Fan stability state evaluation method and device, electronic equipment, storage medium and program product

Abstract

The invention relates to the technical field of wind power generation, and discloses a fan stability state evaluation method and device, electronic equipment, a storage medium and a program product, and the method comprises the steps: collecting original operation data of a target fan; the original operation data of the target fan comprises fan cabin displacement data, fan vibration acceleration data, fan cabin inclination angle data, wind speed data and fan resonance data; performing data preprocessing on the original operation data of the target fan to obtain preprocessed original operation data; and based on the preprocessed original operation data, performing stability state evaluation on the target fan by using the fan stability state evaluation function to obtain a fan stability evaluation result. According to the method, the interaction and the influence among the factors are fully considered, so that the misjudgment on the real stability state of the fan caused by one-sided evaluation is avoided.

Description

Technical Field

[0001] This invention relates to the field of wind power generation technology, specifically to a method, apparatus, electronic device, storage medium, and program product for assessing the stability of wind turbines. Background Technology

[0002] In the field of wind power generation, the stable operation of wind turbines is crucial for power generation efficiency and equipment safety.

[0003] The existing methods for assessing the stability of wind turbines rely on only one or a few factors, and cannot comprehensively consider the synergistic effect of different factors on the stability of wind turbines, thus failing to provide timely and effective protection for the safe operation of wind turbines. Summary of the Invention

[0004] This invention provides a method, apparatus, electronic device, storage medium, and program product for assessing the stability of wind turbines, in order to solve the problem that the synergistic effect between different factors on the stability of wind turbines cannot be comprehensively considered, thus failing to provide timely and effective protection for the safe operation of wind turbines.

[0005] In a first aspect, the present invention provides a method for evaluating the stability status of a wind turbine, the method comprising:

[0006] Collect raw operating data of the target wind turbine; the raw operating data of the target wind turbine includes wind turbine nacelle displacement data, wind turbine vibration acceleration data, wind turbine nacelle tilt angle data, wind speed data and wind turbine resonance data; The raw operating data of the target wind turbine is preprocessed to obtain preprocessed raw operating data; Based on the preprocessed raw operating data, the stability status of the target wind turbine is evaluated using the wind turbine stability status evaluation function, and the wind turbine stability evaluation result is obtained.

[0007] In a second aspect, the present invention provides a wind turbine stability assessment device, the device comprising: The data acquisition module is used to collect the raw operating data of the target wind turbine. The raw operating data of the target wind turbine includes wind turbine nacelle displacement data, wind turbine vibration acceleration data, wind turbine nacelle tilt angle data, wind speed data, and wind turbine resonance data. The data preprocessing module is used to preprocess the raw operating data of the target wind turbine to obtain preprocessed raw operating data; The stability status assessment module is used to assess the stability status of the target wind turbine based on the preprocessed raw operating data and using the wind turbine stability status assessment function to obtain the wind turbine stability assessment result.

[0008] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the wind turbine stability status assessment method of the first aspect or any corresponding embodiment described above.

[0009] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the wind turbine stability status assessment method of the first aspect or any corresponding embodiment described above.

[0010] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the wind turbine stability status assessment method of the first aspect or any corresponding embodiment described above.

[0011] This invention provides a method for assessing the stability of wind turbines. By comprehensively considering multiple key factors such as nacelle displacement, vibration acceleration, tilt angle, extreme winds, and turbine resonance, and using a complex and scientific wind turbine stability assessment function for quantitative analysis, it can accurately assess the stability of wind turbines. Compared with assessment methods that rely on only one or a few parameters, this method fully considers the interaction and influence between various factors, thus avoiding misjudgments of the true stability of wind turbines due to one-sided assessments. It is of great significance in ensuring the safe and stable operation of wind turbines, improving power generation efficiency, reducing operation and maintenance costs, and promoting the development of wind turbine technology, providing solid technical support for the sustainable development of the wind power industry. Attached Figure Description

[0012] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0013] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the first process of a wind turbine stability status assessment method according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the wind turbine monitoring system architecture according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the second process of a wind turbine stability status assessment method according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the data processing flow according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the third process of a wind turbine stability status assessment method according to an embodiment of the present invention; Figure 7 This is a schematic diagram of the fourth process of a wind turbine stability status assessment method according to an embodiment of the present invention; Figure 8 This is a structural block diagram of a wind turbine stability assessment device according to an embodiment of the present invention; Figure 9 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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 embodiments of the present invention, not all embodiments. 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.

[0015] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0016] As an optional application scenario of this invention, such as Figure 1 As shown, application 101 is installed in terminal device 110, and user 130 can interact with application 101 through terminal device 110 and / or access device of terminal device 110.

[0017] For example, application 101 can be any application that provides question-and-answer related services. For instance, application 101 could be a question-and-answer interactive application, such as a text-to-text application, an image-to-text application, etc. Figure 1 In the application scenario shown, if application 101 is active, the terminal device 110 can display the interface 102 of application 101. The interface 102 may include various pages that application 101 can provide, such as interactive pages, settings pages, query pages, etc.

[0018] In some embodiments, terminal device 110 is communicatively connected to server 120 to provide services to application 101. Terminal device 110 may be a mobile terminal, fixed terminal, or portable terminal, etc., including but not limited to mobile phones, desktop computers, laptop computers, multimedia tablets, e-book devices, gaming devices, or any combination thereof, including accessories and peripherals of these devices or any combination thereof. In some embodiments, terminal device 110 may also support any type of interface, and server 120 may be various types of computing systems or servers capable of providing computing power, including but not limited to mainframes, edge computing nodes, computing devices in cloud environments, etc.

[0019] It should be noted that, Figure 1 This is merely an example of an application scenario and does not limit the scope of protection of this invention.

[0020] The embodiments of the present invention will now be described with reference to the accompanying drawings. It should be understood that the pages shown in the drawings are merely examples, and various page designs are possible in practice. The various graphic elements on the page may have different arrangements and different visual representations; one or more elements may be omitted or replaced, and one or more other elements may also be present; no limitations are imposed in the embodiments of the present invention. Furthermore, the embodiments described below primarily pertain to terminal device 110. It should be understood that the actions described relative to terminal device 110 can be performed by application 101 on terminal device 110, or can be performed by application 101 in conjunction with its server (e.g., server 120).

[0021] In the field of wind power generation, the stable operation of wind turbines is crucial for power generation efficiency and equipment safety. Currently, wind turbine stability assessment methods have many limitations. Some methods rely on only a single parameter for evaluation, such as monitoring only the turbine blade speed to determine the turbine's operating status. However, wind turbine operation is a complex system engineering project, and a single parameter cannot comprehensively reflect the overall stability of the turbine. Even if the blade speed is within the normal range, anomalies in the turbine nacelle displacement, vibration acceleration, or tilt angle can still lead to potential instability risks. Such single-parameter assessment methods easily overlook these critical factors, thus failing to detect problems in the turbine in a timely manner.

[0022] Furthermore, while some evaluation methods consider multiple parameters, they employ simple threshold judgments. For example, fixed thresholds are set for displacement, vibration acceleration, and tilt angle; as long as each parameter does not exceed the threshold, the wind turbine is considered to be in a stable state. However, in reality, these parameters have complex interrelationships, and simple threshold judgments cannot comprehensively consider the synergistic effect of their interactions on wind turbine stability. In some cases, even if individual parameters are within the threshold range, poor coupling between parameters can still lead to a decrease in wind turbine stability, and the relevant evaluation methods cannot effectively identify this potential instability.

[0023] Furthermore, most relevant assessment methods lack the ability to dynamically track the operating status of wind turbines. The stability characteristics of wind turbines change under different environmental conditions and at different operating stages. These assessment methods are often based on fixed standards and models, and cannot dynamically adjust their assessment strategies according to real-time operating data, making it difficult to accurately reflect the true stability status of the wind turbine. When the wind turbine's operating environment changes suddenly, such as encountering strong winds or sudden temperature fluctuations, these assessment methods may fail to detect changes in wind turbine stability in a timely manner, thus failing to provide timely and effective protection for the safe operation of the wind turbine.

[0024] In summary, existing wind turbine stability assessment methods are insufficient in terms of comprehensiveness, accuracy, and dynamic adaptability. There is an urgent need for a new method that can comprehensively consider multiple key parameters such as wind turbine nacelle displacement, vibration acceleration, and tilt angle, and accurately and dynamically assess the stability status of the wind turbine.

[0025] This invention provides a method for assessing the stability of wind turbines. By comprehensively considering multiple key factors such as nacelle displacement, vibration acceleration, tilt angle, extreme winds, and turbine resonance, and using a complex and scientific wind turbine stability assessment function for quantitative analysis, it can accurately assess the stability of wind turbines. Compared with assessment methods that rely on only one or a few parameters, this method fully considers the interaction and influence between various factors, thus avoiding misjudgments of the true stability of wind turbines due to one-sided assessments. For example, related wind turbine stability assessment methods may only focus on vibration acceleration, while ignoring the synergistic effect of nacelle displacement on wind turbine stability under extreme winds. This method, however, can comprehensively and accurately reflect the stability of wind turbines under various operating conditions.

[0026] Among them, the multi-factor-based wind turbine stability assessment method is innovative, differing from assessment methods that rely on only one or a few factors. It comprehensively considers various complex factors affecting wind turbine stability and their interrelationships, providing a brand-new approach and method for wind turbine stability assessment. The quantification methods of each factor in the wind turbine stability assessment function, the combination form of the function, and the application of integral summation operations have been carefully designed and verified by a large number of experiments, enabling accurate and effective assessment of wind turbine stability. The layout of sensors in the wind turbine nacelle and key parts, as well as the preprocessing strategy for the collected data, are important aspects to ensure the accuracy of the assessment.

[0027] According to an embodiment of the present invention, a method for evaluating the stability status of a wind turbine is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0028] This embodiment provides a method for evaluating the stability of a wind turbine, which can be used in the aforementioned terminal equipment. Figure 2 This is a flowchart of a wind turbine stability status assessment method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps: Step S201: Collect the raw operating data of the target wind turbine; the raw operating data of the target wind turbine includes wind turbine nacelle displacement data, wind turbine vibration acceleration data, wind turbine nacelle tilt angle data, wind speed data and wind turbine resonance data.

[0029] Specifically, multiple sensors are used to collect raw operating data of the target wind turbine at a preset acquisition frequency; among them, multiple sensors are set at the target location in the wind turbine nacelle.

[0030] Furthermore, the stability of a wind turbine during operation is affected by a combination of factors. To comprehensively and accurately obtain key information reflecting wind turbine stability, it is necessary to install different types of high-precision sensors at specific locations within the wind turbine nacelle; such as... Figure 3 As shown, the overall wind turbine monitoring system architecture diagram illustrates the installation locations of displacement sensors, vibration acceleration sensors, tilt angle sensors, wind speed sensors, and resonance monitoring sensors on the wind turbine nacelle. For example, displacement sensors are distributed in the stress concentration area connecting the nacelle and the tower, and vibration acceleration sensors are located at the center of mass of the nacelle. This visually demonstrates the layout of each sensor and marks the connection relationships between each sensor and data acquisition, data preprocessing, and evaluation calculations, explaining the data flow, i.e., how the data collected by the sensors is preprocessed before stability assessment.

[0031] Furthermore, the displacement sensor was installed in the stress concentration area connecting the nacelle and the tower because this area bears significant stress during wind turbine operation, and displacement changes can sensitively reflect the stability of the wind turbine structure. For example, the LK-N100 displacement sensor, with its nanometer-level precision (capable of accurately sensing displacement changes as low as 10 nanometers), can capture extremely subtle displacement changes, monitoring nacelle displacement from all directions (x, y, z), providing a precise data foundation for subsequent analysis.

[0032] Furthermore, the vibration accelerometer is installed at the center of gravity of the nacelle because the vibration at this location can represent the vibration characteristics of the entire nacelle; the 356A16 vibration accelerometer features a wide dynamic range and picometer-level resolution, with an accuracy of up to 0.001. It can accurately capture various vibration acceleration signals from low frequency to high frequency, thereby accurately reflecting the vibration state during the operation of the wind turbine.

[0033] Furthermore, the tilt angle sensor is installed on a precisely calibrated horizontal reference plane on the top of the nacelle, because the tilt angle of the nacelle has a significant impact on the stability of the wind turbine; the RTS02-0.1 tilt angle sensor has an ultra-high accuracy of 0.1 arcseconds and can acquire the tilt angle of the nacelle relative to the horizontal position in real time, providing key parameters for assessing the stability of the wind turbine.

[0034] Furthermore, considering the significant impact of extreme winds and turbine resonance on turbine stability, a WindSonic ultrasonic anemometer is installed on the windward side of the nacelle, with a measurement range of up to 75. It can monitor wind speed in real time, especially accurately capturing wind speed changes under extreme wind conditions. FBG-RS resonance monitoring sensors based on fiber optic grating technology are installed in key locations such as the root of the wind turbine blades and the middle of the tower, achieving a frequency resolution of 0.01Hz and an amplitude resolution of 1. It can accurately detect parameters such as resonance frequency and amplitude, and effectively monitor the resonance state of the wind turbine.

[0035] Furthermore, different parameters exhibit varying frequency characteristics during wind turbine operation, necessitating the setting of appropriate acquisition frequencies based on their specific features. Displacement, vibration acceleration, and tilt angle change relatively frequently during normal wind turbine operation; acquiring data at a frequency of 100Hz effectively captures their rapid dynamic changes, ensuring no critical information is missed. While wind speed changes relatively slowly, it can shift rapidly under extreme wind conditions. Therefore, acquiring data at a frequency of 20Hz provides timely response to rapid wind speed changes without generating excessive redundant data. Wind turbine resonance is often accompanied by high-frequency parameter fluctuations; therefore, resonance monitoring sensors acquiring data at a high frequency of 500Hz accurately capture subtle changes under resonance conditions, providing precise data for assessing the impact of resonance on wind turbine stability.

[0036] Step S202: Perform data preprocessing on the raw operating data of the target wind turbine to obtain preprocessed raw operating data.

[0037] Specifically, the raw operating data of the target wind turbine will inevitably contain noise and outliers. These interference factors will affect the accurate assessment of the wind turbine's stability, so data preprocessing is required.

[0038] Step S203: Based on the preprocessed raw operating data, the stability status of the target wind turbine is evaluated using the wind turbine stability status evaluation function to obtain the wind turbine stability evaluation result.

[0039] Specifically, the stability of a wind turbine is a complex system characteristic, which is affected by the interaction of various factors such as nacelle displacement, vibration acceleration, tilt angle, extreme wind, and wind turbine resonance. When constructing the wind turbine stability state evaluation function, it is necessary to fully consider these factors and reasonably quantify their contribution to the wind turbine stability.

[0040] Furthermore, the continuous evaluation of wind turbine stability accumulates a wealth of operational data, including displacement, vibration acceleration, tilt angle, wind speed, and resonance data collected by various sensors. This data can not only be used for real-time evaluation of wind turbine stability but also, through further analysis, provide strong data support for wind turbine design improvements and performance optimization. For example, long-term data analysis might reveal that a certain type of wind turbine is prone to resonance issues within a specific wind speed range, providing wind turbine manufacturers with a reference for design improvements and fundamentally enhancing the stability and reliability of the wind turbine.

[0041] This embodiment provides a wind turbine stability assessment method that comprehensively considers multiple key factors such as nacelle displacement, vibration acceleration, tilt angle, extreme winds, and turbine resonance. It utilizes a complex and scientific wind turbine stability assessment function for quantitative analysis, enabling extremely accurate assessment of the wind turbine's stability. Compared to assessment methods that rely on only one or a few parameters, this method fully considers the interactions and influences between various factors, thus avoiding misjudgments of the wind turbine's true stability due to incomplete assessments. This method is of great significance in ensuring the safe and stable operation of wind turbines, improving power generation efficiency, reducing operation and maintenance costs, and promoting the development of wind turbine technology, providing solid technical support for the sustainable development of the wind power industry.

[0042] This embodiment provides a method for evaluating the stability of a wind turbine, which can be used in the aforementioned terminal equipment. Figure 4 This is a flowchart of a wind turbine stability status assessment method according to an embodiment of the present invention, such as... Figure 4 As shown, the process includes the following steps: Step S401: Collect the raw operating data of the target wind turbine. The raw operating data includes turbine nacelle displacement data, turbine vibration acceleration data, turbine nacelle tilt angle data, wind speed data, and turbine resonance data. For details, please refer to [link to relevant documentation]. Figure 2 Step S201 of the illustrated embodiment will not be described again here.

[0043] Step S402: Perform data preprocessing on the raw operating data of the target wind turbine to obtain preprocessed raw operating data.

[0044] Specifically, such as Figure 5 As shown, the entire process from data acquisition to evaluation is illustrated in the form of a flowchart: starting with the acquisition of raw data from sensors, high-frequency noise is filtered out by an elliptic low-pass filter, outliers are detected by the isolated forest algorithm, outliers are corrected by a Kalman filter, and finally the preprocessed data is substituted into the wind turbine stability state evaluation function for calculation to obtain the wind turbine stability evaluation result. The flowchart details the name and function of each processing step, as well as the changes in data at each step.

[0045] Step S402 includes: Step S4021: Use an elliptic low-pass filter to filter out high-frequency noise in the original operating data of the target wind turbine.

[0046] Specifically, the 8th-order elliptic low-pass filter has a steep cutoff characteristic, which can effectively filter out high-frequency noise with a frequency higher than 50Hz, making the data smoother and more accurately reflecting the operating status of the wind turbine.

[0047] Step S4022: Perform outlier detection on the original operating data after filtering out high-frequency noise to obtain abnormal operating data.

[0048] Specifically, the Isolation Forest algorithm is used for outlier detection. The principle of the Isolation Forest algorithm is as follows: in the data space, normal data points are usually clustered in high-density areas, while outlier data points are distributed in low-density areas. By constructing 50 isolated trees, the path length of each data point in the tree is analyzed. The shorter the path length, the more the data point deviates from the normal data distribution, and the higher the degree of anomaly. If the outlier score of a data point exceeds a set threshold (this threshold is determined through statistical analysis of a large amount of normal data, for example, set to 0.8), it is judged as an outlier.

[0049] Step S4023: Use a Kalman filter to correct the abnormal running data to obtain the preprocessed original running data.

[0050] Specifically, the Kalman filter is used to correct outliers. The Kalman filter is an optimal estimation method based on the state-space model of a linear system. It uses the physical model of the wind turbine operation and the data from the previous moment to predict the value at the current moment, and combines the current measurement value to make the optimal estimate. By continuously updating the error covariance between the predicted value and the measured value, the Kalman filter can effectively correct outliers, making the data more consistent with the actual state of wind turbine operation, and providing reliable data input for subsequent stability assessment.

[0051] Step S403: Based on the preprocessed raw operating data, the stability status of the target wind turbine is evaluated using the wind turbine stability status evaluation function to obtain the wind turbine stability evaluation result. For details, please refer to [link to relevant documentation]. Figure 2 Step S203 of the illustrated embodiment will not be described again here.

[0052] This embodiment provides a method for assessing the stability of a wind turbine. Based on the original operating data of the target wind turbine, noise is removed using an elliptic low-pass filter, and outliers are detected and corrected, ensuring the accuracy of the wind turbine stability assessment.

[0053] This embodiment provides a method for evaluating the stability of a wind turbine, which can be used in the aforementioned terminal equipment. Figure 6 This is a flowchart of a wind turbine stability status assessment method according to an embodiment of the present invention, such as... Figure 6 As shown, the process includes the following steps: Step S601: Collect the raw operating data of the target wind turbine. The raw operating data includes turbine nacelle displacement data, turbine vibration acceleration data, turbine nacelle tilt angle data, wind speed data, and turbine resonance data. For details, please refer to [link to relevant documentation]. Figure 4 Step S401 of the illustrated embodiment will not be described again here.

[0054] Step S602: Perform data preprocessing on the raw operating data of the target wind turbine to obtain preprocessed raw operating data. For details, please refer to [link to relevant documentation]. Figure 4 Step S402 of the illustrated embodiment will not be described again here.

[0055] Step S603: Based on the preprocessed raw operating data, the stability status of the target wind turbine is evaluated using the wind turbine stability status evaluation function to obtain the wind turbine stability evaluation result.

[0056] Specifically, step S603 includes: Step S6031: Calculate the displacement deviation metric based on the wind turbine nacelle displacement data, and normalize the wind turbine nacelle displacement data using an error function to obtain the contribution value of the wind turbine nacelle displacement to the wind turbine stability.

[0057] Specifically, starting from the wind turbine nacelle displacement data, the deviation of displacement in each direction from the mean is calculated and normalized by combining it with the standard deviation. The degree of deviation of the displacement factor from the ideal state is measured in the form of the sum of absolute values. The displacement deviation metric is... The calculation formula is as follows: (1) Among them, the larger ones This indicates that the displacement deviates significantly from the mean in multiple directions, suggesting that the wind turbine may have structural instability or foundation problems, which will negatively affect the stability of the wind turbine.

[0058] Furthermore, the displacement changes of the wind turbine nacelle in different directions have a significant impact on its stability. By processing the displacement data in the x, y, and z directions respectively, and normalizing the displacement data using an error function, the expression of which is: (2) For example, for the first The cabin displacement data in the x-direction collected this time. First, calculate its average displacement in that direction. The deviation is then mapped to an error function. The interval is obtained After normalization, displacement data in different directions have a unified dimension and comparable scale in the evaluation function, which can comprehensively reflect the impact of nacelle displacement on wind turbine stability.

[0059] Furthermore, the contribution of wind turbine nacelle displacement to wind turbine stability. The calculation formula is: (3) Among them, the normalized wind turbine nacelle displacement data is , and , For the first The wind turbine nacelle obtained in the second sampling Displacement data in the direction reflects the cabin's position. Changes in orientation and position are one of the key parameters for assessing the impact of wind turbine nacelle displacement on stability; For the first The wind turbine nacelle obtained in the second sampling Displacement data in the direction reflects the cabin's position. Changes in direction and position, and and Together, they describe the cabin displacement. For the first The wind turbine nacelle obtained in the second sampling Displacement data in the direction reflects the cabin's position. Changes in orientation and position are an indispensable part of a comprehensive assessment of the impact of nacelle displacement on wind turbine stability; For all collected wind turbine nacelles in The mean of directional displacement data is used to measure... The average level of directional displacement helps in analyzing the overall characteristics of displacement data; For all collected wind turbine nacelles in The mean of directional displacement data reflects The average displacement in a direction helps to understand the overall trend of displacement in that direction; For all collected wind turbine nacelles in The mean of directional displacement data reflects The average level of directional displacement provides an important reference for analyzing the impact of nacelle displacement on wind turbine stability; For the wind turbine nacelle in The standard deviation of directional displacement data reflects The degree of dispersion of directional displacement data is used to measure The fluctuation of directional displacement data relative to the mean; For the wind turbine nacelle The standard deviation of directional displacement data reflects The degree of dispersion in directional displacement data helps to understand The magnitude of the change in directional displacement; For the wind turbine nacelle in The standard deviation of directional displacement data reflects The degree of dispersion of directional displacement data is of great significance for comprehensively assessing the impact of nacelle displacement on wind turbine stability. Here, the error function is used to evaluate the wind turbine nacelle at different times. Displacement data in different directions are normalized to ensure that displacement data in different directions have a unified dimension and comparable scale in the evaluation function.

[0060] in, By integrating displacement information of the wind turbine nacelle in the x, y, and z directions, and multiplying the displacement data in each direction after normalization using an error function, the impact of spatial position changes of the nacelle on stability is comprehensively considered. Since any abnormal displacement in any direction during wind turbine operation may affect its overall stability, for example, excessive displacement of the nacelle in the x direction may indicate foundation loosening or structural deformation, the comprehensive evaluation of displacement in the three directions can more accurately reflect the effect of displacement factors on wind turbine stability.

[0061] Step S6032: Calculate the vibration acceleration deviation metric based on the fan vibration acceleration data, and use the inverse hyperbolic tangent function to filter outliers in the fan vibration acceleration data to obtain the contribution value of fan vibration acceleration to fan stability.

[0062] Specifically, a vibration acceleration deviation metric is calculated using time-series data of vibration acceleration. This metric measures the degree of abnormal changes in vibration acceleration. The calculation formula is as follows: (4) in, For the first The collected wind turbine vibration acceleration data is used to reflect the vibration situation during wind turbine operation and is an important basis for assessing the impact of wind turbine vibration on stability.

[0063] The above formula reflects the difference between the current vibration acceleration and the previous and next moments. Abnormal changes may mean that a sudden mechanical failure or abnormal vibration mode has occurred during the operation of the wind turbine, thus affecting the stability of the wind turbine. The larger the value, the greater the threat of vibration acceleration to stability.

[0064] Furthermore, vibration acceleration factor processing: Vibration acceleration is one of the key indicators reflecting the operating status of the wind turbine. In order to accurately assess its impact on the stability of the wind turbine, the inverse hyperbolic tangent function is used to filter outliers in the vibration acceleration data. The expression of the inverse hyperbolic tangent function is: ( (5) By comparing the first Vibration acceleration collected in the second sampling Compared with the values ​​collected before and after and The relationship was analyzed using the inverse hyperbolic tangent function to obtain the contribution value of the fan vibration acceleration to the fan stability. The calculation formula is as follows: (6) in, The parameters for adjusting the outlier filtering effect were determined through analysis of a large amount of normal and abnormal vibration acceleration data, for example, a value of 0.5 was set. The above processing method can effectively remove abnormal fluctuations in vibration acceleration data, making the assessment more accurate. For the first The vibration acceleration data collected this time, and and Together they are used to analyze the changing trend of vibration acceleration and help determine the impact of vibration on the stability of the fan. For the first The vibration acceleration data collected in this second acquisition is used in conjunction with the data collected in the other two acquisitions when analyzing the trend of vibration acceleration changes, so as to more accurately assess the impact of vibration on the stability of the wind turbine. This is the inverse hyperbolic tangent function, used to filter outliers in wind turbine vibration acceleration data to ensure the reliability of the vibration acceleration data. To adjust the filtering effect of abnormal values ​​in fan vibration acceleration, parameters were determined through analysis of a large amount of normal and abnormal vibration acceleration data. For example, a value of 0.5 was used to optimize the processing of abnormal values ​​in vibration acceleration data, making the assessment more accurate.

[0065] in, This study focuses on processing wind turbine vibration acceleration data. The inverse hyperbolic tangent function is used to filter outliers in the vibration acceleration data. Further normalization of the denominator ensures that vibration acceleration has an appropriate weight in the overall evaluation. During wind turbine operation, vibration acceleration is a crucial indicator reflecting its internal mechanical state. Abnormal vibration may indicate problems such as component wear and loosening, significantly impacting wind turbine stability. Therefore, this study... Incorporate vibration acceleration factors appropriately into the assessment.

[0066] Step S6033: Calculate the tilt and wind speed deviation metric based on the wind turbine nacelle tilt angle data and wind speed data.

[0067] Specifically, the deviation from the ideal state is measured from two aspects: tilt angle and wind speed. The deviation values ​​for tilt and wind speed are... The calculation formula is as follows: (7) in, It reflects the deviation between the tilt angle and the average tilt angle, and reflects the stability of the wind turbine nacelle's tilt state; By comparing with the critical wind speed, the impact of wind speed on the stability of the wind turbine is quantified. The closer the wind speed is to or exceeds the critical wind speed, the greater the harm to stability. The sum of the two reflects the degree of negative effect of tilt angle and wind speed on the stability of the wind turbine.

[0068] Step S6034: Quantitatively evaluate the wind turbine nacelle tilt angle data and wind speed data to obtain the contribution values ​​of the wind turbine nacelle tilt angle and wind speed to the stability of the wind turbine.

[0069] Specifically, the contribution of the wind turbine nacelle tilt angle and wind speed to the stability of the wind turbine. The calculation formula is as follows: (8) Furthermore, the tilt angle of the nacelle directly affects the stability of the wind turbine, through an exponential function. To illustrate the impact of the difference between the wind turbine nacelle tilt angle and the average value on the evaluation function, among which, For the first The tilt angle data collected this time reflects the tilt state of the nacelle and is a key parameter for assessing the impact of the wind turbine's tilt angle on stability. This is the average value of all collected tilt angle data, used to measure the average level of the nacelle tilt angle and help analyze the overall impact of tilt angle on wind turbine stability. The parameters for controlling the influence of the tilt angle on the evaluation function are determined through experiments and data analysis. For example, a value of 0.3 is used to adjust the weight of the tilt angle in evaluating wind turbine stability. The greater the deviation of the tilt angle from the average value, the smaller the value of the exponential function, indicating a greater negative impact on wind turbine stability.

[0070] Furthermore, wind speed is introduced: extreme winds are a significant external factor affecting wind turbine stability. The impact of extreme winds on wind turbine stability is represented by a transformation of the sigmoid function (S-shaped function). The sigmoid function is transformed as follows: ,in, For the first The wind speed data collected this time, taking into account the impact of extreme winds on the stability of the wind turbine, is an important data for assessing the effect of extreme wind factors on the stability of the wind turbine. The critical wind speed for extreme winds is determined through analysis of wind turbine design parameters and historical operating data; for example, a value of 30 is used. It is used to determine whether the wind speed has reached the level of extreme gale, so as to assess its impact on the stability of the wind turbine; The parameter used to control the influence of wind speed on the evaluation function is determined by simulating the operating state of the wind turbine under different wind speeds. For example, a value of 0.2 is used to adjust the weight of the wind speed factor in evaluating the stability of the wind turbine.

[0071] Furthermore, The exponential function combines the effects of wind turbine nacelle tilt angle and wind speed on stability. This demonstrates the effect of the difference between the tilt angle and the mean on stability; the greater the deviation of the tilt angle from the mean, the more negative the impact on stability. (Sigmoid function deformation) This is used to quantify the impact of extreme winds on wind turbine stability when the wind speed approaches or exceeds the critical wind speed. At this time, the negative impact on stability increases rapidly. The multiplication of these two functions comprehensively considers the combined effect of the two important environmental factors, tilt angle and wind speed, on the stability of the wind turbine.

[0072] Step S6035: Calculate the resonance and tilt deviation values ​​based on the wind turbine resonance data and the wind turbine nacelle tilt angle data.

[0073] Specifically, the deviations of resonant frequency, resonant amplitude, and tilt angle from safe values ​​are considered. This is achieved by calculating the deviations of the resonant frequency and amplitude from their mean values ​​and normalizing them using the standard deviation, as well as the ratio of the deviation of the tilt angle from the safe value to the allowable range. These deviations are then expressed as absolute values ​​to measure the degree to which these factors deviate from the safe or ideal state. The calculation formula is as follows: (9) Among them, the larger ones This indicates resonance or a significant deviation of the tilt angle from the safe range, posing a substantial threat to the stability of the wind turbine.

[0074] Step S6036: Quantitatively evaluate the wind turbine resonance frequency and amplitude, as well as the wind turbine nacelle tilt angle data in the wind turbine resonance data, to obtain the contribution values ​​of wind turbine resonance and tilt angle to wind turbine stability.

[0075] Specifically, the formulas for calculating the contribution of wind turbine resonance and tilt angle to wind turbine stability are as follows: (10) Furthermore, the resonance factor is quantified: wind turbine resonance poses a significant threat to its stability, and is quantified from two aspects: resonance frequency and resonance amplitude; for resonance frequency, through... To measure its impact on stability, among which, For the first The collected data on wind turbine resonant frequency parameters are used to assess the effect of the wind turbine resonant frequency on stability, and are one of the key data points for analyzing the impact of resonance factors on wind turbine stability. The mean value of all collected wind turbine resonant frequency-related parameter data reflects the average level of the resonant frequency, aiding in the analysis of the impact of the resonant frequency on wind turbine stability. The standard deviation of the wind turbine's resonant frequency-related parameters illustrates the dispersion of the resonant frequency data, helping to understand the impact of resonant frequency fluctuations on wind turbine stability. The weighting index for the influence of resonant frequency is determined through experimental and theoretical analysis. For example, a value of 0.4 is used to measure the relative importance of the influence of resonant frequency on the stability of the wind turbine.

[0076] Regarding the resonance amplitude, through To measure, among which, For the first The collected wind turbine resonance amplitude-related parameter data were used to evaluate the effect of wind turbine resonance amplitude on stability, and... Jointly assess the impact of resonance on wind turbine stability. The mean value of all collected wind turbine resonance amplitude-related parameter data reflects the average state of the resonance amplitude and is used to assess the impact of resonance amplitude on wind turbine stability. The standard deviation of the relevant parameters of the wind turbine resonance amplitude reflects the discrete characteristics of the resonance amplitude data and is of great significance for assessing the impact of resonance amplitude on wind turbine stability. The weighting index for the influence of resonance amplitude is determined through experiments and theoretical analysis. For example, a value of 0.6 is used to determine the weight of resonance amplitude in assessing wind turbine stability. The greater the deviation of resonance frequency and amplitude from the normal range, the greater the negative impact on wind turbine stability.

[0077] Furthermore, Used to demonstrate the impact of the wind turbine nacelle tilt angle deviating from the safe value on stability. The weighting index for the influence of tilt angle is determined through experiments and data analysis. For example, a value of 0.5 is used to adjust the weight of the tilt angle factor in evaluating wind turbine stability.

[0078] Furthermore, The study incorporated the impact of wind turbine resonant frequency, resonant amplitude, and tilt angle deviations from safe values ​​on stability. Power function methods were used to measure the effects of resonant frequency and amplitude on stability, as well as the degree of influence of tilt angle deviations from safe ranges. Wind turbine resonance can lead to structural fatigue damage, severely affecting stability, while tilt angle deviations from safe values ​​also increase the risk of wind turbine tipping over. By integrating these factors, the assessment of factors affecting wind turbine stability has been improved.

[0079] Step S6037: Obtain the data acquisition time and time scale, and calculate the time decay factor based on the data acquisition time and time scale.

[0080] Specifically, as a time-dependent decay factor, considering the changes in wind turbine operating status over time, recent data better reflects the current situation. For example, a wind turbine may have undergone maintenance or environmental changes over a period of time, making recent data more critical for assessing its current stability. As time progresses, the influence of earlier data gradually weakens, making the assessment results more consistent with the real-time status of the wind turbine; time decay factor The calculation formula is as follows: (11) in, The data collection start time is determined based on the moment when the wind turbine starts up and begins full-scale monitoring. Data collected from this point will be used to evaluate the stability of the wind turbine. The timeframe corresponding to the current ongoing assessment, and This constitutes a time period, within which data is analyzed to assess wind turbine stability; It is the first The time point of this data collection; It is a set time scale used to adjust the rate of time decay. The time decay factor makes recent data have a greater impact on the evaluation results.

[0081] Step S6038: Determine the wind turbine stability assessment result based on the displacement deviation metric, the contribution of the wind turbine nacelle displacement to the wind turbine stability, the acceleration deviation metric, the contribution of the wind turbine vibration acceleration to the wind turbine stability, the tilt and wind speed deviation metric, the contribution of the wind turbine nacelle tilt angle and wind speed to the wind turbine stability, the resonance and tilt deviation metric, the contribution of the wind turbine resonance and tilt angle to the wind turbine stability, and the time decay factor.

[0082] Specifically, the quantitative results of the above factors are integrated to construct a wind turbine stability state evaluation function. By using integration and summation operations, the changes of various factors over time are comprehensively considered during the data collection period. The integral parts of the numerator and denominator have the same structure, and a very small positive number is added to the denominator. (For example, the value is) To prevent the denominator from being zero, the constructed evaluation function can comprehensively and accurately reflect the stability state of the wind turbine during operation.

[0083] Furthermore, the formula for calculating the wind turbine stability state evaluation function is as follows: (12) in, This is a wind turbine stability state assessment function value constructed based on multiple factors such as wind turbine nacelle displacement, vibration acceleration, tilt angle, extreme wind, and wind turbine resonance. It is used to determine the stability state of the wind turbine, and the range of its value determines whether the wind turbine is in a healthy, unstable, or faulty state. From the start time of data collection up to the current time The number of data points collected during this period reflects the quantity of data and is used to comprehensively consider the changes in various parameters of the wind turbine during this period. The set safe tilt angle value for the wind turbine nacelle is determined through wind turbine structural mechanics analysis and safety standards. For example, a value of 1 degree is used to determine whether the nacelle tilt angle is within the safe range, so as to assess its impact on wind turbine stability. The permissible tilt angle range for the wind turbine nacelle is determined by wind turbine design specifications, for example, a value of 5 degrees. Together they are used to assess the impact of nacelle tilt angle on wind turbine stability. To prevent extremely small positive numbers with a denominator of zero from being used in the formula, for example, values ​​of... This ensures the formula's validity in mathematical operations and avoids calculation errors caused by a denominator of zero.

[0084] Furthermore, in the aforementioned wind turbine stability state evaluation function, the numerator is composed of functions related to displacement, vibration acceleration, tilt angle, wind speed, and resonance. , , , Multiplication comprehensively considers multiple key factors affecting wind turbine stability, while also introducing a time-related attenuation factor. This emphasizes the importance of recent data for assessing wind turbine stability, better reflecting the reality that wind turbine operating conditions change over time and that recent conditions are more valuable for reference; the denominator is composed of... , , , The four components measure the degree to which each factor deviates from its mean or safe range, including displacement, vibration acceleration, tilt angle and wind speed, resonance, and safe deviation of tilt angle. This is expressed as the sum of absolute values. This design differs significantly from the numerator in structure and calculation method. The denominator reflects the degree of deviation of each factor, echoing the numerator's comprehensive contribution to stability, thus forming a comprehensive assessment of wind turbine stability. This design, with its different numerator and denominator, comprehensively considers multiple factors affecting wind turbine stability and their interactions. Different calculation methods highlight the different aspects of each factor's impact on stability, making the assessment function more flexible and accurate. It more effectively reflects the actual operational stability of the wind turbine, providing a more reliable basis for wind turbine operation and maintenance management. In other words, the assessment function can comprehensively and meticulously reflect the wind turbine's stability state. When the numerator is relatively small compared to the denominator... A smaller value means that the overall contribution of each factor to stability is relatively small, and the wind turbine is in a relatively stable state; conversely, when the numerator is relatively large compared to the denominator, A larger value indicates that the factors deviate significantly from the ideal state, and the stability of the wind turbine faces a greater risk. Maintenance personnel need to pay attention and take corresponding measures. This design can effectively transform various physical factors into a quantitative stability assessment index, providing strong support for the operation and maintenance management of wind turbines.

[0085] Furthermore, in high-wind environments, wind speeds approach or exceed the extreme wind threshold. This will significantly affect the stability of the wind turbine. Under these operating conditions, The value of this item will decrease rapidly, thus lowering the overall value. Value; Technicians should pay special attention to the impact of wind speed on wind turbine stability and take measures in advance, such as adjusting the angle of the wind turbine blades to reduce wind resistance, and increasing the monitoring frequency of nacelle displacement, vibration acceleration, and tilt angle, etc. Meanwhile, according to According to the changes in the value, the operation strategy of the fan should be adjusted in a timely manner to ensure that the fan can still operate safely and stably under high wind speed conditions.

[0086] Furthermore, based on different operating conditions and wind turbine stability assessment results, the wind turbine operation strategy is optimized. Specifically, under special conditions such as high wind speeds or complex terrain, the stability of the wind turbine is more accurately assessed by adjusting the weights of relevant parameters in the formula, thereby guiding the wind turbine to adopt a more suitable operating mode. For example, at high wind speeds, the wind turbine blade angle is adjusted to reduce wind resistance, while the monitoring frequency of parameters such as displacement and vibration is increased to ensure the safe and stable operation of the wind turbine in harsh environments. This helps to improve the power generation efficiency of the wind turbine, extend its service life, and enhance the economic benefits of the entire wind farm.

[0087] Furthermore, for wind turbines installed in complex terrain, the terrain may cause irregular changes in wind speed and direction, thus affecting the turbine's vibration and tilt state. In this case, displacement, vibration acceleration, tilt angle, and resonance-related parameters may exhibit complex variations. When applying the above formulas, technicians need to pay closer attention to the dynamic changes of these parameters and make appropriate adjustments to the relevant parameters in the formulas (such as the weights of each factor) based on the terrain characteristics. For example, in areas with significant terrain undulations, it may be necessary to increase the weight of the tilt angle's influence on the evaluation function. and This will allow for a more accurate assessment of the wind turbine's stability.

[0088] Furthermore, a logical diagram of the wind turbine stability state evaluation function is drawn, graphically displaying the various factors involved in the function (such as displacement, vibration acceleration, tilt angle, wind speed, resonance, etc.). Arrows are used to indicate the interrelationships and data flow between the factors. For example, the displacement factor is normalized by an error function and then used in calculations with other factors within the function. Simultaneously, the parameters in the function (such as...) are labeled. , , The position and function of (etc.) in the logic diagram help to understand the calculation logic of the wind turbine stability state evaluation function.

[0089] This embodiment provides a method for assessing the stability of a wind turbine. It establishes a comprehensive evaluation system based on nacelle displacement, vibration acceleration, and tilt angle. This system abandons methods relying on single parameters or simple thresholds, fully recognizing the significant impact of these three parameters on wind turbine stability and their complex interrelationships. Through in-depth research into the wind turbine's mechanical structure, dynamic principles, and actual operating data, it determines how to organically combine these three parameters to comprehensively and accurately reflect the wind turbine's stability. For example, the study found that changes in vibration acceleration may cause changes in nacelle displacement, while the nacelle tilt angle, in turn, affects vibration characteristics. Comprehensive consideration of these factors allows for a more accurate grasp of the wind turbine's stability. Furthermore, based on the above... This paper describes a multi-parameter comprehensive evaluation system and constructs a wind turbine stability evaluation function. This function takes wind turbine nacelle displacement, vibration acceleration, and tilt angle as input parameters. Through a series of mathematical operations and logical relationships, it outputs a numerical value that represents the wind turbine's stability state. In the function construction process, a large amount of experimental data and theoretical analysis were used, and each parameter was assigned a reasonable weight to reflect its relative importance in the wind turbine stability evaluation. For example, through statistical analysis of wind turbine operating data under different operating conditions, it was determined that vibration acceleration has a more critical impact on wind turbine stability under certain specific operating conditions. Therefore, it was given a higher weight in the function to ensure that the function output value accurately reflects the actual stability state of the wind turbine.

[0090] This embodiment provides a method for evaluating the stability of a wind turbine, which can be used in the aforementioned terminal equipment. Figure 7 This is a flowchart of a wind turbine stability status assessment method according to an embodiment of the present invention, such as... Figure 7 As shown, the process includes the following steps: Step S701: Collect the raw operating data of the target wind turbine. The raw operating data includes turbine nacelle displacement data, turbine vibration acceleration data, turbine nacelle tilt angle data, wind speed data, and turbine resonance data. For details, please refer to [link to relevant documentation]. Figure 6 Step S601 of the illustrated embodiment will not be described again here.

[0091] Step S702: Perform data preprocessing on the raw operating data of the target wind turbine to obtain preprocessed raw operating data. For details, please refer to [link to relevant documentation]. Figure 6 Step S602 of the illustrated embodiment will not be described again here.

[0092] Step S703: Based on the preprocessed raw operating data, the stability status of the target wind turbine is evaluated using the wind turbine stability status evaluation function to obtain the wind turbine stability evaluation result. For details, please refer to [link to relevant documentation]. Figure 6 Step S603 of the illustrated embodiment will not be described again here.

[0093] Step S704: The stability status of the wind turbine is classified and judged based on the stability assessment results to obtain the stability status of the target wind turbine, and the wind turbine operation strategy is optimized based on the stability status of the target wind turbine.

[0094] Specifically, step S704 above includes: Step S7041: The wind turbine stability assessment result is compared with the first preset threshold, the second preset threshold and the third preset threshold respectively; the first preset threshold is greater than the second preset threshold, and the second preset threshold is greater than the third preset threshold.

[0095] Specifically, The range of values ​​is ,when When the value approaches 0, it indicates that the wind turbine is in excellent stability, all influencing factors are within a very ideal range, and the wind turbine's operational risk is extremely low; as... A gradually increasing value indicates a gradual deterioration in the stability of the wind turbine, potentially leading to problems such as abnormal displacement, excessive vibration, tilt angle deviating from the safe range, encountering extreme winds, or resonance that could affect the stable operation of the wind turbine. This is because the sum of the terms in the denominator... The existence of It will not tend to infinity, but it is relatively large. This indicates that the wind turbine is in a high-risk state and requires immediate inspection and maintenance by operation and maintenance personnel to ensure the safe and stable operation of the wind turbine.

[0096] Furthermore, assuming the first preset threshold is 1, the second preset threshold is 0.8, and the third preset threshold is 0.6; when When the value is between 0.6 and 0.8, it indicates that the fan has encountered some factors that affect its stability, but has not yet reached the level of a serious failure. It is in an unstable state. At this time, although the fan can still run, some factors have deviated from the ideal range. It is necessary to reduce the power and carry out maintenance to prevent the problem from worsening and to ensure that the fan can continue to operate safely. A value less than 0.6 indicates a severe decline in wind turbine stability and the occurrence of a malfunction. This means that multiple influencing factors may have exceeded safe limits, seriously affecting the wind turbine's structure and operation, necessitating immediate shutdown and repair. Otherwise, it could lead to wind turbine damage or even safety accidents, causing significant economic losses and casualties. The above-mentioned classification and value range interpretation provide a clear and scientific basis for wind turbine operation management and maintenance decisions, ensuring stable operation and extending the wind turbine's service life.

[0097] Step S7042: If the wind turbine stability assessment result is less than or equal to the first preset threshold and greater than or equal to the second preset threshold, then the target wind turbine is in a healthy state, and the wind turbine operation strategy is maintained.

[0098] Specifically, when When the target wind turbine is deemed to be in a healthy state, it means that the wind turbine's stability state assessment function calculates that during operation, the nacelle's displacement, vibration acceleration, tilt angle, and the effects of wind speed and resonance are all within a reasonable range, and the various factors are coordinated with each other, resulting in stable overall wind turbine operation. At this time, the wind turbine can operate normally in the current mode and continuously generate electricity stably. The monitoring system continuously records various parameter data, including displacement, vibration acceleration, tilt angle, wind speed, resonance frequency, and amplitude in different directions. This data is not only used for real-time monitoring of the wind turbine's operating status but also provides detailed data support for subsequent operation analysis and performance optimization, so as to promptly identify and prevent potential problems.

[0099] Step S7043: If the stability assessment result of the wind turbine is less than the second preset threshold and greater than or equal to the third preset threshold, the target wind turbine is in an unstable state, the output power of the target wind turbine is reduced, and an alarm message is generated.

[0100] Specifically, if The system determines that the target wind turbine is in an unstable state. This indicates that the wind turbine stability assessment function has detected factors affecting its stability. These factors could include a slight increase in displacement in a certain direction, leading to changes in structural stress; vibration acceleration or tilt angle approaching critical values, indicating an abnormal trend in the wind turbine's operation; or wind speed and resonance affecting the wind turbine to some extent, causing a decrease in overall stability. The wind turbine control system automatically reduces its output power to decrease the operating load of the wind turbine in an unstable state, preventing further deterioration of the problem due to continued high-load operation. Simultaneously, the system issues an alarm to maintenance personnel. The alarm information includes the specific values ​​of various wind turbine parameters, the stability assessment results, and potential problem warnings. Based on the alarm information, maintenance personnel conduct a comprehensive inspection and repair of the wind turbine, checking everything from the tightness of the mechanical structure to the connection status of the electrical system, from the balance of the blades to the verticality of the tower, systematically identifying potential unstable factors and making corresponding adjustments and repairs to restore the wind turbine to a stable operating state.

[0101] Step S7044: If the stability assessment result of the wind turbine is less than the third preset threshold, the target wind turbine is in a fault state and the target wind turbine is stopped from running.

[0102] Specifically, when When a fan malfunctions, it is determined that the target fan has experienced a significant decrease in stability, possibly due to large displacement anomalies leading to structural deformation; or severe vibrations that could damage components; tilt angles exceeding safe limits affecting normal operation; or encountering extreme winds and severe resonance, posing a serious threat to the fan's structure and operational safety. The fan control system immediately initiates an emergency shutdown procedure, halting fan rotation to prevent further damage or safety accidents, such as blade breakage or tower collapse. Maintenance personnel conduct a comprehensive and thorough inspection and repair of the fan, utilizing specialized testing equipment and techniques to thoroughly investigate the cause of the malfunction, from macroscopic structural deformation to microscopic material damage, and from power system failures to control system anomalies. After repairs are completed, the fan is restarted, and a stability assessment is performed again to ensure that all fan parameters return to normal ranges and the stability status assessment function value meets the health status standard before the fan can be put back into normal operation.

[0103] This embodiment provides a wind turbine stability assessment method that can monitor various parameters during wind turbine operation in real time. Based on the wind turbine stability assessment results, it can issue timely warnings before the wind turbine shows signs of instability or failure. When the wind turbine stability assessment result is in the unstable range between a second and a third preset threshold, it automatically reduces the wind turbine output power and simultaneously notifies maintenance personnel for inspection and repair. This allows maintenance personnel to take measures before the wind turbine problem worsens, avoiding problems such as prolonged downtime and aggravated equipment damage caused by wind turbine failure, greatly reducing maintenance costs and production losses. For example, it can issue warnings in advance. The abnormal amplitude of the wind turbine blades due to resonance was promptly adjusted or reinforced to prevent blade breakage and ensure the continuous and stable operation of the wind turbine. Furthermore, accurate stability assessment and timely early warning mechanisms maximize the safety of the wind turbine equipment and surrounding personnel. Specifically, when the wind turbine stability assessment result falls below the third preset threshold, indicating a serious risk of failure, the emergency shutdown procedure is immediately initiated, avoiding potential serious safety accidents such as blade detachment and tower collapse, preventing harm to surrounding personnel, protecting valuable wind turbine equipment assets, and reducing potential major safety hazards and economic losses.

[0104] The following specific embodiment illustrates the specific steps of a wind turbine stability status assessment method.

[0105] Example 1: The specific steps of a method for assessing the stability of a wind turbine include: Step 1: Data Acquisition and Preprocessing 1) Sensor layout and selection concept: To accurately acquire key data during the operation of the target wind turbine, a variety of high-precision sensors are strategically placed on the turbine nacelle: In the stress concentration area connecting the nacelle and the tower, a displacement sensor LK-N100 with nanometer-level precision is installed, capable of accurately sensing displacement changes as low as 10 nanometers and monitoring nacelle displacement from all directions (x, y, z); a vibration acceleration sensor 356A16 with a wide dynamic range and picometer-level resolution is selected, achieving an accuracy of 0.001... The sensors are carefully positioned at the center of mass of the nacelle to ensure accurate capture of various vibration acceleration signals, covering vibrations from low to high frequencies. The tilt angle sensor, RTS02-0.1, boasts ultra-high precision of 0.1 arcseconds and is installed on a precisely calibrated horizontal reference surface on the top of the nacelle to acquire the nacelle's tilt angle relative to the horizontal position in real time. Additionally, a WindSonic ultrasonic anemometer, capable of measuring extreme wind speeds, with a measurement range of up to 75 degrees, is installed on the windward side of the nacelle. Furthermore, fiber optic grating-based resonance monitoring sensors (FBG-RS) are installed at key locations such as the wind turbine blade roots and the middle of the tower. These sensors can accurately detect parameters such as resonance frequency and amplitude, with a frequency resolution of up to 0.01 Hz and an amplitude resolution of up to 1 Hz. .

[0106] 2) Basis for setting the sampling frequency: Considering the different frequency characteristics of the parameters changing during the operation of the target wind turbine, the displacement, vibration acceleration, and tilt angle sensors collect data at a frequency of 100Hz. This frequency can effectively capture the rapid dynamic changes in displacement, vibration, and tilt angle during normal wind turbine operation. The wind speed sensor collects data at a frequency of 20Hz to respond promptly to rapid changes in wind speed, especially in extreme wind conditions, to quickly obtain real-time wind speed information. The resonance monitoring sensor collects data at a frequency of 500Hz to ensure accurate capture of subtle changes in the wind turbine's resonance state, as resonance phenomena are often accompanied by high-frequency parameter fluctuations.

[0107] 3) Data preprocessing: The collected raw data is first passed through an 8th-order elliptic low-pass filter, which effectively filters out high-frequency noise above 50Hz, ensuring data smoothness and making the data more reflective of the actual operating state of the wind turbine. For outlier detection, an isolated forest algorithm is used. This algorithm constructs 50 isolated trees and analyzes the path length of each data point in the tree to score its degree of anomaly. If the anomaly score of a data point exceeds a set threshold (determined through statistical analysis of a large amount of normal operating data, for example, set to 0.8), it is judged as an outlier. Subsequently, a Kalman filter is used to correct the outliers. The Kalman filter predicts the current value based on the physical model of wind turbine operation and the data from the previous moment, and combines the current measurement value to make the optimal estimate, making the data more consistent with the actual operating state of the wind turbine. The preprocessed data will serve as reliable input for subsequent evaluation functions.

[0108] Step 2: Construct the state evaluation function.

[0109] Step 3: Stability state classification judgment: 1) Health status assessment: When When the wind turbine is in a healthy state, it is determined that the displacement, vibration acceleration, tilt angle, wind speed, and resonance effects of the nacelle are all within a reasonable range during operation, and the operation of each component is well coordinated. At this time, the wind turbine can operate normally in the current mode and generate electricity continuously and stably. At the same time, the monitoring system continuously records various parameter data, including displacement, vibration acceleration, tilt angle, wind speed, resonance frequency, and amplitude in different directions, providing detailed data support for subsequent operation analysis and performance optimization.

[0110] 2) Unstable state judgment: If The system determines that the wind turbine is in an unstable state, indicating that factors affecting its stability have emerged. This could be a slight increase in displacement in a certain direction, vibration acceleration or tilt angle approaching critical values, or wind speed and resonance impacting the turbine. The wind turbine control system automatically reduces its output power to decrease the operating load and prevent further deterioration. Simultaneously, the system sends an alarm to maintenance personnel, including the specific values ​​of various turbine parameters, stability assessment results, and potential problem alerts. Maintenance personnel then conduct a comprehensive inspection and repair of the turbine based on the alarm information, checking everything from the tightness of the mechanical structure and the connections of the electrical system to the balance of the blades and the verticality of the tower, systematically identifying and addressing any potential instability factors.

[0111] 3) Fault status judgment: When When a fan malfunctions, it is determined that the fan's stability has severely deteriorated. This could indicate significant abnormal displacement, severe vibration, tilt angles exceeding safe limits, or exposure to extreme winds and severe resonance, posing a serious threat to the fan's structure and operational safety. The fan control system immediately initiates an emergency shutdown procedure, halting the fan's rotation to prevent further damage or safety accidents, such as blade breakage or tower collapse. Maintenance personnel conduct a comprehensive and thorough inspection and repair of the fan, utilizing specialized testing equipment and techniques to investigate everything from macroscopic structural deformation to microscopic material damage, and from power system malfunctions to control system anomalies. After repairs are completed, the fan is restarted, and a stability assessment is performed again to ensure that all fan parameters return to normal ranges and the stability status assessment function value meets the health status standard before the fan can be put back into normal operation.

[0112] Example 2: Under normal operating conditions, the specific steps of a wind turbine stability assessment method include: Step 1: Data Acquisition and Processing: During normal wind turbine operation, data is continuously collected using various sensors (displacement, vibration acceleration, tilt angle, wind speed, resonance monitoring, etc.) at a set acquisition frequency. The collected data undergoes preprocessing, such as removing high-frequency noise using an elliptic low-pass filter and detecting and correcting outliers using the isolated forest algorithm and Kalman filter to ensure data accuracy and reliability. This preprocessed data will be used as input to the formulas.

[0113] Step 2: Formula application: Substitute the processed data into the wind turbine stability state evaluation function. Under normal operating conditions, the wind turbine parameters are relatively stable, the nacelle displacement fluctuates within a small range, the vibration acceleration and tilt angle are also within the normal range, the wind speed does not reach the extreme wind threshold, and the resonance-related parameters also show that the wind turbine has not resonated or the degree of resonance is very weak.

[0114] Step 3: Analysis and Judgment: The calculated wind turbine stability state assessment function value is usually close to 1, indicating high wind turbine stability and a healthy state. For example, if the wind turbine stability state assessment function value is calculated to be 0.9, it means that under the current operating conditions, all components of the wind turbine are operating in good coordination, and the influence of factors such as nacelle displacement, vibration acceleration, tilt angle, wind speed, and resonance on wind turbine stability is within the ideal range. At this time, the wind turbine can operate normally in the current mode and continuously generate electricity stably. Simultaneously, the monitoring system continuously records the data of various parameters, which can be used for subsequent trend analysis to promptly identify potential problems.

[0115] Example 3: When a wind turbine is approaching an unstable state, the specific steps of a wind turbine stability assessment method include: Step 1, Data Characteristics: As the wind turbine's operating time increases or the operating environment gradually changes, some parameters may begin to deviate from the normal range; for example, the nacelle displacement may gradually increase, but has not yet exceeded the safety threshold; the vibration acceleration may occasionally show a high value; the tilt angle may change slightly; the wind speed may approach the extreme wind threshold; resonance-related parameters may show a resonance trend, but have not yet reached a serious level.

[0116] Step 2, Formula Application and Analysis: Similarly, substitute the collected and preprocessed data into the wind turbine stability state evaluation function S. At this point, the calculated S value may be around 0.6. If the value is between 0.8 and 0.7, such as S=0.7, it indicates that the wind turbine has encountered some factors affecting its stability and is in an unstable state. Although the wind turbine can still operate, it needs to be closely monitored and appropriate measures should be taken.

[0117] Step 3, Decision Guidance: Given that the S-value is in an unstable range, the wind turbine control system should automatically reduce its output power to decrease the operating load on the turbine under unstable conditions and prevent further deterioration of the problem. Simultaneously, the system should issue an alarm to maintenance personnel, including the specific values ​​of various turbine parameters, stability assessment results, and potential problem alerts. Maintenance personnel should conduct a comprehensive inspection and repair of the turbine based on the alarm information, focusing on components and systems related to displacement, vibration acceleration, tilt angle, wind speed, and resonance. For example, they should check for loose nacelle support structures, blade imbalances, tower tilting tendencies, wind speed sensor accuracy, and whether resonant components require adjustment. Through these measures, attempts should be made to bring the turbine back to a stable operating state, and changes in the S-value should be continuously monitored.

[0118] Example 4: In the event of a fault warning, the specific steps of a wind turbine stability status assessment method include: Step 1, Data Changes: When the wind turbine faces more severe situations, such as encountering extreme strong winds, increased vibration due to component aging, large displacement or tilt angle exceeding the safe range caused by structural deformation, or obvious resonance, the collected data will show obvious anomalies.

[0119] Step 2, Formula Calculation and Judgment: Substitute the abnormal data into the wind turbine stability status evaluation function S. The calculated S value will be less than 0.6, for example, S=0.5. This clearly indicates that the wind turbine stability has seriously decreased and there is a risk of failure.

[0120] Step 3, Emergency Measures: Once the S-value falls below 0.6, the wind turbine control system should immediately initiate the emergency shutdown procedure to stop the turbine's rotation and prevent potential further damage or safety accidents, such as blade breakage or tower collapse. Maintenance personnel should conduct a comprehensive and thorough inspection and repair of the turbine, utilizing professional testing equipment and techniques to thoroughly investigate the cause of the malfunction, from macroscopic structural deformation to microscopic material damage, and from power system failures to control system anomalies. For example, non-destructive testing techniques should be used to check for cracks in the turbine structure, a vibration analyzer should be used to identify the vibration source, and a level should be used to check the tower's verticality. After repairs are completed, the turbine should be restarted, and a stability assessment should be performed again to ensure that all turbine parameters return to normal ranges and the stability status assessment function value meets the healthy state standard before the turbine can be put back into normal operation.

[0121] In the above embodiments, comprehensive and synchronous monitoring of multiple key factors, such as wind turbine nacelle displacement, vibration acceleration, tilt angle, extreme winds, and wind turbine resonance, is conducted. By deploying various high-precision sensors in the wind turbine nacelle and key components, dynamic data of each factor is acquired in real time, which is the foundation for accurately assessing wind turbine stability. Precise selection and reasonable layout of different types of sensors ensure that the impact of various subtle changes on stability during wind turbine operation can be captured. Based on the collected multi-factor data, a highly complex and scientific wind turbine stability state evaluation function is constructed. This function comprehensively utilizes error functions, inverse hyperbolic tangent functions, exponential functions, and variations of the sigmoid function, among others. A mathematical function quantifies and normalizes various factors, considering their interactions. Through integration and summation, it comprehensively assesses the changes of each factor over a period of time, thereby accurately evaluating the stability of the wind turbine. Dynamic threshold setting and grading are implemented: based on the wind turbine's design parameters, operating characteristics, and historical data, dynamic thresholds are set for the evaluation function, and grading is performed accordingly. Different values ​​within different ranges correspond to different stability states of the wind turbine (healthy, unstable, faulty), providing clear decision-making basis for maintenance personnel. This threshold-based grading mechanism can reflect the actual operating status of the wind turbine in a timely and accurate manner, facilitating the implementation of appropriate measures.

[0122] This embodiment also provides a wind turbine stability assessment device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0123] This embodiment provides a device for evaluating the stability of a wind turbine, such as... Figure 8 As shown, it includes: The data acquisition module 801 is used to acquire the raw operating data of the target wind turbine. The raw operating data of the target wind turbine includes wind turbine nacelle displacement data, wind turbine vibration acceleration data, wind turbine nacelle tilt angle data, wind speed data, and wind turbine resonance data. The data preprocessing module 802 is used to preprocess the raw operating data of the target wind turbine to obtain preprocessed raw operating data; The stability state assessment module 803 is used to assess the stability state of the target wind turbine based on the preprocessed raw operating data and using the wind turbine stability state assessment function to obtain the wind turbine stability assessment result.

[0124] The wind turbine stability assessment device provided in this embodiment of the invention can execute a wind turbine stability assessment method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method. Further functional descriptions of the various modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0125] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0126] The following is a detailed reference. Figure 9 This diagram illustrates a suitable structure for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor 901, such as a central processing unit (CPU), a graphics processing unit (GPU), etc., which can perform various appropriate actions and processes based on programs stored in ROM 902 (read-only memory) or programs loaded from memory 908 into RAM 903 (random access memory). RAM 903 also stores various programs and data required for the operation of the electronic device. The processor 901, ROM 902, and RAM 903 are interconnected via bus 904. An I / O interface 905, i.e., an input / output interface, is also connected to bus 904.

[0127] Typically, the following devices can be connected to I / O interface 905: input devices 906 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 907 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 908 including, for example, magnetic tapes, hard disks, etc.; and communication devices 909. Communication device 909 allows electronic devices to exchange data via wireless or wired communication with other devices. Although Figure 9 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0128] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 909, or installed from a memory 908, or installed from a ROM 902. When the computer program is executed by a processor 901, it performs the functions defined in a wind turbine stability state assessment method according to embodiments of the present invention.

[0129] Figure 9The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0130] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, it implements the wind turbine stability assessment method shown in the above embodiments.

[0131] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0132] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for evaluating the stability status of a wind turbine, characterized in that, The method includes: Collect raw operating data of the target wind turbine; the raw operating data of the target wind turbine includes wind turbine nacelle displacement data, wind turbine vibration acceleration data, wind turbine nacelle tilt angle data, wind speed data and wind turbine resonance data; The raw operating data of the target wind turbine is preprocessed to obtain preprocessed raw operating data; Based on the preprocessed raw operating data, the stability status of the target wind turbine is evaluated using the wind turbine stability status evaluation function to obtain the wind turbine stability evaluation result.

2. The method according to claim 1, characterized in that, The process of preprocessing the raw operating data of the target wind turbine to obtain preprocessed raw operating data includes: High-frequency noise in the raw operating data of the target wind turbine is removed using an elliptic low-pass filter. Anomaly detection is performed on the original operating data after filtering out the high-frequency noise to obtain abnormal operating data; The abnormal operating data is corrected using a Kalman filter to obtain the preprocessed original operating data.

3. The method according to claim 1, characterized in that, Based on the preprocessed raw operating data, the stability status of the target wind turbine is evaluated using a wind turbine stability status evaluation function to obtain the wind turbine stability evaluation result, including: The displacement deviation metric is calculated based on the wind turbine nacelle displacement data, and the wind turbine nacelle displacement data is normalized using an error function to obtain the contribution value of the wind turbine nacelle displacement to the stability of the wind turbine. Based on the wind turbine vibration acceleration data, the vibration acceleration deviation metric is calculated, and the outlier value of the wind turbine vibration acceleration data is filtered using the inverse hyperbolic tangent function to obtain the contribution value of wind turbine vibration acceleration to wind turbine stability. Calculate the tilt and wind speed deviation values ​​based on the wind turbine nacelle tilt angle data and the wind speed data; The wind turbine nacelle tilt angle data and the wind speed data are quantitatively evaluated to obtain the contribution values ​​of the wind turbine nacelle tilt angle and wind speed to the stability of the wind turbine. Calculate resonance and tilt deviation values ​​based on the wind turbine resonance data and the wind turbine nacelle tilt angle data; The wind turbine resonance frequency and amplitude, as well as the wind turbine nacelle tilt angle data, are quantitatively evaluated to obtain the contribution values ​​of wind turbine resonance and tilt angle to wind turbine stability. Obtain the data acquisition time and time scale, and calculate the time decay factor based on the data acquisition time and the time scale; The wind turbine stability assessment result is determined based on the displacement deviation metric, the contribution of the nacelle displacement to the wind turbine stability, the acceleration deviation metric, the contribution of the wind turbine vibration acceleration to the wind turbine stability, the tilt and wind speed deviation metric, the contribution of the nacelle tilt angle and wind speed to the wind turbine stability, the resonance and tilt deviation metric, the contribution of the wind turbine resonance and tilt angle to the wind turbine stability, and the time decay factor.

4. The method according to claim 1, characterized in that, The raw operating data of the target wind turbine collected includes: The raw operating data of the target wind turbine is collected using multiple sensors at a preset acquisition frequency; wherein, the multiple sensors are set at the target location in the wind turbine nacelle.

5. The method according to claim 1, characterized in that, Also includes: The stability status of the wind turbine is classified and judged according to the stability assessment results to obtain the stability status of the target wind turbine, and the wind turbine operation strategy is optimized based on the stability status of the target wind turbine.

6. The method according to claim 5, characterized in that, The step of classifying the stability status of the wind turbine based on the stability assessment results to obtain the stability status of the target wind turbine, and optimizing the wind turbine operation strategy based on the stability status of the target wind turbine, includes: The wind turbine stability assessment results are compared with a first preset threshold, a second preset threshold, and a third preset threshold, respectively; the first preset threshold is greater than the second preset threshold, and the second preset threshold is greater than the third preset threshold. If the wind turbine stability assessment result is less than or equal to the first preset threshold and greater than or equal to the second preset threshold, then the target wind turbine is in a healthy state, and the wind turbine operation strategy is maintained. If the stability assessment result of the wind turbine is less than the second preset threshold and greater than or equal to the third preset threshold, the target wind turbine is in an unstable state, the output power of the target wind turbine is reduced, and an alarm message is generated. If the stability assessment result of the wind turbine is less than the third preset threshold, the target wind turbine is in a fault state and the target wind turbine is stopped from operating.

7. A device for evaluating the stability of a wind turbine, characterized in that, The device includes: The data acquisition module is used to collect the raw operating data of the target wind turbine; the raw operating data of the target wind turbine includes wind turbine nacelle displacement data, wind turbine vibration acceleration data, wind turbine nacelle tilt angle data, wind speed data and wind turbine resonance data; The data preprocessing module is used to preprocess the raw operating data of the target wind turbine to obtain preprocessed raw operating data; The stability status assessment module is used to assess the stability status of the target wind turbine based on the preprocessed raw operating data and using the wind turbine stability status assessment function to obtain the wind turbine stability assessment result.

8. An electronic device, characterized in that, include: A memory and a processor are interconnected, the memory stores computer instructions, and the processor executes the wind turbine stability status assessment method according to any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the wind turbine stability status assessment method according to any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes computer instructions for causing a computer to execute the wind turbine stability status assessment method according to any one of claims 1 to 6.

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