CN110554090A - Wind turbine generator and crack monitoring system and method of variable-pitch bearing of wind turbine generator - Google Patents
Wind turbine generator and crack monitoring system and method of variable-pitch bearing of wind turbine generator Download PDFInfo
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- CN110554090A CN110554090A CN201810552860.4A CN201810552860A CN110554090A CN 110554090 A CN110554090 A CN 110554090A CN 201810552860 A CN201810552860 A CN 201810552860A CN 110554090 A CN110554090 A CN 110554090A
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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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/14—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object using acoustic emission techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
- G01N29/48—Processing the detected response signal, e.g. electronic circuits specially adapted therefor by amplitude comparison
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Abstract
The invention provides a crack monitoring system and method for a wind turbine generator and a variable-pitch bearing thereof, wherein the crack monitoring system comprises: a plurality of acoustic emission sensors configured to acquire acoustic emission signals of corresponding pitch bearings; the controller is installed in the hub and configured to control each acoustic emission sensor to acquire the acoustic emission signal of the corresponding variable pitch bearing, acquire the acoustic emission signal of the corresponding variable pitch bearing from each acoustic emission sensor, and determine whether each variable pitch bearing has cracks according to the acoustic emission signals of all the variable pitch bearings. According to the wind turbine generator and the crack monitoring system of the pitch bearing of the wind turbine generator, online crack monitoring of the pitch bearing can be achieved through an acoustic emission technology, the pitch bearing is not affected by a shielding object, reliability is high, crack faults can be found in the crack initiation stage, compared with monitoring technologies such as manual troubleshooting and video troubleshooting, cracks can be found earlier, and planned maintenance can be achieved.
Description
Technical Field
The invention relates to the field of wind power generation, in particular to a wind turbine generator and a crack monitoring system and method for a variable-pitch bearing of the wind turbine generator.
Background
The working environment of the variable pitch bearing of the wind turbine generator is mostly severe environments such as sand blown by wind, rain, dew, humidity and low temperature, and various faults such as fracture occur easily. And the change of the variable-pitch bearing is very inconvenient, so the crack monitoring of the variable-pitch bearing is very important. The existing methods for monitoring cracks of a pitch bearing have various disadvantages. For example, fig. 1 shows a structural schematic diagram of an existing video monitoring system, two imaging systems 101 need to be arranged to perform scanning shooting on a high-risk region where a pitch bearing is prone to cracking through a method for monitoring cracks through video, the imaging systems 101 are fixed on a hub, and the imaging systems 101 complete monitoring of the high-risk region where the pitch bearing is prone to cracking by means of a pitch retracting action of a wind turbine. Fig. 2 shows a block diagram of a prior art video surveillance system. As shown in fig. 2, the imaging systems 101 of the three pitch bearings send the shot images to the processor 202 in the hub measurement and control cabinet 201, and the processor 202 analyzes crack faults of the pitch bearings according to the shot images and sends the analysis results to the fan PLC 203. However, the video monitoring area is often shielded by oil stains, and the pitch bearing cannot be directly monitored on the wind turbine with the reinforcing ring, so that the reliability of the monitoring result is not high. In addition, the existing monitoring technologies such as video, tinfoil and conductive paint can be found only after cracks are expanded to the surface of the variable-pitch bearing, and planned maintenance cannot be achieved.
Disclosure of Invention
The invention aims to provide a wind turbine generator and a crack monitoring system and method of a variable-pitch bearing of the wind turbine generator, and aims to solve the problems that the existing crack monitoring mode is low in reliability and cannot realize planned maintenance.
One aspect of the present invention provides a crack monitoring system for a pitch bearing of a wind turbine generator, the crack monitoring system comprising: a plurality of acoustic emission sensors, wherein at least one acoustic emission sensor is provided corresponding to each pitch bearing, the at least one acoustic emission sensor being mounted on the hub in proximity to the corresponding pitch bearing and configured to acquire acoustic emission signals of the corresponding pitch bearing; the controller is installed in the hub and configured to control each acoustic emission sensor to acquire the acoustic emission signal of the corresponding variable pitch bearing, acquire the acoustic emission signal of the corresponding variable pitch bearing from each acoustic emission sensor, and determine whether each variable pitch bearing has cracks according to the acoustic emission signals of all the variable pitch bearings.
Optionally, an acoustic emission sensor is arranged corresponding to each pitch bearing, and the acoustic emission sensor is mounted on the hub close to the position of the 0-scale pitch bearing when the blade is in the pitch take-up state.
Optionally, the controller is further configured to: and aiming at the fault pitch bearing with the crack, determining the position on the fault pitch bearing, which is just opposite to the acoustic emission sensor, as the crack initiation position when the acoustic emission signal with the strongest energy occurs at the first moment in the process of acquiring the acoustic emission signal.
Optionally, the controller is further configured to: and aiming at the fault variable pitch bearing with the crack, determining the position on the fault variable pitch bearing, which is just opposite to the acoustic emission sensor, at the first moment according to the initial position, the rotating speed and the first moment of the fault variable pitch bearing before pitch withdrawing.
Optionally, the controller is configured to: the acoustic emission signals of the variable pitch bearings are subjected to Fourier transform, the acoustic emission signals subjected to Fourier transform are filtered to obtain acoustic emission signals in a preset frequency range, comparison data of the variable pitch bearings are calculated respectively, the comparison data of each variable pitch bearing are compared with preset multiples of a larger value in the comparison data of the other two variable pitch bearings, the variable pitch bearing with the comparison data larger than the preset multiples of the larger value is determined as a fault variable pitch bearing with cracks, and the comparison data of each variable pitch bearing is the square sum of the amplitudes of the acoustic emission signals in the preset frequency range of each variable pitch bearing.
Optionally, the controller is further configured to: and for the fault variable-pitch bearing, dividing the comparison data of the fault variable-pitch bearing by the larger value in the comparison data of the other two variable-pitch bearings to obtain a quotient, and determining the size of the expansion area of the crack according to the quotient.
optionally, three acoustic emission sensors are arranged corresponding to each pitch bearing, wherein one acoustic emission sensor is installed on the hub close to the position of the 0-scale of the pitch bearing when the blade is in the pitch-retracting state, and the other two acoustic emission sensors are respectively installed on two sides of the acoustic emission sensor.
Optionally, each acoustic emission sensor stores an acoustic emission signal of which the amplitude is greater than a threshold value in the acquired acoustic emission signals, and the controller acquires the stored acoustic emission signals from each acoustic emission sensor.
Optionally, the threshold value is a peak value of the amplitude of the acoustic emission signal of the pitch bearing when the wind turbine generator has not been put into use, or an average value of the peak values of the amplitudes of the acoustic emission signals of the pitch bearing when a plurality of wind turbine generators of the same model have not been put into use.
Optionally, the control appliance is configured to control each acoustic emission sensor to acquire an acoustic emission signal of the corresponding pitch bearing when the following trigger conditions are met: the controller detects a paddle retracting signal and the distance between the paddle retracting signal and the last crack monitoring exceeds a first preset time, or the distance between the paddle retracting signal and the last crack monitoring exceeds a second preset time.
Another aspect of the invention provides a wind turbine comprising a crack monitoring system for a pitch bearing as described above.
The invention provides a crack monitoring method for a variable-pitch bearing of a wind turbine generator, which comprises the following steps: controlling each acoustic emission sensor to collect an acoustic emission signal of the corresponding pitch bearing, wherein at least one acoustic emission sensor is arranged corresponding to each pitch bearing, and the at least one acoustic emission sensor is arranged on the hub close to the corresponding pitch bearing; acquiring acoustic emission signals of corresponding variable pitch bearings from each acoustic emission sensor; and determining whether each pitch bearing has cracks according to the acoustic emission signals of all the pitch bearings.
Optionally, the method further comprises: and aiming at the fault pitch bearing with the crack, determining the position on the fault pitch bearing, which is just opposite to the acoustic emission sensor, as the crack initiation position at the first moment when the acoustic emission signal with the strongest energy appears in the process of acquiring the acoustic emission signal.
Optionally, the method further comprises: and aiming at the fault variable pitch bearing with the crack, determining the position on the fault variable pitch bearing, which is just opposite to the acoustic emission sensor, at the first moment according to the initial position, the rotating speed and the first moment of the fault variable pitch bearing before pitch withdrawing.
Optionally, the step of determining whether each pitch bearing has a crack according to the acoustic emission signals of all the pitch bearings includes: fourier transformation is carried out on the acoustic emission signals of each variable pitch bearing; filtering the acoustic emission signals subjected to Fourier transform to obtain acoustic emission signals in a preset frequency range; respectively calculating comparison data of each variable pitch bearing; and comparing the comparison data of each pitch bearing with a preset multiple of a larger value in the comparison data of the other two pitch bearings, and determining the pitch bearing with the comparison data larger than the preset multiple of the larger value as a cracked fault pitch bearing, wherein the comparison data of each pitch bearing is the square sum of the amplitude of the acoustic emission signal in the preset frequency range of each pitch bearing.
Optionally, the method further comprises: and for the fault variable-pitch bearing, dividing the comparison data of the fault variable-pitch bearing by the larger value in the comparison data of the other two variable-pitch bearings to obtain a quotient, and determining the size of the expansion area of the crack according to the quotient.
Optionally, the step of controlling each acoustic emission sensor to acquire an acoustic emission signal of the corresponding pitch bearing includes: when the following triggering conditions are met, controlling each acoustic emission sensor to acquire the acoustic emission signal of the corresponding pitch bearing: and detecting a propeller retracting signal and exceeding a first preset time from the last crack monitoring, or exceeding a second preset time from the last crack monitoring.
Another aspect of the invention provides a computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the crack monitoring method as described above.
According to the wind turbine generator and the crack monitoring system and method of the variable-pitch bearing of the wind turbine generator, online crack monitoring of the variable-pitch bearing can be achieved through an acoustic emission technology, the influence of a shielding object is avoided, reliability is high, crack faults can be found in the crack initiation stage, compared with monitoring technologies such as manual troubleshooting and video troubleshooting, cracks can be found earlier, and planned maintenance can be achieved.
additional aspects and/or advantages of the invention 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 invention.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings, in which:
Fig. 1 is a schematic diagram showing the structure of a conventional video monitoring system;
FIG. 2 is a block diagram illustrating an existing video surveillance system;
FIG. 3 is a block diagram illustrating a crack monitoring system for a pitch bearing of a wind turbine according to an embodiment of the invention;
FIG. 4 is a diagram illustrating mounting locations of acoustic emission sensors according to an embodiment of the present invention;
FIG. 5 is a diagram illustrating an installation location of an acoustic emission sensor according to another embodiment of the present invention;
FIG. 6A is a distribution diagram illustrating valid data for a faulty pitch bearing according to an embodiment of the invention;
FIG. 6B is a distribution graph showing valid data for a normal pitch bearing according to an embodiment of the invention;
FIG. 7A is a schematic diagram illustrating an original acquired acoustic emission signal of a faulty pitch bearing according to an embodiment of the present invention;
FIG. 7B is a schematic diagram showing a raw acquired acoustic emission signal of a normal pitch bearing according to an embodiment of the invention;
FIG. 8A is a schematic diagram illustrating a Fourier transformed acoustic emission signal of a faulty pitch bearing according to an embodiment of the present invention;
FIG. 8B is a schematic diagram showing acoustic emission signals after Fourier transform of a normal pitch bearing according to an embodiment of the invention;
FIG. 9 is a flow chart illustrating a crack monitoring method for a pitch bearing of a wind turbine according to an embodiment of the invention.
Detailed Description
Embodiments of the present invention are described in detail below with reference to the accompanying drawings.
FIG. 3 is a block diagram illustrating a crack monitoring system for a pitch bearing of a wind turbine according to an embodiment of the invention.
As shown in fig. 3, a crack monitoring system of a pitch bearing of a wind turbine according to an embodiment of the invention comprises a plurality of acoustic emission sensors 301 and a controller 302.
it is clear to a person skilled in the art that a wind turbine typically comprises three blades, one pitch bearing for each blade, i.e. a wind turbine typically comprises three pitch bearings. At least one acoustic emission sensor 301 is provided corresponding to each pitch bearing.
The at least one acoustic emission sensor 301 is mounted on the hub in proximity to the corresponding pitch bearing and is configured to acquire acoustic emission signals of the corresponding pitch bearing. Acoustic emission sensor 301 may be any of a variety of devices that may acquire an acoustic emission signal. For example, acoustic emission sensor 301 may be an R6A acoustic emission probe. The data line of the acoustic emission sensor 301 is arranged along the hub, enters the hub and is connected with a measurement and control cabinet in the hub.
In a preferred embodiment, in order to be able to fully collect acoustic emission signals for high risk areas where the pitch bearing is prone to cracking and to reduce monitoring costs, an acoustic emission sensor 301 is provided for each pitch bearing.
Fig. 4 is a diagram illustrating a mounting position of an acoustic emission sensor according to an embodiment of the present invention. As shown in fig. 4, the acoustic emission sensor 301 is mounted on the hub close to the pitch bearing 0 scale when the blade is in the feathered state. Therefore, in the blade pitch-retracting process, the pitch bearing rotates clockwise, the trailing edge region which is easy to crack sequentially passes through the position where the acoustic emission sensor 301 is installed, and therefore the acoustic emission signal of the trailing edge region which is easy to crack of the pitch bearing can be collected by arranging the acoustic emission sensor 301.
The controller 302 is mounted within the hub. For example, the controller 302 is mounted in a test cabinet within the hub. The inside of the measurement and control cabinet can also be provided with a power supply, a wireless module, a lightning protection module and the like.
The controller 302 is configured to, when the blade is in a pitch-retracting state, start crack monitoring, that is, control each acoustic emission sensor 301 to collect an acoustic emission signal of the corresponding pitch bearing, acquire an acoustic emission signal of the corresponding pitch bearing from each acoustic emission sensor 301, and determine whether each pitch bearing has a crack according to the acoustic emission signals of all the pitch bearings.
In a preferred embodiment, to reduce unnecessary monitoring, the controller 302 is configured to initiate crack monitoring when the trigger condition is met.
The triggering condition is used to start each acoustic emission sensor 301, that is, each acoustic emission sensor 301 is controlled to start collecting the acoustic emission signal of the corresponding pitch bearing.
The trigger condition includes the controller 302 detecting a pitch signal and exceeding a first predetermined time from the last crack monitoring. The controller 302 detects that the feathering signal indicates that a feathering operation is about to be performed. The first predetermined time is the shortest interval time for crack monitoring, and can be set according to actual conditions, such as one day. When the controller 302 detects that the feathering operation is about to be performed and the distance from the last crack monitoring exceeds the shortest interval time, the controller 302 starts the crack monitoring, so that the crack monitoring and the feathering operation are performed simultaneously.
As another example, the triggering condition may further include exceeding a second predetermined time from the last crack monitoring. The second predetermined time is the longest interval time of crack monitoring, and can be set according to actual conditions, and for example, can be three days. When the controller 302 detects that the maximum interval time is exceeded by the last crack monitoring, the controller 302 starts crack monitoring and starts a feathering operation so that the crack monitoring is performed simultaneously with the feathering operation.
In addition, in order to ensure the accuracy of crack monitoring, the wind turbine generator needs to be in a shutdown state before crack monitoring is started.
When the trigger condition is met and the blade is in the state of retracting the propeller, the controller 302 controls each acoustic emission sensor 301 to start collecting the acoustic emission signal of the corresponding pitch bearing, and after the propeller retracting operation is completed, controls each acoustic emission sensor 301 to finish collecting the acoustic emission signal of the corresponding pitch bearing.
The acoustic emission sensor 301 stores the acquired acoustic emission signals.
in a preferred embodiment, in order to reduce the amount of data stored in acoustic emission sensors 301, each acoustic emission sensor 301 takes an acoustic emission signal whose amplitude is greater than a threshold value in the collected acoustic emission signals as valid data, and stores the acoustic emission signal whose amplitude is less than the threshold value as invalid data, and does not store the data.
the threshold value is the peak value of the amplitude of the acoustic emission signal of the non-cracked pitch bearing.
Alternatively, the peak value of the amplitude of the acoustic emission signal of the pitch bearing of the wind turbine generator can be measured when the wind turbine generator is not put into use, and the peak value is used as a threshold value.
or measuring the peak value of the amplitude of the acoustic emission signal of the variable pitch bearing when a plurality of wind turbine generators of the same type are not put into use, and taking the average value of the measured peak values as a threshold value.
In addition, the threshold value can be updated in a machine learning mode according to historical data of acoustic emission signals of the normal variable pitch bearing. For example, the normal pitch bearing of a plurality of wind turbines of the same type which are put into use is obtained, the peak value of the amplitude of the acoustic emission signal in each crack monitoring is obtained, and the average value of the obtained peak values is used as the current threshold value.
Controller 302 acquires the acoustic emission signal of the corresponding pitch bearing from each acoustic emission sensor 301. That is, controller 302 acquires stored acoustic emission signals from each acoustic emission sensor 301.
The controller 302 determines from all of the acoustic emission signals acquired (i.e. acoustic emission signals for all of the pitch bearings) whether a crack has occurred in each pitch bearing. That is, for any one pitch bearing, the controller 302 determines whether any one pitch bearing has a crack according to the acoustic emission signal of any one pitch bearing and the acoustic emission signals of the other two pitch bearings.
Here, to make the monitoring result more accurate, the controller 302 may pre-process all acoustic emission signals. The pre-treatment may include: and carrying out Fourier transform on the acoustic emission signals, and filtering the acoustic emission signals subjected to Fourier transform to obtain the acoustic emission signals in a preset frequency range.
The predetermined frequency range refers to the frequency range within which the acoustic emission signal of the material used to make the pitch bearing is located.
The predetermined frequency range may be empirically determined, for example, may be empirically determined to be 100kHz to 150 kHz.
In addition, the preset frequency range can be updated in a machine learning mode according to historical data of acoustic emission signals of the fault pitch bearing. For example, the method includes the steps of acquiring the fault pitch bearing of a plurality of wind turbines of the same type which are put into use, acquiring the frequency of the acoustic emission signal with the strongest energy in each previous crack monitoring, and taking the average value of the acquired frequencies as the center frequency of the current preset frequency range.
The bandwidth of the current predetermined frequency range may be empirically determined, for example, may be empirically determined to be 50 kHz. In addition, the bandwidth can be updated in a machine learning mode according to historical data of acoustic emission signals of the fault pitch bearing. For example, calculating the fault pitch bearing of a plurality of wind turbines of the same model which are put into use, monitoring the bandwidth of the preset frequency range in each previous crack, and taking the maximum bandwidth of the calculated bandwidths of the plurality of preset frequency ranges as the bandwidth of the current preset frequency range. The bandwidth of the predetermined frequency range in any previous crack detection may be determined by: the frequency of the acoustic emission signal with the strongest energy of the fault pitch bearing in any previous crack monitoring is used as the center frequency of any crack monitoring, the spectrum envelope curve with the center frequency as the center covers a preset proportion (for example, 80%) of area, and the bandwidth of the corresponding frequency range is used as the bandwidth of the preset frequency in any crack monitoring.
The controller 302 calculates comparison data for each pitch bearing, which is the sum of the squares of the amplitudes of the acoustic emission signals within a predetermined frequency range for each bearing.
The controller 302 compares the comparison data of each pitch bearing with a predetermined multiple of the greater value of the comparison data of the other two pitch bearings, and determines the pitch bearing with the comparison data greater than the predetermined multiple of the greater value as a failed pitch bearing with a crack.
The predetermined multiple may be determined empirically, and may be, for example, 10 times. That is, the controller 302 compares the comparison data of each pitch bearing with 10 times of the larger value of the comparison data of the other two pitch bearings, determines the pitch bearing with the comparison data larger than 10 times of the larger value as the faulty pitch bearing with cracks, and determines the pitch bearing with the comparison data smaller than or equal to 10 times of the larger value as the normal pitch bearing without cracks.
The controller 302 may send the crack monitoring result to a main controller of the wind turbine. And the main controller can prompt a user to repair or maintain the fault variable pitch bearing according to the crack monitoring result. For example, the controller 302 may send the crack detection results by sending a predetermined form of data, with different data representing different crack detection results. For example, 000 indicates no fault, 100 indicates cracking for pitch bearing number 1, 010 indicates cracking for pitch bearing number 2, and 001 indicates cracking for pitch bearing number 3.
The time when the variable pitch bearing is monitored for the first time until cracks appear is the time when the cracks are initiated.
In a preferred embodiment, the controller 302 may also determine the propagation of a crack of a faulty pitch bearing from all acoustic emission signals. The expansion case may include an expansion region and an expansion speed. And a user can perform planned maintenance on the fault variable pitch bearing according to the crack propagation condition of the fault variable pitch bearing.
For the propagation region, the crack of the pitch bearing typically propagates in the axial direction of the pitch bearing. The controller 302 divides the comparison data of the faulty pitch bearing by the larger of the comparison data of the other two pitch bearings to obtain a quotient and determines the size of the propagation area of the crack from the quotient. Here, the correspondence relationship between the quotient and the size of the propagation region of the crack may be set in advance. The correspondence may be determined empirically. And determining the size of the crack propagation area of the fault variable pitch bearing according to the quotient and the corresponding relation between the quotient and the size of the crack propagation area.
For the propagation speed, the controller 302 may determine the propagation speed of the crack according to the energy change speed of the acoustic emission signal with the strongest energy in the multiple crack monitoring of the faulty pitch bearing. A faster energy change rate indicates a faster crack propagation rate.
In a preferred embodiment, the controller 302 may also determine the location of crack initiation based on the acoustic emission signal of the failed pitch bearing. The controller 302 further determines, for a faulty pitch bearing with a crack, a position on the faulty pitch bearing, which is directly opposite to the acoustic emission sensor, at a first moment when the acoustic emission signal with the strongest energy appears in the process of collecting the acoustic emission signal of the faulty pitch bearing, as a position where the crack in the faulty pitch bearing is initiated. That is, the position on the faulty pitch bearing directly opposite the acoustic emission sensor at the first moment is determined as the position of crack initiation in the faulty pitch bearing. Therefore, a user can accurately maintain or repair the fault pitch bearing according to the crack initiation position.
Specifically, for a faulty pitch bearing with a crack, the controller 302 determines the position of the faulty pitch bearing directly facing the acoustic emission sensor at the first moment according to the initial position of the faulty pitch bearing before the pitch taking, the rotation speed of the faulty pitch bearing, and the first moment. The initial position can be represented as a position on the fault pitch bearing where the acoustic emission sensor is right before the pitch of the fault pitch bearing is taken down, and the initial position can be determined according to the pitch angle of the fault pitch bearing before the pitch is taken down. Here, the time from the initial time to the first time indicates the rotation time spent by the faulty pitch bearing to rotate from the initial position to the crack initiation position, the rotation time is multiplied by the rotation speed to obtain the rotation distance, the rotation distance is added to the initial position to obtain the position on the faulty pitch bearing, and at the first time, the acoustic emission sensor faces the position on the faulty pitch bearing.
In a preferred embodiment, in order to more accurately locate the crack initiation, three acoustic emission sensors 301 are provided for each pitch bearing, i.e. two further acoustic emission sensors 301 are provided in addition to the one acoustic emission sensor 301 mounted on the hub close to the pitch bearing 0 scale when the blade is in the feathered state.
FIG. 5 is a block diagram illustrating an installation location of an acoustic emission sensor according to another embodiment of the present invention. As shown in fig. 5, two other acoustic emission sensors 301 are disposed on both sides of the one acoustic emission sensor 301. Two additional acoustic emission sensors 301 are used to further determine the location of crack initiation. For example, the side of the acoustic emission sensor 301 where the acoustic emission sensor 301 acquires an acoustic emission signal with stronger energy intensity may be determined as the crack initiation position by comparing the energy intensity of the acoustic emission signals acquired by the other two acoustic emission sensors 301 at the first time.
The above mainly describes the way of crack monitoring for the trailing edge region of the pitch bearing where cracks are likely to occur, and it can be understood that the cracks can also be monitored for other regions of the pitch bearing by installing acoustic emission sensors at other positions. For example, an acoustic emission sensor is installed at a position on the hub close to the 180-degree scale of the pitch bearing when the blades are in the pitch pulling state to monitor cracks in the leading edge region of the pitch bearing, except that the installation positions of the acoustic emission sensors are not consistent, the monitoring mode is consistent with the above-mentioned crack monitoring mode in the trailing edge region, and details are not repeated here.
Fig. 6A to 8B show information about acoustic emission signals of a faulty pitch bearing and a normal pitch bearing, respectively, according to an embodiment of the invention.
FIGS. 6A and 6B show a distribution diagram of valid data for a faulty pitch bearing and a normal pitch bearing, respectively, according to an embodiment of the invention. As shown in FIG. 6A, the acoustic emission signal of the failed pitch bearing includes a plurality of valid data 601. As shown in FIG. 6B, there is no valid data in the acoustic emission signal for a normal pitch bearing.
FIGS. 7A and 7B show schematic diagrams of the original acquired acoustic emission signals of a faulty pitch bearing and a normal pitch bearing, respectively, according to an embodiment of the invention. As shown in FIG. 7A, the amplitude of part of the acoustic emission signals in the acoustic emission signals of the failed pitch bearing is high. As shown in FIG. 7B, all acoustic emission signals of a normal pitch bearing have amplitudes within the normal range.
FIGS. 8A and 8B show schematic diagrams of acoustic emission signals after Fourier transform for a faulty pitch bearing and a normal pitch bearing, respectively, according to an embodiment of the invention. As shown in FIG. 8A, the amplitude of the acoustic emission signal of the failed pitch bearing at a Fourier transformed frequency between 100kHz and 150kHz is high. As shown in FIG. 8B, the amplitude of the acoustic emission signal for a normal pitch bearing with a Fourier transformed frequency between 100kHz and 150kHz is within the normal range.
FIG. 9 is a flow chart illustrating a crack monitoring method for a pitch bearing of a wind turbine according to an embodiment of the invention.
It is clear to a person skilled in the art that a wind turbine typically comprises three blades, one pitch bearing for each blade, i.e. a wind turbine typically comprises three pitch bearings. In the crack monitoring method for the pitch bearing of the wind turbine generator, at least one acoustic emission sensor is arranged corresponding to each pitch bearing.
The at least one acoustic emission sensor is mounted on the hub proximate to the corresponding pitch bearing and is configured to acquire acoustic emission signals of the corresponding pitch bearing. The acoustic emission sensor can be any of a variety of devices that can acquire an acoustic emission signal. For example, the acoustic emission sensor may be an R6A acoustic emission probe. And a data line of the acoustic emission sensor is arranged along the hub, enters the hub and is connected with a measurement and control cabinet in the hub.
In a preferred embodiment, in order to comprehensively acquire acoustic emission signals of high-risk areas where the pitch bearing is prone to cracking and reduce monitoring cost, an acoustic emission sensor is arranged corresponding to each pitch bearing, and specific installation positions can be referred to fig. 4.
Referring to fig. 9, in step S901, when the blade is in the state of retracting the pitch, crack monitoring is started, that is, each acoustic emission sensor is controlled to acquire an acoustic emission signal of a corresponding pitch bearing.
in step S902, acoustic emission signals of the corresponding pitch bearing are acquired from each acoustic emission sensor.
In step S903, whether cracks occur in each pitch bearing is determined according to the acoustic emission signals of all the pitch bearings.
In a preferred embodiment, in step S901, crack monitoring is initiated when the trigger condition is met.
The triggering condition is used for starting each acoustic emission sensor, namely controlling each acoustic emission sensor to start collecting the acoustic emission signal of the corresponding variable pitch bearing.
the triggering condition includes detecting a pitch pull signal and exceeding a first predetermined time from the last crack monitoring. The detected paddle withdrawing signal indicates that the paddle withdrawing operation is about to be carried out. The first predetermined time is the shortest interval time for crack monitoring, and can be set according to actual conditions, such as one day. And when the propeller retracting operation is detected to be about to be carried out and the distance from the last crack monitoring exceeds the shortest interval time, starting the crack monitoring, so that the crack monitoring and the propeller retracting operation are carried out simultaneously.
As another example, the triggering condition may further include exceeding a second predetermined time from the last crack monitoring. The second predetermined time is the longest interval time of crack monitoring, and can be set according to actual conditions, and for example, can be three days. When the crack monitoring exceeds the longest interval time at the last time of detection, the crack monitoring is started, and the propeller retracting operation is started, so that the crack monitoring and the propeller retracting operation are carried out simultaneously.
in addition, in order to ensure the accuracy of crack monitoring, the wind turbine generator needs to be in a shutdown state before crack monitoring is started.
and when the triggering conditions are met and the blade is in a state of retracting the propeller, controlling each acoustic emission sensor to start collecting the acoustic emission signal of the corresponding pitch bearing, and after the propeller retracting operation is finished, controlling each acoustic emission sensor to finish collecting the acoustic emission signal of the corresponding pitch bearing.
And the acoustic emission sensor stores the acquired acoustic emission signals.
In a preferred embodiment, in order to reduce the amount of data stored by the acoustic emission sensors, each acoustic emission sensor takes the acoustic emission signals with the amplitude larger than the threshold value in the collected acoustic emission signals as valid data, and stores the acoustic emission signals with the amplitude smaller than the threshold value as invalid data, and does not store the invalid data.
The threshold value is the peak value of the amplitude of the acoustic emission signal of the non-cracked pitch bearing.
Alternatively, the peak value of the amplitude of the acoustic emission signal of the pitch bearing of the wind turbine generator can be measured when the wind turbine generator is not put into use, and the peak value is used as a threshold value.
Or measuring the peak value of the amplitude of the acoustic emission signal of the variable pitch bearing when a plurality of wind turbine generators of the same type are not put into use, and taking the average value of the measured peak values as a threshold value.
in addition, the threshold value can be updated in a machine learning mode according to historical data of acoustic emission signals of the normal variable pitch bearing. For example, the normal pitch bearing of a plurality of wind turbines of the same type which are put into use is obtained, the peak value of the amplitude of the acoustic emission signal in each crack monitoring is obtained, and the average value of the obtained peak values is used as the current threshold value.
In step S902, acoustic emission signals of the corresponding pitch bearing are acquired from each acoustic emission sensor. That is, stored acoustic emission signals are acquired from the respective acoustic emission sensors.
In step S903, it is determined whether each pitch bearing has a crack according to all the acquired acoustic emission signals (i.e. acoustic emission signals of all pitch bearings). Namely, for any one pitch bearing, whether any one pitch bearing has a crack is determined according to the acoustic emission signal of any one pitch bearing and the acoustic emission signals of the other two pitch bearings.
here, in order to make the monitoring result more accurate, all acoustic emission signals may be preprocessed first. The pre-treatment may include: and carrying out Fourier transform on the acoustic emission signals, and filtering the acoustic emission signals subjected to Fourier transform to obtain the acoustic emission signals in a preset frequency range.
The predetermined frequency range refers to the frequency range within which the acoustic emission signal of the material used to make the pitch bearing is located.
the predetermined frequency range may be empirically determined, for example, may be empirically determined to be 100kHz to 150 kHz.
In addition, the preset frequency range can be updated in a machine learning mode according to historical data of acoustic emission signals of the fault pitch bearing. For example, the method includes the steps of acquiring the fault pitch bearing of a plurality of wind turbines of the same type which are put into use, acquiring the frequency of the acoustic emission signal with the strongest energy in each previous crack monitoring, and taking the average value of the acquired frequencies as the center frequency of the current preset frequency range.
The bandwidth of the current predetermined frequency range may be empirically determined, for example, may be empirically determined to be 50 kHz. In addition, the bandwidth can be updated in a machine learning mode according to historical data of acoustic emission signals of the fault pitch bearing. For example, calculating the fault pitch bearing of a plurality of wind turbines of the same model which are put into use, monitoring the bandwidth of the preset frequency range in each previous crack, and taking the maximum bandwidth of the calculated bandwidths of the plurality of preset frequency ranges as the bandwidth of the current preset frequency range. The bandwidth of the predetermined frequency range in any previous crack detection may be determined by: the frequency of the acoustic emission signal with the strongest energy of the fault pitch bearing in any previous crack monitoring is used as the center frequency of any crack monitoring, the spectrum envelope curve with the center frequency as the center covers a preset proportion (for example, 80%) of area, and the bandwidth of the corresponding frequency range is used as the bandwidth of the preset frequency in any crack monitoring.
In step S903, comparison data of each pitch bearing is calculated, and the comparison data of each pitch bearing is the sum of squares of the amplitudes of the acoustic emission signals in the predetermined frequency range of each bearing.
And comparing the comparison data of each variable pitch bearing with a preset multiple of a larger value in the comparison data of the other two variable pitch bearings, and determining the variable pitch bearing of which the comparison data is larger than the preset multiple of the larger value as a fault variable pitch bearing with cracks.
The predetermined multiple may be determined empirically, and may be, for example, 10 times. Namely, the comparison data of each pitch bearing is compared with 10 times of the larger value of the comparison data of the other two pitch bearings, the pitch bearing with the comparison data larger than 10 times of the larger value is determined as a fault pitch bearing with cracks, and the pitch bearing with the comparison data smaller than or equal to 10 times of the larger value is determined as a normal pitch bearing without cracks.
the crack monitoring result can be sent to a main controller of the wind turbine generator. And the main controller can prompt a user to repair or maintain the fault variable pitch bearing according to the crack monitoring result. For example, the crack monitoring results may be transmitted by transmitting a predetermined form of data, with different data representing different crack monitoring results. For example, 000 indicates no fault, 100 indicates cracking for pitch bearing number 1, 010 indicates cracking for pitch bearing number 2, and 001 indicates cracking for pitch bearing number 3.
The time when the variable pitch bearing is monitored for the first time until cracks appear is the time when the cracks are initiated.
In a preferred embodiment, the crack monitoring method for the pitch bearing of the wind turbine generator according to the embodiment of the present invention may further include the following steps (not shown in the figure): and determining the crack propagation condition of the fault variable pitch bearing according to all the acoustic emission signals. The expansion case may include an expansion region and an expansion speed. And a user can perform planned maintenance on the fault variable pitch bearing according to the crack propagation condition of the fault variable pitch bearing.
For the propagation region, the crack of the pitch bearing typically propagates in the axial direction of the pitch bearing. The comparison data of the faulty pitch bearing may be divided by the larger of the comparison data of the two other pitch bearings to obtain a quotient, and the size of the propagation area of the crack may be determined from the quotient. Here, the correspondence relationship between the quotient and the size of the propagation region of the crack may be set in advance. The correspondence may be determined empirically. And determining the size of the crack propagation area of the fault variable pitch bearing according to the quotient and the corresponding relation between the quotient and the size of the crack propagation area.
For the propagation speed, the propagation speed of the crack can be determined according to the energy change speed of the acoustic emission signal with the strongest energy in the multiple crack monitoring of the fault variable pitch bearing. A faster energy change rate indicates a faster crack propagation rate.
in a preferred embodiment, the crack monitoring method for the pitch bearing of the wind turbine generator according to the embodiment of the present invention may further include the following steps (not shown in the figure): and determining the crack initiation position according to the acoustic emission signal of the fault variable pitch bearing. The position on the fault pitch bearing, which is just opposite to the acoustic emission sensor, at the first moment when the acoustic emission signal with the strongest energy appears in the process of collecting the acoustic emission signal of the fault pitch bearing can be determined as the position where the crack in the fault pitch bearing is initiated. That is, the position on the faulty pitch bearing directly opposite the acoustic emission sensor at the first moment is determined as the position of crack initiation in the faulty pitch bearing. Therefore, a user can accurately maintain or repair the fault pitch bearing according to the crack initiation position.
Specifically, for a fault variable pitch bearing with a crack, the position on the fault variable pitch bearing opposite to the acoustic emission sensor at the first moment can be determined according to the initial position of the fault variable pitch bearing before pitch taking, the rotating speed of the fault variable pitch bearing and the first moment. The initial position can be represented as a position on the fault pitch bearing where the acoustic emission sensor is right before the pitch of the fault pitch bearing is taken down, and the initial position can be determined according to the pitch angle of the fault pitch bearing before the pitch is taken down. Here, the time from the initial time to the first time indicates the rotation time taken by the faulty pitch bearing to rotate from the initial position to the position where the crack is initiated, the rotation time is multiplied by the rotation speed to obtain the rotation distance, the rotation distance is added to the initial position to obtain the position on the faulty pitch bearing directly opposite to the acoustic emission sensor at the first time.
in a preferred embodiment, in order to more accurately locate the crack initiation position, three acoustic emission sensors are provided corresponding to each pitch bearing, namely, two acoustic emission sensors are provided in addition to the acoustic emission sensor mounted on the hub close to the pitch bearing 0 scale when the blade is in the feathering state, and the specific mounting position refers to fig. 5.
the above mainly describes the way of crack monitoring for the trailing edge region of the pitch bearing where cracks are likely to occur, and it can be understood that the cracks can also be monitored for other regions of the pitch bearing by installing acoustic emission sensors at other positions. For example, an acoustic emission sensor is installed at a position on the hub close to the 180-degree scale of the pitch bearing when the blades are in the pitch pulling state to monitor cracks in the leading edge region of the pitch bearing, except that the installation positions of the acoustic emission sensors are not consistent, the monitoring mode is consistent with the above-mentioned crack monitoring mode in the trailing edge region, and details are not repeated here.
The invention further provides a wind turbine generator which comprises the crack monitoring system of the variable-pitch bearing.
The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the crack monitoring method as described above.
According to the wind turbine generator and the crack monitoring system and method of the variable pitch bearing of the wind turbine generator, the crack of the variable pitch bearing can be monitored on line through an acoustic emission technology, the influence of a shielding object is avoided, the reliability is high, the crack fault can be found in the crack initiation stage, the crack can be found earlier than the crack fault can be found through monitoring technologies such as manual troubleshooting and video troubleshooting, and planned maintenance can be achieved. In addition, the labor cost, the time cost and the possible missing detection caused by manual inspection can be avoided, and the problem that the machine set faults are caused due to the fact that the manual inspection is not found in time due to long interval time of the manual inspection is avoided.
While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present invention as defined by the following claims.
Claims (18)
1. The utility model provides a crack monitoring system of wind turbine generator system's change oar bearing which characterized in that includes:
A plurality of acoustic emission sensors, wherein at least one acoustic emission sensor is provided corresponding to each pitch bearing, the at least one acoustic emission sensor being mounted on the hub in proximity to the corresponding pitch bearing and configured to acquire acoustic emission signals of the corresponding pitch bearing;
The controller is installed in the hub and configured to control each acoustic emission sensor to acquire the acoustic emission signal of the corresponding variable pitch bearing, acquire the acoustic emission signal of the corresponding variable pitch bearing from each acoustic emission sensor, and determine whether each variable pitch bearing has cracks according to the acoustic emission signals of all the variable pitch bearings.
2. The crack monitoring system of claim 1, wherein one acoustic emission sensor is provided for each pitch bearing, the one acoustic emission sensor being mounted on the hub close to the pitch bearing 0 scale when the blade is in the feathered state.
3. The crack monitoring system of claim 2, wherein the controller is further configured to: and aiming at the fault pitch bearing with the crack, determining the position on the fault pitch bearing, which is just opposite to the acoustic emission sensor, as the crack initiation position when the acoustic emission signal with the strongest energy occurs at the first moment in the process of acquiring the acoustic emission signal.
4. The crack monitoring system of claim 3, wherein the controller is further configured to: and aiming at the fault variable pitch bearing with the crack, determining the position on the fault variable pitch bearing, which is just opposite to the acoustic emission sensor, at the first moment according to the initial position, the rotating speed and the first moment of the fault variable pitch bearing before pitch withdrawing.
5. The crack monitoring system of claim 1, wherein the controller is configured to: fourier transform is carried out on the acoustic emission signals of each variable pitch bearing, the acoustic emission signals after Fourier transform are filtered to obtain acoustic emission signals in a preset frequency range, comparison data of each variable pitch bearing are respectively calculated, the comparison data of each variable pitch bearing are compared with preset multiples of a larger value in the comparison data of other two variable pitch bearings, the variable pitch bearing of which the comparison data is larger than the preset multiples of the larger value is determined as a fault variable pitch bearing with cracks,
Wherein the comparison data for each pitch bearing is the sum of the squares of the amplitudes of the acoustic emission signals within the predetermined frequency range for each pitch bearing.
6. The crack monitoring system of claim 5, wherein the controller is further configured to: and for the fault variable-pitch bearing, dividing the comparison data of the fault variable-pitch bearing by the larger value in the comparison data of the other two variable-pitch bearings to obtain a quotient, and determining the size of the expansion area of the crack according to the quotient.
7. The crack monitoring system of claim 1, wherein three acoustic emission sensors are provided for each pitch bearing, wherein one acoustic emission sensor is mounted on the hub close to the pitch bearing 0 scale when the blade is in the feathered state, and two acoustic emission sensors are mounted on either side of the acoustic emission sensor.
8. The crack monitoring system of claim 1, wherein each acoustic emission sensor stores an acoustic emission signal having an amplitude greater than a threshold value in the collected acoustic emission signals, and the controller obtains the stored acoustic emission signal from each acoustic emission sensor.
9. The crack monitoring system of claim 8, wherein the threshold value is a peak value of the amplitude of the acoustic emission signal of the pitch bearing when the wind turbine generator has not been put into use, or an average value of the peak values of the amplitudes of the acoustic emission signals of the pitch bearing when a plurality of wind turbine generators of the same type have not been put into use.
10. The crack monitoring system of claim 1, wherein the controller is configured to control each acoustic emission sensor to acquire an acoustic emission signal of the corresponding pitch bearing when the following triggering conditions are met: the controller detects a paddle retracting signal and the distance between the paddle retracting signal and the last crack monitoring exceeds a first preset time, or the distance between the paddle retracting signal and the last crack monitoring exceeds a second preset time.
11. Wind turbine comprising a crack monitoring system for a pitch bearing according to any of claims 1-10.
12. The crack monitoring method for the variable-pitch bearing of the wind turbine generator is characterized by comprising the following steps of:
Controlling each acoustic emission sensor to collect an acoustic emission signal of the corresponding pitch bearing, wherein at least one acoustic emission sensor is arranged corresponding to each pitch bearing, and the at least one acoustic emission sensor is arranged on the hub close to the corresponding pitch bearing;
Acquiring acoustic emission signals of corresponding variable pitch bearings from each acoustic emission sensor;
And determining whether each pitch bearing has cracks according to the acoustic emission signals of all the pitch bearings.
13. The crack monitoring method of claim 12, further comprising:
And aiming at the fault pitch bearing with the crack, determining the position on the fault pitch bearing, which is just opposite to the acoustic emission sensor, as the crack initiation position at the first moment when the acoustic emission signal with the strongest energy appears in the process of acquiring the acoustic emission signal.
14. the crack monitoring method of claim 13, further comprising:
And aiming at the fault variable pitch bearing with the crack, determining the position on the fault variable pitch bearing, which is just opposite to the acoustic emission sensor, at the first moment according to the initial position, the rotating speed and the first moment of the fault variable pitch bearing before pitch withdrawing.
15. The crack monitoring method of claim 12, wherein the step of determining whether a crack has occurred in each pitch bearing based on the acoustic emission signals of all pitch bearings comprises:
Fourier transformation is carried out on the acoustic emission signals of each variable pitch bearing;
Filtering the acoustic emission signals subjected to Fourier transform to obtain acoustic emission signals in a preset frequency range;
Respectively calculating comparison data of each variable pitch bearing;
Comparing the comparison data of each pitch bearing with a predetermined multiple of the greater value of the comparison data of the other two pitch bearings, determining the pitch bearing with the comparison data greater than the predetermined multiple of the greater value as a failed pitch bearing with cracks,
Wherein the comparison data for each pitch bearing is the sum of the squares of the amplitudes of the acoustic emission signals within the predetermined frequency range for each pitch bearing.
16. The crack monitoring method of claim 15, further comprising:
And for the fault variable-pitch bearing, dividing the comparison data of the fault variable-pitch bearing by the larger value in the comparison data of the other two variable-pitch bearings to obtain a quotient, and determining the size of the expansion area of the crack according to the quotient.
17. The crack monitoring method of claim 12, wherein the step of controlling each acoustic emission sensor to acquire an acoustic emission signal of a corresponding pitch bearing comprises: when the following triggering conditions are met, controlling each acoustic emission sensor to acquire the acoustic emission signal of the corresponding pitch bearing: and detecting a propeller retracting signal and exceeding a first preset time from the last crack monitoring, or exceeding a second preset time from the last crack monitoring.
18. a computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the crack monitoring method as claimed in any one of claims 12 to 17.
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Application publication date: 20191210 |