A fan tower cylinder aerodynamic force identification method based on vibration signals

Abstract

The application discloses a fan tower cylinder aerodynamic force identification method based on a vibration signal, which comprises the following steps: screening and optimizing vibration data of collected data; expanding unknown node displacement; and identifying aerodynamic force load. The method expands and identifies the aerodynamic force of a fan structure at different heights along the tower cylinder by using limited measured vibration response data, provides key technical support for health monitoring and risk early warning of the fan structure, solves the deficiency of missing aerodynamic force monitoring sensors at present, and is helpful to guarantee long-term safe operation of the fan structure.

Description

Technical Field

[0001] This invention relates to the field of wind power structural health monitoring technology, and in particular to a method for identifying the aerodynamic forces of wind turbine towers based on vibration signals. Background Technology

[0002] Wind turbines, being tall and with low damping, are wind-sensitive structures, and damage from strong winds is common. Accurately acquiring the wind-induced aerodynamic forces on the tower structure during wind turbine operation is crucial for its design and overall health assessment. However, directly measuring the aerodynamic forces of the wind turbine tower under operating conditions is currently very difficult, thus requiring the use of other monitoring indicators for inverse calculation to identify the aerodynamic forces on the tower. This patent proposes a method for identifying the aerodynamic forces of the wind turbine tower structure based on measured vibration response signals (such as displacement and acceleration). This technology can obtain the distribution of aerodynamic forces on the wind turbine tower structure, providing a foundational algorithm for further development of corresponding aerodynamic monitoring sensors, and contributing to ensuring the long-term safe operation of wind turbine units. Summary of the Invention

[0003] In view of the aforementioned existing problems, the present invention is proposed.

[0004] Therefore, this invention provides a method for identifying the aerodynamic forces of wind turbine towers based on vibration signals, which can obtain the distribution of aerodynamic forces in the wind turbine tower structure, providing a basic algorithm for further development of corresponding aerodynamic monitoring sensors, and helping to ensure the long-term safe operation of wind turbine units.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for identifying the aerodynamic forces of a wind turbine tower based on vibration signals, comprising:

[0006] The collected vibration data is filtered and optimized; unknown node displacements are expanded; and aerodynamic loads are identified.

[0007] As a preferred embodiment of the wind turbine tower aerodynamic identification method based on vibration signals described in this invention, the screening and optimization of the vibration data includes selecting at least three vibration signal sensors (accelerometers or displacement gauges), and one of the sensors should be located as close as possible to the top of the tower.

[0008] The vibration sensor data used in the analysis should typically be displacement data. If the acquired signal is acceleration data, it should be integrated twice using the following formula and converted into displacement data:

[0009]

[0010] In the formula, U(t) represents displacement data, and α(λ) represents acceleration data.

[0011] As a preferred embodiment of the wind turbine tower aerodynamic identification method based on vibration signals described in this invention, the screening and optimization of vibration data further includes the following: Measured data typically contains a large amount of noise interference signals, and directly applying it to aerodynamic inversion will lead to distorted results. Therefore, the vibration data needs to be screened and optimized to remove interference signals and select vibration data that reflects modal information. The specific process is as follows: Identify the local maximum and local minimum points of the vibration signal, and obtain the upper envelope curve bmax and the lower envelope curve bmin by processing the envelope of the local maximum and local minimum points using spline functions, as follows:

[0012] S new =S ori -(b max +b min ) / twenty two)

[0013] In the formula S ori As the initial signal, S new This is the processed signal.

[0014] As a preferred embodiment of the wind turbine tower aerodynamic identification method based on vibration signals described in this invention, the screening and optimization of the vibration data further includes repeating the operation until (b max +b min The value of S is obtained when ) / 2 = 0. new That is, the first-order eigenfunction (IF) obtained by separation, which is the initial displacement signal U. ori Subtracting the IF obtained from the initial separation yields the residual U. r ,as follows:

[0015] U r =U ori -IF (3)

[0016] For residual U r Repeat the above operation to obtain each order of IF components. Perform Fourier transform on each separated IF component and select the IF component whose resonant frequency is the tower structure modal frequency. If multiple IF components are distributed around the structural modal frequency, select the IF component with the maximum power spectral density value to represent the vibration signal of the corresponding mode based on the power spectral density.

[0017] As a preferred embodiment of the wind turbine tower aerodynamic identification method based on vibration signals described in this invention, the screening and optimization of the vibration data further includes:

[0018] The IF values ​​for each order are selected according to the principle of selecting the wind turbine structural modal frequencies from low to high. i And combine them according to the following formula (4) to obtain the vibration signal data after eliminating signal interference:

[0019]

[0020] In the formula, u(t) represents the vibration signal data after removing noise interference, and IF i Let be the selected IF components representing the i-th modal information, and k be the required total modal order.

[0021] As a preferred embodiment of the vibration signal-based aerodynamic identification method for wind turbine towers described in this invention, the unknown node displacement expansion includes: constructing a mass condensation model based on the wind turbine structural parameters, that is, discretizing the wind turbine structure into multiple units, each unit being a concentrated mass node, ensuring that the sensor position is at the concentrated mass node, and establishing the following corresponding wind turbine dynamic equations based on the mass condensation model.

[0022]

[0023] Where F is an n×1 dimensional wind load vector, u is an n×1 dimensional displacement vector after noise removal, and M... n C n and K n These are the mass, damping, and stiffness matrices, respectively, in n×n dimensions, provided by the structural finite element design model, where n is the number of discrete elements in the wind turbine structure.

[0024] As a preferred embodiment of the wind turbine tower aerodynamic identification method based on vibration signals described in this invention, the unknown node displacement extension further includes, since the vibration of the wind turbine tower is mainly contributed by the first two modes, the node displacement can be approximately expressed as...

[0025] u i =φ i1 y1+φ i2 y2 (6)

[0026] In the formula u i Let φ be the displacement of the i-th node in the condensation model. i1 and φ i2 Let y1 and y2 be the displacements of the i-th node in the first and second modes, which can be obtained from the structural finite element design model. y1 and y2 are the generalized coordinates of the first and second modes, respectively.

[0027] Substituting the measured displacement of the highest point u1 and the displacement of the second height sensor u2 into the following equation (7), the generalized coordinates are obtained:

[0028]

[0029] Substituting the solved generalized coordinates into equation (6) yields the displacement response matrix u of nodes at different heights. 11 ;

[0030] According to formula (7), the new modal coordinates are solved again using the displacement data of the lowest position sensors u1 and u3 as displacement inputs, and then substituted into formula (6) to obtain the new displacement response matrix of each node, thus obtaining u 22 The average value of the nodal displacement data obtained from the two solutions is used to obtain u. mean As shown in Equation (8), it is used as the input for the next step of identifying aerodynamic loads.

[0031] u mean =(u 11 +u 22 ) / 2 (8)

[0032] As a preferred embodiment of the wind turbine tower aerodynamic identification method based on vibration signal described in this invention, the aerodynamic load identification includes performing a Fourier transform on the displacement signal to obtain the displacement response signal X(ω) in the frequency domain, as shown in equation (9):

[0033] X(ω)=∫u mean (t)exp(-jwt)dt (9)

[0034] In the formula, j is an imaginary number, and thus the power spectral matrix F(ω) of the aerodynamic force can be expressed as:

[0035] F(ω)=(H T H) -1 H T X(ω) (10)

[0036] In the formula, H(ω) is the frequency response function matrix of the structure, which can be obtained from the wind turbine structural design model. The aerodynamic time history is obtained by performing an inverse Fourier transform on the aerodynamic power spectrum matrix F(ω) according to the following formula (11):

[0037] F(t)=1 / 2π∫F(ω)exp(-iwt)dω (11)

[0038] A computer device includes a memory and a processor, the memory storing a computer program, characterized in that the processor executes the computer program to implement the steps of a wind turbine tower aerodynamic identification method based on vibration signals.

[0039] A computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of a method for identifying the aerodynamic forces of a wind turbine tower based on vibration signals.

[0040] The beneficial effects of this invention are as follows: The method of this invention utilizes limited measured vibration response data to expand and identify the aerodynamic forces of the wind turbine structure at different heights along the tower, providing key technical support for health monitoring and risk warning of the wind turbine structure. It solves the current deficiency of lacking aerodynamic monitoring sensors and helps to ensure the long-term safe operation of the wind turbine structure. Attached Figure Description

[0041] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a schematic flowchart of a wind turbine tower aerodynamic identification method based on vibration signals, provided as an embodiment of the present invention.

[0043] Figure 2 This is a schematic diagram of a wind turbine structural mass condensation model, which is provided as an embodiment of the present invention for a wind turbine tower aerodynamic identification method based on vibration signals. Detailed Implementation

[0044] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0045] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0046] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0047] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0048] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0049] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0050] Example 1

[0051] Reference Figure 1 This is the first embodiment of the present invention, which provides a method for identifying the aerodynamic forces of a wind turbine tower based on vibration signals, including:

[0052] S1: Filter and optimize the collected vibration data.

[0053] The screening and optimization of the vibration data includes selecting vibration data that should include at least three vibration signal sensors, accelerometers or displacement gauges, and one of the sensors should be located at the top of the tower as much as possible;

[0054] The vibration sensor data used in the analysis should typically be displacement data. If the acquired signal is acceleration data, it should be integrated twice using the following formula and converted into displacement data:

[0055]

[0056] In the formula, U(t) represents displacement data, and α(λ) represents acceleration data.

[0057] The screening and optimization of vibration data also includes the fact that measured data often contains a large amount of noise interference signals, and directly applying them to aerodynamic inversion will lead to distorted results. Therefore, vibration data needs to be screened and optimized to filter out interference signals and select vibration data that reflects modal information. The specific process is as follows: Identify the local maximum and local minimum points of the vibration signal, and obtain the upper envelope curve bmax and the lower envelope curve bmin by processing the envelope of the local maximum and local minimum points through spline functions, as follows:

[0058] S new =S ori -(b max +b min ) / twenty two)

[0059] In the formula S ori As the initial signal, S new This is the processed signal.

[0060] The screening and optimization of the vibration data also includes repeating the operation until (b) max +b min The value of S is obtained when ) / 2 = 0. new That is, the first-order eigenfunction (IF) obtained by separation, which is the initial displacement signal U. ori Subtracting the IF obtained from the initial separation yields the residual U. r ,as follows:

[0061] U r =U ori -IF (3)

[0062] For residual U r Repeat the above operation to obtain each order of IF components. Perform Fourier transform on each separated IF component and select the IF component whose resonant frequency is the tower structure modal frequency. If multiple IF components are distributed around the structural modal frequency, select the IF component with the maximum power spectral density value to represent the vibration signal of the corresponding mode based on the power spectral density.

[0063] The screening and optimization of the vibration data also includes selecting the corresponding IF values ​​for each order according to the principle of ascending the modal frequencies of the wind turbine structure. i And combine them according to the following formula (4) to obtain the vibration signal data after eliminating signal interference:

[0064]

[0065] In the formula, u(t) represents the vibration signal data after removing noise interference, and IF i Let be the selected IF components representing the i-th modal information, and k be the required total modal order.

[0066] S2: Unknown node displacement extension.

[0067] The expansion of the unknown node displacement includes constructing a mass condensation model based on the wind turbine structural parameters. This involves discretizing the wind turbine structure into multiple elements, each element being a lumped mass node, ensuring the sensor position is at the lumped mass node, and establishing the corresponding wind turbine dynamics equations based on the mass condensation model.

[0068]

[0069] Where F is an n×1 dimensional wind load vector, u is an n×1 dimensional displacement vector after noise removal, and M... n C n and K n These are the mass, damping, and stiffness matrices, respectively, in n×n dimensions, provided by the structural finite element design model, where n is the number of discrete elements in the wind turbine structure.

[0070] The extension of the unknown nodal displacement also includes the fact that, since the vibration of the wind turbine tower is mainly contributed by the first two modes, the nodal displacement can be approximately expressed as...

[0071] u i =φ i1 y1+φ i2 y2 (6)

[0072] In the formula u i Let φ be the displacement of the i-th node in the condensation model. i1 and φ i2 Let y1 and y2 be the displacements of the i-th node in the first and second modes, which can be obtained from the structural finite element design model. y1 and y2 are the generalized coordinates of the first and second modes, respectively.

[0073] Substituting the measured displacement of the highest point u1 and the displacement of the second height sensor u2 into the following equation (7), the generalized coordinates are obtained:

[0074]

[0075] Substituting the solved generalized coordinates into equation (6) yields the displacement response matrix u of nodes at different heights. 11 ;

[0076] According to formula (7), the new modal coordinates are solved again using the displacement data of the lowest position sensors u1 and u3 as displacement inputs, and then substituted into formula (6) to obtain the new displacement response matrix of each node, thus obtaining u 22 The average value of the nodal displacement data obtained from the two solutions is used to obtain u. mean As shown in Equation (8), it is used as the input for the next step of identifying aerodynamic loads.

[0077] umean =(u 11 +u 22 ) / 2 (8)

[0078] S3: Identify aerodynamic loads.

[0079] The identification of aerodynamic loads includes performing a Fourier transform on the displacement signal to obtain the displacement response signal X(ω) in the frequency domain, as shown in equation (9):

[0080] X(ω)=∫u mean (t)exp(-jwt)dt (9)

[0081] In the formula, j is an imaginary number, and thus the power spectral matrix F(ω) of the aerodynamic force can be expressed as:

[0082] F(ω)=(H T H) -1 H T X(ω) (10)

[0083] In the formula, H(ω) is the frequency response function matrix of the structure, which can be obtained from the wind turbine structural design model. The aerodynamic time history is obtained by performing an inverse Fourier transform on the aerodynamic power spectrum matrix F(ω) according to the following formula (11):

[0084] F(t)=1 / 2π∫F(ω)exp(-iwt)dω (11)

[0085] Example 2

[0086] Reference Figure 2 As an embodiment of the present invention, a method for identifying the aerodynamic forces of a wind turbine tower based on vibration signals is provided. To verify the beneficial effects of the present invention, scientific demonstration is carried out through experiments.

[0087] The building in this embodiment is a 7.5MW wind turbine located in a coastal area. The rotor diameter is 204m and the hub height is about 120m. The terrain where the building is located is Class A terrain according to the load code (GB50009-2012). Three acceleration sensors are arranged along the top of the tower, the middle of the tower and the base of the tower.

[0088] Step 1): For the acceleration signals collected at the top of the tower, the middle of the tower, and the base of the tower, the displacement response data U1, U2, and U3 are calculated according to formula (1). These are then substituted into formulas (2)-(3) to remove noise interference and filter out the IF1 to IF5 data corresponding to the first five modal frequencies (i.e., k=5). These are then substituted into formula (4) to obtain the displacement signal after removing noise interference.

[0089] Step 2): Construct a mass condensation model. Based on the structural design finite element model, derive the M, C, and K matrices. Divide the wind turbine model into 10 lumped mass elements, with mass nodes near the tower top, middle of the tower, and tower base designated as nodes 1, 5, and 10, respectively. The corresponding measured displacement data after noise cancellation are represented as u1, u5, u... 10 .

[0090] Step 3): First, using u1 and u5 as inputs, solve for the first two generalized coordinates y1 and y2 according to equation (7), and then solve for the displacement response matrix u of each node according to equation (6). 11 .

[0091] Step 4): Using u1, u 10 Repeat step 3) to obtain the new displacement response matrix u of each node. 22 Substituting the two displacement results into formula (8), we obtain the nodal displacement response matrix u used to calculate the aerodynamic forces. mean .

[0092] Step 5): Put u mean Substitute into equation (9) and perform Fourier transform to obtain the displacement response matrix X(ω) of each node in the frequency domain of the tower. Construct the frequency response function matrix H(ω) according to the structural design model, and substitute both into equations (10) and (11) to obtain the aerodynamic load time history of each node of the tower.

[0093] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

[0094] Example 3

[0095] The third embodiment of the present invention differs from the first two embodiments in that:

[0096] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0097] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0098] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0099] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0100] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0101] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for identifying the aerodynamic forces of a wind turbine tower based on vibration signals, characterized in that: include, The collected vibration data is filtered and optimized; Perform displacement expansion of unknown nodes; Identify aerodynamic loads; The expansion of the unknown node displacement includes constructing a mass condensation model based on the wind turbine structural parameters. This involves discretizing the wind turbine structure into multiple elements, each element being a lumped mass node, ensuring the sensor position is at the lumped mass node, and establishing the corresponding wind turbine dynamic equations based on the mass condensation model. in, for The wind load vector of dimension u is The displacement vector after removing noise interference in the dimension. , and They are respectively The mass, damping, and stiffness matrices of the dimensional structure are provided by the finite element design model of the structure, where n is the number of discrete elements in the wind turbine structure. The extension of the unknown nodal displacement also includes the fact that, since the vibration of the wind turbine tower is mainly contributed by the first two modes, the nodal displacement can be approximately expressed as: In the formula Let be the displacement of the i-th node in the condensation model. and The displacement of the i-th node in the first and second modes can be obtained from the structural finite element design model. , These are the generalized coordinates of the first and second order modes, respectively; Measured nodal vibration response Displacement at highest point and Substituting the displacement data from the second altitude sensor into the following equation (7), the generalized coordinates are obtained: Substituting the solved generalized coordinates into equation (6) yields the displacement response matrix u of nodes at different heights. 11 ; According to formula (7), again... and The displacement data of the lowest position sensor is used as the displacement input to resolve the new modal coordinates, and then substituted into formula (6) to obtain the new displacement response matrix of each node, thus obtaining u. 22 The average value of the nodal displacement data obtained from the two solutions is used to obtain u. mean As shown in Equation (8), it is used as the input for the next step of identifying aerodynamic loads: The identification of aerodynamic loads includes performing a Fourier transform on the displacement signal to obtain the displacement response signal in the frequency domain. As in equation (9): In the formula, j is an imaginary number, and thus the power spectrum matrix of the aerodynamic force is obtained. It can be represented as: In the formula The frequency response function matrix of the structure can be obtained from the wind turbine structural design model, and the aerodynamic power spectrum matrix is ​​calculated using the following equation (11). The aerodynamic time history is obtained by performing an inverse Fourier transform: 。 2. The method for identifying the aerodynamic forces of a wind turbine tower based on vibration signals as described in claim 1, characterized in that: The screening and optimization of the vibration data includes the following: the selection of vibration data should include at least three vibration signal sensors for collecting acceleration data or displacement data, and one of the sensors should be located at the top of the tower as much as possible. The vibration sensor data used in the analysis should typically be displacement data. If the acquired signal is acceleration data, it should be integrated twice using the following formula and converted into displacement data: In the formula For displacement data, This is acceleration data.

3. The method for identifying the aerodynamic forces of a wind turbine tower based on vibration signals as described in claim 2, characterized in that: The screening and optimization of vibration data also includes the fact that measured data often contains a large amount of noise interference signals, and directly applying them to aerodynamic inversion will lead to distorted results. Therefore, vibration data needs to be screened and optimized to filter out interference signals and select vibration data that reflects modal information. The specific process is as follows: Identify the local maximum and local minimum points of the vibration signal, and obtain the upper envelope curve by processing the envelope of the local maximum and local minimum points through spline functions. and lower envelope ,as follows: In the formula As the initial signal, This is the processed signal.

4. The method for identifying the aerodynamic forces of a wind turbine tower based on vibration signals as described in claim 3, characterized in that: The screening and optimization of the vibration data also includes, Repeat the operation until Up to this point, what we have obtained That is, the first-order eigenfunction (IF) obtained by separation, which is the initial displacement signal. Subtracting the IF obtained from the initial separation yields the residual. ,as follows: For residuals Repeat the above operation to obtain each order of IF components. Perform Fourier transform on each separated IF component and select the IF component whose resonant frequency is the tower structure modal frequency. If multiple IF components are distributed around the structural modal frequency, select the IF component with the maximum power spectral density value to represent the vibration signal of the corresponding mode based on the power spectral density.

5. The method for identifying the aerodynamic forces of a wind turbine tower based on vibration signals as described in claim 4, characterized in that: The screening and optimization of the vibration data also includes, The IF values ​​for each order are selected according to the principle of selecting the wind turbine structural modal frequencies from low to high. i And combine them according to the following formula (4) to obtain the vibration signal data after eliminating signal interference: In the formula To remove noise interference from vibration signal data, To select the characteristics of the i-th modal information The component, k, is the total number of modal orders required.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

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