Wind turbine, blade, and stall detection method, apparatus, system, and medium

Abstract

Embodiments of the present application provide a wind turbine, a blade, a stall detection method, device, system and medium. The method comprises: obtaining wind condition data at a blade position on a leeward surface of the blade, the wind condition data comprising wind condition parameters at M collection time points within a target time period; determining a distribution characteristic parameter of the wind condition at the blade position within the target time period according to the wind condition data at the blade position; and detecting whether the blade stalls according to the distribution characteristic parameter at the blade position and a preset blade stall condition. According to the embodiments of the present application, the accuracy of blade stall detection can be improved.

Description

Technical Field

[0001] This application pertains to the field of wind power generation, and particularly relates to wind turbine generator sets, blades, and stall detection methods, devices, systems, and media. Background Technology

[0002] Wind turbine blade stall occurs when the airflow separates on the blade surface after the angle of attack of the blade cross-section exceeds a certain critical value. Since wind turbine blade stall can affect the safety and power generation efficiency of wind turbine generators, it is necessary to detect wind turbine blade stall.

[0003] In one related technology, the blade angle of attack can be used as the basis for determining whether a blade is stalling. However, since the blade angle of attack obtained through table lookup and arctangent function methods is often too large, the stall detection accuracy of this technology is low. In another related technology, wind turbine power is used as the basis for determining whether a blade is stalling. However, in addition to blade stall, failures in wind turbine components such as motors and converters are also factors affecting wind turbine power. This related technology cannot exclude the influence of these other factors on blade stall detection, resulting in a low stall detection accuracy.

[0004] Therefore, a solution is needed to improve the accuracy of blade stall detection. Summary of the Invention

[0005] This application provides a wind turbine generator set, blades, and a stall detection method, device, system, and medium, which can improve the accuracy of blade stall detection.

[0006] In a first aspect, embodiments of this application provide a method for detecting stall in wind turbine blades, including:

[0007] Acquire wind condition data at the blade position on the leeward side of the blade. The wind condition data includes wind condition parameters at M collection times within the target time period, where M is an integer greater than or equal to 1.

[0008] Based on the wind condition data at the blade location, determine the distribution characteristic parameters of the wind condition at the blade location within the target time period;

[0009] Based on the distribution characteristic parameters at the blade location and the preset blade stall conditions, the system detects whether the blade is stalling.

[0010] Secondly, embodiments of this application provide a wind turbine blade stall detection device, comprising:

[0011] The wind condition parameter acquisition module is used to acquire wind condition data at the blade position on the leeward side of the blade. The wind condition data includes wind condition parameters at M acquisition times within the target time period, where M is an integer greater than or equal to 1.

[0012] The feature parameter determination module is used to determine the distribution feature parameters of the wind conditions at each blade position within the target time period based on the wind condition data at each blade position.

[0013] The stall detection module is used to detect whether the wind turbine blades are stalling based on the distribution characteristic parameters at the blade position and the preset blade stall conditions.

[0014] Thirdly, embodiments of this application provide a wind turbine blade stall detection system, comprising:

[0015] A wind condition detection device, wherein the wind condition detection device is used to detect wind condition parameters at the blade position;

[0016] The wind turbine blade stall detection device provided by the second aspect or any optional embodiment of the second aspect.

[0017] Fourthly, a blade is provided, comprising:

[0018] Wind-sensing components are installed on the leeward side of the blades;

[0019] Among them, the wind condition data detected by the wind sensing component is used to calculate the distribution characteristic parameters of the wind condition at the blade position within the target time period; the distribution characteristic parameters at the blade position and the preset stall condition are used to detect whether the blade stalls.

[0020] Fifthly, a wind turbine generator set is provided, comprising:

[0021] The wind turbine blade stall detection device provided by the second aspect or any optional embodiment of the second aspect, and / or the wind turbine blade stall detection system provided by the third aspect or any optional embodiment of the third aspect, and / or the blade provided by the fourth aspect or any optional embodiment of the fourth aspect.

[0022] Sixthly, a wind turbine blade stall detection device is provided, comprising:

[0023] Processor and memory storing computer program instructions;

[0024] The processor reads and executes computer program instructions to implement the wind turbine blade stall detection method provided in the first aspect or any optional implementation of the first aspect.

[0025] In a seventh aspect, a computer storage medium is provided, on which computer program instructions are stored, wherein when the computer program instructions are executed by a processor, the wind turbine blade stall detection method provided in the first aspect or any optional embodiment of the first aspect is implemented.

[0026] The wind turbine generator set, blade, stall detection method, device, system, and medium of this application embodiment can calculate a distribution characteristic parameter based on wind condition parameters collected at M acquisition times within a target time period at the blade position. Since the distribution characteristic parameter accurately reflects the wind condition distribution characteristics at the blade position within the target time period, compared to methods using blade angle of attack to detect blade stall, using the distribution characteristic parameter at the blade position can improve the accuracy of blade stall detection. Furthermore, compared to methods using turbine power to detect blade stall, firstly, since turbine component failures such as motors and converters have a smaller impact on wind condition parameters than blade stall, and the distribution characteristic parameters of wind condition parameters differ under blade stall and normal turbulence conditions, this application embodiment, by using the respective distribution characteristic parameters at each blade position as the basis for stall judgment, can eliminate the influence of other causes on blade stall detection, thereby improving the accuracy of blade stall detection. Attached Figure Description

[0027] 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.

[0028] Figure 1 This is a schematic diagram of the angle of attack of a blade cross section;

[0029] Figure 2 This is a schematic diagram of the structure of a wind turbine blade provided in an embodiment of this application;

[0030] Figure 3 yes Figure 2 The cross-section of the blade along the axial direction;

[0031] Figure 4 This is a schematic diagram of the structure of a wind turbine generator set provided in an embodiment of this application;

[0032] Figure 5 This is a system architecture diagram of a wind turbine blade stall detection system provided in an embodiment of this application;

[0033] Figure 6 This is a schematic diagram of a pressure sensor installation location provided in an embodiment of this application;

[0034] Figure 7 This is a schematic diagram of another pressure sensor installation position provided in an embodiment of this application;

[0035] Figure 8 This is a schematic diagram of a swing component in a windless state provided in an embodiment of this application;

[0036] Figure 9This is a schematic diagram of a swinging component provided in an embodiment of this application under windy and windless conditions;

[0037] Figure 10 yes Figure 9 A magnified view of a portion of region E in the middle;

[0038] Figure 11 This is a flowchart illustrating the first wind turbine blade stall detection method provided in this application embodiment;

[0039] Figure 12 This is a schematic flowchart of the second wind turbine blade stall detection method provided in the embodiments of this application;

[0040] Figure 13 This is a flowchart illustrating the third wind turbine blade stall detection method provided in the embodiments of this application;

[0041] Figure 14 This is a flowchart illustrating the fourth wind turbine blade stall detection method provided in the embodiments of this application;

[0042] Figure 15 This is a flowchart illustrating the fifth wind turbine blade stall detection method provided in this application embodiment;

[0043] Figure 16 This is a schematic flowchart of an exemplary wind turbine blade stall detection method provided in an embodiment of this application;

[0044] Figure 17 This is a schematic diagram of the structure of a wind turbine blade stall detection device provided in an embodiment of this application;

[0045] Figure 18 A schematic diagram of the hardware structure of the wind turbine blade stall detection device provided in an embodiment of the present invention is shown. Detailed Implementation

[0046] 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.

[0047] 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 the element.

[0048] Angle of attack refers to the angle between the airflow direction and the blade chord. Figure 1 This is a schematic diagram of the angle of attack of a blade cross-section. For example... Figure 1 As shown, this cross section is a cross section of the blade, and the angle α between the chord of this cross section and the airflow direction is the angle of attack.

[0049] Blade stall refers to the phenomenon where, under normal operating conditions, the angle of attack is very small, and the airflow remains streamlined around the blades. However, when the airflow forms a positive angle of attack with the blade inlet (α > 0), and this positive angle of attack exceeds a certain critical value, the airflow separates on the blade surface. Specifically, blade stall manifests as flow separation and stagnation when the airflow passes a point on the leeward side of the blade, as observed from the blade cross-section. The surface pressure increases from the separation point to the trailing edge. Due to the stagnation ring and blade rotation effects, the pressure in the region from the separation point to the trailing edge not only increases but also exhibits enhanced pulsation, with the observed surface pressure showing an increasing and discrete trend.

[0050] Because blade stall can affect the safety and power generation efficiency of wind turbine generators, it is necessary to monitor blade stall.

[0051] To better understand this application, the structure of the blade will be explained in detail in the embodiments of this application.

[0052] For a better understanding of the blade, please refer to [the relevant documentation / reference]. Figure 2 as well as Figure 3 , Figure 2 This is a schematic diagram of the structure of a wind turbine blade provided in an embodiment of this application. Figure 3 yes Figure 2 The cross-section of the blade in the axial direction. Figure 2 and Figure 3 The diagram shows the chordal direction X of the blade, the thickness direction Y of the blade, and the axial direction Z of the blade.

[0053] The blade 10 includes a blade body 11 and a blade cavity 12 enclosed by the blade body 11. Specifically, the blade body 11 may include a windward shell 111 and a leeward shell 112, which are fastened together to form the blade cavity 12. The outer surface of the blade body 10 has a windward surface 1111 and a leeward surface 1121. The windward surface 1111 is the outer surface of the windward shell 111, i.e., the surface away from the leeward shell 112. The leeward surface 1111 is the outer surface of the leeward shell 112, i.e., the surface away from the leeward shell 112. The blade body 11 has a root portion 13 and a tip portion 14 in its axial direction Z. The blade body has a leading edge 15, a trailing edge 16, and a maximum thickness region 17 disposed between the leading edge 15 and the trailing edge 16 in its chordal direction X. In each cross section along the blade axis Z, the maximum thickness region corresponds to the maximum thickness in the thickness direction Y of that cross section. That is, in each cross section along the blade axis Z, the relative distance in the thickness direction Y between the position of the maximum thickness region 17 on the windward side shell 111 and the position of the maximum thickness region 17 on the leeward side shell 112 is the maximum thickness in the thickness direction Y of that cross section.

[0054] In some embodiments, the blade shell may be made of a hollow composite material composed of glass fiber and resin.

[0055] After introducing the blade structure, in order to better understand this application, the following will describe in detail the wind turbine generator set, blade, stall detection method, device, system and medium according to the embodiments of this application with reference to the accompanying drawings. It should be noted that these embodiments are not intended to limit the scope of this application.

[0056] First, in order to detect blade stall, this application provides a wind turbine generator set, which may include at least one of the blades provided in this application, the wind turbine blade stall detection device provided in this application, and the wind turbine blade stall detection system.

[0057] In some embodiments of this application, the wind turbine generator set can be any one of a direct-drive wind turbine generator set, a doubly-fed wind turbine generator set, or a semi-direct-drive wind turbine generator set. This application does not limit the specific type of wind turbine generator set to which the blade stall detection scheme can be applied in its embodiments.

[0058] In one example Figure 4 This is a structural schematic diagram of a wind turbine generator set provided in an embodiment of this application. Figure 4 As shown, the wind turbine generator set 1 may include blades 10 and a wind turbine blade stall detection system 20.

[0059] First, regarding the wind turbine blade stall detection system 20, the following parts of the embodiments of this application will be described in detail with reference to the accompanying drawings.

[0060] Figure 5 This is a system architecture diagram of a wind turbine blade stall detection system provided in an embodiment of this application. Figure 5 As shown, the wind turbine blade stall detection system 20 may include a wind condition detection device 21 and a wind turbine blade stall detection device 23.

[0061] First, regarding the wind condition detection device 21, in terms of location and function, the wind condition detection device 21 is used to detect wind condition parameters at N blade positions. Here, N is an integer greater than or equal to 1.

[0062] First, regarding the blade locations. In some embodiments, since blade stall specifically manifests as flow separation and stagnation when airflow passes a point on the leeward side of the blade as observed from the blade cross-section, the N blade locations can be sampling points on the leeward side of the blade. In some embodiments, if N equals 1, the blade location can be located on any blade of the wind turbine. In other embodiments, if N is an integer greater than or equal to 2, the N blade locations can be different blade locations on the same wind turbine blade. In this application embodiment, stall detection can be performed on one wind turbine blade, and the stall detection result of that blade can be used as the stall detection result of all blades on the wind turbine generator set. Alternatively, the N blade locations on each blade can be used to perform stall detection on each blade separately. In this case, the value of N on different blades can be the same or different.

[0063] Secondly, regarding the wind condition detection device 21, specifically, it is used to collect wind condition parameters that differ between normal and stall conditions. In some embodiments, the difference from the normal condition is that, under stall conditions, due to factors such as stagnation rings and blade rotation effects, the pressure in the region from the separation point to the trailing edge not only increases, but the pulsation of the wind condition in this region also intensifies. Therefore, the pressure applied to the leeward surface of the blade and / or the pulsation characteristics of the wind condition on the leeward surface of the blade can be collected as wind condition parameters. In one embodiment, the wind condition detection device 21 may include N wind-sensing components, each corresponding to one of the N blade positions. At least one of the N wind-sensing components is a wind-sensing component with a detection function. For example, to collect the pressure applied to a certain blade position, the wind-sensing component may include a pressure sensor corresponding to that blade position. The number of pressure sensors is an integer not greater than N, meaning that pressure sensors can be used to collect wind condition parameters at all or some of the N blade positions. In another embodiment, at least one of the N wind-sensing components is a wind-sensing component without detection function, such as a swing component. Specifically, to collect the pulsation characteristics of wind conditions at a certain blade position, a swing component can be set at that blade position to characterize the pulsation characteristics of the wind condition by the characteristics of the swing component being driven by the wind. Accordingly, the wind condition detection device 21 also includes at least one swing component and at least one monitoring device for the swing component, used to detect the swing angle and / or swing frequency of the swing component. The number of swing components is an integer not greater than N, that is, the swing components and their monitoring devices can be used to collect wind condition parameters at all or some of the N blade positions. The number of monitoring devices can be one or more. When there are multiple monitoring devices, each monitoring device can monitor one or more swing components. In one example, the wind condition detection device 21 may include N1 pressure sensors, N2 swing components, and monitoring devices for N2 swing components, where N1 + N2 = N. N1 and N2 can be integers greater than or equal to 0.

[0064] Regarding quantity, in some embodiments, to improve detection accuracy and reliability, the number of wind-sensing components can be increased, i.e., more wind-sensing components can be used to detect wind condition data at more blade locations. In other embodiments, due to equipment cost and to minimize the impact of the wind condition detection device 21 on the airflow over the blade surface, the number of components at each blade location can be reduced, i.e., the number of wind-sensing components can be reduced. For example, detection can be performed only at one blade location, and correspondingly, only one wind-sensing component can be used. The specific number of wind-sensing components can be set according to actual needs and specific scenarios, and is not specifically limited thereto. In a specific example, the number of wind-sensing components can be determined based on at least one of the following factors: the size of the blade's output area, the spacing between the wind-sensing components in the wind condition detection device 21, equipment cost, and the impact of airflow over the blade surface.

[0065] Next, the following embodiments of this application will provide a detailed description of the pressure sensor and the monitoring device for the swing component.

[0066] First, regarding pressure sensors.

[0067] Regarding the specific type, it can be a thin-film pressure sensor, an oil film pressure sensor, a piezoresistive pressure sensor, or other sensors with pressure acquisition functions. This application does not limit the type. Furthermore, the pressure sensor can be absolute pressure type, or it can be gauge pressure type or differential pressure type. This application does not limit the pressure measurement method.

[0068] Regarding the location settings, in some embodiments, Figure 6 This is a schematic diagram illustrating the installation location of a pressure sensor according to an embodiment of this application. Figure 6 As shown, to prevent the pressure sensor from affecting the airflow on the blade surface, the pressure sensor can be embedded inside the blade body 11 and close to the leeward side 1112 of the blade. Specifically, during the blade manufacturing process, it can be embedded inside the blade body 11 using a pre-embedding process. In one example, each pressure sensor can be installed inside the blade body 11 and attached to the blade position corresponding to that pressure sensor.

[0069] This setting method reduces the interference of measurements on the operation of the blades themselves, enabling seamless measurement of wind parameters.

[0070] In one embodiment, to facilitate signal acquisition and processing by the pressure sensor, the wind turbine blade stall detection system 20 further includes a transmission line 30 connected to the pressure sensor. One end of each transmission line 30 is located inside the blade body 11 and connected to a pressure sensor, while the other end of the transmission line 30 passes through the blade body 11 and extends into the blade cavity 12. The transmission lines 30 can be pre-embedded during the blade manufacturing process.

[0071] In one example, transmission line 30 may include a power transmission line and / or a signal transmission line. For instance, if transmission line 30 includes a power transmission line, the end of the power transmission line extending into the blade cavity 12 can be connected to a power source, thereby transmitting electrical energy from the power source to the pressure sensor to power it. Alternatively, if transmission line 30 includes a signal transmission line, the end of the signal transmission line extending into the blade cavity 12 can be connected to a signal acquisition device. Thus, after the pressure sensor converts the acquired pressure signal into electrical signals such as voltage and current, the electrical signals are transmitted to the signal acquisition device via the signal transmission line, facilitating subsequent stall determination based on the pressure value represented by the electrical signal.

[0072] Regarding the distribution of pressure sensors: If there are multiple pressure sensors, they can be arranged in an array. Alternatively, they can be distributed in other forms; there are no specific limitations on this.

[0073] In some embodiments, taking the wind condition detection device 21 as an example, which includes N pressure sensors corresponding one-to-one with the positions of N blades, the pressure sensors can be placed within a preset area during the optimization of their arrangement. This ensures that relatively accurate wind condition parameters are collected while reducing the impact of the pressure sensors on the blades and lowering equipment costs. Accordingly, the distribution of the pressure sensors in the chordal X and / or axial Y directions can be optimized. The distribution in both the chordal X and axial Y directions will be described in detail below.

[0074] Regarding the distribution of pressure sensors along the chordal X-axis, in one embodiment, during the optimization of the pressure sensor arrangement, since the flow separation phenomenon during blade stall mainly occurs in the region between the maximum thickness region and the trailing edge, N blade positions are arranged on the leeward side of the blade between the maximum thickness region and the trailing edge. Accordingly, since each pressure sensor is used to collect the pressure value at one blade position, the N pressure sensors can be located between the maximum thickness region and the trailing edge. See also, for an example, [further details omitted]. Figure 6 The area of ​​maximum thickness is Figure 6 The cross-section shown corresponds to the maximum thickness line AA, so N pressure sensors can be located between the maximum thickness line AA and the trailing edge 16.

[0075] In one embodiment, since the flow separation phenomenon of the airflow at the trailing edge of the blade has little impact on the blade stall, in order to optimize the arrangement of the pressure sensors, the blade position and the corresponding pressure sensor on the blade cross section in the Z-axis direction can be located between the maximum thickness line AA and the thickness line BB.

[0076] Accordingly, if on each cross-section of axis X where pressure sensors are distributed, the distance between the maximum thickness line AA and the trailing edge is a% of the chord length, the distance between the thickness line BB and the trailing edge is b% of the chord length, and the distance between each pressure sensor and the trailing edge 16 is x%, then the value of x is within the range [b, a]. Here, b can be determined based on the effect of flow separation on blade stall. In one example, the value of b could be 10.

[0077] In a specific example, in order to further optimize the arrangement of pressure sensors, the blade position and the corresponding pressure sensor can be located on the thickness line BB. That is, on each axis X cross section where pressure sensors are distributed, the distance between the pressure sensor and the trailing edge 16 is 10% of the chord length.

[0078] Regarding the distribution of pressure sensors along the Z-axis, since the driving torque provided to the main shaft varies at different positions of the blades along the Z-axis—for example, the driving torque provided at the blade root 13 and blade tip 14 is smaller than that at other positions—the pressure sensors can be positioned at the blade locations or in the intermediate or transitional sections between the blade root 13 and blade tip 14.

[0079] In some embodiments, during the optimization of the pressure sensor arrangement, since a larger driving torque is provided from a location where the distance from the blade root 13 accounts for 30% to 80% of the total blade axis length, the ratio of the first distance from the blade root 13 at N blade positions along the axial direction Z to the total blade axis length is within a preset range. Here, the blade axis length is the length of the blade 10 along the axial direction Z. The lower limit of this preset range is 30%, and the upper limit is 80%. It should be noted that the specific upper and lower limits of the preset range can be set according to the actual scenario and specific needs; for example, it can be an empirical range, and this embodiment does not specifically limit it.

[0080] For example, Figure 7 This is a schematic diagram illustrating another pressure sensor placement location provided in an embodiment of this application. See also... Figure 7 The distance between the first edge line CC and the blade root 13 accounts for 30% of the total blade axis length, and the distance between the second edge line DD and the blade root 13 accounts for 80% of the total blade axis length. Along the Z-axis, N pressure sensors can be distributed within the region between the first edge line CC and the second edge line DD. Accordingly, the N pressure sensors are arranged in an array within this region.

[0081] In one example, to further optimize the arrangement of pressure sensors, one or more pressure sensors can be installed in the leeward housing 112, a cross-section with a distance of 30% to 80% of the blade axis length from the blade root 13, within a region axially oriented from the blade root 13. This is because larger driving torques are provided at positions 50% and 80% of the blade axis length from the blade root 13. Alternatively, one or more pressure sensors can be installed in the leeward housing 112, a cross-section with a distance of 80% of the blade axis length from the blade root 13. It should be noted that, based on actual conditions and specific needs, as well as fitting data or actual measurement data of the actual power output area of ​​the wind turbine, pressure sensors can be installed in cross-sections other than 50% or 80%. This embodiment does not limit this selection.

[0082] In one example, the number of pressure sensors can be one. In this case, one pressure sensor can be installed in the lee housing 112 of the cross section where the distance from the blade root in the axial direction accounts for 80% of the total blade axis length, or in the lee housing 112 of the cross section where the distance from the blade root in the axial direction accounts for 50% of the total blade axis length, and the distance from the pressure sensor to the trailing edge 16 in the chord X direction accounts for 10% of the total chord length.

[0083] After introducing the pressure sensor, the following sections of the embodiments of this application will provide a detailed description of the monitoring device for the swinging component.

[0084] First, since the wind turbine blade stall detection system also needs to include a oscillating component that works in conjunction with the monitoring device for the oscillating component during the blade stall detection process, we will first provide a detailed explanation of the oscillating component before formally introducing the monitoring device for the oscillating component.

[0085] A oscillating component is a part that can oscillate according to the wind conditions on the leeward side of the blades. The oscillating component can be linear, such as straight, or curved, and its shape is not specifically limited. In some embodiments, to avoid the influence of elastic deformation of the oscillating component itself on the accuracy of wind condition parameters, the oscillating component can be made of a material with high stiffness, such as high-stiffness metal wires or metal strips, or high-stiffness fiber filaments, such as wool or synthetic fibers. In other embodiments, to avoid the influence of the oscillating component on the weight of the blades, the oscillating component can be made of a lightweight material, thereby enabling imperceptible measurement of wind condition parameters. In one example, based on the above factors, a lightweight and high-stiff material can be selected as the oscillating component, such as wool.

[0086] Figure 8This is a schematic diagram of a swinging component in a windless state, provided in an embodiment of this application. Figure 8 As shown, one end of the swing component 22 is connected to the leeward side 1112 of the blade, and the other end of the swing component 22 is not connected to other components and is in a free swinging state.

[0087] Figure 9 This is a schematic diagram of a swinging component provided in this application under windy and windless conditions. Figure 10 yes Figure 9 A magnified view of a portion of region E in the middle. Please refer to the attached image. Figure 9 and Figure 10 In a windless state, the length extension direction of the oscillating component 22 is consistent with the chordal X direction of the blades. In a windy state, the oscillating component 22 oscillates with one end as a fixed point and its own length as a radius. The oscillation angle α of the oscillating component 22 in a windy state represents the angle by which the oscillating component 22 deviates from the chordal X direction of the fan.

[0088] Furthermore, the specific distribution of the oscillating components on the leeward side of the blades is the same as that of the pressure sensors, and will not be elaborated further here.

[0089] After introducing the swing component 22, the following sections of this application embodiment will provide a detailed description of the monitoring device for the swing component 22.

[0090] The monitoring device for the oscillating component 22 can be a monitoring device capable of acquiring oscillation characteristics such as the oscillation frequency and oscillation angle of the oscillating component, such as an image acquisition device or a proximity switch. In some embodiments, if the monitoring device for the oscillating component 22 is an image acquisition device, it can be installed at a location where the leeward side of the blade can be observed, such as on the outer wall of the tower. In other embodiments, if the monitoring device for the oscillating component 22 is a proximity switch, the proximity switch can be located on the leeward side of the blade. Specifically, in a windless state, the sensing surface of the proximity switch can sense the oscillating component 22. In a windy state, the proximity switch cannot sense the oscillating component 22.

[0091] After fully introducing the data acquisition device provided in the embodiments of this application, the following embodiments of this application will describe the blade stall detection device.

[0092] The blade stall detection device 23 is used to determine whether there is stall at N blade positions based on the wind condition data collected by the wind condition detection device 21, and to generate stall detection results at N blade positions.

[0093] Having thoroughly described the blade stall detection device 23 above, the blade will now be described in detail. For the blade 10, a wind-sensing component is provided on its leeward side. In some embodiments, the wind-sensing component includes at least one pressure sensor and / or at least one oscillation component. The specific details of the wind-sensing component can be found in the relevant sections of the embodiments of this application above, and will not be repeated here.

[0094] In addition, other details about blade 10 can be found in the combined description. Figure 2 and Figure 3 The specific details will not be elaborated upon here.

[0095] In some embodiments, the wind turbine blade stall detection system 20 may further include a control device. The control device can determine whether the blade is stalling based on the stall detection result at the blade location. In one example, after determining that the blade is stalling, the wind turbine can also be controlled according to a corresponding wind turbine control strategy.

[0096] After fully introducing the wind turbine blade stall detection system provided in the embodiments of this application, the embodiments of this application will now provide a detailed description of the blade stall detection device.

[0097] Before fully understanding the blade stall detection device provided in the embodiments of this application, the embodiments of this application will first provide a detailed description of the blade stall detection method.

[0098] Figure 11 This is a flowchart illustrating the first wind turbine blade stall detection method provided in this application. The execution entity for each step of the blade stall detection method in this application can be a module or component with control capabilities, either inside or outside the wind turbine generator set. For example, it could be the main controller of the wind turbine generator set, a newly added blade stall detection module, or the control modules of the existing component systems. This application does not specifically limit this.

[0099] like Figure 11 As shown, the wind turbine blade stall detection method may include S1110 to S1130.

[0100] S1110: Obtain wind condition data at the blade position on the leeward side of the blade. The number of blade positions in S1110 can be N, where N is an integer greater than or equal to 1.

[0101] In S1110, the wind condition data includes wind condition parameters at M acquisition times within the target time period. Here, M is an integer greater than or equal to 1. That is, M wind condition parameters within the target time period are acquired at the blade location.

[0102] First, regarding wind condition data. Wind condition data is used to reflect the wind condition characteristics on the blade surface. Specifically, it can be wind condition characteristics that differentiate between normal and stall conditions.

[0103] In some embodiments, due to the effects of stagnation rings and blade rotation during stall, the pressure in the region from the separation point to the trailing edge not only increases, but the pulsation of the wind conditions in this region also intensifies. If the wind condition parameter at the j-th acquisition time of the i-th blade position within the target time period is expressed as wind condition parameter W... ij Where i is any positive integer less than or equal to N, and j is any positive integer greater than 1 and less than or equal to M. Wind condition parameter W ij It may include at least one of the following parameters AC:

[0104] Parameter A: Pressure P applied by the wind at the i-th blade position on the leeward side of the blade. ij .

[0105] Parameter B, the swing angle α of the swing component at the i-th blade position on the leeward side of the wind-driven blade. ij .

[0106] Parameter C, the oscillation frequency f of the oscillating component at the i-th blade position on the leeward side of the wind-driven blade. ij .

[0107] Here, parameter A represents the airflow pressure at the i-th blade position on the leeward side of the blade. Parameters B and C represent the pulsation of the wind conditions at the i-th blade position at the j-th moment. Furthermore, other details regarding parameters AC can be found in the relevant descriptions of the embodiments of this application in conjunction with the data acquisition device, and will not be repeated here.

[0108] By measuring the above parameters, stall phenomenon data can be directly measured, which avoids the decrease in accuracy caused by the calculation method compared to data obtained indirectly such as blade angle of attack and output power.

[0109] Secondly, the target time period can represent the time period during which stall detection is required. It can be a specific period, or, when periodic detection of blade stall is needed, each cycle can be considered a target time period. In some embodiments, the target time period can be determined based on the analysis time step, and its duration can be set according to specific scenarios and actual needs, without limitation. In some embodiments, the number of data acquisition moments within the target time period can be determined based on the data acquisition frequency and analysis time step of the acquisition device, without specific limitation. For example, if the data acquisition frequency and analysis time step are 50 Hz and 10 minutes respectively, a target time period can include 50 * 60 * 10 = 30,000 acquisition moments. Correspondingly, a wind condition data set includes 30,000 wind condition parameters.

[0110] Secondly, regarding the specific implementation of S1110.

[0111] In some embodiments, wind condition parameters can be acquired through a data acquisition device. For example, each data acquisition device acquires the wind condition parameters at the corresponding blade position, converts them into corresponding electrical signals, sends the electrical signals to a signal collection device, and then the signal collection device sends them to the execution body of S110.

[0112] S1120, based on wind condition data at the blade location, determines the distribution characteristic parameters of wind conditions at the blade location within the target time period.

[0113] In some embodiments, the distribution characteristic parameters include: the average of M wind condition parameters and / or the variance of M wind condition parameters. In one example, if M equals 1, the value of the wind condition parameter can be used as the average value over the target time period.

[0114] Specifically, for the i-th blade position, the average wind condition parameter can reflect the magnitude of the wind condition parameter within the target time period. The following formula (1) can be satisfied:

[0115]

[0116] Among them, W ij It can be the pressure value P applied by the wind at the i-th blade position on the leeward side of the blade. ij Or, the swing angle α of the swinging component at the i-th blade position driven by the wind. ij Or, the oscillation frequency f of the oscillating component at the i-th blade position driven by the wind. ij .

[0117] Secondly, for the i-th blade position, the variance of its wind condition parameters can reflect the pulsation of wind conditions within the target time period. The variance σ of the wind condition parameters can satisfy the following formula (2):

[0118]

[0119] S1130 detects whether the blade is stalling based on the distribution characteristic parameters of each blade position and the preset blade stall conditions.

[0120] First, regarding the preset blade stall condition, this condition is used to determine whether stall has occurred at each blade location. In other words, if the distribution characteristic parameters at a certain blade location meet the preset blade stall condition, then blade stall is determined to have occurred at that location. If the distribution characteristic parameters at a certain blade location do not meet the preset blade stall condition, then blade stall is determined not to have occurred at that location.

[0121] In some embodiments, when the distribution characteristic parameters include the average value of M wind condition parameters, the preset blade stall condition includes: the average value of the M wind condition parameters is greater than a preset wind condition parameter threshold.

[0122] Taking the wind condition parameter as the pressure value applied by the wind to the leeward side of the blade as an example, the preset wind condition parameter threshold can be a preset pressure threshold. Because in a stall state, the pressure in the region from the airflow separation point to the trailing edge increases due to the stagnation ring and blade rotation effect, leading to an increase in the pressure applied by the wind to the leeward side of the blade. Therefore, by determining whether the average pressure value applied by the wind at each blade location is greater than the preset pressure threshold, it is possible to determine whether a blade stall occurs at that location.

[0123] Taking the swing angle or swing frequency of the oscillating component as an example, the preset wind condition parameter thresholds can be preset angle thresholds and preset frequency thresholds, respectively. Because airflow pulsation intensifies during stall, the swing angle and swing frequency of the oscillating component increase. Therefore, by determining whether the average swing angle of the oscillating component is greater than the preset angle threshold, or whether the average swing frequency of the oscillating component is greater than the preset frequency threshold, it is possible to determine whether a blade stall occurs at that location.

[0124] It should be noted that, in actual wind turbine operation scenarios, normal turbulence may occasionally cause wind condition parameters such as pressure values ​​to be too high at certain times. The embodiments of this application utilize whether the average value of wind condition parameters within the target time period is greater than a threshold. This can avoid the possibility of misjudging the excessive wind condition parameters at certain sampling times caused by normal turbulence as blade stall, and further improve the detection accuracy of blade stall.

[0125] In other embodiments, when the distribution characteristic parameters include the variances of M wind condition parameters, the preset blade stall condition includes: the variances of the M wind condition parameters are less than a preset variance threshold.

[0126] Because wind parameters can be too high at certain times during normal turbulence, leading to an overall higher average wind parameter value, the applicant's research found that when the average wind parameter value caused by normal turbulence is too high, the variance of the wind parameter value also increases. Therefore, by determining whether the variance of the wind parameter value is less than a preset variance threshold, it is possible to further avoid misjudgment of blade stall caused by an excessively high average wind parameter value due to normal turbulence, thereby further improving the detection accuracy of blade stall.

[0127] In one example, to improve the detection accuracy of blade stall, the preset blade stall condition can be expressed as:

[0128] This application embodiment uses the preset blade stall condition to identify and distinguish between normal surface pressure pulsations and stall pulsations.

[0129] After introducing the preset blade stall conditions, this application will now describe a specific implementation of S130.

[0130] In some embodiments, if N is 1, the distribution characteristic parameters at the blade position satisfy the preset blade stall condition, and the wind turbine blade stall can be determined.

[0131] In other embodiments, if N is an integer greater than or equal to 2, the distribution characteristic parameters at any of the N blade positions can satisfy the preset blade stall condition, thus determining the wind turbine blade stall.

[0132] In some other embodiments, in order to improve the stall detection accuracy and the reliability of the detection method, when N is an integer greater than or equal to 2, the stall detection results at the N sampled blade positions can be used to comprehensively determine whether the blade has stalled.

[0133] Accordingly, Figure 12 This is a flowchart illustrating the second wind turbine blade stall detection method provided in this application embodiment. Figure 12 and Figure 11 The difference is that S1130 can specifically include S1131 and S1132.

[0134] S1131, based on the distribution characteristic parameters at the blade position and the preset blade stall conditions, detect whether stall has occurred at each blade position, and obtain the stall detection result at each blade position.

[0135] In S1131, the stall detection result at each blade position may include a first stall detection result characterizing the stall at that blade position, and a second stall detection result indicating that the blade position has not stalled.

[0136] In one example, the first stall detection result and the second stall detection result can be represented by data identifiers. Specifically, the first stall detection result and the second stall detection result can be represented by different blade identifiers.

[0137] Accordingly, S1131 may specifically include steps A1 and A2.

[0138] Step A1: If the distribution characteristic parameters at the blade location meet the preset blade stall conditions, it is determined that a stall has occurred at that blade location, and a first stall detection result carrying a blade stall indicator is generated. For example, if a stall occurs at that blade location, a first digital signal BladeStall = 1 is generated.

[0139] Step A2: If the distribution characteristic parameters at the blade location do not meet the preset blade stall conditions, it is determined that no stall has occurred at that blade location, and a second stall detection result carrying a blade no-stall indicator is generated. For example, if no stall has occurred at that blade location, a second digital signal BladeStall = 0 is generated.

[0140] It should be noted that the first stall detection result and the second stall detection result can also be represented in other forms. For example, a detection result message can be generated. If the value of a certain field in the message is 1, it indicates that a stall has occurred; if the value of a certain field is 0, it indicates that no stall has occurred. This application does not specifically limit the representation of the first stall result and the second stall result in the embodiments.

[0141] S1132, based on the stall detection results at the at least one blade position, determine the ratio of the number of blade positions where stall occurred to the total number of blade positions D, and determine that the blade has stalled when the ratio is greater than or equal to a preset threshold.

[0142] In one embodiment, the executing entity of S1132 may be a different functional module or component of the same control device as the executing entity of S1131, or it may be two different control devices, which will not be elaborated further in this embodiment. In one example, the executing entity of S1132 may be the main controller of a wind turbine.

[0143] In some embodiments, the preset ratio threshold can be 30%. It should be noted that the preset ratio threshold can be set according to the actual scenario and specific needs, or it can be other values, without specific limitations.

[0144] In some embodiments, if the stall result can be bladestall = 0 or bladestall = 1, then the ratio of the number of 1s in the stall result to the total number D at the blade position can be calculated.

[0145] In some embodiments, the total number of blade positions can be N. Accordingly, the control device can count the proportion of blade positions where stall occurs among the N blade positions, and then determine whether the blade has stalled based on the proportion.

[0146] In other embodiments, the total number D at the blade positions can be an integer greater than N. Accordingly, the control device determines whether a blade has stalled by determining the proportion of blade positions where stalling has occurred among the D blade positions. In one example, since the stall results at the D blade positions may not be sent to the control device simultaneously, the control device can, while receiving the stall results at the D blade positions, determine in real time whether the number of stalled blade positions reaches the product of D and a preset threshold. If the number of stalled blade positions is greater than or equal to the product of D and the preset threshold, the control device determines that the blade has stalled.

[0147] Among them, the D blade positions can be located on one blade of the wind turbine or on at least two blades of the wind turbine, without limitation.

[0148] In some embodiments, to further improve blade safety, the wind turbine generator can be controlled to change its operating state after blade stall is detected. Figure 13 This is a flowchart illustrating the third wind turbine blade stall detection method provided in this application embodiment. Figure 13 and Figure 12 The difference is that, after S1130, wind turbine blade stall detection also includes S1140.

[0149] S1140, when the control equipment determines that the blades have stalled, it controls the fan to operate according to a preset control strategy.

[0150] In one embodiment, the preset control strategy is a strategy for instructing the wind turbine to pitch, such as controlling the wind turbine to increase the pitch angle. For example, the wind turbine pitch can be controlled by the main controller sending a command to the controller of the pitch system to increase the pitch angle.

[0151] By controlling the wind turbine's blade retraction, risks such as blade cracking caused by blade flutter can be prevented in a timely manner, thus improving the safety of wind turbine operation.

[0152] In another example, the wind turbine control command is a strategy to control the wind turbine generator to increase its rotational speed.

[0153] Specifically, the main controller can send a command to the generator controller to increase the speed of the wind turbine generator set.

[0154] By increasing the rotational speed of the wind turbine generator set, the output power of the wind turbine generator set can be guaranteed as much as possible.

[0155] In yet another example, the wind turbine control commands are strategies for controlling the shutdown of the wind turbine generator set. In one example, during the shutdown process, the main controller can send a shutdown control command to the pitch controller, which then retracts the pitch. It can also send a shutdown control command to the generator controller to gradually reduce the generator speed, and send a shutdown control command to the braking system to activate the brake discs.

[0156] In one embodiment, a suitable control method can be selected from the three control strategies mentioned above based on factors such as wind speed, operational safety, and output power. In one example, when the wind speed is less than a preset wind speed threshold (i.e., when the wind speed is low), the wind turbine generator is shut down. The preset wind speed threshold can be a critical wind speed value that distinguishes between strong and light winds, and it can be set according to the actual scenario and specific needs; for example, it could be 12 m / s. In another example, when the wind speed is greater than or equal to the preset threshold (i.e., when the wind speed is high), if it is necessary to improve the wind turbine's operational safety, the turbine's pitch angle can be increased. In yet another example, when the wind speed is greater than or equal to the preset threshold (i.e., when the wind speed is high), if it is necessary to maximize output power, the turbine's rotational speed can be increased.

[0157] In some embodiments, if the wind condition parameters include the pressure value applied by the wind to the leeward side of the blades, the preset blade stall condition includes the average value of M pressure values ​​being greater than a preset pressure threshold. Since the air pressure data varies depending on the geographical environment and the height of the wind turbine, a suitable preset pressure threshold can be set according to the environment in which the wind turbine is located.

[0158] Accordingly, Figure 14 This is a flowchart illustrating the fourth wind turbine blade stall detection method provided in this application embodiment. Figure 14 and Figure 11 The difference is that, prior to S1130, the method also includes S1150 and S1160.

[0159] S1150, Obtain the atmospheric pressure value of the environment where the wind turbine blades are located. In some embodiments, the atmospheric pressure value can be collected by an atmospheric pressure sensor. In one example, considering the influence of blade height, the atmospheric pressure sensor can be placed at a position close to the blade height, such as the top of the nacelle or the hub, or it can be placed on the blade. The specific placement position of the atmospheric pressure sensor is not limited in this application embodiment.

[0160] S1160, based on the preset ratio between atmospheric pressure value and wind condition parameter threshold, determines the preset wind condition parameter threshold corresponding to the atmospheric pressure value.

[0161] In one example, a baseline atmospheric pressure value and its corresponding wind condition parameter threshold can be determined. Then, through linear transformation, a preset wind condition parameter threshold corresponding to the atmospheric pressure value of the surrounding environment can be calculated. For example, if the baseline atmospheric pressure 'a' corresponds to the wind condition parameter threshold W0, and the atmospheric pressure value 'b' of the surrounding environment corresponds to the preset wind condition parameter threshold W... th Then it satisfies the following formula (3):

[0162]

[0163] For example, the reference atmospheric pressure value can be 1 standard atmosphere. If the atmospheric pressure of the environment where the wind turbine blades are located is 0.8 standard atmospheres, then the preset wind condition parameter threshold W corresponding to the atmospheric pressure value b of the environment is... th =0.8W0.

[0164] In one example, different preset pressure thresholds can be set for different airfoils. For instance, preset pressure thresholds for different airfoils can be set according to the actual scenario and specific requirements.

[0165] In one example, the preset pressure threshold of the airfoil under the atmospheric pressure of the wind turbine environment can be determined based on the reference atmospheric pressure under a certain airfoil and the preset pressure threshold corresponding to the reference atmospheric pressure.

[0166] In this embodiment, when using the pressure value applied by the wind to the leeward side of the blade to detect blade stall, a suitable preset pressure threshold can be selected according to the atmospheric pressure of the wind turbine generator environment, thereby improving the detection accuracy of blade stall.

[0167] In some embodiments, since the wind turbine blades are rotating, the pressure sensor will be affected by changes in its own weight, which in turn affects the accuracy of wind condition data acquisition. Therefore, in order to avoid the impact of the accuracy of wind condition parameter acquisition on the blade detection accuracy, the deviation of wind condition data caused by gravity effect can be compensated.

[0168] Accordingly, Figure 15 This is a flowchart illustrating the fifth wind turbine blade stall detection method provided in this application embodiment. Figure 15 and Figure 11 The difference is that, after S1110, the wind turbine blade stall detection methods also include S1170 to S1190.

[0169] S1170, for at least one wind condition parameter among M wind condition data, obtains the impeller azimuth angle of the wind turbine at the time of acquisition of at least one wind condition parameter. In other words, S1170 can compensate for some or all wind condition parameters, without limitation.

[0170] In one embodiment, an impeller azimuth angle can be acquired at each acquisition moment.

[0171] In another embodiment, an impeller azimuth angle can be acquired at preset time intervals, and this impeller azimuth angle can be used as the impeller azimuth angle for all acquisition times within the preset time interval. The preset time interval can be selected according to the actual scenario and specific needs, and this embodiment does not limit this selection.

[0172] In one embodiment, the impeller azimuth angle can be acquired using a detection device with angle detection function, such as an absolute encoder or a relative encoder, or it can be estimated based on information such as the impeller rotation speed. This application does not limit the specific method for obtaining the impeller azimuth angle.

[0173] S1180, determine the wind condition parameter compensation amount corresponding to the impeller azimuth angle.

[0174] In one embodiment, the wind condition parameter compensation amount corresponding to the impeller azimuth angle can be determined for at least one blade position; alternatively, the wind condition parameter compensation amount corresponding to the impeller azimuth angle for all blade positions on the same cross section can be determined; furthermore, the wind condition parameter compensation amount corresponding to the impeller azimuth angle for at least one blade can be determined for different blades; or, the same wind condition parameter compensation amount corresponding to the impeller azimuth angle can be determined for all blade positions. This application does not limit this approach.

[0175] In one embodiment, the wind condition parameter compensation amount can be calculated using an interpolation method. Accordingly, S1180 may specifically include steps B1 to B3.

[0176] Step B1: Obtain wind condition parameters under multiple reference angle values.

[0177] In one example, the wind condition parameters under multiple reference angle values ​​can be historical wind condition parameters of the wind turbine or experimental data, without specific limitations.

[0178] In one example, a preset angle value can be used at intervals, and one angle value can be selected as a reference angle value. For example, starting from 0°, a reference angle value can be set at 15° intervals, such as 0°, 15°, 30°, ..., 233°, 345°. Alternatively, a reference angle value can be set at 90° intervals, such as 0°, 90°, 180°, 270°. This application does not specifically limit the interval step size of the reference angle values; a suitable interval step size can be selected according to actual needs and specific scenarios. For example, considering calculation accuracy, a smaller interval step size can be set; considering calculation efficiency, a larger interval step size can be selected.

[0179] In addition, other methods of selecting the reference angle value may be used in the embodiments of this application, such as random selection, and no specific limitation is made thereto.

[0180] Step B2: Use zero as the wind condition parameter compensation amount for the first reference angle value, and determine the difference between the wind condition parameter of the first reference angle value and each reference angle value other than the first reference angle value as the wind condition parameter compensation amount for each reference angle value.

[0181] For example, if the wind condition parameter corresponding to 0° is W0, the wind condition parameter corresponding to 90° is W1, the wind condition parameter corresponding to 180° is W2, and the wind condition parameter corresponding to 270° is W3, then the compensation amount for the wind condition parameter corresponding to 0° can be determined as ΔW0 (0), the compensation amount for the wind condition parameter corresponding to 90° can be determined as ΔW1 (W0-W1), the compensation amount for the wind condition parameter corresponding to 180° can be determined as ΔW2 (W0-W2), and the compensation amount for the wind condition parameter corresponding to 270° can be determined as ΔW3 (W0-W3).

[0182] Step B3 involves interpolating the wind condition parameter compensation amounts corresponding to each of the multiple reference angle values ​​to obtain the wind condition parameter compensation amounts corresponding to the impeller azimuth angle.

[0183] In the embodiments of this application, either a linear interpolation algorithm or a nonlinear interpolation algorithm may be used. This application does not specifically limit the methods used in this regard.

[0184] S1190 uses wind condition parameter compensation to compensate for at least one wind condition parameter.

[0185] For example, the sum of each wind condition parameter and the wind condition parameter compensation amount can be determined as the compensated wind condition parameter.

[0186] Accordingly, S1120 may specifically include:

[0187] S1121, using M wind condition parameters after compensation for at least one wind condition parameter, determine the distribution characteristic parameters of the wind condition at each blade position within the target time period.

[0188] It should be noted that the method for calculating the distribution characteristic parameters using the compensated wind condition parameters can be found in the relevant content in S1120, and will not be repeated here.

[0189] To facilitate understanding of the blade stall detection method in the embodiments of this application, Figure 16 This is a schematic flowchart of an exemplary wind turbine blade stall detection method provided in an embodiment of this application.

[0190] like Figure 16 As shown, the wind turbine blade stall detection method can be implemented by the wind turbine blade stall detection device 23 and the control device 24. In some embodiments, the wind turbine blade stall detection device 23 and the control device 24 can be two independent devices, or they can be two functional modules in one device. This application embodiment does not limit this.

[0191] Specifically, the wind turbine blade stall detection method may include S1601 to S1608.

[0192] S1601, for the i-th blade position out of N blade positions, the wind turbine blade stall detection device 23 collects pressure data at the i-th blade position. The pressure data can be 30,000 pressure values ​​collected within 10 minutes at a sampling frequency of 50Hz.

[0193] S1602, the wind turbine blade stall detection device 23 performs time-series data processing on 30,000 pressure values ​​at the i-th blade position to obtain the average pressure value at the i-th blade position. and variance

[0194] Among them, the average value and variance It can be calculated according to the above formulas (1) and (2) respectively.

[0195] S1603, the wind turbine blade stall detection device 23 acquires the atmospheric pressure value of the environment in which the blade is located.

[0196] S1604, the wind turbine blade stall detection device 23 determines the preset pressure threshold corresponding to the atmospheric pressure value.

[0197] For the specific implementation of S1604, please refer to the relevant content of S1150 and S1160 above, which will not be repeated here.

[0198] Furthermore, this application embodiment does not specifically limit the execution order between S1601-S1602 and S1603-S1604, that is, the two can be executed sequentially or simultaneously.

[0199] S1605, Wind turbine blade stall detection device 23 judges the average value Is it greater than the preset pressure threshold P? th And variance Less than the preset variance threshold S i If the judgment result is negative, wait for the next target time period and re-execute S1601 and S1602. If the judgment result is positive, continue to execute S1606.

[0200] S1606, the wind turbine blade stall detection device 23 generates a stall detection result at the i-th blade position and sends it to the control device 24. The stall detection result can be BladeStall = 1.

[0201] It should be noted that if the judgment result of S1605 is negative, the stall detection result of BladeStall=0 can be sent to the control device 24, or it can be left unsent; the comparison is not limited.

[0202] S1607, Control device 24 determines whether the ratio of the number of BladeStall=1 to N is greater than 0.3.

[0203] S1607 If the judgment result is yes, then the control device 24 executes the strategy of stopping, pitching, or increasing speed.

[0204] Based on the same concept, in addition to providing a method for detecting wind turbine blade stall, this application also provides a corresponding wind turbine blade stall detection device.

[0205] The following description, in conjunction with the accompanying drawings, details the wind turbine blade stall detection device according to an embodiment of this application.

[0206] Figure 17 This is a schematic diagram of the structure of a wind turbine blade stall detection device provided in an embodiment of this application. Figure 17 As shown, the wind turbine blade stall detection device 230 includes:

[0207] The wind condition parameter acquisition module 231 is used to acquire wind condition data at the respective positions of the blades on the leeward side of the blades. The wind condition data includes wind condition parameters at M acquisition times within the target time period, where M is an integer greater than or equal to 1.

[0208] The feature parameter determination module 232 is used to determine the distribution feature parameters of the wind conditions at each blade position within a target time period based on the wind condition data at the blade position.

[0209] Stall detection module 233 is used to detect whether the blade is stalling based on the distribution characteristic parameters of each blade position and the preset blade stall conditions.

[0210] In some embodiments of this application, N is an integer greater than or equal to 2.

[0211] Stall detection module 233 includes:

[0212] The detection unit is used to detect whether stall has occurred at at least one blade position based on the distribution characteristic parameters of at least one blade position among N blade positions and the preset blade stall condition, and to obtain the stall detection result at at least one blade position.

[0213] The transmitting unit is used to determine the ratio of the number of blade positions where stall has occurred to the total number of blade positions based on the stall detection results at at least one blade position, and to determine that a blade has stalled when the ratio is greater than or equal to a preset threshold.

[0214] In some embodiments of this application, the stall determination module 233 includes:

[0215] The detection unit is used to detect whether stall has occurred at at least one blade position based on the distribution characteristic parameters of at least one blade position among N blade positions and the preset blade stall condition, and to obtain the stall detection result at at least one blade position.

[0216] Accordingly, the wind turbine blade stall detection system also includes control equipment.

[0217] The control device is used to determine the ratio of the number of blade positions where stall has occurred to the total number of blade positions based on the stall detection results at at least one blade position. When the ratio is greater than or equal to a preset threshold, the device determines that the blade has stalled.

[0218] In some embodiments of this application, the stall determination module 233 specifically includes:

[0219] The first processing unit is used to determine that a stall has occurred at at least one blade position when the distribution characteristic parameters at at least one blade position meet the preset blade stall conditions, and to generate a first stall detection result carrying a blade stall identifier.

[0220] The second processing unit is used to determine that no stall has occurred at at least one blade position when the distribution characteristic parameters at at least one blade position do not meet the preset blade stall conditions, and to generate a second stall detection result carrying a blade non-stall indicator.

[0221] In some embodiments of this application, when the distribution characteristic parameters include the average value of M wind condition parameters, the preset blade stall condition includes: the average value is greater than the preset wind condition parameter threshold.

[0222] Given that the distribution characteristic parameters include the variances of M wind condition parameters, the preset blade stall condition includes: the variance is less than a preset variance threshold.

[0223] In some embodiments of this application, the wind condition parameters include the pressure value applied by the wind at the blade position corresponding to the wind condition parameters, and the preset blade stall condition includes: the average value of M pressure values ​​is greater than a preset pressure threshold.

[0224] The wind turbine blade stall detection device 230 also includes:

[0225] Atmospheric pressure value acquisition module, used to acquire the atmospheric pressure value of the environment where the wind turbine blades are located;

[0226] The threshold determination module is used to determine the preset pressure threshold corresponding to the atmospheric pressure value based on the ratio between the preset atmospheric pressure value and the wind condition parameter threshold.

[0227] In some embodiments of this application, the wind turbine blade stall detection device 230 further includes:

[0228] The azimuth angle acquisition module is used to acquire the impeller azimuth angle of the wind turbine at the time of acquisition of at least one of the M wind condition parameters.

[0229] The compensation amount determination module is used to determine the compensation amount of the wind condition parameters corresponding to the impeller azimuth angle;

[0230] The compensation module is used to compensate for at least one wind condition parameter using the wind condition parameter compensation amount;

[0231] Accordingly, the feature parameter determination module 232 is specifically used for:

[0232] Using M wind condition parameters after compensation for at least one wind condition parameter, determine the distribution characteristic parameters of wind conditions at at least one blade position within the target time period.

[0233] In some embodiments of this application, the compensation amount determination module specifically includes:

[0234] The parameter acquisition unit is used to acquire wind condition parameters under multiple reference angle values;

[0235] The second processing unit is used to take the zero value as the wind condition parameter compensation amount of the first reference angle value, and to determine the difference between the wind condition parameter of the first reference angle value and each reference angle value other than the first reference angle value as the wind condition parameter compensation amount of each reference angle value.

[0236] The compensation amount determination unit is used to interpolate the wind condition parameter compensation amounts corresponding to multiple reference angle values ​​to obtain the wind condition parameter compensation amounts corresponding to the impeller azimuth angle.

[0237] In some embodiments of this application, the wind turbine blade stall detection device further includes:

[0238] The wind turbine control module is used to control the wind turbine to operate according to a preset control strategy when blade stall is detected.

[0239] The preset control strategies include those for instructing the wind turbine to adjust its pitch, increase its speed, or shut down.

[0240] In some embodiments of this application, the wind condition parameters include at least one of the pressure value applied by the wind at the blade position, the swing angle of the swing component at the wind-driven blade position, and the swing frequency of the wind-driven swing component, wherein the swing angle is used to characterize the angle by which the swing component deviates from the chord direction of the blade.

[0241] When the wind condition parameters include the pressure value at the blade position corresponding to the wind condition parameters, the wind turbine includes a pressure sensor installed inside the blade body.

[0242] When wind parameters include the swing angle and / or swing frequency of the swing component, the wind turbine includes the swing component and a monitoring device for the swing component.

[0243] Other details of the wind turbine blade stall detection device according to embodiments of this application, in conjunction with the above. Figures 11 to 16 The wind turbine blade stall detection method described in the example is similar and can achieve the same technical effect. For the sake of brevity, it will not be elaborated further here.

[0244] The wind turbine blade stall detection device of this application can calculate a distribution characteristic parameter based on wind condition parameters collected at M sampling times within a target time period. Since the distribution characteristic parameter accurately reflects the wind condition distribution at the blade location within the target time period, compared to methods that detect blade stall using the blade angle of attack, using the distribution characteristic parameter at the blade location improves the accuracy of blade stall detection. Furthermore, compared to methods that detect blade stall using turbine power, firstly, since faults in turbine components such as motors and converters have a smaller impact on wind condition parameters than blade stall, and the distribution characteristic parameters of wind condition parameters differ under blade stall and normal turbulence conditions, this application embodiment, by using the distribution characteristic parameters at each blade location as the basis for stall judgment, can eliminate the influence of other causes on blade stall detection, thereby improving the accuracy of blade stall detection.

[0245] Figure 18A schematic diagram of the hardware structure of the wind turbine blade stall detection device provided in an embodiment of the present invention is shown.

[0246] The wind turbine blade stall detection device may include a processor 1801 and a memory 1802 storing computer program instructions.

[0247] Specifically, the processor 1801 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 the present invention.

[0248] Memory 1802 may include mass storage for data or instructions. For example, and not limitingly, memory 1802 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. In some instances, memory 1802 may include removable or non-removable (or fixed) media, or memory 1802 may be a non-volatile solid-state memory. In some embodiments, memory 1802 may be internal or external to a wind turbine blade stall detection device.

[0249] In some instances, memory 1802 may be read-only memory (ROM). In one instance, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0250] Memory 1802 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. 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 method according to one aspect of this disclosure.

[0251] Processor 1801 reads and executes computer program instructions stored in memory 1802 to achieve... Figures 11-16 The method in the illustrated embodiment achieves... Figures 11-16 The technical effects achieved by executing the methods / steps shown in the examples are not elaborated here for the sake of brevity.

[0252] In one example, the wind turbine blade stall detection device may also include a communication interface 1803 and a bus 1810. For example, Figure 18 As shown, the processor 1801, memory 1802, and communication interface 1803 are connected through bus 1810 and complete communication with each other.

[0253] The communication interface 1803 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of the present invention.

[0254] Bus 1810 includes hardware, software, or both, that couples components of an online data flow metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (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 1810 may include one or more buses. While specific buses are described and illustrated in embodiments of the invention, the invention contemplates any suitable bus or interconnect.

[0255] The wind turbine blade stall detection device can execute the wind turbine blade stall detection method in the embodiments of the present invention, thereby achieving a combination of Figures 11 to 17 The described method and apparatus for detecting stall in wind turbine blades.

[0256] Furthermore, in conjunction with the wind turbine blade stall detection method in the above embodiments, this invention can be implemented using a computer storage medium. 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 stall detection methods described in the above embodiments.

[0257] It should be clarified that the present invention 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 the present invention 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 the present invention.

[0258] The functional blocks shown in the above structural 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 invention are programs or code segments used to perform the required tasks. The 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.

[0259] It should also be noted that the exemplary embodiments mentioned in this invention describe methods or systems based on a series of steps or apparatus. However, this invention is not limited to the order of the steps described above; 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.

[0260] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatuses, devices, 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 flowchart illustrations, and combinations of blocks in the block diagrams and / or flowchart illustrations, 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.

[0261] The above description is merely a specific embodiment of the present invention. 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 the present invention 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 the present invention, and these modifications or substitutions should all be covered within the protection scope of the present invention.

Claims

1. A method of stall detection for a wind turbine blade, the method comprising: The method comprises: obtaining wind condition data at a blade position on the leeward surface of the blade, the wind condition data comprising wind condition parameters at M collection time points within a target time period, M being an integer greater than or equal to 1; determining a distribution characteristic parameter of the wind condition at the blade position within the target time period according to the wind condition data at the blade position; detecting whether the blade stalls according to the distribution characteristic parameter at the blade position and a preset blade stall condition; after the obtaining of the wind condition data at the blade position on the leeward surface of the blade, the method further comprises: for at least one wind condition parameter of the M wind condition parameters, obtaining an impeller azimuth angle of the wind turbine at the collection time point of the at least one wind condition parameter; determining a wind condition parameter compensation amount corresponding to the impeller azimuth angle; compensating the at least one wind condition parameter by using the wind condition parameter compensation amount; the determining of the distribution characteristic parameter of the wind condition at the blade position within the target time period according to the wind condition data at the blade position comprises: determining the distribution characteristic parameter of the wind condition at the blade position within the target time period by using the M wind condition parameters after the compensation of the at least one wind condition parameter.

2. The method of claim 1, wherein, the determining of the wind condition parameter compensation amount corresponding to the impeller azimuth angle specifically comprises: obtaining wind condition parameters at a plurality of reference angle values; taking zero as a wind condition parameter compensation amount of a first reference angle value, and determining a difference between a wind condition parameter at the first reference angle value and a wind condition parameter at each reference angle value of the plurality of reference angle values other than the first reference angle value as the wind condition parameter compensation amount of the each reference angle value; performing interpolation processing on wind condition parameter compensation amounts corresponding to the plurality of reference angle values respectively to obtain a wind condition parameter compensation amount corresponding to the impeller azimuth angle.

3. The method of claim 1, wherein, the blade positions are set to N, N being a positive integer, when N is an integer greater than or equal to 2, the detecting of whether the blade stalls according to the distribution characteristic parameter at the blade position and the preset blade stall condition comprises: detecting whether stall occurs at at least one blade position of the N blade positions according to the distribution characteristic parameter at the at least one blade position and the preset blade stall condition to obtain a stall detection result at the at least one blade position; determining a ratio of the number of blade positions at which stall occurs to the total number of blade positions according to the stall detection result at the at least one blade position, and determining that the blade stalls when the ratio is greater than or equal to a preset threshold.

4. The method according to claim 3, wherein the detecting of whether stall occurs at the at least one blade position according to the distribution characteristic parameter at the at least one blade position and the preset blade stall condition to obtain a stall detection result at the at least one blade position specifically comprises: determining that stall occurs at the at least one blade position and generating a first stall detection result carrying a blade stall identifier when the distribution characteristic parameter at the at least one blade position meets the preset blade stall condition. In a case where the distribution characteristic parameter at the at least one blade position does not meet the preset blade stall condition, it is determined that stall does not occur at the at least one blade position, and a second stall detection result carrying a blade non-stall identifier is generated.

5. The method according to any one of claims 1 to 4, characterized in that, In a case where the distribution characteristic parameter comprises the average value of the M wind condition parameters, the preset blade stall condition comprises that the average value is greater than a preset wind condition parameter threshold value. In a case where the distribution characteristic parameter comprises the variance of the M wind condition parameters, the preset blade stall condition comprises that the variance is less than a preset variance threshold value.

6. The method of claim 1, wherein, The wind condition parameter comprises a pressure value of the wind applied at the blade position corresponding to the M wind condition parameters, and the preset blade stall condition comprises that the average value of the M pressure values is greater than a preset pressure threshold value, Before the detecting whether the blade stalls according to the distribution characteristic parameter at the blade position and the preset blade stall condition, the method further comprises: obtaining an atmospheric pressure value of an environment in which the fan blade is located; determining a preset pressure threshold value corresponding to the atmospheric pressure value based on a proportional relationship between a preset atmospheric pressure value and a wind condition parameter threshold value.

7. The method of claim 1, wherein, after the detecting whether the blade stalls, the method further comprises: in a case where it is determined that the blade stalls, controlling the fan to operate in a preset control strategy, wherein the preset control strategy comprises a strategy for instructing the fan to pitch, increase a rotating speed, or shut down.

8. The method of any one of claims 1-4, wherein, the wind condition parameter comprises at least one of a swing angle of a swing component driven by the wind at the blade position or a swing frequency of the swing component driven by the wind, wherein the swing angle is used to represent an angle at which the swing component deviates from a chord direction of the blade.

9. A stall detection device for a wind turbine blade, the device comprising: The device comprises: a wind condition parameter acquisition module, configured to acquire wind condition data at a blade position on a leeward surface of the blade, the wind condition data comprising M wind condition parameters at M collection time points within a target time period, M being an integer greater than or equal to 1; a characteristic parameter determination module, configured to determine a distribution characteristic parameter of wind conditions at the blade position within the target time period according to the wind condition data at the blade position; a stall judgment module, configured to detect whether the fan blade stalls according to the distribution characteristic parameter at the blade position and a preset blade stall condition; The device further comprises: an azimuth angle acquisition module, configured to acquire an impeller azimuth angle of the fan at a collection time point of at least one of the M wind condition parameters; a compensation amount determination module, configured to determine a wind condition parameter compensation amount corresponding to the impeller azimuth angle; a compensation module, configured to compensate the at least one wind condition parameter by using the wind condition parameter compensation amount; The characteristic parameter determination module is specifically configured to: determine the distribution characteristic parameter of the wind conditions at the blade position within the target time period by using the M wind condition parameters after the compensation of the at least one wind condition parameter.

10. The device of claim 9, wherein, The number of the blade positions is N, N is a positive integer, When N is an integer greater than or equal to 2, the stall judging module comprises: A stall detecting unit, configured to, for at least one of the N blade positions, detect whether stall occurs at the at least one blade position according to the distribution characteristic parameter of the at least one blade position and a preset blade stall condition, and obtain a stall detection result of the at least one blade position; A stall judging unit, configured to determine a ratio of the number of the blade positions where stall occurs to the total number of the blade positions according to the stall detection result of the at least one blade position, and determine that the blade stalls when the ratio is greater than or equal to a preset threshold.

11. The apparatus according to claim 9 or 10, wherein The fan blade stall detecting apparatus further comprises: A fan control module, configured to control the fan to operate in a preset control strategy when it is determined that the blade stalls, The preset control strategy comprises a strategy for instructing the fan to pitch, increase the rotating speed or stop.

12. A stall detection system for a wind turbine blade, the system comprising: The apparatus comprises: A wind condition detecting apparatus, wherein the wind condition detecting apparatus is configured to detect a wind condition parameter at the blade position. The fan blade stall detecting apparatus according to claim 9.

13. The system according to claim 12, wherein The blade stall detecting apparatus comprises: A stall detecting unit, configured to, for at least one of the N blade positions, detect whether stall occurs at the at least one blade position according to the distribution characteristic parameter of the at least one blade position and a preset blade stall condition, and obtain a stall detection result of the at least one blade position; The system further comprises a control device, The control device is configured to determine a ratio of the number of the blade positions where stall occurs to the total number of the blade positions according to the stall detection result of the at least one blade position, and determine that the blade stalls when the ratio is greater than or equal to a preset threshold.

14. The system according to claim 13, wherein The control device is further configured to: Control the fan to operate in a preset control strategy when it is determined that the blade stalls, The preset control strategy comprises a strategy for instructing the fan to pitch, increase the rotating speed or stop.

15. The system according to claim 12, wherein The ratio of the first distance to the length of the blade in the axial direction is in a preset interval; The first distance is the distance between the blade position and the blade root in the axial direction of the blade, the lower limit of the preset interval is 30%, and the upper limit of the preset interval is 80%.

16. The system according to claim 12, wherein The blade body comprises a leading edge, a trailing edge and a maximum thickness region arranged between the leading edge and the trailing edge in the chordal direction, The blade position is located between the maximum thickness region and the trailing edge.

17. The system according to any one of claims 13-16, wherein The wind condition detecting apparatus comprises at least one pressure sensor, and / or at least one swing component and a monitoring apparatus of the at least one swing component; The at least one pressure sensor corresponds to at least one blade position one by one; the blade comprises a blade body and a blade inner cavity formed by the blade body, a leeward surface is formed on an outer surface of the blade body, the at least one pressure sensor is embedded in the blade body and close to one side of the blade leeward surface; and / or, The at least one swing component corresponds to the at least one blade position one by one, one end of the at least one swing component is connected to the blade position corresponding to the at least one swing component, Wherein, in the windless state, the length extension direction of the at least one swing component is consistent with the chord direction of the blade, and in the windy state, the at least one swing component swings with one end of the swing component as the fixed point.

18. A wind power unit, characterized in that The fan blade stall detection device comprises: The fan blade stall detection device according to any one of claims 9-11.

19. A wind power unit, characterized in that The fan blade stall detection system comprises: The fan blade stall detection system according to any one of claims 12-17.

20. A stall detection apparatus for a wind turbine blade, the apparatus comprising: The device comprises a processor and a memory storing computer program instructions; The processor reads and executes the computer program instructions to realize the fan blade stall detection method according to any one of claims 1-8.

21. A computer storage medium, comprising, The computer storage medium stores computer program instructions, and the computer program instructions are executed by the processor to realize the fan blade stall detection method according to any one of claims 1-8.

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