CN116928039A - Method, device, equipment and medium for identifying vibration overrun faults of offshore wind turbine generator - Google Patents
Method, device, equipment and medium for identifying vibration overrun faults of offshore wind turbine generator Download PDFInfo
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Classifications
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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
-
- 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
- F03D7/0296—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor to prevent, counteract or reduce noise emissions
-
- 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
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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
- F03D80/00—Details, components or accessories not provided for in groups F03D1/00 - F03D17/00
Abstract
The invention relates to the technical field of electric signal processing, and discloses a method, a device, equipment and a medium for identifying a vibration overrun fault of an offshore wind turbine, wherein when an offshore wind turbine has a resonance overrun fault, fourier spectrum analysis is carried out on first vibration acceleration data before the occurrence of the vibration overrun fault, second vibration acceleration data in a vibration overrun fault stage and third vibration acceleration data in a wind turbine shutdown stage, wind turbine excitation frequency in a normal rotation stage of an impeller, wind turbine excitation frequency in the vibration overrun fault stage and natural frequency in the shutdown stage are determined, and whether the offshore wind turbine has the resonance overrun fault is determined according to a first deviation value between the wind turbine excitation frequency in the normal rotation stage of the impeller and the natural frequency, a second deviation value between the wind turbine excitation frequency with the vibration overrun fault and the natural frequency and a preset deviation value, so that the problem of resource waste and unnecessary shutdown caused by manual troubleshooting in the related technology are solved.
Description
Technical Field
The invention relates to the technical field of electric signal processing, in particular to a method, a device, equipment and a medium for identifying a vibration overrun fault of an offshore wind turbine.
Background
The offshore wind power has the advantages of high power generation amount of the fan and suitability for development, at present, the offshore wind power enters a rapid development period, but the offshore wind power is easy to be affected by the environment to generate various faults due to the special environment where the offshore wind power is located, so that the operation and maintenance work of the offshore wind power is very important.
At present, when the offshore wind turbine generator detects that the wind turbine generator has vibration overrun faults, the wind turbine generator can be controlled to stop, and then operation and maintenance staff carry out offshore wind power operation and maintenance work. When operation and maintenance personnel perform operation and maintenance work, faults possibly existing in the offshore wind turbine generator set are generally checked one by one based on past experience, and the defects of wasting human resources and consuming long time exist.
Disclosure of Invention
In view of the above, the invention provides a method, a device, equipment and a medium for identifying the vibration overrun fault of an offshore wind turbine, which are used for solving the problems of wasting human resources and consuming long time of the existing fault field arrangement method of the offshore wind turbine.
In a first aspect, the invention provides a method for identifying a vibration overrun fault of an offshore wind turbine, which comprises the following steps:
when the offshore wind turbine has a vibration overrun fault, acquiring first vibration acceleration data in a preset period of time before the offshore wind turbine has the vibration overrun fault, second vibration acceleration data in a vibration overrun fault stage and third vibration acceleration data in a wind turbine stopping stage; performing Fourier spectrum analysis on the first vibration acceleration data, the second vibration acceleration data and the third vibration acceleration data respectively to obtain a first frequency corresponding to the first vibration acceleration data, a second frequency corresponding to the second vibration acceleration data and a third frequency corresponding to the third vibration acceleration data, wherein the first frequency is a fan excitation frequency in a normal rotation stage of the impeller before the occurrence of the vibration overrun fault of the offshore wind turbine, the second frequency is a fan excitation frequency in which the vibration overrun fault of the offshore wind turbine occurs, and the third frequency is a natural frequency in a shutdown stage of the offshore wind turbine; determining a first deviation value between the first frequency and the third frequency and a second deviation value between the second frequency and the third frequency; judging whether the offshore wind turbine has resonance overrun faults or not based on the first deviation value, the second deviation value and the preset deviation value, and obtaining a fault identification result.
According to the method for identifying the vibration overrun faults of the offshore wind turbine, when the offshore wind turbine is subjected to resonance overrun faults, fourier spectrum analysis is conducted on first vibration acceleration data, second vibration acceleration data and third vibration acceleration data in a preset period before the offshore wind turbine is subjected to vibration overrun faults, so that the excitation frequency of the offshore wind turbine in a normal rotation period of the impeller before the offshore wind turbine is subjected to vibration overrun faults, the excitation frequency of the offshore wind turbine in the vibration overrun faults and the natural frequency of the offshore wind turbine in the shutdown period are obtained, whether the offshore wind turbine is subjected to resonance overrun faults is determined according to a first deviation value between the excitation frequency of the offshore wind turbine in the normal rotation period and the natural frequency, a second deviation value between the excitation frequency of the vibration overrun faults and the natural frequency and the preset deviation value, intelligent diagnosis of the offshore wind turbine vibration faults is achieved, the reason that the offshore wind turbine is subjected to vibration overrun faults can be determined through analysis on the vibration acceleration data of the offshore wind turbine, and the problem that manpower resources are wasted and time consumption is long in the related technology is solved.
In an alternative embodiment, based on the first deviation value, the second deviation value and the preset deviation value, whether the offshore wind turbine has a resonance overrun fault is judged, and after the fault identification result is obtained, the method further comprises: a fault handling scheme is determined based on the fault identification result.
According to the method provided by the alternative embodiment, the fault processing scheme is determined based on the fault recognition result, so that the efficiency of offshore wind power operation and maintenance work is improved, and the safe operation of the fan is ensured.
In an alternative embodiment, based on the first deviation value, the second deviation value and the preset deviation value, judging whether the offshore wind turbine has a resonance overrun fault, and after obtaining the fault identification result, the method further includes: when the offshore wind turbine has resonance overrun fault, determining a sweep frequency band of the offshore wind turbine blade based on the rotating speed range of the impeller of the offshore wind turbine; judging whether the third frequency falls into a sweeping frequency band; when the third frequency falls into the sweep frequency band, determining a resonance rotating speed interval corresponding to the sweep frequency band based on the third frequency; and determining whether the offshore wind turbine has self-excitation resonance faults or not based on the measured rotating speed of the impeller before the resonance rotating speed interval and the vibration overrun faults of the offshore wind turbine.
The method provided by the alternative embodiment is used for determining whether the offshore wind turbine has self-excited resonance faults or not based on the sweep frequency band and the natural frequency of the offshore wind turbine, so that the corresponding fault solution is conveniently determined based on the judgment result.
In one possible implementation manner, before the offshore wind turbine is subjected to the vibration overrun fault, the method further comprises the steps of: acquiring vibration acceleration data in an offshore wind turbine nacelle; respectively comparing the vibration acceleration data with a preset threshold value to obtain a comparison result; and judging whether the offshore wind turbine has a vibration overrun fault or not based on the comparison result.
According to the method provided by the alternative embodiment, the vibration acceleration data is compared with the preset threshold value, and whether the offshore wind turbine has the vibration overrun fault can be accurately judged based on the comparison result.
In an alternative embodiment, before the offshore wind turbine is subjected to the vibration overrun fault, the first vibration acceleration data, the second vibration acceleration data in the vibration overrun fault stage and the third vibration acceleration data in the wind turbine shutdown stage in a target period before the offshore wind turbine is subjected to the vibration overrun fault are obtained, and the method further includes: acquiring vibration acceleration data acquired by a first acceleration sensor and vibration acceleration data acquired by a second acceleration sensor; judging whether the working states of the first acceleration sensor and the second acceleration sensor are normal or not based on the vibration acceleration data acquired by the first acceleration sensor and the vibration acceleration data acquired by the second acceleration sensor; if the working states of the first acceleration sensor and the second acceleration sensor are normal, judging whether the offshore wind turbine has a vibration overrun fault or not according to vibration acceleration data acquired by the first acceleration sensor and vibration acceleration data acquired by the second acceleration sensor; and if the vibration overrun fault of the offshore wind turbine is judged, sending a shutdown control instruction to the offshore wind turbine.
The method provided by the alternative embodiment can more accurately determine whether the offshore wind turbine has resonance overrun faults, and effectively avoid the problem of wind turbine shutdown caused by abnormal working states of the vibration sensor.
In one possible implementation manner, judging whether the offshore wind turbine has a vibration overrun fault according to the vibration acceleration data acquired by the first acceleration sensor and the vibration acceleration data acquired by the second acceleration sensor includes: respectively comparing the vibration acceleration data acquired by the first acceleration sensor and the vibration acceleration data acquired by the second acceleration sensor with a preset threshold value to obtain a comparison result; and if the vibration acceleration data acquired by the first acceleration sensor is greater than a preset threshold value and/or the vibration acceleration data acquired by the second acceleration sensor is greater than the preset threshold value, judging that the offshore wind turbine has a vibration overrun fault.
The method provided by the alternative embodiment can more accurately determine whether the offshore wind turbine has resonance overrun faults.
In one possible implementation manner, when the offshore wind turbine has a vibration overrun fault, acquiring first vibration acceleration data in a preset period of time before the offshore wind turbine has the vibration overrun fault, second vibration acceleration data in a vibration overrun fault stage, and third vibration acceleration data in a wind turbine shutdown stage, including: when the offshore wind turbine has a vibration overrun fault, acquiring first initial vibration acceleration data, second initial vibration acceleration data and third initial vibration acceleration data of a wind turbine stopping stage in a preset period before the offshore wind turbine has the vibration overrun fault; and performing signal zero padding processing on the first initial vibration acceleration data, the second initial vibration acceleration data and the third initial vibration acceleration data respectively to obtain first vibration acceleration data corresponding to the first initial vibration acceleration data, second vibration acceleration data corresponding to the second initial vibration acceleration data and third vibration acceleration data corresponding to the third initial vibration acceleration data.
According to the method provided by the embodiment, the vibration acceleration data are increased, the interval of analysis frequencies is shortened, and the follow-up Fourier spectrum analysis of the vibration acceleration data is facilitated to obtain a high-precision spectrum analysis result.
In a second aspect, the invention provides a device for identifying a vibration overrun fault of an offshore wind turbine, which comprises: the first acquisition module is used for acquiring first vibration acceleration data, second vibration acceleration data and third vibration acceleration data of the offshore wind turbine in a preset period before the offshore wind turbine is subjected to the vibration overrun fault, and the third vibration acceleration data of the wind turbine in a shutdown stage when the offshore wind turbine is subjected to the vibration overrun fault; the frequency spectrum analysis module is used for carrying out Fourier frequency spectrum analysis on the first vibration acceleration data, the second vibration acceleration data and the third vibration acceleration data respectively to obtain a first frequency corresponding to the first vibration acceleration data, a second frequency corresponding to the second vibration acceleration data and a third frequency corresponding to the third vibration acceleration data, wherein the first frequency is the fan excitation frequency of the impeller in the normal rotation stage before the occurrence of the vibration overrun fault of the offshore wind turbine, the second frequency is the fan excitation frequency of the offshore wind turbine in the vibration overrun fault, and the third frequency is the natural frequency of the offshore wind turbine in the shutdown stage; a first determining module for determining a first deviation value between the first frequency and the third frequency and a second deviation value between the second frequency and the third frequency; the second determining module is used for judging whether the offshore wind turbine has resonance overrun faults or not based on the first deviation value, the second deviation value and the preset deviation value, and obtaining a fault identification result.
In one possible embodiment, the apparatus further comprises: and the third determining module is used for determining a fault processing scheme based on the fault recognition result.
In a third aspect, the present invention provides a computer device comprising: the device comprises a memory and a processor, wherein the memory and the processor are in communication connection, the memory stores computer instructions, and the processor executes the computer instructions so as to execute the method for identifying the vibration overrun faults of the offshore wind turbine generator according to the first aspect or any implementation mode corresponding to the first aspect.
In a fourth aspect, the present invention provides a computer readable storage medium, on which computer instructions are stored, the computer instructions being configured to cause a computer to execute the method for identifying a vibration overrun fault of an offshore wind turbine according to the first aspect or any one of the embodiments corresponding to the first aspect.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for identifying a vibration overrun fault of an offshore wind turbine according to an embodiment of the invention;
fig. 2A is a schematic diagram of change information of vibration acceleration with time in the Y direction in the first vibration acceleration according to an embodiment of the present invention;
FIG. 2B is a schematic diagram of Fourier spectrum analysis results of vibration acceleration in the Y direction in the first vibration acceleration according to an embodiment of the present invention;
fig. 2C is a schematic diagram of change information of vibration acceleration with time in the Y direction in the second vibration acceleration according to the embodiment of the present invention;
FIG. 2D is a schematic diagram of Fourier spectrum analysis results of vibration acceleration in the Y direction in a second vibration acceleration according to an embodiment of the present invention;
fig. 2E is a schematic diagram of change information of vibration acceleration with time in the Y direction in the third vibration acceleration according to the embodiment of the present invention;
FIG. 2F is a schematic diagram of Fourier spectrum analysis results of vibration acceleration in the Y direction in a third vibration acceleration according to an embodiment of the present invention;
fig. 2G is a schematic diagram of time-dependent information of vibration acceleration in the X direction among the first vibration accelerations according to an embodiment of the present invention;
FIG. 2H is a schematic diagram of Fourier spectrum analysis results of vibration acceleration in the X direction in the first vibration acceleration according to an embodiment of the present invention;
Fig. 2I is a schematic diagram of time-dependent information of vibration acceleration in the X direction in the second vibration acceleration according to an embodiment of the present invention;
FIG. 2J is a schematic diagram of Fourier spectrum analysis results of vibration acceleration in the X direction in the second vibration acceleration according to the embodiment of the present invention;
fig. 2K is a schematic diagram of time-dependent information of vibration acceleration in the X direction among third vibration accelerations according to an embodiment of the present invention;
FIG. 2L is a schematic diagram of Fourier spectrum analysis results of vibration acceleration in the X direction in the third vibration acceleration according to the embodiment of the present invention;
FIG. 3 is a flow chart of another method for identifying a vibration overrun fault of an offshore wind turbine according to an embodiment of the invention;
FIG. 4 is a flow chart of a method for identifying a vibration overrun fault of an offshore wind turbine according to an embodiment of the invention;
FIG. 5 is a flow chart of a method for identifying vibration overrun faults of an offshore wind turbine according to an embodiment of the present invention;
FIG. 6 is a flow chart of a method for identifying vibration overrun faults of an offshore wind turbine according to an embodiment of the present invention;
FIG. 7 is a flow chart of a method for identifying vibration overrun faults of an offshore wind turbine according to an embodiment of the present invention;
FIG. 8 is a block diagram of a device for identifying an overrun fault in vibration of an offshore wind turbine according to an embodiment of the invention;
fig. 9 is a schematic diagram of a hardware structure of a computer device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Based on the defects of wasting human resources and consuming long time existing in the prior art that faults possibly existing in the offshore wind turbine are checked one by one based on past experience, the embodiment of the invention provides a method for identifying the vibration overrun faults of the offshore wind turbine, which can be applied to any electronic equipment or processor and the like, and the fault identification result of the offshore wind turbine is determined through processing and analyzing the vibration acceleration data of the offshore wind turbine.
According to an embodiment of the present application, there is provided an embodiment of a method for identifying a vibration overrun fault of an offshore wind turbine, it being noted that the steps illustrated in the flowchart of the figures may be performed in a computer system, such as a set of computer executable instructions, and that although a logical sequence is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in a different order than that illustrated herein.
In this embodiment, a method for identifying a vibration overrun fault of an offshore wind turbine is provided, which may be used for the above electronic device, the processor, etc., fig. 1 is a flowchart of a method for identifying a vibration overrun fault of an offshore wind turbine according to an embodiment of the present application, as shown in fig. 1, where the flowchart includes the following steps:
step S101, when the offshore wind turbine is in a vibration overrun fault, acquiring first vibration acceleration data in a preset period of time before the offshore wind turbine is in the vibration overrun fault, second vibration acceleration data in a vibration overrun fault stage and third vibration acceleration data in a wind turbine stopping stage.
Illustratively, the occurrence of the vibration overrun fault of the offshore wind turbine means that when the vibration of the offshore wind turbine exceeds a preset management threshold, it can be determined that the vibration overrun fault of the offshore wind turbine occurs. The first vibration acceleration, the second vibration acceleration and the third vibration acceleration can be acquired by a vibration acceleration sensor preset in the fan; the vibration acceleration sensor can acquire vibration acceleration data of the offshore wind turbine in real time based on preset sampling, the first vibration acceleration data can be data in a preset time period before the occurrence of the vibration overrun fault, the preset time period can be any time period, the specific content of the preset time period is not limited in the embodiment of the application, the specific content of the preset time period can be determined by a person skilled in the art according to requirements, and the preset time period can comprise but is not limited to 1 minute in the embodiment of the application.
Step S102, fourier spectrum analysis is carried out on the first vibration acceleration data, the second vibration acceleration data and the third vibration acceleration data respectively to obtain a first frequency corresponding to the first vibration acceleration data, a second frequency corresponding to the second vibration acceleration data and a third frequency corresponding to the third vibration acceleration data, wherein the first frequency is the fan excitation frequency of the impeller in the normal rotation stage before the occurrence of the vibration overrun fault of the offshore wind turbine, the second frequency is the fan excitation frequency of the offshore wind turbine in the vibration overrun fault, and the third frequency is the natural frequency of the offshore wind turbine in the shutdown stage.
In the embodiment of the application, the fourier spectrum analysis is to segment the time domain vibration signal for analysis, and the frequency obtained when the power spectrum density is maximum is the main frequency in the period. The vibration acceleration sensor can collect vibration acceleration data in two directions of X (parallel to a blade wind sweeping surface) and Y (perpendicular to the blade wind sweeping surface) in a fan cabin, the change information of the vibration acceleration in the Y direction along time in the first vibration acceleration can be shown in fig. 2A, the result of Fourier spectrum analysis on the vibration acceleration data in the Y direction in the first vibration acceleration can be shown in fig. 2B, as can be seen from fig. 2A and 2B, fourier transform is carried out on time domain data in the Y direction of the vibration acceleration of the cabin in a time range of-60 s to-20 s, the time domain data is converted into a self-power spectral density amplitude-frequency relation curve, the maximum energy (amplitude) is found to be 0.53, and the vibration frequency corresponding to the maximum energy is 0.275Hz, which is based on the vibration excitation frequency in the normal operation stage of the fan in the Y direction. The time-dependent change information of the vibration acceleration in the Y direction in the second vibration acceleration may be shown in fig. 2C, the result of fourier spectrum analysis of the second vibration acceleration may be shown in fig. 2D, and as can be seen from fig. 2C and fig. 2D, fourier transformation is performed on time domain data of the vibration acceleration in the Y direction of the nacelle in a time range of-10 s to 10s, and the time domain data is converted into a frequency domain amplitude-frequency relation curve, where the maximum energy (amplitude) is found to be 0.313, and the vibration frequency corresponding to the maximum energy is 0.35Hz, which is the vibration frequency based on the over-limit stage of the fan vibration in the Y direction. As can be seen from fig. 2E, the time-dependent change information of the vibration acceleration in the Y direction in the third vibration acceleration may be shown in fig. 2F, and as can be seen from fig. 2E and 2F, fourier transform is performed on the time domain data of the vibration acceleration in the Y direction of the nacelle in the time range of 20s to 60s, so that the maximum energy is found to be 0.144, and the vibration frequency corresponding to the maximum energy is 0.325Hz, which is the vibration frequency based on the shutdown stage of the fan in the Y direction, and is approximately the natural frequency, which is the natural frequency of the whole machine. The time-dependent change information of the vibration acceleration in the X direction in the first vibration acceleration may be shown in fig. 2G, the result of fourier spectrum analysis of the first vibration acceleration may be shown in fig. 2H, and as can be seen from fig. 2G and fig. 2H, fourier transform is performed on time domain data of the vibration acceleration in the X direction of the nacelle to a frequency domain amplitude in a time range of-60 s to-20 s, so that the maximum energy is found to be 0.069, and the vibration frequency corresponding to the maximum energy is 0.325Hz, which is the vibration excitation frequency based on the normal operation stage of the fan in the X direction. The time-dependent change information of the vibration acceleration in the X direction in the second vibration acceleration can be shown in fig. 2I, the result of fourier spectrum analysis of the second vibration acceleration can be shown in fig. 2J, as can be seen from fig. 2I and fig. 2J, the time domain data of the vibration acceleration in the X direction of the nacelle is fourier transformed into a frequency domain amplitude and frequency relation curve in the time domain of-10 s, the maximum energy is found to be 0.187, the vibration frequency corresponding to the maximum energy is 0.35Hz, and the time domain amplitude and frequency relation curve is the fan vibration frequency in the over-limit stage based on the X direction. As can be seen from fig. 2K, the time-dependent change information of the vibration acceleration in the X direction in the third vibration acceleration may be shown in fig. 2L, and as can be seen from fig. 2K and 2L, fourier transform is performed on the time domain data of the nacelle vibration acceleration in the X direction in a time range of 20s to 60s, so that the maximum energy is found to be 0.077, and the vibration frequency corresponding to the maximum energy is found to be 0.333Hz, which is the vibration frequency in the shutdown stage of the fan based on the X direction, and is approximately the natural frequency, which is the natural frequency of the whole machine. The frequency data of each stage obtained above is shown in table 1 below:
TABLE 1
| Operation type | Y-direction frequency/Hz | X-direction frequency/Hz |
| Normal operation phase | 0.275 | 0.325 |
| Overrun phase of vibration | 0.35 | 0.35 |
| Shutdown phase | 0.325 | 0.333 |
Step S103, determining a first deviation value between the first frequency and the third frequency and a second deviation value between the second frequency and the third frequency.
The first deviation value is illustratively the difference between the first frequency and the third frequency, and the second deviation value is the deviation between the second frequency and the third frequency. In the embodiment of the application, the data Y in Table 1 can be analyzed, and it can be known that during the running of the unit, the vibration response frequency of the cabin vibration acceleration is about 0.275Hz and 0.35Hz, the vibration frequency after the unit is stopped is 0.325Hz, the first deviation value is equal to the value of 0.275Hz minus 0.325Hz, and the second deviation value is equal to the value of 0.35Hz minus 0.325 Hz.
And step S104, judging whether the offshore wind turbine has resonance overrun faults or not based on the first deviation value, the second deviation value and the preset deviation value, and obtaining a fault identification result.
The preset deviation value may be any value, and the specific content of the preset deviation value is not limited in the embodiment of the present application, and may be determined by those skilled in the art according to requirements. In the embodiment of the application, the preset deviation value may include, but is not limited to, 0.05, and when the first deviation value or the second deviation value is smaller than 0.05, determining that the offshore wind turbine has resonance overrun fault.
According to the method for identifying the vibration overrun faults of the offshore wind turbine, when the offshore wind turbine is subjected to resonance overrun faults, fourier spectrum analysis is conducted on the first vibration acceleration data, the second vibration acceleration data and the third vibration acceleration data in the vibration overrun fault stage, the first vibration acceleration data and the third vibration acceleration data in the fan stop stage, so that the fan excitation frequency, the fan excitation frequency and the natural frequency are obtained, and the problem that manpower resources are wasted and time is long in the related technology is solved.
In this embodiment, a method for identifying a vibration overrun fault of an offshore wind turbine is provided, which may be used for the above electronic device, the processor, etc., fig. 3 is a flowchart of a method for identifying a vibration overrun fault of an offshore wind turbine according to an embodiment of the present invention, and as shown in fig. 3, the flowchart includes the following steps:
step S301, when the offshore wind turbine has a vibration overrun fault, acquiring first vibration acceleration data in a preset period of time before the offshore wind turbine has the vibration overrun fault, second vibration acceleration data in a vibration overrun fault stage and third vibration acceleration data in a wind turbine shutdown stage. Please refer to step S101 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S302, fourier spectrum analysis is carried out on the first vibration acceleration data, the second vibration acceleration data and the third vibration acceleration data respectively to obtain a first frequency corresponding to the first vibration acceleration data, a second frequency corresponding to the second vibration acceleration data and a third frequency corresponding to the third vibration acceleration data, wherein the first frequency is the fan excitation frequency in the normal rotation stage of the impeller before the occurrence of the vibration overrun fault of the offshore wind turbine, the second frequency is the fan excitation frequency in the occurrence of the vibration overrun fault of the offshore wind turbine, and the third frequency is the natural frequency in the shutdown stage of the offshore wind turbine. Please refer to step S102 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S303, determining a first deviation value between the first frequency and the third frequency and a second deviation value between the second frequency and the third frequency. Please refer to step S103 in the embodiment shown in fig. 1 in detail, which is not described herein.
And step S304, judging whether the offshore wind turbine has resonance overrun faults or not based on the first deviation value, the second deviation value and the preset deviation value, and obtaining a fault identification result. Please refer to step S104 in the embodiment shown in fig. 1 in detail, which is not described herein.
After the step S304, the method specifically further includes:
step S305, determining a fault handling scheme based on the fault recognition result.
For example, when a fan is in resonance overrun fault, a corresponding solution can be given based on the resonance overrun fault, when a non-resonance fault occurs, whether the fan vibration overrun is caused by high wind load such as typhoon or the like is judged first, and if typhoon factors are eliminated, the fan rotation stress is judged to be caused by unbalance. The reasons are that the internal of the wind turbine generator system has mechanical problems, so that the structure is stressed unbalance to cause vibration overrun faults in the rotating process of the fan impeller, such as asynchronous independent pitch system, standard zero baseline installation dislocation of three blades, abrasion of a friction contact surface of a main bearing in the gear box, improper lubrication of the bearing, incorrect lubrication mode, unbalanced rotor quality, loose impeller connecting pieces and the like. And carrying out inspection item by item aiming at possible faults, and judging the cause of the faults.
According to the method for identifying the vibration overrun faults of the offshore wind turbine, provided by the embodiment of the invention, the fault processing scheme is determined based on the fault identification result, so that the efficiency of offshore wind power operation and maintenance work is improved, and the safe operation of the fan is ensured.
In this embodiment, a method for identifying a vibration overrun fault of an offshore wind turbine is provided, which may be used for the above electronic device, the processor, etc., fig. 4 is a flowchart of a method for identifying a vibration overrun fault of an offshore wind turbine according to an embodiment of the present invention, as shown in fig. 4, where the flowchart includes the following steps:
step S401, when the offshore wind turbine has a vibration overrun fault, acquiring first vibration acceleration data in a preset period of time before the offshore wind turbine has the vibration overrun fault, second vibration acceleration data in a vibration overrun fault stage and third vibration acceleration data in a wind turbine stopping stage. Please refer to step S101 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S402, fourier spectrum analysis is carried out on the first vibration acceleration data, the second vibration acceleration data and the third vibration acceleration data respectively to obtain a first frequency corresponding to the first vibration acceleration data, a second frequency corresponding to the second vibration acceleration data and a third frequency corresponding to the third vibration acceleration data, wherein the first frequency is fan excitation frequency in a normal rotation stage of the impeller before the occurrence of the vibration overrun fault of the offshore wind turbine, the second frequency is fan excitation frequency in the occurrence of the vibration overrun fault of the offshore wind turbine, and the third frequency is natural frequency in a shutdown stage of the offshore wind turbine. Please refer to step S102 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S403, determining a first deviation value between the first frequency and the third frequency and a second deviation value between the second frequency and the third frequency. Please refer to step S103 in the embodiment shown in fig. 1 in detail, which is not described herein.
And step S404, judging whether the offshore wind turbine has resonance overrun faults or not based on the first deviation value, the second deviation value and the preset deviation value, and obtaining a fault identification result. Please refer to step S104 in the embodiment shown in fig. 1 in detail, which is not described herein.
Specifically, after the step S404, the method further includes:
in step S405, when the offshore wind turbine has a resonance overrun fault, a sweep frequency band of the offshore wind turbine blade is determined based on the impeller rotation speed range of the offshore wind turbine.
Illustratively, the impeller speed range is a fan factory set parameter, the sweep frequency band may include, but is not limited to, a 1P frequency band and a 3P frequency band, and the 1P frequency band and the 3P frequency band may be determined based on the impeller speed range, for example, when the impeller speed range RMP range is RPM1 to RPM2, the 1P frequency band refers to a frequency of one rotation of the fan hub, the 1P frequency band f1p=rpm 1/60 to RPM2/60,3P frequency band refers to a frequency of three blades passing through a tower shadow, and the 3P frequency band f3p= (RPM 1/60 to RPM 2/60) x 3. In the embodiment of the present application, the sweep frequency band may be a 3P frequency band.
In step S406, it is determined whether the third frequency falls within the sweep frequency band. Illustratively, in the embodiment of the present application, whether the third frequency falls within the 3P frequency band is determined based on the value of the third frequency and the range of the 3P frequency band.
In step S407, when the third frequency falls within the sweep frequency band, a resonance rotation speed interval corresponding to the sweep frequency band is determined based on the third frequency.
Illustratively, in the embodiment of the present application, when the third frequency does not fall into the 3P frequency band, it may be determined that vortex-induced resonance occurs in the offshore wind turbine; when the third frequency falls into the 3P frequency band, a 3P resonance rotation speed interval needs to be calculated based on the third frequency, where the 3P resonance rotation speed r3p=fs×60s/3, where fs is the third resonance frequency, s is a time unit second, and the 3P resonance rotation speed interval may take ±15% of R3P.
And step S408, determining whether the offshore wind turbine has self-excitation resonance faults or not based on the measured rotating speed of the impeller before the vibration overrun faults of the offshore wind turbine occur. In an exemplary embodiment, when the measured rotation speed of the impeller is within the measured rotation speed resonance rotation speed interval before the over-limit vibration fault occurs in the offshore wind turbine, the self-excitation resonance fault occurs in the offshore wind turbine, otherwise, the vortex-induced resonance fault occurs in the offshore wind turbine.
According to the method for identifying the vibration overrun faults of the offshore wind turbine, whether the offshore wind turbine has self-excited resonance faults or not is determined based on the sweep frequency band and the natural frequency of the offshore wind turbine, and the corresponding fault solution is convenient to determine based on the judgment result.
In this embodiment, a method for identifying a vibration overrun fault of an offshore wind turbine is provided, which may be used for the above electronic device, the processor, and the like, and fig. 5 is a flowchart of a method for identifying a vibration overrun fault of an offshore wind turbine according to an embodiment of the present application, as shown in fig. 5, where the flowchart includes the following steps:
step S501, obtaining vibration acceleration data in an offshore wind turbine nacelle. For example, vibration acceleration data in an offshore wind turbine nacelle is acquired by a vibration acceleration sensor provided inside the nacelle.
And step S502, respectively comparing the vibration acceleration data with a preset threshold value to obtain a comparison result. The preset threshold may be a preset management threshold, and the specific content of the preset threshold is not limited in the embodiment of the present application, and may be determined by a person skilled in the art according to requirements.
And step S503, judging whether the offshore wind turbine has a vibration overrun fault or not based on the comparison result. For example, when the vibration acceleration is greater than a preset threshold, it is determined that the offshore wind turbine has a vibration overrun fault.
Step S504, when the offshore wind turbine has a vibration overrun fault, acquiring first vibration acceleration data in a preset period of time before the offshore wind turbine has the vibration overrun fault, second vibration acceleration data in a vibration overrun fault stage and third vibration acceleration data in a wind turbine stopping stage. Please refer to step S101 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S505, performing Fourier spectrum analysis on the first vibration acceleration data, the second vibration acceleration data and the third vibration acceleration data respectively to obtain a first frequency corresponding to the first vibration acceleration data, a second frequency corresponding to the second vibration acceleration data and a third frequency corresponding to the third vibration acceleration data, wherein the first frequency is a fan excitation frequency in a normal rotation stage of the impeller before the occurrence of the vibration overrun fault of the offshore wind turbine, the second frequency is a fan excitation frequency in which the vibration overrun fault of the offshore wind turbine occurs, and the third frequency is a natural frequency in a shutdown stage of the offshore wind turbine. Please refer to step S102 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S506, determining a first deviation value between the first frequency and the third frequency and a second deviation value between the second frequency and the third frequency. Please refer to step S103 in the embodiment shown in fig. 1 in detail, which is not described herein.
And step S507, judging whether the offshore wind turbine has resonance overrun faults or not based on the first deviation value, the second deviation value and the preset deviation value, and obtaining a fault identification result. Please refer to step S104 in the embodiment shown in fig. 1 in detail, which is not described herein.
According to the method for identifying the vibration overrun faults of the offshore wind turbine, provided by the embodiment of the application, the vibration acceleration data is compared with the preset threshold value, and whether the vibration overrun faults of the offshore wind turbine occur can be accurately judged based on the comparison result.
In this embodiment, a method for identifying a vibration overrun fault of an offshore wind turbine is provided, which may be used for the above electronic device, the processor, etc., fig. 6 is a flowchart of a method for identifying a vibration overrun fault of an offshore wind turbine according to an embodiment of the present application, as shown in fig. 6, where the flowchart includes the following steps:
step S601, vibration acceleration data acquired by the first acceleration sensor and vibration acceleration data acquired by the second acceleration sensor are acquired. In an exemplary embodiment of the present application, two vibration acceleration sensors, a first acceleration sensor and a second acceleration sensor, may be symmetrically disposed along the center line of the main shaft in the nacelle of the offshore wind turbine.
Step S602, determining whether the working states of the first acceleration sensor and the second acceleration sensor are normal based on the vibration acceleration data acquired by the first acceleration sensor and the vibration acceleration data acquired by the second acceleration sensor. The method for judging whether the jump abnormality occurs in the acceleration data is specifically as follows: if the four groups of data amplitude values of the two acceleration sensors arranged in the fan cabin are subjected to individual mutation in the X direction and the Y direction, the sensor fault is indicated to be abnormal; if the four groups of data amplitude values of the two acceleration sensors arranged in the fan cabin are close to each other in the X direction and the Y direction, the working state of the sensors is reliable, and jump abnormality does not occur in the data.
And step S603, if the working states of the first acceleration sensor and the second acceleration sensor are normal, judging whether the offshore wind turbine has a vibration overrun fault or not according to the vibration acceleration data acquired by the first acceleration sensor and the vibration acceleration data acquired by the second acceleration sensor. In an exemplary embodiment, when the working states of the first acceleration sensor and the second acceleration sensor are monitored to be normal, whether the offshore wind turbine has a vibration overrun fault is further judged based on vibration acceleration data acquired by the acceleration sensors.
Step S604, if the vibration overrun fault of the offshore wind turbine is determined, a shutdown control instruction is sent to the offshore wind turbine. Illustratively, if the offshore wind turbine fails to vibrate out of limits, the offshore wind turbine is controlled to shut down.
Step S605, when the offshore wind turbine has a vibration overrun fault, acquiring first vibration acceleration data in a preset period of time before the offshore wind turbine has the vibration overrun fault, second vibration acceleration data in a vibration overrun fault stage and third vibration acceleration data in a wind turbine stopping stage. Please refer to step S101 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S606, fourier spectrum analysis is carried out on the first vibration acceleration data, the second vibration acceleration data and the third vibration acceleration data respectively to obtain a first frequency corresponding to the first vibration acceleration data, a second frequency corresponding to the second vibration acceleration data and a third frequency corresponding to the third vibration acceleration data, wherein the first frequency is the fan excitation frequency in the normal rotation stage of the impeller before the occurrence of the vibration overrun fault of the offshore wind turbine, the second frequency is the fan excitation frequency in the occurrence of the vibration overrun fault of the offshore wind turbine, and the third frequency is the natural frequency in the shutdown stage of the offshore wind turbine. Please refer to step S102 in the embodiment shown in fig. 1 in detail, which is not described herein.
In step S607, a first deviation value between the first frequency and the third frequency and a second deviation value between the second frequency and the third frequency are determined. Please refer to step S103 in the embodiment shown in fig. 1 in detail, which is not described herein.
And step 608, judging whether the offshore wind turbine has resonance overrun faults or not based on the first deviation value, the second deviation value and the preset deviation value, and obtaining a fault identification result. Please refer to step S104 in the embodiment shown in fig. 1 in detail, which is not described herein.
The method for identifying the vibration overrun faults of the offshore wind turbine provided by the embodiment of the invention can more accurately determine whether the resonance overrun faults occur in the offshore wind turbine, and effectively avoid the problem of shutdown of the wind turbine caused by abnormal working state of the vibration sensor.
In this embodiment, a method for identifying a vibration overrun fault of an offshore wind turbine is provided, which may be used for the above electronic device, the processor, etc., fig. 7 is a flowchart of a method for identifying a vibration overrun fault of an offshore wind turbine according to an embodiment of the present invention, and as shown in fig. 7, the flowchart includes the following steps:
step S701, vibration acceleration data acquired by the first acceleration sensor and vibration acceleration data acquired by the second acceleration sensor are acquired. Please refer to step S601 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S702, determining whether the working states of the first acceleration sensor and the second acceleration sensor are normal based on the vibration acceleration data collected by the first acceleration sensor and the vibration acceleration data collected by the second acceleration sensor. For example, please refer to step S602 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S703, if the working states of the first acceleration sensor and the second acceleration sensor are normal, judging whether the offshore wind turbine has a vibration overrun fault according to the vibration acceleration data acquired by the first acceleration sensor and the vibration acceleration data acquired by the second acceleration sensor. Please refer to step S603 in the embodiment shown in fig. 1 in detail, which is not described herein.
In some alternative embodiments, the step S703 includes:
step S7031, comparing the vibration acceleration data collected by the first acceleration sensor and the vibration acceleration data collected by the second acceleration sensor with a preset threshold value, respectively, to obtain a comparison result. For example, the preset threshold may be a vibration acceleration management threshold determined based on actual demand.
Step S7032, if the vibration acceleration data collected by the first acceleration sensor is greater than a preset threshold value, and/or the vibration acceleration data collected by the second acceleration sensor is greater than a preset threshold value, determining that the offshore wind turbine has a vibration overrun fault. For example, when the comparison result shows that the comparison result of the vibration acceleration acquired by at least one vibration acceleration sensor is larger than the preset threshold value, the offshore wind turbine has a vibration overrun fault.
Step S704, if the vibration overrun fault of the offshore wind turbine is determined, a shutdown control instruction is sent to the offshore wind turbine. Please refer to step S504 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S705, when the offshore wind turbine has a vibration overrun fault, acquiring first vibration acceleration data in a preset period of time before the offshore wind turbine has the vibration overrun fault, second vibration acceleration data in a vibration overrun fault stage and third vibration acceleration data in a wind turbine stopping stage. Please refer to step S101 in the embodiment shown in fig. 1 in detail, which is not described herein.
In some alternative embodiments, step S705 includes:
step S7051, when the offshore wind turbine has a vibration overrun fault, acquiring first initial vibration acceleration data in a preset period of time before the offshore wind turbine has the vibration overrun fault, second initial vibration acceleration data in a vibration overrun fault stage, and third initial vibration acceleration data in a wind turbine shutdown stage.
For example, in the embodiment of the present application, the first initial vibration acceleration data, the second initial vibration acceleration data, and the third initial vibration acceleration data may be raw data acquired by a vibration acceleration sensor.
Step S7052, performing signal zero padding processing on the first initial vibration acceleration data, the second initial vibration acceleration data and the third initial vibration acceleration data, so as to obtain first vibration acceleration data corresponding to the first initial vibration acceleration data, second vibration acceleration data corresponding to the second initial vibration acceleration data and third vibration acceleration data corresponding to the third initial vibration acceleration data.
In the case of performing fourier FFT spectrum analysis, for example, frequency resolution may not meet the requirement due to limited field acquisition data length, where frequency resolution=sampling frequency/FFT length of FFT, in order to improve spectrum analysis accuracy, a vibration signal zero-padding method is used to add a vibration signal with zero amplitude for a certain time length to the vibration signal, so as to effectively prolong the FFT length, shorten the analysis frequency interval, and obtain a high-accuracy spectrum analysis result. In the embodiment of the application, the signal zero padding processing is carried out on the first initial vibration acceleration data, the second initial vibration acceleration data and the third initial vibration acceleration data, so that the accuracy of the subsequent spectrum analysis result can be effectively improved.
Step S706, performing Fourier spectrum analysis on the first vibration acceleration data, the second vibration acceleration data and the third vibration acceleration data respectively to obtain a first frequency corresponding to the first vibration acceleration data, a second frequency corresponding to the second vibration acceleration data and a third frequency corresponding to the third vibration acceleration data, wherein the first frequency is a fan excitation frequency in a normal rotation stage of the impeller before the occurrence of the vibration overrun fault of the offshore wind turbine, the second frequency is a fan excitation frequency in which the vibration overrun fault of the offshore wind turbine occurs, and the third frequency is a natural frequency in a shutdown stage of the offshore wind turbine. Please refer to step S102 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S707 determines a first deviation value between the first frequency and the third frequency and a second deviation value between the second frequency and the third frequency. Please refer to step S103 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S708, judging whether the offshore wind turbine has resonance overrun faults or not based on the first deviation value, the second deviation value and the preset deviation value, and obtaining a fault identification result. Please refer to step S104 in the embodiment shown in fig. 1 in detail, which is not described herein.
According to the method for identifying the vibration overrun faults of the offshore wind turbine, intelligent diagnosis of the vibration faults of the offshore wind turbine is achieved, the reason for the vibration overrun faults of the offshore wind turbine can be determined through analysis of vibration acceleration data of the offshore wind turbine, and the problems that manpower resources are wasted and time is long in the related technology due to troubleshooting of faults by manpower are solved.
The following describes specific steps of a method for identifying the vibration overrun fault of the offshore wind turbine by using a specific embodiment.
Examples:
step 1, two vibration acceleration sensors are symmetrically arranged on a cabin along the central line of a main shaft, the two vibration acceleration sensors are installed according to a redundant design, the change of vibration acceleration of two components of the cabin X, Y is measured, a wind meter is arranged at the top of the outer side of the cabin to measure environmental data such as wind speed, the rotating speed data of a fan impeller is measured through a fan hub rotating speed testing module, and the variable pitch angle of a fan blade is monitored through a variable pitch angle sensor.
Step 2, monitoring data are recorded according to 50Hz by default in real time for vibration acceleration, if a fan runs normally, the acceleration data are dynamically processed at intervals of 1h, and only 1s is reserved, namely a 1Hz sampling frequency monitoring result is reserved; if the actually measured acceleration exceeds a set management threshold in the running process of the fan, a vibration overrun fault occurs at the moment, and data of two minutes before and after overrun are automatically recorded according to the 50Hz sampling frequency.
And 3, judging whether jump abnormality occurs in the acceleration data. If the four groups of data amplitude values of the two acceleration sensors arranged in the fan cabin are subjected to individual mutation in the X direction and the Y direction, the sensor fault is indicated to be abnormal; if the two acceleration sensors arranged in the fan cabin are close to each other in the X direction and the Y direction in four groups of data amplitude values, the working state of the sensors is reliable, jump abnormality does not occur in the data, the data belongs to normal overrun, and the data can be subjected to next-step spectrum analysis.
And 4, respectively carrying out Fourier spectrum analysis on the X, Y directional vibration acceleration components monitored by the sensor to obtain the fan excitation frequency at the normal rotation stage of the impeller before the fan overruns, the excitation frequency at the overrun stage and the natural frequency fs of the fan in a period of time after the fan impeller is stopped, judging the fan to be in resonance overrun fault if the deviation between the fan operation excitation frequency and the natural frequency is within +/-5%, and judging the fan to be in non-resonance overrun fault if the deviation between the fan operation excitation frequency and the natural frequency is outside +/-5%.
And 5, aiming at the resonance overrun fault, the intrinsic cause of the fault needs to be further identified. Calculating 1P frequency and 3P frequency bandwidth through the impeller rotating speed range, judging whether the natural frequency of the actually measured fan falls into a 3P frequency band, if so, calculating 3P resonance rotating speed R3P of the fan according to a formula R3 P=fs 60s/3, wherein the 3P resonance rotating speed interval takes +/-15% of R3P, and if the actually measured rotating speed of the impeller and the 3P resonance rotating speed interval overlap before the fan exceeds the limit, identifying the vibration overrun factor of the fan as 3P self-excitation resonance; otherwise, judging that vortex-induced resonance occurs in the fan under the action of external factors such as wind fields and the like.
And 6, for the non-resonance faults, firstly judging whether the vibration overrun of the fan is caused by the vibration overrun caused by the heavy wind load such as typhoon, and if the typhoon factor is eliminated, judging that the rotation stress of the fan is caused by unbalance. The reasons are that the internal of the wind turbine generator system has mechanical problems, so that the structure is stressed unbalance to cause vibration overrun faults in the rotating process of the fan impeller, such as asynchronous independent pitch system, standard zero baseline installation dislocation of three blades, abrasion of a friction contact surface of a main bearing in the gear box, improper lubrication of the bearing, incorrect lubrication mode, unbalanced rotor quality, loose impeller connecting pieces and the like. Checking is carried out item by item aiming at possible faults, the fault cause is judged,
Specifically, when performing fourier FFT spectrum analysis, frequency resolution is often not up to the requirement because the length of field acquired data is limited, wherein the frequency resolution of fft=sampling frequency/FFT length, in order to improve the spectrum analysis accuracy, a vibration signal zero-filling method is adopted, a vibration signal with zero amplitude and a certain length is added to the vibration signal, so that the FFT length is effectively prolonged, the analysis frequency interval is shortened, and a high-accuracy spectrum analysis result is obtained.
The vibration signal of vibration acceleration sensor field test has held various noise interference information in the production and transmission process, and marine environment is abominable, need carry out filter processing with time domain vibration signal when fourier spectrum analysis, set up low pass filter as required, filter high frequency signal, obtain the frequency domain data in the real range of marine wind turbine generator system whole frequency, remove interference signal.
The vibration acceleration sensor test data is characterized in that the sensor connector is easily influenced due to the fact that the marine environment has high salt mist and high corrosion severe environment, the sensor data transmission is induced to be abnormal, the data is suddenly increased in a jumping mode and is far away from an acceleration management threshold value, a control strategy controls a fan to stop operation, normal power generation capacity is influenced, the problem can be solved through data analysis and screening, and the sensor is regularly maintained or a salt mist-resistant corrosion-resistant gold or silver-made metal connector is used for connecting a data line with the sensor.
In this embodiment, a device for identifying a vibration overrun fault of an offshore wind turbine is further provided, and the device is used for implementing the foregoing embodiments and preferred embodiments, and is not described again. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
The embodiment provides a device for identifying a vibration overrun fault of an offshore wind turbine, as shown in fig. 8, including:
the first obtaining module 801 is configured to obtain, when a vibration overrun fault occurs in the offshore wind turbine, first vibration acceleration data in a preset period of time before the vibration overrun fault occurs in the offshore wind turbine, second vibration acceleration data in a vibration overrun fault stage, and third vibration acceleration data in a wind turbine shutdown stage.
The spectrum analysis module 802 is configured to perform fourier spectrum analysis on the first vibration acceleration data, the second vibration acceleration data, and the third vibration acceleration data, to obtain a first frequency corresponding to the first vibration acceleration data, a second frequency corresponding to the second vibration acceleration data, and a third frequency corresponding to the third vibration acceleration data, where the first frequency is a fan excitation frequency in a normal rotation stage of the impeller before the occurrence of a vibration overrun fault of the offshore wind turbine, the second frequency is a fan excitation frequency in which the occurrence of the vibration overrun fault of the offshore wind turbine, and the third frequency is a natural frequency in a shutdown stage of the offshore wind turbine.
A first determining module 803 is configured to determine a first deviation value between the first frequency and the third frequency and a second deviation value between the second frequency and the third frequency.
The second determining module 804 is configured to determine whether the offshore wind turbine has a resonance overrun fault based on the first deviation value, the second deviation value, and the preset deviation value, and obtain a fault recognition result.
In some alternative embodiments, the apparatus further comprises: and the third determining module is used for determining a fault processing scheme based on the fault recognition result.
In some alternative embodiments, the apparatus further comprises: the fourth determining module is used for determining a sweeping frequency band of the offshore wind turbine blade based on the rotating speed range of the impeller of the offshore wind turbine when the offshore wind turbine has a resonance overrun fault; the first judging module is used for judging whether the third frequency falls into a sweeping frequency band; a fifth determining module, configured to determine, when the third frequency falls within the sweep frequency band, a resonance rotation speed interval corresponding to the sweep frequency band based on the third frequency; and the sixth determining module is used for determining whether the offshore wind turbine has self-excitation resonance faults or not based on the resonance rotation speed interval and the actual measurement rotation speed of the impeller before the offshore wind turbine has the vibration overrun faults.
In some alternative embodiments, the apparatus further comprises: the second acquisition module is used for acquiring vibration acceleration data in the offshore wind turbine cabin; the comparison module is used for respectively comparing the vibration acceleration data with a preset threshold value to obtain a comparison result; and the second judging module is used for judging whether the offshore wind turbine has a vibration overrun fault or not based on the comparison result.
In some alternative embodiments, the apparatus further comprises: the third acquisition module is used for acquiring the vibration acceleration data acquired by the first acceleration sensor and the vibration acceleration data acquired by the second acceleration sensor; the third judging module is used for judging whether the working states of the first acceleration sensor and the second acceleration sensor are normal or not based on the vibration acceleration data acquired by the first acceleration sensor and the vibration acceleration data acquired by the second acceleration sensor; the third judging module is used for judging whether the offshore wind turbine has a vibration overrun fault or not according to the vibration acceleration data acquired by the first acceleration sensor and the vibration acceleration data acquired by the second acceleration sensor if the working states of the first acceleration sensor and the second acceleration sensor are normal; and the sending module is used for sending a shutdown control instruction to the offshore wind turbine if the offshore wind turbine is judged to have the vibration overrun fault.
In some optional embodiments, the third determining module includes: the comparison unit is used for respectively comparing the vibration acceleration data acquired by the first acceleration sensor and the vibration acceleration data acquired by the second acceleration sensor with a preset threshold value to obtain a comparison result; and the judging unit is used for judging that the offshore wind turbine has vibration overrun faults if the vibration acceleration data acquired by the first acceleration sensor is greater than a preset threshold value and/or the vibration acceleration data acquired by the second acceleration sensor is greater than the preset threshold value.
Further functional descriptions of the above respective modules and units are the same as those of the above corresponding embodiments, and are not repeated here.
The device for identifying the vibration overrun fault of the offshore wind turbine generator in this embodiment is presented in the form of functional units, where the units are ASIC (Application Specific Integrated Circuit ) circuits, processors and memories executing one or more software or fixed programs, and/or other devices that can provide the above functions.
The embodiment of the invention also provides computer equipment, which is provided with the device for identifying the vibration overrun faults of the offshore wind turbine shown in the figure 8.
Referring to fig. 9, fig. 9 is a schematic structural diagram of a computer device according to an alternative embodiment of the present invention, as shown in fig. 9, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are communicatively coupled to each other using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing within the computer device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In some alternative embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple computer devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). One processor 10 is illustrated in fig. 9.
The processor 10 may be a central processor, a network processor, or a combination thereof. The processor 10 may further include a hardware chip, among others. The hardware chip may be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general-purpose array logic, or any combination thereof.
Wherein the memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform a method for implementing the embodiments described above.
The memory 20 may include a storage program area that may store an operating system, at least one application program required for functions, and a storage data area; the storage data area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, memory 20 may optionally include memory located remotely from processor 10, which may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk, or solid state disk; the memory 20 may also comprise a combination of the above types of memories.
The computer device also includes a communication interface 30 for the computer device to communicate with other devices or communication networks.
The embodiments of the present invention also provide a computer readable storage medium, and the method according to the embodiments of the present invention described above may be implemented in hardware, firmware, or as a computer code which may be recorded on a storage medium, or as original stored in a remote storage medium or a non-transitory machine readable storage medium downloaded through a network and to be stored in a local storage medium, so that the method described herein may be stored on such software process on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, a solid state disk or the like; further, the storage medium may also comprise a combination of memories of the kind described above. It will be appreciated that a computer, processor, microprocessor controller or programmable hardware includes a storage element that can store or receive software or computer code that, when accessed and executed by the computer, processor or hardware, implements the methods illustrated by the above embodiments.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the invention as defined by the appended claims.
Claims (11)
1. The method for identifying the vibration overrun fault of the offshore wind turbine generator is characterized by comprising the following steps of:
when the offshore wind turbine has a vibration overrun fault, acquiring first vibration acceleration data in a preset period of time before the offshore wind turbine has the vibration overrun fault, second vibration acceleration data in a vibration overrun fault stage and third vibration acceleration data in a wind turbine stopping stage;
performing Fourier spectrum analysis on the first vibration acceleration data, the second vibration acceleration data and the third vibration acceleration data respectively to obtain a first frequency corresponding to the first vibration acceleration data, a second frequency corresponding to the second vibration acceleration data and a third frequency corresponding to the third vibration acceleration data, wherein the first frequency is a fan excitation frequency in a normal rotation stage of the impeller before the occurrence of the vibration overrun fault of the offshore wind turbine, the second frequency is a fan excitation frequency in which the vibration overrun fault of the offshore wind turbine occurs, and the third frequency is a natural frequency in a shutdown stage of the offshore wind turbine;
Determining a first deviation value between the first frequency and the third frequency and a second deviation value between the second frequency and the third frequency;
and judging whether the offshore wind turbine has resonance overrun faults or not based on the first deviation value, the second deviation value and the preset deviation value, and obtaining a fault identification result.
2. The method of claim 1, wherein determining whether the offshore wind turbine has a resonance overrun fault based on the first deviation value, the second deviation value, and a preset deviation value, and after obtaining the fault identification result, further comprises:
and determining a fault processing scheme based on the fault identification result.
3. The method of claim 1, wherein determining whether the offshore wind turbine has a resonance overrun fault based on the first deviation value, the second deviation value, and a preset deviation value, and after obtaining the fault identification result, further comprises:
when the offshore wind turbine has resonance overrun faults, determining a sweep frequency band of the offshore wind turbine blade based on the impeller rotating speed range of the offshore wind turbine;
judging whether the third frequency falls into the sweeping frequency band;
When the third frequency falls into a sweeping frequency band, determining a resonance rotating speed interval corresponding to the sweeping frequency band based on the third frequency;
and determining whether the offshore wind turbine has self-excitation resonance faults or not based on the measured rotating speed of the impeller before the resonance rotating speed interval and the vibration overrun faults of the offshore wind turbine.
4. The method of claim 1, wherein, before the obtaining the first vibration acceleration data, the second vibration acceleration data, and the third vibration acceleration data for the target period of time before the occurrence of the vibration overrun fault, the second vibration acceleration data, and the third vibration acceleration data for the fan shutdown phase for the offshore wind turbine when the vibration overrun fault occurs, the method further comprises:
acquiring vibration acceleration data in an offshore wind turbine nacelle;
respectively comparing the vibration acceleration data with a preset threshold value to obtain a comparison result;
and judging whether the offshore wind turbine has a vibration overrun fault or not based on the comparison result.
5. The method of claim 1, wherein, when an offshore wind turbine fails in a vibration overrun, prior to obtaining first vibration acceleration data, second vibration acceleration data for a vibration overrun failure phase, and third vibration acceleration data for a wind turbine shutdown phase for a target period of time before the offshore wind turbine fails in a vibration overrun, the method further comprises:
Acquiring vibration acceleration data acquired by a first acceleration sensor and vibration acceleration data acquired by a second acceleration sensor;
judging whether the working states of the first acceleration sensor and the second acceleration sensor are normal or not based on vibration acceleration data acquired by the first acceleration sensor and vibration acceleration data acquired by the second acceleration sensor;
if the working states of the first acceleration sensor and the second acceleration sensor are normal, judging whether the offshore wind turbine has a vibration overrun fault or not according to vibration acceleration data acquired by the first acceleration sensor and vibration acceleration data acquired by the second acceleration sensor;
and if the offshore wind turbine is judged to have the vibration overrun fault, sending a shutdown control instruction to the offshore wind turbine.
6. The method of claim 5, wherein determining whether the offshore wind turbine has a vibration overrun fault based on the vibration acceleration data collected by the first acceleration sensor and the vibration acceleration data collected by the second acceleration sensor comprises:
respectively comparing the vibration acceleration data acquired by the first acceleration sensor and the vibration acceleration data acquired by the second acceleration sensor with a preset threshold value to obtain a comparison result;
And if the vibration acceleration data acquired by the first acceleration sensor is greater than a preset threshold value and/or the vibration acceleration data acquired by the second acceleration sensor is greater than the preset threshold value, judging that the offshore wind turbine has a vibration overrun fault.
7. The method of claim 1, wherein when an offshore wind turbine fails in a vibration overrun, obtaining first vibration acceleration data for a predetermined period of time before the offshore wind turbine fails in a vibration overrun, second vibration acceleration data for a vibration overrun failure phase, and third vibration acceleration data for a wind turbine shutdown phase, comprises:
when the offshore wind turbine has a vibration overrun fault, acquiring first initial vibration acceleration data, second initial vibration acceleration data and third initial vibration acceleration data of a wind turbine stopping stage in a preset period before the offshore wind turbine has the vibration overrun fault;
and performing signal zero padding processing on the first initial vibration acceleration data, the second initial vibration acceleration data and the third initial vibration acceleration data respectively to obtain first vibration acceleration data corresponding to the first initial vibration acceleration data, second vibration acceleration data corresponding to the second initial vibration acceleration data and third vibration acceleration data corresponding to the third initial vibration acceleration data.
8. An offshore wind turbine vibration overrun fault identification device, the device comprising:
the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring first vibration acceleration data, second vibration acceleration data and third vibration acceleration data of a fan stopping stage in a preset period of time before the occurrence of the vibration overrun fault of the offshore wind turbine when the vibration overrun fault of the offshore wind turbine occurs;
the frequency spectrum analysis module is used for carrying out Fourier frequency spectrum analysis on the first vibration acceleration data, the second vibration acceleration data and the third vibration acceleration data respectively to obtain a first frequency corresponding to the first vibration acceleration data, a second frequency corresponding to the second vibration acceleration data and a third frequency corresponding to the third vibration acceleration data, wherein the first frequency is a fan excitation frequency in a normal rotation stage of the impeller before the offshore wind turbine generates the vibration overrun fault, the second frequency is a fan excitation frequency of the offshore wind turbine generating the vibration overrun fault, and the third frequency is a natural frequency in a shutdown stage of the offshore wind turbine;
a first determining module configured to determine a first deviation value between the first frequency and the third frequency and a second deviation value between the second frequency and the third frequency;
And the second determining module is used for judging whether the offshore wind turbine has resonance overrun faults or not based on the first deviation value, the second deviation value and the preset deviation value, and obtaining a fault identification result.
9. The apparatus of claim 8, wherein the apparatus further comprises:
and the third determining module is used for determining a fault processing scheme based on the fault identification result.
10. A computer device, comprising:
the marine wind turbine vibration overrun fault identification method according to any one of claims 1 to 7, comprising a memory and a processor, wherein the memory and the processor are in communication connection, the memory stores computer instructions, and the processor executes the computer instructions, thereby executing the marine wind turbine vibration overrun fault identification method.
11. A computer-readable storage medium, wherein computer instructions for causing a computer to execute the method for identifying an overrun fault in a marine wind turbine according to any one of claims 1 to 7 are stored on the computer-readable storage medium.
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| CN202310898246.4A CN116928039A (en) | 2023-07-20 | 2023-07-20 | Method, device, equipment and medium for identifying vibration overrun faults of offshore wind turbine generator |
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| CN202310898246.4A CN116928039A (en) | 2023-07-20 | 2023-07-20 | Method, device, equipment and medium for identifying vibration overrun faults of offshore wind turbine generator |
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