WO2023142372A1 - 一种针对风力发电机的检测方法和相关装置 - Google Patents

一种针对风力发电机的检测方法和相关装置 Download PDF

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Publication number
WO2023142372A1
WO2023142372A1 PCT/CN2022/102767 CN2022102767W WO2023142372A1 WO 2023142372 A1 WO2023142372 A1 WO 2023142372A1 CN 2022102767 W CN2022102767 W CN 2022102767W WO 2023142372 A1 WO2023142372 A1 WO 2023142372A1
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WO
WIPO (PCT)
Prior art keywords
data
threshold
wind power
rotational speed
wind
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2022/102767
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English (en)
French (fr)
Inventor
孙涛
屈帆
张晓曼
唐浩
黄晓芳
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Goldwind Science and Technology Co Ltd
Original Assignee
Xinjiang Goldwind Science and Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from CN202210114345.4A external-priority patent/CN116557223A/zh
Priority claimed from CN202210333126.5A external-priority patent/CN116928013A/zh
Application filed by Xinjiang Goldwind Science and Technology Co Ltd filed Critical Xinjiang Goldwind Science and Technology Co Ltd
Priority to EP22923180.8A priority Critical patent/EP4345298A4/en
Priority to KR1020237045401A priority patent/KR20240016353A/ko
Priority to US18/574,184 priority patent/US20240352921A1/en
Priority to AU2022437623A priority patent/AU2022437623B2/en
Publication of WO2023142372A1 publication Critical patent/WO2023142372A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
    • F03D17/009—Monitoring or testing of wind motors, e.g. diagnostics characterised by the purpose
    • F03D17/013—Monitoring or testing of wind motors, e.g. diagnostics characterised by the purpose for detecting abnormalities or damage
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
    • F03D17/027—Monitoring or testing of wind motors, e.g. diagnostics characterised by the component being monitored or tested
    • F03D17/029—Blade pitch or yaw drive systems, e.g. pitch or yaw angle
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/0264—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor for stopping; controlling in emergency situations
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/04—Automatic control; Regulation
    • F03D7/042—Automatic control; Regulation by means of an electrical or electronic controller
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/18—Status alarms
    • G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2260/00—Function
    • F05B2260/80—Diagnostics
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/30—Control parameters, e.g. input parameters
    • F05B2270/327—Rotor or generator speeds
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/30—Control parameters, e.g. input parameters
    • F05B2270/328—Blade pitch angle
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/72—Wind turbines with rotation axis in wind direction

Definitions

  • the present application relates to the technical field of wind power generation, in particular to a detection method and related devices for wind power generators.
  • Wind power generation is the main energy supply method in new energy.
  • relevant personnel will set alarm thresholds for wind power generators. Once the operating parameters of wind power generators exceed this threshold, it will Alarm, so as to realize the detection of the running state of the wind turbine.
  • this wind turbine detection method can only provide relatively accurate alarms for data exceeding the alarm threshold, and cannot analyze data that does not exceed the alarm threshold, so it is difficult to effectively detect wind turbines.
  • this application provides a detection method for wind power generators.
  • the processing equipment can analyze the overall operation status of wind power generators within a period of time.
  • an alarm can also be issued to avoid wear and tear of the generator caused by continuous operation of the generator in a relatively abnormal state.
  • the embodiment of the present application discloses a detection method for wind power generators, the method comprising:
  • the first warning information is used to identify that the wind power generator is in an abnormal operation state within the preset period of time , the first data threshold is smaller than the second data threshold, and the second data threshold is used for judging whether the wind power generator fails.
  • the method further includes:
  • the operation data exceeds a second data threshold, generating second alarm information corresponding to the wind power generator, the first data threshold is smaller than the second data threshold, and the second alarm information is used to identify the The wind turbine has malfunctioned.
  • the operating data is pitch angle data
  • the determining the comprehensive data corresponding to the wind turbine according to the operating data includes:
  • the pitch angle data determine the minimum value of the pitch angle fluctuation amplitude, the pitch angle fluctuation period, the pitch angle fluctuation cycle mean value, the pitch angle main frequency and the pitch angle main frequency amplitude corresponding to the wind turbine;
  • the first data threshold includes a pitch angle dominant frequency amplitude threshold, a pitch angle periodic interval fluctuation threshold, and a pitch angle fluctuation amplitude threshold, and the wind generator is generated in response to the comprehensive data exceeding the first data threshold.
  • the corresponding first warning information includes:
  • the operating data is rotational speed data
  • determining the comprehensive data corresponding to the wind power generator according to the operating data includes:
  • the rotational speed data determine the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the mean value of the rotational speed fluctuation period, the main frequency of the rotational speed, and the main frequency amplitude of the rotational speed corresponding to the wind turbine;
  • the first data threshold includes a speed main frequency amplitude threshold, a speed cycle interval fluctuation threshold and a speed fluctuation amplitude threshold, and in response to the comprehensive data exceeding the first data threshold, generating the first data corresponding to the wind turbine A warning message, including:
  • the method further includes:
  • the natural mode frequency is generated based on the vibration during the operation of the wind power generator
  • determining the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the mean value of the rotational speed fluctuation period, the main frequency of the rotational speed and the main frequency amplitude of the rotational speed corresponding to the wind turbine including:
  • the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the mean value of the rotational speed fluctuation period, the main frequency of the rotational speed, and the main frequency amplitude of the rotational speed corresponding to the wind turbine are determined.
  • the method further includes:
  • the determining the comprehensive data corresponding to the wind generator according to the operation data includes:
  • the comprehensive data corresponding to the wind power generator is determined.
  • the embodiment of the present application discloses a detection device for wind power generators, the device includes an acquisition unit, a first determination unit and a first response unit:
  • the acquisition unit is used to acquire the corresponding operation data of the wind power generator within a preset period of time
  • the first determination unit is configured to determine comprehensive data corresponding to the wind generator according to the operation data, the comprehensive data is used to reflect the continuous operation state of the wind generator within the preset period;
  • the first response unit is configured to generate first alarm information corresponding to the wind power generator in response to the comprehensive data exceeding a first data threshold, and the first alarm information is used to identify that the wind power generator is in the It is in an abnormal operation state within the preset period of time, the first data threshold is smaller than the second data threshold, and the second data threshold is used to judge whether the wind power generator is faulty.
  • the device further includes a second response unit:
  • the second response unit is configured to generate second alarm information corresponding to the wind turbine in response to the operating data exceeding a second data threshold, the first data threshold being smaller than the second data threshold, the The second warning information is used to identify that the wind power generator has an operation failure.
  • the operating data is pitch angle data
  • the first determining unit is specifically configured to:
  • the pitch angle data determine the minimum value of the pitch angle fluctuation amplitude, the pitch angle fluctuation period, the pitch angle fluctuation cycle mean value, the pitch angle main frequency and the pitch angle main frequency amplitude corresponding to the wind turbine;
  • the first data threshold includes a pitch angle dominant frequency amplitude threshold, a pitch angle periodic interval fluctuation difference threshold, and a pitch angle fluctuation amplitude threshold, and the first response unit is specifically used for:
  • the running data is rotational speed data
  • the first determining unit is specifically configured to:
  • the rotational speed data determine the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the mean value of the rotational speed fluctuation period, the main frequency of the rotational speed, and the main frequency amplitude of the rotational speed corresponding to the wind turbine;
  • the first data threshold includes a speed main frequency amplitude threshold, a speed cycle interval fluctuation difference threshold, and a speed fluctuation amplitude threshold, and the first response unit is specifically used for:
  • the device also includes a first filter unit:
  • the first filtering unit is configured to filter out the natural mode frequency in the rotational speed signal, and the natural mode frequency is generated based on the vibration during the operation of the wind power generator;
  • the first determining unit is specifically used for:
  • the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the mean value of the rotational speed fluctuation period, the main frequency of the rotational speed, and the main frequency amplitude of the rotational speed corresponding to the wind turbine are determined.
  • the device also includes a second filter unit:
  • the second filtering unit is configured to filter the operating data
  • the first determining unit is specifically used for:
  • the comprehensive data corresponding to the wind power generator is determined.
  • the running data is acceleration data
  • the first data threshold is an overrun ratio threshold
  • the first determining unit is specifically configured to:
  • the device also includes a judging unit and a first control unit:
  • the judging unit is configured to judge whether the acceleration number satisfies a persistent abnormal condition within the preset period of time according to the persistent overrun threshold;
  • the first control unit is configured to control the wind turbine to enter a first load reduction control mode in response to the acceleration data meeting the continuous abnormal condition within the preset period of time.
  • the judging unit is specifically configured to:
  • the acceleration data does not meet a continuous abnormal condition within the preset period of time.
  • the device further includes a second determination unit and a second control unit:
  • the second determination unit is configured to determine an instantaneous overrun threshold corresponding to the wind turbine, where the instantaneous overrun threshold is greater than the continuous overrun threshold;
  • the second control unit is configured to control the wind turbine to enter a second load reduction control mode in response to the acceleration data exceeding the instantaneous overrun threshold.
  • the device further includes a third control unit:
  • the third control unit is configured to control the wind turbine to perform shutdown protection in response to the acceleration data exceeding a limit protection threshold, the limit protection threshold is greater than the instantaneous overrun threshold, and the limit protection threshold is based on The ultimate load of the tower corresponding to the wind generator is determined.
  • the device further includes a fourth control unit:
  • the fourth control unit is configured to control the wind power generation in response to the acceleration data meeting the continuous abnormal condition within the preset time period and the wind power generator is in the first load reduction control mode machine for shutdown protection.
  • the continuous overrun threshold is obtained in the following manner:
  • a data deviation coefficient is determined, and the data deviation coefficient is used to identify the difference between the simulation environment of the simulation experiment and the actual operating environment;
  • the continuous overrun threshold is determined according to the data deviation coefficient and the simulated acceleration data.
  • the continuous exceeding threshold includes multiple thresholds, the multiple continuous exceeding thresholds are different thresholds, and the preset time periods corresponding to different continuous exceeding thresholds are different, and the judging unit is specifically used to :
  • the persistent exceeding threshold it is judged whether the acceleration data satisfies a persistent abnormal condition within a preset period corresponding to the persistent exceeding threshold.
  • the embodiment of the present application discloses a computer-readable storage medium.
  • the instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor executes the method described in the first aspect. Any one of the detection methods for wind power generators.
  • the embodiment of the present application discloses a computer device, including:
  • At least one memory storing computer-executable instructions
  • the at least one processor executes the detection method for the wind power generator according to any one of the first aspect.
  • the computer equipment is set in a controller of the wind farm.
  • the embodiment of the present application discloses a detection system for wind power generators, the system includes:
  • An operating data sensor configured to collect corresponding operating data of the wind generator within a preset period of time
  • the main controller is used to acquire the operation data, so as to execute the detection method for the wind power generator according to any one of the first aspect.
  • the comprehensive data corresponding to the wind generator can be determined according to the operating data, which can reflect wind power generation.
  • the comprehensive data exceeds the first data threshold, it can be explained to a certain extent that the wind turbine continues to operate in a state with relatively abnormal data. In this operating state, although the operating data does not exceed the second data threshold corresponding to the fault, However, it will increase the fatigue load of the wind turbine unit and reduce the service life of the unit.
  • the processing device may generate first alarm information corresponding to the wind turbine, where the first alarm information is used to identify that the wind turbine is in an abnormal state within a preset period of time, and the first alarm information
  • a data threshold is smaller than a second data threshold, and the second data threshold is used for judging whether the wind power generator fails. Therefore, in this way, on the basis of identifying whether the generator is faulty, it is also possible to further detect whether the wind generator is in an unhealthy operating state, so that to a certain extent, it is possible to prevent the wind generator from operating in an unhealthy state. A problem that causes damage to the unit.
  • Fig. 1 is the schematic diagram of a kind of wind power generator provided by the embodiment of the present application.
  • FIG. 2 is a flow chart of a detection method for wind power generators provided by an embodiment of the present application
  • Fig. 3 is a detection method and a schematic diagram for a wind power generator provided by the embodiment of the present application;
  • Fig. 4 is a detection method and a schematic diagram for a wind power generator provided by the embodiment of the present application.
  • Fig. 5 is a detection method and schematic diagram for a wind power generator provided by the embodiment of the present application.
  • Fig. 6 is a detection method and schematic diagram for a wind power generator provided by the embodiment of the present application.
  • FIG. 7 is a schematic diagram of detection based on pitch angle data provided by an embodiment of the present application.
  • Fig. 8 is a schematic diagram of detection based on rotational speed data provided by the embodiment of the present application.
  • FIG. 9 is a flow chart of a detection method for wind power generators provided by an embodiment of the present application.
  • Fig. 10 is a schematic diagram of a detection method for wind power generators provided by the embodiment of the present application.
  • Fig. 11 is a schematic diagram of a detection method for wind power generators provided by the embodiment of the present application.
  • Fig. 12 is a structural block diagram of a detection device for wind power generators provided by the embodiment of the present application.
  • Fig. 13 is a schematic diagram of a detection system for wind power generators provided by an embodiment of the present application.
  • this application provides a detection method for wind power generators.
  • the processing equipment can analyze the overall operation status of wind power generators within a period of time.
  • an alarm can also be issued to avoid wear and tear of the generator caused by continuous operation of the generator in a relatively abnormal state.
  • the method can be applied to a processing device, which is a processing device capable of detecting wind power generators, for example, it can be a main controller of a wind power generator, it can also be a field-level controller, and it can also be a wind power generator.
  • the method can be independently executed by a terminal device or a server, and can also be applied to a network scenario where the terminal device communicates with the server, and is executed by cooperation of the terminal device and the server.
  • the terminal device may be a computer, a mobile phone and other devices.
  • the server can be understood as an application server or a Web server. In actual deployment, the server can be an independent server or a cluster server.
  • Fig. 1 exemplarily shows a schematic diagram of a wind power generator of the present application.
  • the wind generator 100 comprises a tower 110, a nacelle 120 installed on the tower, and a rotor 130 connected to the nacelle; wherein, the nacelle includes key components of the wind generator, such as transmission chain components (main shaft, gear box, generator and other related components), heat dissipation system, controller (such as the main controller), etc.
  • transmission chain components main shaft, gear box, generator and other related components
  • controller such as the main controller
  • the rotor includes a plurality of blades extending from a hub; in the example of Figure 1, the rotor includes a rotor and three blades; each blade is spaced around the hub to facilitate rotation of the rotor to enable kinetic energy to be converted from wind force into usable mechanical energy , and then converted into electrical energy.
  • the hub may be rotatably coupled to a generator located within the nacelle to generate electrical power. In some other examples, other numbers of rotors and blades may also be included.
  • the wind turbine may also include a plurality of different physical sensors and/or virtual sensors.
  • the physical sensors may include operating data sensors for measuring the operating data of the wind generator according to their different uses.
  • the operating data sensor may be Including acceleration sensors, vibration sensors, load sensors, etc.; physical sensors may also include environmental sensors for measuring the environmental state of the wind turbine, for example, the environmental sensors may include temperature sensors, air density sensors, wind speed sensors, wind direction sensors and the like; in addition, the physical sensors may also include sensors for other purposes, which is not limited in this embodiment of the present application.
  • the aforementioned virtual sensor may be a controller based on a virtual model, which may simulate a scenario in which a sensor installed on the wind turbine measures multiple measurements of the wind turbine.
  • the above-mentioned sensors can be connected in communication with the controller, and can perform various functions, such as receiving, transmitting, and/or executing control signals of the wind power generator.
  • the acceleration sensor 140 arranged at the base of the nacelle can collect the acceleration data of the wind power generator; afterward, the acceleration data is converted into an electrical signal, and then the electrical signal can be transmitted to the main controller; the main control After acquiring the above acceleration data, the controller detects the wind power generator based on the acceleration data.
  • Fig. 2 is a flow chart of a detection method for wind power generators provided by the embodiment of the present application, the method includes:
  • the preset time period can be set based on the operating characteristics of the wind generator, for example, it can be set to 60s; the operating data is used to reflect the corresponding operating status of the wind generator, for example, it can be speed data, pitch data, etc. , there is no limit here.
  • the comprehensive data is used to reflect the continuous running state of the wind generator within the preset period, and the continuous running state refers to the running state with less changes when the wind generator is continuously running within the preset time period.
  • the continuous running state can reflect the overall running characteristics of the wind turbine within the preset time period.
  • the processing device can set two types of thresholds for wind turbines, including a first data threshold and a second data threshold, wherein the first data threshold is used to determine whether the wind turbine is When working in an abnormal state, the second data threshold is used to judge whether the wind power generator fails, and the first data threshold is smaller than the second data threshold.
  • the processing device can, on the one hand, judge whether the wind power generator is faulty or not based on the second data threshold. In response to the operation data exceeding the second data threshold, the processing device may generate second alarm information corresponding to the wind power generator, where the second alarm information is used to identify that the wind power generator has an operation failure.
  • the processing device can also determine whether the wind power generator is in an abnormal operation state based on the first data threshold and the comprehensive data. In response to the comprehensive data exceeding the first data threshold, it indicates that the wind power generator continues to work in a relatively abnormal working state within the target time period. At this time, the processing device may generate first alarm information corresponding to the wind power generator. The first The alarm information is used to identify that the wind power generator is in an abnormal operation state within a preset period of time.
  • the comprehensive data corresponding to the wind generator can be determined according to the operating data, which can reflect wind power generation.
  • the comprehensive data exceeds the first data threshold, it can be explained to a certain extent that the wind turbine continues to operate in a state with relatively abnormal data. In this operating state, although the operating data does not exceed the second data threshold corresponding to the fault, However, it will increase the fatigue load of the wind turbine unit and reduce the service life of the unit.
  • the processing device may generate first alarm information corresponding to the wind turbine, where the first alarm information is used to identify that the wind turbine is in an abnormal state within a preset period of time, and the first alarm information
  • a data threshold is smaller than a second data threshold, and the second data threshold is used for judging whether the wind power generator fails. Therefore, in this way, on the basis of identifying whether the generator is faulty, it is also possible to further detect whether the wind generator is in an unhealthy operating state, so that to a certain extent, it is possible to prevent the wind generator from operating in an unhealthy state. A problem that causes damage to the unit.
  • the detection manner of the processing device may also be different.
  • a detailed introduction will be given to different types of operating data.
  • the operating data may be pitch angle data.
  • the processing device may determine the minimum value of the pitch angle fluctuation amplitude and the pitch angle fluctuation value corresponding to the wind turbine according to the pitch angle data. period, the mean value of the pitch fluctuation period, the main frequency of the pitch and the amplitude of the main frequency of the pitch.
  • the fluctuation amplitude refers to the difference between the peak and the trough in the data waveform of the pitch angle, and the interval between the peak and the peak is the fluctuation period, as shown in Fig. 3 .
  • the peaks and troughs of the graph can be found by the difference method, and then the relevant data can be determined.
  • the dominant frequency refers to the dominant frequency, as shown in Figure 4.
  • the first data threshold may include a pitch angle main frequency amplitude threshold, a pitch angle periodic interval fluctuation difference threshold, and a pitch angle fluctuation amplitude threshold.
  • First-order frequency, and the amplitude of the main frequency of the pitch angle is greater than the threshold of the main frequency amplitude of the pitch angle, indicating that the operating parameters of the wind turbine within the target period are relatively abnormal, and the processing device can generate the first alarm corresponding to the wind turbine information.
  • the processing device may also generate the first alarm information corresponding to the wind turbine.
  • the first-order frequency of the tower is an inherent parameter corresponding to the wind turbine, which can be set by relevant personnel when constructing the wind turbine.
  • the operation data may be rotational speed data
  • the processing device may determine the minimum value of rotational speed fluctuation amplitude, rotational speed fluctuation period, mean value of rotational speed fluctuation period, main rotational speed Frequency and speed main frequency amplitude, the speed waveform can be shown in Figure 5, and the speed main frequency can be shown in Figure 6.
  • the first data threshold may include a speed main frequency amplitude threshold, a speed cycle interval fluctuation threshold and a speed fluctuation amplitude threshold.
  • the processing device can generate the first alarm information corresponding to the wind turbine; If the rotational speed period interval fluctuation difference threshold is met, and the minimum value of the rotational speed fluctuation amplitude is greater than the rotational speed fluctuation amplitude, the processing device may generate first alarm information corresponding to the wind turbine.
  • the processing device can filter out the natural mode frequency in the rotational speed signal, and the natural mode frequency is generated based on the vibration during the operation of the wind turbine .
  • the processing device can determine the minimum value of the speed fluctuation amplitude, the speed fluctuation cycle, the average value of the speed fluctuation cycle, the main frequency of the speed and the amplitude of the main frequency of the speed corresponding to the wind turbine according to the filtered speed data, thereby eliminating the wind turbine.
  • the impact of vibration on the speed data improves the accuracy of wind turbine detection.
  • the processing device may also perform filtering processing on the operating data, so as to remove interference such as noise data in the operating data and improve the reliability of the operating data.
  • the processing device can determine the comprehensive data corresponding to the wind power generator according to the operation data after filtering and processing, so as to further improve the detection accuracy.
  • FIG. 7 is a schematic diagram of detection based on pitch angle data provided by an embodiment of the present application.
  • the processing device may collect pitch angle data through a pitch angle measurement unit, for example, a rotary encoder installed in a pitch control system. Through the pitch filter processing unit, low-pass filter processing can be performed to make the calculation of the main frequency and time domain period more accurate. Then, the fast Fourier algorithm can be used to calculate the main frequency and amplitude, and the peak and trough can be found by the difference method. The difference between the peak value and the trough value is the fluctuation amplitude, and the interval between the peak and the peak is the fluctuation period.
  • the processing device can acquire the pitch angle signal fed back by the pitch angle measuring unit in real time as the pitch angle data.
  • the thresholds can be set as follows:
  • the value range for reference is 0.2 ⁇ 5
  • the lower the value the higher the sensitivity of the algorithm for oscillation identification, but the accuracy rate is relatively low when the value is high, it needs to be controlled according to the actual unit characteristics are adjusted.
  • the reference value range is >4, the lower the value, the higher the algorithm’s sensitivity to oscillation identification, but the accuracy rate is lower than when the value is high, it needs to be determined according to the actual unit control characteristics Adjustment.
  • k-period interval fluctuation difference threshold you can refer to the value range from 0.1 to 0.2, the higher the value, the higher the algorithm’s sensitivity to oscillation identification, but the accuracy rate is relatively low when the value is low, it needs to be based on the actual unit control characteristics Make adjustments.
  • the value range for reference is 0.2 ⁇ 10, the lower the value, the higher the sensitivity of the algorithm for oscillation identification, but the accuracy rate is relatively low when the value is high, it needs to be determined according to the actual unit Adjust the control characteristics.
  • the processing device may generate a pitch vibration warning (ie, first warning information) to notify the wind turbine that abnormal vibration occurs in the pitch dimension.
  • a pitch vibration warning ie, first warning information
  • FIG. 8 is a schematic diagram of detection based on rotational speed data provided by an embodiment of the present application.
  • the processing equipment can measure the rotational speed through the rotational speed measurement unit integrated in the converter device of the unit, and then perform low-pass filtering processing, so that the calculation of the main frequency and time domain period is more accurate.
  • the speed signal (that is, the speed data) comes from the source of the speed measurement. It is necessary to filter out the natural modal frequency of the unit in the measured speed signal before it can be applied to the control of the unit. Otherwise, the natural modal frequency of the unit is coupled to the control speed, and the modal frequency will be Further excitation by the control system causes the control system to oscillate.
  • the processing equipment can use the fast Fourier algorithm to calculate the main frequency and amplitude, and use the difference method to find the peak and valley.
  • the difference between the peak value and the valley value is the fluctuation amplitude, and the interval between the peak and the peak is the fluctuation period.
  • the rotational speed signal fed back by the rotational speed measurement unit can be obtained in real time.
  • the threshold used for speed detection is as follows:
  • the value range for reference is 0.2 ⁇ 4, the lower the value, the higher the algorithm’s sensitivity to oscillation identification, but the accuracy rate is relatively low when the value is high, it needs to be based on the actual unit control characteristics Make adjustments.
  • the reference value range is >4, the lower the value, the higher the sensitivity of the algorithm to identify oscillations, but the accuracy rate is relatively low when the value is high, and it needs to be adjusted according to the actual unit control characteristics .
  • k-period interval fluctuation difference threshold you can refer to the value range from 0.1 to 0.2, the higher the value, the higher the algorithm’s sensitivity to oscillation identification, but the accuracy rate is relatively low when the value is low, it needs to be based on the actual unit control characteristics Make adjustments.
  • the reference value range is 0.7 ⁇ 0.9, it needs to be adjusted according to the actual unit control characteristics.
  • the reference value range is 0.7 ⁇ 0.9, and it needs to be adjusted according to the actual unit control characteristics.
  • the processing equipment can further diagnose the root cause of the control system oscillation, which improves the self-diagnosis capability of the unit and reduces the cost of operation and maintenance throughout the life cycle.
  • the operating data is acceleration data
  • the first data threshold is an overrun ratio threshold.
  • the processing device can determine the wind power The generator corresponds to the continuous overrun threshold, and then determine the total number of peaks of the acceleration data within the preset time period, and determine the number of abnormal peaks whose peak value is greater than the continuous overrun threshold in the acceleration data within the preset time period, and the abnormal The ratio of the number of peaks to the total number of peaks was determined as composite data.
  • the processing device may judge whether the acceleration data satisfies the continuous abnormal condition within the preset time period according to the continuous overrun threshold, and control the acceleration data to meet the continuous abnormal condition within the preset time period The wind turbine enters the first load reduction control mode.
  • FIG. 9 is a flow chart of a detection method for wind power generators provided by an embodiment of the present application. The method includes:
  • the acceleration data is used to reflect the vibration of the wind generator, and the vibration can reflect the running state of the wind generator.
  • the acceleration data may be an effective value of acceleration corresponding to the wind turbine, and the effective value of acceleration is determined by the acceleration in the front-back direction and left-right direction corresponding to the wind turbine, and the formula is as follows:
  • A is the effective value of acceleration
  • x is the acceleration value in the front and rear directions
  • y is the acceleration value in the left and right directions.
  • the continuous overrun threshold is used to judge whether the wind turbine has been operating with a large load for a long time. It can be understood that when the load of the wind turbine is large, the vibration amplitude of the wind turbine will be large, and the wind power generator The acceleration data corresponding to the machine will be larger. Of course, the continuous overrun threshold is lower than the instantaneous overrun threshold corresponding to the wind turbine, and the instantaneous overrun threshold is used to determine whether the load of the wind turbine is too high and needs to be shut down.
  • S903 Determine whether the acceleration data satisfies a continuous abnormal condition within a preset period of time according to the continuous overrun threshold.
  • the processing device can judge whether the acceleration data satisfies the continuous abnormal condition within the preset time period according to the continuous overrun threshold value, and the continuous abnormal condition is used to judge whether the wind turbine meets the long-term load operation condition.
  • the set period is determined based on the operating characteristics of the wind turbine.
  • the processing device determines that the acceleration data satisfies the continuous abnormal condition within a preset period of time, it can be determined that the wind turbine is in a state of high load for a long time, causing a high probability of wear and shutdown of the wind turbine.
  • the processing device can reduce the load corresponding to the wind turbine, so that the wind turbine enters the first load reduction control mode with a relatively low load, and the load corresponding to the wind turbine in the first load reduction control mode is lower than that of entering the first load reduction control mode.
  • a load corresponding to the wind turbine before the load reduction control mode Therefore, by reducing the load of the wind power generator, the vibration of the wind power generator is reduced, thereby reducing the wear and the probability of shutdown.
  • the processing device when controlling the wind turbine, can first obtain the acceleration data corresponding to the wind turbine, and determine the continuous exceeding threshold corresponding to the wind turbine, and the continuous exceeding threshold is used for Analyze whether the operating state of the wind turbine is abnormal.
  • the processing device can judge whether the acceleration data satisfies the continuous abnormal condition within the preset time period according to the continuous overrun threshold.
  • the abnormal state for a long time will cause wear and tear on the wind turbine.
  • the processing equipment may not directly shut down the wind turbine, but first perform load reduction processing, and control the wind turbine to enter the first
  • the load reduction control method reduces the load of the wind turbine, attenuates the vibration of the unit, and avoids shutdown due to excessive acceleration data, thereby reducing the loss of the wind turbine and prolonging the operating life of the engine.
  • the processing device may determine the total number of peaks of the acceleration data within a preset time period, and determine the number of abnormal peaks of the acceleration data whose peak values are greater than the continuous exceeding threshold within the preset time period. If the ratio of the number of abnormal peaks to the total number of peaks exceeds the overrun ratio threshold, it indicates that the acceleration data is in a state of high acceleration data for a relatively long part of the preset period of time.
  • the processing device can determine that the acceleration data is within the preset The continuous abnormal condition is satisfied within the time period; if the ratio of the number of abnormal peaks to the total number of peaks does not exceed the overrun ratio threshold, it is determined that the acceleration data does not meet the continuous abnormal condition within the preset time period.
  • Figure 10 is a schematic diagram of a detection method for wind power generators provided by the embodiment of the present application.
  • the processing device can obtain the acceleration effective value obtained by the acceleration sensor in real time, and then use the acceleration effective value peak counting unit to perform Acceleration effective value peak count is recorded as variable a, and the peak count of acceleration effective value peak value greater than the continuous exceeding threshold is recorded as variable b.
  • the processing device can judge whether the value of b/a exceeds the effective value overrun ratio threshold, if it exceeds, it will trigger acceleration fatigue protection and enter the first load reduction control mode, if it does not exceed it, it will recalculate.
  • the processing device can also set an instantaneous overrun threshold for the wind generator, the instantaneous overrun threshold is based on the acceleration during the operation of the wind turbine The maximum value is determined, and is used to judge whether the load condition corresponding to the wind turbine exceeds the maximum value of the acceleration data corresponding to the wind turbine, and the instantaneous overrun threshold is greater than the continuous overrun threshold.
  • the processing device may determine the instantaneous overrun threshold corresponding to the wind turbine, and then make a judgment based on the acceleration data, and in response to the acceleration data exceeding the instantaneous overrun threshold, the processing device may control the wind turbine to enter a second load reduction control mode, The load of the wind power generator corresponding to the second load reduction control mode is lower than the first load reduction control mode. It can be understood that since the instantaneous overrun threshold is relatively high, when the acceleration data exceeds the threshold, it indicates that the current acceleration is too high, and the processing device can directly determine that the wind turbine has a relatively serious operation problem, At this time, the processing device may control the generator to enter a working state with a lower load to protect the wind turbine.
  • the processing device may determine the limit protection threshold corresponding to the wind turbine based on the tower load limit corresponding to the wind turbine, where the limit protection threshold refers to the acceleration data limit that the wind turbine can withstand , the limit protection threshold is greater than the instantaneous overrun threshold. Therefore, in response to the acceleration data exceeding the limit protection threshold, the processing device may control the wind turbine to perform shutdown protection, so as to ensure that the tower load does not exceed the design limit.
  • the processing device in response to the acceleration data meeting the continuous abnormal condition within a preset period of time, and the wind turbine is in the first load reduction control mode, it means that the wind turbine has been in a relatively abnormal state for a long time. In the working state, at this time, the processing device can control the wind turbine for shutdown protection to prevent further wear and tear of the wind turbine.
  • FIG 11 is a schematic diagram of a wind turbine detection method provided by the embodiment of the present application.
  • the processing device can obtain the effective acceleration value obtained by the acceleration sensor in real time. If the acceleration fatigue protection continues to exceed the limit trigger flag bit is TRUE, it means that the effective value of the acceleration meets the continuous abnormal condition. At this time, the processing device can judge whether the wind turbine is in the process of continuous over-limit load reduction control due to acceleration fatigue protection, that is, whether it has entered the first load reduction control mode , if yes, the processing equipment can perform acceleration fatigue protection continuous overrun failure shutdown processing, if not, increase the pitch angle, limit the power and enter the load reduction control, and output the load reduction control mode as 2, that is, the first load reduction control mode .
  • the acceleration limit protection failure shutdown processing can be performed.
  • the processing device can first obtain the wind turbine when determining the threshold value. According to the simulation acceleration data corresponding to the simulation experiment, and then according to the actual operating environment corresponding to the wind turbine, the data deviation coefficient is determined, and the data deviation coefficient is used to identify the difference between the simulation environment of the simulation delay and the actual operating environment.
  • the processing device may determine the continuous overrun threshold according to the data deviation coefficient and the simulated acceleration data.
  • the data deviation coefficient can be 0.6-0.9, referring to 0.6-0.9 times of the maximum effective value of the acceleration under normal power generation conditions calculated by the simulation design, or according to the design margin of the fatigue load of the tower of the actual wind parameter computer unit, according to the design Margin size adjusts this factor.
  • the instantaneous overrun threshold can refer to the maximum effective value of the acceleration amplitude in the simulation design statistics under normal power generation conditions. Considering that there are certain differences between the actual operation and the simulation, it is desirable 1.15 to 1.2 times magnification factor.
  • the determination of the preset time period considers that the modal frequency of the tower of the general wind power generation group is between 0.12-0.4Hz, that is, the vibration period is between 2.5s-8.3s, so it can be set to 60s.
  • the processing device can set multiple levels of continuous overrun thresholds for the wind turbine, that is, the continuous overrun threshold can include multiple, multiple The continuous exceeding thresholds are different thresholds, and the preset time periods corresponding to different continuous exceeding thresholds are different.
  • the processing device can judge whether the acceleration data meets the continuous abnormal condition within the preset period corresponding to the continuous exceeding threshold according to the continuous exceeding threshold, so that the wind turbine can be judged more flexibly. For example, when the continuous overrun threshold is high, the loss probability corresponding to the wind turbine is relatively high, and the corresponding preset period can be short; when the continuous overrun threshold is low, the corresponding loss probability of the wind turbine is low, The corresponding preset time period may be longer. For example, the 10s acceleration RMS peak value continuously exceeds 0.1g, the 30s acceleration RMS peak value continuously exceeds 0.08g, and the 60s acceleration RMS peak value continuously exceeds 0.06g to trigger the control of the wind turbine.
  • the acceleration data in this application can not only obtain the effective value of acceleration by integrating the acceleration in the front-back direction and left-right direction, but also judge the effective value of acceleration in the front-back direction and the effective value of acceleration in the left-right direction separately, and one of them can satisfy the threshold condition. Carry out load shedding or shutdown control.
  • the embodiment of the present application also provides a detection device for wind power generators, see Figure 12, which is a wind power detection device provided by the embodiment of the application Structural block diagram of the detection device 1200 of the generator, the device includes an acquisition unit 1201, a first determination unit 1202 and a first response unit 1203:
  • the acquisition unit 1201 is configured to acquire the corresponding operation data of the wind power generator within a preset period of time;
  • the first determining unit 1202 is configured to determine comprehensive data corresponding to the wind power generator according to the operation data, the comprehensive data is used to reflect the continuous operation state of the wind power generator within the preset period of time;
  • the first response unit 1203 is configured to generate first alarm information corresponding to the wind power generator in response to the comprehensive data exceeding a first data threshold, where the first alarm information is used to identify that the wind power generator is It is in an abnormal operation state within the preset period of time, and the first data threshold is smaller than the second data threshold, and the second data threshold is used to judge whether the wind power generator fails.
  • the device further includes a second response unit:
  • the second response unit is configured to generate second alarm information corresponding to the wind power generator in response to the operating data exceeding a second data threshold, the first data threshold is smaller than the second data threshold, the The second warning information is used to identify that the wind power generator has an operation failure.
  • the operating data is pitch data
  • the first determining unit 1202 is specifically configured to:
  • the pitch angle data determine the minimum value of the pitch angle fluctuation amplitude, the pitch angle fluctuation period, the pitch angle fluctuation cycle mean value, the pitch angle main frequency and the pitch angle main frequency amplitude corresponding to the wind turbine;
  • the first data threshold includes a pitch angle dominant frequency amplitude threshold, a pitch angle periodic interval fluctuation difference threshold, and a pitch angle fluctuation amplitude threshold, and the first response unit 1203 is specifically configured to:
  • the running data is rotational speed data
  • the first determining unit 1202 is specifically configured to:
  • the rotational speed data determine the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the mean value of the rotational speed fluctuation period, the main frequency of the rotational speed, and the main frequency amplitude of the rotational speed corresponding to the wind turbine;
  • the first data threshold includes a speed main frequency amplitude threshold, a speed cycle interval fluctuation difference threshold, and a speed fluctuation amplitude threshold, and the first response unit 1203 is specifically used for:
  • the device also includes a first filter unit:
  • the first filtering unit is configured to filter out the natural mode frequency in the rotational speed signal, and the natural mode frequency is generated based on the vibration during the operation of the wind power generator;
  • the first determining unit 1202 is specifically configured to:
  • the minimum value of the rotational speed fluctuation amplitude, the rotational speed fluctuation period, the mean value of the rotational speed fluctuation period, the main frequency of the rotational speed, and the main frequency amplitude of the rotational speed corresponding to the wind turbine are determined.
  • the device also includes a second filter unit:
  • the second filtering unit is configured to filter the operating data
  • the first determining unit 1202 is specifically configured to:
  • the comprehensive data corresponding to the wind power generator is determined.
  • the running data is acceleration data
  • the first data threshold is an overrun ratio threshold
  • the first determining unit 1202 is specifically configured to:
  • the device also includes a judging unit and a first control unit:
  • the judging unit is configured to judge whether the acceleration number satisfies a persistent abnormal condition within the preset period of time according to the persistent overrun threshold;
  • the first control unit is configured to control the wind turbine to enter a first load reduction control mode in response to the acceleration data meeting the continuous abnormal condition within the preset period of time.
  • the judging unit is specifically configured to:
  • the acceleration data does not meet a continuous abnormal condition within the preset period of time.
  • the device further includes a second determination unit and a second control unit:
  • the second determination unit is configured to determine an instantaneous overrun threshold corresponding to the wind turbine, where the instantaneous overrun threshold is greater than the continuous overrun threshold;
  • the second control unit is configured to control the wind turbine to enter a second load reduction control mode in response to the acceleration data exceeding the instantaneous overrun threshold.
  • the device further includes a third control unit:
  • the third control unit is configured to control the wind turbine to perform shutdown protection in response to the acceleration data exceeding a limit protection threshold, the limit protection threshold is greater than the instantaneous overrun threshold, and the limit protection threshold is based on The ultimate load of the tower corresponding to the wind generator is determined.
  • the device further includes a fourth control unit:
  • the fourth control unit is configured to control the wind power generation in response to the acceleration data meeting the continuous abnormal condition within the preset time period and the wind power generator is in the first load reduction control mode machine for shutdown protection.
  • the continuous overrun threshold is obtained in the following manner:
  • a data deviation coefficient is determined, and the data deviation coefficient is used to identify the difference between the simulation environment of the simulation experiment and the actual operating environment;
  • the continuous overrun threshold is determined according to the data deviation coefficient and the simulated acceleration data.
  • the continuous exceeding threshold includes multiple thresholds, the multiple continuous exceeding thresholds are different thresholds, and the preset time periods corresponding to different continuous exceeding thresholds are different, and the judging unit is specifically used to :
  • the persistent exceeding threshold it is judged whether the acceleration data satisfies a persistent abnormal condition within a preset period corresponding to the persistent exceeding threshold.
  • the embodiment of the present application also provides a computer-readable storage medium.
  • the instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor executes the method described in any one of the above-mentioned embodiments. Detection methods for wind turbines.
  • the embodiment of the present application also provides a computer device, including:
  • At least one memory storing computer-executable instructions
  • the at least one processor executes the detection method for the wind power generator described in any one of the above embodiments.
  • the computer equipment is set in a controller of the wind farm.
  • the embodiment of the present application also provides a detection system for wind-driven generators. As shown in FIG. main controller;
  • the operation data sensor is used to collect the operation data of the wind power generator and send the operation data to the main controller; the main controller is used to execute the detection method for the wind power generator described in any one of the above embodiments.
  • each embodiment in this specification is described in a progressive manner, the same and similar parts of each embodiment can be referred to each other, and each embodiment focuses on the differences from other embodiments. place.
  • the description is relatively simple, and for relevant parts, please refer to part of the description of the method embodiments.
  • the device and system embodiments described above are only illustrative, and the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in One place, or it can be distributed to multiple network elements. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. It can be understood and implemented by those skilled in the art without creative effort.

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Abstract

一种针对风力发电机的检测方法、检测装置和执行该方法的计算机可读存储介质、计算机设备和检测系统，该方法获取风力发电机在预设时段内对应的运行数据，然后根据该运行数据确定风力发电机对应的综合数据，该综合数据用于体现出风力发电机在预设时段内的持续运行状态；当该综合数据超过第一数据阈值时，生成风力发电机对应的第一告警信息，第一告警信息用于标识所述风力发电机在所述预设时段内处于异常运行状态，该异常运行状态会造成风力发电机机组疲劳载荷增大，降低机组使用寿命；第一数据阈值小于第二数据阈值，第二数据阈值用于判断风力发电机是否出现故障。因此，响应于该综合数据超过第一数据阈值，风力发电机处理设备能够生成风力发电机对应的第一告警信息，从而在一定程度上能够避免风力发电机由于工作在不健康的运行状态导致机组损坏的问题。

Description

一种针对风力发电机的检测方法和相关装置
本申请要求于2022年03月31日提交中国专利局、申请号为202210333126.5、申请名称为“一种针对风力发电机的控制方法和相关装置”的中国专利申请的优先权，本申请要求于2022年01月30日提交中国专利局、申请号为202210114345.4、申请名称为“一种针对风力发电机的检测方法和相关装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及风力发电技术领域，特别是涉及一种针对风力发电机的检测方法和相关装置。
背景技术
风力发电是新能源中的主要供能方式，为了维持风力发电机的稳定运行，在相关技术中，相关人员会针对风力发电机设定告警阈值，一旦风力发电机的运行参数超过该阈值就会告警，从而实现对风力发电机运行状态的检测。
然而，这种风力发电机检测方式只能对超过告警阈值的数据进行较为准确的告警，无法针对未超过告警阈值的数据进行分析，因此难以对风力发电机进行有效检测。
发明内容
为了解决上述技术问题，本申请提供了一种针对风力发电机的检测方法，处理设备可以对风力发电机在一段时间内的整体运行状态进行分析，当该时间段内的持续运行状态都对应较为异常的数据时，虽然没有达到故障报警的数据阈值，也可以进行告警，以避免发电机持续工作在较为异常的状态造成发电机磨损。
本申请实施例公开了如下技术方案：
第一方面，本申请实施例公开了一种针对风力发电机的检测方法，所述方法包括：
获取风力发电机在预设时段内对应的运行数据；
根据所述运行数据确定所述风力发电机对应的综合数据，所述综合数据用于体现所述风力发电机在所述预设时段内的持续运行状态；
响应于所述综合数据超过第一数据阈值，生成所述风力发电机对应的第一告警信息，所述第一告警信息用于标识所述风力发电机在所述预设时段内处于异常运行状态，所述第一数据阈值小于第二数据阈值，所述第二数据阈值用于判断所述风力发电机是否出现故障。
在一种可能的实现方式中，所述方法还包括：
响应于所述运行数据超过第二数据阈值，生成所述风力发电机对应的第二告警信息，所述第一数据阈值小于所述第二数据阈值，所述第二告警信息用于标识所述风力发电机出现运行故障。
在一种可能的实现方式中，所述运行数据为桨角数据，所述根据所述运行数据确定所述风力发电机对应的综合数据，包括：
根据所述桨角数据，确定所述风力发电机对应的桨角波动幅值最小值、桨角波动周期、桨角波动周期均值、桨角主频和桨角主频幅值；
所述第一数据阈值包括桨角主频幅值阈值、桨角周期间隔波动差阈值和桨角波动幅值阈值，所述响应于所述综合数据超过第一数据阈值，生成所述风力发电机对应的第一告警信息，包括：
响应于所述桨角主频大于所述风力发电机对应的塔架一阶频率，且所述桨角主频幅值大于所述桨角主频幅值阈值，生成所述风力发电机对应的第一告警信息；
或，响应于所述预设时段内多个桨角波动周期均满足所述桨角周期间隔波动差阈值，且所述桨角波动幅值最小值大于所述桨角波动幅值，生成所述风力发电机对应的第一告警信息。
在一种可能的实现方式中，所述运行数据为转速数据，所述根据所述运行数据确定所述风力发电机对应的综合数据，包括：
根据所述转速数据，确定所述风力发电机对应的转速波动幅值最小值、转速波动周期、转速波动周期均值、转速主频和转速主频幅值；
所述第一数据阈值包括转速主频幅值阈值、转速周期间隔波动差阈值和转速波动幅值阈值，所述响应于所述综合数据超过第一数据阈值，生成所述风力发电机对应的第一告警信息，包括：
响应于所述转速主频大于所述风力发电机对应的塔架一阶频率，且所述转 速主频幅值大于所述转速主频幅值阈值，生成所述风力发电机对应的第一告警信息；
或，响应于所述预设时段内多个转速波动周期均满足所述转速周期间隔波动差阈值，且所述转速波动幅值最小值大于所述转速波动幅值，生成所述风力发电机对应的第一告警信息。
在一种可能的实现方式中，所述方法还包括：
滤除所述转速信号中的固有模态频率，所述固有模态频率是基于所述风力发电机运行过程中的震动生成的；
所述根据所述转速数据，确定所述风力发电机对应的转速波动幅值最小值、转速波动周期、转速波动周期均值、转速主频和转速主频幅值，包括：
根据滤除后的所述转速数据，确定所述风力发电机对应的转速波动幅值最小值、转速波动周期、转速波动周期均值、转速主频和转速主频幅值。
在一种可能的实现方式中，所述方法还包括：
对所述运行数据进行滤波处理；
所述根据所述运行数据确定所述风力发电机对应的综合数据，包括：
根据滤波处理后的所述运行数据，确定所述风力发电机对应的综合数据。
第二方面，本申请实施例公开了一种针对风力发电机的检测装置，所述装置包括获取单元、第一确定单元和第一响应单元：
所述获取单元，用于获取风力发电机在预设时段内对应的运行数据；
所述第一确定单元，用于根据所述运行数据确定所述风力发电机对应的综合数据，所述综合数据用于体现所述风力发电机在所述预设时段内的持续运行状态；
所述第一响应单元，用于响应于所述综合数据超过第一数据阈值，生成所述风力发电机对应的第一告警信息，所述第一告警信息用于标识所述风力发电机在所述预设时段内处于异常运行状态，所述第一数据阈值小于第二数据阈值，所述第二数据阈值用于判断所述风力发电机是否出现故障。
在一种可能的实现方式中，所述装置还包括第二响应单元：
所述第二响应单元，用于响应于所述运行数据超过第二数据阈值，生成所述风力发电机对应的第二告警信息，所述第一数据阈值小于所述第二数据阈值， 所述第二告警信息用于标识所述风力发电机出现运行故障。
在一种可能的实现方式中，所述运行数据为桨角数据，所述第一确定单元具体用于：
根据所述桨角数据，确定所述风力发电机对应的桨角波动幅值最小值、桨角波动周期、桨角波动周期均值、桨角主频和桨角主频幅值；
所述第一数据阈值包括桨角主频幅值阈值、桨角周期间隔波动差阈值和桨角波动幅值阈值，所述第一响应单元具体用于：
响应于所述桨角主频大于所述风力发电机对应的塔架一阶频率，且所述桨角主频幅值大于所述桨角主频幅值阈值，生成所述风力发电机对应的第一告警信息；
或，响应于所述预设时段内多个桨角波动周期均满足所述桨角周期间隔波动差阈值，且所述桨角波动幅值最小值大于所述桨角波动幅值，生成所述风力发电机对应的第一告警信息。
在一种可能的实现方式中，所述运行数据为转速数据，所述第一确定单元具体用于：
根据所述转速数据，确定所述风力发电机对应的转速波动幅值最小值、转速波动周期、转速波动周期均值、转速主频和转速主频幅值；
所述第一数据阈值包括转速主频幅值阈值、转速周期间隔波动差阈值和转速波动幅值阈值，所述第一响应单元具体用于：
响应于所述转速主频大于所述风力发电机对应的塔架一阶频率，且所述转速主频幅值大于所述转速主频幅值阈值，生成所述风力发电机对应的第一告警信息；
或，响应于所述预设时段内多个转速波动周期均满足所述转速周期间隔波动差阈值，且所述转速波动幅值最小值大于所述转速波动幅值，生成所述风力发电机对应的第一告警信息。
在一种可能的实现方式中，所述装置还包括第一过滤单元：
所述第一过滤单元，用于滤除所述转速信号中的固有模态频率，所述固有模态频率是基于所述风力发电机运行过程中的震动生成的；
所述第一确定单元具体用于：
根据滤除后的所述转速数据，确定所述风力发电机对应的转速波动幅值最小值、转速波动周期、转速波动周期均值、转速主频和转速主频幅值。
在一种可能的实现方式中，所述装置还包括第二过滤单元：
所述第二过滤单元，用于对所述运行数据进行滤波处理；
所述第一确定单元具体用于：
根据滤波处理后的所述运行数据，确定所述风力发电机对应的综合数据。
在一种可能的实现方式中，所述运行数据为加速度数据，所述第一数据阈值为超限占比阈值，所述第一确定单元具体用于：
确定所述风力发电机对应的持续超限阈值；
确定所述加速度数据在所述预设时段内的波峰总数，以及确定所述加速度数据在所述预设时段内波峰值大于所述持续超限阈值的异常波峰数；
将所述异常波峰数与所述波峰总数的比值确定为所述综合数据；
所述装置还包括判断单元和第一控制单元：
所述判断单元，用于根据所述持续超限阈值，判断所述加速度数在所述预设时段内是否满足持续异常条件；
所述第一控制单元，用于响应于所述加速度数据在所述预设时段内满足所述持续异常条件，控制所述风力发电机进入第一降载控制模式。
在一种可能的实现方式中，所述判断单元具体用于：
若所述异常波峰数与所述波峰总数的比值超过超限占比阈值，确定所述加速度数据在所述预设时段内满足持续异常条件；
若所述异常波峰数与所述波峰总数的比值未超过超限占比阈值，确定所述加速度数据在所述预设时段内不满足持续异常条件。
在一种可能的实现方式中，所述装置还包括第二确定单元和第二控制单元：
所述第二确定单元，用于确定所述风力发电机对应的瞬时超限阈值，所述瞬时超限阈值大于所述持续超限阈值；
所述第二控制单元，用于响应于所述加速度数据超过所述瞬时超限阈值，控制所述风力发电机进入第二降载控制模式。
在一种可能的实现方式中，所述装置还包括第三控制单元：
所述第三控制单元，用于响应于所述加速度数据超过极限保护阈值，控制 所述风力发电机进行停机保护，所述极限保护阈值大于所述瞬时超限阈值，所述极限保护阈值是基于所述风力发电机对应的塔架极限载荷确定的。
在一种可能的实现方式中，所述装置还包括第四控制单元：
所述第四控制单元，用于响应于所述加速度数据在所述预设时段内满足所述持续异常条件，且所述风力发电机处于所述第一降载控制模式，控制所述风力发电机进行停机保护。
在一种可能的实现方式中，所述持续超限阈值是通过以下方式得到的：
获取所述风力发电机在仿真实验下对应的仿真加速度数据；
根据所述风力发电机对应的实际运行环境，确定数据偏差系数，所述数据偏差系数用于标识所述仿真实验的仿真环境与所述实际运行环境之间的差异；
根据所述数据偏差系数和所述仿真加速度数据，确定所述持续超限阈值。
在一种可能的实现方式中，所述持续超限阈值包括多个，多个持续超限阈值为不同阈值，不同的持续超限阈值所对应的预设时段不同，所述判断单元具体用于：
根据所述持续超限阈值，判断所述加速度数据在所述持续超限阈值对应的预设时段内是否满足持续异常条件。
第三方面，本申请实施例公开了一种计算机可读存储介质，当所述计算机可读存储介质中的指令被至少一个处理器运行时，所述至少一个处理器执行如第一方面中的任一项所述的针对风力发电机的检测方法。
第四方面，本申请实施例公开了一种计算机设备，包括：
至少一个处理器；
至少一个存储计算机可执行指令的存储器，
其中，所述计算机设备可执行指令在被所述至少一个处理器运行时，所述至少一个处理器执行如第一方面中的任一项所述的针对风力发电机的检测方法。
在一种可能的实现方式中，所述计算机设备设置在风电场的控制器中。
第五方面，本申请实施例公开了一种针对风力发电机的检测系统，所述系统包括：
运行数据传感器，用于采集所述风力发电机在预设时段内对应的运行数据；
主控制器，用于获取所述运行数据，以执行如第一方面中的任一项所述的针对风力发电机的检测方法。
由上述技术方案可以看出，在进行检测时，可以获取风力发电机在预设时段内对应的运行数据，然后根据该运行数据确定风力发电机对应的综合数据，该综合数据能够体现出风力发电机在预设时段内的持续运行状态。当该综合数据超过第一数据阈值时，在一定程度上可以说明该风力发电机持续运行在数据较为异常的状态，在这种运行状态下，虽然运行数据没有超过故障对应的第二数据阈值，但是会造成风力发电机机组疲劳载荷增大，降低机组使用寿命。因此，响应于该综合数据超过第一数据阈值，处理设备可以生成风力发电机对应的第一告警信息，该第一告警信息用于标识风力发电机在预设时段内出于异常状态，该第一数据阈值小于第二数据阈值，该第二数据阈值用于判断风力发电机是否出现故障。从而，通过该方式，在对发电机是否故障进行识别的基础上，还能够进一步对风力发电机是否处于不健康的运行状态进行检测，从而在一定程度上能够避免风力发电机由于工作在不健康的运行状态导致机组损坏的问题。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本申请实施例提供的一种风力发电机的示意图；
图2为本申请实施例提供的一种针对风力发电机的检测方法的流程图；
图3为本申请实施例提供的一种针对风力发电机的检测方法和示意图；
图4为本申请实施例提供的一种针对风力发电机的检测方法和示意图；
图5为本申请实施例提供的一种针对风力发电机的检测方法和示意图；
图6为本申请实施例提供的一种针对风力发电机的检测方法和示意图；
图7为本申请实施例提供的一种基于桨角数据进行检测的示意图；
图8为本申请实施例提供的一种基于转速数据进行检测的示意图；
图9为本申请实施例提供的一种针对风力发电机的检测方法的流程图；
图10为本申请实施例提供的一种针对风力发电机的检测方法的示意图；
图11为本申请实施例提供的一种针对风力发电机的检测方法的示意图；
图12为本申请实施例提供的一种针对风力发电机的检测装置的结构框图；
图13为本申请实施例提供的一种针对风力发电机的检测系统的示意图。
具体实施方式
下面结合附图，对本申请的实施例进行描述。
目前风力发电机机组并无针对控制系统振荡的识别与保护方案。既有的加速度超限故障保护、功率超限保护、叶轮过速保护在控制系统振荡异常严重情况下，即加速度幅值、功率、转速超过故障保护阈值时才能起到保护作用。机组在日常的运行中会存在控制系统振荡导致加速度幅值相对较大，转速、功率、桨距角波动，但未达到以上故障标准，机组长期运行在此状态下会造成机组疲劳载荷增大，降低机组使用寿命。
为了解决上述技术问题，本申请提供了一种针对风力发电机的检测方法，处理设备可以对风力发电机在一段时间内的整体运行状态进行分析，当该时间段内的持续运行状态都对应较为异常的数据时，虽然没有达到故障报警的数据阈值，也可以进行告警，以避免发电机持续工作在较为异常的状态造成发电机磨损。
可以理解的是，该方法可以应用于处理设备上，该处理设备为能够进行风力发电机检测的处理设备，例如可以是风力发电机的主控制器，还可以是场级控制器，还可以为具有动作控制功能的终端设备或服务器。该方法可以通过终端设备或服务器独立执行，也可以应用于终端设备和服务器通信的网络场景，通过终端设备和服务器配合执行。其中，终端设备可以为计算机、手机等设备。服务器可以理解为是应用服务器，也可以为Web服务器，在实际部署时，该服务器可以为独立服务器，也可以为集群服务器。
图1示例性示出了本申请的风力发电机的一个示意图。风力发电机100包括塔架110、安装在塔架上的机舱120、以及连接到机舱的转子130；其中，机舱内包括风力发电机的关键部件，如传动链部件(主轴、齿轮箱、发电机等相关部件)、散热系统、控制器(如主控制器)等。
转子包括从轮毂延伸的多个叶片；如图1的示例中，转子包括一个转子和 三个叶片；每个叶片围绕轮毂间隔开以便于转子的旋转，以使得动能能够从风力转换成可用的机械能，并且随后转换成电能。例如，轮毂可以可旋转地联接到位于机舱内的发电机，以产生电能。在一些其他示例中，还可以包括其他数量的转子和叶片。
风力发电机还可以包括多个不同的物理传感器和/或虚拟传感器，物理传感器根据其用途不同，可以包括运行数据传感器，用于测量风力发电机的运行数据，示例性地，该运行数据传感器可以包括加速度传感器、振动传感器、载荷传感器等等；物理传感器还可以包括环境传感器，用于测量风力发电机的环境状态，示例性地，该环境传感器可以包括温度传感器、空气密度传感器、风速传感器、风向传感器等等；此外，物理传感器还可以包括其他用途的传感器，本申请实施例对此不作限定。上述虚拟传感器可以是基于虚拟模型的控制器，可以模拟安装在风力发电机上的传感器测量风力发电机的多个测量的场景。
上述传感器可以与控制器通信连接，可以执行各种不同的功能，如接收、传输、和/或执行风力发电机的控制信号。
在本申请的一个示例中，设置在机舱底座的加速度传感器140，可以采集风力发电机的加速度数据；之后，将该加速度数据转换为电信号，然后可以将电信号传输给主控制器；主控制器在获取到上述加速度数据后，基于该加速度数据对风力发电机进行检测。
接下来，将结合附图，对本申请实施例提供的一种针对风力发电机的检测方法进行介绍。
参见图2，图2为本申请实施例提供的一种针对风力发电机的检测方法的流程图，该方法包括：
S201：获取风力发电机在预设时段内对应的运行数据。
其中，预设时段可以为基于风力发电机的运行特点所设定的，例如可以设定为60s；该运行数据用于体现风力发电机对应的运行状态，例如可以为转速数据、桨角数据等，此处不作限制。
S202：根据运行数据确定风力发电机对应的综合数据。
该综合数据用于体现所述风力发电机在预设时段内的持续运行状态，持续 运行状态是指该风力发电机在该预设时段内持续运行时所处的变化较少的运行状态，该持续运行状态能够反映出该风力发电机在该预设时段内的整体运行特点。
S203：响应于综合数据超过第一数据阈值，生成风力发电机对应的第一告警信息。
为了避免风力发电机长期运行在不健康的运行状态，处理设备可以针对风力发电机设定两类阈值，包括第一数据阈值和第二数据阈值，其中，第一数据阈值用于判定风力发电机是否工作在异常状态，第二数据阈值用于判断风力发电机是否出现故障，该第一数据阈值小于该第二数据阈值。
在进行风力发电机检测时，处理设备一方面可以通过该第二数据阈值，判断该风力发电机是否出现故障。响应于该运行数据超过第二数据阈值，处理设备可以生成风力发电机对应的第二告警信息，该第二告警信息用于标识该风力发电机出现运行故障。
另一方面，即使该运行数据没有超过该第二数据阈值，处理设备还可以基于第一数据阈值和综合数据判断该风力发电机是否处于异常的运行状态。响应于该综合数据超过第一数据阈值，说明该风力发电机在目标时段内持续工作在较为异常的工作状态，此时，处理设备可以生成该风力发电机对应的第一告警信息，该第一告警信息用于标识该风力发电机在预设时段内出于异常运行状态。
由上述技术方案可以看出，在进行检测时，可以获取风力发电机在预设时段内对应的运行数据，然后根据该运行数据确定风力发电机对应的综合数据，该综合数据能够体现出风力发电机在预设时段内的持续运行状态。当该综合数据超过第一数据阈值时，在一定程度上可以说明该风力发电机持续运行在数据较为异常的状态，在这种运行状态下，虽然运行数据没有超过故障对应的第二数据阈值，但是会造成风力发电机机组疲劳载荷增大，降低机组使用寿命。因此，响应于该综合数据超过第一数据阈值，处理设备可以生成风力发电机对应的第一告警信息，该第一告警信息用于标识风力发电机在预设时段内出于异常状态，该第一数据阈值小于第二数据阈值，该第二数据阈值用于判断风力发电机是否出现故障。从而，通过该方式，在对发电机是否故障进行识别的基础上，还能够进一步对风力发电机是否处于不健康的运行状态进行检测，从而在一定 程度上能够避免风力发电机由于工作在不健康的运行状态导致机组损坏的问题。
其中，针对不同的运行数据种类，处理设备进行检测的方式也可以有所不同。接下来，将针对不同类型的运行数据进行详细介绍。
在一种可能的实现方式中，该运行数据可以为桨角数据，在确定综合数据时，处理设备可以根据桨角数据，确定该风力发电机对应的桨角波动幅值最小值、桨角波动周期、桨角波动周期均值、桨角主频和桨角主频幅值。其中，波动幅值是指桨角数据波形中波峰和波谷的差值，波峰与波峰的间隔为波动周期，如图3所示。通过差分法可以找到图形的波峰和波谷，进而确定出相关数据。主频是指主导频率，如图4所示。
在该实现方式中，第一数据阈值可以包括桨角主频幅值阈值、桨角周期间隔波动差阈值和桨角波动幅值阈值，响应于该桨角主频大于风力发电机对应的塔架一阶频率，且该桨角主频幅值大于桨角主频幅值阈值，说明该风力发电机在目标时段内的运行参数都较为异常，处理设备可以生成该风力发电机对应的第一告警信息。或，响应于预设时段内多个桨角波动周期均满足桨角周期间隔波动差阈值，且桨角波动幅值最小值大于桨角波动幅值，也可以证明该风力发电机在目标时段内的运行状态异常，处理设备同样可以生成该风力发电机对应的第一告警信息。塔架一阶频率是该风力发电机所对应的固有参数，可以由相关人员在建设该风力发电机时进行设定。
在另一种可能的实现方式中，该运行数据可以为转速数据，处理设备可以根据转速数据，确定该风力发电机对应的转速波动幅值最小值、转速波动周期、转速波动周期均值、转速主频和转速主频幅值，转速波形可以如图5所示，转速主频可以如图6所示。在该实现方式中，第一数据阈值可以包括转速主频幅值阈值、转速周期间隔波动差阈值和转速波动幅值阈值，在进行检测时，响应于该转速主频大于风力发电机对应的塔架一阶频率，且转速主频幅值大于该转速主频幅值阈值，处理设备可以生成该风力发电机对应的第一告警信息；或，响应于该预设时段内多个转速波动周期均满足转速周期间隔波动差阈值，且该转速波动幅值最小值大于转速波动幅值，处理设备可以生成该风力发电机对应的第一告警信息。
可以理解的是，在风力发电机运行的过程中，由于环境中的风、叶轮转动等原因，风力发电机自身在运行过程中可能会产生一定的震动，而这些震动在一定程度上会对处理设备收集的转速数据带来影响。因此，在一种可能的实现方式中，为了进一步提高检测的准确性，处理设备可以滤除转速信号中的固有模态频率，该固有模态频率是基于风力发电机运行过程中的震动生成的。处理设备可以根据滤除后的转速数据，确定该风力发电机对应的转速波动幅值最小值、转速波动周期、转速波动周期均值、转速主频和转速主频幅值，从而消除风力发电机的震动对转速数据的影响，提高针对风力发电机检测的准确度。
此外，为了进一步提高数据精度，在一种可能的实现方式中，处理设备还可以对运行数据进行滤波处理，从而去除运行数据中的噪音数据等干扰，提高运行数据的可靠程度。处理设备可以根据滤波处理后的运行数据，确定该风力发电机对应的综合数据，进一步提高检测准确度。
例如，如图7所示，图7为本申请实施例提供的一种基于桨角数据进行检测的示意图。处理设备可以通过桨角测量单元，例如可以为安装在变桨系统的旋转编码器，采集桨角数据。通过桨角滤波处理单元，可以进行低通滤波处理，使主频及时域周期计算更加准确。然后，可以使用快速傅里叶算法计算主频及幅值，并且以差分法找出波峰及波谷，波峰值与波谷值的差即为波动幅值，波峰与波峰的间隔为波动周期。处理设备可以实时获取桨角测量单元反馈的桨角信号作为桨角数据。其中，各项阈值可以进行如下设置：
m-主频幅值阈值，可参考的取值范围为0.2～5，取值越低时代表算法对振荡的识别灵敏度越高，但准确率相对取值高时偏低，需要根据实际机组控制特性进行调整。
n-桨角波动周期数，可参考取值范围为>4，取值越低时代表算法对振荡的识别灵敏度越高，但准确率相对取值高时偏低，需要根据实际机组控制特性进行调整。
k-周期间隔波动差阈值，可参考取值范围为0.1～0.2，取值越高时代表算法对振荡的识别灵敏度越高，但准确率相对取值低时偏低，需要根据实际机组控制特性进行调整。
y-桨角波动幅值阈值，可参考的取值范围为0.2～10，取值越低时代表算 法对振荡的识别灵敏度越高，但准确率相对取值高时偏低，需要根据实际机组控制特性进行调整。
如图7所示，在满足相应的条件后，处理设备可以生成桨角振动预警(即第一告警信息)，以通知该风力发电机在桨角维度出现了异常振动情况。
参见图8，图8为本申请实施例提供的一种基于转速数据进行检测的示意图。处理设备可以通过集成在机组变流器装置中转速测量单元测量转速，然后进行低通滤波处理，使主频及时域周期计算更加准确。转速信号(即转速数据)来源于转速测量来源，需要先滤除测量转速信号中机组固有模态频率后才能应用于机组控制，否则机组固有模态频率耦合到控制转速中，该模态频率会被控制系统进一步激励导致控制系统振荡。处理设备可以使用快速傅里叶算法计算主频及幅值，并且以差分法找出波峰及波谷，波峰值与波谷值的差即为波动幅值，波峰与波峰的间隔为波动周期，处理设备可以实时获取转速测量单元反馈的转速信号。其中，转速检测所使用的阈值如下所示：
m-主频幅值阈值，可参考的取值范围为0.2～4，取值低时代表算法对振荡的识别灵敏度越高，但准确率相对取值高时偏低，需要根据实际机组控制特性进行调整。
n-转速波动周期数，可参考取值范围为>4，取值越低时代表算法对振荡的识别灵敏度越高，但准确率相对取值高时偏低，需要根据实际机组控制特性进行调整。
k-周期间隔波动差阈值，可参考取值范围为0.1～0.2，取值越高时代表算法对振荡的识别灵敏度越高，但准确率相对取值低时偏低，需要根据实际机组控制特性进行调整。
y-转速波动差值系数阈值，可参考的取值范围为0.7～0.9，需要根据实际机组控制特性进行调整。
r-转速波动主频幅值差值系数，可参考的取值范围为0.7～0.9，需要根据实际机组控制特性进行调整。
通过上述方式，在风力发电机机组由于控制系统振荡运行在亚健康状态，但严重程度未足以引起其它衍生故障时，可以及时对这种不稳定状态进行识别并预警，保证机组寿命。同时，通过多样化的阈值判定，处理设备可以对控制 系统振荡的根因能够进一步诊断，提升了机组自诊断能力，降低全生命周期运维成本。
在一种可能的实现方式中，该运行数据为加速度数据，第一数据阈值为超限占比阈值，在根据所述运行数据确定所述风力发电机对应的综合数据时，处理设备可以确定风力发电机对应的持续超限阈值，然后确定该加速度数据在所述预设时段内的波峰总数，以及确定加速度数据在预设时段内波峰值大于所述持续超限阈值的异常波峰数，将异常波峰数与波峰总数的比值确定为综合数据。
此外，处理设备可以根据持续超限阈值，判断加速度数在所述预设时段内是否满足持续异常条件，响应于所述加速度数据在所述预设时段内满足所述持续异常条件，控制所述风力发电机进入第一降载控制模式。
参见图9，图9为本申请实施例提供的一种针对风力发电机的检测方法的流程图，该方法包括：
S901：获取风力发电机对应的加速度数据。
该加速度数据用于体现风力发电机的振动情况，该振动情况能够反映出风力发电机的运行状态。其中，该加速度数据可以为风力发电机对应的加速度有效值，该加速度有效值是通过风力发电机对应的前后方向和左右方向的加速度确定的，公式如下：
Figure PCTCN2022102767-appb-000001
其中，A为加速度有效值，x为前后方向加速度值，y为左右方向加速度值。
S902：确定风力发电机对应的持续超限阈值。
该持续超限阈值用于判断该风力发电机是否长时间处于载荷较大的运行状态，可以理解的是，当风力发电机载荷较大时，风力发电机的振动幅度就会较大，风力发电机对应的加速度数据也就越大。当然，该持续超限阈值要低于该风力发电机对应的瞬时超限阈值，该瞬时超限阈值用于判定风力发电机是否载荷过高需要停机处理。
S903：根据持续超限阈值，判断加速度数据在预设时段内是否满足持续异常条件。
可以理解的是，当风力发电机持续运行在载荷较高的工作状态下时，虽然 可能还没有达到必须停机的状况，但是也会对该风力发电机造成一定磨损。因此，处理设备可以根据该持续超限阈值，判断加速度数据在预设时段内是否满足持续异常条件，该持续异常条件用于判断该风力发电机是否满足长时间载荷过高的运行情况，该预设时段是基于风力发电机的运行特点确定的。
S904：响应于该加速度数据在预设时段内满足持续异常条件，控制风力发电机进行第一降载控制模式。
若处理设备确定该加速度数据在预设时段内满足持续异常条件，则可以判定该风力发电机长时间处于载荷较高的状态，造成风力发电机磨损以及停机的概率较大。此时，处理设备可以降低该风力发电机对应的载荷，使风力发电机进入到载荷较低的第一降载控制模式，该第一降载控制模式对应的风力发电机载荷低于进入该第一降载控制模式之前风力发电机对应的载荷。从而，通过降低风力发电机的载荷，降低风力发电机的振荡情况，从而降低磨损以及停机概率。
由上述技术方案可以看出，在对风力发电机进行控制时，处理设备可以先获取风力发电机对应的加速度数据，并确定该风力发电机对应的持续超限阈值，该持续超限阈值用于分析风力发电机的运行状态是否异常。处理设备可以根据该持续超限阈值，判断该加速度数据在预设时段内是否满足持续异常条件，若满足，则说明风力发电机此时处于异常的运行状态，由于该异常状态还在该风力发电机的承受范围内，但是长期处于该异常状态会对风力发电机造成磨损，因此，处理设备可以不直接将风力发电机进行停机，而是先进行降载处理，控制该风力发电机进入第一降载控制方式，从而使风力发电机的载荷降低，衰减机组振动，避免由于加速度数据过高导致停机，进而降低对风力发电机的损耗，延长发动机的运行寿命。
具体的，在一种可能的实现方式中，处理设备可以确定该加速度数据在预设时段内的波峰总数，以及确定该加速度数据在预设时段内波峰值大于持续超限阈值的异常波峰数。若该异常波峰数与波峰总数的比值超过超限占比阈值，则说明在预设时段内有较长一部分时间处于加速度数据较高的状态，此时，处理设备可以确定该加速度数据在预设时段内满足持续异常条件；若该异常波峰数与波峰总数的比值未超过超限占比阈值，则确定该加速度数据在预设时段内 不满足持续异常条件。
如图10所示，图10为本申请实施例提供的一种针对风力发电机的检测方法的示意图，处理设备可以实时获取加速度传感器获取的加速度有效值，然后通过加速度有效值波峰计数单元，进行加速度有效值波峰计数，记为变量a，以及进行加速度有效值波峰值大于持续超限阈值的波峰计数，记为变量b。通过60s计数器，处理设备可以判断b/a的值是否超过有效值超限占比阈值，若超过则触发加速度疲劳保护，进入第一降载控制模式，若未超过则重新计算。
在一种可能的实现方式中，为了进一步提高对风力发电机的保护能力，处理设备还可以为风力发电机设定瞬时超限阈值，该瞬时超限阈值是基于风力发电机运行过程中的加速度最大值确定的，用于判断该风力发电机对应的载荷情况是否超出该风力发电机对应的加速度数据最大值，该瞬时超限阈值大于持续超限阈值。处理设备可以确定该风力发电机对应的瞬时超限阈值，然后基于加速度数据进行判断，响应于该加速度数据超过该瞬时超限阈值，处理设备可以控制该风力发电机进入第二降载控制模式，该第二降载控制模式对应的风力发电机载荷低于第一降载控制模式。可以理解的是，由于该瞬时超限阈值较高，因此当加速度数据超过该阈值时，说明当前加速度出现了过高的情况，处理设备可以直接认定该风力发电机出现了较为严重的运行问题，此时，处理设备可以控制发电机进入载荷更低的工作状态以对风力发电机进行保护。
在一种可能的实现方式中，处理设备可以基于风力发电机对应的塔架载荷极限，确定该风力发电机对应的极限保护阈值，该极限保护阈值是指风力发电机所能够承受的加速度数据极限，该极限保护阈值大于瞬时超限阈值。因此，响应于该加速度数据超过极限保护阈值，处理设备可以控制风力发电机进行停机保护，以保证塔架载荷不超设计极限。
同理，在一种可能的实现方式中，响应于该加速度数据在预设时段内满足该持续异常条件，且风力发电机处于第一降载控制模式，说明该风力发电机长期处于较为异常的工作状态，此时，处理设备可以控制风力发电机进行停机保护，防止风力发电机造成进一步的磨损。
如图11所示，图11为本申请实施例提供的一种针对风力发电机检测方法的示意图，处理设备可以实时获取加速度传感器获取的加速度有效值，若加速 度疲劳保护持续超限触发标志位为TRUE，则说明该加速度有效值满足持续异常条件，此时处理设备可以判断该风力发电机机组是否正处于因加速度疲劳保护持续超限降载控制过程，即是否已经进入了第一降载控制模式，若是，则处理设备可以进行加速度疲劳保护持续超限故障停机处理，若否，则提升桨距角、限功率进入降载控制，并输出降载控制模式为2，即第一降载控制模式。
若不为TURE，则判断加速度有效值是否大于加速度疲劳保护瞬时超限阈值，若大于，则判断机组是否正处于因加速度疲劳保护瞬时超限降载控制过程，即是否正处于第二降载控制模式，若处于，则继续保持当前降载控制模式，若不处于，则预警并提升桨距角，限制功率进入降载控制，并输出降载控制模式为1(即第二降载控制模式)。若检测到加速度有效值大于加速度极限保护阈值，则可以进行加速度极限保护故障停机处理。
可以理解的是，风力发电机进行测试的场景与实际运行场景可能会存在一定的差别，因此，为了保障针对风力发电机控制的准确度，处理设备在进行阈值确定时，可以先获取风力发电机在仿真实验下对应的仿真加速度数据，然后根据风力发电机对应的实际运行环境，确定数据偏差系数，该数据偏差系数用于标识仿真时延的仿真环境与实际运行环境之间的差异。处理设备可以根据该数据偏差系数和仿真加速度数据，确定该持续超限阈值。例如，该数据偏差系数可以为0.6～0.9，参照仿真设计统计到的正常发电工况加速度有效值最大值的0.6-0.9倍，或者根据实际风参计算机组塔架疲劳载荷设计裕度，根据设计裕度大小调整此系数。
同理，其他参数阈值也可以采用该方式进行确定，例如，瞬时超限阈值可以参考正常发电工况下仿真设计统计的加速度幅值有效值最大值，考虑现场实际运行与仿真存在一定差异，可取1.15～1.2倍放大系数。预设时段的确定考虑一般风力发电组的塔架模态频率在0.12-0.4Hz之间，即振动周期在2.5s-8.3s之间，因此可以设置为60s。
此外，为了对风力发电机进行更加精确的控制，在一种可能的实现方式中，处理设备可以为风力发电机设定多档持续超限阈值，即该持续超限阈值可以包括多个，多个持续超限阈值为不同阈值，不同的持续超限阈值所对应的预设时段不同。处理设备可以根据持续超限阈值，判断该加速度数据在持续超限阈值 对应的预设时段内是否满足持续异常条件，从而可以对该风力发电机进行更加灵活的判断。例如，当持续超限阈值较高时，风力发电机对应的损耗概率较大，所对应的预设时段可以较短；当持续超限阈值较低时，风力发电机对应的损耗概率较低，所对应的预设时段可以较长。例如10s加速度有效值波峰值持续超过0.1g，30s加速度有效值波峰值持续超过0.08g，60s加速度有效值波峰值持续超过0.06g后触发对风力发电机的控制。
此外，本申请中的加速度数据既可以为综合前后和左右方向加速度得到加速度有效值，也可以对前后方向的加速度有效值和左右方向的加速度有效值进行单独判断，其中一项满足阈值条件即可进行降载或停机控制。
基于上述实施例提供的一种针对风力发电机的检测方法，本申请实施例还提供了一种针对风力发电机的检测装置，参见图12，图12为本申请实施例提供的一种针对风力发电机的检测装置1200的结构框图，所述装置包括获取单元1201、第一确定单元1202和第一响应单元1203：
所述获取单元1201，用于获取风力发电机在预设时段内对应的运行数据；
所述第一确定单元1202，用于根据所述运行数据确定所述风力发电机对应的综合数据，所述综合数据用于体现所述风力发电机在所述预设时段内的持续运行状态；
所述第一响应单元1203，用于响应于所述综合数据超过第一数据阈值，生成所述风力发电机对应的第一告警信息，所述第一告警信息用于标识所述风力发电机在所述预设时段内处于异常运行状态，所述第一数据阈值小于第二数据阈值，所述第二数据阈值用于判断所述风力发电机是否出现故障。
在一种可能的实现方式中，所述装置还包括第二响应单元：
所述第二响应单元，用于响应于所述运行数据超过第二数据阈值，生成所述风力发电机对应的第二告警信息，所述第一数据阈值小于所述第二数据阈值，所述第二告警信息用于标识所述风力发电机出现运行故障。
在一种可能的实现方式中，所述运行数据为桨角数据，所述第一确定单元 具体1202用于：
根据所述桨角数据，确定所述风力发电机对应的桨角波动幅值最小值、桨角波动周期、桨角波动周期均值、桨角主频和桨角主频幅值；
所述第一数据阈值包括桨角主频幅值阈值、桨角周期间隔波动差阈值和桨角波动幅值阈值，所述第一响应单元1203具体用于：
响应于所述桨角主频大于所述风力发电机对应的塔架一阶频率，且所述桨角主频幅值大于所述桨角主频幅值阈值，生成所述风力发电机对应的第一告警信息；
或，响应于所述预设时段内多个桨角波动周期均满足所述桨角周期间隔波动差阈值，且所述桨角波动幅值最小值大于所述桨角波动幅值，生成所述风力发电机对应的第一告警信息。
在一种可能的实现方式中，所述运行数据为转速数据，所述第一确定单元1202具体用于：
根据所述转速数据，确定所述风力发电机对应的转速波动幅值最小值、转速波动周期、转速波动周期均值、转速主频和转速主频幅值；
所述第一数据阈值包括转速主频幅值阈值、转速周期间隔波动差阈值和转速波动幅值阈值，所述第一响应单元1203具体用于：
响应于所述转速主频大于所述风力发电机对应的塔架一阶频率，且所述转速主频幅值大于所述转速主频幅值阈值，生成所述风力发电机对应的第一告警信息；
或，响应于所述预设时段内多个转速波动周期均满足所述转速周期间隔波动差阈值，且所述转速波动幅值最小值大于所述转速波动幅值，生成所述风力发电机对应的第一告警信息。
在一种可能的实现方式中，所述装置还包括第一过滤单元：
所述第一过滤单元，用于滤除所述转速信号中的固有模态频率，所述固有模态频率是基于所述风力发电机运行过程中的震动生成的；
所述第一确定单元1202具体用于：
根据滤除后的所述转速数据，确定所述风力发电机对应的转速波动幅值最小值、转速波动周期、转速波动周期均值、转速主频和转速主频幅值。
在一种可能的实现方式中，所述装置还包括第二过滤单元：
所述第二过滤单元，用于对所述运行数据进行滤波处理；
所述第一确定单元1202具体用于：
根据滤波处理后的所述运行数据，确定所述风力发电机对应的综合数据。
在一种可能的实现方式中，所述运行数据为加速度数据，所述第一数据阈值为超限占比阈值，所述第一确定单元1202具体用于：
确定所述风力发电机对应的持续超限阈值；
确定所述加速度数据在所述预设时段内的波峰总数，以及确定所述加速度数据在所述预设时段内波峰值大于所述持续超限阈值的异常波峰数；
将所述异常波峰数与所述波峰总数的比值确定为所述综合数据；
所述装置还包括判断单元和第一控制单元：
所述判断单元，用于根据所述持续超限阈值，判断所述加速度数在所述预设时段内是否满足持续异常条件；
所述第一控制单元，用于响应于所述加速度数据在所述预设时段内满足所述持续异常条件，控制所述风力发电机进入第一降载控制模式。
在一种可能的实现方式中，所述判断单元具体用于：
若所述异常波峰数与所述波峰总数的比值超过超限占比阈值，确定所述加速度数据在所述预设时段内满足持续异常条件；
若所述异常波峰数与所述波峰总数的比值未超过超限占比阈值，确定所述加速度数据在所述预设时段内不满足持续异常条件。
在一种可能的实现方式中，所述装置还包括第二确定单元和第二控制单元：
所述第二确定单元，用于确定所述风力发电机对应的瞬时超限阈值，所述瞬时超限阈值大于所述持续超限阈值；
所述第二控制单元，用于响应于所述加速度数据超过所述瞬时超限阈值，控制所述风力发电机进入第二降载控制模式。
在一种可能的实现方式中，所述装置还包括第三控制单元：
所述第三控制单元，用于响应于所述加速度数据超过极限保护阈值，控制所述风力发电机进行停机保护，所述极限保护阈值大于所述瞬时超限阈值，所述极限保护阈值是基于所述风力发电机对应的塔架极限载荷确定的。
在一种可能的实现方式中，所述装置还包括第四控制单元：
所述第四控制单元，用于响应于所述加速度数据在所述预设时段内满足所述持续异常条件，且所述风力发电机处于所述第一降载控制模式，控制所述风力发电机进行停机保护。
在一种可能的实现方式中，所述持续超限阈值是通过以下方式得到的：
获取所述风力发电机在仿真实验下对应的仿真加速度数据；
根据所述风力发电机对应的实际运行环境，确定数据偏差系数，所述数据偏差系数用于标识所述仿真实验的仿真环境与所述实际运行环境之间的差异；
根据所述数据偏差系数和所述仿真加速度数据，确定所述持续超限阈值。
在一种可能的实现方式中，所述持续超限阈值包括多个，多个持续超限阈值为不同阈值，不同的持续超限阈值所对应的预设时段不同，所述判断单元具体用于：
根据所述持续超限阈值，判断所述加速度数据在所述持续超限阈值对应的预设时段内是否满足持续异常条件。
本申请实施例还提供了一种计算机可读存储介质，当所述计算机可读存储介质中的指令被至少一个处理器运行时，所述至少一个处理器执行上述任一项实施例所述的针对风力发电机的检测方法。
本申请实施例还提供了一种计算机设备，包括：
至少一个处理器；
至少一个存储计算机可执行指令的存储器，
其中，所述计算机设备可执行指令在被所述至少一个处理器运行时，所述至少一个处理器执行上述任一项实施例所述的针对风力发电机的检测方法。
在一种可能的实现方式中，所述计算机设备设置在风电场的控制器中。
本申请实施例还提供了一种针对风力发电机的检测系统，如图12所示，该控制系统包括：风力发电机、运行数据传感器，其中，运行数据传感器设置在机舱底座，风力发电机包括主控制器；
运行数据传感器用于采集风力发电机的运行数据，将运行数据发送给主控制器；主控制器用于执行上述任一项实施例所述的针对风力发电机的检测方法。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可 以通过程序指令相关的硬件来完成，前述程序可以存储于一计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质可以是下述介质中的至少一种：只读存储器(英文：read-only memory，缩写：ROM)、RAM、磁碟或者光盘等各种可以存储程序代码的介质。
需要说明的是，本说明书中的各个实施例均采用递进的方式描述，各个实施例之间相同相似的部分互相参见即可，每个实施例重点说明的都是与其他实施例的不同之处。尤其，对于设备及系统实施例而言，由于其基本相似于方法实施例，所以描述得比较简单，相关之处参见方法实施例的部分说明即可。以上所描述的设备及系统实施例仅仅是示意性的，其中作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。本领域普通技术人员在不付出创造性劳动的情况下，即可以理解并实施。
以上所述，仅为本申请的一种具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到的变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应该以权利要求的保护范围为准。

Claims (18)

  1. 一种针对风力发电机的检测方法，其特征在于，所述方法包括：
    获取风力发电机在预设时段内对应的运行数据；
    根据所述运行数据确定所述风力发电机对应的综合数据，所述综合数据用于体现所述风力发电机在所述预设时段内的持续运行状态；
    响应于所述综合数据超过第一数据阈值，生成所述风力发电机对应的第一告警信息，所述第一告警信息用于标识所述风力发电机在所述预设时段内处于异常运行状态，所述第一数据阈值小于第二数据阈值，所述第二数据阈值用于判断所述风力发电机是否出现故障。
  2. 根据权利要求1所述的方法，其特征在于，所述方法还包括：
    响应于所述运行数据超过第二数据阈值，生成所述风力发电机对应的第二告警信息，所述第一数据阈值小于所述第二数据阈值，所述第二告警信息用于标识所述风力发电机出现运行故障。
  3. 根据权利要求1所述的方法，其特征在于，所述运行数据为桨角数据，所述根据所述运行数据确定所述风力发电机对应的综合数据，包括：
    根据所述桨角数据，确定所述风力发电机对应的桨角波动幅值最小值、桨角波动周期、桨角波动周期均值、桨角主频和桨角主频幅值；
    所述第一数据阈值包括桨角主频幅值阈值、桨角周期间隔波动差阈值和桨角波动幅值阈值，所述响应于所述综合数据超过第一数据阈值，生成所述风力发电机对应的第一告警信息，包括：
    响应于所述桨角主频大于所述风力发电机对应的塔架一阶频率，且所述桨角主频幅值大于所述桨角主频幅值阈值，生成所述风力发电机对应的第一告警信息；
    或，响应于所述预设时段内多个桨角波动周期均满足所述桨角周期间隔波动差阈值，且所述桨角波动幅值最小值大于所述桨角波动幅值，生成所述风力发电机对应的第一告警信息。
  4. 根据权利要求1所述的方法，其特征在于，所述运行数据为转速数据，所述根据所述运行数据确定所述风力发电机对应的综合数据，包括：
    根据所述转速数据，确定所述风力发电机对应的转速波动幅值最小值、转 速波动周期、转速波动周期均值、转速主频和转速主频幅值；
    所述第一数据阈值包括转速主频幅值阈值、转速周期间隔波动差阈值和转速波动幅值阈值，所述响应于所述综合数据超过第一数据阈值，生成所述风力发电机对应的第一告警信息，包括：
    响应于所述转速主频大于所述风力发电机对应的塔架一阶频率，且所述转速主频幅值大于所述转速主频幅值阈值，生成所述风力发电机对应的第一告警信息；
    或，响应于所述预设时段内多个转速波动周期均满足所述转速周期间隔波动差阈值，且所述转速波动幅值最小值大于所述转速波动幅值，生成所述风力发电机对应的第一告警信息。
  5. 根据权利要求4所述的方法，其特征在于，所述方法还包括：
    滤除所述转速信号中的固有模态频率，所述固有模态频率是基于所述风力发电机运行过程中的震动生成的；
    所述根据所述转速数据，确定所述风力发电机对应的转速波动幅值最小值、转速波动周期、转速波动周期均值、转速主频和转速主频幅值，包括：
    根据滤除后的所述转速数据，确定所述风力发电机对应的转速波动幅值最小值、转速波动周期、转速波动周期均值、转速主频和转速主频幅值。
  6. 根据权利要求1所述的方法，其特征在于，所述方法还包括：
    对所述运行数据进行滤波处理；
    所述根据所述运行数据确定所述风力发电机对应的综合数据，包括：
    根据滤波处理后的所述运行数据，确定所述风力发电机对应的综合数据。
  7. 根据权利要求1所述的方法，其特征在于，所述运行数据为加速度数据，所述第一数据阈值为超限占比阈值，所述根据所述运行数据确定所述风力发电机对应的综合数据，包括：
    确定所述风力发电机对应的持续超限阈值；
    确定所述加速度数据在所述预设时段内的波峰总数，以及确定所述加速度数据在所述预设时段内波峰值大于所述持续超限阈值的异常波峰数；
    将所述异常波峰数与所述波峰总数的比值确定为所述综合数据；
    所述方法还包括：
    根据所述持续超限阈值，判断所述加速度数在所述预设时段内是否满足持续异常条件；
    响应于所述加速度数据在所述预设时段内满足所述持续异常条件，控制所述风力发电机进入第一降载控制模式。
  8. 根据权利要求7所述的方法，其特征在于，所述根据所述持续超限阈值，判断所述加速度数在所述预设时段内是否满足持续异常条件，包括：
    若所述异常波峰数与所述波峰总数的比值超过超限占比阈值，确定所述加速度数据在所述预设时段内满足持续异常条件；
    若所述异常波峰数与所述波峰总数的比值未超过超限占比阈值，确定所述加速度数据在所述预设时段内不满足持续异常条件。
  9. 根据权利要求7所述的方法，其特征在于，所述方法还包括：
    确定所述风力发电机对应的瞬时超限阈值，所述瞬时超限阈值大于所述持续超限阈值；
    响应于所述加速度数据超过所述瞬时超限阈值，控制所述风力发电机进入第二降载控制模式。
  10. 根据权利要求7所述的方法，其特征在于，所述方法还包括：
    响应于所述加速度数据超过极限保护阈值，控制所述风力发电机进行停机保护，所述极限保护阈值大于所述瞬时超限阈值，所述极限保护阈值是基于所述风力发电机对应的塔架极限载荷确定的。
  11. 根据权利要求7所述的方法，其特征在于，所述方法还包括：
    响应于所述加速度数据在所述预设时段内满足所述持续异常条件，且所述风力发电机处于所述第一降载控制模式，控制所述风力发电机进行停机保护。
  12. 根据权利要求7所述的方法，其特征在于，所述持续超限阈值是通过以下方式得到的：
    获取所述风力发电机在仿真实验下对应的仿真加速度数据；
    根据所述风力发电机对应的实际运行环境，确定数据偏差系数，所述数据偏差系数用于标识所述仿真实验的仿真环境与所述实际运行环境之间的差异；
    根据所述数据偏差系数和所述仿真加速度数据，确定所述持续超限阈值。
  13. 根据权利要求7所述的方法，其特征在于，所述持续超限阈值包括多 个，多个持续超限阈值为不同阈值，不同的持续超限阈值所对应的预设时段不同，所述根据所述持续超限阈值，判断所述加速度数据在预设时段内是否满足持续异常条件，包括：
    根据所述持续超限阈值，判断所述加速度数据在所述持续超限阈值对应的预设时段内是否满足持续异常条件。
  14. 一种针对风力发电机的检测装置，其特征在于，所述装置包括获取单元、第一确定单元和第一响应单元：
    所述获取单元，用于获取风力发电机在预设时段内对应的运行数据；
    所述第一确定单元，用于根据所述运行数据确定所述风力发电机对应的综合数据，所述综合数据用于体现所述风力发电机在所述预设时段内的持续运行状态；
    所述第一响应单元，用于响应于所述综合数据超过第一数据阈值，生成所述风力发电机对应的第一告警信息，所述第一告警信息用于标识所述风力发电机在所述预设时段内处于异常运行状态，所述第一数据阈值小于第二数据阈值，所述第二数据阈值用于判断所述风力发电机是否出现故障。
  15. 一种计算机可读存储介质，其特征在于，当所述计算机可读存储介质中的指令被至少一个处理器运行时，所述至少一个处理器执行如权利要求1-13中的任一项所述的针对风力发电机的检测方法。
  16. 一种计算机设备，其特征在于，包括：
    至少一个处理器；
    至少一个存储计算机可执行指令的存储器，
    其中，所述计算机设备可执行指令在被所述至少一个处理器运行时，所述至少一个处理器执行如权利要求1-13中的任一项所述的针对风力发电机的检测方法。
  17. 根据权利要求16所述的计算机设备，其特征在于，所述计算机设备设置在风电场的控制器中。
  18. 一种针对风力发电机的检测系统，其特征在于，所述系统包括：
    运行数据传感器，用于采集所述风力发电机在预设时段内对应的运行数据；
    主控制器，用于获取所述运行数据，以执行如权利要求1-13中的任一项 所述的针对风力发电机的检测方法。
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