Abnormal vibration early warning method, device and equipment of wind turbine generator and storage medium

Abstract

The invention discloses an abnormal vibration early warning method, device and equipment of a wind turbine generator and a storage medium, and relates to the technical field of fans, the method comprises the steps that original sensing signals of the wind turbine generator in the operation process are collected through a sensor array, and spectrum analysis is carried out to determine abnormal spectrum features; determining an abnormal vibration area according to the abnormal spectrum features and the sensor array; and comparing the abnormal frequency spectrum characteristics with a frequency spectrum database according to the abnormal vibration area to obtain an abnormal vibration value of the wind turbine generator, so as to carry out abnormal early warning on the wind turbine generator. Original sensing signals in the operation process of the wind turbine generator are monitored through the sensor array, and the abnormal spectrum characteristics are determined through spectral analysis. Through the abnormal frequency spectrum characteristics, the abnormal vibration area and the abnormal vibration value of the wind turbine generator in the operation process can be determined, so that the device of the wind turbine generator which may have a fault can be maintained in time, the timely early warning of the abnormal vibration of the wind turbine generator is realized, and the occurrence of the vibration fault is avoided.

Description

Technical Field

[0001] The present application relates to the field of wind turbine technology, and in particular to an abnormal vibration early warning method, device, equipment and storage medium for a wind turbine set. Background Art

[0002] Wind energy is a renewable energy source, and using wind energy to generate electricity is a common way of generating electricity. Wind power generation is achieved through wind turbines that can convert wind mechanical energy into electrical energy. Wind turbines mainly consist of blades, nacelles, and towers. The blades are connected to the generator in the nacelle through the main shaft so that when the blades rotate under the action of wind, they can drive the generator to generate electricity, thereby realizing the conversion of wind energy into electrical energy.

[0003] In the process of wind turbines converting wind mechanical energy into electrical energy, many parts of the wind turbines will vibrate. Under normal circumstances, this vibration does not affect the operation of the wind turbines. However, since the wind turbine main bearings, gear boxes, couplings, generators, blades and other devices of the wind turbine are a huge mechanical transmission chain system, when any of the devices has problems (such as blade corrosion, cracking of leading and trailing blades, imbalance, loose shaft system components, etc.), the vibration will intensify. When the vibration reaches a certain level, it will lead to vibration failure, thereby damaging the entire wind turbine.

[0004] Therefore, how to detect the vibration condition of wind turbines, quickly make a correct diagnosis during the fault warning period, and prevent vibration failures of wind turbines is an urgent problem to be solved. Summary of the invention

[0005] The main purpose of this application is to provide an abnormal vibration early warning method, device, equipment and storage medium for a wind turbine, aiming to solve the technical problem that when any device in the wind turbine has a problem, it is easy to cause the vibration to intensify and cause vibration failure, thereby damaging the entire wind turbine.

[0006] To achieve the above objectives, the present application proposes an abnormal vibration early warning method for a wind turbine generator set, the method comprising:

[0007] Collecting original sensor signals during the operation of the wind turbine generator set through a sensor array, wherein the sensor array is installed on various components of the wind turbine generator set;

[0008] Performing spectrum analysis on the original sensor signal to determine abnormal spectrum characteristics;

[0009] Determining an abnormal vibration area of ​​the wind turbine generator set according to the abnormal frequency spectrum characteristics and the sensor array;

[0010] Comparing the abnormal frequency spectrum characteristics with a preset frequency spectrum database according to the abnormal vibration area to obtain an abnormal vibration value of the wind turbine generator set, wherein the frequency spectrum database stores conventional frequency spectrum data of each component;

[0011] Based on the abnormal vibration value of the wind turbine generator set, an abnormal warning is issued for the wind turbine generator set.

[0012] In one embodiment, the step of performing spectrum analysis on the original sensor signal to determine abnormal spectrum characteristics includes:

[0013] Extracting an original vibration signal and an original sound signal from the original sensing signal, wherein the sensor array includes a sound sensor and a vibration sensor;

[0014] Performing spectrum analysis on the original vibration signal by fast Fourier transform to obtain abnormal vibration peak value and corresponding change frequency characteristics of the original vibration signal;

[0015] Performing harmonic analysis on the original sound signal to obtain abnormal harmonics of the original sound signal;

[0016] The abnormal vibration peak value, the change frequency characteristic and the abnormal harmonic are used as abnormal frequency spectrum characteristics of the original sensing signal.

[0017] In one embodiment, the step of performing spectrum analysis on the original vibration signal by fast Fourier transform to obtain the abnormal vibration peak value and the corresponding change frequency characteristics of the original vibration signal includes:

[0018] Performing filtering on the original vibration signal to obtain a filtered vibration signal;

[0019] Converting the filtered vibration signal from the time domain to the frequency domain by fast Fourier transform to obtain a frequency domain vibration signal;

[0020] Performing spectrum analysis on the frequency domain vibration signal to obtain an abnormal vibration peak value;

[0021] A time-frequency analysis is performed based on the abnormal vibration peak value to determine a change frequency characteristic corresponding to the abnormal vibration peak value.

[0022] In one embodiment, the step of performing harmonic analysis on the original sound signal to obtain abnormal harmonics of the original sound signal includes:

[0023] Performing noise reduction processing on the original sound signal to obtain a target sound signal;

[0024] Performing intensity measurement according to the target sound signal to obtain a corresponding sound intensity value;

[0025] Performing harmonic analysis on the target sound signal to determine the harmonic characteristics of the target sound signal;

[0026] The original sound signal is subjected to spectrum analysis based on the sound intensity value and the harmonic feature to determine abnormal harmonics of the original sound signal.

[0027] In one embodiment, the step of comparing the abnormal frequency spectrum feature with a preset frequency spectrum database according to the abnormal vibration area to obtain the abnormal vibration value of the wind turbine generator system includes:

[0028] Extracting conventional spectrum data corresponding to the abnormal vibration area in the preset spectrum database;

[0029] Comparing the normal spectrum data with the abnormal spectrum characteristics to obtain corresponding frequency deviation data and amplitude change data;

[0030] Based on the frequency deviation data, the amplitude change data and a preset weight value, an abnormal vibration value of the wind turbine is determined.

[0031] In one embodiment, after the step of providing an abnormal warning to the wind turbine generator set based on the abnormal vibration value of the wind turbine generator set, the method further includes:

[0032] Determining whether the abnormal vibration value of the wind turbine generator set reaches a preset threshold;

[0033] When the abnormal vibration value of the wind turbine generator set reaches the preset threshold, it is determined that there is a damaged component in the wind turbine generator set, and the fault type and component health of the damaged component are determined according to the abnormal vibration value of the wind turbine generator set;

[0034] Generate a maintenance strategy according to the fault type, the component health and the damaged component data;

[0035] The maintenance strategy is sent to maintenance personnel, so that the maintenance personnel can inspect and repair the wind turbine generator set according to the maintenance strategy.

[0036] In addition, to achieve the above purpose, the present application also proposes an abnormal vibration early warning device for a wind turbine generator set, the device comprising:

[0037] A signal acquisition module, used to acquire original sensor signals during the operation of the wind turbine generator set through a sensor array, wherein the sensor array is installed on various components of the wind turbine generator set;

[0038] A spectrum analysis module, used to perform spectrum analysis on the original sensor signal to determine abnormal spectrum characteristics;

[0039] A region determination module, used for determining an abnormal vibration region of the wind turbine generator set according to the abnormal frequency spectrum characteristics and the sensor array;

[0040] A database comparison module, used for comparing the abnormal spectrum characteristics with a preset spectrum database according to the abnormal vibration area to obtain abnormal vibration values ​​of the wind turbine, wherein the spectrum database stores conventional spectrum data of each component;

[0041] The abnormal warning module is used to issue an abnormal warning to the wind turbine generator set based on the abnormal vibration value of the wind turbine generator set.

[0042] In addition, to achieve the above-mentioned purpose, the present application also proposes an abnormal vibration warning device for a wind turbine group, the device comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the abnormal vibration warning method for the wind turbine group as described above.

[0043] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the abnormal vibration warning method for the wind turbine set as described above are implemented.

[0044] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the abnormal vibration early warning method for a wind turbine as described above.

[0045] One or more technical solutions proposed in the present application have at least the following technical effects: the abnormal vibration early warning method of the wind turbine group of the present application includes: collecting the original sensor signal of the wind turbine group during operation through a sensor array, and the sensor array is installed on each component of the wind turbine group; performing spectrum analysis on the original sensor signal to determine abnormal spectrum characteristics; determining the abnormal vibration area of ​​the wind turbine group according to the abnormal spectrum characteristics and the sensor array; comparing the abnormal spectrum characteristics with a preset spectrum database according to the abnormal vibration area to obtain the abnormal vibration value of the wind turbine group, and the spectrum database stores the conventional spectrum data of the various components; based on the abnormal vibration value of the wind turbine group, performing abnormal early warning on the wind turbine group.

[0046] Since the present application monitors the original sensor signals of the wind turbine operation process through the sensor array and performs spectrum analysis on the original sensor signals, the abnormal spectrum characteristics can be determined. The abnormal vibration area and the abnormal vibration value of the wind turbine operation process can be determined through the abnormal spectrum characteristics. Therefore, the device of the wind turbine that may fail can be timely maintained and repaired according to the abnormal vibration value of the wind turbine, which realizes the timely early warning of the abnormal vibration of the wind turbine, avoids the occurrence of vibration failure, and ensures the reliable operation of the wind turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0049] Figure 1 A schematic diagram of a flow chart provided for the first embodiment of the abnormal vibration early warning method for a wind turbine generator system of the present application;

[0050] Figure 2 A schematic diagram of a flow chart provided for the second embodiment of the abnormal vibration early warning method for a wind turbine generator system of the present application;

[0051] Figure 3 This is a schematic diagram of the module structure of the abnormal vibration warning device for a wind turbine generator set according to an embodiment of the present application;

[0052] Figure 4 Schematic diagram of the equipment structure of the hardware operating environment involved in the abnormal vibration early warning method for a wind turbine generator set in an embodiment of the present application.

[0053] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0054] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0055] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0056] It should be noted that the execution subject of this embodiment can be a computing service device with data collection, spectrum analysis and abnormal warning functions, such as a personal computer, a vibration detector, etc., or an electronic device capable of realizing the above functions, an abnormal vibration warning device of a wind turbine that executes the abnormal vibration warning method of the wind turbine of this application (hereinafter referred to as the warning device), etc., and this embodiment does not limit this. The following takes the warning device as an example to illustrate this embodiment and the following embodiments.

[0057] Based on this, the first embodiment of the present application is proposed. The embodiment of the present application provides an abnormal vibration early warning method for a wind turbine generator set, referring to Figure 1 , Figure 1 A flow chart of the abnormal vibration early warning method for a wind turbine generator system according to the present invention is provided.

[0058] In this embodiment, the abnormal vibration early warning method of the wind turbine generator system includes steps S10 to S50:

[0059] Step S10: collecting original sensor signals during the operation of the wind turbine generator set through a sensor array, wherein the sensor array is installed on various components of the wind turbine generator set.

[0060] It is understandable that a wind turbine is a device that converts wind energy into electrical energy, and is mainly composed of blades, hubs, nacelles, towers, etc. When the wind blows the blades to rotate, it drives the generator through a series of mechanical and electrical systems to generate electrical energy.

[0061] The sensor array may refer to an array formed by installing multiple sensors (including vibration sensors, sound sensors, etc.) on various components of the wind turbine (such as the main shaft, bearings, impellers, gears, shaft assemblies, etc.) in a certain arrangement.

[0062] It should be understood that the original sensor signal is an unprocessed sensor signal collected by the sensor array during the operation of the wind turbine generator set converting wind energy into electrical energy.

[0063] In a specific implementation, when a wind turbine is running, various sensors in the sensor array (such as vibration sensors, rotation speed sensors, sound sensors, etc.) will collect original sensor signals related to various states and parameters of the wind turbine operation from different positions and angles.

[0064] Step S20: performing spectrum analysis on the original sensing signal to determine abnormal spectrum features.

[0065] It should be noted that the abnormal spectrum characteristics may be performance characteristics different from the normal operation of the wind turbine generator set presented when the spectrum analysis is performed on the original sensor signal.

[0066] For example, under normal circumstances, the frequency spectrum of the bearing of the wind turbine generator set during operation may have a specific frequency distribution pattern. However, when a bearing fails, an abnormal peak may appear within a specific frequency range.

[0067] In specific implementation, the early warning device can use the spectrum analysis method to convert the original sensor signal of the wind turbine collected by the sensor array from the time domain to the frequency domain to obtain different frequency components and their intensity information. Then, the different frequency components and their intensity information are compared with the spectrum characteristics under normal conditions to obtain abnormal spectrum characteristics that are obviously deviated from normal characteristics.

[0068] In a feasible implementation, step S20 of this embodiment may include the steps of: extracting the original vibration signal and the original sound signal from the original sensor signal, the sensor array including a sound sensor and a vibration sensor; performing spectrum analysis on the original vibration signal through fast Fourier transform to obtain an abnormal vibration peak value and a corresponding change frequency characteristic of the original vibration signal; performing harmonic analysis on the original sound signal to obtain abnormal harmonics of the original sound signal; and using the abnormal vibration peak value, the change frequency characteristic and the abnormal harmonics as abnormal spectrum characteristics of the original sensor signal.

[0069] It should be noted that the original sound signal may be a sound signal generated during the operation of the wind turbine generator set collected by a sound sensor. The original vibration signal may be a vibration signal generated during the operation of the wind turbine generator set collected by a vibration sensor.

[0070] For example, vibration sensors can be arranged inside the blade and on the blade root flange mating surface (for example, the vibration sensor can be installed at 1 / 3 of the blade root of the fan and installed by gluing), to obtain blade vibration data and mating flange gap data, and send them to the data collector in the hub in real time. The collector transmits the data to the wireless AP (Wireless Access Point) in the wind turbine cabin via wireless Wi-Fi, and accesses the wind farm ring network through the optical fiber in the cabin, and finally sends the wind turbine data to the early warning device of the wind farm wind turbine blade status monitoring server. Therefore, through the monitoring of the vibration sensor, damage detection and early warning of wind turbine blade icing, lightning damage, surface peeling, cracks, etc. can be carried out.

[0071] For example, a sound sensor may be installed at the upper portion of the tower door to collect the aerodynamic noise of the wind turbine blades when they are in operation.

[0072] It is understandable that Fast Fourier Transform (FFT) is a fast algorithm that can perform discrete Fourier transform and inverse transform of the original vibration signal. Through discrete Fourier transform, the discrete signal in the time domain corresponding to the original vibration signal can be converted into its representation in the frequency domain, thereby characterizing the amplitude and phase of different frequency components contained in the signal.

[0073] The abnormal vibration peak value may be a vibration amplitude value that appears in the original vibration signal and is significantly higher than the normal vibration value of the wind turbine when the wind turbine is running. The change frequency feature may be the frequency at which the abnormal vibration peak value appears in the entire original vibration signal.

[0074] It should be understood that when performing harmonic analysis on the original sound signal, the sound signal will normally present regular harmonic components. Abnormal harmonics are harmonic components found during the analysis that are inconsistent with the normal expected harmonic pattern. For example, the amplitude of some harmonics increases or decreases abnormally, and harmonic frequencies that should not exist appear.

[0075] Specifically, the early warning device can extract characteristic values ​​based on the collected original sound signal, analyze it from multiple angles such as time domain, energy spectrum, and power spectrum, and determine its harmonic components. Then the monitored harmonic components are compared with the sound signals of intact blades. By analyzing the sound signals, the abnormal harmonics of the blade damage state can be identified, achieving the purpose of blade monitoring and early warning. For example, blade leading edge corrosion, front and rear edge blade cracking, drainage hole blockage, protective film damage and shedding, and other external structural damage to the blade can all be judged from the source of the sound to be in a certain abnormal state.

[0076] In this embodiment, the early warning device first extracts the original vibration signal collected by the vibration sensor and the original sound signal collected by the sound sensor. Then, the original vibration signal is subjected to spectrum analysis through fast Fourier transform to obtain the vibration amplitude value that is significantly higher than the normal vibration of the wind turbine during operation and the change frequency characteristics of the vibration amplitude value in the entire original vibration signal. Then, the original sound signal is subjected to harmonic analysis to identify the abnormal harmonics of the damage state of the blade. Finally, the abnormal vibration peak value, the change frequency characteristics and the abnormal harmonics can be used as the abnormal spectrum characteristics of the above-mentioned original sensor signal. Therefore, through the analysis of the original vibration signal and the original sound signal, the accuracy of the abnormal spectrum characteristics can be further improved.

[0077] In another feasible implementation manner, the step of performing spectrum analysis on the original vibration signal by fast Fourier transform to obtain the abnormal vibration peak value and corresponding change frequency characteristics of the original vibration signal described in this embodiment includes: filtering the original vibration signal to obtain a filtered vibration signal; converting the filtered vibration signal from the time domain to the frequency domain by fast Fourier transform to obtain a frequency domain vibration signal; performing spectrum analysis on the frequency domain vibration signal to obtain an abnormal vibration peak value; performing time-frequency analysis based on the abnormal vibration peak value to determine the change frequency characteristics corresponding to the abnormal vibration peak value.

[0078] In this embodiment, the early warning device can first perform preprocessing such as denoising and filtering on the collected original vibration signal to obtain a filtered vibration signal to improve the quality of the original vibration signal. Then, the filtered vibration signal is converted from a time domain signal to a frequency domain signal through fast Fourier transform to obtain a frequency domain vibration signal. Then, check whether the filtered vibration signal has abnormal peaks or features within a specific frequency range. For example, the broken teeth of a wind turbine may cause obvious impact peaks. If a similar situation occurs, the frequency domain vibration signal will have obvious abnormal vibration peaks. Finally, the abnormal vibration peak is analyzed in the time and frequency dimensions through short-time Fourier transform or wavelet transform to clearly capture the frequency characteristics that change with time, and obtain the changing frequency characteristics corresponding to the abnormal vibration peak, so as to further improve the accuracy of the abnormal vibration data.

[0079] In another feasible implementation manner, the step of performing harmonic analysis on the original sound signal to obtain abnormal harmonics of the original sound signal described in this embodiment includes: performing noise reduction processing on the original sound signal to obtain a target sound signal; performing intensity measurement based on the target sound signal to obtain a corresponding sound intensity value; performing harmonic analysis on the target sound signal to determine the harmonic characteristics of the target sound signal; and performing spectral analysis on the original sound signal based on the sound intensity value and the harmonic characteristics to determine the abnormal harmonics of the original sound signal.

[0080] It should be noted that the sound intensity value may be the sound energy per unit area perpendicular to the direction of sound wave propagation per unit time, and is used to indicate the intensity of the sound generated by the wind turbine during operation.

[0081] The analysis of the sound intensity value can assist in determining abnormal damage to the wind turbine. For example, a sudden high-intensity sound may occur when a tooth is broken, and this is not limited in the present embodiment.

[0082] In this embodiment, the early warning device can perform noise reduction processing on the original sound signal to remove interference such as environmental noise and obtain the target sound signal to improve the purity of the sound signal. Then the sound intensity of the target sound signal is measured to obtain the corresponding sound intensity value. Then the harmonic components in the target sound signal are analyzed, and abnormal harmonics related to the fault are further extracted from the analysis results such as frequency and intensity.

[0083] Step S30: determining an abnormal vibration area of ​​the wind turbine generator system according to the abnormal frequency spectrum characteristics and the sensor array.

[0084] It should be noted that the abnormal vibration area can be a part of the wind turbine that vibrates abnormally compared to the normal state. This situation means that there are problems such as failure, damage, imbalance, looseness, etc.

[0085] In a specific implementation, the early warning device can determine the abnormal vibration area of ​​the wind turbine from the corresponding sensor array according to the collection source of the abnormal spectrum characteristics.

[0086] Exemplarily, abnormal monitoring of wind turbines may include: main bearing / main shaft, bearing failure (bearing inner ring failure, outer ring failure, rolling element failure, cage failure, etc.), main shaft failure (shaft cracks, bending, imbalance, loose shaft system components, etc.), impeller failure (blade imbalance, hub rotation and friction, etc.); gear failure (broken teeth, tooth surface wear, pitting, spalling, tooth surface bonding, etc.); shaft assembly failure (shaft bending, gear eccentricity, shaft system asymmetry, etc.); generator mechanical failure (generator guide bar loosening, breakage, loosening and friction of internal components, loose foundation, insufficient foundation rigidity, etc.), generator electrical failure (three-phase current imbalance, turn-to-turn short circuit, etc.).

[0087] Through the above monitoring, timely correction can be made to ensure that the wind turbine operates under the best conditions.

[0088] Step S40: comparing the abnormal frequency spectrum feature with a preset frequency spectrum database according to the abnormal vibration area to obtain abnormal vibration values ​​of the wind turbine generator set, wherein the frequency spectrum database stores conventional frequency spectrum data of each component.

[0089] Step S50: Based on the abnormal vibration value of the wind turbine generator set, an abnormal warning is issued to the wind turbine generator set.

[0090] It should be noted that the spectrum database may be a database specifically storing spectrum data of various components of the wind turbine generator set in a normal state (ie, conventional spectrum data), which reflects the inherent characteristics of various components in a normal state.

[0091] It is understandable that the abnormal vibration value of the wind turbine generator set may be an abnormal value in which the vibration amplitude of a key part (such as a nacelle, blades, main shaft, etc.) of the wind turbine generator set exceeds a normal range during operation.

[0092] In the specific implementation, the early warning device can compare the abnormal spectrum characteristics actually detected with the regular spectrum data stored in the spectrum database, determine the abnormal degree of the working state of the component, and obtain the abnormal vibration value of the wind turbine. Finally, according to the abnormal vibration value of the wind turbine, the wind turbine is given abnormal early warnings of different degrees and strategies, thus providing an important basis for the monitoring, maintenance and fault diagnosis of the wind turbine.

[0093] In the technical solution provided by this embodiment, when the wind turbine is running, various sensors (such as vibration sensors, speed sensors, sound sensors, etc.) of the sensor array will collect original sensor signals related to various states and parameters of the wind turbine from different positions and angles. At this time, the early warning device can convert the original sensor signal uploaded by the sensor array from the time domain to the frequency domain using the spectrum analysis method to obtain different frequency components and their intensity information. Then, the different frequency components and their intensity information are compared with the spectrum characteristics under normal conditions to obtain abnormal spectrum characteristics that are obviously deviated from normal characteristics. Then, according to the acquisition source of the abnormal spectrum characteristics, the abnormal vibration area of ​​the wind turbine is determined from the corresponding sensor array. Then, the abnormal spectrum characteristics actually detected can be compared with the conventional spectrum data stored in the spectrum database to determine the abnormal degree of the working state of the component and obtain the abnormal vibration value of the wind turbine. Finally, according to the abnormal vibration value of the wind turbine, the wind turbine is given abnormal warnings of different degrees and strategies, thereby providing an important basis for the monitoring, maintenance and fault diagnosis of the wind turbine. Since this embodiment monitors the original sensor signals of the wind turbine during operation through the sensor array and performs spectrum analysis on the original sensor signals, the abnormal spectrum characteristics can be determined. The abnormal vibration area and abnormal vibration value of the wind turbine during operation can be determined by the abnormal spectrum characteristics. Therefore, the device of the wind turbine that may fail can be timely maintained and repaired according to the abnormal vibration value of the wind turbine, which realizes the timely warning of abnormal vibration of the wind turbine, avoids the occurrence of vibration failure, and ensures the reliable operation of the wind turbine.

[0094] Based on the above-mentioned first embodiment of the present application, the second embodiment of the present application is proposed. In the second embodiment of the present application, the same or similar contents as those of the above-mentioned first embodiment can be referred to the above introduction, and will not be repeated later. On this basis, please refer to Figure 2 , Figure 2 A flow chart of the second embodiment of the abnormal vibration early warning method for a wind turbine generator system of the present application is provided.

[0095] In this example, step S40 includes steps S41 to S43:

[0096] Step S41: extracting regular spectrum data corresponding to the abnormal vibration region in the preset spectrum database.

[0097] Step S42: Compare the normal spectrum data with the abnormal spectrum characteristics to obtain corresponding frequency deviation data and amplitude change data.

[0098] It should be noted that the frequency deviation data may be the deviation value between the normal spectrum data and the abnormal spectrum features in terms of frequency. The amplitude change data may be the degree of change between the normal spectrum data and the abnormal spectrum features in terms of amplitude.

[0099] Step S43: determining the abnormal vibration value of the wind turbine generator system based on the frequency deviation data, the amplitude change data and a preset weight value.

[0100] It should be noted that the preset weight value is a pre-set value in the early warning device for weighing the frequency deviation data and amplitude change data in the abnormal spectrum characteristics, and the weight of the factors affecting the vibration of the wind turbine. For example, in the comprehensive evaluation of the abnormal vibration value of the wind turbine, in order to reflect the importance of the wind turbine in the vibration frequency, a weight value of 0.3 is provided for the frequency deviation data, and a weight value of 0.7 is provided for the amplitude change data, which can more accurately reflect the influence of the abnormal vibration value of the wind turbine on the vibration of the wind turbine in terms of vibration frequency.

[0101] In this embodiment, the early warning device can first extract the conventional spectrum data corresponding to the abnormal vibration area in the preset spectrum database. Then compare the conventional spectrum data with the abnormal spectrum characteristics to obtain the frequency deviation data of the two in terms of frequency and the amplitude change data of the two in terms of amplitude. Finally, different preset weight values ​​are configured for the above frequency deviation data and the above amplitude change data, so that the influence of the abnormal vibration value of the wind turbine on the vibration of the wind turbine under different factors can be more accurately reflected.

[0102] Furthermore, after step S50, this example also includes the steps of: determining whether the abnormal vibration value of the wind turbine set reaches a preset threshold; when the abnormal vibration value of the wind turbine set reaches the preset threshold, determining that there are damaged components in the wind turbine set, and determining the fault type and component health of the damaged component through the abnormal vibration value of the wind turbine set; generating a maintenance strategy based on the fault type, the component health and damaged component data; and sending the maintenance strategy to maintenance personnel so that the maintenance personnel can inspect and repair the wind turbine set according to the maintenance strategy.

[0103] It should be noted that the preset threshold value may be a limit value pre-set in the early warning device for determining whether the wind turbine is damaged. When the abnormal vibration value of the wind turbine reaches or exceeds the preset threshold value, it can be determined that the vibration of the wind turbine is too severe, and a certain component of the wind turbine is damaged (i.e., a damaged component) and needs to be repaired.

[0104] Exemplarily, the failure type of the damaged component is the type of failure of the wind turbine set, which may include damage to mechanical components, circuit failure, control system failure, etc., and may include: bearing failure (bearing inner ring failure, outer ring failure, rolling element failure, retaining cage failure, etc.), main shaft failure (shaft cracks, bending, imbalance, loose shaft system components, etc.), impeller failure, etc., which is not limited in this embodiment.

[0105] Component health is an indicator to measure the good condition of the above damaged components. When a damaged component fails, it has a certain degree of wear and damage. A series of maintenance plans (i.e. maintenance strategies) can be formulated based on its component health to ensure the normal operation and safety of the entire wind turbine.

[0106] In this embodiment, the early warning device can first determine whether the abnormal vibration value of the wind turbine has reached a preset threshold; when the preset threshold is reached, it indicates that there are damaged components in the wind turbine. At this time, the abnormal vibration value of the wind turbine can be used to determine the fault type of the damaged component (such as mechanical transmission chain problems such as the wind turbine main bearing, gear box, coupling, generator, etc.) and evaluate the health of the component, so that a maintenance strategy can be proposed in time, so that maintenance personnel can inspect and repair the wind turbine according to the maintenance strategy to ensure the normal operation and safety of the entire wind turbine.

[0107] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the abnormal vibration warning method for the wind turbine set of the present application. More simple transformations based on this technical concept are all within the protection scope of the present application.

[0108] This application also provides an abnormal vibration warning device for a wind turbine generator set, please refer to Figure 3 , Figure 3 This is a schematic diagram of the module structure of the abnormal vibration warning device of the wind turbine generator set according to the embodiment of the present application; the abnormal vibration warning device of the wind turbine generator set comprises:

[0109] A signal acquisition module 301 is used to acquire original sensor signals during the operation of the wind turbine generator set through a sensor array, wherein the sensor array is installed on various components of the wind turbine generator set;

[0110] The spectrum analysis module 302 is used to perform spectrum analysis on the original sensor signal to determine abnormal spectrum characteristics;

[0111] A region determination module 303, configured to determine an abnormal vibration region of the wind turbine generator system according to the abnormal frequency spectrum characteristics and the sensor array;

[0112] A database comparison module 304 is used to compare the abnormal spectrum characteristics with a preset spectrum database according to the abnormal vibration area to obtain an abnormal vibration value of the wind turbine, wherein the spectrum database stores conventional spectrum data of each component;

[0113] The abnormal warning module 305 is used to issue an abnormal warning to the wind turbine generator set based on the abnormal vibration value of the wind turbine generator set.

[0114] As an implementation mode, the spectrum analysis module 302 is also used to extract the original vibration signal and the original sound signal from the original sensor signal, and the sensor array includes a sound sensor and a vibration sensor; perform spectrum analysis on the original vibration signal through fast Fourier transform to obtain the abnormal vibration peak value and the corresponding change frequency characteristics of the original vibration signal; perform harmonic analysis on the original sound signal to obtain the abnormal harmonics of the original sound signal; and use the abnormal vibration peak value, the change frequency characteristics and the abnormal harmonics as the abnormal spectrum characteristics of the original sensor signal.

[0115] As an implementation mode, the spectrum analysis module 302 is also used to filter the original vibration signal to obtain a filtered vibration signal; convert the filtered vibration signal from the time domain to the frequency domain by fast Fourier transform to obtain a frequency domain vibration signal; perform spectrum analysis on the frequency domain vibration signal to obtain an abnormal vibration peak; perform time-frequency analysis based on the abnormal vibration peak to determine the changing frequency characteristics corresponding to the abnormal vibration peak.

[0116] As an implementation mode, the spectrum analysis module 302 is also used to perform noise reduction processing on the original sound signal to obtain a target sound signal; perform intensity measurement based on the target sound signal to obtain a corresponding sound intensity value; perform harmonic analysis on the target sound signal to determine the harmonic characteristics of the target sound signal; perform spectrum analysis on the original sound signal based on the sound intensity value and the harmonic characteristics to determine abnormal harmonics of the original sound signal.

[0117] As an implementation mode, the database comparison module 304 is also used to extract conventional spectrum data corresponding to the abnormal vibration area in the preset spectrum database; compare the conventional spectrum data with the abnormal spectrum characteristics to obtain corresponding frequency deviation data and amplitude change data; and determine the abnormal vibration value of the wind turbine based on the frequency deviation data, the amplitude change data and the preset weight value.

[0118] As an implementation mode, the abnormal warning module 305 is also used to determine whether the abnormal vibration value of the wind turbine set reaches a preset threshold; when the abnormal vibration value of the wind turbine set reaches the preset threshold, it is determined that there are damaged components in the wind turbine set, and the fault type and component health of the damaged component are determined by the abnormal vibration value of the wind turbine set; a maintenance strategy is generated according to the fault type, the component health and the damaged component data; and the maintenance strategy is sent to maintenance personnel so that the maintenance personnel can inspect and repair the wind turbine set according to the maintenance strategy.

[0119] Other embodiments or specific implementations of the abnormal vibration warning device for the wind turbine set of the present application can refer to the above-mentioned method embodiments, which will not be repeated here.

[0120] The abnormal vibration early warning device for a wind turbine provided by the present application adopts the abnormal vibration early warning method for a wind turbine in the above-mentioned embodiment, and can solve the technical problem that when any device in a wind turbine has a problem, it is easy to cause the vibration to intensify and cause a vibration failure, thereby damaging the entire wind turbine. Compared with the prior art, the beneficial effects of the abnormal vibration early warning device for a wind turbine provided by the present application are the same as the beneficial effects of the abnormal vibration early warning method for a wind turbine provided by the above-mentioned embodiment, and the other technical features of the abnormal vibration early warning device for a wind turbine are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0121] The present application provides an abnormal vibration warning device for a wind turbine group, the abnormal vibration warning device for a wind turbine group comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the abnormal vibration warning method for the wind turbine group in the above-mentioned embodiment one.

[0122] Reference below Figure 4 , Figure 4 The device structure diagram of the hardware operating environment involved in the abnormal vibration early warning method of the wind turbine set in the embodiment of the present application shows a schematic diagram of the structure of the abnormal vibration early warning device of the wind turbine set suitable for implementing the embodiment of the present application. The abnormal vibration early warning device of the wind turbine set in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The abnormal vibration warning device for the wind turbine set shown is only an example and should not bring any limitation to the function and scope of use of the embodiment of the present application.

[0123] like Figure 4 As shown, the abnormal vibration warning device of the wind turbine generator set may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 to the random access memory (RAM: Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the abnormal vibration warning device of the wind turbine generator set are also stored. The processing device 1001, the ROM 1002 and the RAM 1004 are connected to each other through a bus 1005. The input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the abnormal vibration warning device of the wind turbine to communicate with other devices wirelessly or by wire to exchange data. Although the abnormal vibration warning device of the wind turbine with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0124] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0125] The abnormal vibration early warning device for a wind turbine provided by the present application adopts the abnormal vibration early warning method for a wind turbine in the above-mentioned embodiment, which can solve the technical problem that when any device in the wind turbine has a problem, it is easy to cause the vibration to intensify and cause a vibration failure, thereby damaging the entire wind turbine. Compared with the prior art, the beneficial effects of the abnormal vibration early warning device for a wind turbine provided by the present application are the same as the beneficial effects of the abnormal vibration early warning method for a wind turbine provided by the above-mentioned embodiment, and the other technical features of the abnormal vibration early warning device for a wind turbine are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0126] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0127] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0128] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the abnormal vibration early warning method for a wind turbine generator set in the above-mentioned embodiment.

[0129] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0130] The computer-readable storage medium may be included in the abnormal vibration warning device of the wind turbine generator set; or may exist independently without being assembled into the abnormal vibration warning device of the wind turbine generator set.

[0131] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the abnormal vibration warning device of the wind turbine set, the abnormal vibration warning device of the wind turbine set: collects original sensor signals of the wind turbine set during operation through a sensor array, and the sensor array is installed on various components of the wind turbine set; performs spectrum analysis on the original sensor signals to determine abnormal spectrum characteristics; determines the abnormal vibration area of ​​the wind turbine set based on the abnormal spectrum characteristics and the sensor array; compares the abnormal spectrum characteristics with a preset spectrum database based on the abnormal vibration area to obtain abnormal vibration values ​​of the wind turbine set, and the spectrum database stores conventional spectrum data of the various components; and performs abnormal warning on the wind turbine set based on the abnormal vibration value of the wind turbine set.

[0132] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0133] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0134] The modules involved in the embodiments described in the present application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0135] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the abnormal vibration early warning method of the above-mentioned wind turbine set, and can solve the technical problem that when any device in the wind turbine set has a problem, it is easy to cause the vibration to intensify and cause a vibration failure, thereby damaging the entire wind turbine set. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the abnormal vibration early warning method of the wind turbine set provided by the above-mentioned embodiment, and will not be repeated here.

[0136] The present application also provides a computer program product, including a computer program, which implements the steps of the abnormal vibration early warning method for a wind turbine generator set as described above when the computer program is executed by a processor.

[0137] The computer program product provided by the present application can solve the technical problem that when any device in a wind turbine has a problem, it is easy to cause the vibration to intensify and cause a vibration failure, thereby damaging the entire wind turbine. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the abnormal vibration early warning method of the wind turbine provided by the above embodiment, and will not be repeated here.

[0138] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for early warning of abnormal vibration of a wind turbine, characterized in that: The method comprises: Collecting original sensor signals during the operation of the wind turbine generator set through a sensor array, wherein the sensor array is installed on various components of the wind turbine generator set; Performing spectrum analysis on the original sensor signal to determine abnormal spectrum characteristics; Determining an abnormal vibration area of ​​the wind turbine generator set according to the abnormal frequency spectrum characteristics and the sensor array; According to the abnormal vibration area, the abnormal spectrum feature is compared with a preset spectrum database to obtain an abnormal vibration value of the wind turbine set, wherein the spectrum database stores conventional spectrum data of each component; Based on the abnormal vibration value of the wind turbine generator set, an abnormal warning is issued for the wind turbine generator set.

2. The method according to claim 1, characterized in that The step of performing spectrum analysis on the original sensor signal to determine abnormal spectrum characteristics comprises: Extracting an original vibration signal and an original sound signal from the original sensing signal, wherein the sensor array includes a sound sensor and a vibration sensor; Performing spectrum analysis on the original vibration signal by fast Fourier transform to obtain abnormal vibration peak value and corresponding change frequency characteristics of the original vibration signal; Performing harmonic analysis on the original sound signal to obtain abnormal harmonics of the original sound signal; The abnormal vibration peak value, the change frequency characteristic and the abnormal harmonic are used as abnormal frequency spectrum characteristics of the original sensing signal.

3. The method according to claim 2, characterized in that The step of performing spectrum analysis on the original vibration signal by fast Fourier transform to obtain the abnormal vibration peak value and the corresponding change frequency characteristics of the original vibration signal comprises: Performing filtering on the original vibration signal to obtain a filtered vibration signal; Converting the filtered vibration signal from the time domain to the frequency domain by fast Fourier transform to obtain a frequency domain vibration signal; Performing spectrum analysis on the frequency domain vibration signal to obtain an abnormal vibration peak value; A time-frequency analysis is performed based on the abnormal vibration peak value to determine a change frequency characteristic corresponding to the abnormal vibration peak value.

4. The method according to claim 2, characterized in that The step of performing harmonic analysis on the original sound signal to obtain abnormal harmonics of the original sound signal comprises: Performing noise reduction processing on the original sound signal to obtain a target sound signal; Performing intensity measurement according to the target sound signal to obtain a corresponding sound intensity value; Performing harmonic analysis on the target sound signal to determine the harmonic characteristics of the target sound signal; The original sound signal is subjected to spectrum analysis based on the sound intensity value and the harmonic feature to determine abnormal harmonics of the original sound signal.

5. The method according to claim 1, characterized in that The step of comparing the abnormal frequency spectrum feature with a preset frequency spectrum database according to the abnormal vibration area to obtain the abnormal vibration value of the wind turbine generator set includes: Extracting conventional spectrum data corresponding to the abnormal vibration area in the preset spectrum database; Comparing the normal spectrum data with the abnormal spectrum characteristics to obtain corresponding frequency deviation data and amplitude change data; Based on the frequency deviation data, the amplitude change data and a preset weight value, an abnormal vibration value of the wind turbine is determined.

6. The method according to any one of claims 1 to 5, characterized in that After the step of providing an abnormal warning to the wind turbine generator set based on the abnormal vibration value of the wind turbine generator set, the method further includes: Determining whether the abnormal vibration value of the wind turbine generator set reaches a preset threshold; When the abnormal vibration value of the wind turbine generator set reaches the preset threshold, it is determined that there is a damaged component in the wind turbine generator set, and the fault type and component health of the damaged component are determined according to the abnormal vibration value of the wind turbine generator set; Generate a maintenance strategy according to the fault type, the component health and the damaged component data; The maintenance strategy is sent to maintenance personnel, so that the maintenance personnel can inspect and repair the wind turbine generator set according to the maintenance strategy.

7. An abnormal vibration warning device for a wind turbine generator set, characterized in that: The device comprises: A signal acquisition module, used to acquire original sensor signals during the operation of the wind turbine generator set through a sensor array, wherein the sensor array is installed on various components of the wind turbine generator set; A spectrum analysis module, used to perform spectrum analysis on the original sensor signal to determine abnormal spectrum characteristics; A region determination module, used for determining an abnormal vibration region of the wind turbine generator set according to the abnormal frequency spectrum characteristics and the sensor array; A database comparison module, used for comparing the abnormal spectrum characteristics with a preset spectrum database according to the abnormal vibration area to obtain abnormal vibration values ​​of the wind turbine, wherein the spectrum database stores conventional spectrum data of each component; The abnormal warning module is used to issue an abnormal warning to the wind turbine generator set based on the abnormal vibration value of the wind turbine generator set.

8. An abnormal vibration warning device for a wind turbine, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the abnormal vibration early warning method for a wind turbine set according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the abnormal vibration early warning method for a wind turbine set according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the abnormal vibration early warning method for a wind turbine set according to any one of claims 1 to 6 are implemented.

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