Wind driven generator blade clearance monitoring method, device, equipment and medium

Abstract

The invention relates to a wind driven generator blade clearance monitoring method and device, equipment and a medium. The method comprises the steps that multi-source state data of a wind driven generator are acquired; determining a clearance safety margin index according to the multi-source state data; when the clearance safety margin index is smaller than a preset warning threshold value, a dangerous state is judged, a propeller retracting instruction or an emergency shutdown instruction is executed, and a root diagnosis result of insufficient clearance is generated based on the multi-source state data. Thus, according to the method, the multi-source state data are fused, the clearance safety margin index is determined, accurate perception, intelligent diagnosis and active prevention and control of the clearance risk of the wind turbine generator are achieved, and the safety and reliability of operation of the generator are remarkably improved.

Description

Technical Field

[0001] This application relates to the technical field of safety monitoring of wind power generation equipment, and in particular to a method, device, equipment and medium for monitoring the clearance of wind turbine blades. Background Technology

[0002] During the operation of wind turbine generators, the clearance between the blade rotation trajectory and the tower, ground, and surrounding obstacles is a core indicator for ensuring the safe operation of the equipment. Insufficient clearance can easily lead to serious accidents such as blade sweeping, blade tip impact, and structural fracture, causing not only significant economic losses but also potentially endangering the safety of on-site personnel. Systematic analysis has identified the following five main causes of abnormal clearance: (1) Settlement or displacement of tower foundation: Due to defects in foundation construction quality, reduction of bearing capacity of foundation soil, changes in groundwater or geological disasters, the tower foundation may experience vertical settlement or horizontal displacement, which in turn causes the entire tower to tilt, significantly compressing the safe distance between the blade rotation envelope and the tower. (2) Blade deformation or fatigue damage: Under the influence of long-term alternating wind load, diurnal temperature stress, sand and dust erosion and lightning strikes, the blades are prone to structural damage such as bending, twisting, leading edge cracking or composite material delamination, which causes the actual rotation trajectory to deviate from the design path and encroach on the original clearance margin. (3) Hub or main shaft misalignment: factors such as main shaft bearing wear, hub connecting bolt loosening, transmission chain assembly deviation or flange surface deformation can cause the hub to drive the three blades to move spatially as a whole, especially if they are continuously close to the tower in a certain position, creating a local clearance risk. (4) Changes in the wind farm environment: After the wind farm is put into operation, new structures, excessively grown trees or other foreign objects may appear within the airspace. The intrusion of these foreign objects will significantly reduce the actual distance between the blades and external obstacles, constituting a highly concealed airspace hazard. (5) Impact of extreme weather events: Strong gusts, high turbulence intensity or severe convective weather can cause the blades to bear loads exceeding the design load in a short period of time, resulting in severe elastic deformation and instantaneous breach of the conventional aerodynamic and structural safety margins, causing temporary but high-risk airspace shortages.

[0003] To address the aforementioned risks, existing technologies have proposed several clean air monitoring solutions. For example, one solution uses millimeter-wave radar to track and measure the movement of the blade tip. However, due to the small size of the blade tip, the long distance, and the ease with which it is blocked by the nacelle structure, the effective echo signal is weak, making it difficult to guarantee measurement stability and accuracy. Another solution is to indirectly calculate blade deformation based on blade root strain gauges. Although this can reflect some mechanical states, it cannot directly identify blade surface defects or external environmental obstacles.

[0004] However, existing airspace monitoring technologies still have the following significant shortcomings, making it difficult to meet the full-scenario safety protection needs under complex operating conditions: Single sensing dimension: Most solutions rely on only a single sensor, such as radar, strain gauge or camera, which has a limited coverage and cannot simultaneously capture multiple factors such as mechanical structure status, environmental changes and operating conditions, resulting in monitoring blind spots. Lack of multi-source fault correlation analysis: Existing systems generally focus on superficial judgments of whether the clearance distance exceeds the limit, without establishing a mapping relationship with root causes of faults such as loose bolts, spindle misalignment, and foundation settlement, which leads to a significant increase in troubleshooting costs; Insufficient environmental adaptability and measurement accuracy: Vision-based solutions experience a sharp decline in performance under low visibility conditions such as rain, snow, fog, and dust storms; while industrial-grade displacement or tilt sensors are susceptible to factors such as temperature drift, electromagnetic interference, and weak lightning protection, resulting in severe data drift during long-term operation and making it difficult to support high-reliability decision-making. Passive alarms and lack of proactive intervention capabilities: Most systems only have data acquisition and threshold alarm functions, and do not achieve closed-loop linkage with the wind turbine main control system. They cannot automatically trigger protective actions such as pitch control, feathering, or emergency shutdown when the airspace risk reaches a critical state. The response is lagging and the safety protection effect is limited. Summary of the Invention

[0005] In view of the above-mentioned problems of the prior art, this application provides a method, device, equipment and medium for monitoring the airspace clearance of wind turbine blades. By integrating multi-source status data, this application determines the airspace safety margin index, realizes accurate perception, intelligent diagnosis and active prevention and control of airspace risks of wind turbine units, and significantly improves the safety and reliability of unit operation.

[0006] To achieve the above objectives, the first aspect of this application provides a method for monitoring the air clearance of wind turbine blades, comprising: Acquire multi-source state data of the wind turbine, the multi-source state data including: Real-time images of the blades and tower are acquired by visual monitoring equipment installed on the top of the tower or in the nacelle, and the clearance distance is calculated based on image processing algorithms. The unit's operating parameters, including wind speed and impeller vibration amplitude, are obtained in real time through the SCADA system interface. The real-time spatial position of the wheel hub is obtained by using an inertial measurement unit (IMU) or a laser displacement sensor to calculate the wheel hub offset. The real-time height of the tower foundation is obtained by installing tilt sensors or GPS displacement sensors at the tower foundation to calculate the displacement of the tower top caused by settlement. Based on the multi-source status data, determine the airspace safety margin index; When the airspace safety margin index is less than the preset warning threshold, it is determined to be a dangerous state, and a paddle retraction command or an emergency stop command is executed. Based on the multi-source status data, a root cause diagnosis result of insufficient airspace is generated.

[0007] Thus, this application integrates multi-source status data collected from visual monitoring equipment, SCADA systems, inertial measurement units or laser displacement sensors, and tilt sensors or GPS displacement sensors, achieving comprehensive coverage and collaborative perception of the main causes of airspace anomalies. This multi-dimensional collaborative monitoring mechanism effectively overcomes the problems of coverage blind spots, poor environmental adaptability, and insufficient measurement accuracy caused by relying on a single sensor in existing technologies. Furthermore, based on multi-source status data, an airspace safety margin index is constructed, which can not only assess the current airspace risk level but also automatically trigger active protection commands such as propeller retraction or emergency shutdown when the airspace safety margin index falls below a preset warning threshold. The resulting closed-loop linkage mechanism of "perception-assessment-execution" upgrades this application from a traditional passive alarm mode to an intelligent safety system with active early warning and autonomous protection capabilities, significantly improving response timeliness and operational reliability, thereby effectively preventing major safety accidents such as blade sweeping and blade tip impact, and ensuring the safe and stable operation of wind turbine units.

[0008] As one possible implementation of the first aspect, the hub offset is determined by the following formula:

[0009] in, This is the wheel hub offset. As the reference position, , For real-time location, , The aging factor is... This refers to the actual running time. For design lifespan.

[0010] Thus, by introducing a "time offset benchmark" correction mechanism, that is, at the benchmark position... Medium superimposed aging coefficient Ratio of running time dynamic factors ( This method enables adaptive assessment of hub offset. It fully considers the minor structural offsets caused by natural aging factors such as material fatigue and loose connections during long-term operation of wind turbines, thus avoiding, to a certain extent, the frequent false alarms that occur in traditional fixed-benchmark judgment methods during the middle to late stages of equipment service.

[0011] As one possible implementation of the first aspect, the tower top displacement is determined by the following formula:

[0012] in, This is the displacement at the top of the tower. As the initial reference elevation, For real-time altitude, The coupling coefficient is... This is the cumulative value of the maximum spindle offset within each historical monitoring period. , The effective offset peak value in the t-th period. This refers to the maximum cumulative peak displacement that the spindle's materials and structure can withstand within its design life.

[0013] Thus, by incorporating the cumulative effect of the main shaft impact load, this formula constructs an adaptive safety assessment model that not only considers the actual height variation of the tower foundation but also comprehensively reflects the impact of the impact load and its cumulative effect on the foundation settlement during long-term operation of the main shaft. This method significantly improves the scientific rigor, accuracy, and engineering practicality of wind turbine structural health monitoring, providing reliable technical support for early identification of potential settlement risks and prevention of structural safety accidents.

[0014] As one possible implementation of the first aspect, the safety margin index is determined by the following formula:

[0015] in, For safety margin index, Net air risk coefficient, This refers to the clearance distance. For the minimum allowable clearance distance, This is the wind speed amplification factor. For real-time wind speed, This is the wheel hub offset. The maximum allowable offset, This is the displacement at the top of the tower. To design the maximum allowable settlement, The amplitude of vibration. This is the coupling amplification factor. This refers to the actual running time. For design lifespan.

[0016] Thus, this invention innovatively proposes an assessment formula for airspace safety margin. This formula weights and integrates directly measured airspace distance with key indirect influencing factors such as wind speed, hub offset, tower settlement, vibration amplitude, and equipment lifespan to calculate a comprehensive safety index, thereby achieving a leap from traditional single-threshold alarm to multi-factor collaborative and dynamic risk assessment.

[0017] As one possible implementation of the first aspect, it also includes: When the airspace safety margin index is greater than or equal to the preset safety threshold, it is determined to be in a safe state, and the monitoring command for the next cycle is executed. When the airspace safety margin index is greater than the preset safety threshold and less than or equal to the preset warning threshold, it is determined to be a warning state and a warning command is executed.

[0018] In this way, implementing a tiered response to the airspace safety margin index not only enables continuous monitoring under safe conditions but also provides timely warnings when risks first emerge without interrupting operation. In dangerous situations, it rapidly triggers proactive protection measures, thus balancing the stability and safety of the unit's operation. This mechanism effectively avoids the crude control logic of "either normal or shut down" under the traditional binary alarm mode, significantly improving the wind turbine's early identification, process control, and emergency protection capabilities against airspace risks.

[0019] As one possible implementation of the first aspect, the multi-source state data further includes: vibration signals of the bolt area collected by vibration sensors installed at the blade root bolts, and blade images and ground images acquired by visual monitoring equipment installed at the top of the tower or the nacelle. The process of generating a root cause diagnosis result for insufficient airspace based on the multi-source status data includes: Based on the multi-source state data and the preset fault rule base, a root cause diagnosis result of insufficient clearance is generated; the root cause diagnosis result includes at least one of the following: loose blade root bolts, blade structure damage, foreign object intrusion into the clearance, hub misalignment, tower foundation settlement, and extreme weather effects.

[0020] Traditional monitoring methods typically rely on a single sensor outputting a clearance distance value. When this value falls below a threshold, only a general alarm for insufficient clearance is issued, failing to differentiate between structural faults, external interference, and temporary weather disturbances. This forces maintenance personnel to spend considerable time on-site troubleshooting. In contrast, this application, based on intelligent matching analysis of multi-source status data and a pre-defined fault rule base, automatically and accurately identifies the root cause of insufficient clearance, achieving a closed loop from risk perception to root cause diagnosis. This significantly shortens fault location time and improves maintenance efficiency.

[0021] As one possible implementation of the first aspect, it also includes: pushing the root cause diagnosis results, trigger time, clearance distance, safety margin index, and executed paddle recovery command or emergency shutdown command to the remote operation and maintenance terminal.

[0022] In this way, maintenance personnel can grasp the complete context information of wind turbine airspace abnormality events in real time on the remote maintenance terminal without being on-site. This includes when it occurred, the degree of risk, what measures have been taken, and the most likely root cause. This allows them to quickly determine whether to dispatch a maintenance team, adjust the operation strategy, or activate the emergency plan, significantly shortening the decision-making process.

[0023] To achieve the above objectives, a second aspect of this application provides a wind turbine blade clearance monitoring device, comprising: The acquisition unit is used to acquire multi-source state data of the wind turbine generator, the multi-source state data including: Real-time images of the blades and tower are acquired by visual monitoring equipment installed on the top of the tower or in the nacelle, and the clearance distance is calculated based on image processing algorithms. The unit's operating parameters, including wind speed and impeller vibration amplitude, are obtained in real time through the SCADA system interface. The real-time spatial position of the wheel hub is obtained by using an inertial measurement unit (IMU) or a laser displacement sensor to calculate the wheel hub offset. The real-time height of the tower foundation is obtained by installing tilt sensors or GPS displacement sensors at the tower foundation to calculate the displacement of the tower top caused by settlement. The determining unit is used to determine the airspace safety margin index based on the multi-source status data. The execution unit is used to determine a dangerous state when the airspace safety margin index is less than a preset warning threshold, execute a paddle retraction command or an emergency stop command, and generate a root cause diagnosis result of insufficient airspace based on the multi-source status data.

[0024] To achieve the above objectives, a third aspect of this application provides a computing device, comprising: processor, and A memory storing program instructions that, when executed by the processor, cause the processor to perform the blade clearance monitoring method described in any of the first aspects above.

[0025] To achieve the above objectives, a fourth aspect of this application provides a computer-readable storage medium having program instructions stored thereon, which, when executed by a computer, cause the computer to implement the blade clearance monitoring method described in any of the first aspects above. Attached Figure Description

[0026] Figure 1 This is a flowchart of the main steps of a wind turbine blade clearance monitoring method provided in this application; Figure 2 This is a flowchart of the method of Embodiment 1 provided in this application; Figure 3This is a structural schematic diagram of a wind turbine blade clearance monitoring device provided in this application; Figure 4 This is a structural schematic diagram of a computing device provided in this application; It should be understood that the dimensions and shapes of the blocks in the above structural diagrams are for reference only and should not constitute an exclusive interpretation of the embodiments of the present invention. The relative positions and inclusion relationships between the blocks presented in the structural diagrams are only schematic representations of the structural relationships between the blocks, and are not intended to limit the physical connection methods of the embodiments of the present invention. Detailed Implementation

[0027] The technical solutions provided in this application will be further described below with reference to the accompanying drawings and embodiments. It should be understood that the system architecture and business scenarios provided in the embodiments of this application are mainly for illustrating possible implementations of the technical solutions of this application and should not be construed as the sole limitation on the technical solutions of this application. Those skilled in the art will recognize that the technical solutions provided in this application are equally applicable to similar technical problems as system architectures evolve and new business scenarios emerge.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. In case of any inconsistency, the meaning set forth in this specification or derived from the content described herein shall prevail. Furthermore, the terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit the scope of this application.

[0029] 1) SCADA (Supervisory Control and Data Acquisition) system: The wind turbine generator sets establish a communication interface with the system to read the key operating parameters generated by the generator sets during operation in real time.

[0030] This application provides a method for monitoring the clearance of wind turbine blades, such as... Figure 1 As shown, it includes: S101. Obtain multi-source state data of the wind turbine generator, wherein the multi-source state data includes: Real-time images of the blades and tower are acquired by visual monitoring equipment installed on the top of the tower or in the nacelle, and the clearance distance is calculated based on image processing algorithms. The unit's operating parameters, including wind speed and impeller vibration amplitude, are obtained in real time through the SCADA system interface. The real-time spatial position of the wheel hub is obtained by using an inertial measurement unit (IMU) or a laser displacement sensor to calculate the wheel hub offset. The real-time height of the tower foundation is obtained by installing tilt sensors or GPS displacement sensors at the tower foundation to calculate the displacement of the tower top caused by settlement. S102. Determine the airspace safety margin index based on the multi-source status data; S103. When the clearance safety margin index is less than the preset warning threshold, it is determined to be a dangerous state, and the paddle retraction command or emergency stop command is executed. Based on the multi-source status data, the root cause diagnosis result of insufficient clearance is generated.

[0031] Thus, this application integrates multi-source status data collected from visual monitoring equipment, SCADA systems, inertial measurement units or laser displacement sensors, and tilt sensors or GPS displacement sensors, achieving comprehensive coverage and collaborative perception of the main causes of airspace anomalies. This multi-dimensional collaborative monitoring mechanism effectively overcomes the problems of coverage blind spots, poor environmental adaptability, and insufficient measurement accuracy caused by relying on a single sensor in existing technologies. Furthermore, based on multi-source status data, an airspace safety margin index is constructed, which can not only assess the current airspace risk level but also automatically trigger active protection commands such as propeller retraction or emergency shutdown when the airspace safety margin index falls below a preset warning threshold. The resulting closed-loop linkage mechanism of "perception-assessment-execution" upgrades this application from a traditional passive alarm mode to an intelligent safety system with active early warning and autonomous protection capabilities, significantly improving response timeliness and operational reliability, thereby effectively preventing major safety accidents such as blade sweeping and blade tip impact, and ensuring the safe and stable operation of wind turbine units.

[0032] In some embodiments, the hub offset is determined by the following formula:

[0033] in, This is the wheel hub offset. As the reference position, , For real-time location, , The aging factor is... This refers to the actual running time. For design lifespan.

[0034] One point to note is that the above formula uses [a specific location] as the reference position. Introducing "time offset benchmark" ( This reflects the natural hub misalignment caused by factors such as material fatigue and loose connections during long-term operation of the wind turbine. Specifically, The aging factor is typically set within the range of 0.05 to 0.1 based on the design life requirements of the unit, but it can also be calibrated based on statistical data from actual wind farm operation. Simultaneously, it represents the ratio of actual operating time to the design life. Incorporating the baseline calculation allows the permissible offset range to be dynamically adjusted as the equipment's lifespan deteriorates.

[0035] For example, when the unit has reached 50% of its design life ( When α = 0.5 and α = 0.1, the corrected reference position will become 1 + 0.1 × 0.5 = 1.05 times the original reference, that is, the allowable offset range is widened by about 5%; if α is a higher value or the running time is longer, the tolerance can be further increased to 10% or even more.

[0036] Thus, by introducing a "time offset benchmark" correction mechanism, that is, at the benchmark position... Medium superimposed aging coefficient Ratio of running time dynamic factors ( This method enables adaptive assessment of hub offset. It fully considers the minor structural offsets caused by natural aging factors such as material fatigue and loose connections during long-term operation of wind turbines, thus avoiding, to a certain extent, the frequent false alarms that occur in traditional fixed-benchmark judgment methods during the middle to late stages of equipment service.

[0037] In some embodiments, the tower top displacement is determined by the following formula:

[0038] in, This is the displacement at the top of the tower. As the initial reference elevation, For real-time altitude, The coupling coefficient is... This is the cumulative value of the maximum spindle offset within each historical monitoring period. , The effective offset peak value in the t-th period. This refers to the maximum cumulative peak displacement that the spindle's materials and structure can withstand within its design life.

[0039] It should be noted that settlement issues cannot be considered solely based on geological conditions; the long-term dynamic impact loads on the wind turbine's main shaft must also be taken into account. The more frequent and intense the impacts, the more prone the foundation is to fatigue or accelerated settlement, thus the safety tolerance for settlement should be correspondingly reduced. To scientifically reflect this engineering reality, this scheme incorporates the coupling effect of the "main shaft impact load" into the settlement calculation formula.

[0040] Specifically, It represents the sum of the maximum peak values ​​of spindle offset recorded in each monitoring cycle since commissioning, reflecting the cumulative intensity of the impact on the spindle; This indicates the maximum cumulative peak offset that the main shaft structure can safely withstand within the design life of the unit; it is a design parameter provided by the manufacturer. This represents an empirical coupling coefficient, typically ranging from 0.3 to 0.5, used to adjust the degree of influence of the main shaft impact on the foundation settlement tolerance. It can be calibrated based on actual wind farm data.

[0041] As can be seen from the above formula, the reference height is obtained by using the square root term. Dynamic corrections are performed to ensure that the calculated tower top displacement is accurate. It not only reflects actual geometric changes but also implicitly includes the "equivalent risk amplification" effect brought about by the history of principal axis impact. With... The increase of , the decrease of the value inside the square root, leads to the corrected value Compressed, thus It more sensitively reflects potential dangers.

[0042] Thus, by incorporating the cumulative effect of the main shaft impact load, this formula constructs an adaptive safety assessment model that not only considers the actual height variation of the tower foundation but also comprehensively reflects the impact of the impact load and its cumulative effect on the foundation settlement during long-term operation of the main shaft. This method significantly improves the scientific rigor, accuracy, and engineering practicality of wind turbine structural health monitoring, providing reliable technical support for early identification of potential settlement risks and prevention of structural safety accidents.

[0043] In some embodiments, the safety margin index is determined by the following formula:

[0044] in, For safety margin index, Net air risk coefficient, This refers to the clearance distance. For the minimum allowable clearance distance, This is the wind speed amplification factor. For real-time wind speed, This is the wheel hub offset. The maximum allowable offset, This is the displacement at the top of the tower. To design the maximum allowable settlement, The amplitude of vibration. This is the coupling amplification factor. This refers to the actual running time. For design lifespan.

[0045] Specifically, The typical range is 1.2 to 1.6. The typical range is 0.01~0.03. The typical range is 0.5 to 0.8; when When the time is right, it automatically becomes negative; The relative offset value of the main axis; The relative value of the basic settlement; In the above formula, This is a coupling term that, by normalizing the two physical quantities separately before multiplying them, effectively eliminates the coupling distortion problem that may occur when the two quantities have the same dimensions but different engineering scales or numerical ranges. When =0.5 ,and =0.5 In this case, the contribution of the coupling term is 0.5 * 0.5 * ξ = 0.25ξ; instead of directly using the product of absolute values, such as 0.5 *0.5 The latter, due to the difference in physical magnitude, is difficult to reflect the true relative risk level. More importantly, this design can accurately characterize the nonlinear risk amplification effect generated when hub offset and tower settlement simultaneously approach their limits: for example, when both reach 80% of their respective allowable values, the coupling term contribution is 0.8*0.8*ξ=0.64ξ, compared to only... Reaching 80% If the value is close to zero (or vice versa), the coupling term approaches zero and contributes almost nothing to the overall risk assessment. This means that a significant risk penalty is only imposed when both hazard factors are present and at high levels. Therefore, this coupling term causes the overall safety margin index to decrease much more significantly under "dual-high" conditions than under "single-high" conditions, thus more accurately reflecting the combined safety threat posed by the combined compression of clearance by offset and settlement, and effectively improving the ability to identify and warn of high-risk conditions.

[0046] Thus, this invention innovatively proposes an assessment formula for airspace safety margin. This formula weights and integrates directly measured airspace distance with key indirect influencing factors such as wind speed, hub offset, tower settlement, vibration amplitude, and equipment lifespan to calculate a comprehensive safety index, thereby achieving a leap from traditional single-threshold alarm to multi-factor collaborative and dynamic risk assessment.

[0047] In some embodiments, it also includes: When the airspace safety margin index is greater than or equal to the preset safety threshold, it is determined to be in a safe state, and the monitoring command for the next cycle is executed. When the airspace safety margin index is greater than the preset safety threshold and less than or equal to the preset warning threshold, it is determined to be a warning state and a warning command is executed.

[0048] In this way, implementing a tiered response to the airspace safety margin index not only enables continuous monitoring under safe conditions but also provides timely warnings when risks first emerge without interrupting operation. In dangerous situations, it rapidly triggers proactive protection measures, thus balancing the stability and safety of the unit's operation. This mechanism effectively avoids the crude control logic of "either normal or shut down" under the traditional binary alarm mode, significantly improving the wind turbine's early identification, process control, and emergency protection capabilities against airspace risks.

[0049] In some embodiments, the multi-source state data further includes: vibration signals of the bolt area collected by vibration sensors installed at the blade root bolts, and blade images and ground images acquired by visual monitoring equipment installed at the top of the tower or the nacelle; The process of generating a root cause diagnosis result for insufficient airspace based on the multi-source status data includes: Based on the multi-source state data and the preset fault rule base, a root cause diagnosis result of insufficient clearance is generated; the root cause diagnosis result includes at least one of the following: loose blade root bolts, blade structure damage, foreign object intrusion into the clearance, hub misalignment, tower foundation settlement, and extreme weather effects.

[0050] Specifically, the root cause diagnosis process is achieved through intelligent matching analysis of multi-source state data and a pre-set fault rule base. This rule base pre-integrates feature patterns and causal logic for various typical insufficient airspace scenarios. A specific example will be provided below.

[0051] Example 1: Vibration signals from the bolt area are acquired in real time, and frequency characteristics are extracted using spectral analysis (such as Fast Fourier Transform, FFT). These characteristics are then compared with a pre-stored reference spectrum under normal conditions. If a significant deviation is detected, such as a characteristic frequency shift exceeding a threshold or the appearance of abnormal harmonics, it is determined that the bolt is at risk of loosening. Example 2: If the blade image is obtained through visual monitoring equipment and the blade surface is found to have twisting, cracks, peeling of adhesive layer or traces of lightning ablation, it is determined to be blade structural damage; Example 3: If a ground image is obtained through visual monitoring equipment and a moving or static foreign object, such as a crane boom or fallen vegetation, is detected near the tower, causing a sudden drop in the clearance distance, then it is diagnosed as a foreign object intruding into the clearance. Example 4: When the IMU or laser displacement sensor detects that the wheel hub spatial position continuously deviates from the initial reference, and the direction of the deviation is consistent with the direction of the reduction in clearance, it is determined to be wheel hub misalignment. Example 5: If the tilt sensor or GPS data shows that the overall tilt of the tower or the displacement of the tower top exceeds the allowable threshold after life aging correction, it is determined to be tower foundation settlement; Example 6: When the wind speed is extremely high and the impeller vibration amplitude is huge, resulting in a temporary reduction in the clearance distance, it is determined to be the impact of extreme weather.

[0052] Traditional monitoring methods typically rely on a single sensor outputting a clearance distance value. When this value falls below a threshold, only a general alarm for insufficient clearance is issued, failing to differentiate between structural faults, external interference, and temporary weather disturbances. This forces maintenance personnel to spend considerable time on-site troubleshooting. In contrast, this application, based on intelligent matching analysis of multi-source status data and a pre-defined fault rule base, automatically and accurately identifies the root cause of insufficient clearance, achieving a closed loop from risk perception to root cause diagnosis. This significantly shortens fault location time and improves maintenance efficiency.

[0053] In some embodiments, the method further includes: pushing the root cause diagnosis results, trigger time, clearance distance, safety margin index, executed paddle recovery command or emergency shutdown command to a remote operation and maintenance terminal.

[0054] In this way, maintenance personnel can grasp the complete context information of wind turbine airspace abnormality events in real time on the remote maintenance terminal without being on-site. This includes when it occurred, the degree of risk, what measures have been taken, and the most likely root cause. This allows them to quickly determine whether to dispatch a maintenance team, adjust the operation strategy, or activate the emergency plan, significantly shortening the decision-making process.

[0055] To more clearly illustrate the above method, this application provides a specific embodiment, combined with... Figure 2 As shown.

[0056] Step 1: Obtain multi-source status data of the wind turbine, including clearance distance, wind speed, rotor vibration amplitude, hub offset and tower top displacement. Specifically, methods for obtaining clearance distance can include, but are not limited to, the following: To achieve real-time monitoring of the clearance distance between wind turbine blades and the tower, two calibrated high-definition cameras (or infrared cameras for nighttime or inclement weather) can be installed side-by-side on the top of the nacelle or the upper part of the tower, forming a binocular vision system. During wind turbine operation, the two cameras simultaneously capture images including the blade tips and the tower surface. Image processing algorithms identify the position of the blade tips at the same moment in the left and right images respectively, and calculate the pixel offset between these two positions, called "parallax." Based on the principle of binocular vision, given the distance between the two cameras (baseline length) and the lens focal length, the depth distance from the blade tip to the camera can be calculated using the following formula: Depth distance = (Focal length × Baseline length) / Parallax. Meanwhile, the tower's position is fixed, and its corresponding spatial position in the image can be predetermined through calibration during installation. Combining the three-dimensional position of the blade tip and the spatial position of the tower surface, the shortest distance between them can be directly calculated, which is the current clearance distance.

[0057] Wind speed can be obtained directly through the SCADA system interface, usually from a standard anemometer on the top of the nacelle.

[0058] For impeller vibration amplitude, it is preferred to read it directly from the unit's existing SCADA system; if the SCADA system is not configured to monitor this, a vibration sensor is added at the blade root to collect the impeller vibration amplitude.

[0059] The hub offset is obtained in real time through an inertial measurement unit or laser displacement sensor installed near the hub or spindle, and then combined with the formula. Perform the calculation.

[0060] The tower top displacement is monitored by tilt sensors or high-precision GPS displacement sensors deployed at the tower foundation to detect changes in the overall tilt or settlement of the tower, combined with the formula. Perform the calculation.

[0061] In addition, the multi-source condition data also includes: vibration signals from the bolt area collected by vibration sensors installed at the blade root bolts, and blade images and ground images acquired by visual monitoring equipment installed on the top of the tower or in the nacelle. These are used for subsequent analysis and diagnosis.

[0062] Specifically, in addition to calculating clearance distance, the visual monitoring equipment can simultaneously monitor the blade surface condition and the surrounding environment of the wind turbine. Specifically, high-definition or infrared cameras capture image details of the blade surface while recording the blade tip's movement trajectory. Through image recognition algorithms, such as edge detection, texture analysis, or deep learning models, it can determine whether the blade has defects such as cracks, delamination, lightning damage, or leading-edge corrosion. If structural damage to the blade surface, such as obvious cracks, is identified, the subsequent diagnostic module can output a fault cause of "blade structural damage" as one of the potential causes of clearance anomalies. Simultaneously, the visual monitoring equipment can also monitor environmental changes around the wind turbine, such as excessively tall trees near the tower, temporarily piled large objects, newly constructed structures, or other external obstacles. These external factors may intrude into the blade's rotation envelope, reducing the effective clearance distance. When the system detects such environmental interference, it can be marked as a "foreign object intrusion into clearance" risk and incorporated into the clearance safety assessment system.

[0063] Step 2: Based on the obtained clearance distance, wind speed, impeller vibration amplitude, hub offset, and tower top displacement, use the formula... Calculate the safety margin index; Step 3: Determine the airspace status of the unit based on the calculated airspace safety margin index S. Specifically: when the airspace safety margin index is greater than or equal to the preset safety threshold, it is determined to be in a safe state, and the monitoring instruction for the next cycle is executed, that is, return to step 1; When the airspace safety margin index is greater than the preset safety threshold but less than or equal to the preset warning threshold, a warning state is declared, and a warning instruction is executed, indicating that the safety margin has decreased and requires closer attention, but emergency control is not implemented at this time. When the airspace safety margin index is less than the preset warning threshold, it is determined to be a dangerous state.

[0064] Step 4: When a dangerous situation is determined, the system executes the following two actions in parallel: First, generate and send a pitch reduction or emergency shutdown signal, and force the main controller of the unit to change the pitch angle or cut off the power, so that the wind turbine can quickly get out of the high-risk operating state and avoid the blades from colliding with the tower.

[0065] Second, while issuing control commands, the system quickly analyzes the most likely cause of insufficient airspace by matching multi-source status data with the built-in fault rule base.

[0066] For example: if If the limit is significantly exceeded, the diagnosis is "wheel hub misalignment".

[0067] If the bolt sensor signal is abnormal and the vibration spectrum is specific, the diagnosis is "loose leaf root bolt".

[0068] If the visual monitoring equipment detects cracks on the blade surface, it is diagnosed as "blade structural damage".

[0069] If SCADA displays extremely high wind speeds and large impeller amplitudes, the diagnosis is "severe weather impact".

[0070] like If the increase continues, the diagnosis is "tower foundation settlement / displacement".

[0071] If the vision system detects a foreign object entering the clearance area of ​​the blade, it is diagnosed as "foreign object entering the clearance area".

[0072] Step 5: Generate a detailed alarm and diagnostic report, including the trigger time, real-time headroom value, safety margin index S, executed control actions, and the root cause diagnosed.

[0073] The report is simultaneously pushed to the handheld devices of wind farm maintenance personnel and the central control room via audible and visual alarms, workstation screens, and remote networks, guiding them to conduct subsequent precise inspections and repairs.

[0074] Step 6: After completing all the above steps, the system will not stop, but will wait for a preset period and then automatically return to Step 1 to start a new round of data collection and monitoring, thus forming a 24 / 7 uninterrupted closed-loop intelligent safety protection network to ensure the lifelong safe operation of the wind turbine.

[0075] This application provides a wind turbine blade clearance monitoring device 300, such as... Figure 3 As shown, it includes: Acquisition unit 301 is used to acquire multi-source state data of a wind turbine generator, the multi-source state data including: Real-time images of the blades and tower are acquired by visual monitoring equipment installed on the top of the tower or in the nacelle, and the clearance distance is calculated based on image processing algorithms. The unit's operating parameters, including wind speed and impeller vibration amplitude, are obtained in real time through the SCADA system interface. The real-time spatial position of the wheel hub is obtained by using an inertial measurement unit (IMU) or a laser displacement sensor to calculate the wheel hub offset. The real-time height of the tower foundation is obtained by installing tilt sensors or GPS displacement sensors at the tower foundation to calculate the displacement of the tower top caused by settlement. The determining unit 302 is used to determine the airspace safety margin index based on the multi-source status data; The execution unit 303 is used to determine a dangerous state when the airspace safety margin index is less than a preset warning threshold, execute a paddle retraction command or an emergency stop command, and generate a root cause diagnosis result of insufficient airspace based on the multi-source status data.

[0076] Figure 4 This is a structural schematic diagram of a computing device 600 provided in an embodiment of this application. The computing device performs the methods described above, such as... Figure 4 As shown, the computing device 600 includes: a processor 610, a memory 620, and a communication interface 630.

[0077] It should be understood that Figure 4 The communication interface 630 in the computing device 600 shown can be used to communicate with other devices, and may specifically include one or more transceiver circuits or interface circuits.

[0078] The processor 610 can be connected to the memory 620. The memory 620 can be used to store the program code and data. Therefore, the memory 620 can be a storage unit inside the processor 610, an external storage unit independent of the processor 610, or a component that includes both the storage unit inside the processor 610 and the external storage unit independent of the processor 610.

[0079] Optionally, the computing device 600 may also include a bus. The memory 620 and communication interface 630 can be connected to the processor 610 via the bus. The bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 The symbol is represented by a line without an arrow, but this does not mean that there is only one bus or one type of bus.

[0080] It should be understood that in the embodiments of this application, the processor 610 may be a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor. Alternatively, the processor 610 may employ one or more integrated circuits to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0081] The memory 620 may include read-only memory and random access memory, and provides instructions and data to the processor 610. A portion of the processor 610 may also include non-volatile random access memory. For example, the processor 610 may also store device type information.

[0082] When the computing device 600 is running, the processor 610 executes computer execution instructions stored in the memory 620 to perform any of the operational steps of the above method and any of the optional embodiments thereof.

[0083] It should be understood that the computing device 600 according to the embodiments of this application can correspond to the corresponding subject in executing the methods according to the various embodiments of this application, and the above and other operations and / or functions of each module in the computing device 600 are respectively for implementing the corresponding processes of the methods of this embodiment. For the sake of brevity, they will not be described in detail here.

[0084] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0085] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0086] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0087] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0088] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0089] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0090] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, is used to perform the above-described method, which includes at least one of the schemes described in the above embodiments.

[0091] The computer storage medium in this application embodiment can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0092] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0093] The program code contained on a computer-readable medium may be transmitted using any suitable medium, including, but not limited to, wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0094] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0095] Furthermore, the terms "first, second, third, etc." or similar terms such as module A, module B, and module C used in the specification and claims are only used to distinguish similar objects and do not represent a specific ordering of objects. It is understood that, where permissible, a specific order or sequence may be interchanged so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0096] In the above description, the labels of the steps involved, such as S110, S120, etc., do not mean that the steps will necessarily be executed. The order of the steps can be interchanged or executed simultaneously if permitted.

[0097] The term "comprising" as used in the specification and claims should not be construed as limiting itself to what follows; it does not exclude other elements or steps. Therefore, it should be interpreted as specifying the presence of the mentioned feature, integral, step, or component, but does not exclude the presence or addition of one or more other features, integrals, steps, or components, or groups thereof. Thus, the statement "device comprising means A and B" should not be limited to a device consisting solely of components A and B.

[0098] The terms "an embodiment" or "an embodiment" as used in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in at least one embodiment of this application. Therefore, the terms "in one embodiment" or "in an embodiment" appearing throughout this specification do not necessarily refer to the same embodiment, but may refer to the same embodiment. Furthermore, in one or more embodiments, the particular features, structures, or characteristics can be combined in any suitable manner, as will be apparent to those skilled in the art from this disclosure.

[0099] Note that the above are merely preferred embodiments and the technical principles employed in this application. Those skilled in the art will understand that this application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of this application, all of which fall within the scope of protection of this application.

Claims

1. A method for monitoring the clearance of wind turbine blades, characterized in that, include: Acquire multi-source state data of the wind turbine, the multi-source state data including: Real-time images of the blades and tower are acquired by visual monitoring equipment installed on the top of the tower or in the nacelle, and the clearance distance is calculated based on image processing algorithms. The unit's operating parameters, including wind speed and impeller vibration amplitude, are obtained in real time through the SCADA system interface. The real-time spatial position of the wheel hub is obtained by using an inertial measurement unit (IMU) or a laser displacement sensor to calculate the wheel hub offset. The real-time height of the tower foundation is obtained by installing tilt sensors or GPS displacement sensors at the tower foundation to calculate the displacement of the tower top caused by settlement. Based on the multi-source status data, determine the airspace safety margin index; When the airspace safety margin index is less than the preset warning threshold, it is determined to be a dangerous state, and a paddle retraction command or an emergency stop command is executed. Based on the multi-source status data, a root cause diagnosis result of insufficient airspace is generated.

2. The method as described in claim 1, characterized in that, The hub offset is determined by the following formula: ； in, This is the wheel hub offset. As the reference position, , For real-time location, , The aging factor is... This refers to the actual running time. For design lifespan.

3. The method as described in claim 1, characterized in that, The displacement at the top of the tower is determined by the following formula: ； in, This is the displacement at the top of the tower. As the initial reference elevation, For real-time altitude, The coupling coefficient is... This is the cumulative value of the maximum spindle offset within each historical monitoring period. , The effective offset peak value in the t-th period. This refers to the maximum cumulative peak displacement that the spindle's materials and structure can withstand within its design life.

4. The method as described in claim 1, characterized in that, The safety margin index is determined by the following formula: ； in, For safety margin index, Net air risk coefficient, This refers to the clearance distance. For the minimum allowable clearance distance, This is the wind speed amplification factor. For real-time wind speed, This is the wheel hub offset. The maximum allowable offset, This is the displacement at the top of the tower. To design the maximum allowable settlement, The amplitude of vibration. This is the coupling amplification factor. This refers to the actual running time. For design lifespan.

5. The method as described in claim 1, characterized in that, Also includes: When the airspace safety margin index is greater than or equal to the preset safety threshold, it is determined to be in a safe state, and the monitoring command for the next cycle is executed. When the airspace safety margin index is greater than the preset safety threshold and less than or equal to the preset warning threshold, it is determined to be a warning state and a warning command is executed.

6. The method as described in claim 1, characterized in that, The multi-source status data also includes: vibration signals in the bolt area collected by vibration sensors installed at the blade root bolts, and blade images and ground images obtained by visual monitoring equipment installed at the top of the tower or the nacelle; The process of generating a root cause diagnosis result for insufficient airspace based on the multi-source status data includes: Based on the multi-source state data and the preset fault rule base, a root cause diagnosis result of insufficient clearance is generated; the root cause diagnosis result includes at least one of the following: loose blade root bolts, blade structure damage, foreign object intrusion into the clearance, hub misalignment, tower foundation settlement, and extreme weather effects.

7. The method as described in claim 6, characterized in that, Also includes: The root cause diagnosis results, trigger time, clearance distance, safety margin index, and executed paddle recovery or emergency shutdown commands are pushed to the remote operation and maintenance terminal.

8. A wind turbine blade clearance monitoring device, characterized in that, include: The acquisition unit is used to acquire multi-source state data of the wind turbine generator, the multi-source state data including: Real-time images of the blades and tower are acquired by visual monitoring equipment installed on the top of the tower or in the nacelle, and the clearance distance is calculated based on image processing algorithms. The unit's operating parameters, including wind speed and impeller vibration amplitude, are obtained in real time through the SCADA system interface. The real-time spatial position of the wheel hub is obtained by using an inertial measurement unit (IMU) or a laser displacement sensor to calculate the wheel hub offset. The real-time height of the tower foundation is obtained by installing tilt sensors or GPS displacement sensors at the tower foundation to calculate the displacement of the tower top caused by settlement. The determining unit is used to determine the airspace safety margin index based on the multi-source status data. The execution unit is used to determine a dangerous state when the airspace safety margin index is less than a preset warning threshold, execute a paddle retraction command or an emergency stop command, and generate a root cause diagnosis result of insufficient airspace based on the multi-source status data.

9. A computing device, characterized in that, include: processor, and A memory having stored program instructions that, when executed by the processor, cause the processor to perform the blade clearance monitoring method according to any one of claims 1-7.

10. A storage medium, characterized in that, It stores program instructions, which, when executed by a computer, cause the computer to perform the blade clearance monitoring method according to any one of claims 1-7.

Images