Hybrid wind turbine tower modal testing method and system

Abstract

The application discloses a hybrid wind turbine tower modal test method and system, comprising the following steps: S1, obtaining target tower design parameters; S2, forming an overall and local test point array; S3, applying excitation in a manner of combining environmental excitation and artificial excitation and collecting response signals; S4, synchronously collecting acceleration, excitation force and environmental parameters through a multi-channel collector; S5, after data preprocessing, respectively adopting a random subspace method and a frequency response function modal analysis method to extract modal parameters, and obtaining final modal parameters through fusion correction; and S6, result verification and application, comparing the test results with a finite element model, correcting the model and outputting structure evaluation and optimization suggestions. The local modal of a cross rod, an inclined rod and a connecting node is captured, a weak link of the structure is effectively identified, the loading mode of environmental excitation+artificial excitation cooperation is adopted, and a modal confidence criterion is introduced for verification, so that the modal frequency test error is reduced.

Description

Technical Field

[0001] This invention belongs to the field of wind power equipment technology, specifically relating to a method and system for modal testing of hybrid wind turbine towers. Background Technology

[0002] As wind power development expands to ultra-high altitudes (above 180 meters) and complex terrain areas, quadrilateral truss towers are gradually replacing traditional steel towers and hybrid towers as the preferred tower type for ultra-high-altitude wind turbines due to their advantages of lightweight design, low wind resistance, and high structural redundancy. Modal parameters, including natural frequencies, mode shapes, and damping ratios, are the core basis for evaluating the wind resistance stability of truss towers, avoiding resonance risks, and predicting structural fatigue life.

[0003] However, quadrilateral truss towers have structural characteristics such as open grid structure, multiple members cooperating in stress, and local nodes being prone to weakness. Traditional modal testing methods have the following shortcomings: 1. The layout of measuring points is unreasonable. Existing methods are mostly aimed at the overall modal design of traditional steel towers and hybrid towers. They only arrange measuring points in the tower body and ignore the local vibration of crossbars, diagonal bars and connection nodes, which cannot identify local modal coupling problems caused by insufficient connection stiffness.

[0004] 2. Poor adaptability of excitation methods: It is difficult to implement large-scale vibration installation on ultra-high truss towers. Relying solely on natural wind environmental excitation is susceptible to turbulence interference, resulting in low signal-to-noise ratio and insufficient accuracy in low-order mode extraction.

[0005] 3. The data processing methods are limited. Most existing testing methods only use a single algorithm such as the random subspace method or the frequency response function method, without considering the influence of environmental parameters such as temperature and wind speed on the modality, and without verification through multi-source data, resulting in low reliability of the results.

[0006] Therefore, how to achieve accurate and efficient acquisition of overall and local modal parameters to provide reliable technical support for the safe operation and maintenance of truss towers is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0007] The technical problem to be solved by this invention is to provide a hybrid wind turbine tower modal testing method and system to address the shortcomings of the prior art. By capturing the local modal characteristics of crossbars, diagonal bars, and connecting nodes, the method effectively identifies structural weak points, adopts a loading method that combines environmental and artificial excitation, and introduces modal confidence criteria for verification, thereby reducing modal frequency testing errors and solving the technical problems of existing modal testing methods in terms of adaptability, local modal capture, data reliability, and system integration.

[0008] This invention adopts the following technical solution: a modal testing method for hybrid wind turbine towers, comprising the following steps: S1: Obtain the design parameters of the target tower, calculate the theoretical modal parameters through finite element simulation, and determine the test coverage area as the top surface of the tower foundation to the flange surface of the tower top nacelle; S2: Three-dimensional acceleration sensors are arranged in layers in the truss section, transition section and steel tower section, and sensors are densely arranged at the midpoints of the horizontal and diagonal bars of the truss section to form an overall and local measurement point array; S3: Apply incentives using a combination of environmental and artificial incentives and collect response signals; S4: Acceleration, excitation force and environmental parameters are collected synchronously through a multi-channel data acquisition device.

[0009] S5: After data preprocessing, modal parameters are extracted using the random subspace method and the frequency response function modal analysis method, respectively, and the final modal parameters are obtained through fusion correction; S6: Result verification and application. The test results are compared with the finite element model, the model is corrected, and structural evaluation and optimization suggestions are output.

[0010] Preferably, in step S2, A test section is set every 20m along the tower height of the truss section, and a triaxial acceleration sensor is arranged on each of the four columns of each section. The transition section is equipped with a first section, and a triaxial acceleration sensor is arranged in each of the four directions of the first section; a second section is set at the bottom, middle and top of the steel tower section, and two triaxial acceleration sensors are arranged in each second section. 2 additional crossbars and diagonal braces are densely arranged at the midpoints of each layer of the truss section. Four triaxial accelerometers.

[0011] Preferably, the environmental stimulus in step S3 is: collecting response signals under shutdown conditions with wind speed <2m / s and wind speed ≤5m / s for 30 minutes, and simultaneously recording wind speed, temperature and humidity.

[0012] Preferably, the artificial excitation in step S3 is: applying pulse excitation with a force hammer along the X, Y and torsional directions at the intermediate section of the truss section, the transition section section, and the intermediate section of the steel tower section.

[0013] Preferably, the striking force of the hammer is 1. The hammer is 5kN, and it strikes the object 5 times each in the X, Y, and torsional directions, and the average value is taken.

[0014] Preferably, the preprocessing in step S5 includes detrending, low-pass filtering with a cutoff frequency of 20Hz, and whitening.

[0015] Preferably, in step S5, the random subspace method uses 0.1 5Hz frequency range, 0 Stability plots within a 5% damping ratio range are used to screen effective modes; frequency response function modal analysis is performed using peak picking to determine the frequency and half-power bandwidth to calculate the damping ratio; when the natural frequency deviation between the two methods is >3%, it is corrected using the modal confidence criterion (MAC).

[0016] Another technical solution of the present invention is a hybrid wind turbine tower modal testing system, comprising a sensing module, a data acquisition module, a data processing module, and a result output module connected in sequence; The sensing module includes a triaxial accelerometer, a force hammer, and an environmental parameter acquisition instrument; The data acquisition module includes a multi-channel data acquisition instrument; The data processing module includes a data preprocessing unit, a modal parameter extraction unit, and a fusion correction unit, integrating the random subspace method and the frequency response function modal analysis method. The result output module includes a model verification unit, a report generation unit, and an early warning push unit, and can be connected to the wind farm SCADA system.

[0017] Preferably, the triaxial accelerometer has a range of ±5g and a frequency response of 0.1. 50Hz, resolution 0.001g, installation stiffness ≥10 6 N / m; hammer range is 0 5kN, with a frequency response of 0.1 kN with a force sensor. 10kHz.

[0018] Preferably, the GPS synchronization accuracy of the data acquisition module is ≤1ms and the sampling rate is 200Hz; the data processing module is developed based on LabVIEW and MATLAB, and the processing time for a single set of data is <5min.

[0019] Compared with the prior art, the present invention has at least the following beneficial effects: For quadrilateral trusses The structural characteristics of steel-cylinder hybrid wind turbine towers were determined through finite element pre-analysis to define the test range. A complete process was adopted, which combined overall and local layered measurement point layout, environmental excitation and artificial excitation, and dual algorithm fusion correction. This process can accurately obtain overall and local modal parameters, solving the problems of incomplete measurement point coverage, poor excitation adaptation and single data processing in traditional methods, and providing reliable support for tower safety assessment and maintenance.

[0020] Furthermore, the truss section, transition section, and steel tower section are divided into sections with standardized sensor layout, and sensors are densified at the midpoints of the horizontal and diagonal members of the truss section to form a complete overall + local measuring point array. This can effectively capture the local vibration of the horizontal members, diagonal members, and connecting nodes, identify local modal coupling problems, and accurately locate the weak points of the structure.

[0021] Furthermore, by selecting key sections and applying artificial pulse excitation in multiple directions, the shortcomings of insufficient accuracy of pure environmental excitation are compensated for, thereby achieving precise excitation of different structural sections of the tower and improving the accuracy of low-order mode extraction.

[0022] Furthermore, by taking the average value of multiple taps, the testing error can be further reduced, and the accuracy of the artificially stimulated data can be improved.

[0023] Furthermore, preprocessing methods such as detrending, low-pass filtering, and whitening are used to eliminate interference factors such as temperature drift and noise, thereby improving the quality of the original data and laying the foundation for accurate extraction of modal parameters in the future.

[0024] Furthermore, an integrated system encompassing sensing, data acquisition, processing, and output is constructed, with each module working collaboratively. This system supports simultaneous acquisition of multi-source data and dual-algorithm processing, and can interface with wind farm SCADA systems to enable testing. Evaluate Early warning closed-loop management improves testing efficiency and the application value of results.

[0025] In summary, the hybrid wind turbine tower modal testing method and system of this invention, through the design of an overall + local layered and densified measuring point layout, can achieve local modal capture of cross members, diagonal members, and connection nodes, effectively identifying structural weak points, taking into account the structural characteristics of quadrilateral truss towers. It employs a collaborative loading method combining environmental excitation and artificial excitation, combined with multi-algorithm fusion processing of SSI and EMA, and introduces modal confidence criteria for verification, reducing modal frequency testing errors. The method constructs an integrated testing system for sensing, acquisition, processing, and output, supporting simultaneous acquisition of multi-source data and cloud backup, shortening the testing cycle. The test results can be directly used to correct finite element models, identify resonance risks, output structural optimization suggestions, and can be integrated with wind farm SCADA systems to achieve closed-loop management of testing, evaluation, and early warning.

[0026] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the following description of the relative 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.

[0028] Figure 1 This is a flowchart of the modal testing method of the present invention.

[0029] Figure 2 This is a schematic diagram of the layout of measuring points for a quadrilateral truss tower.

[0030] Figure 3 This is a structural block diagram of the modal testing system of the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "one side," "one end," and "one side," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing the invention and 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, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0033] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0034] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0035] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0036] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0037] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0038] This invention provides a method for modal testing of hybrid wind turbine towers, which can accurately and efficiently obtain data on quadrilateral trusses. The overall and local modal parameters of the steel cylinder hybrid wind turbine tower effectively solve the problems of poor adaptability, missing local modes, unreliable data, and low system integration of traditional methods, providing reliable technical support for the safe operation, structural optimization, and operation and maintenance early warning of ultra-high-altitude truss towers.

[0039] Please see Figure 1 As shown, the present invention provides a hybrid wind turbine tower modal testing method applicable to ultra-high-altitude wind turbine towers of 180m and above. Addressing the structural characteristics of the truss section with its hollowed-out grid structure, multi-member collaborative stress distribution, and sensitive connection node stiffness, this method achieves simultaneous and accurate testing of overall and local modal characteristics. Specifically, it includes the following steps: S1: Structural property pre-analysis First, obtain the target quadrilateral truss. The complete set of design parameters for the steel cylinder hybrid tower includes the total tower height, truss segment height, steel cylinder segment height, transition section location, member cross-sectional dimensions, material grade, elastic modulus, density, Poisson's ratio, node connection type, and foundation constraint conditions.

[0040] A simulation model of the entire tower was established using finite element analysis software. Boundary conditions consistent with actual working conditions were applied, and the theoretical natural frequencies, theoretical mode shapes, and theoretical damping ratios of the first five orders of the tower were calculated to clarify the modal distribution range.

[0041] Based on this, the complete coverage area of ​​this modal test was determined: starting from the top surface of the tower foundation and extending to the mounting flange surface of the tower top nacelle. Key monitoring sections included the truss section at 1 / 4 tower height, 1 / 2 tower height, 3 / 4 tower height, the transition section between the truss and the steel cylinder, and the middle and top of the steel cylinder section, providing accurate basis for subsequent measurement point layout.

[0042] S2: Measurement point layout like Figure 2 As shown, sensors are arranged according to the principle of overall monitoring + local densification to form a three-dimensional measuring point array covering the entire height of the tower, key members, and connection nodes: In the truss section, a standard test section is divided every 20m along the tower height. Each section corresponds to the four main columns of the quadrilateral truss. A triaxial acceleration sensor is installed on each column to collect the vertical, lateral and torsional vibration responses of the column.

[0043] Transition section: A separate test section, designated as the first section, is set up at the connection between the truss section and the steel cylinder section. A triaxial acceleration sensor is arranged at each of the four positions of the first section to capture the vibration characteristics at the location of the sudden change in stiffness in the transition section.

[0044] Steel tower section: One test section is set at the bottom, middle and top of the steel cylinder section, respectively, and is referred to as the second section. Two triaxial acceleration sensors are installed at each second section to ensure the integrity of the overall vibration data of the steel cylinder section. Local reinforcement: Two to four additional triaxial acceleration sensors are placed at the midpoint of the horizontal and diagonal members of each layer of the truss section. These sensors are specifically designed to identify easily overlooked weak features such as local modes of the members, loose nodes, and insufficient connection stiffness. This avoids the problem of traditional testing focusing only on the overall structure and missing local hidden dangers.

[0045] The final layout is as follows Figure 2 As shown, multiple modal information such as overall tower bending, overall torsion, and local member bending can be obtained simultaneously.

[0046] S3: Excitation Loading To balance testing convenience and signal quality, a dual-source co-excitation mode combining environmental and manual excitation is adopted to avoid the problems of low signal-to-noise ratio and mode omission caused by single excitation. The specific steps are as follows: S31 environmental excitation: With the wind turbine in a shutdown state, response signals were collected under two typical operating conditions for data acquisition. First operating condition: wind speed < 2m / s, near-windless environment; The second operating condition: wind speed ≤ 5m / s, low wind speed and light wind environment.

[0047] Under the above operating conditions, the natural vibration response signal of the tower was continuously collected. The collection time for each group lasted for 30 minutes. During the collection process, the real-time wind speed, ambient temperature and air humidity were recorded simultaneously for subsequent data correction and result comparison, so as to reduce the interference of environmental factors on modal parameters.

[0048] S32 artificial excitation, using a pulse force hammer to implement fixed-point directional excitation: Specifically, the middle section of the truss section, the transition section section, and the middle section of the steel tower section are selected as excitation points. Pulse excitation is applied by a force hammer with a force sensor along the X-direction, Y-direction, and torsional direction of the tower, respectively. The excitation force is controlled within the range of 1–5 kN to avoid structural damage caused by insufficient signal-to-noise ratio due to insufficient excitation or excessive excitation.

[0049] Five consecutive taps were performed in each direction, with a 5-minute interval between each tap, to ensure that the structure could decay freely and eliminate the residual response of the previous excitation. The average value of the results from multiple taps was then taken as the effective excitation data.

[0050] S4: Data Acquisition A high-performance 64-channel data acquisition instrument is used as the core of the acquisition. The instrument is equipped with a GPS synchronization module, and the synchronization accuracy of the GPS synchronization module is better than 0.5ms, ensuring that the time reference of all measurement points is strictly consistent. The sampling frequency is set to 200Hz.

[0051] All triaxial accelerometers are connected to the data acquisition unit via shielded cables. The cables are neatly fixed along the tower and kept at a distance of more than 1.5m from the tower's power cable to avoid electromagnetic interference.

[0052] The data acquisition system simultaneously collects three types of data: acceleration response signals, hammer excitation signals, and environmental parameter signals, filtering outliers in real time. Specifically, the acquisition process involves real-time online monitoring and automatic removal of abnormal data such as over-range readings, disconnections, and sudden changes.

[0053] The collected raw data is saved to a local high-speed hard drive in TDMS / CSV format, and simultaneously transmitted to a cloud server via a 5G network for backup, ensuring data security and traceability.

[0054] S5: Data Processing S51 Data Preprocessing The collected data was standardized and preprocessed using the MATLAB platform, specifically including the following steps: Detrending processing: Eliminates signal baseline drift caused by sensor temperature drift and zero drift; Low-pass filter: Set the cutoff frequency to 20Hz to filter out high-frequency noise and high-frequency stray vibrations from the structure; Whitening: Reduces the correlation of noise signals and improves the stability and accuracy of subsequent modality recognition.

[0055] S52 Modal Parameter Extraction A dual-algorithm parallel extraction process is employed to ensure reliable results: The environmental excitation data is processed using the Stochastic Subspace Identification (SSI) method to construct a Hankel matrix. Singular value decomposition is used to separate system modes from noise. Combined with the stability plot, stable and reliable effective modes are automatically selected, and the natural frequencies, mode shapes, and damping ratios are output. The stability plot is set to a frequency range of 0.1–5 Hz and a damping ratio range of 0–5%.

[0056] Experimental Modal Analysis (EMA) is used to process artificial excitation data, calculate the frequency response function curve between input force and output response, locate modal frequencies using peak picking method, and accurately calculate damping ratio using half-power bandwidth method to obtain modal parameter results under artificial excitation.

[0057] S53 Fusion Correction Compare the SSI results with the EMA results item by item: If the deviation of the same natural frequency is greater than 3%, the Modal Assurance Criterion (MAC) is activated to verify the mode shape correlation and correct the parameters, eliminate false modes, retain the true physical modes, and finally determine the accurate natural frequency, mode shape and damping ratio of the tower.

[0058] S6: Results Validation and Engineering Applications The measured modal parameters are compared with the theoretical values ​​from finite element simulations to correct the model and output structural evaluation and optimization suggestions. Specifically: If the overall error is greater than 5%, return to the modified finite element model and focus on adjusting key parameters such as member connection stiffness, boundary constraints, and material elastic modulus to make the model consistent with the actual structure.

[0059] Based on the measured vibration modes, local weak points such as diagonal members, nodes, and transition sections can be intuitively identified. Based on this, resonance risk assessment reports, resonance avoidance schemes, and structural optimization suggestions can be generated, providing direct data support for tower structure reinforcement, operation control strategy adjustment, and full life cycle fatigue life prediction.

[0060] like Figure 3 As shown, the present invention provides a hybrid wind turbine tower modal testing system, which consists of four parts: a sensing module, a data acquisition module, a data processing module, and a result output module. The modules are interconnected and work together to realize full automation from signal acquisition to early warning output.

[0061] Specifically, the sensing module provides signal input to the entire system, including the following types: Triaxial accelerometers: 60 in total, measuring range ±5g, operating frequency response 0.1–50Hz, resolution 0.001g, installation stiffness not less than 10. 6 N / m, ensuring a rigid connection with the tower and preventing loss of high-frequency and weak vibration signals.

[0062] Excitation force hammers: a total of 2, with a range of 0–5kN. The hammer head has a built-in high-precision force sensor with a working frequency response of 0.1–10kHz, which meets the requirements of pulse excitation.

[0063] Environmental parameter acquisition system: 1 set, integrating an anemometer, temperature sensor, and humidity sensor. The anemometer has a measurement range of 0–60 m / s, the temperature sensor has a range of -20 to 45℃, and the humidity sensor has a range of 0 to 100%RH, enabling synchronous acquisition of environmental data.

[0064] The data acquisition module is responsible for multi-channel synchronous acquisition, storage, and transmission, specifically including: 64-channel data acquisition instrument: 1 unit, sampling rate of 200Hz, input impedance of 10GΩ, to ensure that weak signal acquisition is not distorted.

[0065] GPS synchronization unit: 1 unit, synchronization accuracy ≤1ms, supports time unification for multiple channels and multiple devices.

[0066] Industrial computer and storage: The data acquisition unit connects to an industrial computer via a high-speed USB 3.0 interface, supports TDMS and CSV standard format storage, and cloud backup uses HTTPS encryption protocol to ensure data transmission security.

[0067] The data processing module is deployed on a high-performance industrial computer and is jointly developed using LabVIEW and MATLAB. The industrial computer can be configured with an i7-12700 CPU and 32GB of memory. The data processing module specifically comprises the following three units: Data preprocessing unit: Automatically performs detrending, filtering, and outlier removal; processing time for a single set of data is less than 5 minutes.

[0068] Modal parameter extraction unit: integrates SSI and EMA algorithms, supporting batch processing of multiple sets of data.

[0069] Fusion Correction Unit: Corrects modal parameters by importing vibration measurement data and performing mode shape correlation analysis. Supports comparison of results from two algorithms, MAC mode shape correlation analysis, spurious mode removal, and parameter calibration.

[0070] The results output module visualizes and facilitates engineering applications of test results, specifically including: Model verification unit: Automatically plots curves comparing measured and simulated modal parameters, error bar charts, etc., and calculates and displays error values.

[0071] Report generation unit: Automatically generates a complete PDF test report with one click, including tower information, measuring point layout, acquisition parameters, modal parameter table, vibration mode cloud map, error analysis, optimization suggestions, etc.

[0072] Early warning push unit: It communicates with the wind farm SCADA system. When resonance risk is identified, it immediately pushes early warning information to the operation and maintenance terminal in real time, realizing closed-loop management of test-evaluation-early warning.

[0073] In summary, the modal testing method and system for quadrilateral truss-steel cylinder hybrid wind turbine towers of this invention, tailored to the structural characteristics of quadrilateral truss towers, employs a layered and densely packed measurement point layout, combining overall and local measurements, to capture local modal characteristics of crossmembers, diagonal members, and connecting nodes, effectively identifying structural weaknesses. The method utilizes a collaborative loading approach combining environmental and artificial excitation, integrating SSI and EMA multi-algorithm fusion processing, and incorporating modal confidence criteria for verification, thereby reducing modal frequency testing errors. The method constructs an integrated testing system encompassing sensing, acquisition, processing, and output, supporting simultaneous acquisition of multi-source data and cloud backup. This shortens the testing cycle, and the test results can be directly used to correct finite element models, identify resonance risks, and output structural optimization suggestions. Furthermore, it can interface with wind farm SCADA systems to achieve closed-loop management of testing, evaluation, and early warning.

[0074] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A hybrid wind turbine tower modal testing method, characterized in that, Includes the following steps: S1: Obtain the design parameters of the target tower, calculate the theoretical modal parameters through finite element simulation, and determine the test coverage area as the top surface of the tower foundation to the flange surface of the tower top nacelle; S2: Three-dimensional acceleration sensors are arranged in layers in the truss section, transition section and steel tower section, and sensors are densely arranged at the midpoints of the horizontal and diagonal bars of the truss section to form an overall and local measurement point array; S3: Apply incentives using a combination of environmental and artificial incentives and collect response signals; S4: Acceleration, excitation force, and environmental parameters are simultaneously acquired using a multi-channel data acquisition device; S5: After data preprocessing, modal parameters are extracted using the random subspace method and the frequency response function modal analysis method, respectively, and the final modal parameters are obtained through fusion correction; S6: Result verification and application. The test results are compared with the finite element model, the model is corrected, and structural evaluation and optimization suggestions are output.

2. The method for modal testing of hybrid wind turbine towers according to claim 1, characterized in that, In step S2 A test section is set every 20m along the tower height of the truss section, and a triaxial acceleration sensor is arranged on each of the four columns of each section. The transition section is equipped with a first section, and a triaxial acceleration sensor is arranged in each of the four directions of the first section; a second section is set at the bottom, middle and top of the steel tower section, and two triaxial acceleration sensors are arranged in each second section. 2 additional crossbars and diagonal braces are densely arranged at the midpoints of each layer of the truss section. Four triaxial accelerometers.

3. The method for modal testing of hybrid wind turbine towers according to claim 1, characterized in that, The environmental stimulus in step S3 is as follows: under shutdown conditions with wind speed < 2m / s and wind speed ≤ 5m / s, the response signal is collected for 30 minutes, and the wind speed, temperature and humidity are recorded simultaneously.

4. The method for modal testing of hybrid wind turbine towers according to claim 1, characterized in that, The artificial excitation in step S3 is as follows: pulse excitation is applied by a force hammer along the X, Y and torsional directions at the middle section of the truss section, the transition section section and the middle section of the steel tower section.

5. The method for modal testing of hybrid wind turbine towers according to claim 4, characterized in that, The striking force of the hammer is 1. The hammer is 5kN, and it strikes the object 5 times each in the X, Y, and torsional directions, and the average value is taken.

6. The method for modal testing of hybrid wind turbine towers according to claim 1, characterized in that, The preprocessing in step S5 includes detrending, low-pass filtering with a cutoff frequency of 20Hz, and whitening.

7. The method for modal testing of hybrid wind turbine towers according to claim 1, characterized in that, In step S5, the random subspace method uses 0.1 5Hz frequency range, 0 Stability plots within a 5% damping ratio range are used to screen effective modes; frequency response function modal analysis is performed using peak picking to determine the frequency and half-power bandwidth to calculate the damping ratio; when the natural frequency deviation between the two methods is >3%, it is corrected using the modal confidence criterion (MAC).

8. A hybrid wind turbine tower modal testing system, characterized in that, It includes a sensing module, a data acquisition module, a data processing module, and a result output module connected in sequence; The sensing module includes a triaxial accelerometer, a force hammer, and an environmental parameter acquisition instrument; The data acquisition module includes a multi-channel data acquisition instrument; The data processing module includes a data preprocessing unit, a modal parameter extraction unit, and a fusion correction unit, integrating the random subspace method and the frequency response function modal analysis method. The result output module includes a model verification unit, a report generation unit, and an early warning push unit, and can be connected to the wind farm SCADA system.

9. The hybrid wind turbine tower modal testing system according to claim 8, characterized in that, The triaxial accelerometer has a range of ±5g and a frequency response of 0.

1. 50Hz, resolution 0.001g, installation stiffness ≥10 6 N / m; hammer range is 0 5kN, with a frequency response of 0.1 kN with a force sensor. 10kHz.

10. The hybrid wind turbine tower modal testing system according to claim 8, characterized in that, The data acquisition module has a GPS synchronization accuracy of ≤1ms and a sampling rate of 200Hz; the data processing module is developed based on LabVIEW and MATLAB, and the processing time for a single set of data is <5min.

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