Diagnostic method, device and equipment for wind driven generator tower foundation settlement based on multi-source data fusion and storage medium

Abstract

The invention discloses a diagnosis method, device and equipment for wind driven generator tower foundation settlement based on multi-source data fusion and a storage medium, and relates to the technical field of geological survey, and the method comprises the steps: firstly, obtaining multi-source data such as settlement observation, soil mechanics, meteorology and tower vibration; a fusion evaluation index is determined accordingly; and the foundation settlement condition is diagnosed according to the indexes. Specifically, if the index is smaller than a first threshold value, no settlement is diagnosed; when the index is between the first threshold value and the second threshold value, judging by combining the index change rate, if the change rate is smaller than the threshold value, not settling, otherwise settling; if the index is greater than or equal to the second threshold value, settlement is diagnosed. Obtaining a theoretical total settlement amount, and correcting the theoretical settlement amount by using meteorological data to obtain a corrected theoretical value; the actual total settlement amount is obtained, and the settlement deviation rate is determined; and correcting the first threshold value and the second threshold value according to the settlement deviation rate in combination with the threshold value adjustment coefficient. The method improves the diagnosis accuracy, and provides guarantee for the safe operation of the tower.

Description

Technical Field

[0001] This application relates to the field of geological surveying technology, and in particular to a diagnostic method, apparatus, equipment and storage medium for wind turbine tower foundation settlement based on multi-source data fusion. Background Technology

[0002] As the global energy structure shifts towards clean energy, wind power, as an important means of utilizing renewable energy, continues to see its installed capacity grow. The stability of the foundation of the wind turbine tower, as a key supporting structure, directly affects the safe operation and power generation efficiency of the unit.

[0003] However, under complex geological conditions, long-term loads, and natural environmental factors, tower foundations are prone to settlement. Traditional methods have poor accuracy in diagnosing settlement phenomena in tower foundations. Summary of the Invention

[0004] This application provides a diagnostic method, apparatus, equipment, and storage medium for wind turbine tower foundation settlement based on multi-source data fusion, which can improve the accuracy of diagnosing settlement phenomena occurring on tower foundations.

[0005] To achieve the above objectives, this application adopts the following technical solution: Firstly, this application provides a diagnostic method for wind turbine tower foundation settlement based on multi-source data fusion, including: Acquire multi-source data related to foundation settlement, including settlement observation data, soil mechanics data, meteorological data, and tower vibration data; Based on the settlement observation data, the soil mechanics data, the meteorological data, and the tower vibration data, a fusion evaluation index for foundation settlement is determined; The settlement of the wind turbine tower foundation is diagnosed based on the fusion evaluation indicators.

[0006] Optionally, based on the fusion evaluation indicators, the settlement of the wind turbine tower foundation is diagnosed, including: If the fusion evaluation index is less than the first threshold, it is diagnosed that there is no settlement of the wind turbine tower foundation.

[0007] Optionally, the method further includes: If the fusion evaluation index is greater than or equal to a first threshold and less than a second threshold, the rate of change of the fusion evaluation index is obtained. If the rate of change of the fusion evaluation index is less than the rate of change threshold, it is diagnosed that there is no settlement of the wind turbine tower foundation. Wherein, the first threshold is less than the second threshold.

[0008] Optionally, the method further includes: If the rate of change of the fusion evaluation index is greater than or equal to the rate of change threshold, the existence of the wind turbine tower foundation settlement is diagnosed.

[0009] Optionally, the method further includes: If the fusion evaluation index is greater than or equal to the second threshold, the existence of the wind turbine tower foundation settlement is diagnosed.

[0010] Optionally, the method further includes: Obtain the theoretical total settlement of the foundation; Using the meteorological data, the theoretical total settlement of the foundation settlement is corrected to obtain the corrected theoretical total settlement. Obtain the actual total settlement of the foundation; The settlement deviation rate is determined based on the actual total settlement and the corrected theoretical total settlement. The first threshold and the second threshold are corrected based on the settlement deviation rate.

[0011] Optionally, the step of correcting the first threshold and the second threshold based on the settlement deviation rate includes:

[0012]

[0013] in, The corrected first threshold, The corrected second threshold, The first threshold, The second threshold, This is the threshold adjustment coefficient. This represents the settlement deviation rate.

[0014] Secondly, this application provides a diagnostic device for wind turbine tower foundation settlement based on multi-source data fusion, comprising: The acquisition module is used to acquire multi-source data related to foundation settlement, including settlement observation data, soil mechanics data, meteorological data, and tower vibration data. The determination module is used to determine the integrated evaluation index of foundation settlement based on the settlement observation data, the soil mechanics data, the meteorological data and the tower vibration data; The diagnostic module is used to diagnose the settlement of the wind turbine tower foundation based on the fusion evaluation indicators.

[0015] Thirdly, this application provides a computing device, including a memory and a processor; The memory stores one or more computer programs, the one or more computer programs including instructions; when the instructions are executed by the processor, the computing device performs the method as described in any one of the first aspects.

[0016] Fourthly, this application provides a computer-readable storage medium for storing a computer program for performing the method as described in any one of the first aspects.

[0017] As can be seen from the above technical solution, this application has at least the following beneficial effects: In this application, by integrating settlement observation data, soil mechanics data, meteorological data, and tower vibration data, the limitations of a single data source are overcome. It comprehensively considers multi-dimensional information such as direct settlement performance, foundation soil characteristics, environmental impact, and structural response, providing a more comprehensive and richer basis for diagnosis and significantly improving the quality of basic data for diagnosis.

[0018] Furthermore, by comparing the integrated evaluation indicators with different thresholds and combining the rate of change of the indicators for stratified judgment, a refined distinction of the foundation settlement state is achieved. It can accurately identify normal conditions with no settlement, and promptly detect potential settlement trends and existing settlement phenomena, avoiding misjudgments or omissions caused by the single judgment criteria in traditional diagnosis.

[0019] Furthermore, the theoretical total settlement of the foundation is introduced and corrected using meteorological data. The diagnostic threshold is then dynamically adjusted based on the deviation rate between the actual total settlement and the corrected theoretical value. This allows the threshold to adapt to different geological and meteorological conditions and dynamic changes in foundation settlement, further improving the adaptability and accuracy of the diagnosis. This dynamic correction mechanism ensures that the diagnostic criteria always match the actual situation, making the diagnostic results more consistent with the true settlement state of the wind turbine tower foundation, and providing reliable technical support for ensuring the safe operation and stable power generation of the unit.

[0020] It should be understood that the descriptions of technical features, technical solutions, beneficial effects, or similar language in this application do not imply that all features and advantages can be achieved in any single embodiment. Rather, it is understood that the description of a feature or beneficial effect means that a specific technical feature, technical solution, or beneficial effect is included in at least one embodiment. Therefore, the descriptions of technical features, technical solutions, or beneficial effects in this specification do not necessarily refer to the same embodiment. Furthermore, the technical features, technical solutions, and beneficial effects described in this embodiment can be combined in any suitable manner. Those skilled in the art will understand that embodiments can be implemented without one or more specific technical features, technical solutions, or beneficial effects of a particular embodiment. In other embodiments, additional technical features and beneficial effects may be identified in specific embodiments that do not embody all embodiments. Attached Figure Description

[0021] Figure 1 A flowchart illustrating a diagnostic method for wind turbine tower foundation settlement based on multi-source data fusion, provided for embodiments of this application; Figure 2 A schematic diagram of a diagnostic device for wind turbine tower foundation settlement based on multi-source data fusion, provided for an embodiment of this application; Figure 3 This is a schematic diagram of a computing device provided in an embodiment of this application. Detailed Implementation

[0022] The terms "first," "second," and "third," etc., used in this application specification and accompanying drawings are used to distinguish different objects, not to limit a specific order.

[0023] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0024] To ensure clarity and conciseness in the description of the following embodiments, a brief introduction to the related technologies is given first: Wind turbine tower foundation settlement refers to the vertical subsidence of the foundation upon which the wind turbine tower rests, caused by factors such as its own weight, the load of the upper tower and equipment, changes in geological conditions, and the influence of the natural environment.

[0025] Traditional methods for diagnosing wind turbine tower foundation settlement often rely on a single data source for analysis. For example, they may determine the foundation settlement by setting up settlement observation points and periodically measuring their vertical displacement data; or they may assess the stability of the foundation solely based on the test results of the mechanical parameters of the foundation soil.

[0026] However, traditional methods have significant limitations. Relying solely on displacement data from settlement observation points is insufficient to comprehensively reflect the deformation patterns and stress distribution within the foundation, and is easily affected by the number and location of observation points, leading to incomplete diagnostic results. Furthermore, relying solely on soil mechanical parameters cannot capture the dynamic changes in foundation settlement in real time, failing to meet the need for timely early warning. This is because wind turbine tower foundation settlement is the result of the combined effects of multiple factors, including geological conditions, superstructure loads, and time effects; a single data source cannot encompass the comprehensive impact of these complex factors.

[0027] Traditional methods often use a single threshold or simple judgment criteria, without combining dynamic factors such as the rate of change of indicators for stratified judgment. This makes it difficult to accurately distinguish different degrees of settlement and is prone to misjudgment or omission.

[0028] Traditional diagnostic thresholds are usually fixed, without taking into account the differences in foundation settlement characteristics under different geological and meteorological conditions, and without dynamically correcting the deviation between actual settlement and theoretical calculations. This results in a mismatch between diagnostic criteria and actual conditions, affecting diagnostic accuracy.

[0029] In view of this, this application provides a diagnostic method for wind turbine tower foundation settlement based on multi-source data fusion, which can be executed by a processing device. This processing device can be a terminal or a server. Terminals include, but are not limited to, smartphones, tablets, laptops, personal digital assistants, or smart wearable devices. Servers can be cloud servers, such as central servers in a central cloud computing cluster or edge servers in an edge cloud computing cluster. Alternatively, servers can be located in a local data center. A local data center refers to a data center directly controlled by the user.

[0030] In this method, which addresses the problem of poor accuracy in traditional wind turbine tower foundation settlement diagnosis methods, the invention concept is based on multi-source data fusion. By comprehensively integrating information, optimizing diagnostic logic, and realizing dynamic adjustment, the accuracy and reliability of the diagnosis are improved.

[0031] First, considering that foundation settlement is the result of multiple factors working together, a single data point is insufficient to fully reflect its true state. Therefore, we devised a multi-source data approach, incorporating observational data that directly reflects settlement, mechanical data that reflects soil properties, meteorological data that affects settlement, and vibration data that reflects structural response into the diagnostic system. This approach captures settlement-related information from multiple dimensions, providing a rich data foundation for accurate diagnosis.

[0032] Secondly, to avoid misjudgments or omissions caused by the simplistic logic of traditional diagnostic methods, a hierarchical judgment approach is adopted. This approach is based on the comparison of integrated evaluation indicators with different thresholds, combined with the rate of change of these indicators, to conduct a comprehensive diagnosis. By setting a first threshold and a second threshold, different settlement states are distinguished, and the development trend of settlement is judged based on the rate of change, making the diagnostic results more consistent with the actual situation.

[0033] Finally, considering the differences in foundation settlement characteristics under different geological and meteorological conditions, and the potential discrepancies between theoretical calculations and actual conditions, a dynamic adjustment mechanism is conceived to correct the diagnostic threshold using the settlement deviation rate, ensuring that the diagnostic criteria can adapt to actual changes and further improve the accuracy of the diagnosis.

[0034] To make the technical solution of this application clearer and easier to understand, the following describes, in conjunction with the accompanying drawings, a diagnostic method for wind turbine tower foundation settlement based on multi-source data fusion provided by an embodiment of this application. Figure 2 As shown, this figure is a flowchart of a diagnostic method for wind turbine tower foundation settlement based on multi-source data fusion, provided in an embodiment of this application. The method includes: S201. The processing equipment acquires multi-source data related to foundation settlement, including settlement observation data, soil mechanics data, meteorological data, and tower vibration data.

[0035] Settlement observation data is collected by processing equipment connected to high-precision measuring instruments such as levels and total stations, receiving vertical displacement data from observation points set up around the tower and at different depths in the foundation. This data is the most direct manifestation of foundation settlement, intuitively reflecting the subsidence of the foundation at different locations and depths, and is the basic basis for judging whether settlement has occurred and its extent.

[0036] Soil mechanics data refers to the physical and mechanical parameters of foundation soil obtained by processing equipment through geological exploration methods such as drilling sampling and in-situ testing. These parameters include compression modulus, internal friction angle, and cohesion. This data reflects the bearing capacity and deformation characteristics of the foundation soil itself and is a key factor in analyzing why foundation settlement occurs and its potential. Different soil mechanical properties directly affect the rate and ultimate scale of settlement.

[0037] Meteorological data is obtained by processing equipment through a data interface with local weather stations, acquiring meteorological information such as rainfall, temperature, and wind speed. Meteorological factors indirectly affect foundation settlement. For example, heavy rainfall may increase soil moisture content, reduce soil strength, and accelerate settlement; temperature changes may cause thermal expansion and contraction of the soil, affecting its stability; strong winds may generate additional dynamic loads on the foundation through the tower, indirectly affecting the settlement process. Therefore, meteorological data is an important basis for analyzing the environmental factors affecting settlement.

[0038] Tower vibration data is collected by processing equipment connected to vibration sensors installed at different heights on the tower, receiving the vibration acceleration data they gather. Foundation settlement alters the stress state of the tower structure, leading to changes in its vibration characteristics, such as vibration frequency and amplitude. By acquiring tower vibration data, the stability of the foundation can be indirectly reflected. When foundation settlement occurs, the tower's vibration mode often becomes abnormal, providing a structural response-level reference for settlement diagnosis.

[0039] When acquiring this data, the processing equipment ensures its timeliness and synchronization, collecting various types of data within a similar timeframe to guarantee correlation and comparability between different data sets. This lays a solid foundation for their effective integration in settlement diagnosis. Simultaneously, the equipment performs preliminary format conversion and storage of the data to facilitate subsequent data preprocessing.

[0040] S202. The processing equipment determines the integrated evaluation index of foundation settlement based on settlement observation data, soil mechanics data, meteorological data and tower vibration data.

[0041] The fusion assessment index is a quantitative indicator that comprehensively reflects the foundation settlement state in the diagnosis of wind turbine tower foundation settlement. It is obtained by processing and fusion calculations of multi-source data (including settlement observation data, soil mechanics data, meteorological data and tower vibration data) related to foundation settlement.

[0042] First, the processing equipment will perform targeted preprocessing on the multi-source data to prepare for fusion.

[0043] For settlement observation data, smoothing is used to eliminate random errors and highlight the settlement trend. The formula is:

[0044] in, For the processed first Settlement data at each observation point To resize the movable window, The first in the original settlement observation data Data points.

[0045] For example, if the original settlement data for a certain observation point is [2.1mm, 2.3mm, 2.2mm, 2.5mm, 2.4mm], then a moving window is used. Then the third data point, after processing, becomes:

[0046] Soil mechanics data are normalized to unify parameters of different dimensions into the range [0,1], avoiding interference from different parameter units on the fusion results. The formula is as follows:

[0047] in, For the processed first A soil mechanics data, For the original first A soil mechanics data, This is the minimum value in the soil mechanics data. This represents the maximum value in the soil mechanics data.

[0048] For example, the original data for the soil compression modulus of a certain area are [8MPa, 10MPa, 12MPa, 15MPa], where, It is 8MPa. If the pressure is 15 MPa, then the normalized value of 10 MPa is:

[0049] Outlier handling is performed on meteorological data. If a certain meteorological data... satisfy If it is an outlier, it will be discarded. The mean of the meteorological data. The standard deviation of the meteorological data. The first in the raw meteorological data Data points.

[0050] Example: The rainfall data for a certain region over 10 days is [20mm, 22mm, 21mm, 23mm, 22mm, 21mm, 24mm, 23mm, 22mm, 50mm]. The calculation yields:

[0051]

[0052] in, Indicates the first Rainfall data.

[0053] The outlier condition is not met; if a data point is 55mm, If 55mm is an outlier, it needs to be rejected.

[0054] Spectral analysis was performed on the tower vibration data to extract key characteristic parameters such as the dominant frequency, focusing on vibration information related to foundation settlement. The formula is:

[0055] in, For the first One main frequency, This is the frequency index corresponding to the peak value in the spectrum. The number of sampling points. The sampling interval is defined by the dominant frequency characteristics. These characteristics can more clearly reflect the main components of tower vibration, facilitating subsequent analysis of its relationship with foundation settlement.

[0056] The processing equipment assigns corresponding weights to multi-source data, the magnitude of which depends on the reliability and timeliness of each data point in settlement diagnosis. On one hand, based on historical diagnostic data, data that more accurately reflects the settlement state in the past is given a higher initial weight; for example, settlement observation data, being directly related to settlement, may have a higher initial weight than other data. On the other hand, a time decay factor is introduced to dynamically adjust the weights of data acquired at different times. Recent data, because it better reflects the current settlement state, will have its weight reduced using a decay formula (e.g., weight multiplied by a factor). , The attenuation coefficient is... The time interval has been increased to ensure the sensitivity of the fusion index to the latest settlement changes.

[0057] After preprocessing and weight allocation, the processing equipment multiplies the feature values ​​of the multi-source data by their corresponding weights, then sums them to obtain the fusion evaluation index. For example, if the preprocessed settlement observation data is... Weights are Soil mechanics data are Weights are Meteorological data is Weights are Tower vibration data are Weights are ,and The integration evaluation index is as follows:

[0058] in, To integrate evaluation indicators, The interval between the time when the settlement observation data was acquired and the current time. This represents the interval between the time the soil mechanics data was acquired and the current time. The interval between the time the meteorological data was acquired and the current time. This is the interval between the time the tower vibration data was acquired and the current time.

[0059] This weighted fusion approach integrates multi-dimensional information on direct settlement manifestations, soil characteristics, environmental impacts, and structural responses. It also uses weights to reflect the importance and timeliness of different data, ultimately forming a quantitative indicator that can comprehensively measure the state of foundation settlement, providing an intuitive and reliable basis for subsequent diagnosis.

[0060] S203. The processing equipment diagnoses the settlement of the wind turbine tower foundation based on the integrated evaluation indicators.

[0061] If the fusion evaluation index is less than the first threshold, the diagnosis is that there is no settlement of the wind turbine tower foundation.

[0062] First threshold It is a critical value used to classify the state of foundation settlement risk, and is an important boundary for judging whether there is no settlement risk or potential settlement risk.

[0063] From the perspective of the integrated assessment index, it is a comprehensive quantitative index obtained by preprocessing and weighted fusion of settlement observation data, soil mechanics data, meteorological data, and tower vibration data, which centrally reflects multi-dimensional information related to foundation settlement. If the integrated assessment index... Less than This indicates that the results from multiple data sources point to the following: the current vertical displacement of the foundation is at an extremely low level, the soil mechanical properties are stable, meteorological factors have not had an adverse effect on the stability of the foundation, and the tower vibration has not shown any abnormal pattern caused by settlement.

[0064] Maintain regular monitoring frequency, conducting multi-source data collection and analysis monthly. Regularly inspect the tower and the surrounding environment of the foundation, recording any new influencing factors. Generate a settlement diagnosis report quarterly, archive and save it to provide data support for subsequent trend analysis.

[0065] If the fusion evaluation index is greater than or equal to the first threshold and less than the second threshold, the rate of change of the fusion evaluation index is obtained; if the rate of change of the fusion evaluation index is less than the rate of change threshold, it is diagnosed that there is no settlement of the wind turbine tower foundation; wherein, the first threshold is less than the second threshold.

[0066] When the fusion evaluation index is greater than or equal to the first threshold And less than the second threshold At this time, it is necessary to further determine whether there is settlement of the wind turbine tower foundation by obtaining the rate of change of the integrated assessment indicators. This logic is a refined distinction of settlement risk under critical conditions, which improves the rigor of diagnosis.

[0067] From the perspective of the hierarchical relationship of thresholds, the first threshold It is the dividing line between no settlement risk and potential settlement risk, the second threshold. It is the boundary between potential risks and definite settlement, and and The range between these values ​​falls within the critical risk zone. Fusion assessment indicators falling within this range indicate that the settlement signal reflected by the multi-source data is not yet clear; it is neither stable within an absolutely safe range nor sufficient to determine the existence of settlement. Therefore, conclusions cannot be drawn solely based on the numerical values ​​of the indicators themselves; a dynamic indicator such as the rate of change must be introduced to assist in the judgment.

[0068] The rate of change of the fusion evaluation index is obtained by comparing two consecutive fusion evaluation indices. The ratio of the difference to the time interval is calculated using the following expression:

[0069] in, Indicates the rate of change of the integrated evaluation indicators. For the first The next integration evaluation indicators, For the first The next integration evaluation indicators, The time interval for obtaining data for the two fusion evaluation metrics.

[0070] The rate of change threshold is set based on historical data and engineering experience, and is a critical value used to measure whether the trend of change is significant. When the rate of change is less than the rate of change threshold, it means that although the indicator is in the critical range, it does not show a continuous upward trend. It may be a temporary state caused by short-term data fluctuations or environmental disturbances. The foundation as a whole is still in a relatively stable state. Therefore, it is diagnosed that there is no settlement of the wind turbine tower foundation.

[0071] Increase the monitoring frequency appropriately, conducting multi-source data acquisition and analysis every two weeks, focusing on changes in settlement observation data and tower vibration data. Sampling and testing of the soil around the foundation will analyze changes in soil moisture content, density, and other indicators. Technical personnel will conduct a visual inspection of the tower structure to check for any minor deformations or cracks.

[0072] If the rate of change of the integrated assessment indicators is greater than or equal to the rate of change threshold, a case of wind turbine tower foundation settlement is diagnosed.

[0073] When the rate of change of the fusion assessment index is greater than or equal to the rate of change threshold, it means that the relevant factors of foundation settlement are developing in an unfavorable direction, and the risk of settlement is accumulating. This continuously strengthening trend, even if the current fusion assessment index has not exceeded the second threshold, is enough to indicate that the foundation may have already begun to settle, or that the possibility of settlement is extremely high.

[0074] Therefore, diagnosing foundation settlement under these circumstances is a forward-looking judgment on the settlement trend, which can prompt relevant personnel to take monitoring and preventive measures in advance to avoid further settlement and more serious consequences, reflecting the dynamism and early warning nature of the diagnostic logic.

[0075] For example, the Second , No. Second , ,but:

[0076] If the threshold for the rate of change is set at 0.02, and the rate of change exceeds this threshold, the monitoring frequency needs to be further increased. Multi-source data should be collected and analyzed daily to calculate the daily settlement change. The calculation expression is as follows:

[0077] in, This represents the change in settlement. For the first The settlement value monitored this time, For the first The settlement value monitored this time, This represents the number of monitoring sessions conducted that day. If... If the threshold is exceeded, it must be reported immediately.

[0078] Shallow drilling was conducted on the foundation to obtain more detailed geological structure information, and static cone penetration tests were used to determine the bearing capacity of the foundation. Emergency reinforcement plans were activated, such as using grouting reinforcement technology around the tower foundation, and the formula was used to determine the bearing capacity. Calculate the grouting volume, where For grouting volume, This is the slurry loss coefficient. To reinforce the soil volume, To maintain soil porosity and ensure foundation stability, the tower load should be limited, and the power output of the wind turbine should be appropriately reduced according to the settlement trend to avoid exacerbating foundation settlement due to excessive load.

[0079] If the fusion assessment index is greater than or equal to the second threshold, a case of wind turbine tower foundation settlement is diagnosed.

[0080] When the integrated assessment index is greater than or equal to the second threshold, it means that the settlement observation data has shown a significant subsidence trend, the soil mechanics data reflects a decrease in soil bearing capacity and an increase in deformation, the meteorological data may indicate the continued effect of adverse environmental factors, and the tower vibration data may also show abnormal vibration patterns caused by settlement. These multi-dimensional pieces of information together prove that the foundation settlement phenomenon has actually occurred and has reached a level that requires serious attention and specific countermeasures.

[0081] This diagnostic result has strong practical guiding significance. It clearly indicates to relevant personnel that foundation settlement has become a reality, and the operation of the wind turbines must be stopped immediately. A safety warning zone must be established, and unauthorized personnel must be prohibited from approaching. Real-time monitoring of foundation settlement and tower tilt is crucial, with multi-source data collected hourly to analyze settlement trends. A professional construction team should be organized to carry out emergency reinforcement measures, such as using pile foundation underpinning technology. By calculating the bearing capacity and settlement of the piles, the number and arrangement of piles can be determined to quickly improve the bearing capacity of the foundation.

[0082] The method also includes: First, obtain the theoretical total settlement of the foundation.

[0083] The theoretical total settlement is the expected settlement calculated using classical soil mechanics formulas based on the physical and mechanical properties of the foundation soil, such as compression modulus and layer thickness. The calculation expression is:

[0084] in, This represents the theoretical total settlement. This represents the total number of soil layers. Add pressure to the foundation, For the first Soil compression modulus For the first By combining the thickness of each soil layer with parameters from soil mechanics data, the total potential settlement of the foundation under ideal conditions can be obtained. This value reflects the settlement potential based on the inherent properties of the soil and serves as a theoretical benchmark for judging whether actual settlement is abnormal.

[0085] By using meteorological data, the theoretical total settlement of the foundation is corrected to obtain the corrected theoretical total settlement.

[0086] Meteorological factors (such as rainfall) can significantly affect the physical state of foundation soil. For example, increased moisture content reduces soil strength and accelerates settlement. Therefore, theoretical values ​​need to be corrected using meteorological data. For instance, meteorological influence coefficients can be obtained by fitting historical data. The corrected theoretical total settlement is:

[0087] in, This represents the corrected theoretical total settlement. The meteorological impact coefficient. For the first The ratio of the rainfall at any given time to the historical average rainfall.

[0088] This step incorporates dynamic environmental factors into the theoretical calculations, making the revised theoretical values ​​closer to actual working conditions.

[0089] Next, the actual total settlement of the foundation is obtained. The actual total settlement is the cumulative settlement value directly obtained from settlement observation data. This is calculated by processing equipment by integrating vertical displacement data from observation points around the tower and at different depths in the foundation. For example, a weighted average of the settlement data from multiple observation points (the weights are set based on the representativeness of the observation points) is taken to obtain the actual total settlement reflecting the overall foundation condition. This value reflects the actual settlement of the foundation and serves as a practical basis for verifying the accuracy of theoretical calculations.

[0090] The settlement deviation rate is determined based on the actual total settlement and the corrected theoretical total settlement.

[0091] Settlement deviation rate is used to quantify the difference between actual settlement and corrected theoretical settlement. The calculation formula is as follows:

[0092] in, Settlement deviation rate This represents the actual total settlement. For example, if the actual total settlement is 85mm, and the corrected theoretical total settlement is 80.3mm, then:

[0093] The larger the settlement deviation rate, the worse the fit between the theoretical model and the actual situation. This deviation needs to be compensated by adjusting the deviation rate threshold.

[0094] The first and second thresholds are corrected based on the settlement deviation rate.

[0095] When the deviation rate exceeds a preset deviation rate threshold, for example, a preset deviation rate threshold of 5%, corrections are required using a first threshold and a second threshold, including:

[0096]

[0097] in, The corrected first threshold, The corrected second threshold, The first threshold, The second threshold, This is the threshold adjustment coefficient. This represents the settlement deviation rate.

[0098] For example, if =1, =0.5, =5.85%, then the corrected first threshold is:

[0099] This correction mechanism ensures that the threshold is dynamically adjusted according to the deviation between theory and reality, so that the diagnostic criteria are always synchronized with the actual settlement characteristics of the foundation and avoid misjudgment caused by model rigidity.

[0100] Based on the above description, this application has the following beneficial effects: In this application, by integrating settlement observation data, soil mechanics data, meteorological data, and tower vibration data, the limitations of a single data source are overcome. It comprehensively considers multi-dimensional information such as direct settlement performance, foundation soil characteristics, environmental impact, and structural response, providing a more comprehensive and richer basis for diagnosis and significantly improving the quality of basic data for diagnosis.

[0101] Furthermore, by comparing the integrated evaluation indicators with different thresholds and combining the rate of change of the indicators for stratified judgment, a refined distinction of the foundation settlement state is achieved. It can accurately identify normal conditions with no settlement, and promptly detect potential settlement trends and existing settlement phenomena, avoiding misjudgments or omissions caused by the single judgment criteria in traditional diagnosis.

[0102] Furthermore, the theoretical total settlement of the foundation is introduced and corrected using meteorological data. The diagnostic threshold is then dynamically adjusted based on the deviation rate between the actual total settlement and the corrected theoretical value. This allows the threshold to adapt to different geological and meteorological conditions and dynamic changes in foundation settlement, further improving the adaptability and accuracy of the diagnosis. This dynamic correction mechanism ensures that the diagnostic criteria always match the actual situation, making the diagnostic results more consistent with the true settlement state of the wind turbine tower foundation, and providing reliable technical support for ensuring the safe operation and stable power generation of the unit.

[0103] The above text combined Figure 1 The diagnostic method for wind turbine tower foundation settlement based on multi-source data fusion provided in this application embodiment is described in detail below. The device and equipment provided in this application embodiment will be described in conjunction with the accompanying drawings.

[0104] like Figure 2 As shown in the figure, this is a schematic diagram of a diagnostic device for wind turbine tower foundation settlement based on multi-source data fusion provided in an embodiment of this application. The device includes: The acquisition module 301 is used to acquire multi-source data related to foundation settlement, including settlement observation data, soil mechanics data, meteorological data and tower vibration data; The determination module 302 is used to determine the integrated evaluation index of foundation settlement based on the settlement observation data, the soil mechanics data, the meteorological data and the tower vibration data; The diagnostic module 303 is used to diagnose the settlement of the wind turbine tower foundation based on the fusion evaluation index.

[0105] The diagnostic module 303 is specifically used to diagnose the absence of settlement of the wind turbine tower foundation when the fusion evaluation index is less than the first threshold.

[0106] The diagnostic module 303 is further configured to: obtain the rate of change of the fusion evaluation index when the fusion evaluation index is greater than or equal to a first threshold and the fusion evaluation index is less than a second threshold; and diagnose that there is no settlement of the wind turbine tower foundation when the rate of change of the fusion evaluation index is less than a rate of change threshold; wherein the first threshold is less than the second threshold.

[0107] The diagnostic module 303 is also used to diagnose the existence of the wind turbine tower foundation settlement when the rate of change of the fusion evaluation index is greater than or equal to the rate of change threshold.

[0108] The diagnostic module 303 is also used to diagnose the existence of the wind turbine tower foundation settlement when the fusion evaluation index is greater than or equal to the second threshold.

[0109] The acquisition module 301 is also used to acquire the theoretical total settlement of the foundation settlement; The determining module 302 is also used to use the meteorological data to correct the theoretical total settlement of the foundation settlement, so as to obtain the corrected theoretical total settlement. The acquisition module 301 is also used to acquire the actual total settlement of the foundation settlement; The determining module 302 is further configured to determine the settlement deviation rate based on the actual total settlement and the corrected theoretical total settlement; and to correct the first threshold and the second threshold based on the settlement deviation rate.

[0110] The determining module 302 is specifically used to correct the first threshold and the second threshold based on the settlement deviation rate, including:

[0111]

[0112] in, The corrected first threshold, The corrected second threshold, The first threshold, The second threshold, This is the threshold adjustment coefficient. This represents the settlement deviation rate.

[0113] The diagnostic device for wind turbine tower foundation settlement based on multi-source data fusion according to the embodiments of this application can correspond to the execution of the method described in the embodiments of this application, and the other operations and / or functions of each module / unit of the diagnostic device for wind turbine tower foundation settlement based on multi-source data fusion are respectively for implementing Figure 1 For the sake of brevity, the corresponding processes of each method in the illustrated embodiments will not be described in detail here.

[0114] This application also provides a computing device. For example... Figure 3 As shown in the figure, this is a schematic diagram of a computing device provided in an embodiment of this application. The computing device 700 includes a bus 701, a processor 702, a communication interface 703, and a memory 704. The processor 702, the memory 704, and the communication interface 703 communicate with each other via the bus 701.

[0115] The 701 bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0116] The processor 702 can be any one or more of the following processors: central processing unit (CPU), graphics processing unit (GPU), microprocessor (MP), or digital signal processor (DSP).

[0117] The communication interface 703 is used for communication with external devices.

[0118] Memory 704 may include volatile memory, such as random access memory (RAM). Memory 704 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0119] The memory 704 stores executable code, and the processor 702 executes the executable code to perform the aforementioned diagnostic method for wind turbine tower foundation settlement based on multi-source data fusion.

[0120] Specifically, in achieving Figure 2 In the case of the illustrated embodiment, and Figure 2 When the modules or units of the diagnostic device for wind turbine tower foundation settlement based on multi-source data fusion described in the embodiments are implemented in software, the following steps are performed: Figure 2 The software or program code required for the functions of each module / unit can be partially or entirely stored in memory 704. Processor 702 executes the program code corresponding to each unit stored in memory 704, and executes the aforementioned diagnostic method for wind turbine tower foundation settlement based on multi-source data fusion.

[0121] This application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that a computing device can store, or a data storage device such as a data center containing one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive). The computer-readable storage medium includes instructions that instruct the computing device to execute the aforementioned diagnostic method for wind turbine tower foundation settlement based on multi-source data fusion.

[0122] This application also provides a computer program product comprising one or more computer instructions. When the computer instructions are loaded and executed on a computing device, all or part of the processes or functions described in this application are generated.

[0123] The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, or data center to another website, computer, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0124] When the computer program product is executed by a computer, the computer performs any of the aforementioned diagnostic methods for wind turbine tower foundation settlement based on multi-source data fusion. The computer program product can be a software installation package; when any of the aforementioned diagnostic methods for wind turbine tower foundation settlement based on multi-source data fusion is required, the computer program product can be downloaded and executed on the computer.

[0125] The descriptions of the processes or structures corresponding to the above figures each have their own emphasis. For parts of a process or structure that are not described in detail, please refer to the relevant descriptions of other processes or structures.

[0126] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be covered within the scope of protection of this application.

Claims

1. A diagnostic method for wind turbine tower foundation settlement based on multi-source data fusion, characterized in that, The method includes: Acquire multi-source data related to foundation settlement, including settlement observation data, soil mechanics data, meteorological data, and tower vibration data; Based on the settlement observation data, the soil mechanics data, the meteorological data, and the tower vibration data, a fusion evaluation index for foundation settlement is determined; The settlement of the wind turbine tower foundation is diagnosed based on the fusion evaluation indicators.

2. The method according to claim 1, characterized in that, Based on the aforementioned fusion evaluation indicators, the settlement of the wind turbine tower foundation is diagnosed, including: If the fusion evaluation index is less than the first threshold, it is diagnosed that there is no settlement of the wind turbine tower foundation.

3. The method according to claim 2, characterized in that, The method further includes: If the fusion evaluation index is greater than or equal to a first threshold and less than a second threshold, the rate of change of the fusion evaluation index is obtained. If the rate of change of the fusion evaluation index is less than the rate of change threshold, it is diagnosed that there is no settlement of the wind turbine tower foundation. Wherein, the first threshold is less than the second threshold.

4. The method according to claim 3, characterized in that, The method further includes: If the rate of change of the fusion evaluation index is greater than or equal to the rate of change threshold, the existence of the wind turbine tower foundation settlement is diagnosed.

5. The method according to claim 3, characterized in that, The method further includes: If the fusion evaluation index is greater than or equal to the second threshold, the existence of the wind turbine tower foundation settlement is diagnosed.

6. The method according to claim 5, characterized in that, The method further includes: Obtain the theoretical total settlement of the foundation; Using the meteorological data, the theoretical total settlement of the foundation settlement is corrected to obtain the corrected theoretical total settlement. Obtain the actual total settlement of the foundation; The settlement deviation rate is determined based on the actual total settlement and the corrected theoretical total settlement. The first threshold and the second threshold are corrected based on the settlement deviation rate.

7. The method according to claim 6, characterized in that, The step of correcting the first threshold and the second threshold based on the settlement deviation rate includes: in, The corrected first threshold, The corrected second threshold, The first threshold, The second threshold, This is the threshold adjustment coefficient. This represents the settlement deviation rate.

8. A diagnostic device for wind turbine tower foundation settlement based on multi-source data fusion, characterized in that, The device includes: The acquisition module is used to acquire multi-source data related to foundation settlement, including settlement observation data, soil mechanics data, meteorological data, and tower vibration data. The determination module is used to determine the integrated evaluation index of foundation settlement based on the settlement observation data, the soil mechanics data, the meteorological data and the tower vibration data; The diagnostic module is used to diagnose the settlement of the wind turbine tower foundation based on the fusion evaluation indicators.

9. A computing device, characterized in that, Including memory and processor; The memory stores one or more computer programs, the one or more computer programs including instructions; when the instructions are executed by the processor, the computing device performs the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program for performing the method as described in any one of claims 1 to 7.

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