State monitoring method and device for new energy wind driven generator

Abstract

The invention relates to the technical field of wind power generation, and discloses a state monitoring method and device for a new energy wind driven generator. Direct physical correlation between sound velocity attenuation and icing thickness is established by analyzing propagation time delay change of sound waves in a blade material; by calculating the time delay gradient ratios of different blade sections (blade tips, blade middle parts and blade roots), the axial position of icing is directly deduced by using the spatial characteristics of sound wave propagation path differences. Compared with a traditional monitoring means based on a temperature threshold value or a vibration amplitude value, sound wave time delay is extremely sensitive to microscopic changes of a material boundary layer, and tiny structure changes formed at the initial stage of icing can be captured.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of wind power generation technology, in particular to a state monitoring method and device for a new energy wind turbine. BACKGROUND

[0002] The existing blade icing monitoring of wind turbines mainly relies on temperature threshold method or vibration spectrum analysis method. The temperature method is based on the latent heat effect released by the phase change of icing, and needs to wait for the ice layer to accumulate to a certain thickness to make the sensor reach the preset threshold, which has a response lag. The vibration method judges icing by capturing the natural frequency offset or amplitude anomaly of the blade, but the structural stiffness change caused by weak icing is easily overwhelmed by the broadband mechanical vibration noise generated by the rotation of the wind wheel, especially in low wind speed conditions, the signal-to-noise ratio deteriorates sharply. Both methods lack effective sensing ability for early icing, resulting in delayed start of the deicing system and inability to prevent the risk of aerodynamic performance degradation and structural damage caused by thickening of the ice layer. SUMMARY

[0003] The present application provides a state monitoring method and device for a new energy wind turbine to solve the problem of lack of effective sensing ability for early icing of the existing temperature threshold method and vibration spectrum analysis method.

[0004] In a first aspect, the present application provides a state monitoring method for a new energy wind turbine, comprising: Taking the rotational speed signal at the hub as a synchronous reference, triggering the piezoelectric exciter at the leading edge of the blade to output an excitation signal, and simultaneously collecting the sound wave data captured by the acoustic emission sensor under each corresponding propagation path of the blade tip, the middle of the blade, the root of the blade to the root of the blade; For each propagation path of the blade tip, the middle of the blade, the root of the blade to the root of the blade, the sound wave propagation time delay is extracted, and based on the continuous rotation period data, the sound wave propagation time delay change of each path in the adjacent two rotation periods is calculated; A sound speed-icing thickness correlation model is established, and the icing position determination coefficient is calculated according to the time delay change of each path of the blade tip, the middle of the blade, the root of the blade to the root of the blade; According to the time delay change of each propagation path, the time delay change rate in the unit rotation period, and the icing position determination coefficient, the icing state and region are judged.

[0005] The application provides a state monitoring method for a new energy wind turbine.

[0006] In an optional embodiment, the icing state and region are determined according to the time delay variation of each propagation path, the time delay variation rate in a unit rotation period, and the icing position determination coefficient, and the method comprises the following steps. determining whether the time delay variation of each propagation path exceeds a first preset value and whether the time delay variation rate in a unit rotation period is greater than a second preset value; if the time delay variation of each propagation path exceeds the first preset value and the time delay variation rate in a unit rotation period is greater than the second preset value, determining the icing state and region according to the relationship between the icing position determination coefficient and a preset threshold.

[0007] In an optional embodiment, the icing state and region are determined according to the relationship between the icing position determination coefficient and a preset threshold, and the method comprises the following steps. when the icing position determination coefficient is not less than a first threshold but less than a second threshold, determining that the middle of the blade is iced, wherein the second threshold is greater than the first threshold; when the icing position determination coefficient is not less than the second threshold but less than a third threshold, determining that the tip of the blade is iced, wherein the third threshold is greater than the second threshold; when the icing position determination coefficient is less than the first threshold or not less than the third threshold, determining that the root of the blade is iced.

[0008] In an optional embodiment, the icing state and region are determined according to the time delay variation of each propagation path, the time delay variation rate in a unit rotation period, and the icing position determination coefficient, and the method further comprises the following steps. if the time delay variation of each propagation path does not simultaneously exceed the first preset value or the time delay variation rate in a unit rotation period is not greater than the second preset value, determining that the state of the blade is normal.

[0009] In an optional embodiment, the method further comprises the following steps. preprocessing the sound wave data captured by the acoustic emission sensor.

[0010] In an optional embodiment, the preprocessing of the sound wave data captured by the acoustic emission sensor comprises the following steps. Adaptive band-pass filtering is performed on the sound wave data captured by the acoustic emission sensor for each corresponding propagation path of the blade tip, the middle of the blade, the blade root to the blade root. With the rotation speed signal at the hub as a reference, the sound wave data of a continuous preset number of rotations is aligned according to the rotation angle and then superimposed and averaged by using a rotation speed synchronous average algorithm.

[0011] In an optional implementation, the method further includes: Based on the icing determination result, a frozen position distribution thermodynamic map of the blade surface is generated on a monitoring interface. When icing is continuously monitored in multiple complete rotation periods, a hierarchical early warning mechanism is triggered.

[0012] In a second aspect, the application provides a state monitoring device for a new energy wind turbine, the device comprising: A sound wave acquisition module is configured to use the rotation speed signal at the hub as a synchronous reference, trigger the blade leading edge piezoelectric exciter to output an excitation signal, and simultaneously acquire the sound wave data captured by the acoustic emission sensor under each corresponding propagation path of the blade tip, the middle of the blade, the blade root to the blade root. A first calculation module is configured to extract the sound wave propagation time delay for each propagation path of the blade tip, the middle of the blade, the blade root to the blade root, and calculate the sound wave propagation time delay variation of each path in adjacent two rotation periods based on continuous rotation period data. A second calculation module is configured to establish a sound speed-icing thickness correlation model, and calculate an icing position determination coefficient according to the time delay variation of each path of the blade tip, the middle of the blade, the blade root to the blade root. A state judgment module is configured to judge the icing state and region according to the time delay variation of each propagation path, the time delay variation rate in a unit rotation period, and the icing position determination coefficient.

[0013] The application provides a state monitoring device for a new energy wind turbine, which analyzes the propagation time delay variation of sound waves in the blade material, establishes a direct physical correlation between the sound speed attenuation and the icing thickness, calculates the time delay gradient ratio of different blade sections (blade tip, middle of blade, blade root), uses the spatial characteristics of the sound wave propagation path difference, and directly deduces the axial position of the icing occurrence. Compared with the traditional monitoring methods based on temperature threshold or vibration amplitude, the sound wave time delay is extremely sensitive to the micro changes of the material boundary layer and can capture the micro structural changes formed in the initial stage of icing.

[0014] In a third aspect, the application provides an electronic device, including a memory and a processor, the memory and the processor are in communication connection with each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the state monitoring method for the new energy wind turbine of the first aspect or any of the corresponding embodiments thereof.

[0015] In a fourth aspect, the present application provides a computer readable storage medium, having stored thereon computer instructions for causing a computer to execute the state monitoring method for a new energy wind turbine of the first aspect or any of the corresponding embodiments thereof. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the specific embodiments or prior art technical solutions of the present application, the drawings required to be used in the specific embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0017] Figure 1 is a flowchart of the state monitoring method for a new energy wind turbine according to an embodiment of the present application; Figure 2 is a structural block diagram of the state monitoring device for a new energy wind turbine according to an embodiment of the present application; Figure 3 is a hardware structure schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0019] It can be understood that before using the technical solutions disclosed in the embodiments of the present application, the type, use range, use scenario, etc. of the personal information involved in the present application should be informed to the user and the authorization of the user should be obtained through appropriate means according to relevant laws and regulations.

[0020] The terms "first", "second" are only for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "multiple" is two or more than two, unless otherwise specifically limited.

[0021] According to an embodiment of the present invention, a method for monitoring the condition of a new energy wind turbine is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0022] This embodiment provides a condition monitoring method for new energy wind turbine generators. Figure 1 This is a flowchart of a condition monitoring method for new energy wind turbines according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: Step S1: Using the rotational speed signal at the hub as a synchronization reference, the piezoelectric exciter at the leading edge of the blade is triggered to output an excitation signal. At the same time, acoustic wave data captured by the acoustic emission sensor is collected at the corresponding propagation paths from the blade tip, blade middle, blade root to the blade root.

[0023] In this embodiment, piezoelectric exciters (resonant frequency 200kHz) are embedded at the blade tip, middle, and root positions on the leading edge of the blade to actively emit detection sound waves; three broadband acoustic emission sensors (frequency response range 50-300kHz, sampling rate ≥1MHz) are installed at the blade root (0.5m from the hub) to receive sound wave signals from each propagation path from the blade tip, middle, and root; and a high-precision speed encoder (resolution 0.01°) is installed at the hub to obtain high-precision position signals of the blade rotation.

[0024] Signal acquisition uses the position signal from the speed encoder as the core synchronization reference. The synchronization controller receives this position signal in real time. When the blade rotates one revolution and reaches a specific reference angle, the speed encoder outputs a trigger pulse. After receiving the pulse, the synchronization controller immediately instructs the piezoelectric exciters at the blade tip, middle, and root to synchronously generate short 200kHz acoustic pulses. The acoustic waves propagate inward along the blade structure. At the same time, three broadband acoustic emission sensors at the blade root synchronously start high-speed acquisition, recording the acoustic wave signals after propagation through the blade material along each path, thus completely capturing the acoustic wave data of each corresponding propagation path from the blade tip, middle, and root to the root.

[0025] This step involves precisely deploying the aforementioned core components at key locations on the blades and hub, achieving millisecond-level time synchronization based on the rotation angle, and providing high-precision spatiotemporally aligned raw signals for subsequent signal analysis.

[0026] Step S2: Preprocess the acoustic wave data captured by the acoustic emission sensor.

[0027] In this embodiment, step S2 includes: Step S21, for each corresponding propagation path of the blade tip, the middle of the blade, the blade root to the blade root, the sound emission sensor captures the sound wave data is adaptively band-pass filtered.

[0028] Specifically, for the collected original sound signal, an adaptive band-pass filter with a passband of 180-220 kHz is used to effectively suppress wind field environmental noise and mechanical vibration interference generated by the operation of the fan, and to preliminarily screen out the sound wave frequency band related to icing detection, and not to rely on cumulative effect judgment, and to improve the early icing recognition ability.

[0029] Step S22, using the rotational speed signal at the hub as a reference, a rotational speed synchronous averaging algorithm is used to align and superimpose the sound wave data of a continuous preset number of rotations according to the rotation angle.

[0030] Specifically, the rotational speed synchronous averaging algorithm is used to strictly align and superimpose the sound signals of a continuous N rotations (N≥50) according to the blade rotation angle, further suppresses random noise, and ensures the effective extraction of micro time delay changes, thereby securing a key time window for subsequent deicing decision-making. The algorithm expression is as follows:

[0031] Among them, is the sound wave signal after averaging processing, is a time variable, is the number of signal averaging, is the rotation period sequence index, is the original sound wave signal collected in the kth rotation period, is the angle offset of the kth rotation period, is the instantaneous rotational speed of the fan.

[0032] Step S2 removes wind noise and mechanical vibration interference through adaptive filtering, and enhances the signal-to-noise ratio of the sound wave feature by using the rotational speed synchronous averaging algorithm, thereby ensuring the purity of the signal for subsequent analysis. The double noise reduction mechanism of the rotational speed synchronous averaging algorithm and the adaptive frequency band filter is used, the former strictly aligns and superimposes the sound signals according to the rotation angle, and effectively separates the periodic components related to the blade state; the latter selects a sound wave frequency band far from the main frequency of mechanical vibration, thereby avoiding the wide frequency vibration interference caused by the rotation of the wind wheel; this design optimizes from the source and transmission process of the signal, and overcomes the bottleneck of insufficient signal-to-noise ratio of traditional single sensor in strong noise environment; the adaptability of the system to dynamic working conditions such as sudden wind speed change and turbulence is significantly improved, and the false alarm rate is reduced.

[0033] Step S3, for each propagation path of the blade tip, the middle of the blade, the blade root to the blade root, the sound wave propagation time delay is extracted, and based on the continuous rotation period data, the sound wave propagation time delay change of each path in adjacent two rotation periods is calculated.

[0034] In the embodiment, the time delay (denoted as τ) of the excitation signal output by the piezoelectric exciter at the leading edge tip, middle and root positions of the blade is extracted and propagated to the corresponding wideband acoustic emission sensor at the blade root; based on the continuously collected rotating period data, the time delay variation of the same propagation path in adjacent two rotating periods is calculated, and the calculation formula is as follows:

[0035] wherein, is the time delay variation of the acoustic wave, is the time delay of the acoustic wave in the nth rotation, is the time delay of the acoustic wave in the (n-1)th rotation.

[0036] Step S4, the correlation modeling of sound velocity-icing thickness is established, and the icing position determination coefficient is calculated according to the time delay variation of each path from the tip, middle and root of the blade to the blade root.

[0037] In the embodiment, first, the correlation model of the time delay variation of the acoustic wave and the icing thickness of the blade is established according to the propagation characteristics of the acoustic wave in the blade composite material, and the specific expression is as follows:

[0038] wherein, is the length of the acoustic wave propagation path, is the reference value of the acoustic velocity in the blade composite material, is the variation of the acoustic velocity, is the acoustic velocity attenuation coefficient of the ice layer, is the icing thickness.

[0039] On this basis, the icing position determination coefficient is calculated according to the time delay variation of each path from the tip, middle and root of the blade to the blade root, and then the icing area is determined according to the icing position determination coefficient. The calculation formula of the icing position determination coefficient is as follows:

[0040] wherein, is the icing position determination result, is the operator of the maximum value parameter, is the time delay variation of the tip sensor, is the time delay variation of the middle sensor, is the time delay variation of the root sensor, is the anti-zero minimum constant.

[0041] The step is based on the change in sound wave propagation time delay to construct an icing thickness quantification model, and the relative ratio of the change in multi-path time delay is combined to complete the spatial positioning of the icing area, and finally the double-dimensional detection capability of icing thickness and icing position is formed, which provides the core judgment basis for subsequent grading warning.

[0042] The present application establishes a direct physical correlation between sound speed attenuation and icing thickness by analyzing the change in sound wave propagation time delay in the blade material. Compared with the traditional monitoring method based on temperature threshold or vibration amplitude, the sound wave time delay is extremely sensitive to the micro changes of the material boundary layer, which can accurately capture the micro structural changes in the early stage of icing, and breaks through the limitation that the traditional method cannot perceive early icing.

[0043] Step S5, judging the icing state and area according to the time delay change of each propagation path, the time delay change rate in a unit rotation period, and the icing position determination coefficient.

[0044] In the embodiment, step S5 includes: Step S51, judging whether the time delay change of each propagation path exceeds the first preset value and whether the time delay change rate in a unit rotation period is greater than the second preset value.

[0045] Step S52, if the time delay change of each propagation path exceeds the first preset value and the time delay change rate in a unit rotation period is greater than the second preset value, judging the icing state and area according to the relationship between the icing position determination coefficient and the preset threshold.

[0046] Step S53, if the time delay change of each propagation path does not exceed the first preset value at the same time, or the time delay change rate in a unit rotation period is not greater than the second preset value, determining that the blade state is normal.

[0047] Specifically, the time delay change of each propagation path output by the receiving step S3, the icing position determination coefficient output by the step S4, and the length of a single rotation period fed back by the fan speed encoder are combined to calculate the time delay change rate (i.e. time delay gradient) in a unit rotation period. First, verify whether the time delay change of all propagation paths exceeds 0.2 microseconds, and verify whether the time delay change rate in a unit rotation period is greater than 0.05 microseconds / revolution. If both conditions are met, further locate the icing area of the blade based on the icing position determination coefficient; if any condition is not met (i.e. not all path time delay changes exceed 0.2 microseconds, or the time delay change rate is not greater than 0.05 microseconds / revolution), it is determined that the blade is in a normal state without icing. The first preset value is 0.2 microseconds, and the second preset value is 0.05 microseconds / revolution.

[0048] In an alternative embodiment, step S52 includes: Step S521, when the icing position determination coefficient is not less than the first threshold value, but less than the second threshold value, it is determined that icing occurs in the middle of the blade, the second threshold value is greater than the first threshold value.

[0049] Step S522, when the icing position determination coefficient is not less than the second threshold value, but less than the third threshold value, it is determined that icing occurs at the tip of the blade, the third threshold value is greater than the second threshold value.

[0050] Step S523, when the icing position determination coefficient is less than the first threshold value, or not less than the third threshold value, it is determined that icing occurs at the root of the blade.

[0051] In this embodiment, the determination rule of the icing area is as follows: if 0.3≤icing position determination coefficient<0.7, it is determined that icing occurs in the middle of the blade; if 0.7≤icing position determination coefficient<1.3, it is determined that icing occurs at the tip of the blade; and other cases (i.e. icing position determination coefficient<0.3 or ≥1.3) are all classified as icing at the root of the blade. Among them, the first threshold value is 0.3, the second threshold value is 0.7, and the third threshold value is 1.3.

[0052] Step S5, by comprehensively integrating the sound wave propagation time delay variation of each propagation path, the time delay gradient (i.e. time delay variation rate) in a unit rotation period, and the icing position determination coefficient, relying on multi-dimensional threshold determination logic, the icing state (with or without icing) and the specific area of the blade are accurately determined, and finally the decision transformation from the physical detection signal to the icing fault classification is completed.

[0053] The present application determines the icing area based on the relative relationship of the time delay variation of multiple excitation-sensing paths, without the need to increase a dense sensor network on the surface of the blade; by calculating the time delay gradient ratio of different blade sections (tip, middle, root), the spatial characteristics of the difference of the sound wave propagation paths are utilized to directly deduce the axial position where icing occurs; this method forms a distributed perception of the overall structural state of the blade, and does not rely on auxiliary means such as vision or infrared which are easily affected by the environment; the positioning result and the thickness evaluation are output synchronously, providing spatial dimension basis for accurate deicing strategy.

[0054] The present application integrates the time delay variation, gradient and positioning coefficient into a hierarchical decision rule, establishes a closed-loop response link from the icing state to the control action; the system triggers a gradual warning according to the consistency result of the continuous detection period, avoiding false actions caused by single fluctuations; at the same time, based on the thickness evaluation result derived from the physical model, it is directly linked to the differentiated operation and maintenance instructions; this design deeply couples state recognition and control logic, reduces the manual intervention link, improves the response real-time performance, and ensures that the operation and maintenance actions match the actual icing risk.

[0055] The application provides a state monitoring method for a new energy wind turbine.

[0056] In an alternative embodiment, the method further comprises: Step S6, generating a blade surface icing position distribution heat map on a monitoring interface based on the icing determination result.

[0057] In this embodiment, based on the icing determination result output by step S5, a blade surface icing position distribution heat map is generated on a visualization interface of a wind farm central monitoring platform. The heat map is dynamically superimposed on a three-dimensional model of the wind turbine blade, and the icing severity of each region is intuitively mapped through different color depths, so that the operation and maintenance personnel can quickly and accurately grasp the blade icing situation.

[0058] Step S7, triggering a hierarchical early warning mechanism when icing is continuously monitored in multiple complete rotation periods.

[0059] In this embodiment, when the system continuously monitors icing in 5 complete rotation periods, a hierarchical early warning and response mechanism is automatically triggered, and the specific rules are as follows: If the average icing thickness is less than 2 mm, a first level response is started, the yaw system is adjusted to reduce the wind angle of the blade, and the icing growth rate is reduced; if the icing thickness is in the range of 2 mm to 5 mm, a second level response is triggered, the generator output power is reduced to a safe threshold range, and the equipment is stabilized; if the icing thickness exceeds 5 mm, a third highest level of early warning is immediately started: the power connection is quickly cut off and the emergency stop operation is performed, and the blade heating deicing system is activated to prevent safety risks.

[0060] All early warning levels, accurate icing positions, ice thickness change trends and corresponding disposal actions are pushed to the wind farm central control platform in real time and complete logs are automatically stored. This step visually presents the icing situation through the icing position heat map, triggers the hierarchical control strategies such as yaw adjustment, power reduction operation and emergency stop, and finally builds a full-process closed-loop response mechanism from detection to execution, ensuring that the icing risk is quickly and accurately disposed.

[0061] A state monitoring device for a new energy wind turbine is also provided in the embodiment, which is used to implement the above-mentioned embodiments and preferred embodiments and has been described above. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, implementation of hardware or a combination of software and hardware is also possible and contemplated.

[0062] The embodiment provides a state monitoring device for a new energy wind turbine, as shown in the drawings, comprising: Figure 2 An acoustic wave acquisition module 21 is configured to use a rotating speed signal at a hub as a synchronous reference, trigger a blade leading edge piezoelectric exciter to output an excitation signal, and acquire acoustic wave data captured by acoustic emission sensors under respective propagation paths of a blade tip, a blade middle, a blade root and a blade root part.

[0063] A first calculation module 22 is configured to extract acoustic wave propagation time delays of the respective propagation paths of the blade tip, the blade middle, the blade root and the blade root part, and calculate acoustic wave propagation time delay variation amounts of the respective paths in adjacent two rotating periods based on continuous rotating period data.

[0064] A second calculation module 23 is configured to establish an acoustic speed-icing thickness correlation model, and calculate an icing position determination coefficient according to the time delay variation amounts of the respective paths of the blade tip, the blade middle, the blade root and the blade root part.

[0065] A state judgment module 24 is configured to judge an icing state and an icing area according to the time delay variation amounts of the respective paths, a time delay variation rate in a unit rotating period, and the icing position determination coefficient.

[0066] The state monitoring device for the new energy wind turbine provided in the embodiment can execute the state monitoring method for the new energy wind turbine provided in any embodiment of the present application, has a function module and beneficial effects corresponding to the execution method. Further function descriptions of the above-mentioned modules and units are the same as those of the corresponding embodiments, and will not be described here.

[0067] The present application provides a state monitoring device for a new energy wind turbine. The present application establishes a direct physical correlation between acoustic speed attenuation and icing thickness by analyzing acoustic wave propagation time delay variation in a blade material. The axial position of icing occurrence is directly derived by calculating time delay gradient ratios of different blade sections (blade tip, blade middle and blade root) and using spatial characteristics of acoustic wave propagation path differences. Compared with traditional monitoring methods based on temperature threshold or vibration amplitude, acoustic wave time delay is extremely sensitive to micro changes in material boundary layers and can capture micro structural changes formed in the initial stage of icing.

[0068] Figure 3 ​A structural schematic diagram of an electronic device is provided for an embodiment of the present application.

[0069] Reference will now be made in detail to Figure 3 which shows a structural schematic diagram suitable for use to implement an electronic device in an embodiment of the present application. The electronic device can include a processor (such as a central processor, a graphics processor, etc.) 301, which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 302 or programs loaded from a memory 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for operation of the electronic device are also stored. The processor 301, the ROM 302, and the RAM 303 are connected to each other through a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0070] Generally, the following devices can be connected to the I / O interface 305: an input device 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a memory 308 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 309. The communication device 309 can allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although Figure 3 The electronic device with various devices is shown, but it should be understood that it is not required to implement or have all the shown devices, and more or fewer devices can be alternatively implemented or had.

[0071] In particular, according to an embodiment of the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network through the communication device 309, or installed from the memory 308, or installed from the ROM 302. When the computer program is executed by the processor 301, the above-mentioned functions defined in the state monitoring method for a new energy wind turbine of an embodiment of the present application are performed.

[0072] Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and use range of an embodiment of the present application.

[0073] The embodiments of the present application further provide a computer readable storage medium, and the method according to the embodiments of the present application can be implemented in hardware, firmware, or recorded in a storage medium, or be implemented as computer code stored in a remote storage medium or a non-transitory machine readable storage medium and stored in a local storage medium to be downloaded through a network, so that the method described herein can be processed by such software on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, a solid state disk, etc. Further, the storage medium can also include a combination of the above-mentioned types of memories. It can be understood that the computer, the processor, the microprocessor controller, or the programmable hardware includes a storage component that can store or receive software or computer code, when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the above-mentioned embodiments of the state monitoring method for the new energy wind turbine are implemented.

[0074] Although the embodiments of the present application are described in conjunction with the drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application, and such modifications and changes fall within the scope defined by the appended claims.

Claims

1. A method for condition monitoring of a new energy wind turbine, characterized in that, The method comprises: Taking the rotating speed signal at the hub as a synchronous reference, triggering the output of the blade leading edge piezoelectric exciter to output an excitation signal, and simultaneously collecting the sound wave data captured by the acoustic emission sensor under each corresponding propagation path of the blade tip, the middle of the blade, the blade root to the blade root; For each propagation path of the blade tip, the middle of the blade, the blade root to the blade root, the sound wave propagation time delay is extracted, and the sound wave propagation time delay variation of each path in adjacent two rotation periods is calculated based on the continuous rotation period data; A sound speed-icing thickness correlation modeling is established, and the icing position judgment coefficient is calculated according to the time delay variation of each path of the blade tip, the middle of the blade, the blade root to the blade root. According to the time delay variation of each propagation path, the time delay variation rate in the unit rotation period, and the icing position judgment coefficient, the icing state and region are judged.

2. The method for monitoring the state of a new energy wind turbine according to claim 1, characterized in that, According to the time delay variation of each propagation path, the time delay variation rate in the unit rotation period, and the icing position judgment coefficient, the icing state and region are judged, including: Judging whether the time delay variation of each propagation path exceeds the first preset value, and whether the time delay variation rate in the unit rotation period is greater than the second preset value; If the time delay variation of each propagation path exceeds the first preset value, and the time delay variation rate in the unit rotation period is greater than the second preset value, the icing state and region are judged according to the relationship between the broken icing position judgment coefficient and the preset threshold.

3. The method for monitoring the state of a new energy wind turbine according to claim 2, characterized in that, According to the relationship between the broken icing position judgment coefficient and the preset threshold, the icing state and region are judged, including: When the icing position judgment coefficient is not less than the first threshold value, but less than the second threshold value, the middle of the blade is determined to be iced, and the second threshold value is greater than the first threshold value; When the icing position judgment coefficient is not less than the second threshold value, but less than the third threshold value, the tip of the blade is determined to be iced, and the third threshold value is greater than the second threshold value; When the icing position judgment coefficient is less than the first threshold value, or not less than the third threshold value, the blade root is determined to be iced.

4. The method for monitoring the state of a new energy wind turbine according to claim 2, characterized in that, According to the time delay variation of each propagation path, the time delay variation rate in the unit rotation period, and the icing position judgment coefficient, the icing state and region are judged, and further comprising: If the time delay variation of each propagation path does not exceed the first preset value at the same time, or the time delay variation rate in the unit rotation period is not greater than the second preset value, it is determined that the blade state is normal.

5. The method for condition monitoring of new energy wind turbine generator according to claim 1, characterized in that, The method further comprises: Pretreating the sound wave data captured by the acoustic emission sensor.

6. The method for condition monitoring of new energy wind turbine generator according to claim 5, characterized in that, The pretreatment of the sound wave data captured by the acoustic emission sensor comprises: For each corresponding propagation path of the blade tip, the middle of the blade, the blade root to the blade root, the sound wave data captured by the acoustic emission sensor is adaptively band-pass filtered; Taking the rotating speed signal at the hub as a synchronous reference, using the rotating speed synchronous average algorithm, the sound wave data of the continuous preset number of rotations are aligned according to the rotation angle and then superimposed and averaged.

7. The method for condition monitoring of new energy wind turbine generator according to claim 1, characterized in that, The method further comprises: Based on the icing judgment result, a thermal map of the icing position distribution on the blade surface is generated on a monitoring interface; When multiple complete rotation periods are continuously monitored to exist in the icing state, a hierarchical early warning mechanism is triggered.

8. A state monitoring device for a new energy wind turbine, characterized in that, The device comprises: The acoustic wave acquisition module is configured to use a rotating speed signal at the hub as a synchronous reference, trigger the leading edge piezoelectric exciter to output an excitation signal, and simultaneously acquire acoustic wave data captured by acoustic emission sensors in corresponding propagation paths of a blade tip, a blade middle, a blade root to a blade root portion. The first calculation module is configured to extract acoustic wave propagation time delays for the propagation paths of the blade tip, the blade middle, the blade root to the blade root portion, and calculate acoustic wave propagation time delay variation amounts of the paths in adjacent two rotating periods based on continuous rotating period data. The second calculation module is configured to establish an acoustic speed-icing thickness correlation model, and calculate an icing position determination coefficient based on the time delay variation amounts of the paths of the blade tip, the blade middle, the blade root to the blade root portion. The state judgment module is configured to determine an icing state and an icing area based on the time delay variation amounts of the paths, a time delay variation rate in a unit rotating period, and the icing position determination coefficient.

9. An electronic device, comprising: The memory and the processor are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to perform the state monitoring method for the new energy wind turbine according to any one of claims 1 to 7. The computer readable storage medium stores computer instructions, and the computer instructions are used to make the computer perform the state monitoring method for the new energy wind turbine according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, ​

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