CN111749855B - Method for identifying high-frequency vibration abnormity on line and programmable logic controller - Google Patents

Method for identifying high-frequency vibration abnormity on line and programmable logic controller Download PDF

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CN111749855B
CN111749855B CN201910248170.4A CN201910248170A CN111749855B CN 111749855 B CN111749855 B CN 111749855B CN 201910248170 A CN201910248170 A CN 201910248170A CN 111749855 B CN111749855 B CN 111749855B
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data buffer
vibration
data
identifier
accumulated
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CN111749855A (en
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马羽龙
田萌
胡烨
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Beijing Goldwind Science and Creation Windpower Equipment Co Ltd
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Beijing Goldwind Science and Creation Windpower Equipment Co Ltd
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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
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
    • G05B19/05—Programmable logic controllers, e.g. simulating logic interconnections of signals according to ladder diagrams or function charts
    • G05B19/058—Safety, monitoring
    • 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
    • F05B2270/334—Vibration measurements

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  • Sustainable Energy (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Wind Motors (AREA)
  • Emergency Alarm Devices (AREA)

Abstract

A method for on-line recognizing high-frequency vibration abnormity and a programmable logic controller are provided. The method comprises the following steps: periodically reading real-time vibration data of the wind turbine generator; performing first data analysis on the read vibration data through a first data buffer area; performing second data analysis on the read vibration data through a second data buffer area; and identifying the high-frequency vibration abnormality of the wind turbine generator according to the analysis results of the first data analysis and the second data analysis, wherein a first data buffer area and a second data buffer area are established in the programmable logic controller. According to the method and the programmable logic controller, whether the high-frequency vibration abnormity exists in the wind turbine generator can be rapidly and accurately identified on line through the programmable logic controller, and powerful support is provided for guaranteeing safe and stable operation of the wind turbine generator.

Description

Method for identifying high-frequency vibration abnormity on line and programmable logic controller
Technical Field
The invention relates to the technical field of wind power generation, in particular to a method for identifying high-frequency vibration abnormality of a wind turbine generator on line based on a programmable logic controller and the programmable logic controller.
Background
The fundamental wave frequency doubling vibration of the generator, the high-order vibration of a stator of the generator and the like are main vibration modes of the generator of the direct-drive wind turbine generator, the vibration is generally represented as a high-frequency component (for example, the vibration is generally above 15 Hz) in a generator vibration signal, after the high-frequency vibration is large or the generated frequencies are mutually superposed, the generator and even the whole wind turbine generator can be damaged to different degrees, and the generator can be caused to fail in serious conditions.
The operation analysis of the on-site unit shows that the fundamental wave frequency-doubling vibration of the generator is gradually enhanced along with the increase of the generated power on a high-power machine type, and the fundamental wave frequency-doubling vibration of the generator can even become the dominant frequency of the unit vibration at the full-power generation section and can be superposed with adjacent vibration components such as the high-order vibration mode of the stator of the generator, so that the unit has the risk of mutual excitation of the vibration components. High-frequency vibration components such as fundamental wave double-frequency vibration of the generator, high-order vibration of a stator of the generator and the like become one of main sources of abnormal vibration of the unit when the unit is close to full power. Therefore, in the power generation process of the wind turbine generator, it is important to accurately identify whether high-frequency vibration component abnormalities such as fundamental frequency doubling vibration of the generator, high-order vibration of a stator of the generator and the like exist in real time.
The existing vibration identification method for the wind turbine generator set mainly comprises the steps of carrying out Fast Fourier Transform (FFT) on collected generator set vibration signals through a professional software (such as Matlab) tool, and further analyzing frequency components and energy spectrum density distribution conditions in the generator set vibration signals.
Disclosure of Invention
An exemplary embodiment of the present invention provides a method for identifying a high-frequency vibration abnormality of a wind turbine generator on line based on a programmable logic controller and the programmable logic controller, so as to solve the problem that the high-frequency vibration abnormality of the wind turbine generator cannot be identified on line in real time in the prior art.
According to an exemplary embodiment of the invention, a method for identifying high-frequency vibration abnormality of a wind turbine generator on line based on a Programmable Logic Controller (PLC) is provided, and the method comprises the following steps: periodically reading real-time vibration data of the wind turbine generator; performing first data analysis on the read vibration data through a first data buffer area; performing second data analysis on the read vibration data through a second data buffer area; and identifying the high-frequency vibration abnormality of the wind turbine generator according to the analysis results of the first data analysis and the second data analysis, wherein a first data buffer area and a second data buffer area are established in the PLC.
Optionally, the step of performing a first data analysis on the read vibration data through a first data buffer includes: based on the condition that whether the vibration data read in each reading period in the current time period with the preset length exceeds the preset vibration early warning value or not, performing first data analysis on the vibration data in the current time period through a first data buffer area, wherein the step of performing second data analysis on the read vibration data through a second data buffer area comprises the following steps: and performing second data analysis on the vibration data in the current time period through a second data buffer area based on the condition whether the vibration data in the current time period exceeds the vibration early warning value.
Optionally, the step of performing a first data analysis on the vibration data in the current time period through the first data buffer includes: and counting the peak accumulated quantity of the vibration data exceeding the vibration early warning value in the current time period through the first data buffer area.
Optionally, the step of performing a second data analysis on the vibration data in the current time period through a second data buffer includes: and counting the accumulated time length of the vibration data exceeding the vibration early warning value in the current time period through the second data buffer area.
Optionally, the size of the first data buffer and/or the second data buffer is determined based on the reading period of the vibration data and the preset length of the current time period.
Optionally, the step of identifying the abnormal high-frequency vibration of the wind turbine generator according to the analysis results of the first data analysis and the second data analysis includes: when the accumulated number of wave crests in the current time period exceeds the preset accumulated number, determining that high-frequency vibration abnormity exists in the current time period; or when the accumulated number of wave crests in the current time period exceeds a preset accumulated number and the accumulated duration exceeds the preset duration, determining that the high-frequency vibration abnormality exists in the current time period.
Optionally, the step of counting, by the first data buffer, the number of peaks of the vibration data exceeding the vibration warning value in the current time period includes: determining whether the vibration data read in the current reading period exceeds a vibration early warning value and the vibration data read in the previous reading period does not exceed the vibration early warning value; when the vibration data read in the current reading period exceeds the vibration early warning value and the vibration data read in the previous reading period does not exceed the vibration early warning value, writing the first identifier into a first data buffer area; otherwise, writing the second identifier into the first data buffer; adding 1 to the peak accumulated quantity or keeping the peak accumulated quantity unchanged when the first identifier is written into the first data buffer area; and when the second identifier is written into the first data buffer area, subtracting 1 from the peak accumulation number or keeping the peak accumulation number unchanged, wherein the initial value of the peak accumulation number is 0.
Optionally, when writing the first identifier to the first data buffer, the step of adding 1 to the accumulated number of peaks or keeping the accumulated number of peaks unchanged comprises: adding 1 to the peak cumulative number or keeping the peak cumulative number constant based on whether the first data buffer is full, and the data written first therein when full is the first identifier before writing the first identifier to the first data buffer when writing the first identifier to the first data buffer, wherein the step of subtracting 1 from the peak cumulative number or keeping the peak cumulative number constant when writing the second identifier to the first data buffer comprises: when the second identifier is written into the first data buffer, the peak accumulation amount is reduced by 1 or kept unchanged based on whether the first data buffer is full and whether the data written first therein is the first identifier before the second identifier is written into the first data buffer, wherein the first data buffer is a first-in first-out data buffer.
Optionally, the step of counting, by the second data buffer, an accumulated time period during which the vibration data exceeds the vibration warning value in the current time period includes: determining whether the vibration data read in the current reading period exceeds a vibration early warning value; when the vibration data read in the current reading period exceeds the vibration early warning value, writing the first identifier into a second data buffer area; otherwise, writing the second identifier into the second data buffer; when the first identifier is written into the second data buffer area, increasing the accumulated time length by one reading period or keeping the accumulated time length unchanged; and when writing a second identifier into a second data buffer, keeping the accumulated time length unchanged or reducing the accumulated time length by one reading period, wherein the initial value of the accumulated time length is 0.
Optionally, when writing the first identifier into the second data buffer, the step of increasing the accumulated time duration by one read cycle or keeping the accumulated time duration unchanged comprises: when writing the first identifier to the second data buffer, increasing the accumulated time duration by one read cycle or keeping the accumulated time duration constant based on whether the second data buffer is full, and when full, the data that was first written therein is the first identifier before writing the first identifier to the second data buffer, wherein, when writing the second identifier to the second data buffer, keeping the accumulated time duration constant or decreasing the accumulated time duration by one read cycle comprises: when writing the second identifier to the second data buffer, the accumulated time duration is kept unchanged or reduced by one read cycle based on whether the second data buffer is full, and whether the data that was written first therein when full was the first identifier before writing the second identifier to the second data buffer, wherein the second data buffer is a first-in-first-out data buffer.
According to another exemplary embodiment of the present invention, there is provided a programmable logic controller PLC for online identifying a high frequency vibration abnormality of a wind turbine, the PLC including: the data reading unit periodically reads real-time vibration data of the wind turbine generator; the first data analysis unit is used for performing first data analysis on the read vibration data through the first data buffer area; a second data analysis unit performing a second data analysis on the read vibration data through a second data buffer; and the abnormity determining unit is used for identifying the high-frequency vibration abnormity of the wind turbine generator according to the analysis results of the first data analysis and the second data analysis, wherein a first data buffer area and a second data buffer area are established in the PLC.
Optionally, the first data analysis unit performs first data analysis on the vibration data in the current time period through the first data buffer area based on whether the vibration data read in each reading cycle in the current time period with a preset length exceeds a preset vibration warning value, and the second data analysis unit performs second data analysis on the vibration data in the current time period through the second data buffer area based on whether the vibration data in the current time period exceeds the vibration warning value.
Optionally, the first data analysis unit counts the peak accumulated quantity of the vibration data exceeding the vibration early warning value in the current time period through the first data buffer area.
Optionally, the second data analysis unit counts an accumulated time length that the vibration data exceeds the vibration warning value in the current time period through the second data buffer.
Optionally, the size of the first data buffer and/or the second data buffer is determined based on the read cycle of the vibration data and the preset length of the current time period.
Optionally, when the accumulated number of wave crests in the current time period exceeds a preset accumulated number, the abnormality determining unit determines that the high-frequency vibration abnormality exists in the wind turbine generator in the current time period; or when the accumulated number of wave crests in the current time period exceeds a preset accumulated number and the accumulated duration exceeds a preset duration, the abnormity determining unit determines that high-frequency vibration abnormity exists in the wind turbine generator in the current time period.
Optionally, the first data analysis unit comprises: the first determining unit is used for determining whether the vibration data read in the current reading period exceeds the vibration early warning value and the vibration data read in the previous reading period does not exceed the vibration early warning value; the first writing unit writes the first identifier into the first data buffer area when the vibration data read in the current reading period exceeds the vibration early warning value and the vibration data read in the previous reading period does not exceed the vibration early warning value; otherwise, writing the second identifier into the first data buffer; the quantity counting unit adds 1 to the peak accumulated quantity or keeps the peak accumulated quantity unchanged when the first identifier is written into the first data buffer area; and when the second identifier is written into the first data buffer area, subtracting 1 from the peak accumulation number or keeping the peak accumulation number unchanged, wherein the initial value of the peak accumulation number is 0.
Alternatively, when the first identifier is written into the first data buffer, the number counting unit adds 1 to the peak cumulative number or keeps the peak cumulative number constant based on whether the first data buffer is full, and whether the data written first therein when full is the first identifier before the first identifier is written into the first data buffer, and when the second identifier is written into the first data buffer, the number counting unit subtracts 1 from the peak cumulative number or keeps the peak cumulative number constant based on whether the first data buffer is full, and whether the data written first therein when full is the first identifier before the second identifier is written into the first data buffer, wherein the first data buffer is a first-in first-out data buffer.
Optionally, the second data analysis unit comprises: the second determining unit is used for determining whether the vibration data read in the current reading period exceeds a vibration early warning value or not; the second writing unit writes the first identifier into a second data buffer area when the vibration data read in the current reading period exceeds the vibration early warning value; otherwise, writing the second identifier into the second data buffer; the accumulated time counting unit is used for increasing the accumulated time by one reading period or keeping the accumulated time unchanged when the first identifier is written into the second data buffer area; and when writing a second identifier into a second data buffer, keeping the accumulated time length unchanged or reducing the accumulated time length by one reading period, wherein the initial value of the accumulated time length is 0.
Optionally, when writing the first identifier into the second data buffer, the accumulated time statistics unit increases the accumulated time by one read cycle or keeps the accumulated time constant based on whether the second data buffer is full and the data written first therein when full is the first identifier before writing the first identifier into the second data buffer, and when writing the second identifier into the second data buffer, the accumulated time statistics unit keeps the accumulated time constant or decreases the accumulated time by one read cycle based on whether the second data buffer is full and the data written first therein when full is the first identifier before writing the second identifier into the second data buffer, wherein the second data buffer is a first-in first-out data buffer.
According to another exemplary embodiment of the present invention, a computer-readable storage medium is provided, in which a computer program is stored, which, when being executed by a processor, implements the PLC-based online high-frequency vibration abnormality identification method for a wind turbine generator set as described above.
According to another exemplary embodiment of the present invention, there is provided a programmable logic controller, PLC, including: a processor; and the memory stores a computer program, and when the computer program is executed by the processor, the method for identifying the high-frequency vibration abnormity of the wind turbine generator on line based on the PLC is realized.
According to the method for identifying the high-frequency vibration abnormity of the wind turbine generator on line based on the programmable logic controller and the programmable logic controller, whether the high-frequency vibration components (such as fundamental wave frequency doubling vibration of a generator, high-order vibration of a stator of the generator and the like) of the wind turbine generator are abnormal can be accurately identified on line in real time through the PLC, and powerful support is provided for guaranteeing safe and stable operation of the wind turbine generator.
Additional aspects and/or advantages of the present general inventive concept will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the general inventive concept.
Drawings
The above and other objects and features of exemplary embodiments of the present invention will become more apparent from the following description taken in conjunction with the accompanying drawings which illustrate exemplary embodiments, wherein:
FIG. 1 illustrates a flowchart of a method for online PLC-based identification of a dither anomaly of a wind turbine in accordance with an exemplary embodiment of the present invention;
fig. 2 and 4 are flowcharts illustrating a method of counting a peak accumulation amount of vibration data exceeding a vibration alerting value for a current time period through a first data buffer according to an exemplary embodiment of the present invention;
fig. 3 and 5 are flowcharts illustrating a method for counting an accumulated time period in which vibration data exceeds a vibration warning value in a current time period through a second data buffer according to an exemplary embodiment of the present invention;
FIG. 6 illustrates a block diagram of a programmable logic controller that identifies dither anomalies of a wind turbine on-line in accordance with an exemplary embodiment of the present invention;
fig. 7 illustrates a block diagram of a first data analysis unit according to an exemplary embodiment of the present invention;
fig. 8 illustrates a block diagram of a second data analysis unit according to an exemplary embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the like elements throughout. The embodiments are described below in order to explain the present invention by referring to the figures.
Fig. 1 illustrates a flowchart of a method for identifying a dither abnormality of a wind turbine on-line based on a PLC according to an exemplary embodiment of the present invention, that is, the method is performed by a PLC.
Referring to fig. 1, in step S10, real-time vibration data of the wind turbine is periodically read.
As an example, vibration data of a wind turbine may be collected in real-time by a sensor and periodically received from the sensor.
The vibration data of the wind turbine generator is data capable of indicating a vibration condition (for example, vibration amplitude) of the wind turbine generator. As an example, the vibration data of the wind turbine may comprise at least one of: acceleration data of the nacelle in a given direction, displacement data of the nacelle in a given direction, velocity data of the nacelle in a given direction. For example, the designated direction may be an axial direction of the nacelle and/or a lateral direction of the nacelle.
In step S20, a first data analysis is performed on the read vibration data through the first data buffer.
As an example, the first data analysis may be performed on the vibration data in the current time period through the first data buffer based on whether the vibration data read in each reading cycle in the current time period of a preset length exceeds a preset vibration warning value. The current time period with the preset length is the time period with the preset length and taking the current time point as an end point.
As an example, the peak accumulation amount of the vibration data exceeding the vibration warning value in the current time period may be counted by the first data buffer. The accumulated number of peaks is: and the total number of peaks in a time-varying curve of all vibration data exceeding the vibration early warning value in the current time period.
Specifically, the vibration data can indicate the vibration amplitude of the wind turbine generator, and when the vibration data at a certain time point is greater than a preset vibration early warning value, the vibration at the time point can be proved to be severe; the peak accumulation number of the vibration data of all time points when the vibration data exceeds the vibration early warning value in a period of time can reflect the oscillation process of the violent vibration and the frequency of the violent vibration in the period of time.
Various suitable ways may be used to count the peak accumulation amount of the vibration data exceeding the vibration warning value in the current time period through the first data buffer, and an exemplary embodiment of step S20 will be described below with reference to fig. 2 and 4.
In step S30, a second data analysis is performed on the read vibration data through a second data buffer. Wherein a first data buffer and a second data buffer are established in the PLC.
As an example, the second data analysis may be performed on the vibration data in the current time period through the second data buffer based on whether the vibration data in the current time period exceeds the vibration warning value.
As an example, the accumulated time (i.e., the total time) during which the vibration data exceeds the vibration warning value in the current time period may be counted by the second data buffer.
As an example, the size of the first data buffer and/or the second data buffer may be determined based on the read cycle of the vibration data and the preset length of the current time period.
In addition, it should be understood that the first data analysis and the second data analysis may be other types of data analysis in which the analysis result can be used to determine whether the high-frequency vibration abnormality exists.
It should be understood that a corresponding vibration warning value may be set separately for each type of vibration data.
Various suitable ways may be used to count the accumulated time period that the vibration data exceeds the vibration warning value in the current time period through the second data buffer, and an exemplary embodiment of step S30 will be described below with reference to fig. 3 and 5.
In step S40, a high-frequency vibration abnormality of the wind turbine is identified according to the analysis results of the first data analysis and the second data analysis.
By way of example, the high frequency vibrations may include, but are not limited to, the following vibration types: the generator fundamental wave double frequency vibration and the generator stator high-order vibration.
As an example, when the high-frequency vibration of the wind turbine is severe (for example, the vibration amplitude is too large, the vibration acceleration is too large, and the vibration speed is too large), it may be considered that the high-frequency vibration of the wind turbine is abnormal, and therefore, according to the exemplary embodiment of the present invention, when the frequency of the severe vibration of the wind turbine is high, it may be considered that the high-frequency vibration of the wind turbine is abnormal. Or, when the frequency of the violent vibration of the wind turbine generator is high and the duration of the violent vibration is long, it can be considered that the high-frequency vibration abnormality exists in the wind turbine generator.
Accordingly, as an example, it may be determined that the wind turbine generator has the high-frequency vibration abnormality in the current time period when the peak accumulated amount of the current time period exceeds the preset accumulated amount.
As another example, it may be determined that the wind turbine generator has the high-frequency vibration abnormality in the current time period when the accumulated number of peaks in the current time period exceeds the preset accumulated number and the accumulated duration exceeds the preset duration.
It should be understood that whether the wind turbine has the high-frequency vibration abnormality in the current time period may also be determined according to the analysis results of the first data analysis and the second data analysis in other suitable manners.
As an example, the reading period of the vibration data may be a task execution period of the PLC. The task execution cycle can be understood as: the preset series of tasks are executed once every task execution period, namely, the series of tasks are executed repeatedly periodically. The series of tasks may include performing the method for identifying the high-frequency vibration abnormality of the wind turbine generator on line according to the exemplary embodiment of the present invention, and in addition to performing the method, other tasks may be performed, for example, a pitch control task, and the like.
In the prior art, generally, off-line spectrum analysis needs to be performed on a vibration signal, then a high-frequency component is identified based on a spectrum analysis result, and then whether the identified high-frequency component is abnormal or not is judged, so that whether the high-frequency vibration abnormality exists in the wind turbine generator or not is judged. According to the method for identifying the abnormal high-frequency vibration of the wind turbine generator on line based on the PLC, each high-frequency vibration component (for example, high-frequency vibration components such as fundamental frequency doubling vibration of a generator, high-order vibration of a generator stator and the like) and whether the high-frequency vibration component is abnormal do not need to be specifically identified, and only whether the dominant high-frequency vibration is abnormal or not needs to be qualitatively identified, so that whether the high-frequency vibration of the wind turbine generator in the current time period is abnormal or not can be quickly and accurately determined without carrying out a large number of mathematical operations (for example, FFT, spectrum analysis and the like), online real-time execution of the PLC is facilitated, the task execution period of the PLC and the real-time performance of other tasks are not influenced, and support is provided for processing the abnormal high-frequency vibration situation as soon as possible to ensure stable and safe operation of the wind turbine generator.
Fig. 2 is a flowchart illustrating a method of counting a peak accumulation amount of vibration data exceeding a vibration warning value for a current time period through a first data buffer according to an exemplary embodiment of the present invention.
Referring to fig. 2, in step S101, it is determined whether the vibration data read in the current reading period exceeds the vibration warning value and the vibration data read in the previous reading period does not exceed the vibration warning value.
When it is determined in step S101 that the vibration data read in the current reading period exceeds the vibration warning value and the vibration data read in the previous reading period does not exceed the vibration warning value, step S102 is performed to write the first identifier into the first data buffer; otherwise, step S103 is executed to write the second identifier into the first data buffer.
As an example, the first data buffer may be a first-in-first-out (FIFO) data buffer. That is, the data written into the first data buffer is deleted first, for example, when the first data buffer is full before the identifier is written into the first data buffer this time, the identifier written into the first data buffer first may be deleted, and then the identifier may be written into the current time.
As an example, the length of the first data buffer may be determined based on the preset length and a read period of the vibration data. For example, if the preset length is 60s and the task execution period (i.e., the reading period of the vibration data) of the PLC is 10ms, the length of the first data buffer may be 6000.
In step S104, when the first identifier is written into the first data buffer, the peak accumulation amount is added by 1 or kept unchanged. Wherein, the initial value of the peak accumulation number is 0.
As an example, when writing the first identifier to the first data buffer, the peak running total may be incremented by 1 or left unchanged based on whether the first data buffer is full, when full, the data it was first written to is the first identifier before writing the first identifier to the first data buffer.
As an example, in the case where the first data buffer is not full before the identifier is written in the first data buffer (i.e., before step S102 and step S103), when the first identifier is written in the first data buffer, 1 is added to the peak cumulative number; keeping the peak accumulated number unchanged when the first identifier is written into the first data buffer in the case that the first data buffer is full before the identifier is written into the first data buffer and the data written first therein is the first identifier; in the case where the first data buffer is full before the first identifier is written into the first data buffer and the data written first therein is the second identifier, the cumulative number of peaks is added by 1 when the first identifier is written into the first data buffer.
In step S105, when the second identifier is written into the first data buffer, the peak accumulation amount is decremented by 1 or kept unchanged.
As an example, when writing the second identifier to the first data buffer, the peak accumulation amount may be decremented by 1 or kept constant based on whether the first data buffer is full, and whether the data first written therein when full is the first identifier before writing the second identifier to the first data buffer.
As an example, in the case where the first data buffer is not full before writing the identifier into the first data buffer, the peak cumulative number is kept unchanged when writing the second identifier into the first data buffer; when the first data buffer is full before the identifier is written into the first data buffer and the data written first in the first data buffer is the first identifier, the accumulated number of the wave peaks is reduced by 1 when the second identifier is written into the first data buffer; in the case where the first data buffer is full before the first identifier is written into the first data buffer and the data written first therein is the second identifier, the peak cumulative amount is kept constant when the second identifier is written into the first data buffer.
Fig. 3 is a flowchart illustrating a method for counting an accumulated time period in which vibration data exceeds a vibration warning value in a current time period through a second data buffer according to an exemplary embodiment of the present invention.
Referring to fig. 3, in step S106, it is determined whether the vibration data read in the current read cycle exceeds a vibration warning value.
When it is determined in step S106 that the vibration data read in the current reading period exceeds the vibration warning value, performing step S107, and writing the first identifier into the second data buffer; otherwise, step S108 is executed to write the second identifier into the second data buffer.
As an example, the second data buffer may be a first-in-first-out (FIFO) data buffer.
As an example, the length of the second data buffer may be determined based on the preset length and the read period of the vibration data. For example, if the preset length is 60s and the task execution period (i.e., the reading period of the vibration data) of the PLC is 10ms, the length of the second data buffer may be 6000.
In step S109, when the first identifier is written into the second data buffer, the accumulated time length is increased by one reading period or kept unchanged. Wherein the initial value of the accumulated time length is 0.
As an example, when writing the first identifier to the second data buffer, the accumulated time may be increased by one read cycle or left unchanged based on whether the second data buffer is full, when full, the data that was first written therein was the first identifier before writing the first identifier to the second data buffer.
As an example, in the case where the second data buffer is not full before the identifier is written into the second data buffer (i.e., before step S107 and step S108), the accumulated time length is increased by one read cycle when the first identifier is written into the second data buffer; in the case that the second data buffer is full before the identifier is written into the second data buffer and the data written first in the second data buffer is the first identifier, keeping the accumulated time length unchanged when the first identifier is written into the second data buffer; in the case where the second data buffer is full before the first identifier is written into the second data buffer and the data written first therein is the second identifier, the accumulated time period is increased by one read cycle when the first identifier is written into the second data buffer.
In step S110, when writing the second identifier into the second data buffer, the accumulated duration is kept unchanged or reduced by one read cycle.
As an example, when writing the second identifier to the second data buffer, the accumulated time duration may be kept constant or decreased by one read cycle based on whether the second data buffer is full before writing the second identifier to the second data buffer, whether the data first written to it when full is the first identifier.
As an example, in the case where the second data buffer is not full before writing the identifier into the second data buffer, the accumulated time length is kept unchanged when writing the second identifier into the second data buffer; in the case where the second data buffer is full before writing the identifier into the second data buffer and the data written first therein is the first identifier, decreasing the accumulated time length by one read cycle when writing the second identifier into the second data buffer; in the case where the second data buffer is full before the first identifier is written into the second data buffer and the data written first therein is the second identifier, the accumulated time period is kept unchanged when the second identifier is written into the second data buffer.
Fig. 4 is a flowchart illustrating a method of counting a peak accumulation amount of vibration data exceeding a vibration warning value for a current time period through a first data buffer according to an exemplary embodiment of the present invention.
Referring to fig. 4, in step S201, it is determined whether the vibration data read in the current reading period exceeds the vibration warning value and the vibration data read in the previous reading period does not exceed the vibration warning value.
In step S202, it is determined whether the first data buffer is full.
In step S203, when the first data buffer is not full, the vibration data read in the current reading period exceeds the vibration warning value, and the vibration data read in the previous reading period does not exceed the vibration warning value, the first identifier is written in the first data buffer, and the cumulative number of peaks is added by 1.
In step S204, when the first data buffer is not full and the vibration data read in the current reading cycle does not exceed the vibration warning value, or when the first data buffer is not full, the vibration data read in the current reading cycle exceeds the vibration warning value and the vibration data read in the previous reading cycle also exceeds the vibration warning value, the second identifier is written in the first data buffer, and the accumulated number of peaks is kept unchanged.
When it is determined in step S202 that the first data buffer is full, step S205 is performed to determine whether the data written first in the current first data buffer is the first identifier.
In step S206, when the vibration data read in the current reading cycle exceeds the vibration warning value, the vibration data read in the previous reading cycle does not exceed the vibration warning value, and the data written first in the current first data buffer is the first identifier, the first identifier is written in the first data buffer, and the accumulated number of peaks is kept unchanged.
In step S207, when the vibration data read in the current reading cycle exceeds the vibration warning value, the vibration data read in the previous reading cycle does not exceed the vibration warning value, and the data written first in the current first data buffer area is the second identifier, the first identifier is written in the first data buffer area, and the cumulative number of peaks is increased by 1.
In step S208, when the vibration data read in the current reading cycle does not exceed the vibration warning value and the data written first in the current first data buffer is the first identifier; or when the vibration data read in the current reading period exceeds the vibration early warning value, the vibration data read in the previous reading period also exceeds the vibration early warning value, and the data written in the first data buffer area at present is the first identifier, writing the second identifier into the first data buffer area, and subtracting 1 from the peak accumulated quantity.
In step S209, when the vibration data read in the current reading cycle does not exceed the vibration warning value and the current data written first in the first data buffer is the second identifier; or when the vibration data read in the current reading period exceeds the vibration early warning value, the vibration data read in the previous reading period also exceeds the vibration early warning value, and the data written in the first data buffer area at present is the second identifier, writing the second identifier into the first data buffer area, and keeping the peak accumulation number unchanged.
Fig. 5 is a flowchart illustrating a method for counting an accumulated time period in which vibration data exceeds a vibration warning value in a current time period through a second data buffer according to an exemplary embodiment of the present invention.
Referring to fig. 5, in step S210, it is determined whether the vibration data read in the current read cycle exceeds a vibration warning value.
In step S211, it is determined whether the second data buffer is full.
In step S212, when the second data buffer is not full and the vibration data read in the current read cycle exceeds the vibration warning value, the first identifier is written into the second data buffer, and the accumulated time length is increased by one read cycle.
In step S213, when the second data buffer is not full and the vibration data read in the current reading period does not exceed the vibration warning value, the second identifier is written into the second data buffer, and the accumulated time duration is kept unchanged.
When it is determined in step S211 that the second data buffer is full, step S214 is performed to determine whether the data written first in the current second data buffer is the first identifier.
In step S215, when the vibration data read in the current reading cycle exceeds the vibration warning value and the current data written first in the second data buffer is the first identifier, writing the first identifier into the second data buffer and keeping the accumulated time length unchanged.
In step S216, when the vibration data read in the current reading period exceeds the vibration warning value and the data written first in the current second data buffer is the second identifier, the first identifier is written in the second data buffer, and the accumulated time length is increased by one reading period.
In step S217, when the vibration data read in the current read cycle does not exceed the vibration warning value and the data written first in the current second data buffer is the first identifier, writing the second identifier in the second data buffer, and decreasing the accumulated duration by one read cycle.
In step S218, when the vibration data read in the current reading cycle does not exceed the vibration warning value and the current data written first in the second data buffer is the second identifier, writing the second identifier into the second data buffer and keeping the accumulated time length unchanged.
According to the exemplary embodiment of the invention, two data buffers are established, one is used for quickly calculating the peak accumulation amount of the vibration data at the time point when the vibration data exceeds the vibration early warning value in the current time period, and the other is used for quickly calculating the accumulation duration when the vibration data exceeds the vibration early warning value in the current time period. On one hand, the accumulated number of wave crests and the accumulated time length can be updated only based on the identifier which is written in the current data buffer area firstly and the identifier which is written in at the time, and the accumulated number of the wave crests and the accumulated time length do not need to be counted again each time based on all data in the data buffer area, so that the calculation amount of the data can be effectively reduced, less calculation resources are occupied, and the calculation is quick; on the other hand, the accuracy of identifying the high-frequency vibration abnormity can be improved by simultaneously counting the peak accumulated number of the vibration data exceeding the vibration early warning value and the accumulated time exceeding the vibration early warning value, so that the problem that an error control instruction is sent out due to an error identification result, and further loss is caused is avoided.
FIG. 6 illustrates a block diagram of a programmable logic controller that identifies a dithering anomaly of a wind turbine on-line, according to an exemplary embodiment of the present invention.
As shown in fig. 6, the programmable logic controller for online identification of a dither abnormality of a wind turbine according to an exemplary embodiment of the present invention includes: a data reading unit 10, a first data analysis unit 20, a second data analysis unit 30, an abnormality determination unit 40.
Specifically, the data reading unit 10 is used for periodically reading real-time vibration data of the wind turbine.
As an example, vibration data of the wind turbine generator set may be collected in real time by a sensor, and the data reading unit 10 may periodically receive the vibration data collected in real time from the sensor.
The vibration data of the wind turbine generator is data capable of indicating a vibration condition (for example, vibration amplitude) of the wind turbine generator. As an example, the vibration data of the wind turbine may comprise at least one of: acceleration data of the nacelle in a given direction, displacement data of the nacelle in a given direction, velocity data of the nacelle in a given direction. For example, the designated direction may be an axial direction of the nacelle and/or a lateral direction of the nacelle.
The first data analysis unit 20 is configured to perform a first data analysis on the read vibration data through a first data buffer.
As an example, the first data analysis unit 20 may perform the first data analysis on the vibration data in the current time period through the first data buffer based on whether the vibration data read in each reading cycle in the current time period of a preset length exceeds a preset vibration warning value. The current time period of the preset length is the time period with the current time point as an end point and the preset length.
As an example, the first data analysis unit 20 may count the peak accumulated number of the vibration data exceeding the vibration warning value in the current period through the first data buffer. The accumulated number of peaks is: and the total number of peaks in the time-varying curve of all vibration data exceeding the vibration early warning value in the current time period.
Specifically, the vibration data can indicate the vibration amplitude of the wind turbine generator, and when the vibration data at a certain time point is greater than a preset vibration early warning value, the vibration at the time point can be proved to be severe; the peak accumulation number of the vibration data of all time points when the vibration data exceeds the vibration early warning value in a period of time can reflect the oscillation process of the violent vibration and the frequency of the violent vibration in the period of time.
The second data analysis unit 30 is used for performing a second data analysis on the read vibration data through a second data buffer. Wherein a first data buffer and a second data buffer are established in the PLC.
As an example, the second data analysis unit 30 may perform the second data analysis on the vibration data in the current period through the second data buffer based on whether the vibration data in the current period exceeds the vibration warning value.
As an example, the second data analysis unit 30 may count an accumulated time period (i.e., a total time period) in which the vibration data exceeds the vibration warning value in the current time period through the second data buffer.
As an example, the size of the first data buffer and/or the second data buffer may be determined based on the read cycle of the vibration data and the preset length of the current time period.
In addition, it should be understood that the first data analysis and the second data analysis may be other types of data analysis in which the analysis result can be used to determine whether the high-frequency vibration abnormality exists.
It should be understood that a corresponding vibration warning value may be set separately for each type of vibration data.
The first data analysis unit 20 may count the peak accumulated amount of the vibration data exceeding the vibration warning value in the current period of time through the first data buffer in various suitable manners, and the second data analysis unit 30 may count the accumulated time length of the vibration data exceeding the vibration warning value in the current period of time through the second data buffer in various suitable manners, and exemplary structures of the first data analysis unit 20 and the second data analysis unit 30 will be described below with reference to fig. 7 and 8.
The abnormity determining unit 40 is used for identifying the high-frequency vibration abnormity of the wind turbine generator according to the analysis results of the first data analysis and the second data analysis.
As an example, the abnormality determining unit 40 may determine that the wind turbine generator has a high-frequency vibration abnormality in the current time period when the peak accumulated amount of the current time period exceeds a preset accumulated amount.
As another example, the abnormality determining unit 40 may determine that the wind turbine generator has a high-frequency vibration abnormality in the current time period when the accumulated number of peaks of the current time period exceeds a preset accumulated number and the accumulated time period exceeds a preset time period.
As an example, the reading period of the vibration data may be a task execution period of the PLC. The task execution cycle can be understood as: the preset series of tasks are executed once every task execution period, namely, the series of tasks are executed repeatedly and periodically. The series of tasks may include performing the method for identifying the high-frequency vibration abnormality of the wind turbine generator on line according to the exemplary embodiment of the present invention, and in addition to performing the method, other tasks may be performed, for example, a pitch control task, and the like.
Fig. 7 illustrates a block diagram of the first data analysis unit 20 according to an exemplary embodiment of the present invention.
As shown in fig. 7, the first data analysis unit 20 according to an exemplary embodiment of the present invention includes: a first determination unit 201, a first writing unit 202, a number statistics unit 203.
Specifically, the first determination unit 201 is configured to determine whether the vibration data read in the current reading period exceeds the vibration warning value and the vibration data read in the previous reading period does not exceed the vibration warning value.
The first writing unit 202 is configured to write a first identifier into a first data buffer when the vibration data read in the current reading period exceeds the vibration warning value and the vibration data read in the previous reading period does not exceed the vibration warning value; otherwise, the second identifier is written to the first data buffer.
As an example, the first data buffer may be a first-in-first-out data buffer.
As another example, the length of the first data buffer may be determined based on the preset length and a read period of the vibration data.
The quantity counting unit 203 is used for adding 1 to the peak accumulated quantity or keeping the peak accumulated quantity unchanged when the first identifier is written into the first data buffer area; and when the second identifier is written into the first data buffer area, subtracting 1 from the peak accumulation number or keeping the peak accumulation number unchanged, wherein the initial value of the peak accumulation number is 0.
As an example, when writing the first identifier into the first data buffer, the number statistics unit 203 may add 1 to the peak cumulative number or keep the peak cumulative number unchanged based on whether the first data buffer is full before writing the first identifier into the first data buffer, whether the data first written therein is the first identifier when full; when writing the second identifier into the first data buffer, the quantity counting unit 203 may subtract 1 from the peak cumulative quantity or keep the peak cumulative quantity unchanged based on whether the first data buffer is full before writing the second identifier into the first data buffer, whether the data written first therein is the first identifier when full.
Fig. 8 illustrates a block diagram of the second data analysis unit 30 according to another exemplary embodiment of the present invention.
As shown in fig. 8, the second data analysis unit 30 according to an exemplary embodiment of the present invention includes: a second determining unit 301, a second writing unit 302, and an accumulated time counting unit 303.
Specifically, the second determination unit 301 is configured to determine whether the vibration data read in the current reading cycle exceeds the vibration warning value.
The second writing unit 302 is configured to write the first identifier into the second data buffer when the vibration data read in the current read cycle exceeds the vibration warning value; otherwise, the second identifier is written to the second data buffer.
As an example, the second data buffer may be a first-in-first-out data buffer.
As another example, the length of the second data buffer may be determined based on the preset length and a read period of the vibration data.
The accumulated time counting unit 303 is configured to increase the accumulated time by one reading period or keep the accumulated time unchanged when the first identifier is written into the second data buffer; and when writing a second identifier into a second data buffer, keeping the accumulated time length unchanged or reducing the accumulated time length by one reading period, wherein the initial value of the accumulated time length is 0.
As an example, when writing the first identifier to the second data buffer, the accumulated time counting unit 303 may increase the accumulated time by one read cycle or keep the accumulated time constant based on whether the second data buffer is full, and whether the data first written therein is the first identifier when full before writing the first identifier to the second data buffer; when writing the second identifier into the second data buffer, the accumulated time statistics unit 303 may keep the accumulated time constant or decrease the accumulated time by one read cycle based on whether the second data buffer is full, and whether the data first written therein is the first identifier when full before writing the second identifier into the second data buffer.
It should be understood that the specific implementation manner of the programmable logic controller for identifying the high-frequency vibration abnormality of the wind turbine generator on line according to the exemplary embodiment of the present invention may be implemented with reference to the related specific implementation manners described in conjunction with fig. 1 to 5, and will not be described herein again.
It should be appreciated that the various units in the programmable logic controller for online identification of high-frequency vibration anomalies of a wind turbine according to an exemplary embodiment of the present invention may be implemented as hardware components and/or software components.
Exemplary embodiments of the present invention provide a computer-readable storage medium storing a computer program, which when executed by a processor implements the PLC-based online high-frequency vibration abnormality identification method for a wind turbine generator set according to the above exemplary embodiments. The computer readable storage medium is any data storage device that can store data which can be read by a computer system. Examples of computer-readable storage media include: read-only memory, random access memory, compact disc read-only memory, magnetic tape, floppy disk, optical data storage device, and carrier wave (such as data transmission through the internet via a wired or wireless transmission path).
A programmable logic controller according to an exemplary embodiment of the present invention includes: a processor (not shown) and a memory (not shown), wherein the memory stores a computer program, and when the computer program is executed by the processor, the method for identifying the high-frequency vibration abnormality of the wind turbine generator on line based on the PLC as described in the above exemplary embodiment is implemented.
Although a few exemplary embodiments of the present invention have been shown and described, it would be appreciated by those skilled in the art that changes may be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the claims and their equivalents.

Claims (16)

1. A method for identifying high-frequency vibration abnormity of a wind turbine generator on line by a Programmable Logic Controller (PLC) is characterized by comprising the following steps:
periodically reading real-time vibration data of the wind turbine generator;
counting the peak accumulated quantity of the vibration data exceeding the vibration early warning value in the current time period through a first data buffer area based on the condition that whether the vibration data read in each reading period in the current time period with the preset length exceeds the preset vibration early warning value or not;
counting the accumulated time length of the vibration data exceeding the vibration early warning value in the current time period through a second data buffer area based on the condition whether the vibration data in the current time period exceeds the vibration early warning value;
identifying the high-frequency vibration abnormity of the wind turbine generator according to the accumulated number of the wave crests and the accumulated duration,
wherein a first data buffer and a second data buffer are established in the PLC.
2. The method of claim 1,
the size of the first data buffer and/or the second data buffer is determined based on the read cycle of the vibration data and the preset length of the current time period.
3. The method of claim 1, wherein the step of identifying the high frequency vibration anomaly of the wind turbine generator based on the cumulative number of peaks and the cumulative duration comprises:
when the accumulated number of the wave crests exceeds a preset accumulated number, determining that high-frequency vibration abnormity exists in the wind turbine generator in the current time period;
or when the accumulated number of the wave crests exceeds a preset accumulated number and the accumulated duration exceeds a preset duration, determining that the high-frequency vibration abnormality exists in the wind turbine generator in the current time period.
4. The method of claim 1, wherein the step of counting, via the first data buffer, the number of peaks accumulated in the vibration data exceeding the vibration warning value in the current time period comprises:
determining whether the vibration data read in the current reading period exceeds the vibration early warning value and the vibration data read in the previous reading period does not exceed the vibration early warning value;
when the vibration data read in the current reading period exceeds the vibration early warning value and the vibration data read in the previous reading period does not exceed the vibration early warning value, writing the first identifier into a first data buffer area; otherwise, writing the second identifier into the first data buffer;
adding 1 to the peak accumulated quantity or keeping the peak accumulated quantity unchanged when the first identifier is written into the first data buffer area;
when writing the second identifier into the first data buffer, either reducing the peak accumulation number by 1 or keeping the peak accumulation number unchanged,
wherein, the initial value of the peak accumulation number is 0.
5. The method of claim 4, wherein the step of adding 1 to the accumulated number of peaks or leaving the accumulated number of peaks unchanged when writing the first identifier to the first data buffer comprises: when writing the first tag into the first data buffer, adding 1 to the peak cumulative amount or keeping the peak cumulative amount constant based on whether the first data buffer is full before writing the first tag into the first data buffer, whether the data written first therein when full is the first tag,
wherein, when writing the second identifier into the first data buffer, the step of subtracting 1 from the peak accumulation number or keeping the peak accumulation number unchanged comprises: when writing the second identifier into the first data buffer, subtracting 1 from the peak accumulation amount or keeping the peak accumulation amount constant based on whether the first data buffer is full, and the data written first therein when full is the first identifier before writing the second identifier into the first data buffer,
the first data buffer is a first-in first-out data buffer.
6. The method of claim 1, wherein the step of counting the accumulated time period that the vibration data exceeds the vibration warning value in the current time period through the second data buffer area comprises:
determining whether the vibration data read in the current reading period exceeds a vibration early warning value;
when the vibration data read in the current reading period exceeds the vibration early warning value, writing the first identifier into a second data buffer area; otherwise, writing the second identifier into the second data buffer;
when writing the first identifier into the second data buffer, increasing the accumulated time length by one reading period or keeping the accumulated time length unchanged;
maintaining the accumulated time duration unchanged or decreasing the accumulated time duration by one read cycle when writing the second identifier to the second data buffer,
wherein the initial value of the accumulated time length is 0.
7. The method of claim 6, wherein the step of increasing the accumulated time duration by one read cycle or keeping the accumulated time duration constant while writing the first identifier to the second data buffer comprises: when writing the first tag to the second data buffer, increasing the accumulated length of time by one read cycle or keeping the accumulated length of time constant based on whether the second data buffer is full before writing the first tag to the second data buffer, whether the data first written to the second data buffer when full is the first tag,
wherein, when writing the second identifier into the second data buffer, the step of keeping the accumulated duration unchanged or reducing the accumulated duration by one read cycle comprises: when writing the second identifier to the second data buffer, keeping the accumulated duration unchanged or decreasing the accumulated duration by one read cycle based on whether the second data buffer is full, and the data that was first written therein when full was the first identifier before writing the second identifier to the second data buffer,
the second data buffer is a first-in first-out data buffer.
8. The utility model provides an unusual programmable logic controller PLC of high-frequency vibration of on-line identification wind turbine generator system which characterized in that, PLC includes:
the data reading unit periodically reads real-time vibration data of the wind turbine generator;
the first data analysis unit is used for counting the peak accumulated quantity of the vibration data exceeding the vibration early warning value in the current time period through the first data buffer area based on the condition that whether the vibration data read in each reading period in the current time period with the preset length exceeds the preset vibration early warning value or not;
the second data analysis unit is used for counting the accumulated time length of the vibration data exceeding the vibration early warning value in the current time period through a second data buffer area on the basis of the condition that whether the vibration data in the current time period exceeds the vibration early warning value or not;
an abnormality determining unit for identifying the high-frequency vibration abnormality of the wind turbine generator according to the accumulated number of wave crests and the accumulated duration,
wherein a first data buffer and a second data buffer are established in the PLC.
9. The PLC of claim 8,
the size of the first data buffer and/or the second data buffer is determined based on the read cycle of the vibration data and the preset length of the current time period.
10. The PLC of claim 8,
when the accumulated number of the wave crests exceeds a preset accumulated number, determining that high-frequency vibration abnormality exists in the wind turbine generator in the current time period by an abnormality determining unit;
or when the accumulated number of wave crests exceeds a preset accumulated number and the accumulated duration exceeds a preset duration, the abnormity determining unit determines that high-frequency vibration abnormity exists in the wind turbine generator in the current time period.
11. The PLC of claim 8, wherein the first data analysis unit comprises:
the first determining unit is used for determining whether the vibration data read in the current reading period exceeds the vibration early warning value and the vibration data read in the previous reading period does not exceed the vibration early warning value;
the first writing unit writes the first identifier into the first data buffer area when the vibration data read in the current reading period exceeds the vibration early warning value and the vibration data read in the previous reading period does not exceed the vibration early warning value; otherwise, writing the second identifier into the first data buffer;
the quantity counting unit adds 1 to the peak accumulated quantity or keeps the peak accumulated quantity unchanged when the first identifier is written into the first data buffer area; when writing the second identifier into the first data buffer, either reducing the peak accumulation number by 1 or keeping the peak accumulation number unchanged,
wherein, the initial value of the peak accumulation number is 0.
12. The PLC of claim 11, wherein the quantity counting unit adds 1 to the peak cumulative quantity or keeps the peak cumulative quantity constant based on whether the first data buffer is full before writing the first identifier into the first data buffer, whether data written first therein is the first identifier when the first data buffer is full, when the first identifier is written into the first data buffer,
when writing the second identifier into the first data buffer, the quantity counting unit subtracts 1 from the peak cumulative quantity or keeps the peak cumulative quantity constant based on whether the first data buffer is full, whether the data written first therein is the first identifier when the first data buffer is full before writing the second identifier into the first data buffer,
the first data buffer is a first-in first-out data buffer.
13. The PLC of claim 8, wherein the second data analysis unit comprises:
the second determining unit is used for determining whether the vibration data read in the current reading period exceeds a vibration early warning value or not;
the second writing unit writes the first identifier into a second data buffer area when the vibration data read in the current reading period exceeds the vibration early warning value; otherwise, writing the second identifier into the second data buffer;
the accumulated time counting unit is used for increasing the accumulated time by one reading period or keeping the accumulated time unchanged when the first identifier is written into the second data buffer area; maintaining the accumulated duration unchanged or decreasing the accumulated duration by one read cycle when writing a second identifier to a second data buffer,
wherein the initial value of the accumulated time length is 0.
14. The PLC of claim 13, wherein when writing the first identifier to the second data buffer, the accumulated time statistics unit increases the accumulated time by one read cycle or keeps the accumulated time constant based on whether the second data buffer is full, and whether the data that was written first therein was the first identifier when the second data buffer was full before writing the first identifier to the second data buffer,
when writing the second identifier into the second data buffer, the accumulated time statistics unit keeps the accumulated time constant or reduces the accumulated time by one read cycle based on whether the second data buffer is full, data written first therein when full is the first identifier before writing the second identifier into the second data buffer,
the second data buffer is a first-in first-out data buffer.
15. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the method for online identification of a high-frequency vibration abnormality of a wind turbine generator by a PLC according to any one of claims 1 to 7.
16. A programmable logic controller, PLC, characterized in that the PLC comprises:
a processor;
a memory storing a computer program which, when executed by the processor, implements the method for online identification of a dither anomaly of a wind turbine by a PLC according to any one of claims 1 to 7.
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