Monitoring Method and Device for Ice Accretion State of Wind Turbine Blade and Computer Readable Storage Medium

Abstract

An embodiment of the present invention provides a method and device for monitoring the icing state of a wind turbine blade and a computer-readable storage medium. The method includes: obtaining the time-domain vibration data of the wind turbine blade within a predetermined time period; converting the time-domain vibration data of the wind turbine blade into frequency-domain vibration data; dividing the frequency-domain vibration data into multiple frequency segments; determining the frequency change trend of at least one of the multiple frequency segments within the predetermined time period; and monitoring the icing state of the wind turbine blade based on the frequency change trend and in combination with the environmental conditions of the wind turbine within the predetermined time period. Thus, the icing fault of the wind turbine blade can be well monitored.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of wind power generation, and in particular, to a method and a device for monitoring the icing state of a wind turbine blade and a computer-readable storage medium. Background Art

[0002] With the gradual depletion of energy sources such as coal and oil, humans have increasingly attached importance to the utilization of renewable energy. As a clean renewable energy source, wind energy has gained more and more attention from countries around the world. Along with the continuous development of wind power technology, the application of wind turbines in the power system has been increasing day by day. A wind turbine is a large device that converts wind energy into electrical energy and is usually installed in areas with rich wind energy resources.

[0003] The blade is an important component in the wind turbine system. When the wind turbine operates in winter or cold regions, the blade is directly exposed to the harsh environment for a long time, resulting in frequent icing failures of the wind turbine blade. Blade icing will directly affect the economy of wind power generation and also pose a threat to the safety around the wind turbine and the service life of the equipment. Therefore, a method for determining whether the blade is iced is needed to monitor blade faults. Summary of the Invention

[0004] The purpose of the embodiments of the present invention is to provide a method and a device for monitoring the icing state of a wind turbine blade and a computer-readable storage medium, which can well monitor the icing faults of the wind turbine blade.

[0005] One aspect of the embodiments of the present invention provides a method for monitoring the icing state of a wind turbine blade. The method includes: obtaining the time-domain vibration data of the wind turbine blade within a predetermined time period; converting the time-domain vibration data of the wind turbine blade into frequency-domain vibration data; dividing the frequency-domain vibration data into multiple frequency bands; determining the frequency change trend of at least one of the multiple frequency bands within the predetermined time period; and monitoring the icing state of the wind turbine blade based on the frequency change trend and in combination with the environmental conditions where the wind turbine is located within the predetermined time period.

[0006] Another aspect of the embodiments of the present invention further provides a device for monitoring the icing state of a wind turbine blade. The device includes one or more processors for implementing the method for monitoring the icing state of the wind turbine blade as described above.

[0007] Still another aspect of the embodiments of the present invention further provides a computer-readable storage medium. A program is stored on the computer-readable storage medium, and when the program is executed by a processor, the method for monitoring the icing state of the wind turbine blade as described above is implemented.

[0008] The monitoring method, device and computer-readable storage medium for the icing state of a wind turbine blade according to one or more embodiments of the present invention make full use of vibration data and physical data characteristics, analyze and fuse the information of the two, and are very suitable for diagnosing icing faults of wind turbine blades.

[0009] The monitoring method, device and computer-readable storage medium for the icing state of a wind turbine blade according to the embodiments of the present invention comprehensively consider the vibration data of the wind turbine blade and environmental factors, etc., so as to have a high accuracy rate for diagnosing icing faults of the wind turbine blade. Brief Description of the Drawings

[0010] Figure 1 It is a flowchart of the monitoring method for the icing state of a wind turbine blade according to an embodiment of the present invention;

[0011] Figure 2 It is an original high-frequency vibration data waveform diagram and a frequency spectrum diagram at a certain sampling time point in the X direction of the flap of a wind turbine blade according to an embodiment of the present invention;

[0012] Figure 3 It is a frequency spectrum diagram of each multiple frequency band after band-pass filtering of the vibration data of a wind turbine blade according to an embodiment of the present invention;

[0013] Figure 4 It is the specific steps for determining the frequency change trend of a certain frequency band within a predetermined time period according to an embodiment of the present invention;

[0014] Figure 5 It is a schematic diagram of the natural frequency search results of each multiple frequency band after band-pass filtering of the vibration data of a wind turbine blade according to an embodiment of the present invention;

[0015] Figure 6 It is a schematic diagram of the first-order frequency iterative search results of a wind turbine blade according to an embodiment of a specific case of the present invention;

[0016] Figure 7 It is a schematic diagram of the first-order frequency iterative search results of a wind turbine blade according to another specific case of the present invention;

[0017] Figure 8 It is a schematic block diagram of the monitoring device for the icing state of a wind turbine blade according to an embodiment of the present invention. Detailed Description of the Embodiments

[0018] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. On the contrary, they are only examples of the devices consistent with some aspects of the present invention as detailed in the appended claims.

[0019] The terms used in the embodiments of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. Unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present invention should have the ordinary meanings understood by those of ordinary skill in the art to which the present invention pertains. The terms "first", "second" and similar words used in the specification and claims of the present invention do not denote any order, quantity or importance, but are only used to distinguish different components. Similarly, words such as "a" or "an" do not denote a quantity limitation, but mean that there is at least one. "Plurality" or "several" means two or more. Unless otherwise indicated, words such as "front", "rear", "lower" and / or "upper" are for convenience of description only and are not limited to one position or a spatial orientation. Words such as "comprising" or "including" mean that the elements or objects appearing before "comprising" or "including" cover the elements or objects listed after "comprising" or "including" and their equivalents, and do not exclude other elements or objects. Words such as "connected" or "coupled" are not limited to physical or mechanical connections, and may include electrical connections, whether direct or indirect. The singular forms "a", "the" and "said" used in the specification and appended claims of the present invention are also intended to include the plural forms unless the context clearly dictates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0020] The embodiments of the present invention provide a method for monitoring the icing state of a wind turbine blade. Figure 1 The flowchart of the method for monitoring the icing state of a wind turbine blade according to an embodiment of the present invention is disclosed. As Figure 1 shown, the method for monitoring the icing state of a wind turbine blade according to an embodiment of the present invention may include steps S11 to S15.

[0021] In step S11, the time-domain vibration data of the wind turbine blade within a predetermined time period is acquired.

[0022] Figure 2 The first figure in Figure 2 shows the original high-frequency vibration data waveform of the wind turbine blade in the flapping X direction at a certain sampling time point according to an embodiment of the present invention. As

[0023] shown, in one embodiment, the vibration data in the X direction monitored under the flapping state of the wind turbine blade in a certain wind farm within a predetermined time period can be acquired. Of course, in other embodiments, the vibration data in the Y direction monitored under the lead-lag state of the wind turbine blade in a certain wind farm within a predetermined time period can be acquired.

[0024] Figure 2 The second figure in [Figure number] reveals the spectrogram of the original high-frequency vibration data of the wind turbine blade in the X direction of flapping at a certain sampling time point in an embodiment of the present invention. As Figure 2 shown, in one embodiment, the time-domain vibration data of the wind turbine blade can be converted into frequency-domain vibration data by fast Fourier transform (FFT).

[0025] In step S13, the frequency-domain vibration data is divided into multiple frequency bands.

[0026] In some embodiments, the frequency-domain vibration data can be divided into multiple frequency bands by using a band-pass filtering method. By filtering multiple frequency bands using the band-pass filtering method, the noise components in the signals of each frequency band can be effectively eliminated.

[0027] In some embodiments, multiple frequency bands can be determined based on the harmonic frequencies of the wind turbine blade vibration. In one embodiment, the multiple frequency bands include five frequency bands, which can respectively include an ultra-low frequency band, a low frequency band, a medium frequency band, a high frequency band, and an ultra-high frequency band. The five frequency bands can be determined based on the first to fifth harmonic frequencies of the wind turbine blade vibration respectively.

[0028] Figure 3 Reveals the spectrogram of each harmonic frequency band after band-pass filtering of the wind turbine blade vibration data in an embodiment of the present invention. As Figure 3 shown, based on the first to fifth harmonic frequencies of the wind turbine blade vibration, the frequency-domain vibration data of the wind turbine blade is correspondingly divided into five frequency bands of harmonic frequencies.

[0029] Continue to refer to Figure 1 shown, in step S14, the frequency change trend of at least one frequency band within a predetermined time period is determined.

[0030] In one embodiment, the frequency change trend within the predetermined time period is the change trend of the natural frequency of the wind turbine blade vibration within the predetermined time period.

[0031] For any one of the at least one frequency band, the natural frequency of the wind turbine blade vibration at each sampling time point within the predetermined time period can be determined first, and then, based on the natural frequency of the wind turbine blade vibration at each sampling time point, the frequency change trend of the wind turbine blade within the frequency band within the predetermined time period can be determined.

[0032] In some embodiments, determining the natural frequency of the fan blade vibration at each sampling time point within a predetermined time period may include: determining the data processing range of the current sampling time point based on the natural frequency of the fan blade vibration determined at the previous sampling time point within the predetermined time period; and determining the natural frequency of the fan blade vibration at the current sampling time point based on the data processing range of the current sampling time point.

[0033] The following will be combined with Figure 4 to introduce in detail how to determine the frequency change trend of a certain frequency band within a predetermined time period in a specific embodiment of the present invention.

[0034] As Figure 4 shown. In some embodiments, determining the frequency change trend of at least one of the multiple frequency bands within a predetermined time period in step S14 may further include steps S141 to S144.

[0035] The predetermined time period for collecting the fan blade vibration data includes multiple sampling time points.

[0036] In step S141, for any one of the at least one frequency band, determine the frequency search range at each sampling time point within the predetermined time period.

[0037] In step S142, perform a spectral amplitude search within the frequency section corresponding to each sampling time point in the frequency band with the frequency search range of each sampling time point determined in step S141.

[0038] In step S143, determine the natural frequency of the fan blade vibration at each sampling time point based on the results of the spectral amplitude search at each sampling time point in step S142.

[0039] In some embodiments, the sum of the spectral amplitudes of all frequency points within each frequency search range at each sampling time point can be calculated, and then, based on the frequency search range with the largest sum of spectral amplitudes, the natural frequency of the fan blade vibration at each sampling time point can be determined. In one embodiment, the midpoint frequency corresponding to the frequency search range with the largest sum of spectral amplitudes can be used as the natural frequency of the fan blade vibration at each sampling time point.

[0040] In some embodiments of the present invention, a frequency iterative search method can be used to determine the frequency search range at each sampling time point within a predetermined time period.

[0041] The following will introduce in detail how to use the frequency iterative search method to determine the frequency search range at each sampling time point within a predetermined time period.

[0042] (1) First, determine an initial search frequency f0 under this frequency band.

[0043] (2) For the first sampling time point within a predetermined time period, the frequency search range for the first sampling time point is determined using the initial search frequency f0. For example, a predetermined value a can be added and subtracted from the initial search frequency f0 as the frequency search range for the first sampling time point. The frequency search range is, for example, [f0 - a, f0 + a]. Spectrum amplitude search is performed at the first sampling time point according to the frequency search range [f0 - a, f0 + a].

[0044] (3) Search within the above frequency search range [f0 - a, f0 + a], and calculate the sum of the spectrum amplitudes of all frequency points within each frequency search range [f0 - a, f0 + a]. Among them, the midpoint frequency corresponding to the frequency search range with the largest sum of spectrum amplitudes is used as the natural frequency f1 of the fan blade vibration at the first sampling time point.

[0045] (4) For other sampling time points within the predetermined time period except the first sampling time point, the natural frequency f determined at the previous sampling time point is used to iteratively determine the frequency search range for the next sampling time point. For example, a predetermined value a can be added and subtracted from the natural frequency f determined at the previous sampling time point as the frequency search range for the next sampling time point. The frequency search range for the next sampling time point can be expressed as [f - a, f + a]. i For example, for the second sampling time point, the natural frequency f1 of the fan blade vibration determined at the first sampling time point is used to iteratively determine the frequency search range for the second sampling time point as [f1 - a, f1 + a]. Then, spectrum amplitude search is performed at the second sampling time point with the frequency search range [f1 - a, f1 + a], and the sum of the spectrum amplitudes of all frequency points within each frequency search range [f1 - a, f1 + a] is calculated. Then, the midpoint frequency corresponding to the frequency search range with the largest sum of spectrum amplitudes is used as the natural frequency f2 of the fan blade vibration at the second sampling time point. Then, and so on, until the last time point is searched. i For example, for the second sampling time point, the natural frequency f1 of the fan blade vibration determined at the first sampling time point is used to iteratively determine the frequency search range for the second sampling time point as [f1 - a, f1 + a]. Then, spectrum amplitude search is performed at the second sampling time point with the frequency search range [f1 - a, f1 + a], and the sum of the spectrum amplitudes of all frequency points within each frequency search range [f1 - a, f1 + a] is calculated. Then, the midpoint frequency corresponding to the frequency search range with the largest sum of spectrum amplitudes is used as the natural frequency f2 of the fan blade vibration at the second sampling time point. Then, and so on, until the last time point is searched. i - a, f i + a].

[0046] In this way, only the data within the preset search range is processed, which can reduce the burden on the computing device, and at the same time can avoid the interference of noise at other frequencies on the monitoring results to a certain extent, improving the accuracy of obtaining the natural frequency.

[0047] In this way, only the data within the preset search range is processed, which can reduce the burden on the computing device, and at the same time can avoid the interference of noise at other frequencies on the monitoring results to a certain extent, improving the accuracy of obtaining the natural frequency.

[0048] Figure 5 Reveals a schematic diagram of the natural frequency search results of each harmonic frequency band after band-pass filtering of the fan blade vibration data according to an embodiment of the present invention. As Figure 5As shown by the dashed lines and arrows in the figure, the natural frequencies determined by the method of frequency iteration search for the fan blade in the frequency band of one to five times the frequency are respectively shown.

[0049] Return reference Figure 4 , in step S144, the frequency change trend of the fan blade in this frequency band within a predetermined time period can be determined based on the natural frequency of the fan blade vibration at each sampling time point.

[0050] The natural frequency f at each sampling time point obtained in step S143 can be used i to draw a line graph to analyze the frequency change trend of the fan blade in this frequency band within the predetermined time period.

[0051] Return reference Figure 1 , in step S15, the icing state of the fan blade can be monitored based on the frequency change trend and combined with the environmental conditions of the fan within a predetermined time period.

[0052] When an icing fault occurs in the fan blade, the change in the blade mass will affect the change in the frequency value. Therefore, when it is determined that the frequency change of the fan blade exceeds a predetermined frequency threshold based on the frequency change trend in any frequency band, it is determined that the mass of the fan blade has changed. In the case where it is determined that the mass of the fan blade has changed, the environmental conditions of the fan within the predetermined time period can be further combined to determine whether an icing fault has occurred in the fan blade.

[0053] In some embodiments, the environmental conditions may include, for example, but are not limited to, temperature and air humidity.

[0054] In one embodiment, in the case where it is determined that the mass of the fan blade has changed, when the temperature is less than or equal to a predetermined temperature threshold and the air humidity is higher than a predetermined humidity threshold, it is further determined that icing has occurred on the fan blade. For example, in the case where it is determined that the mass of the fan blade has changed, when the temperature is less than or equal to 0 °C and the air humidity is higher than 30%, it can be further determined that the frequency change of the fan blade is affected by the icing phenomenon.

[0055] The method for monitoring the icing state of the fan blade according to the embodiment of the present invention processes the actual vibration signal data in the X or Y direction collected under the flapping or pitching state of the fan blade of a certain wind farm, and the natural frequency of the blade vibration at each sampling time point can be obtained by using the frequency iteration search method through the spectrogram. The change in the frequency value within a certain time period is used to determine whether the blade mass has changed, and then comprehensive consideration is given according to environmental factors such as temperature and air humidity, so that the icing fault of the fan blade can be monitored.

[0056] The following will apply two sets of original vibration data of the fan blade to verify the method for monitoring the icing state of the fan blade according to the embodiment of the present invention.

[0057] Figure 6 Schematic diagram showing the first-order frequency iterative search results of the fan blade in an embodiment of the present invention. In Figure 6 , the vibration data of a fan blade in a certain place in Inner Mongolia at 24 consecutive time points during the period from October 16th to October 17th is selected, and the natural frequency determined by the first-order frequency iterative search is as Figure 6 shown. Within the first 8 time points, the frequency shows an obvious downward trend, and the frequency decreases by more than 12 Hz, indicating that the mass of the blade has increased.

[0058] Figure 7 Schematic diagram showing the first-order frequency iterative search results of the fan blade in another embodiment of the present invention. In Figure 7 , the vibration data of a fan blade in a certain place at 24 consecutive time points during the period from October 19th to October 20th is selected, and the first-order frequency iterative search results are as Figure 7 shown. It can be seen that the frequency drops to the lowest value at the 15th time point, indicating that the mass of the blade has increased during this period. Combining with the local temperature being less than 0 °C and the humidity being greater than 30%, it is comprehensively known that the blade icing phenomenon has occurred.

[0059] Therefore, through the above Figure 6 and Figure 7 frequency search results of the two embodiments both show an obvious downward trend during a certain period, and combined with the comprehensive analysis results of relevant environmental factors, it has accuracy and credibility.

[0060] The monitoring method for the icing state of the fan blade in the embodiment of the present invention makes full use of the vibration data and physical data characteristics, analyzes and fuses the information of the two, and is very suitable for the icing fault diagnosis of the fan blade.

[0061] The monitoring method for the icing state of the fan blade in the embodiment of the present invention comprehensively considers the vibration data and environmental factors of the fan blade, so as to have a high accuracy rate for the icing fault diagnosis of the fan blade.

[0062] The embodiment of the present invention also provides a monitoring device 200 for the icing state of the fan blade. Figure 8 Schematic block diagram showing the monitoring device 200 for the icing state of the fan blade in an embodiment of the present invention. As Figure 8As shown, the monitoring device 200 for the icing state of the fan blade may include one or more processors 201 for implementing the monitoring method for the icing state of the fan blade described in any of the above embodiments. In some embodiments, the monitoring device 200 for the icing state of the fan blade may include a computer-readable storage medium 202, and the computer-readable storage medium 202 may store a program that can be called by the processor 201, which may include a non-volatile storage medium. In some embodiments, the monitoring device 200 for the icing state of the fan blade may include a memory 203 and an interface 204. In some embodiments, the monitoring device 200 for the icing state of the fan blade in the embodiments of the present invention may further include other hardware according to actual applications.

[0063] The monitoring device 200 for the icing state of the fan blade in the embodiments of the present invention has beneficial technical effects similar to those of the monitoring method for the icing state of the fan blade described above. Therefore, it will not be elaborated here.

[0064] The embodiments of the present invention also provide a computer-readable storage medium. A program is stored on the computer-readable storage medium, and when the program is executed by a processor, the monitoring method for the icing state of the fan blade described in any of the above embodiments is implemented.

[0065] The embodiments of the present invention may be in the form of a computer program product implemented on one or more storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing program codes. The computer-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be achieved by any method or technology. The information may be computer-readable instructions, data structures, program modules, or other data. Examples of computer-readable storage media include but are not limited to: new types of memories such as phase change memory / resistive random access memory / magnetic random access memory / ferroelectric random access memory (PRAM / RRAM / MRAM / FeRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information accessible by a computing device.

[0066] The monitoring method, device and computer-readable storage medium for the icing state of the fan blade provided by the embodiments of the present invention have been introduced in detail above. Specific examples are used herein to elaborate on the monitoring method, device and computer-readable storage medium for the icing state of the fan blade in the embodiments of the present invention. The description of the above embodiments is only used to help understand the core idea of the present invention, and is not intended to limit the present invention. It should be noted that for those of ordinary skill in the art in the technical field, without departing from the spirit and principle of the present invention, several improvements and modifications can still be made to the present invention, and these improvements and modifications should also fall within the protection scope of the appended claims of the present invention.

Claims

1. A monitoring method for the icing state of a fan blade, characterized in that: It includes: Obtaining the time-domain vibration data of the wind turbine blade within a predetermined time period; Converting the time-domain vibration data of the wind turbine blade into frequency-domain vibration data; Dividing the frequency-domain vibration data into multiple frequency bands; Determining the frequency change trend of at least one of the multiple frequency bands within the predetermined time period; And Monitoring the icing state of the wind turbine blade based on the frequency change trend and in combination with the environmental conditions of the wind turbine within the predetermined time period.

2. The method according to claim 1, wherein: The dividing the frequency-domain vibration data into multiple frequency bands includes: Dividing the frequency-domain vibration data into the multiple frequency bands by using a band-pass filtering method.

3. The method according to claim 2, wherein: The dividing the frequency-domain vibration data into multiple frequency bands further includes: Determining the multiple frequency bands based on the multiple frequencies of the wind turbine blade vibration.

4. The method according to claim 3, wherein: The multiple frequency bands include five frequency bands, and the five frequency bands are respectively determined based on the first to fifth multiples of the blade vibration.

5. The method according to claim 1, wherein: The frequency change trend within the predetermined time period is the change trend of the natural frequency of the wind turbine blade vibration within the predetermined time period.

6. The method according to claim 5, characterized in that: The determining the frequency change trend of at least one of the multiple frequency bands within the predetermined time period includes: For any one of the at least one frequency band, determining the natural frequency of the wind turbine blade vibration at each sampling time point within the predetermined time period; and Based on the natural frequency of the wind turbine blade vibration at each sampling time point, determining the frequency change trend of the wind turbine blade within the frequency band within the predetermined time period.

7. The method according to claim 6, characterized in that: The determining the natural frequency of the wind turbine blade vibration at each sampling time point within the predetermined time period includes: Determining the data processing range of the current sampling time point according to the natural frequency of the wind turbine blade vibration determined at the previous sampling time point within the predetermined time period; and Determining the natural frequency of the wind turbine blade vibration at the current sampling time point according to the data processing range of the current sampling time point.

8. The method according to claim 6, wherein: The determining the natural frequency of the wind turbine blade vibration at each sampling time point within the predetermined time period includes: For any one of the at least one frequency band, determining the frequency search interval at each sampling time point within the predetermined time period; Performing spectral amplitude search respectively within the frequency section corresponding to each sampling time point in the frequency band with the frequency search interval at each sampling time point; and Based on the results of the spectral amplitude search at each sampling time point, determining the natural frequency of the wind turbine blade vibration at each sampling time point.

9. The method according to claim 8, wherein: The determining the frequency search interval at each sampling time point within the predetermined time period includes: Determining the initial search frequency under the frequency band; For the first sampling time point within the predetermined time period, determining the frequency search interval of the first sampling time point with the initial search frequency; and For other sampling time points within the predetermined time period except the first sampling time point, iteratively determining the frequency search interval of the next sampling time point with the frequency determined at the previous sampling time point.

10. The method according to claim 9, characterized in that: Taking the initial search frequency as a reference, floating up and down by a predetermined value to serve as the frequency search range for the first sampling time point, and taking the frequency determined at the previous sampling time point as a reference, floating up and down by the predetermined value to serve as the frequency search range for the next sampling time point.

11. The method according to claim 8, wherein: Determining the natural frequency of the fan blade vibration at each sampling time point based on the results of the spectrum amplitude search at each sampling time point includes: Calculating, for each sampling time point, the sum of the spectrum amplitudes of all frequency points within each frequency search range; and Determining the natural frequency of the fan blade vibration at each sampling time point based on the frequency search range with the largest sum of spectrum amplitudes.

12. The method according to claim 11, wherein: Determining the natural frequency of the fan blade vibration at each sampling time point based on the frequency search range with the largest sum of spectrum amplitudes includes: Taking the midpoint frequency corresponding to the frequency search range with the largest sum of spectrum amplitudes as the natural frequency of the fan blade vibration at each sampling time point.

13. The method according to claim 1, characterized in that: Monitoring the icing state of the fan blade based on the frequency change trend and in combination with the environmental conditions of the fan within the predetermined time period includes: When it is determined based on the frequency change trend in any frequency band that the frequency change of the fan blade exceeds a predetermined frequency threshold, it is determined that the mass of the fan blade has changed.

14. The method according to claim 13, wherein: The environmental conditions include temperature and air humidity.

15. The method according to claim 14, wherein: In the case where it is determined that the mass of the fan blade has changed, when the temperature is less than or equal to a predetermined temperature threshold and the air humidity is higher than a predetermined humidity threshold, it is further determined that the fan blade has iced up.

16. A monitoring device for the icing state of a fan blade, characterized in that: Including one or more processors for implementing the method for monitoring the icing state of a fan blade as described in any one of claims 1-15.

17. A computer-readable storage medium, characterized in that, Having a program stored thereon, which when executed by the processor, implements the method for monitoring the icing state of a fan blade as described in any one of claims 1-15.

Images