Method and device for detecting icing state of wind generating set

Abstract

The invention provides a method and a device for detecting the icing state of a wind generating set. The detection method comprises the steps that measurement data and control rotating speed data of the wind generating set in a first preset duration are obtained, the measurement data comprise measurement rotating speed data or measurement vibration data, and the control rotating speed data are rotating speed data used for controlling the set; spectrum characteristic analysis is conducted on the measurement data and the control rotating speed data, the frequency corresponding to the maximum value of the spectrum amplitude of the measurement data and the spectrum amplitude of the control rotating speed data in a specific frequency band are obtained, and the specific frequency band is the frequency band where the impeller modal frequency is located; and 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 rotating speed data in the specific frequency band, whether the blade of the wind generating set is in an icing state or not is determined.

Description

Technical Field

[0001] The present disclosure generally relates to the field of wind power generation technology, and more specifically, to a method and device for detecting an icing state of a wind turbine generator set. Background Art

[0002] Blade icing is a common phenomenon in wind turbines (hereinafter referred to as wind turbines) in winter or spring. With the increase in large-capacity, long and flexible blade units, the industry has paid more and more attention to the hazards of blade icing or severe frost, hoping to detect the blade icing status as early as possible and perform shutdown protection in time.

[0003] However, due to the large surface area of ​​the blades (the surface area of ​​a 70-meter-long blade reaches more than 500 square meters), it is very expensive to install heating devices or ice monitoring sensors to achieve the desired effect after the blades are covered with ice. As a result, the installation of hardware equipment for de-icing or ice detection cannot be promoted and applied in actual engineering projects. Summary of the invention

[0004] An exemplary embodiment of the present disclosure provides a method and device for detecting the icing state of a wind turbine generator set, which can automatically detect whether a blade is frozen in a timely and effective manner without the need to install additional hardware equipment.

[0005] According to a first aspect of an embodiment of the present disclosure, a method for detecting an icing state of a wind turbine is provided, the detection method comprising: acquiring measurement data and control speed data of the wind turbine within a first preset time period, 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 spectral feature analysis on the measurement data and the control speed data to obtain a frequency corresponding to a maximum value of the spectral amplitude of the measurement data and a spectral amplitude of the control speed data in a specific frequency band, wherein the specific frequency band is a frequency band where an impeller modal frequency is located; determining whether the blades of the wind turbine are in an icing state based on the frequency corresponding to the maximum value of the spectral amplitude of the measurement data and the spectral amplitude of the control speed data in the specific frequency band.

[0006] Optionally, the step of determining whether the blades of the wind turbine generator set are in an ice-covered state based on the frequency corresponding to the maximum value of the spectrum amplitude of the measurement data and the spectrum amplitude of the control speed data in the specific frequency band includes: determining whether the maximum value of the spectrum amplitude of the measurement data is greater than a first amplitude threshold; in response to the maximum value of the spectrum amplitude being greater than the first amplitude threshold, determining whether the frequency corresponding to the maximum value of the spectrum amplitude of the measurement data is in the specific frequency band; in response to the frequency corresponding to the maximum value of the spectrum amplitude of the measurement data being in the specific frequency band, determining whether the blades are in an ice-covered state based on the spectrum amplitude of the control speed data in the specific frequency band.

[0007] Optionally, the step of determining whether the blade is in an ice-covered state based on the spectral amplitude of the control speed data in the specific frequency band includes: determining whether the maximum spectral amplitude of the control 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 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 being increased after the pitch angle is increased for a second preset time; determining whether the blade is in an ice-covered state based on the changes in the measured data brought about 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 an ice-covered state based on the change in measurement data brought about by each increase in the pitch angle includes: determining whether the maximum value of the speed measurement data after each increase in the pitch angle is greater than a first preset threshold value compared to the speed increase value of the speed measurement data before the pitch angle is increased; in response to the proportion of the number of pitch angle increases in which the corresponding speed increase value is greater than the first preset threshold value to N exceeds a preset proportion, determining that the blade is in an ice-covered state.

[0009] Optionally, the step of determining whether the blade is in an ice-covered state based on the change in measurement data brought about by each increase in the pitch angle includes: determining whether a maximum value of the vibration measurement data after each increase in the pitch angle is greater than a second preset threshold value compared to a vibration reduction value of the vibration measurement data before the pitch angle is increased; in response to the proportion of the number of pitch angle increases in which the corresponding vibration reduction value is greater than the second preset threshold value to N exceeds a preset proportion, determining that the blade is in an ice-covered state.

[0010] Optionally, the detection method further includes: in response to the blade being in an ice-covered state, controlling the wind turbine generator set to shut down.

[0011] Optionally, the step of obtaining the measurement data and control speed data of the wind turbine generator set within a first preset time period includes: when the wind turbine generator set is in a power generation state, determining whether the average ambient temperature of the wind turbine generator set within a third preset time period is less than a first temperature threshold, and whether the average ambient humidity within the third preset time period is greater than a humidity threshold; in response to the average ambient temperature within the third preset time period being less than the first temperature threshold and the average ambient humidity being greater than the humidity threshold, obtaining the measurement data and control speed data of the wind turbine generator set within the first preset time period.

[0012] Optionally, the detection method also includes: when the wind turbine generator set is in a shutdown state due to blade icing, determining whether the average ambient temperature of the wind turbine generator set within a fourth preset time period is greater than a second temperature threshold, and whether the average wind speed within a fifth preset time period is greater than a wind speed threshold; in response to the average ambient temperature within the fourth preset time period being greater than the second temperature threshold and the average wind speed within the fifth preset time period being greater than the wind speed threshold, controlling the wind turbine generator set to dynamically start propellers so that the measured speed data of the wind turbine generator set is close to the first speed threshold; obtaining the measurement data of the wind turbine generator set within a sixth preset time period, and determining whether to control the wind turbine generator set to enter a power generation mode based on the spectrum amplitude of the measurement data within the sixth preset time period in the specific frequency band.

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

[0014] Optionally, the detection method further includes: in response to the maximum value of the spectrum amplitude of the measured rotation speed data within the sixth preset time period in the specific frequency band being greater than or equal to the third amplitude threshold, controlling the wind turbine generator set to continue to shut down.

[0015] Optionally, the detection method also includes: in response to the average value of the measured speed data within the sixth preset time period being less than or equal to the second speed threshold, determining whether the cumulative time at the minimum pitch angle has reached a seventh preset time period; in response to the cumulative time at the minimum pitch angle having reached the seventh preset time period, controlling the wind turbine to continue to shut down; in response to the cumulative time at the minimum pitch angle not reaching the seventh preset time period, returning to execute the step of controlling the wind turbine to dynamically start the propeller.

[0016] According to a second aspect of an embodiment of the present disclosure, a device for detecting an icing state of a wind turbine generator set is provided, the detection device comprising: a data acquisition unit, configured to acquire measurement data and control speed data of the wind turbine generator set within a first preset time period, wherein the measurement data comprises measurement speed data or measurement vibration data, and the control speed data is speed data used for unit control; a spectrum feature analysis unit, configured to perform spectrum feature analysis on the measurement data and the control speed data to obtain a frequency corresponding to a maximum value of the 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 where 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 value of the spectrum amplitude of the measurement data and the spectrum amplitude of the control speed data in the specific frequency band.

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

[0018] Optionally, the icing identification unit is configured to: determine whether the maximum value of the spectrum amplitude of the control 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 value of the spectrum amplitude of the control 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 being increased after the pitch angle is increased for a second preset time; determine whether the blade is in an icing state based on the changes in the measured data brought about 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 the maximum value of the speed measurement data after each increase in the pitch angle is greater than a first preset threshold compared to the speed increase value of the speed measurement data before the pitch angle is increased; in response to the proportion of the number of pitch angle increases whose corresponding speed increase value is greater than the first preset threshold to N exceeds a preset proportion, determine that the blade is in an icing state.

[0020] Optionally, the icing identification unit is configured to: determine whether the maximum value of the vibration measurement data after each increase in the pitch angle is greater than a second preset threshold compared to the vibration reduction value of the vibration measurement data before the pitch angle is increased; in response to the proportion of the number of pitch angle increases for which the corresponding vibration reduction value is greater than the second preset threshold exceeding a preset proportion, determine that the blade is in an icing state.

[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 an ice-covered state.

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

[0023] Optionally, the icing identification unit is further configured to: when the wind turbine is in a shutdown state due to blade icing, determine whether the average ambient temperature of the wind turbine within a fourth preset time period is greater than a second temperature threshold, and whether the average wind speed within a fifth preset time period is greater than a wind speed threshold; in response to the average ambient temperature within the fourth preset time period being greater than the second temperature threshold and the average wind speed within the fifth preset time period being greater than the wind speed threshold, control the wind turbine to dynamically start propellers so that the measured speed data of the wind turbine is close to the first speed threshold; obtain the measurement data of the wind turbine within a sixth preset time period, and determine whether to control the wind turbine to enter a power generation mode based on the spectrum amplitude of the measurement data within the sixth preset time period in the specific frequency band.

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

[0025] Optionally, the ice recognition unit is further configured to: in response to the maximum value of the spectrum amplitude of the measured rotational speed data within the sixth preset time period in the specific frequency band being greater than or equal to the third amplitude threshold, control the wind turbine generator set to continue to shut down.

[0026] Optionally, the ice recognition unit is further configured to: in response to the average value of the measured speed data within the sixth preset time period being less than or equal to the second speed threshold, determine whether the cumulative time at the minimum pitch angle has reached a seventh preset time period; in response to the cumulative time at the minimum pitch angle having reached the seventh preset time period, control the wind turbine to continue to shut down; in response to the cumulative time at the minimum pitch angle not reaching the seventh preset time period, return to execute the step of controlling the wind turbine to dynamically start the propellers.

[0027] According to a third aspect of an embodiment 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 prompted to execute the method for detecting an icing state of a wind turbine generator set as described above.

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

[0029] According to the wind turbine generator set icing detection method and device of the exemplary embodiment of the present disclosure, it is possible to timely and effectively automatically detect whether the blades are frozen, without the need to install additional hardware equipment. In addition, after the blades are frozen and shut down, it is also possible to automatically detect whether the ice on the blades has melted and whether the conditions for starting the machine have been met, thereby achieving unmanned operation and maintenance, improving operation and maintenance efficiency, and reducing power generation losses.

[0030] Additional aspects and / or advantages of the present general inventive concept will be set forth in part in the following description and in part will be apparent from the description or may be learned through practice of the present general inventive concept. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0032] Figure 1 A flow chart showing a method for detecting an icing state of a wind turbine generator set according to an exemplary embodiment of the present disclosure;

[0033] Figure 2 A flow chart showing a method for determining whether a blade is in an ice-covered state according to an exemplary embodiment of the present disclosure;

[0034] Figure 3 A flow chart showing a method for determining whether a blade is in an ice-covered state based on a spectrum amplitude of control rotation speed data in a specific frequency band according to an exemplary embodiment of the present disclosure;

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

[0036] Figure 5 A flow chart showing a method for detecting an icing state of a wind turbine generator set according to another exemplary embodiment of the present disclosure;

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

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

[0039] Reference will now be made in detail to the embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to like parts throughout. The embodiments will be described below with reference to the drawings in order to explain the present disclosure.

[0040] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0041] It should be noted that the phrase "at least one of the items" in the present disclosure includes three types of parallel situations: "any one of the items", "a combination of any number of the items", and "all of the items". For example, "including at least one of A and B" includes the following three parallel situations: (1) including A; (2) including B; (3) including A and B. Another example is "executing at least one of step 1 and step 2" which means the following three parallel situations: (1) executing step 1; (2) executing step 2; (3) executing step 1 and step 2.

[0042] Figure 1 A flow chart showing a method for detecting an icing state of a wind turbine generator system according to an exemplary embodiment of the present disclosure is shown.

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

[0044] Reference Figure 1 In step S101, measurement data and control speed data of the wind turbine generator set within a first preset time period are obtained.

[0045] The measured data includes measured rotation speed data or measured vibration data.

[0046] As an example, the measured rotation speed data is measured impeller rotation speed data.

[0047] As an example, the measured vibration data is measured impeller vibration data or cabin vibration data. For example, the impeller vibration data may include but is not limited to impeller acceleration data. The cabin vibration data may include but is not limited to cabin acceleration data.

[0048] It should be understood that the measurement data can be obtained in various suitable ways. As an example, the measurement data can be obtained from SCADA and / or the PLC or sensors of the unit itself. For example, the measured speed data can be obtained from a sensor for measuring the rotation speed. For example, the measured vibration data can be obtained from an acceleration sensor mounted on the tower or 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 measured 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 generator set within the latest first preset time period can be obtained. It should be understood that the first preset time period can be set according to engineering experience, actual conditions and specific needs. For example, the value of the first preset time period can be between 30s and 120s.

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

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

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

[0054] When identifying blade icing in the power generation state, the present disclosure takes into account that blade icing requires certain meteorological conditions, and therefore limits the ambient temperature and humidity to prevent false triggering of icing protection. For example, if the stall is caused by high temperature and low air density, it will also produce characteristics similar to icing.

[0055] In step S102, spectrum characteristics analysis is performed on the measurement data and the control speed data to obtain the frequency corresponding to the maximum spectrum amplitude of the measurement data and the spectrum amplitude of the control speed data in a specific frequency band.

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

[0057] As an example, the impeller modal frequency may include but is not limited to the impeller surface modal frequency, for example, may specifically include but is not limited to at least one of the following items: the first-order modal frequency within the impeller surface, the second-order modal frequency within the impeller surface, and the third-order modal frequency within the impeller surface.

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

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

[0060] In step S103, based on the frequency corresponding to the maximum value of the spectrum amplitude of the measurement data and the spectrum amplitude of the control speed data in a specific frequency band, it is determined whether the blades of the wind turbine generator set are in an ice-covered state.

[0061] The following will be combined Figure 2 An exemplary embodiment of step S103 is described below, which will not be expanded here.

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

[0063] According to the exemplary embodiments of the present disclosure, considering the abnormal and prominent characteristics of the modal frequency in the impeller surface after the long flexible blades are frozen, a blade icing detection method based on the modal frequency amplitude in the impeller surface is proposed, which can timely, conveniently and effectively determine whether the unit blades are in an iced state based on the spectral characteristics of the measurement data and control data. Even if the unit still reaches the rated power and rated speed in the early stage of icing, the blade icing can be detected in time and shut down for protection in time. And there is no need to install other hardware equipment.

[0064] Existing solutions generally judge whether the blades are frozen based on the operating data of the unit, and shut down for protection after judging that the blades are frozen. When people observe on-site or subjectively believe that the ice has melted, they try to start the machine again. If the machine can be started successfully, it will generate electricity. If it cannot be started successfully, people will continue to wait. At present, there are two major categories of judging whether the blades are frozen based on the operating data of the unit: the mismatch between wind speed and power and speed, and the judgment that the angle of attack exceeds the normal operating range of the unit. However, there are certain limitations in judging whether the blades are frozen by judging the matching between wind speed and power and speed. First, there is an accuracy problem with wind speed. The anemometer is installed behind the impeller. Affected by the rotation of the impeller, the air density will affect the wind energy density, and the wind measurement point cannot truly reflect the actual equivalent wind speed of the entire impeller plane. Wind energy is proportional to the cube of wind speed. Considering the accuracy of wind speed, in order to accurately judge whether the blades are frozen, this judgment method will only perform early warning protection shutdown when the icing is serious in actual application. At the same time, when the blades are frozen, the anemometer may also freeze or become stuck, causing it to be unable to display the true wind speed. When there is a large deviation between the detected wind speed and the actual wind speed, it is impossible to accurately detect blade icing. Similarly, the angle of attack detection method also detects whether the blades are frozen based on the positional relationship and design comparison between the wind speed and the pitch angle. There is also the problem that the wind speed detection cannot well represent the actual impeller equivalent wind speed or the deviation caused by the icing of the anemometer, and there are also limitations. Compared with the existing solutions, the present invention does not have the problem of measurement deviation of the anemometer itself or measurement distortion caused by icing, which makes it impossible or impossible to judge the icing of the blades in time.

[0065] In addition, as an example, the method for detecting the icing state of a wind turbine generator set according to an exemplary embodiment of the present disclosure may further include: when 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. Figure 4 To describe the exemplary embodiment of this example, it will not be expanded here.

[0066] According to the exemplary embodiments of the present disclosure, it can also be used to automatically detect whether the ice on the blades has melted after the blades are frozen and stopped, and whether the conditions for starting the machine have been met, so as to achieve the purpose of unmanned maintenance. It has the function of automatically detecting the melting state and automatically starting the machine during the waiting process of the blades being frozen and stopped, so as to achieve unmanned operation and maintenance, improve operation and maintenance efficiency, and reduce power generation losses.

[0067] Figure 2 A flow chart showing a method of determining whether a blade is in an ice-covered state according to an exemplary embodiment of the present disclosure.

[0068] Reference Figure 2 In step S201, it is determined whether the maximum frequency spectrum amplitude of the measurement data is greater than a first amplitude threshold.

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

[0070] In step S203, in response to the frequency corresponding to the maximum value of the spectrum amplitude of the measurement data being in a specific frequency band, it is determined whether the blade is in an ice-covered state based on the spectrum amplitude of the control speed data in the specific frequency band. Figure 3 An exemplary embodiment of step S203 is described below, which will not be expanded here.

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

[0072] The present disclosure takes into account that if the blades are frozen, the measured data (e.g., measured speed) will reflect a strong impeller modal frequency, but the impeller modal frequency actually exists, regardless of whether it is frozen or not. If the measured speed is not filtered when used for unit control, it will be coupled to the control speed even if it is not frozen, causing further oscillation of the system control. The reason for obtaining the actual measured speed and the control speed is to check whether the control filtering is reasonable to prevent false triggering of ice protection.

[0073] Therefore, the present disclosure proposes to first determine the maximum value of the measured speed spectrum amplitude. If it is not large, it means that the speed is very stable and there is no need to consider the possibility of abnormality in the current unit. If the maximum value of the measured speed spectrum amplitude is large and the corresponding frequency is within the range of the impeller plane frequency, it indicates that the impeller modal frequency meets the icing characteristics.

[0074] Figure 3 A flow chart showing a method of determining whether a blade is in an ice-covered state based on a spectrum amplitude of control rotation speed data in a specific frequency band according to an exemplary embodiment of the present disclosure.

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

[0076] As an example, the second amplitude threshold is smaller 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 needs. For example, when the measured data is speed measurement data, the value range of the second amplitude threshold can be 0.3 to 0.5 of the first amplitude threshold.

[0077] If the amplitude corresponding to the frequency range of the impeller plane mode of the controlled speed is still large, it means that the control has not played its due role. The prominent amplitude of the measured speed impeller modal frequency is caused by the control system filtering control excitation.

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

[0079] The pitch angle increase may be controlled in an appropriate manner. For example, the pitch angle may be increased by a preset amplitude by increasing the minimum pitch angle, and the pitch angle may be restored to the pitch angle before the increase by restoring the minimum pitch angle to the value before the increase.

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

[0081] It should be understood that the second preset time length may be set according to engineering experience, actual conditions and specific requirements. For example, the value range of the second preset time length may be 3s to 5s.

[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 requirements. For example, the value range of N can be 5-8.

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

[0084] In one embodiment, when the measurement data includes measured rotational speed data, step S303 may include: determining whether the maximum value of the rotational speed measurement data after each increase in the pitch angle is greater than a first preset threshold value compared to the rotational speed increase value of the rotational speed measurement data before the pitch angle is increased; in response to the proportion of the number of pitch angle increases for which the corresponding rotational speed increase value is greater than the first preset threshold value to N exceeds a preset proportion, determining that the blade is in an ice-covered state.

[0085] The maximum value of the rotational speed measurement data after each increase in the pitch angle is the maximum value of the rotational speed measurement data within the second preset time after the start of increasing the pitch angle, and the rotational speed measurement data before the increase in the pitch angle is the rotational speed measurement data at the moment when the pitch angle starts to increase.

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

[0087] It should be understood that the preset specific gravity may be set according to engineering experience, actual conditions and specific requirements. For example, the preset specific gravity may range from 0.7 to 0.9.

[0088] In another embodiment, when the measured data includes measured vibration data, step S303 may include: determining whether the maximum value of the vibration measurement data after each increase in the pitch angle is greater than a second preset threshold value compared to the vibration reduction value of the vibration measurement data before the pitch angle is increased; in response to the proportion of the number of pitch angle increases for which the corresponding vibration reduction value is greater than the second preset threshold value to N exceeds the preset proportion, determining that the blade is in an ice-covered state.

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

[0090] The present disclosure takes into account that when the blades of the unit are frozen, it is bound to be in an ice stall state. At this time, by increasing the pitch angle, the speed and power will increase instead (increasing the pitch angle to get rid of the stall state). The result of increasing once is not accurate enough, and N increases are required. If the pitch angle increases in most of the times, it means that the unit is truly iced and stalled, and then the unit is shut down for protection.

[0091] For current large-impeller units, if ice forms, the unit must be shut down for protection. Otherwise, the blades will be severely damaged. Even if the pitch angle is increased to temporarily escape the stall, the blade load is increasing and the ice will not melt for a period of time. The stall state cannot be escaped for long, and the blades will be severely damaged.

[0092] According to an exemplary embodiment of the present disclosure, based on the prominent characteristics of the modal frequency amplitude within the impeller surface in the measurement signal, combined with environmental factors, control speed characteristics, and blade angle increase tests, blade icing can be detected in a timely manner and protection can be performed, even if the unit is in full power state.

[0093] Figure 4 A flow chart showing a method for determining whether to control a wind turbine generator set to enter a power generation mode according to an exemplary embodiment of the present disclosure.

[0094] Reference Figure 4 In step S401, when the wind turbine generator set is in a shutdown state due to blade icing, determine whether the average ambient temperature of the wind turbine generator set within a fourth preset time period is greater than the second temperature threshold, and whether the average wind speed within a fifth preset time period is greater than the wind speed threshold.

[0095] As an example, whether the wind speed average within the fifth preset time period is greater than the wind speed threshold may be calculated by a sliding window method.

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

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

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

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

[0100] In step S402, in response to the average ambient temperature within the fourth preset time period being greater than the second temperature threshold and the average wind speed within the fifth preset time period being greater than the wind speed threshold, the wind turbine is controlled to dynamically start propellers so that the measured speed data of the wind turbine is close to the first speed threshold.

[0101] Dynamic propeller operation can be understood as controlling the rotation speed by controlling the pitch angle so that the rotation speed is as close to the first rotation speed threshold as possible and is near the first rotation speed threshold.

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

[0103] The exemplary embodiment of the present disclosure determines whether the ice may have melted based on the ambient temperature, and determines whether the current wind speed can support the unit to automatically test whether the ice has melted. Only when the ambient temperature reaches the ice melting level and the current wind speed can support the unit speed to meet the test requirements can the test be performed, otherwise continue to wait. Dynamic propeller start makes the unit speed reach a certain level before subsequent feature judgment can be performed. If the speed is low, it will not be possible to judge it later.

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

[0105] Here, the measurement data within the sixth preset time period includes: measured rotation speed data or measured vibration data within the sixth preset time period.

[0106] As an example, step S403 may include: in response to the average value of the measured speed data within the sixth preset time length being greater than the second speed threshold, determining whether the maximum value of the spectrum amplitude of the measured speed data (or measured vibration data) within the sixth preset time length in a specific frequency band is less than the third amplitude threshold; in response to the maximum value of the spectrum amplitude of the measured speed data (or measured vibration data) within the sixth preset time length in a specific frequency band being less than the third amplitude threshold, controlling the wind turbine generator set to enter a power generation mode.

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

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

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

[0110] In addition, as an example, the method for determining whether to control a wind turbine generator set to enter a power generation mode according to an exemplary embodiment of the present disclosure may further include: in response to the maximum value of the spectrum amplitude of the measured rotation speed data in a specific frequency band within a sixth preset time period being greater than or equal to a third amplitude threshold, controlling the wind turbine generator set to continue to stop and wait. That is, controlling the wind turbine generator set to stop with its blades retracted, and returning to step S401.

[0111] In addition, as an example, the method for determining whether to control a wind turbine generator set to enter a power generation mode according to an exemplary embodiment of the present disclosure may also include: in response to an average value of measured speed data within a sixth preset time period being less than or equal to a second speed threshold, determining whether the cumulative time at the minimum pitch angle has reached a seventh preset time period; in response to the cumulative time at the minimum pitch angle having reached the seventh preset time period, controlling the wind turbine generator set to continue to stop and wait; in response to the cumulative time at the minimum pitch angle not reaching the seventh preset time period, returning to continue executing the step of controlling the wind turbine generator set to dynamically start pitching.

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

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

[0114] The disclosure considers that only when the continuously acquired average speed is greater than a certain value, it is worth further judging. If the unit speed does not reach a certain level and the pitch angle has been opened to the minimum and has lasted for a certain period of time, it can only mean that the current wind speed is low or the blades are still severely frozen. You can only wait for a time unit before testing the start-up. If one of the conditions of opening the blade to the minimum and lasting for a certain period of time is not met, continue to dynamically open the blade to increase the speed. When the speed reaches a certain level during the test, the amplitude of the extracted impeller plane modal frequency is no longer large, which means that the ice has melted and it can be connected to the grid.

[0115] Currently, the two major blade icing detection methods based on operating data do not have an automated function to determine whether the ice has melted and can be restarted after the blade icing shutdown protection. They rely on on-site inspections by operation and maintenance personnel or subjective direct restart. When the ice is not completely melted, the unit will shut down again due to icing protection after running for a period of time. In this way, the operation and maintenance efficiency is low, and once the unit is connected to the grid and the speed is high, the blade icing will cause greater fatigue damage to the blade.

[0116] also, Figure 5 A flow chart showing a method for detecting an icing state of a wind turbine generator set according to another exemplary embodiment of the present disclosure; Figure 6 A flow chart showing a method for determining whether to control a wind turbine generator set to enter a power generation mode according to another exemplary embodiment of the present disclosure is shown. In these two embodiments, the measurement data includes measurement rotation 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 exemplary embodiment of the present disclosure is shown.

[0118] Reference Figure 7 According to an exemplary embodiment of the present disclosure, a device for detecting an icing state of a wind turbine generator set 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 period, 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 the frequency corresponding to the maximum spectrum amplitude of the measurement data and the spectrum amplitude of the control speed data in a specific frequency band, wherein the specific frequency band is the frequency band where the impeller modal frequency is located.

[0121] The icing identification unit 103 is configured to determine whether the blades of the wind turbine generator set are in an ice-covered state based on the frequency corresponding to the maximum value of the spectrum amplitude of the measurement data and the spectrum amplitude of the control speed data in the specific frequency band.

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

[0123] As an example, the icing identification unit 103 may be configured to: determine whether the maximum value of the spectrum amplitude of the control 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 value of the spectrum amplitude of the control 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 being increased after the pitch angle is increased for a second preset time; determine whether the blade is in an icing state based on the changes in the measured data brought about by each increase in 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 the maximum value of the rotational speed measurement data after each increase in the pitch angle is greater than a first preset threshold value compared to the rotational speed increase value of the rotational speed measurement data before the pitch angle is increased; in response to the proportion of the number of pitch angle increases whose corresponding rotational speed increase value is greater than the first preset threshold exceeding the preset proportion, determine that the blade is in an ice-covered state.

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

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

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

[0128] As an example, the icing identification unit 103 can also be configured to: when the wind turbine is in a shutdown state due to blade icing, determine whether the average ambient temperature of the wind turbine within a fourth preset time period is greater than the second temperature threshold, and whether the average wind speed within a fifth preset time period is greater than the wind speed threshold; in response to the average ambient temperature within the fourth preset time period being greater than the second temperature threshold and the average wind speed within the fifth preset time period being greater than the wind speed threshold, control the wind turbine to dynamically start propellers so that the measured speed data of the wind turbine is close to the first speed threshold; obtain the measurement data of the wind turbine within a sixth preset time period, and determine whether to control the wind turbine to enter the power generation mode based on the spectrum amplitude of the measurement data within the sixth preset time period in the specific frequency band.

[0129] As an example, the ice cover identification unit 103 can be configured to: in response to the average value of the measured speed data within the sixth preset time period being greater than the second speed threshold, determine whether the maximum value of the spectrum amplitude of the measured speed data within the sixth preset time period in the specific frequency band is less than the third amplitude threshold; in response to the maximum value of the spectrum amplitude of the measured speed data within the sixth preset time period in the specific frequency band being less than the third amplitude threshold, control the wind turbine generator set to enter a power generation mode; wherein the second speed threshold is less than the first speed threshold.

[0130] As an example, the ice recognition unit 103 may also be configured to: in response to the maximum value of the spectrum amplitude of the measured rotational speed data within the sixth preset time period in the specific frequency band being greater than or equal to the third amplitude threshold, control the wind turbine generator set to continue to shut down.

[0131] As an example, the ice recognition unit 103 can also be configured to: in response to the average value of the measured speed data within the sixth preset time period being less than or equal to the second speed threshold, determine whether the cumulative time at the minimum pitch angle has reached the seventh preset time period; in response to the cumulative time at the minimum pitch angle having reached the seventh preset time period, control the wind turbine to continue to shut down; in response to the cumulative time at the minimum pitch angle not reaching the seventh preset time period, return to execute the step of controlling the wind turbine to dynamically start the propeller.

[0132] It should be understood that the specific processing performed by the wind turbine generator set icing state detection device according to the exemplary embodiment of the present disclosure has been referred to. Figures 1 to 6 The details have been described in detail and will not be repeated here.

[0133] It should be understood that each unit in the device for detecting the icing state of a wind turbine generator set according to the exemplary embodiment of the present disclosure may be implemented as a hardware component and / or a software component. A person skilled in the art may implement each unit, for example, using a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC) according to the processing performed by each defined unit.

[0134] An exemplary embodiment of the present disclosure provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to execute the method for detecting the icing state of a wind turbine generator set as described in the above exemplary embodiment. The computer-readable storage medium is any data storage device that can store data read by a computer system. Examples of computer-readable storage media include: read-only memory, random access memory, read-only optical disk, magnetic tape, floppy disk, optical data storage device, and carrier wave (such as data transmission through the Internet via a wired or wireless transmission path).

[0135] An electronic device according to an exemplary embodiment of the present disclosure includes: a processor (not shown) and a memory (not shown), wherein the memory stores a computer program, and when the computer program is executed by the processor, it prompts the processor to execute the method for detecting the icing state of a wind turbine generator set as described in the above exemplary embodiment.

[0136] As an example, the electronic device may be a wind turbine (e.g., a central controller of a wind turbine), a wind farm controller, a terminal (e.g., a personal notebook, a desktop, etc.), or a server (e.g., an independent server, a server cluster, a cloud platform, etc.).

[0137] Although some exemplary embodiments of the present disclosure have been shown and described, it will be appreciated by those skilled in the art that modifications may be made to these embodiments without departing from the principles and spirit of the present disclosure, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for detecting the icing state of a wind turbine generator set, characterized in that: The detection method comprises: Acquire measurement data and control speed data of the wind turbine generator set within a first preset time period, wherein the measurement data includes measurement speed data or measurement vibration data, and the control speed data is speed data used for unit control; Performing spectrum characteristic analysis on the measurement data and the control speed data to obtain the frequency corresponding to the maximum spectrum amplitude of the measurement data and the spectrum amplitude of the control speed data in a specific frequency band, wherein the specific frequency band is the frequency band where the impeller modal frequency is located; Whether the blades of the wind turbine generator set are in an ice-covered state is determined 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 speed data in the specific frequency band.

2. The detection method according to claim 1, characterized in that: The step of determining whether the blades of the wind turbine generator set are in an ice-covered state based on the frequency corresponding to the maximum value of the 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 value of the frequency spectrum amplitude of the measurement data is greater than a first amplitude threshold; In response to the maximum value of the spectrum amplitude being greater than the first amplitude threshold, determining whether the frequency corresponding to the maximum value of the spectrum amplitude of the measurement data is in the specific frequency band; In response to the frequency corresponding to the maximum value of the frequency spectrum amplitude of the measurement data being in the specific frequency band, it is determined whether the blade is in an ice-covered state based on the frequency spectrum amplitude of the control rotation 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 ice-covered state based on the frequency spectrum amplitude of the control speed data in the specific frequency band comprises: Determine whether the maximum value of the frequency spectrum amplitude of the control 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 value of the frequency spectrum amplitude of the control 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 pitch angle is increased after the pitch angle is increased for a second preset time; Determining whether the blade is in an ice-covered state based on changes in the measured data caused by each increase in 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 ice-covered state based on the change of the measured data caused by each increase in the pitch angle comprises: Determine whether the maximum value of the rotational speed measurement data after each increase in the pitch angle is greater than a first preset threshold value compared to the rotational speed increase value of the rotational speed measurement data before the increase in the pitch angle; In response to the proportion of the number of pitch angle increases corresponding to the rotational speed increase value greater than the first preset threshold value to N exceeding the preset proportion, it is determined that the blade is in an ice-covered state.

5. The detection method according to claim 3, characterized in that: The step of determining whether the blade is in an ice-covered state based on the change of the measured data caused by each increase in the pitch angle comprises: 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 compared to a vibration reduction value of the vibration measurement data before the increase in the pitch angle; In response to the proportion of the number of pitch angle increases corresponding to the vibration reduction value greater than the second preset threshold to N exceeding the preset proportion, it is determined that the blade is in an ice-covered state.

6. The detection method according to claim 1, characterized in that: The detection method further comprises: In response to the blades being in an ice-covered state, the wind turbine generator set is controlled to shut down.

7. The detection method according to claim 1, characterized in that: The step of obtaining the measurement data and the control speed data of the wind turbine generator set within a first preset time period comprises: When the wind turbine generator set is in a power generation state, determining whether an average value of an ambient temperature of the wind turbine generator set within a third preset time period is less than a first temperature threshold, and whether an average value of an ambient humidity within the third preset time period is greater than a humidity threshold; In response to the average value of the ambient temperature within the third preset time period being less than the first temperature threshold and the average value of the 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 period are acquired.

8. The detection method according to claim 1, characterized in that: The detection method further comprises: In the case where the wind turbine generator set is in a shutdown state due to ice on the blades, determining 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, and whether an average value of the wind speed within a fifth preset time period is greater than a wind speed threshold; In response to the average value of the ambient temperature within the fourth preset time period being greater than the second temperature threshold and the average value of the wind speed within the fifth preset time period being greater than the wind speed threshold, controlling the wind turbine generator set to dynamically start propeller operation so that the measured rotational speed data of the wind turbine generator set approaches the first rotational speed threshold; The measurement data of the wind turbine generator set within a sixth preset time period is acquired, and based on the spectrum amplitude of the measurement data within the sixth preset time period 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 spectrum amplitude of the measurement data within the sixth preset time period in the specific frequency band comprises: In response to the average of the measured rotation speed data within the sixth preset time period being greater than the second rotation speed threshold, determining whether the maximum value of the spectrum amplitude of the measured rotation speed data within the sixth preset time period in the specific frequency band is less than a third amplitude threshold; In response to the maximum value of the spectrum amplitude of the measured rotation speed data within the sixth preset time period in the specific frequency band being less than the third amplitude threshold, controlling the wind turbine generator set to enter a power generation mode; The second speed threshold is smaller 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 value of the frequency spectrum amplitude of the measured rotation speed data within the sixth preset time period 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 shut down.

11. The detection method according to claim 9, characterized in that: The detection method further comprises: In response to the average of the measured rotation speed data within the sixth preset time period being less than or equal to the second rotation speed threshold, determining whether the accumulated time at the minimum pitch angle has reached a seventh preset time period; In response to the accumulated time at the minimum pitch angle reaching the seventh preset time, controlling the wind turbine generator set to continue to shut down; In response to the accumulated time duration at the minimum pitch angle not reaching the seventh preset time duration, the process returns to the step of controlling the wind turbine generator set to dynamically start pitching.

12. A device for detecting the icing state of a wind turbine generator set, characterized in that: The detection device comprises: A data acquisition unit is configured to acquire measurement data and control speed data of the wind turbine generator set within a first preset time period, wherein the measurement data includes measurement speed data or measurement vibration data, and the control speed data is speed data used for unit control; a frequency spectrum characteristic analysis unit configured to perform frequency spectrum characteristic analysis on the measurement data and the control 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 speed data in a specific frequency band, wherein the specific frequency band is a frequency band where an impeller modal frequency is located; The icing identification unit is configured to determine whether the blades of the wind turbine generator set are in an ice-covered state based on the frequency corresponding to the maximum value of the spectrum amplitude of the measurement data and the spectrum amplitude of the control 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 prompted to execute the method for detecting the icing state of a wind turbine generator set according to any one of claims 1 to 11.

14. An electronic device, characterized in that: The electronic device comprises: processor; A memory storing a computer program, which, when executed by a processor, prompts the processor to execute the method for detecting an icing state of a wind turbine generator set according to any one of claims 1 to 11.

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