A method of wind turbine blade leading edge erosion assessment and related apparatus

Abstract

This invention provides a method and related apparatus for assessing leading-edge erosion of wind turbine blades, belonging to the technical field of wind turbine blade reliability assessment. The method includes: acquiring meteorological data of the wind turbine to be assessed; discretizing the wind turbine blade along its spanwise direction into multiple blade element micro-segments; calculating a bidirectional coupling correction factor for each rainfall event recorded at each blade element micro-segment based on the instantaneous surface morphology of the wind turbine blade; calculating the Miner total cumulative damage variable based on this correction factor, and then calculating the aerodynamic coefficient after damage; calculating the aerodynamic torque based on the aerodynamic coefficient, and then calculating the equivalent annual power generation loss rate, ultimately determining the degree of erosion attenuation of the wind turbine. This invention quantifies the bidirectional coupling mechanism of rain and sand by introducing a liquid resistance-solid buffer attenuation factor and a solid-promoting liquid-water hammer amplification factor, and achieves phased determination of the latency period and mass loss period based on Miner linear cumulative damage, enabling efficient and accurate assessment of the time-varying impact of blade leading-edge erosion on annual power generation.

Description

Technical Field

[0001] This invention belongs to the technical field of wind turbine blade reliability assessment, specifically relating to a method and related apparatus for assessing leading-edge erosion of wind turbine blades. Background Technology

[0002] As the global wind power industry develops towards larger scales and extends to deep-sea and complex inland terrains (such as the Gobi Desert and arid land), the rotor diameter of megawatt-class and above wind turbines is continuously increasing. The linear velocity of the airfoil section near the blade tip increases significantly. Under extremely high relative impact velocities, multiphase flow erosion damage caused by liquid raindrops and solid sand particles in the air on the blade leading edge has become an engineering bottleneck restricting blade lifespan and the economic benefits of wind farms. Once leading-edge erosion develops, it disrupts the smooth aerodynamic shape initially designed for the blade, causing increased surface roughness, leading-edge passivation, and crack propagation. This leads to a significant decrease in the airfoil lift coefficient and a sharp increase in the drag coefficient, resulting in a severe loss of annual power generation from the wind turbine. Therefore, predicting the degree of erosion at the leading edge of wind turbine blades in complex rain and sand environments has significant engineering value.

[0003] Current research and engineering applications on raindrop and aeolian erosion at the leading edge of blades typically employ computational fluid dynamics simulations or empirical formulas based on single physics fields for evaluation. High-mechanism models based on damage mechanics such as Springer, water hammer stress, Finnie, and Oka erosion can explain the evolution mechanisms of rain erosion and aeolian erosion, and assess erosion or fatigue damage in pure droplet or pure aeolian environments. However, when faced with complex meteorological conditions of aeolian erosion accompanied by rainfall, existing technologies simply perform a "linear superposition" of the calculation results from two independent models. This fails to consider the significant viscous damping and buffering effect of the water film formed by rainfall at the blade leading edge on subsequent solid sand impacts, and neglects the micro-jet and stress concentration phenomena caused by sand impact stress and micro-cutting leading to increased blade surface roughness, resulting in micro-jets during subsequent raindrop impacts. The lack of a quantitative standard for the bidirectional coupling mechanism of "water film buffering" and "roughness stress amplification" leads to a significant discrepancy between the predicted joint erosion life and actual measurements of decommissioned wind turbine blades.

[0004] Modern wind turbine blades are typically covered with viscoelastic protective coatings such as polyurethane. In actual operation, when exposed to raindrops or sandstorms, the surface material doesn't begin to be lost immediately; instead, there's a lengthy microcrack initiation stage. During this stage, raindrops and sandstorms also exert coupled erosive effects. Only after the erosion reaches a latency threshold does the crack propagation and mass loss stage begin. However, current technologies typically assume a constant erosion rate, failing to consider damage stages based on cumulative fatigue criteria and the dynamic changes in erosion damage, leading to biased estimates of aerodynamic performance degradation. Engineering focuses more on the future annual power generation reduction of wind turbines, while current research often stops at calculating the final erosion depth or the static final lift-to-drag ratio change.

[0005] Therefore, there is an urgent need for a high-efficiency calculation process for wind turbine leading-edge erosion assessment that can take into account the bidirectional coupling mechanism of rain and sand, and an assessment method that reflects the time-varying characteristics of damage. Summary of the Invention

[0006] The purpose of this invention is to provide a method and related apparatus for assessing leading-edge erosion of wind turbine blades, addressing the technical problems of existing technologies that neglect the rain-sand coupling effect, lack latent mechanical determination, and suffer from low computational efficiency. This invention provides an interpretable, reproducible, and practical assessment method for rapidly evaluating blade erosion and making operation and maintenance decisions in wind farms, without requiring high-fidelity simulations or damage data throughout the entire life cycle of wind turbine blades. This breaks down the engineering barriers from microscopic multiphase flow impacts to macroscopic wind farm power generation losses.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows: In a first aspect, the present invention provides a method for assessing leading-edge erosion of wind turbine blades, comprising the following steps: Obtain meteorological data for the wind turbine to be evaluated, including multiple rainfall event data records; The wind turbine blades of the wind turbine unit to be evaluated are discretized along the spanwise direction into multiple blade element micro-segments; Based on the instantaneous morphology of the wind turbine blade surface, the bidirectional coupling correction factor corresponding to each rain event data record at each blade element micro-segment is calculated; Based on the obtained bidirectional coupling correction factor, the Miner total cumulative damage variable corresponding to each leaf element microsegment for each rain event data record is calculated. The aerodynamic coefficients at each leaf element microsegment after damage were calculated based on the total cumulative damage variable of Miner. Calculate the aerodynamic torque at each leaf element microsegment based on the obtained aerodynamic coefficients after damage; The equivalent annual power generation loss rate of the wind turbine to be evaluated is calculated based on the obtained aerodynamic torque. The degree of erosion and degradation of the wind turbine to be evaluated is determined based on the obtained equivalent annual power generation loss rate.

[0008] Preferably, based on the instantaneous morphology of the wind turbine blade surface, the bidirectional coupling correction factor for each rain event data record at each blade element micro-segment is calculated. Specifically, the method is as follows: Each rainfall event data record includes each time step. Corresponding rainfall Average particle size of wind-blown sand and average wind speed ; Based on time step Corresponding rainfall Calculate the rainfall intensity corresponding to each rainfall event data record; Based on average wind speed Calculate the corresponding number of rain event data records in the first... The transient relative impact velocity of the leading edge of a leaf element microsegment; Based on the obtained rainfall intensity and leading-edge transient relative impact velocity, the water film thickness in each leaf element microsegment corresponding to each rainfall event data record is calculated. Based on the water film thickness and the instantaneous morphology of the wind turbine blade surface, the bidirectional coupling correction factor corresponding to each rain event data record at each blade element micro-segment is calculated. The bidirectional coupling correction factor includes a liquid resistance-solid buffer attenuation factor and a solid-promote-liquid-water hammer amplification factor.

[0009] Preferably, the liquid-solid buffer attenuation factor is calculated using the following formula:

[0010] in, For the first Liquid resistance-solid buffer attenuation factor of individual leaf element microsegments; This is the empirical coefficient for viscous damping; The thickness of the water film; The average particle size of the sand; It is an exponential function with the natural constant e as its base; The amplification factor of water hammer in solid-promoting liquid is calculated using the following formula:

[0011] in, For the first The solid-liquid water hammer amplification factor of individual leaf element microsegments; This refers to the initial surface roughness of the blade's leading edge. This represents the instantaneous surface roughness of the blade's leading edge at the current moment. The current moment; This is the stress concentration sensitivity constant.

[0012] Preferably, the total cumulative damage variable of Miner corresponding to each leaf element microsegment for each rain event data record is calculated based on the obtained bidirectional coupling correction factor. The specific method is as follows: Based on the obtained bidirectional coupling correction factor, the pure raindrop fatigue damage increment and pure sand grain damage increment corresponding to each leaf element microsegment for each rain event data record are calculated. The total cumulative damage variable of Miner for each leaf element microsegment is calculated based on the incremental fatigue damage from pure raindrops and the incremental damage from pure sand grains for each rain event data record.

[0013] Preferably, the aerodynamic coefficient at each leaf element micro-segment after damage is calculated based on the total cumulative damage variable of Miner. The specific method is as follows: The damage stage of the leaf tip at each leaf element microsegment was determined based on the Miner total cumulative damage variable, where: If the first If the leading edge of the leaf at each leaf element microsegment is the latency period, then calculate the aerodynamic coefficient after damage at each leaf element microsegment. If the first If the blade leading edge at each leaf element microsegment is in the mass loss period, then calculate the instantaneous surface roughness of the blade leading edge at the current moment at each leaf element microsegment. Based on the obtained instantaneous surface roughness of the blade leading edge at the current moment, calculate the aerodynamic coefficient of each leaf element microsegment after damage.

[0014] Preferably, the equivalent annual power generation loss rate of the wind turbine to be evaluated is calculated based on the obtained aerodynamic torque. Specifically, the method is as follows: The total mechanical power of the wind turbine to be evaluated at the current moment is calculated based on the obtained aerodynamic torque. Based on the overall mechanical power and combined with the Weibull wind speed probability density distribution function of the wind farm, the attenuated equivalent annual power generation of the wind turbine to be evaluated at the current moment is calculated. Based on the attenuated equivalent annual power generation, calculate the equivalent annual power generation loss rate of the wind turbine unit to be evaluated.

[0015] Preferably, the degree of erosion degradation of the wind turbine to be evaluated is determined based on the obtained equivalent annual power generation loss rate. Specifically, the method is as follows: If the equivalent annual power generation loss rate is less than the first threshold, the degree of erosion attenuation of the wind turbine to be evaluated is determined to be mild erosion. If the equivalent annual power generation loss rate is greater than or equal to the first threshold and less than or equal to the second threshold, the erosion attenuation degree of the wind turbine to be evaluated is determined to be moderate erosion. If the equivalent annual power generation loss rate is greater than the second threshold, the erosion degradation degree of the wind turbine to be evaluated is determined to be severe erosion.

[0016] Secondly, the present invention provides a wind turbine blade leading-edge erosion assessment system, comprising: The meteorological data acquisition unit is used to acquire meteorological series data of the wind turbine to be evaluated, which includes multiple rainfall event data records; The blade spanwise discrete element is used to discretize the wind turbine blades of the wind turbine unit to be evaluated into multiple blade element micro-segments along the spanwise direction. The correction factor calculation unit is used to calculate the bidirectional coupling correction factor of each rain event data record at each blade element micro-segment based on the instantaneous morphology of the wind turbine blade surface; The damage variable calculation unit is used to calculate the total cumulative damage variable of each rain event data record in each leaf element microsegment based on the obtained bidirectional coupling correction factor. The aerodynamic coefficient calculation unit is used to calculate the aerodynamic coefficient after damage at each leaf element micro-segment based on the total cumulative damage variable of Miner. The aerodynamic torque calculation unit is used to calculate the aerodynamic torque at each blade element micro-segment based on the obtained damaged aerodynamic coefficients. The power generation loss rate calculation unit is used to calculate the equivalent annual power generation loss rate of the wind turbine to be evaluated based on the obtained aerodynamic torque. The erosion degree determination unit is used to determine the degree of erosion attenuation of the wind turbine to be evaluated based on the obtained equivalent annual power generation loss rate.

[0017] Thirdly, the present invention provides an electronic device including a processor and a memory, wherein the memory stores computer instructions, and when the computer instructions are executed by the processor, the electronic device performs the aforementioned wind turbine blade leading edge erosion assessment method.

[0018] Fourthly, the present invention provides a computer program product containing computer-executable instructions, which, when executed, implement the aforementioned method for assessing leading-edge erosion of wind turbine blades.

[0019] Compared with the prior art, the beneficial effects of the present invention are: This invention provides a method for assessing the leading edge erosion of wind turbine blades. Addressing the shortcomings of existing technologies that neglect the two-way coupling effect between rain and sand (i.e., the buffering and weakening effect of the water film on sand particles and the amplification effect of roughness on the stress concentration of raindrops), this application quantifies the nonlinear coupling mechanism between the liquid and solid phases by calculating a two-way coupling correction factor based on the instantaneous surface morphology of the wind turbine blade. This avoids the assessment bias caused by traditional linear superposition methods, making the assessment results closer to the measurement data of retired blades in actual wind farms. Addressing the shortcomings of existing technologies that lack damage stage division based on fatigue accumulation criteria and assume a constant erosion rate, this application calculates the Miner total cumulative damage variable, calculates the aerodynamic coefficient after damage based on this damage variable, and combines the stage determination of latency (D<1) and mass loss period (D≥1). This eliminates the physical distortion assumption of "initial loss" and more realistically reflects the time-varying degradation trajectory of the coating in the early stages of service. To address the shortcomings of existing technologies that rely on high-fidelity CFD multiphase flow simulation, resulting in low computational efficiency and difficulty in engineering implementation, this application uses a bidirectional coupling correction factor and Miner linear cumulative damage as proxy driving logic. It relies solely on basic meteorological data (rainfall, wind speed, and dust concentration) and conventional aerodynamic parameters, eliminating the need for mesh deformation calculations and high computational costs. This enables efficient evaluation that can be performed in batches and is easily embedded into wind farm digital twin systems. Furthermore, to address the shortcomings of existing technologies where evaluation indicators often stop at erosion depth or static lift-to-drag ratio, deviating from actual engineering needs, this application calculates the equivalent annual power generation loss rate and determines the degree of mild / moderate / severe erosion degradation based on this rate. It directly outputs the economic indicators most important to wind farm operators, providing quantitative engineering basis for deciding the optimal shutdown repair timing, evaluating the selection of leading-edge protection materials, and mitigating power generation revenue losses.

[0020] In summary, this application breaks down the technical barriers from microscopic multiphase flow impact to macroscopic wind farm power generation loss without requiring full life-cycle damage data of wind turbine blades. It has the technical advantages of high assessment accuracy, realistic time-varying characteristics, high computational efficiency, strong engineering applicability, and intuitive and beneficial assessment indicators. Attached Figure Description

[0021] Figure 1 This is a flowchart of the method involved in an embodiment of the present invention; Figure 2 This is a schematic diagram of the bidirectional coupling mechanism between rain and sand in an embodiment of the present invention; Figure 3 The Miner total cumulative damage variable and the time-varying evolution of leaf surface roughness of the outermost leaf element microsegment involved in the embodiments of the present invention; Figure 4 This refers to the equivalent annual power generation loss rate of the entire unit based on full-extension integral reconstruction, as described in this embodiment of the invention. Detailed Implementation

[0022] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0023] It should be understood that, when used in this application specification, the term "comprising" indicates the presence of the described feature, integral, step, operation, element, and / or component, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or collections thereof.

[0024] It should also be understood that the term “and / or” as used in this application specification means any combination of one or more of the associated listed items, as well as all possible combinations, and includes such combinations.

[0025] As used in this application specification, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [the described condition or event] is detected," or "in response to detection of [the described condition or event]."

[0026] Furthermore, in the description of this application, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0028] Example 1 like Figure 1 As shown in the figure, the wind turbine blade leading edge erosion assessment method provided in this embodiment specifically includes the following steps: S1: Obtain meteorological data and blade geometric aerodynamic parameters of the wind turbine to be evaluated through actual measurement methods using meteorological bureaus or wind field sensors.

[0029] In this embodiment, the meteorological series data includes multiple rainfall event data records, and each rainfall event data record includes each time step. Corresponding rainfall Sandstorm mass concentration Average particle size of wind-blown sand and average wind speed Among them, rainfall This refers to the depth of water that falls to the ground within the recorded time interval; average wind speed. This refers to the average wind speed at the hub height within the recorded time interval; windblown sand mass concentration. It refers to the mass of dust particles contained in a unit volume of air, which can be obtained through meteorological monitoring stations or meteorological departments.

[0030] Calculate the average wind speed based on the characteristic parameters of the wind turbine. Corresponding wind turbine speed .

[0031] Discretize the wind turbine blades along their spanwise direction. The leaf element segment, which is a cross-section of the blade at different radii from the impeller rotation center, is used to extract the first leaf element segment. The central position of each leaf element microsegment, i.e., the spanwise position The geometric aerodynamic parameters at the location, including the airfoil chord length, are as follows: and initial lift coefficient With initial drag coefficient .

[0032] In this embodiment, the rainfall amount All units should be converted to meters, and all units of time should be converted to seconds. Average wind speed. Units are uniformly converted to meters per second for wind and sand mass concentration. The unit is .

[0033] S2: Rainfall based on S1 Time step Calculate the rainfall intensity for each rainfall event data record. :

[0034] Among them, rainfall intensity Rainfall per unit time is the volume of rain passing through a unit area per unit time, expressed in meters per second.

[0035] S3: Average wind speed based on S1 Wind turbine speed Exhibition location Calculate the corresponding number of rain event data records in the first... The transient relative impact velocity of the leading edge of a leaf element microsegment :

[0036] Among them, the transient relative impact velocity at the leading edge represents the absolute impact kinetic energy benchmark of rain and sand particles actually hitting the leading edge of the blade, with the outer blade segment... To occupy a dominant position.

[0037] S4: Due to the dynamic balance between the accumulation effect of rainfall and the shear-blowing effect of high-speed airflow, rainfall forms a dynamically retained water film in the leading edge region of the blade. Based on the rainfall intensity obtained in S2... The leading-edge transient relative impact velocity obtained from S3 The empirical formula based on kinematic stationary point equilibrium is used to calculate the corresponding data record of each rain event at the 1st twentieth ... The water film thickness of each leaf cell microsegment :

[0038] in, The dynamic viscosity of water; For water density, select a common reference value; To ensure dimensional uniformity, a constant can be fitted based on actual measurement or experimental conditions, or a common reference value can be selected; water film thickness With rainfall intensity relative impact velocity with leading edge transient change.

[0039] S5: Water film thickness based on S4 Based on the instantaneous morphology of the wind turbine blade surface, the corresponding data record for each rain event is calculated in the 1st... A bidirectional coupling correction factor for each leaf element microsegment, the bidirectional coupling correction factor including a liquid resistance-solid buffer attenuation factor. And solid-liquid water hammer amplification factor .

[0040] S5-1: Water film thickness based on S4 The average particle size of wind-blown sand obtained from S1 Calculate the liquid resistance solid buffer attenuation factor :

[0041] in, This is an empirical coefficient for viscous damping, which can be fitted based on actual measurements or wind tunnel tests, or a common reference value can be selected. Mathematically, it is expressed as a negative exponential decay function, quantifying the effect of sand particles penetrating the water film at the penetration front. At that time, the proportion of impact kinetic energy lost due to fluid viscosity damping, and the water film thickness The thicker the layer, the larger the average particle size of the sand. The smaller the value, the more severe the kinetic energy reduction; It is an exponential function with the natural constant e as its base.

[0042] S5-2: Based on the obtained initial surface roughness of the blade leading edge and the instantaneous surface roughness of the blade leading edge at the current moment Calculate the amplification factor of solid-liquid water hammer. :

[0043] in, This is a stress concentration sensitive constant, which can be fitted based on actual measurements or wind tunnel tests, or a common reference value can be selected; the initial surface roughness of the blade leading edge... The static material constants reflecting the original morphology of the leading-edge protection material or blade surface material at the time of manufacture can be obtained directly by consulting the supplier's technical specifications or by averaging based on empirical measurements using a surface roughness measuring instrument; the instantaneous surface roughness of the blade leading edge at the current moment... As an endogenous state variable in the iterative process of dynamic erosion bidirectional coupling, at the initial moment of evaluation (t=0), erosion has not yet occurred on the blade surface. At this time, let... The calculated solid-liquid water hammer amplification factor That is, initially without stress amplification effect; with time step The advancement (i.e.) (Time), current moment The instantaneous surface roughness of the blade leading edge that is invoked is essentially the same as the previous time step ( The damaged roughness result is dynamically obtained in step S8. This solid-liquid water hammer amplification factor is used to update the output. Mathematically, it is represented by a logarithmic growth function, which characterizes the pitting roughness caused by micro-cutting or impact of sand grains. This roughness causes subsequent raindrop impacts to generate micro-jet streams, thus producing an exponential amplification effect on water hammer pressure.

[0044] S6: A bidirectional coupling correction factor obtained based on S5, i.e., a liquid resistance-solid buffer attenuation factor. And solid-liquid water hammer amplification factor Establish time step The time-varying iterative loop within the loop calculates the corresponding data record for each rain event in the 1st... Individual damage increments of each leaf element segment and Miner's total cumulative damage variable .

[0045] In this embodiment, each damage increment is a pure raindrop fatigue damage increment. Increase in damage from pure sand particles .

[0046] S6-1: At time step Within, the pure raindrop fatigue damage increment under the coupling correction factor is calculated respectively. Compared with the increase in damage from pure sand particles :

[0047]

[0048] in, and These represent the number of pure raindrop impacts and the number of pure sand grain impacts calculated based on S1 meteorological data within the time step, respectively. and These represent the limit fatigue life of the coating material under a specific kinetic energy, determined by the material... Fatigue curve lookup.

[0049] S6-2: Pure raindrop fatigue damage increment based on the coupled correction factor obtained in S6-1 Compared with the increase in damage from pure sand particles Calculate the current time Miner total cumulative damage variable :

[0050] in, The total cumulative damage variable of Miner for the previous time step represents the continuous superposition of internal damage in the material during the microcrack initiation stage, reflecting the linear accumulation of fatigue damage under the bidirectional coupling effect of the blade leading edge interface.

[0051] S7: Miner's total cumulative damage variable obtained from S6 Determine the first The damage stage at the leading edge of the leaf at each leaf element microsegment, and the corresponding steps are performed: (1) If If the condition is as follows, it is determined to be a "latent period": only micro-fatigue occurs within the coating or blade surface material, without triggering macro-material loss, and the instantaneous surface roughness of the blade leading edge remains unchanged at the current moment. ), then execute step S10.

[0052] (2) If This is then identified as the "quality loss period": microcrack penetration leads to material delamination, activating the multiphase flow erosion rate model, and the instantaneous surface roughness of the blade leading edge at the current moment. With time step Gradually increase in size, then execute S8.

[0053] S8: During the period of mass loss, based on the wind and sand mass concentration of S1. S3 leading edge transient relative impact velocity The baseline pure rain erosion rate was calculated using the bidirectional coupling correction factor obtained from S5. and benchmark pure sand erosion rate Based on the baseline pure rain erosion rate and the baseline pure sand erosion rate, and combined with the two-way coupling correction factor, the time step is calculated. Increase in internal material loss ; Calculate the instantaneous surface roughness of the blade leading edge at the current moment based on the material loss increment. .

[0054] S8-1: Based on the transient relative impact velocity of the leading edge of S3 Solve for the baseline pure rain erosion rate Required water hammer stress :

[0055] in, and These are the density of water and the speed of sound, respectively. and These are the density and sound velocity of the blade material or coating material, respectively. Both are common physical parameters. Consult the material manufacturer's manual or select common reference values ​​based on the actual situation. The angle of impact of the raindrop is the angle between the raindrop and the normal to the blade surface.

[0056] S8-2: Water hammer stress obtained from S8-1 The baseline pure rain erosion rate was calculated using the Springer water hammer fatigue model. :

[0057] in, Rainfall quality flux can be obtained from meteorological data; , , These are the density, fatigue limit, and fatigue index of the blade material or coating material, respectively. Common material reference values ​​or fatigue limit tests can be used to obtain these values.

[0058] S8-3: Sandstorm mass concentration obtained from S1 The leading-edge transient relative impact velocity obtained by S3 The baseline pure sand erosion rate was calculated using the Oka erosion model. :

[0059] in, and impact angle function These are all standard material constants from the Oka model; common reference values ​​can be selected based on actual conditions.

[0060] S8-4: Introducing the two-way coupling correction factor obtained from S5, and the baseline pure rain erosion rate obtained from S8-2 and S8-3. and benchmark pure sand erosion rate The actual erosion rates considering bidirectional interface coupling were calculated separately and then linearly summed to obtain the final time step. The actual total erosion depth increment within :

[0061] S8-5: The actual total erosion depth increment obtained from S8-4 Update the instantaneous surface roughness of the blade leading edge at the current moment. :

[0062] in, and All of these are empirical coefficients for morphology transformation, i.e., the transformation of erosion depth into surface roughness, which can be determined comprehensively based on statistical data of erosion images. This represents the instantaneous surface roughness of the blade leading edge at the previous time step.

[0063] S9: Based on the N leaf element segments, repeat steps S2-S8, according to the airfoil chord length of each leaf element segment in S1. The instantaneous surface roughness of the blade leading edge at the current moment obtained from S8 The aerodynamic performance penalty after damage at each spanwise position is calculated based on the empirical penalty formula for lift and drag coefficients, i.e., the reduction in lift coefficient. and the increase in drag coefficient :

[0064]

[0065] in, and These are all airfoil sensitivity constants, which usually refer to the sensitivity of the lift coefficient, slope, and drag coefficient to the angle of attack. They can be obtained by consulting public airfoil databases or by conducting wind tunnel experiments.

[0066] Increased roughness increases surface friction drag and causes the blade surface boundary layer to change from laminar to turbulent flow, resulting in premature separation of airflow on the suction surface (upper surface), causing a significant decrease in lift coefficient and a multiple increase in drag coefficient.

[0067] S10: The decrease in lift coefficient calculated based on S9 and the increase in drag coefficient and the initial lift coefficient of S1 and initial drag coefficient Update the lift aerodynamic coefficients of each leaf element microsegment after damage. and drag aerodynamic coefficient :

[0068]

[0069] Miner's total cumulative damage increment calculated based on S6 To determine the stage of leading edge damage in the S7 blade, if... This indicates that the blade material or coating is in the fatigue latency period. Although raindrops and sand particles are impacting the material, they only accumulate microscopic damage within the material, and there is no change in the roughness or erosion depth of the blade surface. When the increase or decrease in the lift-drag coefficient is 0, the lift aerodynamic coefficient of the blade element segment is: and drag aerodynamic coefficient .

[0070] S11: Lift aerodynamic coefficient updated based on S10 and drag aerodynamic coefficient Substituting this into the classic blade element momentum theory (BEM) calculation model, combined with the wind turbine speed of S1... and exhibition direction position By iterating through the conventional momentum and leaf element equations, the first... Individual leaf element micro-segments at the current average wind speed Tangential aerodynamic forces Then, the aerodynamic torque of each micro segment can be obtained. :

[0071] S12: Aerodynamic torque calculated based on S11 S1 wind turbine speed Reconstruct the overall mechanical power of the unit to be evaluated at the current moment. :

[0072] in, This refers to the total number of blades in a wind turbine generator.

[0073] By employing Riemann integration or summation to accumulate local aerodynamic penalties into the overall torque output, a core bridge connecting microscopic wear and macroscopic productivity is formed.

[0074] S13: Total mechanical power calculated based on S12 By combining the Weibull wind speed probability density distribution function of the wind field, the current time is calculated. Equivalent annual power generation under the condition of degradation and equivalent annual power generation loss rate .

[0075] S13-1: Let... Wind speed The Weibull probability density function, based on the reconstructed total mechanical power of the machine using S12. Calculate the current time Equivalent annual power generation under the condition of degradation :

[0076] in, The cut-out wind speed of the wind turbine; This refers to the cut-in wind speed of the wind turbine.

[0077] S13-2: Based on the meteorological data and blade geometric aerodynamic parameters obtained in S1, calculate the ideal equivalent annual power generation under the condition of no erosion loss. As a benchmark parameter, or estimated using existing wind turbine operating parameters or wind tunnel test data, and then based on the attenuation equivalent annual power generation obtained from S13-1. Calculate the equivalent annual power generation loss rate at the current moment. :

[0078] S14: Equivalent annual power generation loss rate obtained from S13-2 This allows for the determination of the severity of erosion and degradation in wind turbine units, providing predictive strategies for operation and maintenance. (1) If If the erosion attenuation level of the wind turbine to be evaluated is determined to be mild erosion; (2) If If the erosion attenuation level of the wind turbine to be evaluated is determined to be moderate erosion; (3) If If the erosion attenuation level of the wind turbine to be evaluated is determined to be severe erosion; in, and The first and second thresholds are respectively, which can be determined by a comprehensive fitting of the historical operating rate of return of the wind farm and the blade maintenance cost.

[0079] Example 2 Using the publicly available NREL-5MW wind turbine model from the U.S. National Renewable Energy Laboratory as the application object, this implementation case focuses on the operating conditions of a typical inland wind farm under severe wind, sand, and rainfall conditions. To verify the wind turbine blade leading-edge erosion assessment method proposed in this invention, the environmental meteorological boundary conditions are set as follows: annual average wind speed is... Typical rainfall intensity is The mass concentration of wind and sand is The average particle size of the wind-blown sand is The rated wind speed, cut-in wind speed, rated rotational speed, and pitch angle curves of the NREL-5MW wind turbine model can be found in the reference (Jonkman J, Butterfield S, Musical W, et al. Definition of a 5-MW referencewind turbine for offshore system development[R]. National Renewable Energy Laboratory (NREL), Golden, CO., 2009.). Substituting the above aerodynamic parameters and typical meteorological data into the evaluation method of this invention, the total operating time is set to 5 years. The Miner cumulative damage and time-varying evolution curves of the outermost blade element microsegment calculated according to the method of this invention are shown below. Figure 3 As shown; the evolution curve of the equivalent annual power generation loss rate of the entire unit based on the full span integral reconstruction is as follows. Figure 4 As shown. Figure 3 As shown, based on bidirectional coupling correction and Miner's linear fatigue accumulation calculation, the cumulative damage at the blade leading edge is less than 1 within the first 1.5 years of service, indicating a fatigue latency period where surface roughness remains unchanged from its initial state. After 1.5 years, the damage exceeds the latency threshold, entering the mass loss period, and the leading edge roughness increases nonlinearly and at an accelerated rate. Combined with... Figure 4 The time-varying result of the annual power generation loss rate obtained by the full-stretch integral, if we set the economic tolerance threshold constant of wind farm power generation... , If the corrosion level of the unit is mild in the first two years of its service life, the corrosion level will gradually change from moderate to severe after the unit has been in operation for more than three years.

[0080] Example 3 This embodiment provides a wind turbine blade leading-edge erosion assessment system, including: The meteorological data acquisition unit is used to acquire meteorological series data of the wind turbine to be evaluated, which includes multiple rainfall event data records; The blade spanwise discrete element is used to discretize the wind turbine blades of the wind turbine unit to be evaluated into multiple blade element micro-segments along the spanwise direction. The correction factor calculation unit is used to calculate the bidirectional coupling correction factor of each rain event data record at each blade element micro-segment based on the instantaneous morphology of the wind turbine blade surface; The damage variable calculation unit is used to calculate the Miner total cumulative damage variable for each leaf element microsegment corresponding to each rain event data record based on the obtained bidirectional coupling correction factor. The aerodynamic coefficient calculation unit is used to calculate the aerodynamic coefficient after damage at each leaf element micro-segment based on the total cumulative damage variable of Miner. The aerodynamic torque calculation unit is used to calculate the aerodynamic torque at each blade element micro-segment based on the obtained damaged aerodynamic coefficients. The power generation loss rate calculation unit is used to calculate the equivalent annual power generation loss rate of the wind turbine to be evaluated based on the obtained aerodynamic torque. The erosion degree determination unit is used to determine the degree of erosion attenuation of the wind turbine to be evaluated based on the obtained equivalent annual power generation loss rate.

[0081] Example 4 This embodiment also provides a computing device. The computing device includes a bus, a processor, a memory, and a communication interface. The processor, memory, and communication interface communicate with each other via the bus. The computing device can be a server or a terminal device. It should be understood that this application does not limit the number of processors and memory in the computing device.

[0082] A 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, a bus can include a path for transmitting information between various components of a computing device (e.g., memory, processor, communication interfaces).

[0083] The processor may include any one or more of the following: central processing unit (CPU), graphics processing unit (GPU), tensor processing unit (TPU), application specific integrated circuit (ASIC), field-programmable gate array (FPGA), microprocessor (MP), or digital signal processor (DSP).

[0084] Memory can include volatile memory, such as random access memory (RAM). Processors can also include non-volatile memory. volatile memory, such as read-only memory (ROM). ROM (memory only), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0085] The memory stores executable program code, which the processor executes to implement the functions of the aforementioned units, thereby achieving, for example, the method described in Embodiment 1. That is, the memory may store instructions for the methods and functions relating to the computing device in any of the above embodiments.

[0086] The communication interface uses transceiver modules such as, but not limited to, network interface cards and transceivers to enable communication between computing devices and other devices or communication networks.

[0087] Example 5 This embodiment also provides a computer-readable storage medium storing computer instructions that, when executed by a processor, cause the processor to perform the methods and functions of the computing device involved in any of the above embodiments.

[0088] Generally, the various embodiments of this disclosure can be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. Some aspects can be implemented in hardware, while others can be implemented in firmware or software, which can be executed by a controller, microprocessor, or other computing device. Although various aspects of the embodiments of this disclosure are shown and described as block diagrams, flowcharts, or represented using some other illustration, it should be understood that the blocks, apparatuses, systems, techniques, or methods described herein can be implemented as, as non-limiting examples, in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0089] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for assessing leading-edge erosion of wind turbine blades, characterized in that, Includes the following steps: Obtain meteorological data for the wind turbine to be evaluated, including multiple rainfall event data records; The wind turbine blades of the wind turbine unit to be evaluated are discretized along the spanwise direction into multiple blade element micro-segments; Based on the instantaneous morphology of the wind turbine blade surface, the bidirectional coupling correction factor corresponding to each rain event data record at each blade element micro-segment is calculated; Based on the obtained bidirectional coupling correction factor, the Miner total cumulative damage variable corresponding to each leaf element microsegment for each rain event data record is calculated. The aerodynamic coefficients at each leaf element microsegment after damage were calculated based on the total cumulative damage variable of Miner. Calculate the aerodynamic torque at each leaf element microsegment based on the obtained aerodynamic coefficients after damage; The equivalent annual power generation loss rate of the wind turbine to be evaluated is calculated based on the obtained aerodynamic torque. The degree of erosion and degradation of the wind turbine to be evaluated is determined based on the obtained equivalent annual power generation loss rate.

2. The method for assessing leading-edge erosion of wind turbine blades according to claim 1, characterized in that, Based on the instantaneous morphology of the wind turbine blade surface, the bidirectional coupling correction factor corresponding to each rain event data record at each blade element micro-segment is calculated. The specific method is as follows: Each rainfall event data record includes each time step. Corresponding rainfall Average particle size of wind-blown sand and average wind speed ; Based on time step Corresponding rainfall Calculate the rainfall intensity corresponding to each rainfall event data record; Based on average wind speed Calculate the corresponding number of rain event data records in the first... The transient relative impact velocity of the leading edge of a leaf element microsegment; Based on the obtained rainfall intensity and leading-edge transient relative impact velocity, the water film thickness in each leaf element microsegment corresponding to each rainfall event data record is calculated. Based on the water film thickness and the instantaneous morphology of the wind turbine blade surface, the bidirectional coupling correction factor corresponding to each rain event data record at each blade element micro-segment is calculated. The bidirectional coupling correction factor includes a liquid resistance-solid buffer attenuation factor and a solid-promote-liquid-water hammer amplification factor.

3. The method for assessing leading-edge erosion of wind turbine blades according to claim 2, characterized in that, The liquid-solid buffer attenuation factor is calculated using the following formula: in, For the first Liquid resistance-solid buffer attenuation factor of individual leaf element microsegments; This is the empirical coefficient for viscous damping; The thickness of the water film; The average particle size of the sand; It is an exponential function with the natural constant e as its base; The amplification factor of water hammer in solid-promoting liquid is calculated using the following formula: in, For the first The solid-liquid water hammer amplification factor of individual leaf element microsegments; This refers to the initial surface roughness of the blade's leading edge. This represents the instantaneous surface roughness of the blade's leading edge at the current moment. The current moment; This is the stress concentration sensitivity constant.

4. The method for assessing leading-edge erosion of wind turbine blades according to claim 1, characterized in that, Based on the obtained bidirectional coupling correction factor, the total cumulative damage variable of Miner corresponding to each leaf element microsegment for each rain event data record is calculated. The specific method is as follows: Based on the obtained bidirectional coupling correction factor, the pure raindrop fatigue damage increment and pure sand grain damage increment corresponding to each leaf element microsegment for each rain event data record are calculated. The total cumulative damage variable of Miner for each leaf element microsegment is calculated based on the incremental fatigue damage from pure raindrops and the incremental damage from pure sand grains for each rain event data record.

5. The method for assessing leading-edge erosion of wind turbine blades according to claim 1, characterized in that, The aerodynamic coefficient at each leaf element microsegment after damage is calculated based on the total cumulative damage variable of Miner. The specific method is as follows: The damage stage of the leaf tip at each leaf element microsegment was determined based on the Miner total cumulative damage variable, where: If the first If the leading edge of the leaf at each leaf element microsegment is the latency period, then calculate the aerodynamic coefficient after damage at each leaf element microsegment. If the first If the blade leading edge at each leaf element microsegment is in the mass loss period, then calculate the instantaneous surface roughness of the blade leading edge at the current moment at each leaf element microsegment. Based on the obtained instantaneous surface roughness of the blade leading edge at the current moment, calculate the aerodynamic coefficient of each leaf element microsegment after damage.

6. The method for assessing leading-edge erosion of wind turbine blades according to claim 1, characterized in that, The equivalent annual power generation loss rate of the wind turbine to be evaluated is calculated based on the obtained aerodynamic torque. The specific method is as follows: The total mechanical power of the wind turbine to be evaluated at the current moment is calculated based on the obtained aerodynamic torque. Based on the overall mechanical power and combined with the Weibull wind speed probability density distribution function of the wind farm, the attenuated equivalent annual power generation of the wind turbine to be evaluated at the current moment is calculated. Based on the attenuated equivalent annual power generation, calculate the equivalent annual power generation loss rate of the wind turbine unit to be evaluated.

7. The method for assessing leading-edge erosion of wind turbine blades according to claim 1, characterized in that, The degree of erosion degradation of the wind turbine to be evaluated is determined based on the obtained equivalent annual power generation loss rate. The specific method is as follows: If the equivalent annual power generation loss rate is less than the first threshold, the degree of erosion attenuation of the wind turbine to be evaluated is determined to be mild erosion. If the equivalent annual power generation loss rate is greater than or equal to the first threshold and less than or equal to the second threshold, the erosion attenuation degree of the wind turbine to be evaluated is determined to be moderate erosion. If the equivalent annual power generation loss rate is greater than the second threshold, the erosion degradation degree of the wind turbine to be evaluated is determined to be severe erosion.

8. A wind turbine blade leading-edge erosion assessment system, characterized in that, include: The meteorological data acquisition unit is used to acquire meteorological series data of the wind turbine to be evaluated, which includes multiple rainfall event data records; The blade spanwise discrete element is used to discretize the wind turbine blades of the wind turbine unit to be evaluated into multiple blade element micro-segments along the spanwise direction. The correction factor calculation unit is used to calculate the bidirectional coupling correction factor of each rain event data record at each blade element micro-segment based on the instantaneous morphology of the wind turbine blade surface; The damage variable calculation unit is used to calculate the total cumulative damage variable of each rain event data record in each leaf element microsegment based on the obtained bidirectional coupling correction factor. The aerodynamic coefficient calculation unit is used to calculate the aerodynamic coefficient after damage at each leaf element micro-segment based on the total cumulative damage variable of Miner. The aerodynamic torque calculation unit is used to calculate the aerodynamic torque at each blade element micro-segment based on the obtained damaged aerodynamic coefficients. The power generation loss rate calculation unit is used to calculate the equivalent annual power generation loss rate of the wind turbine to be evaluated based on the obtained aerodynamic torque. The erosion degree determination unit is used to determine the degree of erosion attenuation of the wind turbine to be evaluated based on the obtained equivalent annual power generation loss rate.

9. An electronic device, characterized in that, It includes a processor and a memory, the memory storing computer instructions, which, when executed by the processor, cause the electronic device to perform a wind turbine blade leading-edge erosion assessment method according to any one of claims 1 to 7.

10. A computer program product, characterized in that, The computer program product contains computer-executable instructions, which, when executed, implement a wind turbine blade leading-edge erosion assessment method according to any one of claims 1 to 7.

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