, the first amplitude threshold can be greater than or equal to 0.02.

[0072] The present disclosure considers that if the blade is iced, the measurement data (for example, the measurement rotational speed) will exhibit a strong impeller modal frequency, but the impeller modal frequency actually exists regardless of icing, and if the measurement rotational speed is not filtered when used for unit control, it will be coupled to the control rotational speed even if it is not iced, causing further oscillation of the system control. The reason for obtaining the actual measurement rotational speed and the control rotational speed is to check whether the control filtering is reasonable to prevent false triggering of the icing protection.

[0073] Therefore, the present disclosure proposes to first determine the maximum spectral amplitude of the measurement rotational speed, and if it is not large, it represents that the rotational speed is very stable and there is no need to consider the possibility that the current unit has an abnormality. If the maximum spectral amplitude of the measurement rotational speed is large and the corresponding frequency is in the range close to the impeller plane frequency, it indicates that the impeller modal frequency corresponding to the icing feature appears.

[0074] Figure 3 A flowchart showing a method for determining whether a blade is in an icing state based on the spectral amplitude of control rotational speed data in a specific frequency band according to an exemplary embodiment of the present disclosure is shown.

[0075] Referring to Figure 3 In step S301, it is determined whether the maximum spectral amplitude of the control rotational speed data in the specific frequency band is less than a second amplitude threshold.

[0076] As an example, the second amplitude threshold is less than the first amplitude threshold. It should be understood that the second amplitude threshold can be set according to engineering experience, actual conditions and specific requirements, for example, when the measurement data is the measurement rotational speed data, the second amplitude threshold can be in the range of 0.3-0.5 of the first amplitude threshold.

[0077] If the amplitude corresponding to the frequency range close to the control rotational speed impeller plane modal is still large, it indicates that the control does not have the expected effect, and the prominent amplitude of the measurement rotational speed impeller modal frequency is caused by the filter control excitation of the control system.​

[0078] In step S302, in response to the maximum value of the spectral amplitude of the control rotation speed data in the specific frequency band being less than the second amplitude threshold, the following steps are performed N times: the pitch angle is controlled to increase by a preset amplitude, and the pitch angle is controlled to return to the pitch angle before the last increase after the pitch angle has been increased for a second preset time length.

[0079] The increase of the pitch angle can be controlled in an appropriate manner. For example, the pitch angle can be increased by a preset amplitude by increasing the minimum pitch angle, and the pitch angle can be returned to the pitch angle before the last increase by returning the minimum pitch angle to the value before the increase.

[0080] It should be understood that the preset amplitude can be set according to engineering experience, actual conditions and specific needs. For example, the preset amplitude can be in the range of 1 degree to 2 degrees.

[0081] It should be understood that the second preset time length can be set according to engineering experience, actual conditions and specific needs. For example, the second preset time length can be in the range of 3 seconds to 5 seconds.

[0082] N is an integer greater than 1. It should be understood that the value of N can be set according to engineering experience, actual conditions and specific needs. For example, N can be in the range of 5 to 8.

[0083] In step S303, based on the change in the measurement data caused by each increase in the pitch angle, it is determined whether the blade is in an icing state.

[0084] In one embodiment, when the measurement data includes measured rotation speed data, step S303 can include: determining whether the maximum value of the rotation speed measurement data after each increase in the pitch angle is greater than the first preset threshold value compared to the rotation speed measurement data before the last increase in the pitch angle; and in response to the proportion of the number of times the pitch angle is increased that corresponds to the rotation speed increase value being greater than the first preset threshold value exceeding a preset proportion of N, determining that the blade is in an icing state.

[0085] The maximum value of the rotation speed measurement data after each increase in the pitch angle is the maximum value of the rotation speed measurement data within the second preset time length after the last increase in the pitch angle, and the rotation speed measurement data before the last increase in the pitch angle is the rotation speed measurement data at the time of the last increase in the pitch angle.

[0086] It should be understood that the first preset threshold value can be set according to engineering experience, actual conditions and specific needs. For example, the first preset threshold value can be in the range of 0.15 to 0.3 Rpm.

[0087] It should be understood that the preset proportion can be set according to engineering experience, actual conditions and specific needs. For example, the preset proportion can be in the range of 0.7 to 0.9.

[0088] In another embodiment, when the measurement data comprises vibration measurement data, step S303 can comprise: determining whether the vibration reduction value of the maximum value of the vibration measurement data after each increase in the pitch angle compared to the vibration measurement data before the increase in the pitch angle is greater than a second preset threshold value; and in response to the proportion of the number of times of increasing the pitch angle corresponding to the vibration reduction value being greater than the second preset threshold value exceeding a preset proportion, determining that the blade is in an icing state.

[0089] It should be understood that the second preset threshold value can be set according to engineering experience, actual conditions and specific requirements.

[0090] The present disclosure considers that when the unit blade is iced, it is necessarily in an icing stall state, at which time the rotational speed and power are increased instead of being reduced (the pitch angle is increased to get rid of the stall state), and the result of one increase is not accurate enough, and N increases are needed. If the rotational speed and power are increased in most of the increases, it represents that the unit is truly in an icing stall state, and thus the shutdown is protected.

[0091] For a current large-impeller unit, it needs to be shutdown for protection when iced, otherwise the damage to the blade is great. Even if the pitch angle is increased to temporarily get rid of the stall state, the blade load is increased, the ice will not melt in a period of time, and the stall state cannot be sustained for a long time, and the damage to the blade is great.

[0092] According to the example embodiment of the present disclosure, based on the prominent feature of the amplitude of the in-plane modal frequency of the impeller in the measurement signal, combined with the environmental factors, the control rotational speed feature and the pitch angle increase test, the blade icing can be detected in time and protection is performed, even if the unit is in a full-load state.

[0093] Figure 4 A flowchart of a method for determining whether to control a wind turbine generator to enter a power generation mode according to an example embodiment of the present disclosure is shown.

[0094] Referring to Figure 4 In step S401, in the case that the wind turbine generator is in a shutdown state due to blade icing, it is determined whether the average value of the environmental temperature of the wind turbine generator in a fourth preset time length is greater than a second temperature threshold value, and whether the average value of the wind speed in a fifth preset time length is greater than a wind speed threshold value.

[0095] As an example, the average value of the wind speed in the fifth preset time length can be calculated by a sliding window method.

[0096] It should be understood that the fourth preset time length can be set according to engineering experience, actual conditions and specific requirements, for example, the value range of the fourth preset time length can be 1 hour to 3 hours.

[0097] It should be understood that the fifth preset time length can be set according to engineering experience, actual conditions and specific requirements, for example, the value range of the fifth preset time length can be 3 minutes to 10 minutes.

[0098] It should be understood that the second temperature threshold can be set according to engineering experience, actual conditions and specific requirements, for example, the value range of the second temperature threshold can be 5 degrees to 10 degrees.

[0099] It should be understood that the wind speed threshold can be set according to engineering experience, actual conditions and specific requirements, for example, the value range of the wind speed threshold can be 3 m / s to 4 m / s.

[0100] In step S402, in response to the average of the environmental temperature in the fourth preset time length being greater than the second temperature threshold and the average of the wind speed in the fifth preset time length being greater than the wind speed threshold, the wind turbine generator set is controlled to dynamically open the pitch, so that the measured speed data of the wind turbine generator set approaches the first speed threshold.

[0101] Dynamic opening of the pitch can be understood as controlling the speed by controlling the pitch angle, so that the speed approaches the first speed threshold as much as possible and is near the first speed threshold.

[0102] It should be understood that the first speed threshold can be set according to engineering experience, actual conditions and specific requirements, for example, the first speed threshold can be k*grid-connected speed. For example, the value range of k can be 0.8 to 0.9.

[0103] According to the exemplary embodiments of the present disclosure, it is determined whether the ice has melted away according to the environmental temperature, and it is determined whether the current wind speed can support the unit to automatically test whether the ice has melted. Only when the environmental temperature reaches the ice melting degree and the current wind speed can support the unit speed to reach the test requirement, the test can be performed, otherwise the waiting continues. Dynamic opening of the pitch makes the unit speed reach a certain level, so that subsequent feature judgment can be performed, and if the speed is low, subsequent judgment will not be possible.

[0104] In step S403, the measured data of the wind turbine generator set in the sixth preset time length is obtained, and it is determined whether to control the wind turbine generator set to enter the power generation mode based on the frequency spectrum amplitude of the measured data in the sixth preset time length in a specific frequency band.

[0105] Here, the measured data in the sixth preset time length includes: measured speed data or measured vibration data in the sixth preset time length.

[0106] As an example, step S403 can comprise: in response to the average of the measured rotational speed data in the sixth preset time period being greater than the second rotational speed threshold, determining whether the maximum spectral amplitude of the measured rotational speed data (or the measured vibration data) in the specific frequency band in the sixth preset time period is less than a third amplitude threshold; in response to the maximum spectral amplitude of the measured rotational speed data (or the measured vibration data) in the specific frequency band in the sixth preset time period being less than the third amplitude threshold, controlling the wind turbine to enter the power generation mode.

[0107] The second rotational speed threshold is less than the first rotational speed threshold. It should be understood that the second rotational speed threshold can be set according to engineering experience, actual conditions and specific requirements, for example, the second rotational speed threshold can be l*grid-connected rotational speed. For example, the value range of l can be 0.7-0.8.

[0108] It should be understood that the sixth preset time period can be set according to engineering experience, actual conditions and specific requirements, for example, the value range of the sixth preset time period can be 30s-60s.

[0109] It should be understood that the third amplitude threshold can be set according to engineering experience, actual conditions and specific requirements, for example, the value range of the third amplitude threshold can be 0.01-0.015.

[0110] In addition, as an example, the method for determining whether to control the wind turbine to enter the power generation mode according to the example embodiment of the present disclosure can further comprise: in response to the maximum spectral amplitude of the measured rotational speed data in the specific frequency band in the sixth preset time period being greater than or equal to the third amplitude threshold, controlling the wind turbine to continue to stop and wait. That is, controlling the wind turbine to stop with the blades closed and returning to execute step S401.

[0111] In addition, as an example, the method for determining whether to control the wind turbine to enter the power generation mode according to the example embodiment of the present disclosure can further comprise: in response to the average of the measured rotational speed data in the sixth preset time period being less than or equal to the second rotational speed threshold, determining whether the cumulative time period at the minimum pitch angle has reached a seventh preset time period; in response to the cumulative time period at the minimum pitch angle having reached the seventh preset time period, controlling the wind turbine to continue to stop and wait; in response to the cumulative time period at the minimum pitch angle not having reached the seventh preset time period, returning to continue to execute the step of controlling the wind turbine to dynamically open the blades.

[0112] As an example, being at the minimum pitch angle can be understood as being near the minimum pitch angle, for example, less than (the minimum pitch angle+2 degrees) can also be considered as being at the minimum pitch angle.

[0113] It should be understood that the seventh preset time period can be set according to engineering experience, actual conditions and specific requirements, for example, the value range of the seventh preset time period can be 40s-80s.

[0114] The disclosure considers that when the continuously acquired average speed is greater than a certain value, it has further judgment value, if the unit speed does not reach a certain level and the pitch angle has been opened to the minimum and has been sustained for a certain time, it can only be explained that the current wind speed is small or the blades are still severely frozen, and it can only continue to wait for a time unit to test the start of the machine again. If one of the conditions of opening the pitch to the minimum and sustaining for a certain time is not established, the dynamic pitch opening to improve the speed is continued. When the speed reaches a certain level during testing, the extracted impeller plane modal frequency amplitude is no longer large, which indicates that the ice has melted and can be connected to the grid.

[0115] The two categories of blade icing detection methods based on current operating data do not have the automatic function of judging whether the ice has melted after the blade icing shutdown protection, and can start the machine again. It depends on the on-site inspection of the operation and maintenance personnel or the subjective direct start of the machine. When the ice has not completely melted, the unit will be shut down again due to icing protection after a period of operation. In this way, the operation and maintenance efficiency is low, and when the unit is connected to the grid and the speed is high, the fatigue damage of the blade icing to the blade will be large.

[0116] In addition, Figure 5 A flowchart of a method for detecting an icing state of a wind turbine generator set according to another example embodiment of the disclosure is shown. Figure 6 A flowchart of a method for determining whether to control a wind turbine generator set to enter a power generation mode according to another example embodiment of the disclosure is shown. In the two embodiments, the measurement data includes measurement speed data.

[0117] Figure 7 A structural block diagram of a device for detecting an icing state of a wind turbine generator set according to an example embodiment of the disclosure is shown.

[0118] Referring to Figure 7 The device for detecting an icing state of a wind turbine generator set according to an example embodiment of the disclosure includes a data acquisition unit 101, a spectrum feature analysis unit 102, and an icing identification unit 103.

[0119] Specifically, the data acquisition unit 101 is configured to acquire measurement data and control speed data of the wind turbine generator set within a first preset time length, wherein the measurement data includes measurement speed data or measurement vibration data, and the control speed data is speed data used for unit control.

[0120] The spectrum feature analysis unit 102 is configured to perform spectrum feature analysis on the measurement data and the control speed data to obtain a frequency corresponding to a maximum spectrum amplitude value of the measurement data and a spectrum amplitude value of the control speed data in a specific frequency band, wherein the specific frequency band is a frequency band in which an impeller modal frequency is located.

[0121] The icing identification unit 103 is configured to determine whether the blade of the wind turbine generator is in an icing state based on a frequency corresponding to a maximum spectral amplitude of the measurement data, and a spectral amplitude of the control rotation speed data in the specific frequency band.

[0122] As an example, the icing identification unit 103 can be configured to: determine whether the maximum spectral amplitude of the measurement data is greater than a first amplitude threshold; in response to the maximum spectral amplitude being greater than the first amplitude threshold, determine whether the frequency corresponding to the maximum spectral amplitude of the measurement data is in the specific frequency band; and in response to the frequency corresponding to the maximum spectral amplitude of the measurement data being in the specific frequency band, determine whether the blade is in the icing state based on the spectral amplitude of the control rotation speed data in the specific frequency band.

[0123] As an example, the icing identification unit 103 can be configured to: determine whether the maximum spectral amplitude of the control rotation speed data in the specific frequency band is less than a second amplitude threshold, wherein the second amplitude threshold is less than the first amplitude threshold; in response to the maximum spectral amplitude of the control rotation speed data in the specific frequency band being less than the second amplitude threshold, perform the following steps N times: control the pitch angle to increase by a preset amplitude, and control the pitch angle to return to the pitch angle before the increase after a second preset time length from the start of the increase of the pitch angle; determine whether the blade is in the icing state based on changes in the measurement data caused by each increase of the pitch angle; wherein N is an integer greater than 1.

[0124] As an example, the icing identification unit 103 can be configured to: determine whether a rotation speed increase value of a maximum rotation speed measurement data after each increase of the pitch angle compared to the rotation speed measurement data before the increase of the pitch angle is greater than a first preset threshold; and in response to a proportion of the number of times of the increase of the pitch angle corresponding to the rotation speed increase value being greater than the first preset threshold exceeding a preset proportion of N, determine that the blade is in the icing state.

[0125] As an example, the icing identification unit 103 can be configured to: determine whether a vibration decrease value of a maximum vibration measurement data after each increase of the pitch angle compared to the vibration measurement data before the increase of the pitch angle is greater than a second preset threshold; and in response to a proportion of the number of times of the increase of the pitch angle corresponding to the vibration decrease value being greater than the second preset threshold exceeding a preset proportion of N, determine that the blade is in the icing state.

[0126] As an example, the detection device can further include a shutdown control unit (not shown) configured to control the wind turbine generator to shut down in response to the blade being in the icing state.

[0127] As an example, the data acquisition unit 101 can be configured to, in a case that the wind turbine is in a power generation state, determine whether an average of an ambient temperature of the wind turbine in a third preset time length is less than a first temperature threshold value and an average of an ambient humidity in the third preset time length is greater than a humidity threshold value; in response to the average of the ambient temperature in the third preset time length being less than the first temperature threshold value and the average of the ambient humidity being greater than the humidity threshold value, acquire measurement data and control rotation speed data of the wind turbine in the first preset time length.

[0128] As an example, the icing identification unit 103 can be further configured to, in a case that the wind turbine is in a shutdown state due to blade icing, determine whether an average of an ambient temperature of the wind turbine in a fourth preset time length is greater than a second temperature threshold value and an average of a wind speed in a fifth preset time length is greater than a wind speed threshold value; in response to the average of the ambient temperature in the fourth preset time length being greater than the second temperature threshold value and the average of the wind speed in the fifth preset time length being greater than the wind speed threshold value, control the wind turbine to dynamically open the blades so as to make the measurement rotation speed data of the wind turbine close to a first rotation speed threshold value; acquire measurement data of the wind turbine in a sixth preset time length, and determine whether to control the wind turbine to enter a power generation mode based on a spectral amplitude of the measurement data in the specific frequency band in the sixth preset time length.

[0129] As an example, the icing identification unit 103 can be configured to, in response to the average of the measurement rotation speed data in the sixth preset time length being greater than a second rotation speed threshold value, determine whether a maximum value of the spectral amplitude of the measurement rotation speed data in the specific frequency band in the sixth preset time length is less than a third amplitude threshold value; in response to the maximum value of the spectral amplitude of the measurement rotation speed data in the specific frequency band in the sixth preset time length being less than the third amplitude threshold value, control the wind turbine to enter the power generation mode; wherein the second rotation speed threshold value is less than the first rotation speed threshold value.

[0130] As an example, the icing identification unit 103 can be further configured to, in response to the maximum value of the spectral amplitude of the measurement rotation speed data in the specific frequency band in the sixth preset time length being greater than or equal to the third amplitude threshold value, control the wind turbine to continue to be in the shutdown state.

[0131] As an example, the icing identification unit 103 can be further configured to: in response to the average of the measured rotation speed data in the sixth preset time period being less than or equal to the second rotation speed threshold, determine whether the accumulated time period at the minimum pitch angle has reached a seventh preset time period; in response to the accumulated time period at the minimum pitch angle having reached the seventh preset time period, control the wind turbine to continue to be stopped; and in response to the accumulated time period at the minimum pitch angle not having reached the seventh preset time period, return to perform the step of controlling the wind turbine to dynamically open the pitch.

[0132] It should be understood that the specific processes performed by the wind turbine icing state detection apparatus according to the exemplary embodiments of the present disclosure have been described in detail above with reference to the Figures 1 to 6 related details will not be repeated here.

[0133] It should be understood that each unit in the wind turbine icing state detection apparatus according to the exemplary embodiments of the present disclosure can be implemented by hardware components and / or software components. Those skilled in the art can implement each unit, for example, using a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC), according to the processes performed by each unit defined.

[0134] The exemplary embodiments of the present disclosure provide a computer readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the wind turbine icing state detection method according to the exemplary embodiments described above. The computer readable storage medium is any data storage device that can store data readable by a computer system. Examples of the computer readable storage medium include a read-only memory, a random access memory, a read-only optical disc, a magnetic tape, a floppy disc, an optical data storage device, and a carrier wave (such as data transmission through an internet via a wired or wireless transmission path).

[0135] An electronic device according to the exemplary embodiments of the present disclosure includes a processor (not shown) and a memory (not shown), wherein the memory stores a computer program, which, when executed by the processor, causes the processor to perform the wind turbine icing state detection method according to the exemplary embodiments described above.

[0136] As an example, the electronic device can be a wind turbine (for example, a central controller of a wind turbine), a wind farm controller. In addition, it can also be a terminal (such as a personal notebook, a desktop computer, etc.), and can also be a server (such as a standalone server, a server cluster, a cloud platform, etc.).

[0137] While certain example embodiments of the disclosure have been described and shown, it is understood that modifications will occur to those skilled in the art, without departing from the spirit and scope of the disclosure as defined by the following claims and their equivalents.

Claims

1. A method of detecting icing condition of a wind turbine, characterized in that, The detection method comprises: obtaining measurement data and control speed data of the wind turbine within a first preset time length, wherein the measurement data comprises measurement speed data or measurement vibration data, and the control speed data is speed data used for unit control; performing spectrum feature analysis on the measurement data and the control speed data to obtain a frequency corresponding to a maximum spectrum amplitude of the measurement data and a spectrum amplitude of the control speed data in a specific frequency band, wherein the specific frequency band is a frequency band in which an impeller modal frequency is located; determining whether the blade of the wind turbine is in an icing state based on the frequency corresponding to the maximum spectrum amplitude of the measurement data and the spectrum amplitude of the control speed data in the specific frequency band.

2. The detection method according to claim 1, characterized in that, The step of determining whether the blade of the wind turbine is in an icing state based on the frequency corresponding to the maximum spectrum amplitude of the measurement data and the spectrum amplitude of the control speed data in the specific frequency band comprises: determining whether the maximum spectrum amplitude of the measurement data is greater than a first amplitude threshold value; in response to the maximum spectrum amplitude being greater than the first amplitude threshold value, determining whether the frequency corresponding to the maximum spectrum amplitude of the measurement data is in the specific frequency band; in response to the frequency corresponding to the maximum spectrum amplitude of the measurement data being in the specific frequency band, determining whether the blade is in an icing state based on the spectrum amplitude of the control speed data in the specific frequency band.

3. The detection method according to claim 2, characterized in that, The step of determining whether the blade is in an icing state based on the spectrum amplitude of the control speed data in the specific frequency band comprises: determining whether a maximum spectrum amplitude of the control speed data in the specific frequency band is less than a second amplitude threshold value, wherein the second amplitude threshold value is less than the first amplitude threshold value; in response to the maximum spectrum amplitude of the control speed data in the specific frequency band being less than the second amplitude threshold value, performing the following steps N times: controlling the pitch angle to increase by a preset amplitude, and then controlling the pitch angle to return to the pitch angle before the increase after a second preset time length from the start of the increase of the pitch angle; determining whether the blade is in an icing state based on the measurement data changes caused by each increase of the pitch angle; wherein N is an integer greater than 1.

4. The detection method according to claim 3, characterized in that, The step of determining whether the blade is in an icing state based on the measurement data changes caused by each increase of the pitch angle comprises: determining whether a speed increase value of a maximum speed measurement data after each increase of the pitch angle compared to the speed measurement data before the increase of the pitch angle is greater than a first preset threshold value; in response to a proportion of the number of times of the increase of the pitch angle corresponding to the speed increase value being greater than the first preset threshold value to N exceeding a preset proportion, determining that the blade is in an icing state.

5. The detection method according to claim 3, characterized in that, The step of determining whether the blade is in an icing state based on the measurement data changes caused by each increase of the pitch angle comprises: determining whether a vibration decrease value of a maximum vibration measurement data after each increase of the pitch angle compared to the vibration measurement data before the increase of the pitch angle is greater than a second preset threshold value; In response to the proportion of the number of times of increasing the pitch angle corresponding to the vibration reduction value being greater than the second preset threshold exceeding a preset proportion, it is determined that the blade is in an icing state.

6. The method of claim 1, wherein, The detection method further comprises: In response to the blade being in the icing state, the wind turbine generator set is controlled to stop.

7. The method of claim 1, wherein, The step of obtaining the measurement data and the control speed data of the wind turbine generator set within a first preset time length comprises: In a case where the wind turbine generator set is in a power generation state, it is determined whether an average ambient temperature of the wind turbine generator set within a third preset time length is less than a first temperature threshold and whether an average ambient humidity within the third preset time length is greater than a humidity threshold; In response to the average ambient temperature within the third preset time length being less than the first temperature threshold and the average ambient humidity being greater than the humidity threshold, the measurement data and the control speed data of the wind turbine generator set within the first preset time length are obtained.

8. The method of claim 1, wherein, The detection method further comprises: In a case where the wind turbine generator set is in a stop state due to icing of the blade, it is determined whether an average ambient temperature of the wind turbine generator set within a fourth preset time length is greater than a second temperature threshold and whether an average wind speed within a fifth preset time length is greater than a wind speed threshold; In response to the average ambient temperature within the fourth preset time length being greater than the second temperature threshold and the average wind speed within the fifth preset time length being greater than the wind speed threshold, the wind turbine generator set is controlled to be dynamically pitched to make the measurement speed data of the wind turbine generator set close to a first speed threshold; The measurement data of the wind turbine generator set within a sixth preset time length is obtained, and based on a spectral amplitude of the measurement data within the sixth preset time length in the specific frequency band, it is determined whether to control the wind turbine generator set to enter a power generation mode.

9. The detection method according to claim 8, characterized in that, The step of determining whether to control the wind turbine generator set to enter the power generation mode based on the spectral amplitude of the measurement data within the sixth preset time length in the specific frequency band comprises: In response to the average measurement speed data within the sixth preset time length being greater than a second speed threshold, it is determined whether a maximum spectral amplitude of the measurement speed data within the sixth preset time length in the specific frequency band is less than a third amplitude threshold; In response to the maximum spectral amplitude of the measurement speed data within the sixth preset time length in the specific frequency band being less than the third amplitude threshold, the wind turbine generator set is controlled to enter the power generation mode; The second speed threshold is less than the first speed threshold.

10. The detection method according to claim 9, characterized in that, The detection method further comprises: In response to the maximum spectral amplitude of the measurement speed data within the sixth preset time length in the specific frequency band being greater than or equal to the third amplitude threshold, the wind turbine generator set is controlled to continue to stop.

11. The detection method of claim 9, wherein, The detection method further comprises: In response to the average measurement speed data within the sixth preset time length being less than or equal to the second speed threshold, it is determined whether an accumulated time length in a minimum pitch angle has reached a seventh preset time length; In response to the accumulated time length in the minimum pitch angle having reached the seventh preset time length, the wind turbine generator set is controlled to continue to stop. In response to the accumulated time length in the minimum pitch angle not reaching the seventh preset time length, returning to perform the step of controlling dynamic pitch opening of the wind turbine generator set.

12. An apparatus for detecting icing conditions on a wind turbine generator system, comprising: The detection device comprises: a data acquisition unit configured to acquire measurement data and control rotation speed data of the wind turbine generator set within a first preset time length, wherein the measurement data comprises measurement rotation speed data or measurement vibration data, and the control rotation speed data is rotation speed data for unit control; a spectrum feature analysis unit configured to perform spectrum feature analysis on the measurement data and the control rotation speed data to obtain a frequency corresponding to a maximum spectrum amplitude of the measurement data and a spectrum amplitude of the control rotation speed data in a specific frequency band, wherein the specific frequency band is a frequency band in which an impeller modal frequency is located; an icing identification unit configured to determine whether the blades of the wind turbine generator set are in an icing state based on the frequency corresponding to the maximum spectrum amplitude of the measurement data and the spectrum amplitude of the control rotation speed data in the specific frequency band.

13. A computer readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, the processor is caused to perform the wind turbine generator set icing state detection method according to any one of claims 1 to 11.

14. An electronic device, comprising: The electronic device comprises: a processor; a memory storing a computer program, when the computer program is executed by a processor, the processor is caused to perform the wind turbine generator set icing state detection method according to any one of claims 1 to 11.

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