Blade vortex-induced vibration monitoring and early warning method and device, wind turbine generator and storage medium

Abstract

The application discloses a blade vortex-induced vibration monitoring and early warning method and device, a wind turbine generator and a storage medium. The blade vortex-induced vibration monitoring and early warning method comprises collecting and storing vibration data of a blade; the vibration data is analyzed and processed by using time domain analysis, frequency domain analysis and wavelet analysis; when the monitoring system detects that the blade has a vortex-induced vibration phenomenon, an early warning signal is sent and control measures are taken; and a corresponding emergency plan is formulated according to the construction condition of the wind turbine generator. The vibration data of the blade is collected, the vibration data is analyzed, whether the blade has a vortex-induced vibration phenomenon is judged, the vibration data is further analyzed by using time domain analysis, frequency domain analysis and wavelet analysis, the accuracy of vortex-induced vibration prediction and diagnosis is improved, when it is determined that the vortex-induced vibration phenomenon has occurred, an early warning signal is sent, measures for weakening and eliminating the vortex-induced vibration phenomenon are taken, and an emergency plan is formulated, so that the operation stability of the blade is ensured and the service life of the blade is prolonged.

Description

Technical Field

[0001] This application relates to the field of wind power generation technology, and in particular to a method, device, wind turbine generator and storage medium for monitoring and early warning of blade vortex-induced vibration. Background Technology

[0002] When wind turbine generators generate electricity, it is essential to maintain a constant output frequency. A constant output frequency is crucial for both grid-connected wind turbine power generation and wind-solar hybrid power generation. To ensure a constant frequency, one approach is to maintain a constant generator speed; another is to allow the generator speed to vary with wind speed, employing other methods to ensure a constant output frequency—a process known as variable-speed constant-frequency operation.

[0003] The wind energy utilization coefficient of a wind turbine is related to the tip speed ratio (the ratio of the linear velocity at the tip of the rotor to the wind speed). There exists a specific tip speed ratio that maximizes the wind energy utilization coefficient. Therefore, in variable speed constant frequency operation, the rotational speed of the wind turbine and generator can vary over a wide range without affecting the frequency of the output power.

[0004] However, the blades of current wind turbine generators may become unstable during the installation process, before grid connection, and during operation when power is lost, which will severely deplete the fatigue life of the blades and may lead to direct failure of the blades in a short period of time. To address the above problems, a blade vortex-induced vibration monitoring and early warning method is provided. Summary of the Invention

[0005] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a method, device, wind turbine, and storage medium for monitoring and early warning of blade vortex-induced vibration. The method for monitoring and early warning of blade vortex-induced vibration can detect the vortex-induced vibration phenomenon of the blade and provide early warning, reduction, and elimination of the vortex-induced vibration phenomenon.

[0006] According to the blade vortex-induced vibration monitoring and early warning method of the first aspect of this application, the blade vortex-induced vibration monitoring and early warning method includes:

[0007] Data acquisition involves collecting and storing vibration data from the blades.

[0008] Data analysis and processing: The vibration data is analyzed and processed using time domain analysis, frequency domain analysis, and wavelet analysis.

[0009] Early warning and control: When the monitoring system detects vortex-induced vibration in the blades, it issues an early warning signal and takes control measures.

[0010] Emergency response plans should be developed based on the construction progress of the wind turbine generator sets.

[0011] The blade vortex-induced vibration monitoring and early warning method according to the embodiments of this application has at least the following beneficial effects: collecting vibration data such as vibration amplitude, vibration frequency and vibration acceleration of the blade, analyzing the vibration data to determine whether the blade has vortex-induced vibration, and further analyzing the vibration data using time domain analysis, frequency domain analysis and wavelet analysis to improve the accuracy of vortex-induced vibration prediction and diagnosis. When it is determined that vortex-induced vibration has occurred, an early warning signal is issued, and measures to weaken or eliminate vortex-induced vibration are taken, and an emergency plan is formulated to ensure the operational stability of the blade and improve the service life of the blade.

[0012] According to some embodiments of this application, the acquisition and storage of blade vibration data includes:

[0013] Indicator monitoring involves real-time collection of data on blade vibration amplitude, frequency, and acceleration.

[0014] Link the monitoring system and store the vibration data in the monitoring system;

[0015] Data calibration and testing: Regularly calibrate and test the monitoring system.

[0016] According to some embodiments of this application, the analysis and processing of the vibration data using time-domain analysis, frequency-domain analysis, and wavelet analysis includes:

[0017] Data preprocessing involves cleaning and filtering the raw data within the monitoring system.

[0018] Feature extraction involves extracting characteristic parameters of the blades from the preprocessed data to reflect the vibration characteristics of the blades.

[0019] State judgment: Based on the characteristic parameters, determine whether the blade exhibits vortex-induced vibration.

[0020] According to some embodiments of this application, determining whether a blade exhibits vortex-induced vibration based on the aforementioned characteristic parameters includes:

[0021] If a significant resonant frequency appears in the characteristic parameters, and this frequency matches the expected frequency of vortex-induced vibration, the blade may be experiencing vortex-induced vibration.

[0022] If the mode shape characteristics in the aforementioned characteristic parameters match the typical mode shape of vortex-induced vibration, the blade may exhibit vortex-induced vibration.

[0023] At least one of the following methods should be used to make a comprehensive judgment on whether vortex-induced vibration exists: comparing historical data, simulation analysis, and expert evaluation.

[0024] According to some embodiments of this application, the time-domain analysis includes:

[0025] Remove noise and interference from the signal and determine the reasons for the data quality problems;

[0026] Identify the vibration data, determine the cleaning objectives and requirements based on the data identification results, and formulate corresponding cleaning strategies;

[0027] Analyze the time-domain characteristic waveforms, calculate the time-domain characteristic parameters, and output the results by establishing and optimizing the mathematical model.

[0028] According to some embodiments of this application, the frequency domain analysis includes:

[0029] The purpose of frequency domain analysis is to determine the signal features that need to be extracted.

[0030] Select the appropriate frequency domain transformation method based on the analysis requirements;

[0031] Convert the time-domain signal into the frequency-domain signal to obtain the signal's spectral information;

[0032] Observe the spectrum diagram and interpret the characteristics of the signal in the frequency domain through spectrum analysis results.

[0033] According to some embodiments of this application, when the monitoring system detects vortex-induced vibration in the blades, it issues an early warning signal and takes control measures, including:

[0034] When the monitoring system detects vortex-induced vibration in the blades, it triggers an early warning signal.

[0035] Reduce the blade rotation speed to decrease the amplitude of vortex-induced vibration;

[0036] Adjust the blade angle to reduce the probability of vortex-induced vibration.

[0037] According to a second aspect embodiment of the present application, the blade vortex-induced vibration monitoring and early warning device includes a data monitoring and acquisition module, a data analysis and processing module, and an early warning and control module, used to collect and store vibration data of the blade; to perform time-domain analysis, frequency-domain analysis, and wavelet analysis on the vibration data; and to issue an early warning signal when vortex-induced vibration occurs on the blade, and reduce the amplitude and probability of vortex-induced vibration.

[0038] According to a third aspect embodiment of this application, the wind turbine includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the program to implement the above-described blade vortex-induced vibration monitoring and early warning method.

[0039] According to a fourth aspect embodiment of the present application, a computer-readable storage medium stores computer-executable instructions for causing a computer to perform the blade vortex-induced vibration monitoring and early warning method as described above.

[0040] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0041] The accompanying drawings are used to provide a further understanding of the technical solutions disclosed in this application and form part of the specification. They are used together with the embodiments disclosed in this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions disclosed in this application.

[0042] Figure 1 This is a flowchart of a blade vortex-induced vibration monitoring and early warning method according to an embodiment of this application;

[0043] Figure 2 This is a flowchart of another embodiment of the blade vortex-induced vibration monitoring and early warning method of this application;

[0044] Figure 3 This is a flowchart of another embodiment of the blade vortex-induced vibration monitoring and early warning method of this application;

[0045] Figure 4 This is a flowchart of another embodiment of the blade vortex-induced vibration monitoring and early warning method of this application;

[0046] Figure 5 This is a flowchart of another embodiment of the blade vortex-induced vibration monitoring and early warning method of this application;

[0047] Figure 6 This is a flowchart of another embodiment of the blade vortex-induced vibration monitoring and early warning method of this application;

[0048] Figure 7 This is a flowchart of another embodiment of the blade vortex-induced vibration monitoring and early warning method of this application. Detailed Implementation

[0049] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0050] In the description of this application, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application 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. Therefore, they should not be construed as limitations on this application.

[0051] In the description of this application, "several" means one or more, "multiple" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0052] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0053] In the description of this application, the terms "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0054] This application provides a method for monitoring and early warning of blade vortex-induced vibration, which is applied to wind turbine generator sets.

[0055] A wind turbine generator set includes a wind rotor and a generator; the wind rotor includes blades, a hub, and reinforcing components. The blades rotate to generate electricity under the drive of wind power, which in turn rotates the generator head. Furthermore, a wind power supply unit includes a wind turbine generator set, a tower supporting the generator set, a battery charging controller, an inverter, a load unloader, a grid connection controller, and a battery bank.

[0056] Based on the aforementioned wind turbine generator set, the following are various embodiments of the blade vortex-induced vibration monitoring and early warning method of this application.

[0057] like Figure 1 As shown, Figure 1 This is a flowchart of a blade vortex-induced vibration monitoring and early warning method provided in one embodiment of this application. The blade vortex-induced vibration monitoring and early warning method can be applied to the above-mentioned wind turbine generator set. The blade vortex-induced vibration monitoring and early warning method includes, but is not limited to, steps S100, S110, S120 and S130.

[0058] Step S100: Data acquisition, collecting and storing the vibration data of the blades.

[0059] Additionally, refer to Figure 2 In some examples, step S100 may include, but is not limited to, the following steps:

[0060] Step S200: Index monitoring, real-time acquisition of vibration amplitude, vibration frequency and vibration acceleration data of the blade.

[0061] In some examples, vibration sensors, fiber optic sensors, and accelerometers installed on the blades are used to monitor the vibration amplitude, vibration frequency, and vibration acceleration of the blades in real time. Therefore, the vibration data in this application mainly refers to the vibration amplitude, vibration frequency, and vibration acceleration.

[0062] Furthermore, the vibration sensor includes an internal piezoelectric ceramic plate and a spring, and is constructed by connecting the piezoelectric ceramic plate with a spring-loaded weight. The vibration sensor senses vibration parameters of mechanical motion, such as vibration velocity, frequency, and acceleration, and converts these parameters into usable output signals. These signals are amplified by an operational amplifier and output as control signals, thereby enabling the monitoring and measurement of vibration phenomena.

[0063] Meanwhile, the working principle of fiber optic sensors is to send the incident light beam from the light source through an optical fiber into a modulator. Within the modulator, the light source interacts with the external parameters being measured, causing changes in the optical properties of the light, such as intensity, wavelength, frequency, phase, and polarization state, thus becoming a modulated optical signal. The beam then passes through an optical fiber into a photoelectric device, and after demodulation, the measured parameters are obtained. Throughout the process, the beam is guided through an optical fiber, passes through a modulator, and then exits. It can be understood that the primary function of the optical fiber is to transmit the light beam, and secondly, it acts as an optical modulator. Accelerometers use the interaction of mass and springs, or other physical principles, to sense acceleration. When an object is subjected to acceleration, its internal sensitive elements, such as springs or piezoelectric elements, deform or generate charges. The magnitude and direction of the acceleration are measured by measuring this deformation or charge.

[0064] Step S210: Connect to the monitoring system and store the vibration data in the monitoring system.

[0065] In some examples, the aforementioned sensors are electrically connected to a monitoring system to collect and store the vibration data of the blades in real time.

[0066] Step S220, Data calibration and testing: The monitoring system is calibrated and tested regularly.

[0067] In some examples, the monitoring system is calibrated and tested regularly to ensure the accuracy and reliability of the data.

[0068] Step S110: Data analysis and processing, using time domain analysis, frequency domain analysis, and wavelet analysis to analyze and process the vibration data.

[0069] Additionally, refer to Figure 3 In some examples, step S110 may include, but is not limited to, the following steps:

[0070] Step S300: Data preprocessing, which involves cleaning and filtering the raw data within the monitoring system.

[0071] In some examples, the raw vibration data is cleaned and filtered to remove noise and interference.

[0072] Step S310, Feature extraction: Extract the characteristic parameters of the blade from the preprocessed data to reflect the vibration characteristics of the blade.

[0073] Step S320, State determination: Determine whether the blade exhibits vortex-induced vibration based on the characteristic parameters.

[0074] In some examples, the presence of vortex-induced vibration in the blade is determined based on extracted feature parameters. Vibration data of the blade under specific operating conditions, such as vibration frequency, mode shape characteristics, and response amplitude, can be obtained using the aforementioned sensors and corresponding data acquisition systems. Furthermore, it is also necessary to obtain the mechanical property test results of the blade material, such as strength and stiffness.

[0075] The parameters mentioned above reflect the inherent properties of the blade and are crucial for assessing its resistance to vortex-induced vibration. Meanwhile, factors such as wind speed, wind direction, and atmospheric conditions in the blade's environment can significantly influence its vibration state. After extracting the characteristic parameters, these parameters need to be analyzed to identify the presence of vortex-induced vibration characteristics.

[0076] Additionally, refer to Figure 4 In some examples, step S320 may include, but is not limited to, the following steps:

[0077] Step S400: If a significant resonant frequency appears in the characteristic parameters and the frequency matches the expected frequency of vortex-induced vibration, the blade may exhibit vortex-induced vibration.

[0078] In some examples, typical characteristics of vortex-induced vibration include vibration frequency, mode shape, and response amplitude. Regarding vibration frequency, vortex-induced vibration often causes the blade to resonate at a specific frequency. Therefore, if a distinct resonant frequency appears in the extracted vibration data, and this frequency matches the expected frequency of vortex-induced vibration, it indicates that the blade may be experiencing vortex-induced vibration.

[0079] Step S410: If the mode shape characteristics in the characteristic parameters match the typical mode shape of vortex-induced vibration, the blade may exhibit vortex-induced vibration.

[0080] In some examples, vortex-induced vibrations often result in specific mode shapes in the blades, such as bending or torsional modes. If the extracted mode shapes match typical vortex-induced vibration modes, it may indicate the presence of vortex-induced vibration.

[0081] Furthermore, regarding the response amplitude, vortex-induced vibration typically leads to a significant increase in the vibration response amplitude of the blade. Therefore, if the extracted response amplitude significantly exceeds the normal range, it indicates that the blade may be experiencing vortex-induced vibration.

[0082] Step S420: Use at least one of the following methods to make a comprehensive judgment on whether vortex-induced vibration exists: comparing historical data, simulation analysis, and expert evaluation.

[0083] In some examples, the system also needs to make a comprehensive judgment on whether the blades are experiencing vortex-induced vibration. This comprehensive judgment may involve comparing historical data, simulation analysis, expert evaluation, and other methods.

[0084] The comparison with historical data involves comparing the extracted feature parameters with historical data to assess whether the current vibration state of the blade has changed. If there is a significant difference between the current data and the historical data, and the characteristics are consistent with vortex-induced vibration, it indicates that the blade may be experiencing vortex-induced vibration.

[0085] Furthermore, simulation analysis refers to the use of computer simulation methods to analyze vortex-induced vibration of blades. By establishing a mathematical model and applying numerical calculation methods, the vibration state of the blade under specific operating conditions can be simulated, and the existence of vortex-induced vibration can be assessed. The simulation results can be compared with actual data to verify the accuracy of the judgment.

[0086] Meanwhile, expert evaluation refers to inviting experienced experts to assess and judge the extracted characteristic parameters. Experts can use their professional knowledge and experience, combined with the actual situation, to conduct a comprehensive analysis of the blade's vibration state and conclude whether vortex-induced vibration exists.

[0087] Additionally, refer to Figure 5 In some examples, the time-domain analysis in step S110 may include, but is not limited to, the following steps:

[0088] Step S500: Remove noise, interference and other useless information from the signal and find out the reason for the data quality problem.

[0089] In some examples, it is necessary to remove unwanted information such as noise and interference from the signal before performing time-domain analysis, thereby improving data quality.

[0090] Furthermore, the basic principle of data cleaning lies in identifying the causes of data quality problems based on the analysis of the characteristics of the data source. First, the characteristics of the data source must be analyzed. Data can come from various channels, such as databases, API interfaces, and sensors used for real-time monitoring. Different data sources have different characteristics and reliability.

[0091] For example, database data may be updated more frequently and have stronger standardization, while manually entered data may be more prone to errors. The type of data, such as structured data or unstructured data, also affects its quality and processing methods. Real-time data needs frequent updates, while non-real-time data may be updated less frequently but still requires periodic checking and updating. The scale and scope of the data will affect the complexity of its processing and analysis.

[0092] Meanwhile, large-scale data may require more powerful computing resources and more complex processing flows. Inadequate design and development of database table structures, database constraints, and data validation rules can lead to data entry failures or improper validation, resulting in data duplication, incompleteness, and inaccuracy. Problems with the data interface itself, incorrect configuration of data interface parameters, and unreliable networks can all cause data quality issues during data transmission.

[0093] In addition, there are problems with the configuration of data cleaning rules, data transformation rules, and data loading rules; the data storage design is unreasonable; the data storage capacity is limited; manual backend adjustments to data can easily lead to data loss, invalid data, data distortion, and duplicate records; and the data description and data rules are unclear. These factors can prevent the system from building a reasonable and correct data model. The system also experiences common data entry problems, such as errors in capitalization, full-width / half-width characters, and special characters.

[0094] Step S510: Identify the vibration data, determine the cleaning target and requirements based on the data identification results, and formulate a corresponding cleaning strategy.

[0095] In some examples, the data cleaning process first requires defining the cleaning requirements and establishing a cleaning model. Cleaning algorithms, strategies, and solutions are then applied to data identification and processing to ultimately clean data that meets the quality requirements.

[0096] This involves identifying the types of errors in the data, including incomplete data, erroneous data, and duplicate data. Based on the data identification results, the goals and requirements for data cleaning are determined. Understandably, determining the goals and requirements for data cleaning based on the data identification results, and developing corresponding cleaning strategies, is crucial.

[0097] Specifically, it identifies situations where certain attribute values ​​are missing in the dataset. Missing values ​​may be caused by reasons such as equipment failure, data entry errors, or omissions during the data collection process.

[0098] Identify values ​​in the dataset that are significantly different from most of the data. Outliers may be caused by measurement errors, data entry errors, or the unique characteristics of the data itself.

[0099] Identify records that are exactly or nearly identical in the dataset. Duplicate data may be caused by repeated operations during data entry, errors during data merging, or data synchronization problems.

[0100] Identify inaccurate or invalid data caused by input errors, equipment malfunctions, or data conversion errors;

[0101] Identify contradictory or inconsistent records in the dataset. Inconsistent data may be caused by different sources describing the same thing differently or by errors in the data transformation process.

[0102] Fill in missing values ​​to ensure data integrity and avoid analytical bias caused by missing values; identify and handle outliers to ensure data accuracy and reliability; avoid interference from outliers on data analysis results, delete duplicate records to reduce storage costs, and avoid misleading data analysis results with duplicate data; correct erroneous data to improve the accuracy and reliability of data analysis.

[0103] Simultaneously, integrating and standardizing inconsistent data ensures data consistency and accuracy, improving the efficiency of data analysis and mining. When the number of missing values ​​is small and has little impact on the analysis results, they can be ignored, and filled with statistical measures such as the mean, median, and mode, or with predictive models such as interpolation or regression; alternatively, machine learning algorithms such as K-nearest distance or decision trees can be used.

[0104] When the number of outliers is small and their impact on the analysis results is significant, they can be deleted. When the number of outliers is large or their impact on the analysis results is somewhat significant, outliers can be corrected, such as by replacing them with statistical measures like the mean or median, or by using data smoothing or data transformation methods. Use methods such as uniqueness constraints and similarity calculations to identify and delete duplicate records. When duplicate records contain different but related information, they can be merged while retaining key information.

[0105] Data validation rules and regular expressions are used to identify and correct erroneous data. Correct data values ​​are deduced based on the logic and rules of blade vibration data, and erroneous data is replaced.

[0106] Integrate data from different sources to ensure data consistency and accuracy, and process the data using a unified data format and standards to ensure data consistency and comparability.

[0107] It is worth noting that the cleaning strategy needs to include the selection of cleaning methods, cleaning order, and cleaning tools to remove duplicate records from the dataset. This can be achieved by comparing unique identifiers or key fields in the records, thereby filling in missing values ​​in the dataset. Common processing methods include estimation, whole-case deletion, variable deletion, and pairwise deletion.

[0108] The specific method chosen depends on the number of missing values, their impact on the analysis results, and the needs for blade vibration data. Detecting and processing outliers in the dataset—often referred to as "outliers"—is crucial; these outliers differ significantly from other data points in the dataset. Outliers can be removed or replaced with acceptable values, depending on their nature and impact on the analysis results. Standardizing the data format to a consistent standard facilitates processing and analysis.

[0109] The cleaned data should be evaluated for quality to check whether the cleaning effect meets the expected requirements. If the cleaning effect is not ideal, the cleaning strategy needs to be adjusted and the cleaning operation needs to be repeated.

[0110] Step S520: Analyze the time-domain characteristic waveform, calculate the time-domain characteristic parameters, and output the results by establishing and optimizing the mathematical model.

[0111] In some examples, the signal is first filtered using a suitable filter based on the analysis requirements to remove unwanted frequency components. Then, the time-domain waveform is analyzed to observe its characteristics, including amplitude, periodicity, and shape. Statistical parameters of the signal are calculated, including dimensional extrema, mean, variance, dimensionless margin, kurtosis, and peak value, to reflect the signal's energy distribution and vibration intensity. The extracted parameters are compared with preset thresholds or standards to assess the equipment's operating status, observe the trends of these parameters over time, predict the equipment's future state, and diagnose faults based on the changes in these parameters, combined with the equipment's structure and operating principles.

[0112] Furthermore, appropriate mathematical models are selected for fitting based on the characteristics of the signal, including linear regression and nonlinear regression. The fitted models are then tested to evaluate their accuracy and reliability. Based on the test results, the models are optimized to improve the accuracy of prediction and diagnosis. Finally, based on the analysis results, corresponding maintenance, repair, or replacement decisions are made to ensure the stable operation and safety of the equipment.

[0113] Additionally, refer to Figure 6 In some examples, the frequency domain analysis in step S110 may include, but is not limited to, the following steps:

[0114] Step S600: Determine the signal features to be extracted through frequency domain analysis.

[0115] In some examples, the purpose of frequency domain analysis is clearly defined, and the signal features to be extracted are determined based on this purpose. Furthermore, sensors or other devices are used to acquire the signals to be analyzed, including sound, vibration, and acceleration. Additionally, the acquired signals undergo preprocessing, including noise removal and filtering, to improve signal quality.

[0116] Step S610: Select a suitable frequency domain transformation method according to the analysis requirements.

[0117] Step S620: Convert the time-domain signal into a frequency-domain signal to obtain the signal's spectral information.

[0118] Step S630: Observe the spectrum diagram and interpret the characteristics of the signal in the frequency domain through the spectrum analysis results.

[0119] In some examples, the frequency spectrum is observed to analyze the signal's frequency components, including the dominant frequency, secondary frequencies, and harmonics. Interpreting the signal's characteristics in the frequency domain includes understanding the distribution of frequency components and energy distribution.

[0120] Furthermore, frequency domain transformation methods include Fourier transform and Fast Fourier transform, which represent a function satisfying certain conditions as a trigonometric function, or a linear combination of their integrals. Specifically, the trigonometric functions are sine and / or cosine functions. The Fourier transform and Fast Fourier transform are used to transform a function or signal from the time domain to the frequency domain. Through the Fourier transform, the amplitude and phase information of sine waves at different frequencies in the signal can be obtained.

[0121] Meanwhile, the Fourier transform decomposes a time-domain signal into a superposition of a series of sine waves, each corresponding to a frequency component. Furthermore, the Fast Fourier Transform (FFT) is used to quickly calculate the signal's spectrum.

[0122] Step S120, Early Warning and Control: When the monitoring system detects vortex-induced vibration in the blades, it issues an early warning signal and takes control measures.

[0123] Additionally, refer to Figure 7 In some examples, step S120 may include, but is not limited to, the following steps:

[0124] Step S700: When the monitoring system detects vortex-induced vibration in the blades, an early warning signal is triggered.

[0125] In some examples, when the monitoring system detects vortex-induced vibration in the blades, it immediately triggers an early warning signal, which can be sent to relevant personnel via audible and visual alerts, SMS notifications, or other means. It is understood that wind turbine units include devices such as warning lights and information transmission components.

[0126] Step S710: Reduce the blade rotation speed to decrease the amplitude of vortex-induced vibration.

[0127] In some examples, after the warning process is completed, the system needs to mitigate or eliminate vortex-induced vibration. Therefore, the system reduces the blade speed by adjusting the wind turbine's control strategy to decrease the amplitude of vortex-induced vibration.

[0128] Step S720: Adjust the blade angle to reduce the probability of vortex-induced vibration.

[0129] In some examples, the system uses appropriate actuators to change the blade's angle of attack to reduce the probability of vortex-induced vibration. Additionally, when necessary, the system shuts down the wind turbine and performs a comprehensive inspection of the blades to ensure their integrity and safety.

[0130] Step S130: Emergency plan formulation. Develop corresponding emergency plans based on the construction status of the wind turbine generator set.

[0131] In some examples, the center of gravity and lifting point of the blade are accurately measured and marked before hoisting to ensure the balance of the blade during the hoisting process.

[0132] Meanwhile, during the hoisting process, it is necessary to strengthen the monitoring and tracking of the blades to further ensure the stability and safety of the blades during the hoisting process.

[0133] Furthermore, before the blades are connected to the grid after installation, a comprehensive inspection and testing of the blades is required to ensure that they meet the requirements for grid connection.

[0134] In addition, the monitoring system should be debugged and calibrated to ensure that it can accurately monitor the vibration of the blades; a comprehensive emergency plan should be established during the operation of the wind turbine to deal with sudden power outages; and in the event of a power outage, the monitoring and protection of the blades should be strengthened to prevent blade failure caused by vortex-induced vibration.

[0135] This application provides a blade vortex-induced vibration monitoring and early warning device, which includes a data monitoring and acquisition module, a data analysis and processing module, and an early warning and control module.

[0136] The data monitoring and acquisition module is used to collect and store the vibration data of the blade; the data analysis and processing module is used to perform time domain analysis, frequency domain analysis and wavelet analysis on the vibration data; and the early warning and control module is used to issue an early warning signal when the blade experiences vortex-induced vibration and to reduce the amplitude and probability of vortex-induced vibration.

[0137] This application provides a wind turbine generator, which may include:

[0138] Memory, processor, and computer programs stored in memory and capable of running on the processor.

[0139] When the processor executes the program, it implements the blade vortex-induced vibration monitoring and early warning method provided in the above embodiments.

[0140] Furthermore, wind turbine units also include:

[0141] A communication interface used for communication between the memory and the processor.

[0142] Memory is used to store computer programs that can run on the processor.

[0143] The memory may include high-speed RAM, and may also include non-volatile memory, such as at least one disk drive.

[0144] If the memory, processor, and communication interface are implemented independently, they can be interconnected via a bus to communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc.

[0145] Alternatively, in a specific implementation, if the memory, processor, and communication interface are integrated on a single chip, then the memory, processor, and communication interface can communicate with each other through an internal interface.

[0146] The processor may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0147] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the blade vortex-induced vibration monitoring and early warning method described above.

[0148] This embodiment also provides a computer program product, including a computer program, which, when executed, is used to implement the blade vortex-induced vibration monitoring and early warning method described above.

[0149] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0150] 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 technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0151] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0152] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, deciphering, or otherwise processing as necessary, and then stored in a computer memory.

[0153] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0154] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0155] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0156] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for monitoring and early warning of blade vortex-induced vibration, characterized in that, include: Data acquisition involves collecting and storing vibration data from the blades. Data analysis and processing: The vibration data is analyzed and processed using time domain analysis, frequency domain analysis, and wavelet analysis. Data preprocessing involves cleaning and filtering the raw data from the monitoring system; feature extraction involves extracting characteristic parameters of the blades from the preprocessed data to reflect their vibration characteristics; state judgment involves determining whether vortex-induced vibration exists in the blades based on the characteristic parameters; if a significant resonant frequency appears in the characteristic parameters and this frequency matches the expected frequency of vortex-induced vibration, the blades are likely to experience vortex-induced vibration; if the mode shape characteristics in the characteristic parameters match the typical mode shape of vortex-induced vibration, the blades are likely to experience vortex-induced vibration; at least one of the following methods—comparing historical data, simulation analysis, and expert evaluation—is used to determine whether vortex-induced vibration exists. The comprehensive assessment of eddy-induced vibration includes: time-domain analysis (removing interference from the signal, identifying the causes of data quality problems, identifying the vibration data, determining the cleaning objectives and requirements based on the data identification results, formulating corresponding cleaning strategies, analyzing time-domain characteristic waveforms, calculating time-domain characteristic parameters, and outputting results by establishing and optimizing mathematical models); and frequency-domain analysis (determining the signal features to be extracted based on the frequency-domain analysis objectives, selecting appropriate frequency-domain transformation methods according to analysis requirements, converting the time-domain signal into a frequency-domain signal, obtaining the signal's spectral information, observing the spectrum, and interpreting the signal's characteristics in the frequency domain based on the spectral analysis results). Early warning and control: When the monitoring system detects vortex-induced vibration in the blades, it issues an early warning signal and takes control measures. Emergency response plans should be developed based on the construction progress of the wind turbine generator sets.

2. The blade vortex-induced vibration monitoring and early warning method according to claim 1, characterized in that, The process of collecting and storing the vibration data of the blades includes: Indicator monitoring involves real-time collection of data on blade vibration amplitude, frequency, and acceleration. Link the monitoring system and store the vibration data in the monitoring system; Data calibration and testing: Regularly calibrate and test the monitoring system.

3. The blade vortex-induced vibration monitoring and early warning method according to claim 1, characterized in that, When the monitoring system detects vortex-induced vibration in the blades, it issues an early warning signal and takes control measures, including: When the monitoring system detects vortex-induced vibration in the blades, it triggers an early warning signal. Reduce the blade rotation speed to decrease the amplitude of vortex-induced vibration; Adjust the blade angle to reduce the probability of vortex-induced vibration.

4. A blade vortex-induced vibration monitoring and early warning device, employing the blade vortex-induced vibration monitoring and early warning method as described in any one of claims 1 to 3, characterized in that, include: The data monitoring and acquisition module is used to collect and store the vibration data of the blades; The data analysis and processing module is used to perform time-domain analysis, frequency-domain analysis, and wavelet analysis on the vibration data. The early warning and control module is used to issue an early warning signal when vortex-induced vibration occurs on the blades, and to reduce the amplitude and probability of vortex-induced vibration.

5. A wind turbine generator set, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the blade vortex-induced vibration monitoring and early warning method as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to perform the blade vortex-induced vibration monitoring and early warning method as described in any one of claims 1 to 3.

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