Wind turbine blade damage location method and related apparatus

Abstract

The application discloses a wind turbine blade damage positioning method and related equipment, and relates to the technical field of intelligent operation and maintenance. The method comprises the following steps: determining first spatial position modeling of a high-frequency loudspeaker and second spatial position modeling at a damage position based on an initial position angle and a rotation angular velocity of a wind turbine blade; calculating first time delay information based on the first spatial position modeling and the second spatial position modeling; determining second time delay information based on third spatial position modeling of a target microphone sensor and the second spatial position modeling; determining target physical modeling according to the Doppler effect based on the first time delay information and the second time delay information; determining sound excitation signal energy based on the target physical modeling and a rotation window function, establishing a microphone array sound excitation signal energy maximization criterion, and determining damage position information through parameter iteration. According to the embodiment of the application, the damage position of the wind turbine blade can be accurately positioned.

Description

Technical Field

[0001] This application belongs to the field of intelligent operation and maintenance technology, and in particular relates to a method for locating damage to wind turbine blades and related equipment. Background Technology

[0002] Currently, wind turbine blades are the core components of the unit, and their aerodynamic performance directly determines the efficiency of wind energy capture and conversion. During operation, the blades continuously drive the transmission system and generator to output electrical energy; therefore, their health is crucial to power generation efficiency and system stability. Due to long-term exposure to a complex environment, blades must withstand various external forces such as wind, sand, rain, snow, moisture erosion, and gust impacts, while also experiencing significant time-varying load effects. These factors can easily induce structural damage to the blades, such as cracks, erosion, and even breakage. Severe damage can not only lead to unit shutdown but also threaten the safety of personnel and equipment. Therefore, conducting damage localization of wind turbine blades is of great significance for ensuring the safe and reliable operation of wind turbine units.

[0003] However, existing blade defect detection methods still have limitations in practical applications. For example, traditional non-destructive testing methods such as ultrasonic and radiographic testing often rely on contact or specific operating conditions, making it difficult to meet the needs of online monitoring. Vibration analysis-based detection methods are highly sensitive to operating conditions, and the detection results are prone to deviation. On the other hand, detection methods using drones or computer vision are overly dependent on external environmental conditions, and their stability is limited. When faced with complex and varied blade damage types, these detection methods often suffer from insufficient detection accuracy and limited detection range, making it difficult to comprehensively and accurately locate blade damage.

[0004] Therefore, given the complex external environment faced by wind turbine blades, establishing a highly applicable and accurate damage location mechanism is of great significance for effectively ensuring the stability and reliability of wind turbine blade operation. Summary of the Invention

[0005] This application provides a method and related equipment for locating damage to wind turbine blades, which can more comprehensively and accurately locate damage to wind turbine blades for different users, thereby effectively improving the overall efficiency of wind turbine blade damage location and increasing user satisfaction.

[0006] In a first aspect, embodiments of this application provide a method for locating damage to wind turbine blades, the method comprising: Based on the initial position angle and rotational angular velocity of the wind turbine blade, the first spatial position model of the high-frequency loudspeaker and the second spatial position model of the damaged location of the wind turbine blade are determined. The high-frequency loudspeaker is set at the root of the wind turbine blade and is used to emit acoustic excitation signals. Based on the first spatial position modeling and the second spatial position modeling, the first time delay information of the acoustic excitation signal from the blade root position of the wind turbine blade to the damage position of the wind turbine blade is calculated. Based on the third spatial position modeling and the second spatial position modeling of the target microphone sensor, the second time delay information of the acoustic excitation signal propagating from the damaged location of the wind turbine blade to the target microphone sensor is determined. The target microphone sensor is installed in the wind turbine to receive the acoustic excitation signal. Based on the first and second time delay information, the target physical model is determined according to the Doppler effect to obtain the acoustic excitation signal collected by the target microphone sensor. Based on the target physical modeling of the acoustic excitation signal and the rotating window function, the energy of the acoustic excitation signal collected by the target microphone sensor is determined, and the maximization criterion of the acoustic excitation signal energy of the microphone array is established. The damage location information of the wind turbine blade is determined through parameter iteration.

[0007] In some possible implementations, based on the initial position angle and rotational angular velocity of the wind turbine blades, a first spatial position modeling of the high-frequency loudspeaker and a second spatial position modeling at the location of damage on the wind turbine blades are determined, including: The rotation angle of the wind turbine blades is determined based on the initial position angle and rotational angular velocity of the wind turbine blades. Based on the rotation angle, the first spatial position model of the high-frequency loudspeaker and the second spatial position model of the damaged location of the wind turbine blade are determined.

[0008] In some possible implementations, determining a first spatial location model of the high-frequency loudspeaker and a second spatial location model of the damaged location on the wind turbine blade, based on the rotation angle, includes: Based on the rotation angle, the distance from the high-frequency loudspeaker to the wind turbine's shaft, and a first formula, a first spatial position model is determined. The first formula includes: And / or, based on the rotation angle and the second formula, determine the second spatial position model, the second formula including: in, Modeling the first spatial location, This is the distance from the high-frequency loudspeaker to the shaft of the wind turbine. For rotation angle, Modeling the second spatial location, This represents the distance between the blade root and the location of damage on a hypothetical wind turbine blade.

[0009] In some possible implementations, based on first spatial location modeling and second spatial location modeling, the first time delay information of the acoustic excitation signal from the blade root to the damage location on the wind turbine blade is calculated, including: Based on the first spatial location modeling and the second spatial location modeling, the first time delay information is calculated using a third formula; the third formula includes: in, This is the first delay information. For the speed of sound, Modeling the first spatial location, Model the second spatial location.

[0010] In some possible implementations, based on third and second spatial location modeling of the target microphone sensor, a second time delay information is determined regarding the propagation of the acoustic excitation signal from the damaged location of the wind turbine blade to the target microphone sensor, including: Based on third-space location modeling and second-space location modeling, the second time delay information is determined by a fourth formula; the fourth formula includes: in, This is the second time delay information. Modeling third-space location, Modeling the second spatial location, The speed of sound.

[0011] In some possible implementations, the target microphone sensor is mounted on the tower of the wind turbine. Before determining the second time delay information of the acoustic excitation signal propagating from the damaged location of the wind turbine blade to the target microphone sensor, the method further includes: Based on the radius of the target microphone sensor projected onto the origin of the spatial coordinates on the tower plane, the angular position of the target microphone sensor relative to the rotation axis of the wind turbine, and the relative height of the target microphone sensor, the third spatial position model is determined by the fifth formula. The fifth formula includes: in, Modeling third-space location, Let the radius be the radius of the target microphone sensor projected onto the origin of the spatial coordinate system on the tower plane. The angular position of the target microphone sensor relative to the wind turbine's axis of rotation. The relative height of the target microphone sensor.

[0012] In some possible implementations, based on first and second time delay information, a target physical model is determined according to the Doppler effect to determine the acoustic excitation signal acquired by the target microphone sensor, including: Based on the first time delay information, the second time delay information, the initial audio signal of the acoustic excitation signal, the damage transmission coefficient, the frequency of the acoustic excitation signal, the rotational linear velocity at the damage location, and the angular position of the target microphone sensor relative to the rotation axis at time t, the target physical model of the acoustic excitation signal collected by the target microphone sensor is determined according to the Doppler effect.

[0013] In some possible implementations, based on first time delay information, second time delay information, the initial audio signal of the acoustic excitation signal, the damage transmission coefficient, the frequency of the acoustic excitation signal, the rotational linear velocity at the damage location, and the angular position of the target microphone sensor relative to the axis of rotation at time t, a target physical model is determined according to the Doppler effect, including: Based on the first time delay information, the second time delay information, the initial audio signal of the acoustic excitation signal, the damage transmission coefficient, the frequency of the acoustic excitation signal, the rotational linear velocity at the damage location, and the angular position of the target microphone sensor relative to the rotation axis at time t, the sixth formula is constructed according to the Doppler effect to determine the target physical model of the acoustic excitation signal collected by the target microphone sensor. The sixth formula includes: in, To model the physical properties of the target, The damage transmission coefficient, The initial audio signal is the acoustic excitation signal. The frequency of the acoustic excitation signal, This is the first delay information. This is the second time delay information. The rotational linear velocity at the location of the damage. For the speed of sound, Let be the angular position of the target microphone sensor relative to the rotation axis at time t. This is environmental noise.

[0014] In some possible implementations, the energy of the acoustic excitation signal acquired by the target microphone sensor is determined based on target physical modeling of the acoustic excitation signal and a rotating window function, including: Based on the target physical modeling of the acoustic excitation signal and the rotating window function, the energy of the acoustic excitation signal collected by the target microphone sensor is determined by the seventh formula; the seventh formula includes: in, The energy of the acoustic excitation signal. Physical modeling of the target for acoustic excitation signals. This is a function for rotating the window.

[0015] In some possible implementations, M microphone sensors are installed on the tower of the wind turbine, and the M microphone sensors form a microphone array. The target microphone sensor is the i-th microphone sensor among the M microphone sensors, where i and M are greater than or equal to 1, and i is less than or equal to M. A criterion for maximizing the energy of the acoustic excitation signal from the microphone array is established, and the damage location information of the wind turbine blades is determined through parameter iteration, including: Based on the acoustic excitation signal energy, the weighted energy of the array acoustic excitation signal is established using the eighth formula; the eighth formula includes: in, Weighted energy for the array acoustic excitation signal The energy of the acoustic excitation signal. For the first i Weights of each microphone sensor; Based on the weighted energy of the array acoustic excitation signal, a criterion for maximizing the energy of the microphone array acoustic excitation signal is established using the ninth formula; the ninth formula includes: in, For estimating the damage angle of wind turbine blades, For estimating the damage distance of wind turbine blades; Based on the criterion of maximizing the energy of the acoustic excitation signal from the microphone array, the damage location information of the wind turbine blade is determined through parameter iteration using the tenth formula; the tenth formula includes: in, Let this be the hypothetical distance between the blade root and the location of the damage on a wind turbine blade. This provides information on the location of damage to wind turbine blades.

[0016] In some possible implementations, the initial audio signal of the acoustic excitation signal emitted by the high-frequency loudspeaker is: in, The initial audio signal, The frequency of the acoustic excitation signal, The amplitude of the acoustic excitation signal. .

[0017] Based on the same inventive concept, in a second aspect, embodiments of this application provide a wind turbine blade damage location device, which includes: The first determining module is used to determine the first spatial position modeling of the high-frequency loudspeaker and the second spatial position modeling of the damaged location of the wind turbine blade based on the initial position angle and rotational angular velocity of the wind turbine blade. The high-frequency loudspeaker is set at the root of the wind turbine blade and is used to emit acoustic excitation signals. The first calculation module is used to calculate the first time delay information of the acoustic excitation signal from the root position of the wind turbine blade to the damage position of the wind turbine blade based on the first spatial position modeling and the second spatial position modeling. The second determining module is used to determine the second time delay information of the acoustic excitation signal propagating from the damaged location of the wind turbine blade to the target microphone sensor based on the third spatial position modeling and the second spatial position modeling of the target microphone sensor. The target microphone sensor is set in the wind turbine to receive the acoustic excitation signal. The third determining module is used to determine the target physical model based on the first time delay information and the second time delay information, according to the Doppler effect, the acoustic excitation signal collected by the target microphone sensor. The fourth determination module is used to determine the energy of the acoustic excitation signal collected by the target microphone sensor based on the target physical modeling and rotating window function, and to establish the maximization criterion of the acoustic excitation signal energy of the microphone array. The damage location information of the wind turbine blade is determined through parameter iteration.

[0018] Thirdly, embodiments of this application provide a wind turbine blade damage location device, which includes: Processor and memory storing computer program instructions; When the processor executes the computer program instructions, it implements the wind turbine blade damage location method provided in any of the embodiments of this application described above.

[0019] Fourthly, embodiments of this application provide a computer storage medium storing computer program instructions, which, when executed by a processor, implement the wind turbine blade damage location method provided in any of the above embodiments of this application.

[0020] Fifthly, embodiments of this application provide a computer program product in which instructions are executed by a processor of an electronic device, causing the electronic device to perform the wind turbine blade damage location method provided in any of the embodiments of this application described above.

[0021] This application provides a method and related equipment for locating damage to a wind turbine blade. A high-frequency loudspeaker for emitting acoustic excitation signals is installed at the root of the wind turbine blade. A target microphone sensor for receiving the acoustic excitation signals is installed in the wind turbine. Based on this, a first spatial position model of the high-frequency loudspeaker and a second spatial position model of the damage location on the wind turbine blade are determined based on the initial position angle and rotational angular velocity of the wind turbine blade. Based on the first and second spatial position models, a first time delay information is calculated from the wind turbine blade root to the damage location. Based on the third and second spatial position models of the target microphone sensor, a second time delay information is determined from the damage location to the target microphone sensor. Based on the first and second time delay information, a target physical model of the acoustic excitation signal collected by the target microphone sensor is determined according to the Doppler effect. Based on the target physical modeling of the acoustic excitation signal and the rotating window function, the energy of the acoustic excitation signal collected by the target microphone sensor is determined, and the maximization criterion of the acoustic excitation signal energy of the microphone array is established. The damage location information of the wind turbine blade is determined through parameter iteration.

[0022] As described above, the wind turbine blade damage localization method and related equipment of this application utilize the time delay characteristics and Doppler effect of the acoustic excitation signal to complete the target physical modeling of the acoustic excitation signal collected by the target microphone sensor. To reduce the interference of multi-source noise, a rotating window function is used to enhance the acoustic excitation signal collected by the microphone sensor. Finally, a criterion for maximizing the energy of the microphone array acoustic excitation signal is established, and the damage location of the wind turbine blade is ultimately determined through parameter iteration. This solution establishes a highly applicable and accurate damage localization mechanism for the complex external environment faced by wind turbine blades. It can accurately locate the spatial position of wind turbine blade damage, providing solid technical support for ensuring the stability and reliability of wind turbine blade operation, and effectively guaranteeing the stability and reliability of wind turbine blade operation. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a schematic flowchart of a wind turbine blade damage location method provided in an embodiment of this application; Figure 2 This is a schematic diagram of a scenario flow for a wind turbine blade damage location method provided in an embodiment of this application; Figure 3 This is an example of the field installation of the speaker and microphone sensor provided in one embodiment of this application; Figure 4 This is a rotating window function curve provided in an embodiment of this application; Figure 5 This is a result of wind turbine blade defect location provided in an embodiment of this application; Figure 6 This is a comparison of the detection accuracy results of different methods provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of a wind turbine blade damage location device provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of a wind turbine blade damage location device provided in an embodiment of this application. Detailed Implementation

[0025] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0026] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0027] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0028] To address the problems in the prior art, this application provides a method and related equipment for locating damage to wind turbine blades. It should be noted that the embodiments provided in this application are not intended to limit the scope of this application.

[0029] The following section first introduces the wind turbine blade damage location method provided in the embodiments of this application.

[0030] Figure 1 A flowchart illustrating a wind turbine blade damage location method according to an embodiment of this application is shown. This wind turbine blade damage location method is applied to electronic equipment, which may include a server or user terminal, etc. Figure 1 As shown, the method for locating damage to wind turbine blades includes the following steps: S110, based on the initial position angle and rotational angular velocity of the wind turbine blade, determine the first spatial position model of the high-frequency loudspeaker and the second spatial position model of the damaged location of the wind turbine blade. The high-frequency loudspeaker is set at the root of the wind turbine blade and is used to emit acoustic excitation signals. S120, based on the first spatial position modeling and the second spatial position modeling, calculate the first time delay information of the acoustic excitation signal from the blade root position of the wind turbine blade to the damage position of the wind turbine blade. S130, based on the third spatial position modeling and the second spatial position modeling of the target microphone sensor, determine the second time delay information of the acoustic excitation signal propagating from the damaged location of the wind turbine blade to the target microphone sensor. The target microphone sensor is installed in the wind turbine to receive the acoustic excitation signal. S140, Based on the first time delay information and the second time delay information, determine the target physical model of the acoustic excitation signal collected by the target microphone sensor according to the Doppler effect; S150, based on the target physical modeling of the acoustic excitation signal and the rotating window function, determines the energy of the acoustic excitation signal collected by the target microphone sensor, establishes the maximization criterion of the acoustic excitation signal energy of the microphone array, and determines the damage location information of the wind turbine blade through parameter iteration.

[0031] This application provides a method for locating damage to a wind turbine blade. A high-frequency loudspeaker for emitting acoustic excitation signals is installed at the root of the wind turbine blade. A target microphone sensor for receiving the acoustic excitation signals is installed within the wind turbine. Based on this, a first spatial position model of the high-frequency loudspeaker and a second spatial position model of the damage location on the wind turbine blade are determined based on the initial position angle and rotational angular velocity of the wind turbine blade. Based on the first and second spatial position models, a first time delay information is calculated from the blade root to the damage location of the acoustic excitation signal. Based on the third and second spatial position models of the target microphone sensor, a second time delay information is determined from the damage location to the target microphone sensor. Based on the first and second time delay information, a target physical model of the acoustic excitation signal collected by the target microphone sensor is determined according to the Doppler effect. Based on the target physical modeling of the acoustic excitation signal and the rotating window function, the energy of the acoustic excitation signal collected by the target microphone sensor is determined, and the maximization criterion of the acoustic excitation signal energy of the microphone array is established. The damage location information of the wind turbine blade is determined through parameter iteration.

[0032] As described above, the wind turbine blade damage localization method of this application utilizes the time delay characteristics and Doppler effect of the acoustic excitation signal to complete the target physical modeling of the acoustic excitation signal collected by the target microphone sensor. To reduce the interference of multi-source noise, a rotating window function is used to enhance the acoustic excitation signal collected by the microphone sensor. Finally, a criterion for maximizing the energy of the microphone array acoustic excitation signal is established, and the damage location of the wind turbine blade is ultimately determined through parameter iteration. Thus, this scheme establishes a highly applicable and accurate damage localization mechanism for the complex external environment faced by wind turbine blades. It can accurately locate the spatial position of wind turbine blade damage, providing solid technical support for ensuring the stability and reliability of wind turbine blade operation, and effectively guaranteeing the stability and reliability of wind turbine blade operation.

[0033] The specific implementation methods of steps 110 to 150 above are described in detail below.

[0034] In S110, in a specific implementation, a high-frequency loudspeaker is installed at the root of the wind turbine blade, and the loudspeaker is used to emit acoustic excitation signals. For example, multiple blades of the wind turbine need to have high-frequency loudspeakers installed at their roots, and the generating surface of the loudspeaker needs to face the blade cavity.

[0035] When an acoustic excitation signal is applied to a blade, if there are internal damages such as cracks or delamination, the sound waves will scatter and reflect at the damaged areas during propagation. Therefore, analyzing changes in the acoustic excitation signal can effectively determine the presence of damage.

[0036] In some possible embodiments, the high-frequency loudspeaker is directly powered by a pitch control unit installed in the wind turbine hub, and the operating status of the high-frequency loudspeaker is controlled by a timer switch.

[0037] Optionally, according to some embodiments of this application, the initial audio signal of the acoustic excitation signal emitted by the high-frequency loudspeaker is given by the following formula (1): in, The initial audio signal, The frequency of the acoustic excitation signal, The amplitude of the acoustic excitation signal. .

[0038] In this embodiment, the frequency range of the active acoustic excitation signal emitted by the high-frequency loudspeaker is 1kHz to 5kHz. Considering the actual characteristics of the wind turbine blade material and structure, an acoustic excitation signal of 1kHz to 5kHz within this frequency range helps to more effectively achieve damage identification and location analysis.

[0039] Optionally, according to some embodiments of this application, determining the first spatial position model of the high-frequency loudspeaker and the second spatial position model at the damaged location of the wind turbine blade based on the initial position angle and rotational angular velocity of the wind turbine blade may include: The rotation angle of the wind turbine blades is determined based on the initial position angle and rotational angular velocity of the wind turbine blades. Based on the rotation angle, the first spatial position model of the high-frequency loudspeaker and the second spatial position model of the damaged location of the wind turbine blade are determined.

[0040] In this embodiment, the initial position angle of the wind turbine blade can be measured by an angle sensor. In a wind turbine, the angle sensor is typically installed at the blade root and can be used to measure the blade angle. The angle sensor can be, for example, a potentiometer-type, encoder-type, or magnetic angle sensor.

[0041] The rotational angular velocity of the aforementioned wind turbine blades can be measured using a velocity sensor. Velocity sensors can include photoelectric sensors, magnetoelectric sensors, and Hall effect sensors.

[0042] As an example, let's set the initial position angle of the wind turbine blades as... Then in t The rotation angle of the blade at any given time can be found in formula (2): in, In order to be in t The rotation angle of the wind turbine blades at all times. The rotational angular velocity of the wind turbine blades. This represents the initial position angle of the wind turbine blades.

[0043] More specifically, determining the first spatial location model of the high-frequency loudspeaker and the second spatial location model of the damaged location of the wind turbine blade based on the rotation angle can include: Based on the rotation angle, the distance from the high-frequency loudspeaker to the wind turbine shaft, and the first formula, the first spatial position model is determined. The first formula can be as follows: (3) And / or, based on the rotation angle and the second formula, determine the second spatial position model, the second formula may include: in, Modeling the first spatial location, This is the distance from the high-frequency loudspeaker to the shaft of the wind turbine. For rotation angle, Modeling the second spatial location, This represents the distance between the blade root and the location of damage on a hypothetical wind turbine blade.

[0044] In S120, specifically, to analyze the physical characteristics of the acoustic excitation signal transmitted from the damaged location on the blade, it is first necessary to calculate the time delay from the emission of the acoustic excitation signal from the blade root to its propagation to the damaged location. Based on this, in this step, the first spatial position of the high-frequency loudspeaker and the second spatial position of the damaged location on the wind turbine blade are modeled using the time delay characteristics of sound propagation, and the first time delay information from the emission of the acoustic excitation signal from the blade root to its propagation to the damaged location is calculated.

[0045] Optionally, according to some embodiments of this application, calculating the first time delay information of the acoustic excitation signal from the blade root position of the wind turbine blade to the damage position of the wind turbine blade, based on the first spatial position modeling and the second spatial position modeling, may include: Based on the first spatial location modeling and the second spatial location modeling, the first time delay information is calculated using the third formula; the third formula can be shown as formula (5) below: in, This is the first delay information. For the speed of sound, Modeling the first spatial location, Model the second spatial location.

[0046] Therefore, after calculating the first time delay information mentioned above, the acoustic excitation signal at the location of the wind turbine blade damage can be obtained, expressed as formula (6): In the formula, The damage transmission coefficient is determined by the material of the wind turbine blade.

[0047] In S130, specifically, by utilizing the time delay characteristics of sound propagation, the second time delay information of the sound excitation signal propagating from the damaged location of the wind turbine blade to the target microphone sensor is determined based on the third spatial position modeling of the target microphone sensor and the second spatial position modeling of the damaged location of the wind turbine blade.

[0048] In this embodiment, the target microphone sensor is installed in the wind turbine to receive acoustic excitation signals.

[0049] In some alternative embodiments, more specifically, multiple microphone sensors are evenly mounted on the tower from top to bottom, covering the entire length of the blades, for receiving acoustic excitation signals.

[0050] Thus, the comprehensive coverage and high-precision positioning of multiple microphone sensors significantly improve the accuracy and reliability of blade damage detection and location. This also facilitates easier installation and data processing.

[0051] As an example, a microphone array is formed by multiple uniformly installed microphone sensors, and the microphone sensors are uniformly installed from top to bottom of the tower, covering the entire length of the wind turbine blade. The number of microphone sensors can be calculated from this, as shown in the following formula (7): In the formula, The number of microphone sensors, L The length of the wind turbine blade. Install spacing for the microphone sensor.

[0052] Optionally, according to some embodiments of this application, the target microphone sensor is mounted on the tower of the wind turbine; Before determining the second time delay information of the acoustic excitation signal propagating from the damaged location of the wind turbine blade to the target microphone sensor, the method may further include: Based on the radius of the target microphone sensor projected onto the origin of the spatial coordinates on the tower plane, the angular position of the target microphone sensor relative to the rotation axis of the wind turbine, and the relative height of the target microphone sensor, the third spatial position model is determined by the fifth formula. The fifth formula can be represented by the following formula (8): in, Modeling third-space location, Let the radius be the radius of the target microphone sensor projected onto the origin of the spatial coordinate system on the tower plane. The angular position of the target microphone sensor relative to the wind turbine's axis of rotation. The relative height of the target microphone sensor. The target microphone sensor is, for example, the [number]th of a plurality of microphone sensors. i One microphone sensor.

[0053] Optionally, according to some embodiments of this application, determining the second time delay information of the acoustic excitation signal propagating from the damaged location of the wind turbine blade to the target microphone sensor based on the third spatial location modeling and the second spatial location modeling of the target microphone sensor may include: Based on third-space location modeling and second-space location modeling, the second time delay information is determined by the fourth formula; the fourth formula can be shown as formula (9) below: in, This is the second time delay information. Modeling third-space location, Modeling the second spatial location, The speed of sound.

[0054] In S140, specifically, based on the first time delay information and the second time delay information, the target physical model is determined according to the Doppler effect to determine the acoustic excitation signal collected by the target microphone sensor.

[0055] Optionally, according to some embodiments of this application, since the wind turbine blades are in a rotating state, the location of the damage to the blades is determined. The linear velocity of rotation at a point can be expressed by the following formula (10): in, The rotational linear velocity at the location of the damage. The rotational angular velocity of the wind turbine blades. This represents the distance between the blade root and the location of damage on a hypothetical wind turbine blade.

[0056] Optionally, according to some embodiments of this application, determining the target physical model of the acoustic excitation signal collected by the target microphone sensor based on the first time delay information and the second time delay information, according to the Doppler effect, may include: Based on the first time delay information, the second time delay information, the initial audio signal of the acoustic excitation signal, the damage transmission coefficient, the frequency of the acoustic excitation signal, the rotational linear velocity at the damage location, and the angular position of the target microphone sensor relative to the rotation axis at time t, the target physical model of the acoustic excitation signal collected by the target microphone sensor is determined according to the Doppler effect.

[0057] Optionally, according to some embodiments of this application, determining the target physical model of the acoustic excitation signal collected by the target microphone sensor based on the first time delay information, the second time delay information, the initial audio signal of the acoustic excitation signal, the damage transmission coefficient, the frequency of the acoustic excitation signal, the rotational linear velocity at the damage location, and the angular position of the target microphone sensor relative to the rotation axis at time t, according to the Doppler effect, may include: Based on the first time delay information, the second time delay information, the initial audio signal of the acoustic excitation signal, the damage transmission coefficient, the frequency of the acoustic excitation signal, the rotational linear velocity at the damage location, and the angular position of the target microphone sensor relative to the rotation axis at time t, the sixth formula is constructed according to the Doppler effect to determine the target physical model of the acoustic excitation signal collected by the target microphone sensor. The sixth formula can be expressed as follows (11): in, To model the physical properties of the target, The damage transmission coefficient, The initial audio signal is the acoustic excitation signal. The frequency of the acoustic excitation signal, This is the first delay information. This is the second time delay information. The rotational linear velocity at the location of the damage. For the speed of sound, Let be the angular position of the target microphone sensor relative to the rotation axis at time t. This is environmental noise.

[0058] On the right side of the equation, the first term represents the acoustic excitation signal component after propagation delay and damage transmission, the second term represents Doppler modulation, and the third term represents ambient noise.

[0059] In S150, in specific implementation, based on the target physical modeling of the acoustic excitation signal and the rotating window function, the energy of the acoustic excitation signal collected by the target microphone sensor is determined, and the maximization criterion of the acoustic excitation signal energy of the microphone array is established. The damage location information of the wind turbine blade is determined through parameter iteration.

[0060] Optionally, according to some embodiments of this application, determining the energy of the acoustic excitation signal collected by the target microphone sensor based on target physical modeling of the acoustic excitation signal and a rotating window function may include: Based on the target physical modeling of the acoustic excitation signal and the rotating window function, the energy of the acoustic excitation signal collected by the target microphone sensor is determined by the seventh formula; the seventh formula may include: in, The energy of the acoustic excitation signal. Physical modeling of the target for acoustic excitation signals. This is a function for rotating the window.

[0061] In this embodiment, a rotating window function is used to enhance the acoustic excitation signal collected by the microphone sensor, thereby reducing the interference from multi-source noise.

[0062] The specific expression for the aforementioned rotating window can be, for example: In the formula, For rotating window functions, Representing the target perspective, is the standard deviation. near When, the acoustic excitation signal attenuation decreases; when Deviation When the acoustic excitation signal is suppressed, the rotating window function essentially applies an angle filter to the acoustic excitation signal to highlight the acoustic signal at a specific angle, thereby reducing the interference of multi-source noise.

[0063] Optionally, according to some embodiments of this application, M microphone sensors are installed on the tower of the wind turbine, and the M microphone sensors form a microphone array. The target microphone sensor is the i-th microphone sensor among the M microphone sensors, where i and M are greater than or equal to 1, and i is less than or equal to M. Establishing a criterion for maximizing the energy of the acoustic excitation signal from the microphone array, and determining the damage location information of the wind turbine blades through parameter iteration, may include: Based on the acoustic excitation signal energy, the weighted energy of the array acoustic excitation signal is established through the eighth formula; the eighth formula can be expressed as follows (14): in, Weighted energy for the array acoustic excitation signal The energy of the acoustic excitation signal. For the first i Weights of each microphone sensor; To achieve spatial localization of wind turbine blade damage, the following criterion for maximizing the energy of the microphone array acoustic excitation signal is established based on the weighted energy of the array acoustic excitation signal using the ninth formula; the ninth formula can be expressed as follows (15): in, For estimating the damage angle of wind turbine blades, This is used to estimate the damage distance of wind turbine blades.

[0064] Next, based on the criterion of maximizing the energy of the acoustic excitation signal from the microphone array, the damage location information of the wind turbine blade is determined through parameter iteration using the tenth formula; the tenth formula may include: in, Let this be the hypothetical distance between the blade root and the location of the damage on a wind turbine blade. This provides information on the location of damage to wind turbine blades.

[0065] Thus, in practical applications, the spatial location of wind turbine blade damage, as determined above, provides guidance for subsequent blade maintenance. For example, by accurately determining the spatial location of wind turbine blade damage and developing targeted inspection plans and optimizing maintenance strategies based on this information, the efficiency and quality of blade maintenance can be effectively improved, the service life of the blades can be extended, and the safe and reliable operation of the wind turbine can be ensured.

[0066] For example, damage to the blades can be prioritized based on its spatial location and severity. Areas with severe damage (such as large cracks or extensive erosion) should be inspected and treated first.

[0067] Overall, this application's embodiments establish a highly applicable and accurate damage location mechanism for the complex external environment faced by wind turbine blades. This mechanism can accurately pinpoint the spatial location of damage to wind turbine blades, providing solid technical support for ensuring the stability and reliability of wind turbine blade operation. This solution effectively guarantees the stability and reliability of wind turbine blade operation, avoids unplanned downtime, and has broad prospects for industrial application.

[0068] To facilitate understanding of the wind turbine blade damage location method provided in the above embodiments, the following describes the method using a specific scenario embodiment. Figure 2 This is a schematic flowchart of a scenario embodiment of the wind turbine blade damage location method provided in this application.

[0069] This embodiment uses a 2MW wind turbine in a wind farm to verify the feasibility and effectiveness of the active acoustic excitation-based wind turbine blade damage localization method provided in this application in practical applications. This embodiment specifically includes the following steps: Step 1: Install the high-frequency loudspeaker equipment at the root of the wind turbine blades. All three blades of each wind turbine need to be installed.

[0070] Specifically, for example, an M6×60 expansion bolt is used to fix the high-frequency speaker to the cover plate of the wind turbine blade, so that the speaker's sound-emitting surface faces the blade cavity. The high-frequency speaker is directly powered by the pitch control unit installed in the wind turbine hub, and its operating status is controlled by a timer switch. Figure 3 As shown, high-frequency loudspeakers need to be installed at the blade roots of all three blades of the wind turbine. During the experiment, the frequency of the active acoustic excitation signal emitted by the high-frequency loudspeakers was 5 kHz.

[0071] Step 2: Install the microphone sensors evenly on the tower wall from top to bottom, covering the entire length of the blades.

[0072] Specifically, for example, continuing to combine Figure 3 As shown, six microphone sensors are installed on the tower wall from top to bottom, with each microphone sensor spaced 15 meters apart, thus covering the entire length of the wind turbine blade.

[0073] Step 3: The high-frequency loudspeaker emits an active acoustic excitation signal.

[0074] Step 4: The microphone sensor collects the acoustic excitation signal transmitted from the blade.

[0075] Step 5: Perform physical modeling based on the time delay characteristics of the acoustic excitation signal and the Doppler effect.

[0076] Specifically, for example, the initial position angle of the wind turbine blades is determined, and the spatial position of the high-frequency loudspeaker is dynamically calculated based on the rotational speed information (e.g., 5 revolutions per minute during the test). Simultaneously, spatial position modeling of the damaged location on the wind turbine blades is further completed. Next, the physical characteristics of the acoustic excitation signal transmitted from the damaged location on the blade are analyzed based on the time delay characteristics of the acoustic excitation signal. Finally, physical modeling of the acoustic excitation signal collected by the microphone sensor mounted on the tower wall is completed based on the Doppler effect.

[0077] Step 6: Enhance the acoustic excitation signal using a rotating window function.

[0078] In this step, a rotating window function is used to enhance the acoustic excitation signal acquired by the microphone sensor, reducing the interference from multi-source noise. The rotating window function is shown below during the experiment. Figure 4 As shown, this is used to dynamically determine the change of weighting factors with rotation angle (or time).

[0079] Step 7: Establish the criterion for maximizing the energy of the microphone array acoustic excitation signal.

[0080] Step 8: Determine the location of blade damage through parameter iteration.

[0081] In this embodiment, by iteratively combining the rotation angle and distance parameters, and utilizing the established microphone array acoustic excitation signal energy maximization criterion, the location parameter information of wind turbine blade damage can be obtained: such as... Figure 5 As shown, the defect angle is 179.5°, and the radial position of the defect is... R d=32.56 m. The calculated result is similar to the field test results conducted in the later stage of the experiment, thus proving the effectiveness of the wind turbine blade damage location method based on active acoustic excitation provided in this application in practical industrial applications.

[0082] Step 9: Develop a wind turbine blade operation and maintenance plan.

[0083] For example, blade damage is categorized based on its type (e.g., cracks, erosion, fractures) and severity. Repair priorities are determined based on the severity and location of the damage. Then, appropriate repair methods are selected and a regular inspection plan is developed based on the damage type and location.

[0084] Step 10: Conduct maintenance activities to address blade damage. For example, repair the damaged blades according to the maintenance plan. Perform functional tests and visual inspections on the repaired blades to ensure their performance has been restored to normal.

[0085] Step 11: Continuously monitor and spatially locate wind turbine blade damage. Refer to the wind turbine blade damage location method described in the preceding steps. By regularly running the above damage location method, wind turbine blade damage can be monitored and located in a timely and accurate manner.

[0086] Overall, comparing the method provided in this embodiment with traditional vibration analysis-based detection methods, the results are as follows: Figure 6 As shown, the wind turbine blade damage localization method provided in this embodiment has a smaller error. In traditional vibration analysis-based detection methods, since the rotational speed of the wind turbine blade is dynamically changing, this time-varying condition causes significant nonlinear modulation of the vibration signal, making it difficult to accurately identify and locate local damage to the wind turbine blade using traditional vibration analysis methods.

[0087] In contrast, the wind turbine blade damage location method based on active acoustic excitation provided in this embodiment does not rely on operating condition information. It explores the blade damage location through active acoustic excitation, which has stronger applicability to operating conditions and avoids the engineering problem of traditional methods being constrained by time-varying operating conditions. It effectively improves the accuracy of damage location and provides useful guidance and support for subsequent wind turbine blade operation and maintenance.

[0088] To address the complex operating environment faced by wind turbine blades, this embodiment provides a method for locating wind turbine blade damage based on active acoustic excitation. First, a high-frequency loudspeaker is installed at the blade root to emit active acoustic excitation signals. The loudspeaker is directly powered by a pitch control unit installed in the turbine hub, and its operation is controlled by a timer switch. Simultaneously, microphone sensors are evenly installed along the tower wall from top to bottom to receive the acoustic excitation signals. Multiple evenly installed microphone sensors form a microphone array, covering the entire length of the wind turbine blade. Second, the spatial position of the loudspeaker is dynamically calculated based on the turbine rotation speed information, simultaneously completing the spatial location modeling of the wind turbine blade damage site.

[0089] Based on this, the physical modeling of the acoustic excitation signal acquired by the microphone sensor is completed using the time delay characteristics and Doppler effect of the acoustic excitation signal. To reduce the interference of multi-source noise, a rotating window function is used to enhance the acoustic excitation signal acquired by the microphone sensor. Finally, a criterion for maximizing the energy of the microphone array acoustic excitation signal is established, and the damage location of the wind turbine blade is finally determined through parameter iteration. The method provided in this embodiment can accurately locate the spatial position of wind turbine blade damage, providing solid technical support for ensuring the stability and reliability of wind turbine blade operation.

[0090] Based on the wind turbine blade damage location method provided in the above embodiments, and with the same inventive concept, this application also provides a wind turbine blade damage location device corresponding to the above wind turbine blade damage location method. The following describes... Figure 7 This paper provides a detailed introduction to the wind turbine blade damage location device.

[0091] Figure 7 A schematic diagram of the structure of a wind turbine blade damage location device provided in an embodiment of this application is shown. Figure 7 The wind turbine blade damage location device 700 shown includes: The first determining module 710 is used to determine the first spatial position modeling of the high-frequency loudspeaker and the second spatial position modeling of the damaged location of the wind turbine blade based on the initial position angle and rotational angular velocity of the wind turbine blade. The high-frequency loudspeaker is set at the root of the wind turbine blade and is used to emit acoustic excitation signals. The first calculation module 720 is used to calculate the first time delay information of the acoustic excitation signal from the root position of the wind turbine blade to the damage position of the wind turbine blade based on the first spatial position modeling and the second spatial position modeling. The second determining module 730 is used to determine the second time delay information of the acoustic excitation signal propagating from the damaged location of the wind turbine blade to the target microphone sensor based on the third spatial position modeling and the second spatial position modeling of the target microphone sensor. The target microphone sensor is set in the wind turbine to receive the acoustic excitation signal. The third determining module 740 is used to determine the target physical model of the acoustic excitation signal collected by the target microphone sensor based on the first time delay information and the second time delay information and according to the Doppler effect. The fourth determination module 750 is used for target physical modeling based on acoustic excitation signals and rotating window functions, determining the acoustic excitation signal energy collected by the target microphone sensor, establishing a criterion for maximizing the acoustic excitation signal energy of the microphone array, and determining the damage location information of the wind turbine blade through parameter iteration.

[0092] This application provides a wind turbine blade damage location device, which includes a high-frequency loudspeaker for emitting acoustic excitation signals installed at the root of the wind turbine blade, and a target microphone sensor for receiving the acoustic excitation signals within the wind turbine. Based on this, by setting corresponding functional modules, a first spatial position model of the high-frequency loudspeaker and a second spatial position model of the damage location on the wind turbine blade are determined based on the initial position angle and rotational angular velocity of the wind turbine blade. Based on the first and second spatial position models, a first time delay information is calculated from the wind turbine blade root to the damage location. Based on the third and second spatial position models of the target microphone sensor, a second time delay information is determined from the damage location to the target microphone sensor. Based on the first and second time delay information, a target physical model of the acoustic excitation signal collected by the target microphone sensor is determined according to the Doppler effect. Based on the target physical modeling of the acoustic excitation signal and the rotating window function, the energy of the acoustic excitation signal collected by the target microphone sensor is determined, and the maximization criterion of the acoustic excitation signal energy of the microphone array is established. The damage location information of the wind turbine blade is determined through parameter iteration.

[0093] As described above, the wind turbine blade damage location device of this application utilizes the time delay characteristics and Doppler effect of the acoustic excitation signal to complete the target physical modeling of the acoustic excitation signal collected by the target microphone sensor. To reduce the interference of multi-source noise, a rotating window function is used to enhance the acoustic excitation signal collected by the microphone sensor. Finally, a criterion for maximizing the energy of the microphone array acoustic excitation signal is established, and the damage location of the wind turbine blade is ultimately determined through parameter iteration. Thus, this solution establishes a highly applicable and accurate damage location mechanism for the complex external environment faced by wind turbine blades. It can accurately locate the spatial position of wind turbine blade damage, providing solid technical support for ensuring the stability and reliability of wind turbine blade operation, and effectively guaranteeing the stability and reliability of wind turbine blade operation.

[0094] Optionally, according to some embodiments of this application, the first determining module 710 includes: The first determining submodule is used to determine the rotation angle of the wind turbine blade based on the initial position angle of the wind turbine blade and the rotation angular velocity of the wind turbine blade. The second determination submodule is used to determine the first spatial position modeling of the high-frequency loudspeaker and the second spatial position modeling of the damaged location of the wind turbine blade based on the rotation angle.

[0095] Optionally, according to some embodiments of this application, the second determining submodule described above includes: The first determining unit is used to determine the first spatial position model based on the rotation angle, the distance from the high-frequency loudspeaker to the wind turbine's shaft, and a first formula, the first formula including: And / or, a second determining unit, used to determine a second spatial position model based on a rotation angle and a second formula, the second formula including: in, Modeling the first spatial location, This is the distance from the high-frequency loudspeaker to the shaft of the wind turbine. For rotation angle, Modeling the second spatial location, This represents the distance between the blade root and the location of damage on a hypothetical wind turbine blade.

[0096] Optionally, according to some embodiments of this application, the first computing module 720 includes: Based on the first spatial location modeling and the second spatial location modeling, the first time delay information is calculated using a third formula; the third formula includes: in, This is the first delay information. For the speed of sound, Modeling the first spatial location, Model the second spatial location.

[0097] Optionally, according to some embodiments of this application, the second determining module 730 includes: Based on third-space location modeling and second-space location modeling, the second time delay information is determined by a fourth formula; the fourth formula includes: in, This is the second time delay information. Modeling third-space location, Modeling the second spatial location, The speed of sound.

[0098] Optionally, according to some embodiments of this application, the target microphone sensor is mounted on the tower of the wind turbine; Before determining the second time delay information of the acoustic excitation signal propagating from the damaged location of the wind turbine blade to the target microphone sensor, the device further includes: The modeling module is used to determine the third spatial position modeling based on the radius of the target microphone sensor projected onto the tower plane to the origin of the spatial coordinates, the angular position of the target microphone sensor relative to the rotation axis of the wind turbine, and the relative height of the target microphone sensor, using the fifth formula. The fifth formula includes: in, Modeling third-space location, Let the radius be the radius of the target microphone sensor projected onto the origin of the spatial coordinate system on the tower plane. The angular position of the target microphone sensor relative to the wind turbine's axis of rotation. The relative height of the target microphone sensor.

[0099] Optionally, according to some embodiments of this application, the third determining module 740 includes: Based on the first time delay information, the second time delay information, the initial audio signal of the acoustic excitation signal, the damage transmission coefficient, the frequency of the acoustic excitation signal, the rotational linear velocity at the damage location, and the angular position of the target microphone sensor relative to the rotation axis at time t, the target physical model of the acoustic excitation signal collected by the target microphone sensor is determined according to the Doppler effect.

[0100] Optionally, according to some embodiments of this application, based on first time delay information, second time delay information, the initial audio signal of the acoustic excitation signal, the damage transmission coefficient, the frequency of the acoustic excitation signal, the rotational linear velocity at the damage location, and the angular position of the target microphone sensor relative to the rotation axis at time t, the target physical modeling of the acoustic excitation signal collected by the target microphone sensor is determined according to the Doppler effect, including: Based on the first time delay information, the second time delay information, the initial audio signal of the acoustic excitation signal, the damage transmission coefficient, the frequency of the acoustic excitation signal, the rotational linear velocity at the damage location, and the angular position of the target microphone sensor relative to the rotation axis at time t, the sixth formula is constructed according to the Doppler effect to determine the target physical model of the acoustic excitation signal collected by the target microphone sensor. The sixth formula includes: in, To model the physical properties of the target, The damage transmission coefficient, The initial audio signal is the acoustic excitation signal. The frequency of the acoustic excitation signal, This is the first delay information. This is the second time delay information. The rotational linear velocity at the location of the damage. For the speed of sound, Let be the angular position of the target microphone sensor relative to the rotation axis at time t. This is environmental noise.

[0101] Optionally, according to some embodiments of this application, the energy of the acoustic excitation signal collected by the target microphone sensor is determined based on target physical modeling of the acoustic excitation signal and a rotating window function, including: Based on the target physical modeling of the acoustic excitation signal and the rotating window function, the energy of the acoustic excitation signal collected by the target microphone sensor is determined by the seventh formula; the seventh formula includes: in, The energy of the acoustic excitation signal. Physical modeling of the target for acoustic excitation signals. This is a function for rotating the window.

[0102] Optionally, according to some embodiments of this application, M microphone sensors are installed on the tower of the wind turbine, and the M microphone sensors form a microphone array. The target microphone sensor is the i-th microphone sensor among the M microphone sensors, where i and M are greater than or equal to 1, and i is less than or equal to M. A criterion for maximizing the energy of the acoustic excitation signal from the microphone array is established, and the damage location information of the wind turbine blades is determined through parameter iteration, including: Based on the acoustic excitation signal energy, the weighted energy of the array acoustic excitation signal is established using the eighth formula; the eighth formula includes: in, Weighted energy for the array acoustic excitation signal The energy of the acoustic excitation signal. For the first i Weights of each microphone sensor; Based on the weighted energy of the array acoustic excitation signal, a criterion for maximizing the energy of the microphone array acoustic excitation signal is established using the ninth formula; the ninth formula includes: in, For estimating the damage angle of wind turbine blades, For estimating the damage distance of wind turbine blades; Based on the criterion of maximizing the energy of the acoustic excitation signal from the microphone array, the damage location information of the wind turbine blade is determined through parameter iteration using the tenth formula; the tenth formula includes: in, Let this be the hypothetical distance between the blade root and the location of the damage on a wind turbine blade. This provides information on the location of damage to wind turbine blades.

[0103] Optionally, according to some embodiments of this application, the initial audio signal of the acoustic excitation signal emitted by the high-frequency loudspeaker is: in, The initial audio signal, The frequency of the acoustic excitation signal, The amplitude of the acoustic excitation signal. .

[0104] Based on the wind turbine blade damage location method provided in the above embodiments, and with the same inventive concept, this application also provides a wind turbine blade damage location device corresponding to the above wind turbine blade damage location method. The following describes... Figure 8 This article provides a detailed introduction to wind turbine blade damage location equipment.

[0105] Please see below. Figure 8 , Figure 8 This is a schematic diagram of the structure of a wind turbine blade damage location device provided in an embodiment of this application.

[0106] The wind turbine blade damage location device may include a processor 801 and a memory 802 storing computer program instructions.

[0107] Specifically, the processor 801 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0108] Memory 802 may include mass storage for data or instructions. For example, and not limitingly, memory 802 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 802 may include removable or non-removable (or fixed) media. Where appropriate, memory 802 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 802 is non-volatile solid-state memory.

[0109] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the methods according to one aspect of this disclosure.

[0110] The processor 801 reads and executes computer program instructions stored in the memory 802 to implement any of the wind turbine blade damage location methods in the above embodiments.

[0111] In one example, the data wind turbine blade damage location device may also include a communication interface 803 and a bus 810. For example, Figure 8 As shown, the processor 801, memory 802, and communication interface 803 are connected through bus 810 and complete communication with each other.

[0112] The communication interface 803 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0113] Bus 810 includes hardware, software, or both, that couples components of a wind turbine blade damage location device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 810 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0114] The wind turbine blade damage location device executes the wind turbine blade damage location method in the embodiments of this application, thereby realizing the wind turbine blade damage location method described in the embodiments of this application.

[0115] Furthermore, in conjunction with the wind turbine blade damage location method in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the wind turbine blade damage location methods in the above embodiments.

[0116] Based on the wind turbine blade damage location method in the above embodiments, this application provides a computer program product. When the instructions in the computer program product are executed by the processor of an electronic device, the electronic device performs the wind turbine blade damage location method provided in any of the above embodiments of this application.

[0117] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0118] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0119] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0120] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0121] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for locating damage to wind turbine blades, characterized in that, The method includes: Based on the initial position angle of the wind turbine blade and the rotational angular velocity of the wind turbine blade, a first spatial position model of the high-frequency loudspeaker and a second spatial position model of the damaged location of the wind turbine blade are determined. The high-frequency loudspeaker is set at the root of the wind turbine blade and is used to emit acoustic excitation signals. Based on the first spatial location modeling and the second spatial location modeling, the first time delay information of the acoustic excitation signal from the blade root position of the wind turbine blade to the damage position of the wind turbine blade is calculated. Based on the third spatial position modeling and the second spatial position modeling of the target microphone sensor, a second time delay information is determined for the acoustic excitation signal to propagate from the damaged location of the wind turbine blade to the target microphone sensor. The target microphone sensor is installed in the wind turbine to receive the acoustic excitation signal. Based on the first time delay information and the second time delay information, the target physical model of the acoustic excitation signal collected by the target microphone sensor is determined according to the Doppler effect; Based on the target physical modeling of the acoustic excitation signal and the rotating window function, the energy of the acoustic excitation signal collected by the target microphone sensor is determined, and a criterion for maximizing the acoustic excitation signal energy of the microphone array is established. The damage location information of the wind turbine blade is determined through parameter iteration.

2. The method according to claim 1, characterized in that, The determination of the first spatial position modeling of the high-frequency loudspeaker and the second spatial position modeling of the damaged location of the wind turbine blade, based on the initial position angle and rotational angular velocity of the wind turbine blade, includes: The rotation angle of the wind turbine blade is determined based on the initial position angle of the wind turbine blade and the rotation angular velocity of the wind turbine blade. Based on the rotation angle, the first spatial position model of the high-frequency loudspeaker and the second spatial position model of the damaged location of the wind turbine blade are determined.

3. The method according to claim 2, characterized in that, The process of determining the first spatial position modeling of the high-frequency loudspeaker and the second spatial position modeling of the damaged location of the wind turbine blade based on the rotation angle includes: Based on the rotation angle, the distance from the high-frequency loudspeaker to the wind turbine's shaft, and a first formula, the first spatial position model is determined, wherein the first formula includes: ， And / or, based on the rotation angle and the second formula, determine the second spatial position modeling, wherein the second formula includes: ， in, Model the first spatial location. The distance from the high-frequency loudspeaker to the shaft of the wind turbine is [missing information]. For the rotation angle, Model the second spatial location. This is the hypothetical distance between the blade root on the wind turbine blade and the location of the damage.

4. The method according to claim 1, characterized in that, The calculation of the first time delay information of the acoustic excitation signal from the root of the wind turbine blade to the damaged location of the wind turbine blade, based on the first spatial location modeling and the second spatial location modeling, includes: Based on the first spatial location modeling and the second spatial location modeling, the first time delay information is calculated using a third formula; the third formula includes: ， in, This is the first delay information. For the speed of sound, Model the first spatial location. Model the second spatial location.

5. The method according to claim 1, characterized in that, Based on the third spatial location modeling and the second spatial location modeling of the target microphone sensor, the second time delay information of the acoustic excitation signal propagating from the damaged location of the wind turbine blade to the target microphone sensor is determined, including: Based on the third spatial location modeling and the second spatial location modeling, the second time delay information is determined by a fourth formula; the fourth formula includes: ， in, This is the second delay information. Model the third spatial location. Model the second spatial location. The speed of sound.

6. The method according to claim 1, characterized in that, The target microphone sensor is mounted on the tower of the wind turbine. Before determining the second time delay information of the acoustic excitation signal propagating from the damaged location of the wind turbine blade to the target microphone sensor, the method further includes: Based on the radius of the target microphone sensor projected onto the origin of the spatial coordinates on the tower plane, the angular position of the target microphone sensor relative to the axis of rotation of the wind turbine, and the relative height of the target microphone sensor, the third spatial position model is determined by the fifth formula. The fifth formula includes: ， in, Model the third spatial location. The radius of the target microphone sensor projected onto the origin of the spatial coordinate system from the plane of the tower. The angular position of the target microphone sensor relative to the axis of rotation of the wind turbine. The relative height of the target microphone sensor.

7. The method according to claim 1, characterized in that, The target physical modeling based on the first time delay information and the second time delay information, and determining the acoustic excitation signal collected by the target microphone sensor according to the Doppler effect, includes: Based on the first time delay information, the second time delay information, the initial audio signal of the acoustic excitation signal, the damage transmission coefficient, the frequency of the acoustic excitation signal, the rotational linear velocity at the damage location, and the angular position of the target microphone sensor relative to the rotation axis at time t, the target physical model of the acoustic excitation signal collected by the target microphone sensor is determined according to the Doppler effect.

8. The method according to claim 7, characterized in that, The target physical modeling, based on the first time delay information, the second time delay information, the initial audio signal of the acoustic excitation signal, the damage transmission coefficient, the frequency of the acoustic excitation signal, the rotational linear velocity at the damage location, and the angular position of the target microphone sensor relative to the rotation axis at time t, determines the acoustic excitation signal collected by the target microphone sensor according to the Doppler effect, including: Based on the first time delay information, the second time delay information, the initial audio signal of the acoustic excitation signal, the damage transmission coefficient, the frequency of the acoustic excitation signal, the rotational linear velocity at the damage location, and the angular position of the target microphone sensor relative to the rotation axis at time t, a sixth formula is constructed according to the Doppler effect to determine the target physical model of the acoustic excitation signal collected by the target microphone sensor. The sixth formula includes: ， in, Physical modeling of the target, The damage transmission coefficient, The initial audio signal of the acoustic excitation signal. The frequency of the acoustic excitation signal is... This is the first delay information. This is the second delay information. The rotational linear velocity at the location of the damage is... For the speed of sound, Let be the angular position of the target microphone sensor relative to the rotation axis at time t. This is environmental noise.

9. The method according to claim 1, characterized in that, The determination of the acoustic excitation signal energy collected by the target microphone sensor based on the target physical modeling and rotating window function includes: Based on the target physical modeling of the acoustic excitation signal and the rotating window function, the energy of the acoustic excitation signal collected by the target microphone sensor is determined by the seventh formula; the seventh formula includes: ， in, The energy of the acoustic excitation signal. To perform target physics modeling for the acoustic excitation signal. This is the rotating window function.

10. The method according to claim 1, characterized in that, M microphone sensors are installed on the tower of the wind turbine, and the M microphone sensors form a microphone array. The target microphone sensor is the i-th microphone sensor among the M microphone sensors, where i and M are greater than or equal to 1, and i is less than or equal to M. The establishment of a criterion for maximizing the energy of the microphone array acoustic excitation signal, and the determination of the damage location information of the wind turbine blades through parameter iteration, includes: Based on the acoustic excitation signal energy, the weighted energy of the array acoustic excitation signal is established using the eighth formula; the eighth formula includes: ， in, Weighted energy is added to the array acoustic excitation signal. The energy of the acoustic excitation signal. For the first i Weights of each microphone sensor; Based on the weighted energy of the array acoustic excitation signal, a criterion for maximizing the energy of the microphone array acoustic excitation signal is established using the ninth formula; the ninth formula includes: ， in, For the estimation of the damage angle of the wind turbine blades, For the estimation of the damage distance of the wind turbine blades; Based on the microphone array acoustic excitation signal energy maximization criterion, the damage location information of the wind turbine blade is determined by parameter iteration using the tenth formula; the tenth formula includes: ， in, This is the assumed distance between the blade root and the location of the damage on the wind turbine blade. This refers to the damage location information of the wind turbine blades.

11. The method according to any one of claims 1-10, characterized in that, The initial audio signal of the acoustic excitation signal emitted by the high-frequency loudspeaker is: ， in, The initial audio signal, The frequency of the acoustic excitation signal is... The amplitude of the acoustic excitation signal is given. .

12. A wind turbine blade damage location device, characterized in that, The device includes: The first determining module is used to determine the first spatial position modeling of the high-frequency loudspeaker and the second spatial position modeling of the damaged location of the wind turbine blade based on the initial position angle of the wind turbine blade and the rotational angular velocity of the wind turbine blade. The high-frequency loudspeaker is set at the root of the wind turbine blade and is used to emit acoustic excitation signals. The first calculation module is used to calculate the first time delay information of the acoustic excitation signal from the root position of the wind turbine blade to the damage position of the wind turbine blade based on the first spatial position modeling and the second spatial position modeling. The second determining module is used to determine, based on the third spatial position modeling and the second spatial position modeling of the target microphone sensor, the second time delay information of the acoustic excitation signal propagating from the damaged location of the wind turbine blade to the target microphone sensor, wherein the target microphone sensor is installed in the wind turbine and is used to receive the acoustic excitation signal; The third determining module is used to determine the target physical model of the acoustic excitation signal collected by the target microphone sensor based on the first time delay information and the second time delay information, according to the Doppler effect. The fourth determination module is used to determine the energy of the acoustic excitation signal collected by the target microphone sensor based on the target physical modeling and rotating window function of the acoustic excitation signal, and to establish a criterion for maximizing the acoustic excitation signal energy of the microphone array, and to determine the damage location information of the wind turbine blade through parameter iteration.

13. A wind turbine blade damage location device, characterized in that, The device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the wind turbine blade damage location method as described in any one of claims 1-11.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the wind turbine blade damage location method as described in any one of claims 1-11.

15. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device performs the wind turbine blade damage location method as described in any one of claims 1-11.

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