Wind turbine blade monitoring method and device, storage medium, and wind turbine

Abstract

A method and device for monitoring wind turbine blades, a storage medium, and a wind turbine are disclosed. The method includes: acquiring wavelength signals collected by multiple displacement sensors installed at multiple cross-sectional locations within the wind turbine blade; calculating the bending moment, torque, and / or displacement of the wind turbine blade at the multiple cross-sectional locations based on the wavelength signals from each displacement sensor; and determining the structural state of the wind turbine blade based on the bending moment, torque, and / or displacement. The technical solution of the present invention can improve the accuracy of wind turbine blade condition monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and device for monitoring fan blades of a wind turbine, a storage medium, and a wind turbine. Background Art

[0002] As turbine technology improves, the wind power market is moving towards higher power generation and lower operation and maintenance costs, which is also the main direction of technological research and development innovation for various complete machine manufacturers. Therefore, megawatt-level wind turbines require larger wind turbine blades to capture more wind energy for conversion into electrical energy, which also brings daunting challenges to the design of wind turbines and ultra-long blades. Wind turbine blades are the main components for capturing wind energy. As wind turbine blades grow in length, real-time monitoring of blade loads becomes essential. Especially for wind turbines at sea and in northern regions, after strong winds or typhoons each year, whether the wind turbine blades are damaged and when the wind turbine can be started and operated can currently only be completed through inspections after strong winds or typhoons. This is inefficient, costly, and requires a lot of manpower and time.

[0003] In addition, wind farms are generally located in areas with complex and changeable wind conditions, and the blades are constantly lengthening. Not only are the wind conditions between each wind turbine different, but the wind thrusts on different blades of the wind turbine are also different in different orientations. Coupled with changes in the aerodynamic shape of the blades, the cumulative errors in pitch execution, the centering errors of the transmission chain, etc., the risk factor of the aerodynamic imbalance of the blades to the safety of the wind turbine gradually increases. The function of independent pitch control is particularly important at this time, and it is a necessary way to improve the power generation efficiency and safety factor of the wind turbine. Unlike synchronous pitch control, independent pitch control issues different pitch commands based on the actual load of each blade, controls the change in pitch angle, and enables each blade to obtain a different target position to achieve the purpose of reducing the unbalanced load on the impeller surface. Real-time blade load monitoring is the basic data source for independent pitch control.

[0004] According to statistics, wind farms in Yunnan, Sichuan, and other parts of my country experience frequent thunderstorms each year. As wind turbine towers grow taller, the probability of blades being struck by lightning also increases. Currently, the basic lightning protection design or lightning receptor components of wind turbine blades cannot fully attract lightning, and accidents where blades are damaged by lightning often occur. Lightning current flowing through the blades generates a large electromagnetic force, which can bend the entire wind turbine blade and even cause various mechanical damage, such as perforation of the blade surface, tip explosion, skin cracking, and blade breakage. The short duration and high energy of lightning currents limit the use of many detection technologies. Being able to record information such as the magnitude, frequency, and duration of lightning currents in real time would be a significant aid in improving wind turbine blade design.

[0005] Therefore, real-time monitoring of wind turbine blade loads and long-term recording and collection of lightning currents can, in the short term, assess the turbine's structural status in real time, providing a control strategy basis for independent pitch control systems, fully utilizing wind resources and improving power generation efficiency. In the long term, blade damage and fatigue assessment can be performed, reducing operation and maintenance costs and improving economic benefits. Currently, there are many blade load measurement sensors, which generally use either resistive strain gauges or optical fiber strain gauges.

[0006] However, resistive load sensors are severely susceptible to electromagnetic interference, and the sensor wiring is complex, requiring insulation. Otherwise, if struck by lightning, they must all be replaced, making them unsuitable for long-term monitoring. Furthermore, as wind turbine blades grow longer, the voltage drop in resistive load sensor signals during long-distance cable transmission becomes increasingly prominent. Furthermore, the sensor's sensing voltage is typically in the microvolt and millivolt range, making it susceptible to electromagnetic interference in the wind turbine's operating environment. This is especially true for large-megawatt offshore wind turbine nacelles, which are often equipped with high-voltage transformers that create extremely strong electromagnetic interference. This significantly reduces the strain gauge's service life and monitoring reliability. Therefore, some electronic load or strain sensors, such as resistive and piezoelectric, are no longer suitable for wind turbine monitoring. Summary of the Invention

[0007] The technical problem solved by the present invention is how to improve the accuracy of wind turbine blade status monitoring.

[0008] To solve the above technical problems, an embodiment of the present invention provides a method for monitoring wind blades of a wind turbine. The method includes: obtaining wavelength signals collected by multiple displacement sensors, wherein the multiple displacement sensors are installed at multiple cross-sectional positions within the wind blade; calculating the bending moment, torque and / or displacement of the wind blade at the multiple cross-sectional positions based on the wavelength signals of each displacement sensor; and determining the structural state of the wind blade based on the bending moment, the torque and / or the displacement.

[0009] Optionally, the multiple cross-sectional positions are selected from the root of the fan blade, the maximum chord length of the fan blade, and the diameter change point of the wing-shaped cross-section.

[0010] Optionally, determining the structural state of the fan blade based on the bending moment, the torque and / or the displacement includes: if the bending moment reaches a first preset threshold and / or the torque reaches a second preset threshold, determining that the fan blade is cracked; and / or, if the displacement is less than a third preset threshold, determining that the fan blade is cracked; and / or, if the difference in bending moment and torque between different fan blades reaches a fourth preset threshold, determining that the state of the fan blade is aerodynamically unbalanced.

[0011] Optionally, determining the structural state of the fan blade based on the bending moment, the torque and / or the displacement includes: obtaining the theoretical bending moment, theoretical torque and / or theoretical displacement output by the static model corresponding to the fan blade under the current blade state and environmental state; and comparing the bending moment, the torque and / or the displacement with the theoretical bending moment, the theoretical torque and / or the theoretical displacement, respectively, to determine the structural state of the fan blade.

[0012] Optionally, calculating the bending moment of the wind turbine blade at the multiple cross-sectional positions based on the wavelength signals of each displacement sensor includes: calculating the displacement of the displacement sensor using the wavelength signals of each displacement sensor; and calculating the bending moment using the displacement, a calibrated stiffness coefficient, and the distance between the displacement sensor installation cross-sectional position and the blade root.

[0013] Optionally, the method further includes: calculating, based on the bending moment, a first bending moment of the fan blade in the flapping direction and a second bending moment in the swinging direction at the current pitch angle, azimuth angle, impeller inclination angle, and blade cone angle; the first bending moment of the fan blade in the flapping direction and the second bending moment in the swinging direction are calculated by the following formula: M flap ={{Md(-Cos[θ]Sin[δ]Sin[φ]+Cos[δ](Cos[Ω]Sin[θ]Sin[φ]+Cos[φ]Sin[Ω]))}},

[0014] M edge ={{Md(Cos[θ]Cos[φ]Sin[δ]+Cos[δ](-Cos[φ]Cos[Ω]Sin[θ]+Sin[φ]Sin[Ω]))}}

[0015] , where M flap is the first bending moment, M edge is the second bending moment, Md is the bending moment, Ω is the blade azimuth angle, φ is the blade pitch angle, δ is the impeller inclination angle, and θ is the blade cone angle.

[0016] Optionally, the calibrated stiffness coefficient is calibrated by the following steps: when the wind speed is less than a preset threshold, the azimuth angle and pitch angle of the wind turbine blade are fixed, and the wavelength of each displacement sensor is obtained; the wavelength is converted into actual displacement; the theoretical bending moment is calculated based on the gravity of the blade, the distance between the installation section of the displacement sensor and the blade root, and the distance from the center of gravity of the wind turbine blade to the blade root; the stiffness coefficient to be calibrated is calculated using the mapping relationship between the actual displacement, the theoretical bending moment, and the stiffness coefficient to be calibrated, and the mapping relationship is expressed by the following formula: d M =r0×K B -1 ×M d , where dM represents the actual displacement, K B -1 Indicates the stiffness coefficient to be calibrated, M d represents the theoretical bending moment.

[0017] Optionally, calculating the torque of the fan blade at the multiple cross-sectional positions based on the wavelength signals of each displacement sensor includes: calculating the torque using the wavelength signal of the displacement sensor, the torsional cross-sectional coefficient of the fan blade at the displacement sensor installation cross-sectional position, and a calibrated torque coefficient.

[0018] Optionally, the torque is calculated using the following formula: T0 = K τ ×(λ τ -λ0)×W, where T0 represents the torque, K τ represents the calibrated torque coefficient, λ τ represents the wavelength signal, λ0 represents the initial wavelength of the displacement sensor, and W represents the torsional section coefficient.

[0019] Optionally, the calibrated torque coefficient is calibrated by the following steps: when the wind speed is less than a preset threshold, the azimuth angle and pitch angle of the wind turbine blade are fixed, and the wavelength of each displacement sensor is obtained; the theoretical torque generated by the gravity of the wind turbine blade at the azimuth angle and pitch angle is calculated; the shear stress generated by the theoretical torque is calculated based on the theoretical torque and the torsional section coefficient; the torque coefficient to be calibrated is calculated based on the mapping relationship between the torque coefficient to be calibrated, the shear stress and the wavelength.

[0020] Optionally, the method further includes: collecting current collected by a current sensor, wherein the current sensor is installed in the lightning conductor area inside the wind turbine blade; when the collected current indicates that the wind turbine blade is struck by lightning, the degree of damage to the wind turbine blade is determined using the change in the bending moment, the torque and / or the displacement before and after the lightning strike.

[0021] Optionally, the displacement sensor is a passive sensor.

[0022] To solve the above technical problems, an embodiment of the present invention further discloses a wind turbine blade monitoring device for a wind turbine. The wind turbine blade monitoring device includes: an acquisition module for acquiring wavelength signals collected by multiple displacement sensors, wherein the multiple displacement sensors are installed at multiple cross-sectional positions within the wind turbine blade; a calculation module for calculating the bending moment, torque and / or displacement of the wind turbine blade at the multiple cross-sectional positions based on the wavelength signals of each displacement sensor; and a state determination module for determining the structural state of the wind turbine blade based on the bending moment, torque and / or displacement.

[0023] An embodiment of the present invention further discloses a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the wind turbine blade monitoring method are executed.

[0024] An embodiment of the present invention also discloses a wind turbine, comprising wind blades, and further comprising: one or more displacement sensors, arranged inside at least one wind blade of the wind turbine; a processor, coupled to the displacement sensor, the processor being used to execute the steps of the wind turbine blade monitoring method of the wind turbine.

[0025] Compared with the prior art, the technical solution of the embodiment of the present invention has the following beneficial effects:

[0026] In the technical solution of the present invention, displacement sensors are installed at multiple cross-sectional locations within the wind turbine blade, capable of measuring changes in displacement, bending moment, and / or torque at different locations on the blade. This allows for more accurate monitoring of the blade's structural state by combining changes in multiple physical quantities. Furthermore, the technical solution of the present invention utilizes displacement sensors to collect wavelength information. During transmission, the wavelength signal is not affected by external factors such as transmission distance, light source fluctuations, and fiber optic cable bends, thereby enabling further accurate monitoring of the blade's condition.

[0027] Furthermore, a current sensor is also provided in the blade of the technical solution of the present invention. Through the combination of the displacement sensor and the current sensor, the load state of the blade at the moment of lightning strike and before and after the lightning strike can be captured, thereby further realizing accurate tracking and recording monitoring of the blade load state. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a flow chart of a method for monitoring fan blades according to an embodiment of the present invention;

[0029] Figure 2 is a schematic diagram of a specific application scenario of an embodiment of the present invention;

[0030] Figure 3 is a schematic diagram of another specific application scenario of an embodiment of the present invention;

[0031] Figure 4 It is a structural schematic diagram of a wind turbine blade monitoring device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] As described in the background technology, existing resistive load sensors are severely affected by electromagnetic interference. The wiring of the sensors is relatively complex and requires insulation treatment. Otherwise, if struck by lightning, they must all be replaced, making them unsuitable for long-term monitoring. In addition, as the length of wind turbine blades increases, the voltage drop caused by the signals of resistive load sensors during long-distance cable transmission becomes particularly prominent. At the same time, the sensing voltage of the sensor is generally in the microvolt and millivolt levels, which is susceptible to electromagnetic interference in the environment where the wind turbine is operating. In particular, the cabins of large-megawatt offshore wind turbines are usually equipped with high-voltage transformers, which have extremely strong electromagnetic interference, which greatly reduces the service life of the strain gauges and the monitoring reliability. Therefore, some electronic load or strain sensors such as resistive and piezoelectric types are no longer suitable for monitoring wind turbines.

[0033] In the technical solution of the present invention, displacement sensors are installed at multiple cross-sectional positions within the wind turbine blades, and are capable of measuring changes in displacement, bending moment and / or torque at different positions on the blades. That is, the structural state of the blades is determined by combining changes in multiple types of physical quantities, thereby achieving more accurate state monitoring of the blades.

[0034] Furthermore, a current sensor is also provided in the blade of the technical solution of the present invention. Through the combination of the displacement sensor and the current sensor, the load state of the blade at the moment of lightning strike and before and after the lightning strike can be captured, thereby further realizing accurate tracking and recording monitoring of the blade load state.

[0035] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0036] Figure 1 This is a flow chart of a wind turbine blade monitoring method according to an embodiment of the present invention.

[0037] The wind turbine blade monitoring method can be used for status monitoring of wind turbine blades of a wind turbine, and can be specifically executed by a processor, specifically by a terminal device equipped with a processor, for example, by a device disposed inside a hub casing of a wind turbine.

[0038] Specifically, the wind turbine blade monitoring method may include the following steps:

[0039] Step S101: Acquire wavelength signals collected by a plurality of displacement sensors, wherein the plurality of displacement sensors are installed at a plurality of cross-sectional positions within a wind turbine blade;

[0040] Step S102: calculating the bending moment, torque and / or displacement of the wind turbine blade at the plurality of cross-sectional positions according to the wavelength signals of the displacement sensors;

[0041] Step S103: determining the structural state of the wind turbine blade according to the bending moment, the torque and / or the displacement.

[0042] It should be noted that the serial numbers of the steps in this embodiment do not limit the execution order of the steps.

[0043] In this embodiment, multiple displacement sensors can be installed at multiple cross-sectional locations within a wind turbine blade. Thus, the displacement sensors can collect wavelength signals from the blade at multiple cross-sectional locations, and the wavelength signal at each cross-sectional location can reflect the structural state at that location. The cross-sectional location refers to the location of a cross section of the wind turbine blade, and one or more sensors can be installed at each cross-sectional location.

[0044] Specifically, the displacement sensor can collect relevant parameter information of the light source, such as light intensity, wavelength, etc. For example, the displacement sensor can be a fiber optic sensor. When the light signal is irradiated on the sensor, the sensor will reflect a specific wavelength. The embodiment of the present invention uses a displacement sensor to collect wavelength information. The wavelength signal is not affected by external factors such as transmission distance, light source fluctuations, optical cable bending, etc. during transmission. The signal is more stable, thereby further realizing accurate monitoring of the blade status. In addition, the change in wavelength has a linear relationship with the change in displacement detected by the sensor. The displacement sensor can measure the displacement by collecting the wavelength signal.

[0045] In a specific embodiment, please refer to Figure 2 The multiple cross-sectional locations are selected from the blade root, the maximum chord length of the blade, and the point where the airfoil section changes diameter. In other words, multiple displacement sensors can be placed at the blade root section 21, the maximum chord length section 23, and the point where the airfoil section changes diameter 22.

[0046] Specifically, multiple displacement sensors can be installed on each mounting section, one on the windward and one on the leeward sides. All displacement sensors measure along the blade's length. Sensors should be installed away from the blade's mold seam bonding area and the bonding area between the internal web and the blade, avoiding stress concentration areas in the blade structure.

[0047] It should be noted that the installation cross section may also be the cross section position of other weak areas in the blade that are prone to cracking, and the embodiment of the present invention does not limit this.

[0048] In a specific application scenario, within a preset distance from the blade root, for example, within a range of approximately 2 meters, the blade structure is circular, after which the blade begins to form an airfoil. The airfoil-shaped diameter change point referred to in the present invention may refer to a preset distance from the blade root, specifically a region after the preset distance, for example, a cross-sectional position within a range of 2-8 meters. The maximum chord length point referred to in the present invention refers to the widest point of the blade. The blade root referred to in the embodiments of the present invention refers to the root position of the blade. Specifically, the blade root cross-section may be selected from a circular cross-section within a preset distance from the blade root.

[0049] In a specific embodiment, the displacement sensor can be installed at the above-mentioned cross-sectional position of the blade by means of adhesive, bolts or pre-embedded implantation.

[0050] In the specific implementation of step S101 , the wavelength signal collected by the displacement sensor may be obtained through a transmission medium, such as an optical cable.

[0051] Since the bending moment and torque of the blade will change after the state of the blade changes, for example, the blade cracks, and the displacement sensor will also be displaced, in the specific implementation of step S102 and step S103, the wavelength signals collected by each displacement sensor can be used to calculate the bending moment, torque and / or displacement of the blade to measure whether the state of the blade has changed.

[0052] In an embodiment of the present invention, displacement sensors are installed at multiple cross-sectional positions within the wind turbine blade, and are capable of measuring changes in displacement, bending moment and / or torque at different positions on the blade. That is, the structural state of the blade is determined by combining changes in multiple types of physical quantities, thereby achieving more accurate state monitoring of the blade.

[0053] In a specific embodiment of the present invention, taking the blade root section as an example, please refer to Figure 3 , install 6 fiber optic displacement sensors at the blade root ( Figure 3(As shown in Figure 1, A, B, C, D, E, and F), of which four are used to monitor the blade root bending moment (the installation direction is the blade axis), and two are used to monitor the blade root torque (the installation direction is the tangent direction of the selected installation section circle). The displacement sensors A, B, C, and D are located at the blade root bending moment measurement points. The four measurement points are equally spaced. The connecting lines of the A and B measurement points and the connecting line of the C and D measurement points intersect at the center of the installation section circle, and the connecting lines are orthogonal at the center. The measuring points (A and B) do not coincide with the mold seam. The minimum distance d1 from the measuring points (A and B) to the mold seam is usually not less than 10 cm to avoid the stress concentration area of ​​the mold seam. The displacement sensors E and F are located at the blade root torque measurement points. The connecting line of the two measuring points passes through the center of the installation section circle. The minimum distance d2 from the two blade root torque measurement points to the mold seam is usually not less than 10 cm to avoid the stress concentration area of ​​the mold seam. The measuring direction of displacement sensors A, B, C, and D is the length direction of the blade, and the measuring direction of displacement sensors E and F is the tangent direction of the installation section circle.

[0054] In a specific application scenario, two displacement sensors are arranged on both sides of the trailing edge and the leading edge of the blade at the cross section of the maximum chord length of the blade. The sensors are installed on the internal structure of the blade, avoiding the bonding area of ​​the upper and lower molds of the blade and the bonding area between the web and the blade.

[0055] It should be noted that the number of displacement sensors can be set according to actual application scenarios, for example, it can be 8, 10, etc., and the embodiment of the present invention does not limit this.

[0056] In a non-limiting embodiment of the present invention, the displacement sensor is a passive sensor, such as a MEMS (Micro-Electro-Mechanical System) fiber optic displacement sensor, a MOEMS (Micro-Opto-Electro-Mechanical System) fiber optic displacement sensor, or a MOMS (Micro-Opto-Mechanical System) fiber optic displacement sensor.

[0057] Among them, MEMS fiber optic sensing technology can be a technology based on micron / nano mechanics and optics.

[0058] MEMS fiber optic sensors use semiconductor micro-nano processing technology to achieve mass integrated manufacturing of sensitive structural elements, signal detection optical elements, supporting substrates, packaging shells, etc., and use optical fiber as the medium for signal reading and transmission, so there is no need to consider the power supply issues of sensitive measuring ends and lead-out lines. This not only facilitates long-distance separation and achieves the purpose of safe isolation of test equipment away from the test site, but also greatly simplifies the packaging and installation structure of the on-site measurement end sensor, and the external dimensions are reduced to the millimeter level or even sub-millimeter level.

[0059] MEMS fiber optic displacement sensors utilize a wavelength-based principle, integrating a distance encoder, elastic support, optical reflective micromirrors, and light input and output waveguides directly onto a tiny chip. This enables all-optical monitoring of micron-level displacement signals. Advantages include requiring no power to the probe or transmission line, immunity to electromagnetic interference, high resolution, simple installation, high reliability, and long-distance transmission without compromising detection accuracy.

[0060] Furthermore, the signal output cable of the MEMS fiber-optic displacement sensor is an optical fiber, ensuring that the sensor can still be used during lightning storms without the safety hazard of lightning conduction. The MEMS fiber-optic displacement sensor has extremely high sensitivity and linearity, with a measurement resolution of 1μm and a linearity error of no more than 2%. Therefore, installing multiple fiber-optic displacement sensors on a blade can detect blade cracks and identify their size, with crack identification accuracy unaffected by blade vibration and environmental interference.

[0061] It should be noted that the above-mentioned optical fiber sensor may also be any other feasible single-point sensor or continuous distributed sensor using optical fiber as a sensing or transmission medium, and the embodiment of the present invention does not impose any limitation on this.

[0062] In an embodiment of the present invention, by setting the displacement sensor as a passive sensor, passive detection without electricity at the detection end can be achieved, effectively improving the ability to resist electromagnetic and lightning, helping to avoid interference or even damage to the detection of wind turbines caused by lightning strikes in open wind fields, ensuring the normal progress of monitoring and improving detection accuracy.

[0063] In a non-limiting embodiment of the present invention, Figure 1 Step S103 may include the following steps:

[0064] If the bending moment reaches a first preset threshold and / or the torque reaches a second preset threshold, determining that the wind turbine blade is cracked and determining the size of the crack;

[0065] and / or, if the displacement is less than a third preset threshold, determining that the wind turbine blade is cracked and determining the size of the crack;

[0066] And / or, if the difference between the bending moments and torques of different wind turbine blades reaches a fourth preset threshold, it is determined that the state of the wind turbine blade is aerodynamically unbalanced.

[0067] In this embodiment, by comparing the calculated bending moment, the torque and / or the displacement with corresponding thresholds, the state of the blade can be determined, specifically, whether the blade is cracked or whether the blade is aerodynamically unbalanced.

[0068] Specifically, when cracking or ice forms on the blade structure, the blade bending moment measured by the displacement sensor installed in the blade root area increases. If the bending moment measured on any blade exceeds a first preset threshold, a signal acquisition and processing unit within the blade hub can issue a warning to the wind turbine control system, which then changes the wind turbine's operating mode, such as shutting it down.

[0069] Specifically, when cracks develop between the blade web and the blade structure, the blade web fractures, or the blade spar fractures, the blade torque measured by the displacement sensor installed in the blade root area increases. If the torque measured on any blade exceeds a second preset threshold, the signal acquisition and processing unit in the blade hub issues a warning to the wind turbine control system, which then changes the wind turbine's operating mode, such as shutting it down.

[0070] Specifically, when the trailing edge and / or leading edge of the blade cracks, the crack will produce an opening and closing effect under the action of wind, and at the same time the stiffness of the blade will decrease, and the displacement of the displacement sensor installed near the section will shrink sharply. When the displacement of any blade sensor is less than the third preset threshold value, the signal acquisition and processing unit will send a warning message to the fan control system, and the fan control system will control the fan to change the operating mode, such as shutting down.

[0071] In specific implementations, the system compares and analyzes the differences in blade root bending moment and / or torque between the three blades of a wind turbine during operation to determine whether there is aerodynamic imbalance between the blades. If aerodynamic imbalance is detected, the signal acquisition and processing unit sends a warning message to the wind turbine control system, which then makes appropriate adjustments. Specifically, this can be achieved through independent pitch control using torque. This means adjusting the blade pitch angle individually to achieve a different target position for each blade, reducing uneven fatigue loads on the impeller surface and preventing harmful accidents.

[0072] In one variation of the present invention, Figure 1 The shown step S103 may include the following steps: obtaining the theoretical bending moment, theoretical torque and / or theoretical displacement output by the static model corresponding to the wind turbine blade under the current blade state and environmental state; comparing the bending moment, the torque and / or the displacement with the theoretical bending moment, the theoretical torque and / or the theoretical displacement respectively to determine the structural state of the wind turbine blade.

[0073] In a specific implementation, a simplified static model of the blade can be built into the signal processing and acquisition processing unit located in the hub, and the characteristic quantities of the real-time bending moment and torque of the blade root, such as amplitude, period, etc., are compared with the real-time theoretical bending moment, theoretical torque and / or theoretical displacement output by the static model. If the difference exceeds the specified range, the structural state of the wind turbine blade is determined. When comparing, the real-time bending moment is compared with the theoretical bending moment, the real-time torque is compared with the theoretical torque, and the real-time displacement is compared with the theoretical displacement. It is also possible to further combine the response of multi-section loads to determine whether the blade has cracks, the location of the cracks, and the size of the cracks, and send this information to the wind turbine control system to achieve real-time detection of blade damage and fault identification.

[0074] In a non-limiting embodiment of the present invention, the wind turbine blades may be calibrated in advance to obtain parameters that require calibration, namely, stiffness coefficient and torque coefficient.

[0075] Specifically, when the wind speed is less than a preset threshold, such as 4 m / s, the blade inclination and cone angles are locked, and the blade azimuth angle is adjusted to a fixed angle, typically 90 or 120 degrees. The blade pitch angle is adjusted from 0 to 90 and then to 0 (or from 90 to 0 and then to 90), and the wavelength of each sensor at different pitch angles is recorded during this process.

[0076] The wavelength of each displacement sensor installed on each blade is converted into an actual displacement component using the following relationship: d = k × (λ) - λ0, where d is the real-time displacement of the displacement sensor, k is the fixed coefficient of the displacement sensor, λ is the real-time wavelength of the displacement sensor, and λ0 is the initial wavelength of the displacement sensor. The initial wavelength is defined as the wavelength of the sensor when the blade bending moment is zero, which can be obtained through a calibration process.

[0077] Theoretical bending moment M for the sensor installation section d =m×g×(r-r0), where M d is the theoretical bending moment of the displacement sensor installation section, r is the distance from the center of gravity of the blade to the blade root, and r0 is the distance from the displacement sensor installation section to the blade root. The theoretical displacement of the sensor installation section can be obtained by the following formula: M =r0×K B -1 ×M d , where: d M K is the theoretical displacement of the sensor installation section, B is the undetermined stiffness coefficient, K B -1 is the inverse matrix of the stiffness coefficient, M dThe actual displacement measured by each sensor is d=d M .

[0078] The above completes the calibration of the displacement sensor for monitoring the bending moment, that is, the calibrated stiffness coefficient K is obtained. B .

[0079] In addition, due to the blade's airfoil structure, the blade's center of gravity is not on the centerline of the blade root circle. By adjusting the pitch angle, the blade root is subjected to gravity and torque. The theoretical torque formula for each blade at different pitch angles can be obtained as: T0 = G × cosφ × cos(Ω) × (r-r0) / cosα, where T0 represents torque, G represents blade gravity, φ represents pitch angle, Ω represents azimuth, α represents the angle between the line connecting the blade root center and the blade's center of gravity and the horizontal centerline of the blade root section, r represents the distance from the blade's center of gravity to the blade root, and r0 represents the distance from the displacement sensor installation section to the blade root.

[0080] The shear stress generated by the torque T0 is: τ0 = T0 / W. Where τ0 represents the shear stress and W represents the torsional section coefficient of the blade at the monitoring section. The wavelength of the sensor measured at a certain pitch angle and azimuth angle is λ τ , the torque coefficient K of the sensor monitoring the torque can be calibrated τ K τ =τ0 / (λ τ -λ0);

[0081] The above steps complete the calibration of the monitoring torque sensor to obtain the calibrated torque coefficient.

[0082] After calibration, the wavelength signals collected by each displacement sensor of the blade can output the bending moment of the blade in the flapping and blade swing directions, as well as the blade torque.

[0083] In a specific embodiment, Figure 1 Step S102 may include the following steps: calculating the displacement of the displacement sensor using the wavelength signals of each displacement sensor; and calculating the bending moment using the displacement, the calibrated stiffness coefficient, and the distance between the displacement sensor installation section and the blade root.

[0084] Furthermore, a first bending moment of the wind turbine blade in the flapping direction and a second bending moment in the swinging direction are calculated based on the bending moment at the current pitch angle, azimuth angle, impeller inclination angle, and blade cone angle. The first bending moment of the wind turbine blade in the flapping direction and the second bending moment in the swinging direction are calculated using the following formula:

[0085] M flap={{Md(-Cos[θ]Sin[δ]Sin[φ]+Cos[δ](Cos[Ω]Sin[θ]Sin[φ]+Cos[φ]Sin[Ω]))}},

[0086] M edge ={{Md(Cos[θ]Cos[φ]Sin[δ]+Cos[δ](-Cos[φ]Cos[Ω]Sin[θ]+Sin[φ]Sin[Ω]))}},

[0087] Among them, M flap is the first bending moment, M edge is the second bending moment, Md is the bending moment, Ω is the blade azimuth angle, φ is the blade pitch angle, δ is the impeller inclination angle, and θ is the blade cone angle.

[0088] In a specific embodiment, Figure 1 Step S102 may include the following steps: calculating the torque using the wavelength signal of the displacement sensor, the torsional section coefficient of the wind turbine blade at the displacement sensor installation section position, and a calibrated torque coefficient.

[0089] Specifically, the torque can be calculated using the following formula:

[0090] T0=K τ ×(λ τ -λ0)×W, where T0 represents the torque, K τ represents the calibrated torque coefficient, λ τ represents the wavelength signal, λ0 represents the initial wavelength of the displacement sensor, and W represents the torsional section coefficient.

[0091] In a non-limiting embodiment of the present invention, a current sensor may be installed in the wind turbine blade. Figure 1 The blade monitoring method shown may also include the following steps: collecting the current collected by a current sensor, wherein the current sensor is installed in the lightning conductor area inside the wind turbine blade; when the collected current indicates that the wind turbine blade is struck by lightning, the degree of damage to the wind turbine blade is determined using the changes in the bending moment, the torque and / or the displacement before and after the lightning strike.

[0092] In practice, the current sensor can monitor the magnitude and frequency of lightning strikes on blades. The MEMS fiber-optic current sensor is a passive sensor that utilizes a wavelength-based principle, integrating a magnetic field encoder, an elastic support, an optical reflective micromirror, and light input and output waveguides directly onto a tiny chip. This enables real-time, all-optical monitoring of high-current, high-frequency lightning currents. It offers advantages such as no power supply required for the probe or transmission line, immunity to electromagnetic interference, high resolution, simple installation requirements, high reliability, and long-distance transmission without compromising detection accuracy.

[0093] Specifically, the lightning conductor area refers to the area where the lightning conductor is located inside the blade. For example, the current sensor can be installed near the lightning conductor inside the blade, typically on the lightning conductor. For example, the current sensor is installed near the lightning conductor 2m away from the blade tip. The signal lead-out cable of the current sensor is an optical fiber, which can ensure that the sensor can still be used normally in lightning weather and there is no safety hazard of lightning conduction. The current sensor adopts wavelength signal encoding. The measurement accuracy is not affected by the bending loss of the optical cable, the transmission distance, and the fluctuation of the light source, and can maintain high-precision measurement for a long time.

[0094] Furthermore, a signal acquisition and processing unit, mounted on the blade hub and equipped with a built-in wavelength-tunable laser, collects the current signals measured by each sensor in real time via optical fiber transmission. The acquisition and processing unit incorporates processing algorithms and storage space, and through real-time processing of the current signals, it can determine the blade lightning current magnitude and number of strikes.

[0095] In a specific application, when a lightning strike causes blade cracking damage, the blade torque and / or bending moment measured by the fiber optic displacement sensor changes. If the magnitude of any blade bending moment or torque change exceeds a threshold, the fiber optic signal acquisition and processing unit sends a warning to the wind turbine control system, which then changes the wind turbine's operating mode, such as shutting it down.

[0096] The embodiment of the present invention combines a current sensor and a displacement sensor. The current sensor records the magnitude and frequency of lightning current, and the displacement sensor records the change in blade bending moment during the lightning strike, thereby effectively improving the detection accuracy of lightning damage and cracking.

[0097] Please refer to Figure 4 The embodiment of the present invention further discloses a fan blade monitoring device. The fan blade monitoring device 40 may include:

[0098] An acquisition module 401 is configured to acquire wavelength signals collected by a plurality of displacement sensors installed at a plurality of cross-sectional positions within a wind turbine blade;

[0099] A calculation module 402 is configured to calculate the bending moment, torque and / or displacement of the wind turbine blade at the plurality of cross-sectional positions based on the wavelength signals of the displacement sensors;

[0100] The state determination module 403 is configured to determine the structural state of the wind turbine blade according to the bending moment, the torque and / or the displacement.

[0101] In an embodiment of the present invention, displacement sensors are installed at multiple cross-sectional locations within a wind turbine blade, capable of measuring changes in displacement, bending moment, and / or torque at different locations on the blade. This allows for more accurate blade status monitoring by combining changes in multiple physical quantities to determine the blade's structural state. Furthermore, in an embodiment of the present invention, displacement sensors are used to collect wavelength information. During transmission, wavelength signals are not affected by external factors such as transmission distance, light source fluctuations, and fiber optic cable bends, thereby enabling further accurate monitoring of blade status.

[0102] For more information about the working principle and working mode of the fan blade monitoring device 40, please refer to Figures 1 to 2 The relevant description in will not be repeated here.

[0103] The wind turbine blade monitoring device 40 (virtual device) may be, for example, a chip or a chip module.

[0104] Regarding the various modules / units contained in the various devices and products described in the above embodiments, they can be software modules / units, hardware modules / units, or partly software modules / units and partly hardware modules / units. For example, for various devices and products applied to or integrated in a chip, the various modules / units contained therein can all be implemented in the form of hardware such as circuits, or at least some of the modules / units can be implemented in the form of software programs, which run on the processor integrated inside the chip, and the remaining (if any) modules / units can be implemented in the form of hardware such as circuits; for various devices and products applied to or integrated in a chip module, the various modules / units contained therein can all be implemented in the form of hardware such as circuits, and different modules / units can be located in the same component of the chip module (such as a chip, circuit module, etc.) or in different components, or at least some of the modules / units can be implemented in the form of hardware such as circuits. The element can be implemented in the form of a software program, which runs on the processor integrated inside the chip module, and the remaining (if any) modules / units can be implemented in the form of hardware such as circuits; for various devices and products applied to or integrated in the terminal, the various modules / units contained therein can be implemented in the form of hardware such as circuits, and different modules / units can be located in the same component (for example, chip, circuit module, etc.) or different components in the terminal, or, at least some modules / units can be implemented in the form of a software program, which runs on the processor integrated inside the terminal, and the remaining (if any) modules / units can be implemented in the form of hardware such as circuits.

[0105] The embodiment of the present invention further discloses a storage medium, which is a computer-readable storage medium having a computer program stored thereon. When the computer program is run, the computer program can execute Figure 1 The steps of the method shown in . The storage medium may include ROM, RAM, magnetic disk or optical disk, etc. The storage medium may also include non-volatile memory or non-transitory memory, etc.

[0106] An embodiment of the present invention further discloses a wind turbine comprising multiple blades, typically three blades. The wind turbine may include one or more displacement sensors disposed within at least one of the wind turbine blades. The wind turbine also includes a processor coupled to the displacement sensor, configured to execute the steps of the wind turbine blade monitoring method. Specifically, the processor includes the aforementioned signal acquisition and processing unit.

[0107] It should be noted that the displacement sensor and the current sensor modulate (or encode) the collected wavelength signals and transmit them through optical fibers; accordingly, the processor may further include a signal demodulation module, which demodulates the modulated signals of the displacement sensor and the current sensor to obtain wavelength signals.

[0108] It should be understood that the term "and / or" in this document simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document indicates that the related objects are in an "or" relationship.

[0109] The term "plurality" used in the embodiments of the present application refers to two or more.

[0110] The first, second, etc. descriptions appearing in the embodiments of this application are only for illustration and distinction of the description objects. There is no order, nor does it indicate any special limitation on the number of devices in the embodiments of this application, and cannot constitute any limitation on the embodiments of this application.

[0111] The "connection" appearing in the embodiments of the present application refers to various connection methods such as direct connection or indirect connection to achieve communication between devices, and the embodiments of the present application do not impose any limitations on this.

[0112] It should be understood that in the embodiments of the present application, the processor may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0113] It should also be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0114] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via wired or wireless means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0115] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0116] In the several embodiments provided in this application, it should be understood that the disclosed methods, devices, and systems can be implemented in other ways. For example, the device embodiments described above are merely schematic; for example, the division of the units is merely a logical function division, and there may be other division methods in actual implementation; for example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection of devices or units, which may be electrical, mechanical, or other forms.

[0117] The units described as separate components may or may not be physically separate, and 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 these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0118] In addition, the functional units in various embodiments of the present invention may be integrated into a single processing unit, each unit may be physically included separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional units.

[0119] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to perform some steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, an optical disk, and other media that can store program code.

[0120] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention should be based on the scope defined by the claims.

Claims

1. A method for monitoring fan blades of a wind turbine, characterized in that: include: Acquiring wavelength signals collected by a plurality of displacement sensors, wherein the plurality of displacement sensors are installed at a plurality of cross-sectional positions within a wind turbine blade; Calculating the bending moment, torque and / or displacement of the wind turbine blade at the plurality of cross-sectional positions according to the wavelength signals of the respective displacement sensors; determining a structural state of the wind turbine blade according to the bending moment, the torque and / or the displacement; collecting current collected by a current sensor, wherein the current sensor is installed in the lightning conductor area inside the wind turbine blade; When the collected current indicates that the wind turbine blade is struck by lightning, the degree of damage to the wind turbine blade is determined by using the changes in the bending moment, the torque, and / or the displacement before and after the lightning strike; Determining the structural state of the wind turbine blade according to the bending moment, the torque and / or the displacement includes: Obtaining theoretical bending moment, theoretical torque and / or theoretical displacement output by a statics model corresponding to the wind turbine blade under current blade state and environmental state; comparing the bending moment, the torque and / or the displacement with a theoretical bending moment, a theoretical torque and / or a theoretical displacement, respectively, to determine a structural state of the wind turbine blade; Also includes: According to the bending moment, the first bending moment of the wind turbine blade in the flapping direction and the second bending moment in the swinging direction are calculated under the current pitch angle, azimuth angle, impeller inclination angle and blade cone angle; the first bending moment and the second bending moment are calculated by the following formula: M flap ={{Md(-Cos[θ]Sin[δ]Sin[φ]+Cos[δ](Cos[Ω]Sin[θ]Sin[φ]+Cos[φ]Sin[Ω]))}}, M edge ={{Md(Cos[θ]Cos[φ]Sin[δ]+Cos[δ](-Cos[φ]Cos[Ω]Sin[θ]+Sin[φ]Sin[Ω]))}}, Among them, M flap is the first bending moment, M edge is the second bending moment, Md is the bending moment, Ω is the blade azimuth angle, φ is the blade pitch angle, δ is the impeller inclination angle, and θ is the blade cone angle.

2. The method for monitoring fan blades of a wind turbine according to claim 1, characterized in that: The plurality of cross-sectional positions are selected from the blade root of the fan blade, the maximum chord length of the fan blade, and the diameter change point of the airfoil cross section.

3. The method for monitoring fan blades of a wind turbine according to claim 1, characterized in that: Determining the structural state of the wind turbine blade according to the bending moment, the torque and / or the displacement includes: If the bending moment reaches a first preset threshold and / or the torque reaches a second preset threshold, it is determined that the wind turbine blade is cracked; and / or, if the displacement is less than a third preset threshold, determining that the wind turbine blade is cracked; And / or, if the difference between the bending moments and torques of different wind turbine blades reaches a fourth preset threshold, it is determined that the state of the wind turbine blade is aerodynamically unbalanced.

4. The method for monitoring fan blades of a wind turbine according to claim 1, characterized in that: Calculating the bending moment of the fan blade at the plurality of cross-sectional positions according to the wavelength signals of the displacement sensors includes: Calculating the displacement of the displacement sensor using the wavelength signals of each displacement sensor; The bending moment is calculated using the displacement, a calibrated stiffness coefficient, and a distance between a displacement sensor installation section and a blade root.

5. The method for monitoring fan blades of a wind turbine according to claim 4, characterized in that: The calibrated stiffness coefficient is obtained by calibrating using the following steps: When the wind speed is less than a preset threshold, fixing the azimuth angle and pitch angle of the wind turbine blades and obtaining the wavelength of each displacement sensor; converting the wavelength into an actual displacement; Calculating the theoretical bending moment based on the gravity of the blade, the distance between the displacement sensor installation section and the blade root, and the distance from the center of gravity of the fan blade to the blade root; The stiffness coefficient to be calibrated is calculated using the mapping relationship between the actual displacement, the theoretical bending moment, and the stiffness coefficient to be calibrated. The mapping relationship is expressed by the following formula: M =r0×K B -1 ×M d , where d M represents the actual displacement, K B -1 Indicates the stiffness coefficient to be calibrated, M d represents the theoretical bending moment; r0 is the distance from the displacement sensor installation section to the blade root.

6. The method for monitoring fan blades of a wind turbine according to claim 1, characterized in that: Calculating the torque of the fan blade at the plurality of cross-sectional positions according to the wavelength signals of the displacement sensors includes: The torque is calculated using the wavelength signal of the displacement sensor, the torsional section coefficient of the fan blade at the displacement sensor installation section position, and a calibrated torque coefficient.

7. The method for monitoring fan blades of a wind turbine according to claim 6, characterized in that: The torque is calculated using the following formula: T0=K τ ×(λ τ -λ0)×W, where T0 represents the torque, K τ represents the calibrated torque coefficient, λ τ represents the wavelength signal, λ0 represents the initial wavelength of the displacement sensor, and W represents the torsional section coefficient.

8. The method for monitoring fan blades of a wind turbine according to claim 7, characterized in that: The calibrated torque coefficient is obtained by calibrating using the following steps: When the wind speed is less than a preset threshold, fixing the azimuth angle and pitch angle of the wind turbine blades, and obtaining the wavelengths collected by each displacement sensor; Calculating the theoretical torque generated by the gravity of the wind turbine blade at the azimuth angle and pitch angle; Calculating the shear stress generated by the theoretical torque according to the theoretical torque and the torsional section coefficient; The torque coefficient to be calibrated is calculated according to a mapping relationship between the torque coefficient to be calibrated, the shear stress, and the wavelength.

9. The method for monitoring fan blades of a wind turbine according to claim 1, characterized in that: The displacement sensor and the current sensor are both passive sensors.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for monitoring a wind turbine blade of a wind turbine according to any one of claims 1 to 9 are executed.

11. A wind turbine generator, comprising a wind turbine blade, characterized in that: Also includes: One or more displacement sensors are disposed inside at least one wind turbine blade of the wind turbine; A processor is coupled to the displacement sensor, and the processor is used to execute the steps of the wind turbine blade monitoring method of any one of claims 1 to 9.

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