A method and system for extracting modal response components of wind power support structure

Abstract

The present disclosure provides a method and system for extracting modal response components of a wind power support structure, the scheme comprising: obtaining an acceleration response signal of the wind power support structure in an operating state; decomposing the acceleration response signal using a variational modal decomposition method to obtain a number of intrinsic modal functions; analyzing the probability density function curve of the intrinsic modal function, and determining the intrinsic modal function belonging to the structural modal response component based on the number of different peaks of the probability density function curve, thereby extracting the modal response component. The scheme can extract the modal response component from the vibration response signal of the wind power support structure in an operating state, and provide data support for subsequent structural damage identification.

Description

Technical Field

[0001] The present disclosure belongs to the technical field of signal analysis and processing, and in particular relates to a method and system for extracting modal response components of a wind power support structure. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art.

[0003] Structural damage identification uses on-site non-destructive sensing technology to analyze the structural dynamic characteristics including structural vibration response to achieve the purpose of identifying structural damage and performance change processes. Since large-scale engineering structures are closely related to people's lives, once a problem occurs, it will have a significant impact on people's production and life. Therefore, how to timely and effectively discover potential damage and damage to the structure and evaluate the health of the structure has become an urgent problem to be solved. In recent years, research on vibration-based structural damage identification has developed rapidly. However, due to the influence of measurement noise, incompleteness of modal parameters, difficulty in obtaining system input information, and interference from environmental factors, the accuracy and robustness of structural damage identification need to be improved. The structural damage identification method based on response analysis only requires the output data of the system, without considering the input information of the system.

[0004] Due to the influence of harmonic excitation caused by blade rotation, the vibration response signal of the wind turbine support structure in operation contains harmonic response components with a relatively high energy proportion, resulting in poor structural damage identification based on vibration response analysis. Therefore, before structural damage identification, it is necessary to extract the structural modal response from the vibration response signal of the wind turbine support structure in operation, and then use the structural modal response to conduct structural damage identification research. The inventor found that although domestic and foreign scholars have conducted a lot of research on harmonic detection and proposed many effective methods for harmonic detection; however, the existing methods have some problems, such as loss of structural modal response, pollution of original data and modal aliasing, which seriously affect the accuracy of harmonic detection, and thus seriously affect the accuracy of structural damage identification. Summary of the invention

[0005] In order to solve the above problems, the present disclosure provides a method and system for extracting modal response components of a wind turbine support structure. The scheme can extract modal response components from the vibration response signal of the wind turbine support structure under operation state, provide data support for subsequent structural damage identification, and effectively improve the accuracy of structural damage identification.

[0006] According to a first aspect of an embodiment of the present disclosure, a method for extracting modal response components of a wind power support structure is provided, comprising:

[0007] Acquire the acceleration response signal of the wind turbine support structure under the operating state;

[0008] Decomposing the acceleration response signal by using a variational mode decomposition method to obtain a number of intrinsic mode functions;

[0009] The probability density function curve of the intrinsic modal function is analyzed, and based on the number of different peaks of the probability density function curve, the intrinsic modal function belonging to the structural modal response component is determined to achieve the extraction of the modal response component.

[0010] Furthermore, the acceleration response signal is decomposed by using a variational modal decomposition method, specifically: performing variational modal decomposition on the acquired structural acceleration response signal; obtaining a frequency spectrum of each inherent modal function based on a fast Fourier transform, and using the frequency spectrum to determine whether modal overlap or modal splitting occurs; when modal overlap or modal splitting occurs, adjusting the variational modal decomposition method parameters and re-decomposing until an inherent modal function component containing a single frequency component is obtained.

[0011] Furthermore, the probability density function curve of the intrinsic mode function is analyzed, specifically: the probability density function curve of each intrinsic mode function is drawn, and the intrinsic mode function is classified based on the number of different peaks of the probability density curve.

[0012] According to a second aspect of an embodiment of the present disclosure, a system for extracting modal response components of a wind turbine support structure is provided, comprising:

[0013] A data acquisition unit, which is used to acquire an acceleration response signal of the wind power support structure under an operating state;

[0014] An intrinsic mode function acquisition unit, which is used to decompose the acceleration response signal using a variational mode decomposition method to obtain a number of intrinsic mode functions;

[0015] The probability density function curve of the intrinsic modal function is analyzed, and based on the number of different peaks of the probability density function curve, the intrinsic modal function belonging to the structural modal response component is determined to achieve the extraction of the structural modal response component.

[0016] According to a third aspect of an embodiment of the present disclosure, a method for wind turbine support structure damage identification based on modal response components is provided, comprising:

[0017] Based on the above-mentioned method for extracting modal response components of a wind turbine support structure, a structural modal response component is obtained from the vibration response signal of the wind turbine support structure under the operating state;

[0018] Based on the obtained structural modal response components, the damage identification of wind turbine support structure is realized by using machine learning algorithm and model correction method.

[0019] According to a fourth aspect of an embodiment of the present disclosure, an electronic device is provided, comprising a memory, a processor, and a computer program stored and running on the memory, wherein when the processor executes the program, the method for extracting modal response components of a wind power support structure is implemented.

[0020] According to a fifth aspect of an embodiment of the present disclosure, a non-transitory computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method for extracting a modal response component of a wind power support structure is implemented.

[0021] Compared with the prior art, the beneficial effects of the present invention are:

[0022] The scheme disclosed in the present invention provides a novel method for extracting modal response components of a wind turbine support structure. The scheme first uses variational modal decomposition to decompose and process the structural vibration response signal to obtain a series of intrinsic modal functions IMFs, and selects the structural modal response signal using the probability density function curve shape of the IMF component signal; the scheme can effectively solve the influence of harmonic excitation caused by blade rotation on the accuracy of structural damage identification, and can effectively filter out harmonic response components with a relatively high energy proportion contained in the vibration response signal of the wind turbine support structure in an operating state, accurately extract modal response components from the vibration response signal of the wind turbine support structure in an operating state, provide data support for subsequent structural damage identification, and improve the accuracy of structural damage identification.

[0023] Advantages of additional aspects of the present disclosure will be given in part in the following description and in part will become apparent from the following description or will be learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings constituting a part of the present disclosure are used to provide a further understanding of the present disclosure. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation on the present disclosure.

[0025] FIG1( a ) is a schematic diagram of a probability density curve of an intrinsic modal function of a structural modal response component described in Embodiment 1 of the present disclosure;

[0026] FIG1( b ) is a schematic diagram of a probability density curve of an intrinsic mode function of a harmonic response component described in Embodiment 1 of the present disclosure;

[0027] Figure 2 This is a flow chart of the method for extracting modal response components of a wind power support structure described in the first embodiment of the present disclosure. DETAILED DESCRIPTION

[0028] The present disclosure is further described below in conjunction with the accompanying drawings and embodiments.

[0029] It should be noted that the following detailed descriptions are all illustrative and are intended to provide further explanation of the present disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present disclosure belongs.

[0030] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0031] In the absence of conflict, the embodiments in the present disclosure and the features in the embodiments may be combined with each other.

[0032] Embodiment 1:

[0033] The purpose of this embodiment is to provide a method for extracting modal response components of a wind turbine support structure.

[0034] like Figure 2 As shown, a method for extracting modal response components of a wind turbine support structure includes:

[0035] Acquire the acceleration response signal of the wind turbine support structure under the operating state;

[0036] Decomposing the acceleration response signal by using a variational mode decomposition method to obtain a number of intrinsic mode functions;

[0037] The probability density function curve of the intrinsic modal function is analyzed, and based on the number of different peaks of the probability density function curve, the intrinsic modal function belonging to the structural modal response component is determined to achieve the extraction of the modal response component.

[0038] Furthermore, the acceleration response signal is decomposed by using a variational modal decomposition method, specifically: performing variational modal decomposition on the acquired structural acceleration response signal; obtaining a frequency spectrum of each inherent modal function based on a fast Fourier transform, and using the frequency spectrum to determine whether modal overlap or modal splitting occurs; when modal overlap or modal splitting occurs, adjusting the variational modal decomposition method parameters and re-decomposing until an inherent modal function component containing a single frequency component is obtained.

[0039] Furthermore, the probability density function curve of the intrinsic mode function is analyzed, specifically: the probability density function curve of each intrinsic mode function is drawn, and the intrinsic mode function is classified based on the number of different peaks of the probability density curve.

[0040] Furthermore, the categories of the intrinsic modal functions include intrinsic modal functions belonging to structural modal response components and intrinsic modal functions belonging to harmonic response components.

[0041] Further, when there is only one peak in the probability density function curve of the intrinsic modal function, the intrinsic modal function belongs to the structural modal response component.

[0042] Further, when there are two different peaks in the probability density function curve of the intrinsic mode function, the intrinsic mode function belongs to the harmonic response component.

[0043] Among them, the variational modal decomposition (VMD) is an adaptive signal decomposition method proposed by Dragomiretskiy et al. in 2014. This method determines the bandwidth and frequency center of each intrinsic mode function (IMF) through cyclic iteration and decomposes the signal into multiple IMF components. VMD can effectively suppress modal aliasing because it can adaptively select the bandwidth. Compared with the empirical mode decomposition (EMD) and its improved methods, the VMD algorithm not only has a solid mathematical foundation, but also has the characteristics of fast convergence speed, high computational efficiency and strong robustness. The probability density function (PDF) method is proposed based on the different statistical characteristics of harmonic response signals and modal response signals. By observing the shape of the PDF curve, the harmonic response component and the modal response component can be distinguished more effectively.

[0044] Specifically, for ease of understanding, the solution disclosed in the present disclosure is described in detail below with reference to the accompanying drawings:

[0045] In view of the fact that the vibration response signal of the wind turbine support structure in operation contains both harmonic response components caused by blade rotation and structural modal response components induced by environmental loads, the present disclosure proposes a method for extracting structural modal response components based on variational modal decomposition and probability density function. First, the vibration response signal of the wind turbine support structure in operation is decomposed using variational modal decomposition technology to obtain a series of intrinsic modal functions (IMFs), and the structural modal response components are selected using the probability density function curve shape of the IMF components. Specifically, a method for extracting modal response components of a wind turbine support structure includes:

[0046] Step 1: Obtain the acceleration response signal x(t) of the wind turbine support structure under the operating state;

[0047] Step 2: Decompose the acceleration response x(t) using variational mode decomposition technology to obtain a series of intrinsic mode functions IMF;

[0048] Wherein, the step 2 specifically includes:

[0049] (1) Perform variational mode decomposition (VMD) on the structural acceleration response signal obtained under the operating state;

[0050] 1) In the VMD algorithm, it is assumed that the IMF component is a bandwidth-limited AM-FM signal u n (t):

[0051] u n (t) = A n (t)cos(φ n (t))

[0052] Among them, A n (t) is u n (t) is the instantaneous amplitude; w n (t) = φ′ n (t) is u n (t) is the instantaneous frequency.

[0053] 2) VMD algorithm is based on constraints Under this condition, the frequency center and bandwidth of N IMF components are obtained by iteratively searching for the optimal solution of the variational model, and the constrained variational model is constructed as follows:

[0054]

[0055]

[0056] Among them, {u n}={u 1 ,u 2 , ..., u n} and {ω n}={ω 1 ,ω 2 , ..., ω n} represents the set of modes and their center frequencies; θ t represents the partial derivative of t; δ(t) represents the impulse function; u n (t) represents the nth IMF; ω n represents the center frequency of the nth IMF; f represents the input signal.

[0057] By constructing the Lagrange function, the above equation is transformed into an unconstrained variational problem, and its formula is:

[0058]

[0059] 3) IMF component Instantaneous frequency and 1 Perform initial setting and set m=0;

[0060] 4) Iterate the loop m=m+1, so that the IMF component u n (t) and its w n (t) The following formulas are optimized respectively;

[0061]

[0062]

[0063] 5) Optimize λ;

[0064] 6) Repeat steps 4) and 5) until The iteration ends and the IMF component u is output n (t).

[0065] (2) Perform fast Fourier transform on each intrinsic mode function IMF to obtain its spectrum, and use the spectrum of each IMF to determine whether mode overlap, mode splitting, etc. occur;

[0066] (3) If mode overlap or mode splitting occurs, readjust the VMD parameters for decomposition until an IMF component containing a single frequency component is obtained.

[0067] Step 3: Calculate and draw the probability density function diagram of each intrinsic mode function IMF;

[0068] (1) When the probability density function curve has only one obvious peak, the probability density function curve will approximately obey the Gaussian distribution, indicating that the intrinsic mode function belongs to the structural modal response component, as shown in Figure 1(a);

[0069] (2) When the probability density function curve has two different peaks, it means that the intrinsic mode function belongs to the harmonic response component, as shown in Figure 1(b).

[0070] The present invention discloses a method for extracting modal response components of a wind power support structure based on variational modal decomposition and probability density function, which has rigorous theory, novel method, reasonable scheme and strong operability. The scheme first uses variational modal decomposition to decompose the structural vibration response signal to obtain a series of intrinsic modal functions IMF, and selects the structural modal response signal using the probability density function curve shape of the IMF component signal. This method can extract modal response components from the vibration response signal of the wind power support structure under the operating state, provide data support for subsequent structural damage identification, and can effectively improve the accuracy of structural damage identification.

[0071] Embodiment 2:

[0072] The purpose of this embodiment is to provide a system for extracting modal response components of a wind turbine support structure.

[0073] A wind power support structure modal response component extraction system, comprising:

[0074] A data acquisition unit, which is used to acquire an acceleration response signal of the wind power support structure under an operating state;

[0075] An intrinsic mode function acquisition unit, which is used to decompose the acceleration response signal using a variational mode decomposition method to obtain a number of intrinsic mode functions;

[0076] The probability density function curve of the intrinsic modal function is analyzed, and based on the number of different peaks of the probability density function curve, the intrinsic modal function belonging to the structural modal response component is determined to achieve the extraction of the structural modal response component.

[0077] Embodiment three:

[0078] The purpose of this embodiment is to provide a method for identifying damage to a wind turbine support structure.

[0079] A wind turbine support structure damage identification method based on modal response components, comprising:

[0080] Based on the above-mentioned method for extracting modal response components of a wind turbine support structure, a structural modal response component is obtained from the vibration response signal of the wind turbine support structure under the operating state;

[0081] Based on the obtained structural modal response components, the damage identification of wind turbine support structure is realized by using machine learning algorithm and model correction method.

[0082] Among them, the machine learning algorithm and model modification method can adopt the existing general method for structural damage identification, which can be selected by technical personnel in this field according to needs and will not be described in detail here.

[0083] In further embodiments, there is also provided:

[0084] An electronic device includes a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method described in Embodiment 1 is performed. For the sake of brevity, it will not be described in detail here.

[0085] It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general-purpose processors, digital signal processors DSP, application-specific integrated circuits ASIC, off-the-shelf programmable gate arrays FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0086] The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0087] A computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, the method described in embodiment 1 is completed.

[0088] The method in the first embodiment can be directly embodied as a hardware processor, or a combination of hardware and software modules in the processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware. To avoid repetition, it will not be described in detail here.

[0089] Those skilled in the art will appreciate that the units, i.e., algorithm steps, of the various examples described in conjunction with this embodiment can be implemented in electronic hardware or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0090] The method and system for extracting modal response components of a wind turbine support structure provided in the above embodiment can be implemented and have broad application prospects.

[0091] The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for extracting modal response components of a wind turbine support structure, characterized in that: include: Acquire the acceleration response signal of the wind turbine support structure under the operating state; Decomposing the acceleration response signal by using a variational mode decomposition method to obtain a number of intrinsic mode functions; Analyzing the probability density function curve of the intrinsic modal function, determining the intrinsic modal function belonging to the structural modal response component based on the number of different peaks of the probability density function curve, and realizing the extraction of the modal response component; The acceleration response signal is decomposed by using a variational modal decomposition method, specifically: performing variational modal decomposition on the acquired structural acceleration response signal; obtaining a frequency spectrum of each inherent modal function based on a fast Fourier transform, and using the frequency spectrum to determine whether modal overlap or modal splitting occurs; when modal overlap or modal splitting occurs, adjusting the variational modal decomposition method parameters and re-decomposing until an inherent modal function component containing a single frequency component is obtained; The acceleration response signal x(t) is decomposed by using the variational mode decomposition method to obtain several intrinsic mode functions IMF; specifically: (1) Perform variational mode decomposition (VMD) on the structural acceleration response signal obtained under the operating state; 1) In the VMD algorithm, the IMF component is a bandwidth-limited AM-FM signal u n (t): u n (t)=A n (t)cos(φ n (t)) Among them, A n (t) is u n (t) is the instantaneous amplitude; w n (t) = φ′ n (t) is u n (t) the instantaneous frequency; 2) VMD algorithm is based on constraints Under this condition, the frequency center and bandwidth of N IMF components are obtained by iteratively searching for the optimal solution of the variational model, and the constrained variational model is constructed as follows: Among them, {u m }={u1,u2,...,u n } and {ω m }={ω1,ω2,...,ω n } represents the set of modes and their center frequencies; θ t represents the partial derivative of t; δ(t) represents the impulse function; u n (t) represents the nth IMF; ω n represents the center frequency of the nth IMF; f represents the input signal; By constructing the Lagrange function, the above equation is transformed into an unconstrained variational problem, and its formula is: 3) IMF component Instantaneous frequency and 1 Perform initial setting and set m=0; 4) Iterate the loop m=m+1, so that the IMF component u n (t) and its w n (t) The following formulas are optimized respectively; 5) Optimize λ; 6) Repeat steps 4) and 5) until The iteration ends and the IMF component u is output n (t); (2) Perform fast Fourier transform on each intrinsic mode function IMF to obtain its spectrum, and use the spectrum of each IMF to determine whether mode overlap or mode splitting occurs; (3) If mode overlap or mode splitting occurs, readjust the VMD parameters for decomposition until an IMF component containing a single frequency component is obtained.

2. A method for extracting modal response components of a wind power support structure according to claim 1, characterized in that: The analyzing the probability density function curve of the intrinsic mode function specifically comprises: drawing the probability density function curve of each intrinsic mode function, and classifying the intrinsic mode function based on the different peak numbers of the probability density function curve.

3. A method for extracting modal response components of a wind power support structure according to claim 1, characterized in that: The categories of the intrinsic modal functions include intrinsic modal functions belonging to structural modal response components and intrinsic modal functions belonging to harmonic response components.

4. A method for extracting modal response components of a wind power support structure according to claim 1, characterized in that: When there is only one peak in the probability density function curve of the intrinsic modal function, the intrinsic modal function belongs to the structural modal response component.

5. A method for extracting modal response components of a wind power support structure according to claim 1, characterized in that: When there are two different peaks in the probability density function curve of the intrinsic mode function, the intrinsic mode function belongs to the harmonic response component.

6. A wind turbine support structure modal response component extraction system, based on a wind turbine support structure modal response component extraction method as claimed in any one of claims 1 to 5, characterized in that: include: A data acquisition unit, which is used to acquire an acceleration response signal of the wind power support structure under an operating state; An intrinsic mode function acquisition unit, which is used to decompose the acceleration response signal using a variational mode decomposition method to obtain a number of intrinsic mode functions; The probability density function curve of the intrinsic modal function is analyzed, and based on the number of different peaks of the probability density function curve, the intrinsic modal function belonging to the structural modal response component is determined to achieve the extraction of the structural modal response component.

7. A wind turbine support structure damage identification method based on modal response components, based on a wind turbine support structure modal response component extraction method as claimed in any one of claims 1 to 5, characterized in that: include: Obtaining structural modal response components from the vibration response signal of the wind turbine support structure under operation; Based on the obtained structural modal response components, the damage identification of wind turbine support structure is realized by using machine learning algorithm and model correction method.

8. An electronic device comprising a memory, a processor and a computer program stored and running on the memory, characterized in that: When the processor executes the program, a method for extracting modal response components of a wind power support structure as described in any one of claims 1 to 5 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, a method for extracting modal response components of a wind power support structure as described in any one of claims 1 to 5 is implemented.

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