Offshore wind turbine impeller balance degree analysis method and device
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUANENG GUANGDONG SHANTOU OFFSHORE WIND POWER CO LTD
- Filing Date
- 2025-02-07
- Publication Date
- 2026-08-07
AI Technical Summary
在风力发电快速发展的同时，风电机组运行过程中暴露出的问题越来越突出，尤其是关键机械部件发生的故障导致机组非正常停机维修，严重降低了发电效率，增加了检维修成本
[0043]本申请提供的海上风机叶轮平衡度分析方法、装置、电子设备及存储介质，通过特征数据进行综合分析以确定叶轮平衡度，有效地对海上风机叶片的叶轮平衡度进行监测和异常分析，为海上风机的安全运行和维护提供支持。
Smart Images
Figure CN122524318A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of wind turbine monitoring technology, and in particular to a method and apparatus for analyzing the balance of offshore wind turbine impellers. Background Technology
[0002] Wind energy, as a clean and renewable energy source, is receiving increasing attention from countries worldwide. Its reserves are enormous; global wind energy is ten times greater than the total exploitable hydropower potential on Earth. Therefore, monitoring wind turbines is crucial during wind power generation. While wind power is developing rapidly, problems arising during wind turbine operation are becoming increasingly prominent. In particular, failures in key mechanical components lead to abnormal shutdowns for maintenance, severely reducing power generation efficiency and increasing maintenance costs. The inconvenience of maintaining wind turbines due to malfunctions is further exacerbating application issues.
[0003] In existing technologies, the status of wind turbine units cannot be monitored in a timely manner during use, resulting in a high accident rate and reduced operating efficiency. Summary of the Invention
[0004] This application aims to at least partially address one of the technical problems in the related art.
[0005] Therefore, the first objective of this application is to propose a method for analyzing the balance of offshore wind turbine impellers.
[0006] The second objective of this application is to provide an apparatus.
[0007] The third objective of this application is to propose an electronic device.
[0008] The fourth objective of this application is to provide a computer-readable storage medium.
[0009] The fifth objective of this application is to provide a computer program product.
[0010] To achieve the above objectives, the first aspect of this application proposes a method for analyzing the balance of an offshore wind turbine impeller, comprising:
[0011] Sensors are installed on offshore wind turbines, and the sensor data collected by the sensors is acquired.
[0012] The sensing data is preprocessed, and feature extraction is performed on the preprocessed sensing data to obtain feature data;
[0013] The feature data is comprehensively analyzed to determine the impeller balance, and early warning information is generated based on the impeller balance.
[0014] Optionally, the installation of sensors on the offshore wind turbine includes:
[0015] Flange gap sensors are placed at the leading and trailing edges of the blade root and at the windward flange.
[0016] Install acceleration sensors on the blades;
[0017] Strain sensors are installed in the middle and at the tip of the blade.
[0018] Optionally, acquiring the sensing data collected by the sensor includes:
[0019] Acquire the gap data collected by the flange gap sensor;
[0020] Acquire the acceleration data collected by the accelerometer;
[0021] The strain data collected by the strain sensor is acquired, and the gap data, acceleration data and strain data are sensor data.
[0022] Optionally, the preprocessing of the sensing data includes:
[0023] The sensor data is subjected to filtering, noise reduction, and wavelet transform.
[0024] Optionally, the step of extracting features from the preprocessed sensing data to obtain feature data includes:
[0025] Perform a Fourier transform on the gap data to obtain the impeller rotation frequency, and further determine the impeller speed based on the frequency;
[0026] The peak-to-peak values of different blades at the same position are subtracted pairwise, and the absolute values are taken. Then the average value is taken to obtain the average difference between the front and rear flange gaps of the three blades.
[0027] Calculate the peak-to-peak values of the strain data at the middle and end points, and calculate the average peak-to-peak value of the strain.
[0028] Optionally, the comprehensive analysis of the feature data to determine the impeller balance includes:
[0029] The impeller's rotational speed, the mean difference between the front and rear flange clearances, and the mean peak-to-peak strain value are input into the health assessment model to calculate the impeller's balance.
[0030] Optionally, generating early warning information based on the impeller balance includes:
[0031] If the impeller balance is greater than the preset first warning value, then the impeller balance is determined to be normal.
[0032] If the impeller balance is less than or equal to the first warning value and greater than the preset second warning value, a warning message is generated, which indicates that the impeller balance is slightly abnormal.
[0033] If the impeller balance is less than or equal to the second warning value, a warning message is generated, which indicates that the impeller balance is seriously abnormal.
[0034] To achieve the above objectives, a second aspect of this application provides an offshore wind turbine impeller balance analysis device, comprising:
[0035] The monitoring module is used to install sensors on the offshore wind turbine and acquire the sensing data collected by the sensors.
[0036] The processing module is used to preprocess the sensing data and extract features from the preprocessed sensing data to obtain feature data.
[0037] The analysis module is used to perform comprehensive analysis on the feature data to determine the impeller balance, and generate early warning information based on the impeller balance.
[0038] To achieve the above objectives, a third aspect of this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;
[0039] The memory stores computer-executed instructions;
[0040] The processor executes computer execution instructions stored in the memory to implement the method as described in any one of the first aspects.
[0041] To achieve the above objectives, a fourth aspect of this application provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement the method as described in any one of the first aspects.
[0042] To achieve the above objectives, a fifth aspect of this application provides a computer program product that, when executed by a processor, implements the method described in any one of the first aspects.
[0043] The offshore wind turbine impeller balance analysis method, device, electronic equipment and storage medium provided in this application determine the impeller balance through comprehensive analysis of characteristic data, effectively monitor and analyze the impeller balance of offshore wind turbine blades, and provide support for the safe operation and maintenance of offshore wind turbines.
[0044] 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
[0045] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:
[0046] Figure 1 A flowchart illustrating a method for analyzing the balance of an offshore wind turbine impeller provided in an embodiment of this application;
[0047] Figure 2 This is a schematic diagram of the structure of an offshore wind turbine impeller balance analysis device provided in an embodiment of this application. Detailed Implementation
[0048] 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 intended to explain this application, and should not be construed as limiting this application.
[0049] This application provides a method for analyzing the balance of offshore wind turbine impellers. Figure 1 This is a flowchart illustrating a method for analyzing the balance of an offshore wind turbine impeller, provided in an embodiment of this application. Figure 1 As shown, the method includes the following steps:
[0050] Step 101: Install sensors on the offshore wind turbine and acquire the sensing data collected by the sensors;
[0051] Step 102: Preprocess the sensing data and extract features from the preprocessed sensing data to obtain feature data;
[0052] Step 103: Perform comprehensive analysis on the feature data to determine the impeller balance, and generate early warning information based on the impeller balance.
[0053] Optionally, the installation of sensors on the offshore wind turbine includes:
[0054] Flange gap sensors are placed at the leading and trailing edges of the blade root and at the windward flange.
[0055] Install acceleration sensors on the blades;
[0056] Strain sensors are installed in the middle and at the tip of the blade.
[0057] In one possible embodiment, at least six flange clearance sensors are deployed on each blade. These sensors collect operational data of the support structure, including parameters such as vibration, stress, and deformation, and store the data in a data center or cloud server. The data acquisition frequency and parameters need to be adjusted according to the actual conditions of the support structure to ensure the accuracy and comprehensiveness of the data.
[0058] Optionally, acquiring the sensing data collected by the sensor includes:
[0059] Acquire the gap data collected by the flange gap sensor;
[0060] Acquire the acceleration data collected by the accelerometer;
[0061] The strain data collected by the strain sensor is acquired, and the gap data, acceleration data and strain data are sensor data.
[0062] Optionally, the preprocessing of the sensing data includes:
[0063] The sensor data is subjected to filtering, noise reduction, and wavelet transform.
[0064] Data preprocessing is a set of techniques and procedures used to refine raw data into an analyzable format. The initial preprocessing steps can significantly impact the final insights or predictive accuracy, whether dealing with structured tabular data, complex text data, time-related temporal data, or even multimedia datasets. Preprocessing these different data types strengthens the foundation of the analysis.
[0065] Structured data consists of well-defined data types and is organized by columns and rows. Its tabular nature makes it a common starting point for many data analysis tasks. Preprocessing structured data typically involves handling missing data and transforming the data into the correct format suitable for analysis.
[0066] First, filtering is performed to remove unwanted noise, peaks, trends, and outliers from the signal to improve data quality. Common filtering methods include:
[0067] Mean filtering: This method filters data by taking the average of the values of the sliding windows preceding and following a point in the original observation data. It's simple, but may sacrifice some of the data.
[0068] Median filtering: Similar to mean filtering, but the median value within a fixed-size sliding window is used as the filtering result. Median filtering can effectively overcome fluctuation noise caused by random factors.
[0069] Low-pass, high-pass, and band-pass filters: These filters are used to block high-frequency signals, low-frequency signals, or retain signals within a specific frequency range, respectively.
[0070] Then, we handle missing and outlier values. For outlier detection, we commonly use two methods: statistical outlier detection and visualization-based outlier detection.
[0071] After finding missing values and outliers using the above methods, there are several processing methods: (1) When the number of outliers and missing values is small and has little impact on the overall data distribution, we can directly delete the outliers and missing values. (2) Fill the data with the mean, median, or mode. (3) Fill the data with interpolation. Fill the data with Lagrange interpolation, Newton interpolation, and cubic bar interpolation.
[0072] Then, data transformation is performed, including normalization: scaling the data to a specific range, such as between 0 and 1, to facilitate comparisons between different features; and standardization: converting the data into a distribution with a mean of 0 and a standard deviation of 1.
[0073] Optionally, the step of extracting features from the preprocessed sensing data to obtain feature data includes:
[0074] Perform a Fourier transform on the gap data to obtain the impeller rotation frequency, and further determine the impeller speed based on the frequency;
[0075] The peak-to-peak values of different blades at the same position are subtracted pairwise, and the absolute values are taken. Then the average value is taken to obtain the average difference between the front and rear flange gaps of the three blades.
[0076] Calculate the peak-to-peak values of the strain data at the middle and end points, and calculate the average peak-to-peak value of the strain.
[0077] Optionally, the comprehensive analysis of the feature data to determine the impeller balance includes:
[0078] The impeller's rotational speed, the mean difference between the front and rear flange clearances, and the mean peak-to-peak strain value are input into the health assessment model to calculate the impeller's balance.
[0079] Optionally, generating early warning information based on the impeller balance includes:
[0080] If the impeller balance is greater than the preset first warning value, then the impeller balance is determined to be normal.
[0081] If the impeller balance is less than or equal to the first warning value and greater than the preset second warning value, a warning message is generated, which indicates that the impeller balance is slightly abnormal.
[0082] If the impeller balance is less than or equal to the second warning value, a warning message is generated, which indicates that the impeller balance is seriously abnormal.
[0083] In one possible embodiment, the impeller balance is a value in the range of 0-100%. The higher the impeller balance, the better the balance of the impeller. The first warning value is 80%, the second warning value is 40%, and if the impeller balance is lower than a certain threshold, the impeller needs to be adjusted or maintained.
[0084] To achieve the above embodiments, this application also proposes a device for analyzing the balance of offshore wind turbine impellers. Figure 2 This is a schematic diagram of a device for analyzing the balance of an offshore wind turbine impeller, provided as an embodiment of this application. Figure 2 As shown, the device includes:
[0085] The monitoring module 210 is used to install sensors on the offshore wind turbine and acquire the sensing data collected by the sensors.
[0086] The processing module 220 is used to preprocess the sensing data and extract features from the preprocessed sensing data to obtain feature data.
[0087] The analysis module 230 is used to perform comprehensive analysis on the feature data to determine the impeller balance, and generate early warning information based on the impeller balance.
[0088] To implement the above embodiments, this application also proposes an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiments.
[0089] To implement the above embodiments, this application also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.
[0090] To implement the above embodiments, this application also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.
[0091] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this application comply with relevant laws and regulations and do not violate public order and good morals.
[0092] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.
[0093] This application is intended to provide an implementation scheme for users to selectively prevent the use or access to their personal information data. Specifically, this disclosure is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.
[0094] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "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. 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.
[0095] 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, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.
[0096] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more 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.
[0097] 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, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.
[0098] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple 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.
[0099] Those skilled in the art will understand that all or part of the steps of the methods described 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, it includes one or a combination of the steps of the method embodiments.
[0100] 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.
[0101] 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 analyzing the balance of offshore wind turbine impellers, characterized in that, Includes the following steps: Sensors are installed on offshore wind turbines, and the sensor data collected by the sensors is acquired. The sensing data is preprocessed, and feature extraction is performed on the preprocessed sensing data to obtain feature data; The feature data is comprehensively analyzed to determine the impeller balance, and early warning information is generated based on the impeller balance.
2. The method according to claim 1, characterized in that, The installation of sensors on offshore wind turbines includes: Flange gap sensors are placed at the leading and trailing edges of the blade root and at the windward flange. Install acceleration sensors on the blades; Strain sensors are installed in the middle and at the tip of the blade.
3. The method according to claim 2, characterized in that, The acquisition of the sensing data collected by the sensor includes: Acquire the gap data collected by the flange gap sensor; Acquire the acceleration data collected by the accelerometer; The strain data collected by the strain sensor is acquired, and the gap data, acceleration data and strain data are sensor data.
4. The method according to claim 3, characterized in that, The preprocessing of the sensing data includes: The sensor data is subjected to filtering, noise reduction, and wavelet transform.
5. The method according to claim 4, characterized in that, The step of extracting features from the preprocessed sensing data to obtain feature data includes: Perform a Fourier transform on the gap data to obtain the impeller rotation frequency, and further determine the impeller speed based on the frequency; The peak-to-peak values of different blades at the same position are subtracted pairwise, and the absolute values are taken. Then the average value is taken to obtain the average difference between the front and rear flange gaps of the three blades. Calculate the peak-to-peak values of the strain data at the middle and end points, and calculate the average peak-to-peak value of the strain.
6. The method according to claim 5, characterized in that, The comprehensive analysis of the feature data to determine the impeller balance includes: The impeller's rotational speed, the mean difference between the front and rear flange clearances, and the mean peak-to-peak strain value are input into the health assessment model to calculate the impeller's balance.
7. The method according to claim 6, characterized in that, The step of generating early warning information based on the impeller balance includes: If the impeller balance is greater than the preset first warning value, then the impeller balance is determined to be normal. If the impeller balance is less than or equal to the first warning value and greater than the preset second warning value, a warning message is generated, which indicates that the impeller balance is slightly abnormal. If the impeller balance is less than or equal to the second warning value, a warning message is generated, which indicates that the impeller balance is seriously abnormal.
8. A device for analyzing the balance of an offshore wind turbine impeller, characterized in that, include: The monitoring module is used to install sensors on the offshore wind turbine and acquire the sensing data collected by the sensors. The processing module is used to preprocess the sensing data and extract features from the preprocessed sensing data to obtain feature data. The analysis module is used to perform comprehensive analysis on the feature data to determine the impeller balance, and generate early warning information based on the impeller balance.
9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-7.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.