Wind turbine generator blade icing monitoring method, device and system

Abstract

The invention provides a wind turbine generator blade icing monitoring method, device and system, and the method comprises the steps: obtaining the external environment temperature of a wind turbine generator, and judging whether the wind turbine generator has an icing condition or not according to the external environment temperature; in response to the condition that the wind turbine generator has the icing condition, obtaining a sound signal of a blade of the wind turbine generator, and executing wavelet transform on the sound signal to obtain a wavelet coefficient; and determining whether the wind turbine generator blade is iced according to the wavelet coefficient. By judging the external environment temperature of the wind turbine generator, whether an icing condition is met or not is determined, and misjudgment caused by local microclimate is avoided. On the basis that the wind turbine generator has the icing condition, sound signals of blades of the wind turbine generator are obtained, and wavelet coefficients are extracted by executing wavelet transformation on pickup signals. An icing judgment result is output through time-frequency domain analysis of the wavelet coefficient, a basis is provided for starting deicing operation in time, and the influence of icing on the performance and the service life of the wind turbine generator is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of clean energy, and particularly relates to a wind turbine blade icing monitoring method, device and system. BACKGROUND

[0002] In the operation process of a wind turbine, blade icing is an important problem faced in cold and high humidity areas, which can cause the aerodynamic performance of the blade to decrease, the load to be unbalanced, the power generation efficiency to decrease, and even cause the blade to break and the wind turbine to stop, etc. Therefore, it is crucial to accurately and timely detect the blade icing.

[0003] It should be noted that the above introduction to the technical background is only for the convenience of clearly and completely describing the technical scheme of the present application and for the convenience of understanding by those skilled in the art. The above technical scheme cannot be considered as known to those skilled in the art only because it is described in the background section of the present application. SUMMARY

[0004] The present application aims to at least partly solve one of the problems in the related art.

[0005] To this end, the first object of the present application is to provide a wind turbine blade icing monitoring method.

[0006] The second object of the present application is to provide a wind turbine blade icing monitoring device.

[0007] The third object of the present application is to provide a wind turbine blade icing monitoring system.

[0008] The third object of the present application is to provide an electronic device.

[0009] The fourth object of the present application is to provide a computer readable storage medium.

[0010] The fifth object of the present application is to provide a computer program product.

[0011] To achieve the above objects, the first aspect of the present application provides a wind turbine blade icing monitoring method, comprising:

[0012] obtaining an external environment temperature of a wind turbine, and determining whether the wind turbine has icing conditions according to the external environment temperature;

[0013] in response to the wind turbine having icing conditions, obtaining a sound signal of a wind turbine blade, performing wavelet transform on the sound signal, and obtaining wavelet coefficients;

[0014] determining whether the wind turbine blade is iced according to the wavelet coefficients.

[0015] To achieve the above object, the second aspect of the present application proposes a wind turbine blade icing monitoring device configured to implement the steps of the wind turbine blade icing monitoring method proposed in the first aspect of the present application.

[0016] To achieve the above object, the third aspect of the present application proposes a wind turbine blade icing monitoring system comprising the wind turbine blade icing monitoring device proposed in the second aspect of the present application.

[0017] To achieve the above object, the fourth aspect of the present application proposes an electronic device comprising: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the wind turbine blade icing monitoring method proposed in the first aspect of the present application.

[0018] To achieve the above object, the fifth aspect of the present application proposes a computer readable storage medium, when the instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the wind turbine blade icing monitoring method proposed in the first aspect of the present application.

[0019] To achieve the above object, the sixth aspect of the present application proposes a computer program product comprising a computer program, the computer program implements the wind turbine blade icing monitoring method proposed in the first aspect of the present application when executed by a processor in a communication device.

[0020] In the embodiments of the present application, by judging the external environment temperature of the wind turbine, it is determined whether the icing condition is met, so as to avoid misjudgment caused by local microclimate (such as wind speed, humidity, etc.). On the basis of the icing condition of the wind turbine, the sound signal of the wind turbine blade is obtained, the wavelet transform is performed on the sound signal, and the wavelet coefficient reflecting the non-steady-state characteristics such as steady-state impact caused by icing, frequency component change, blade mass distribution change, and aerodynamic performance change is extracted. The icing judgment result is output through time-frequency domain analysis of the wavelet coefficient, which provides a basis for timely starting the deicing operation and reduces the influence of icing on the performance and service life of the wind turbine.

[0021] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0022] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, taken in conjunction with the accompanying drawings, in which:

[0023] Figure 1A flowchart of a wind turbine blade icing monitoring method provided by an embodiment of the present application is shown in FIG. 1.

[0024] Figure 2 A flowchart of another wind turbine blade icing monitoring method provided by an embodiment of the present application is shown in FIG. 2.

[0025] Figure 3 A structural diagram of a wind turbine blade icing monitoring system according to an embodiment of the present application is shown in FIG. 3.

[0026] Figure 4 A structural diagram of an electronic device according to an embodiment of the present application is shown in FIG. 4. DETAILED DESCRIPTION

[0027] The exemplary embodiments will be described in detail herein below with reference to the drawings. In the following description, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments are not representative of all embodiments consistent with the present application. Rather, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0028] The terminology used in the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used in the present application and the appended claims, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0029] It will be understood that, although the terms first, second, third, etc. can be used herein to describe various information, these terms are not intended to denote a particular order or hierarchy. These terms are used only to distinguish one from another. For example, a first information can be termed a second information, and, similarly, a second information can be termed a first information, without departing from the scope of the present application. Depending on the context, the word "if' and "when" as used herein can be interpreted to mean "upon determining" or "in response to determining."

[0030] Embodiments of the present application are described in detail below with reference to the attached drawings, wherein examples of the embodiments are shown. The embodiments described below are examples and are intended to explain the present application, and should not be understood as limiting the present application.

[0031] In cold and humid areas, the icing problem of wind turbine blades is extremely prominent during the operation of wind turbines, which brings many serious hazards to wind turbines, affecting their safe and stable operation and power generation efficiency.

[0032] Icing on the blade will significantly change the airfoil shape of the blade. The normal blade airfoil is carefully designed to have specific aerodynamic characteristics, which can efficiently convert wind energy into mechanical energy. However, when the blade surface is iced, its shape no longer meets the design requirements, causing changes in the flow state when air flows through the blade. This change will reduce the lift coefficient of the blade and increase the drag coefficient, thereby greatly reducing the ability of the blade to capture wind energy, directly leading to a decrease in the power generation efficiency of the wind turbine.

[0033] The distribution of ice on the blade is often uneven. There may be a large difference in the thickness and weight of icing at different parts, which will cause the stress of each part of the blade to be unbalanced. During the rotation of the wind turbine, this load imbalance will generate additional alternating stress acting on the blade and its connecting parts. Under the action of this alternating stress for a long time, the structural strength of the blade will be affected, and fatigue damage will be easily caused, shortening the service life of the blade.

[0034] The decline in aerodynamic performance of the blade caused by icing reduces the energy obtained by the wind turbine from the wind. At the same time, in order to overcome the additional resistance caused by icing, the turbine needs to consume more energy to maintain operation, which further reduces the power generation efficiency. When the blade icing accumulates to a certain extent, the ice layer will become unstable due to the increase in weight. Under the influence of wind or turbine vibration, the ice layer may suddenly break and fly out. Since the wind turbine blade is usually at a high position and rotates at a high speed, the flying ice pieces have a lot of kinetic energy and are extremely easy to hit the inspection personnel, equipment or other buildings in the wind farm, causing serious personal injury and property damage. In addition, icing may also cause the blade to break, causing the turbine to shut down and other safety accidents, seriously affecting the normal operation of the wind farm.

[0035] In some use scenarios, strain gauges are installed on the blades, which indirectly determine the icing condition by sensing the strain change on the blade surface caused by icing. When installing the strain gauges, the strain gauges are accurately pasted on the key parts of the blade to obtain representative strain data. However, this installation method is extremely complex, usually requiring pre-burial during blade manufacturing or fine operation in the shutdown state, and the technical requirements for the installation personnel are extremely high, and any carelessness will affect the measurement accuracy.

[0036] In some real-time methods, strain gauges are strongly affected by environmental factors. In cold environments, the material properties of strain gauges can change, causing measurement data to deviate. At the same time, the vibration, electromagnetic interference and other factors generated by wind turbines during operation can also interfere with the measurement results of strain gauges, making them unable to accurately reflect the true icing conditions of the blades. In addition, strain gauges are consumable components and are prone to aging, damage and other problems after long-term use, and need to be replaced regularly, which not only increases maintenance costs, but also may cause detection interruption due to untimely replacement.

[0037] In some use scenarios, thermocouples are installed on the blades, which use the thermoelectric effect to measure the temperature changes on the blade surface and then infer the icing conditions. When the blade is iced, the heat exchange between the iced area and the surrounding environment changes, causing abnormal temperature distribution, and the thermocouple detects this temperature difference to determine whether it is iced. However, the installation of thermocouples also faces many difficulties, and multiple temperature measurement points need to be reasonably arranged on the blade to ensure that the blade surface can be fully covered, which increases the complexity and workload of installation.

[0038] In some embodiments, the fluctuations in external environmental temperature have a great impact on the measurement results of thermocouples. In cold climates, the external environmental temperature itself is low and changes frequently, and it is difficult for thermocouples to accurately distinguish between temperature changes caused by icing and natural fluctuations in environmental temperature. Moreover, the measurement accuracy of thermocouples is greatly affected by their own accuracy and installation location, and if the installation location is not properly selected, the temperature changes caused by icing may not be accurately captured, resulting in misjudgment. In addition, thermocouples also need to be calibrated and maintained regularly to ensure their measurement accuracy, which further increases the use cost.

[0039] In summary, whether it is a strain gauge or a thermocouple, they can only measure a local area of the blade and cannot cover the entire blade surface at the same time. The wind turbine blade area is large, and the icing conditions at different parts may differ, making it difficult to fully and accurately understand the overall icing conditions of the blade based on local measurement data. Moreover, due to installation and maintenance restrictions, these sensors are difficult to implement real-time and continuous monitoring, and cannot timely reflect the dynamic changes of blade icing, and cannot provide timely and effective information for the operation control of wind turbines.

[0040] The wind turbine blade icing monitoring method, device and system of the embodiments of the present application are described below with reference to the accompanying drawings.

[0041] Figure 1 A flowchart of a wind turbine blade icing monitoring method provided by an embodiment of the present application.

[0042] As Figure 1 shown, the wind turbine blade icing monitoring method includes but is not limited to the following steps:

[0043] S101, obtaining an external environment temperature of the wind turbine, and determining whether the wind turbine has icing conditions according to the external environment temperature.

[0044] In an available embodiment, during the operation of the wind turbine, the external environment temperature of the wind turbine is accurately obtained, and whether the wind turbine has icing conditions is determined according to the external environment temperature, which is crucial for ensuring the safe and efficient operation of the wind turbine.

[0045] In an available embodiment, after obtaining the external environment temperature data, the icing condition is determined in combination with the principles of meteorology and the actual operation environment characteristics of the wind turbine. When the external environment temperature is continuously lower than 0℃, the water vapor in the air can condense into ice, and at this time, the wind turbine has the basic temperature condition for icing.

[0046] In an available embodiment, the determination according to the single factor of temperature may still not be enough, and other related meteorological factors such as air humidity, wind speed, and precipitation conditions also need to be considered.

[0047] In some embodiments, when the air humidity is high, the water vapor content in the air is rich, and under the condition of low temperature, it is easier to condense into ice. Generally, when the relative humidity exceeds 70%, the risk of icing will significantly increase.

[0048] In some embodiments, the wind speed also has an impact on icing. Lower wind speed is conducive to the accumulation of ice layer on the blade surface, while higher wind speed can make the formed ice layer fall off.

[0049] In some embodiments, the precipitation condition also becomes a factor for forming icing. For example, when freezing rain, sleet and other weather conditions occur, the icing formation process will be accelerated.

[0050] In some embodiments, the external environment temperature, air humidity, wind speed, precipitation condition and other meteorological factors are comprehensively analyzed by pre-set rules. For example, when the external environment temperature is lower than 0℃, the relative humidity exceeds 70%, the wind speed is lower than 5m / s, and freezing rain weather occurs, it can be determined that the wind turbine has icing conditions, and at this time, a warning should be issued to the technical personnel so as to take corresponding anti-icing or de-icing measures.

[0051] S102, in response to the wind turbine having icing conditions, obtaining a sound signal of the blade of the wind turbine, performing wavelet transform on the sound signal, and obtaining wavelet coefficients.

[0052] In an available embodiment, based on the previous comprehensive meteorological factor determination, after confirming that the wind turbine has icing conditions, the sound signal of the blade of the wind turbine is obtained for further accurate monitoring of the icing condition and evaluation of the influence of the icing condition on the operation of the wind turbine.

[0053] In some embodiments, a sensor network deployed on the wind turbine blade can be used to monitor the operating conditions of the wind turbine blade in real time, and shield the wind turbine itself vibration, ambient noise and other interference factors, accurately capture the subtle sound changes generated by the blade in the icing state, and obtain the sound signal.

[0054] For example, the sensor network can use an acoustic sensor with high sensitivity and wide frequency band.

[0055] In a feasible implementation, after obtaining the sound signal, wavelet transform processing is performed on the sound signal. Compared with the traditional Fourier transform, the wavelet transform has the advantage of resolution analysis, and can decompose the sound signal at different scales, so as to obtain the local feature information of the sound signal in time domain and frequency domain at the same time.

[0056] In some embodiments, a suitable wavelet basis function is selected. For example, Daubechies wavelet has the characteristics of compact support and orthogonality, and is suitable for analyzing sound signals with mutation characteristics; Meyer wavelet has the characteristics of smoothness and infinite differentiability, and has good analysis effect on smooth sound signals. According to the characteristics of the sound signal of the wind turbine blade, a suitable wavelet basis function is selected.

[0057] In some embodiments, according to the wavelet basis function, the sound signal is decomposed at multiple scales to obtain a series of wavelet coefficients at different scales. These wavelet coefficients reflect the energy distribution of the sound signal in different frequency bands and time periods. By analyzing the characteristics of the wavelet coefficients, such as the amplitude, energy distribution and change trend of the coefficients, the feature information related to the icing of the blade can be extracted.

[0058] For example, when the blade is iced, the vibration mode of the blade will change, resulting in changes in the frequency components and energy distribution of the sound signal. The characteristics of the wavelet coefficients at a specific scale are reflected in the increase in the amplitude or energy concentration of the coefficients. Through in-depth analysis of the wavelet coefficients, strong evidence can be provided for subsequent icing degree evaluation, fault diagnosis and development of corresponding maintenance strategies.

[0059] S103, determining whether the wind turbine blade is iced according to the wavelet coefficients.

[0060] In a feasible implementation, icing will change the mass distribution of the blade and cause the blade vibration frequency to shift. By mapping the sound signal to a multi-scale frequency band through wavelet transform, and calculating the energy proportion of each sub-band based on the obtained wavelet coefficients, the icing of the wind turbine blade can be determined.

[0061] In some embodiments, the wavelet transform decomposes the sound signal in the range of 0-100Hz into multiple sub-bands, and focuses on analyzing 0-10Hz (icing sensitive frequency band) and 50-100Hz (normal vibration dominant frequency band). The energy of 0-10Hz and 50-100Hz is calculated by wavelet coefficients.

[0062] For example, the low-frequency band (0-10Hz) energy of the blade tip deflection signal of the blade in the icing state will significantly increase, and the high-frequency band (50-100Hz) energy will attenuate. This energy distribution change can be used as an icing criterion.

[0063] In summary, the wind turbine blade icing monitoring method provided in the embodiments of the present application determines whether icing conditions exist by judging the external environment temperature of the wind turbine, thereby avoiding misjudgment caused by local microclimate (such as wind speed, humidity, etc.). On the basis of the icing conditions of the wind turbine, the sound signal of the wind turbine blade is obtained, the wavelet transform is performed on the sound signal, and the wavelet coefficients reflecting the non-steady-state characteristics such as steady-state impact, frequency component change, blade mass distribution change, and aerodynamic performance change caused by icing are extracted. The icing judgment result is output by time-frequency domain analysis of the wavelet coefficients, which provides a basis for timely starting the deicing operation and reduces the impact of icing on the performance and service life of the wind turbine.

[0064] Figure 2 Another flowchart of the wind turbine blade icing monitoring method provided in the embodiments of the present application is shown.

[0065] As shown in Figure 2 , the wind turbine blade icing monitoring method includes but is not limited to the following steps:

[0066] S201, in response to the external environment temperature recorded during the operation of the wind turbine, the external environment temperature during the operation of the wind turbine is obtained according to a preset sampling period.

[0067] In a feasible implementation, in the actual operation of the wind turbine, the external environment temperature is directly related to various performance indicators of the wind turbine, such as power generation efficiency, equipment reliability, and service life. In the key positions of the wind turbine, such as the outside of the nacelle or the vicinity of the hub, a high-precision temperature sensor is installed in the area that can accurately reflect the external environment temperature of the wind turbine. For example, the temperature sensor includes a thermal resistance sensor, a thermocouple sensor, an infrared thermometer, a fiber grating temperature sensor, etc., and the appropriate temperature sensor setting form should be selected according to the environment of the wind turbine.

[0068] In a feasible implementation, according to the operating characteristics of the wind turbine, the sensitivity of different models and different sizes of wind turbines to temperature changes is different, and the appropriate sampling period is selected.

[0069] In some embodiments, large wind turbines are more sensitive to temperature changes due to their complex structure and numerous components, and thus require a shorter sampling period to capture the effects of temperature changes on the turbine in a timely manner.

[0070] In some embodiments, if the ambient temperature of the wind turbine changes dramatically, such as a large diurnal temperature difference or is significantly affected by seasonal climate changes, the sampling period should be set relatively short to ensure that rapid fluctuations in temperature can be accurately recorded.

[0071] In some embodiments, if the ambient temperature changes relatively smoothly, the sampling period can be appropriately extended.

[0072] In some embodiments, a shorter sampling period will generally generate a large amount of data, and if the temperature sensor data processing system cannot process it in a timely manner or has limited storage capacity, the sampling period can be appropriately extended.

[0073] In a feasible implementation, a plurality of external initial temperatures during the operation of the wind turbine are obtained according to a preset sampling period, and the plurality of external initial temperatures are averaged to obtain an external ambient temperature.

[0074] In some embodiments, the 3σ criterion can be used to filter the plurality of external initial temperatures. When a data point deviates from the mean by more than 3 times the standard deviation, it is marked as an outlier and removed.

[0075] In some embodiments, the plurality of external initial temperatures are time-stamped synchronized by a GPS time module to avoid calculation errors caused by time misalignment.

[0076] In some embodiments, the plurality of external initial temperatures are weighted and averaged to obtain the external ambient temperature.

[0077] S202, determining whether the wind turbine has icing conditions according to the external ambient temperature.

[0078] In a feasible implementation, in response to the external ambient temperature being greater than a preset temperature threshold, it is determined that the wind turbine has icing conditions; and in response to the external ambient temperature being less than or equal to the preset temperature threshold, it is determined that the wind turbine does not have icing conditions.

[0079] Icing is the process of supercooled water droplets (external ambient temperature ≤ 0℃) impacting the surface of an object and freezing. When the external ambient temperature is > 0℃, the water droplets exist in a liquid state and cannot form ice; when the external ambient temperature is ≤ 0℃, the water droplets can freeze.

[0080] In some embodiments, in combination with the influence of relative humidity on icing, if the icing is supercooled water droplets (ambient temperature < 0°C), but the relative humidity of the air is low (e.g., relative humidity < 70%), the water droplets can not freeze. Therefore, the relative humidity is used to supplement the icing conditions. For example, if the ambient temperature < 0°C and the relative humidity > 70%, it is determined that there is possible icing.

[0081] In some embodiments, in combination with the influence of wind speed on icing, if the wind speed exceeds 10 meters / second, the blade will be blown cooler, and the actual ambient temperature can be lower than the temperature sensor shows. At this time, the temperature threshold needs to be adjusted down a little bit (e.g., for every 1 meter / second of wind speed, the temperature threshold is reduced by 0.05°C).

[0082] In some embodiments, in combination with the influence of wind turbine altitude on icing, if the wind turbine is built on a mountain (e.g., at an altitude of 2000 meters), the air becomes thin, and the temperature sensor can be "inaccurate", so the ambient temperature collected by the temperature sensor needs to be corrected (e.g., for every 1000 meters of altitude, the ambient temperature is corrected by +0.0065°C).

[0083] S203, in response to the wind turbine having icing conditions, using the sensor network deployed on the wind turbine blade to monitor the running status of the wind turbine blade in real time to obtain a sound signal.

[0084] In a feasible implementation, the sensor network deployed on the wind turbine blade is used to monitor the running status of the wind turbine blade in real time to obtain an initial sound. The initial sound is subjected to data cleaning and analog-to-digital conversion to obtain a sound signal.

[0085] In some embodiments, a plurality of sensor nodes are carefully deployed at key positions of the wind turbine blade, and the plurality of sensor nodes form a sensor network capable of simultaneously collecting multi-dimensional physical information such as vibration, stress, and sound generated by the blade during operation.

[0086] In some embodiments, during continuous operation of the sensor network, the collected initial sound is often disturbed by various factors. From the external environment, the wind turbine is usually installed outdoors, and there can be strong wind, bird calls, noise generated by the operation of other mechanical equipment, etc. From the perspective of the sensor itself, the sensor can generate thermal noise of electronic components during long-term operation, and line noise during signal transmission. These interference factors will cause the initial sound to contain a large amount of noise and abnormal values, seriously affecting the accuracy and reliability of subsequent analysis of the running status of the blade.

[0087] In some embodiments, the initial sound is subjected to data cleaning. A band-pass filtering algorithm is used to set appropriate upper and lower limit frequencies according to the frequency characteristics of the initial sound, and noise signals exceeding the frequency range are filtered out, leaving the effective frequency components related to the operation of the blade; the median filtering method is used to suppress the pulse noise in the initial sound, and the median value of the data in a certain window is taken to replace the data point at the center of the window, so as to eliminate the influence of abnormal values; data smoothing is performed, and the initial sound is smoothed by using the moving average algorithm to reduce random fluctuations.

[0088] In S204, the sound signal is subjected to wavelet decomposition of a preset number of layers using a Haar wavelet basis function, to obtain wavelet coefficients reflecting the time-frequency characteristics of the sound signal.

[0089] In a feasible implementation, the sound signal s(t) is subjected to discrete wavelet transform (i.e., wavelet decomposition) of a preset number of layers (e.g., J layers, J>1) using a Haar wavelet basis function, to obtain approximation coefficients and detail coefficients reflecting the time-frequency characteristics of the sound signal s(t), which are collectively referred to as wavelet coefficients.

[0090] For example, the sound signal s(t) is subjected to J-layer wavelet decomposition, to obtain the approximation coefficients a J,k and the detail coefficients d j,k of the jth layer, and the following expression is obtained:

[0091]

[0092] wherein j represents the decomposition layer number, k represents the discrete time point, ψ J,k (t) is a wavelet function, and φ(k) is a scaling function.

[0093] In S205, it is determined whether the wind turbine blade is iced according to the wavelet coefficients.

[0094] In a feasible implementation, the energy spectrum of the sound signal is determined according to the detail coefficients in the wavelet coefficients. In some embodiments, the energy spectrum density is determined according to the detail coefficients in the wavelet coefficients, and the energy spectrum of the sound signal is determined according to the preset number of layers of wavelet decomposition and the energy spectrum density.

[0095] In one possible implementation, it is determined whether the wind turbine blade is iced according to the energy spectrum and a preset energy threshold. In some embodiments, the preset energy threshold includes a first energy interval, a second energy interval, a third energy interval and a fourth energy interval. In response to the energy spectrum being located in the first energy interval, it is determined that the wind turbine blade is not iced. In response to the energy spectrum being located in the second energy interval, it is determined that the wind turbine blade is in a light icing state. In response to the energy spectrum being located in the third energy interval, it is determined that the wind turbine blade is in a medium icing state. In response to the energy spectrum being located in the fourth energy interval, it is determined that the wind turbine blade is in a heavy icing state.

[0096] For example, the detail coefficient d j,k The energy spectrum density E j wherein:

[0097]

[0098] According to the energy spectrum density E j The energy spectrum E sum wherein:

[0099]

[0100] The first energy interval is [E set0 , E set1 ], the second energy interval is [E set1 , E set2 ], the third energy interval is [E set2 , E set3 ], and the fourth energy interval is [E set3 , E set4 ]. When the energy spectrum E sum is located in [E set0 , E set1 ], it is determined that the wind turbine blade is not iced; when the energy spectrum E sum is located in [E set1 , E set2 ], it is determined that the wind turbine blade is in a light icing state; when the energy spectrum E sum is located in [E set2 , E set3 ], it is determined that the wind turbine blade is in a medium icing state; and when the energy spectrum E sum is located in [E set3 , E set4 ], it is determined that the wind turbine blade is in a heavy icing state.

[0101] In summary, the wind turbine blade icing monitoring method provided by the embodiments of the present application continuously monitors the external environment temperature based on a preset sampling period, and once icing conditions are determined, immediately starts monitoring the running status of the blade. The sound signal is obtained by the blade sensor network and wavelet decomposition analysis is performed by means of the Haar wavelet base function. This multi-level and comprehensive monitoring method can more accurately determine whether the wind turbine blade is iced. Compared with single temperature or simple appearance inspection, the icing characteristics can be more reliably captured, avoiding misjudgment or omission, so that timely measures can be taken to ensure the safe and stable operation of the wind turbine.

[0102] Corresponding to the wind turbine blade icing monitoring method, the present application also provides a wind turbine blade icing monitoring device. Since the wind turbine blade icing monitoring device embodiments of the present application correspond to the wind turbine blade icing monitoring method embodiments described above, for details not disclosed in the wind turbine blade icing monitoring device embodiments, reference can be made to the wind turbine blade icing monitoring method embodiments, which will not be described herein.

[0103] In a feasible implementation, the wind turbine blade icing monitoring device is configured to perform the wind turbine blade icing monitoring method provided by the embodiments of the present application. The wind turbine blade icing monitoring device has specific functional modules, algorithms or logics, and can regulate the running state of the wind turbine according to the series of steps, rules and strategies of the wind turbine blade icing monitoring method described in the embodiments of the present application. Further, by writing specific program codes, the control method of the outdoor fan is converted into instructions that can be understood and executed by the wind turbine blade icing monitoring device. These codes can include conditional judgment, loop control, data processing and other logics to realize dynamic adjustment of the running state of the wind turbine.

[0104] In particular, according to the embodiments of the present application, the wind turbine blade icing monitoring device described above can be implemented as a wind turbine blade icing monitoring system. Figure 3 A structural schematic diagram of a wind turbine blade icing monitoring system according to an embodiment of the present application.

[0105] As shown in Figure 3 The wind turbine blade icing monitoring system includes a wind turbine and a wind turbine blade icing monitoring device. The wind turbine includes a wind turbine base and three blades. The wind turbine blade icing monitoring device is arranged on each blade, and the icing state of the blade is monitored by the wind turbine blade icing monitoring device.

[0106] Figure 4 A structural schematic diagram of an electronic device according to an embodiment of the present application. Figure 4The electronic device shown is merely an example and should not impose any limitation on the functions and usage scope of the embodiments of the present application.

[0107] As shown in Figure 4 The electronic device 400 includes a processor 401 which can perform various appropriate actions and processes according to programs stored in a read only memory (ROM) 402 or loaded from a memory 406 into a random access memory (RAM) 403. Various programs and data required for the operation of the electronic device 400 are also stored in the RAM 403. The processor 401, the ROM 402, and the RAM 403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0108] The following components are connected to the I / O interface 405: the memory 406 including a hard disk or the like; and a communication section 407 including a network interface card such as a LAN (Local Area Network) card, a modem, or the like, which performs communication processing via a network such as the Internet; and a drive 408 is also connected to the I / O interface 405 as necessary.

[0109] In particular, according to the embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, the embodiments of the present application include a computer program carrying on a computer readable medium, which contains program codes for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network by the communication section 407. When the computer program is executed by the processor 401, the above-described functions defined in the methods of the present application are performed.

[0110] In the exemplary embodiments, a storage medium including instructions, for example, a memory including instructions, is also provided, which can be executed by the processor 401 of the electronic device 400 to complete the above-described methods. Alternatively, the storage medium can be a non-transitory computer readable storage medium, for example, the non-transitory computer readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, and the like.

[0111] In this application, computer readable storage medium can be any tangible medium that can contain, or store computer readable program codes. In this application, computer readable program codes can include any type of computer readable instructions, i.e., programs, on a tangible media. A computer readable medium can include computer readable storage medium and computer readable signaling medium. In this application, computer readable storage medium can include any available media that can be accessed by a general purpose or special purpose computer. By way of example, and not limitation, such computer readable medium can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired computer readable program codes in the form of computer readable instructions, data structures or program modules. Computer readable medium can further include propagated data signals with computer readable program codes embodied therein, e.g., in baseband or as part of a carrier wave. Computer readable signaling medium can include any computer readable medium, except for a propagated data signal.

[0112] Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the application being indicated by the following claims.

[0113] It is to be understood that the application is not limited to the specific structures that have been described and that many modifications and variations of detail can be made in the application without departing from the scope of the application. The scope of the application is limited only by the claims that follow.

Claims

1. A wind turbine blade icing monitoring method, characterized in that, The method comprises the following steps: acquiring an external environment temperature of a wind turbine, and determining whether the wind turbine has icing conditions according to the external environment temperature; in response to the wind turbine having icing conditions, acquiring a sound signal of a wind turbine blade, performing wavelet transform on the sound signal to obtain wavelet coefficients; determining whether the wind turbine blade is iced according to the wavelet coefficients.

2. The method of claim 1, wherein, The step of acquiring the external environment temperature of the wind turbine comprises the following steps: in response to an external environment temperature recorded during operation of the wind turbine, acquiring a plurality of external initial temperatures of the wind turbine during operation according to a preset sampling period; performing mean value operation on the plurality of external initial temperatures to obtain the external environment temperature.

3. The method of claim 1, wherein, The step of determining whether the wind turbine has icing conditions according to the external environment temperature comprises the following steps: in response to the external environment temperature being greater than a preset temperature threshold, determining that the wind turbine has icing conditions; in response to the external environment temperature being less than or equal to the preset temperature threshold, determining that the wind turbine does not have icing conditions.

4. The method of claim 1, wherein, The step of acquiring the sound signal of the wind turbine blade comprises the following steps: using a sensor network deployed on the wind turbine blade to monitor the operating condition of the wind turbine blade in real time to obtain an initial sound; performing data cleaning on the initial sound to obtain the sound signal.

5. The method of claim 1, wherein, The step of performing wavelet transform on the sound signal to obtain wavelet coefficients comprises the following steps: using a Haar wavelet basis function to perform wavelet decomposition on the sound signal to a preset number of layers to obtain wavelet coefficients reflecting time-frequency characteristics of the sound signal; wherein the wavelet coefficients comprise approximation coefficients and detail coefficients.

6. The method according to any one of claims 1-5, characterized in that, The step of determining whether the wind turbine blade is iced according to the wavelet coefficients comprises the following steps: determining an energy spectrum of the sound signal according to the detail coefficients in the wavelet coefficients; determining whether the wind turbine blade is iced according to the energy spectrum and a preset energy threshold.

7. The method of claim 6, wherein, The step of determining the energy spectrum of the sound signal according to the detail coefficients in the wavelet coefficients comprises the following steps: determining an energy spectrum density according to the detail coefficients in the wavelet coefficients; determining the energy spectrum of the sound signal according to the preset number of layers of wavelet decomposition and the energy spectrum density.

8. The method of claim 6, wherein, The preset energy threshold comprises a first energy interval, a second energy interval, a third energy interval and a fourth energy interval, and the step of determining whether the wind turbine blade is iced according to the energy spectrum and the preset energy threshold comprises the following steps: in response to the energy spectrum being located in the first energy interval, determining that the wind turbine blade is not iced; in response to the energy spectrum being located in the second energy interval, determining that the wind turbine blade is in a light icing state; in response to the energy spectrum being located in the third energy interval, determining that the wind turbine blade is in a moderate icing state; in response to the energy spectrum being located in the fourth energy interval, determining that the wind turbine blade is in a severe icing state.

9. An ice accretion monitoring device for a wind turbine blade, characterized in that, A device configured to implement the steps of the method of any one of claims 1 to 8.

10. A wind turbine blade ice accretion monitoring system characterized by, A wind turbine blade icing monitoring device as claimed in claim 9.

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