CN114689320A

CN114689320A - Wind turbine generator bearing fault detection method and device, controller and storage medium

Info

Publication number: CN114689320A
Application number: CN202011609194.7A
Authority: CN
Inventors: 宋明彦; 张凯; 周杰
Original assignee: Beijing Goldwind Science and Creation Windpower Equipment Co Ltd
Current assignee: Beijing Goldwind Science and Creation Windpower Equipment Co Ltd
Priority date: 2020-12-30
Filing date: 2020-12-30
Publication date: 2022-07-01

Abstract

The application discloses a wind turbine generator bearing fault detection method, a wind turbine generator bearing fault detection device, a wind turbine generator bearing fault detection controller and a storage medium. The method for detecting the bearing fault of the wind turbine generator comprises the steps of obtaining operation parameters of the wind turbine generator, wherein the operation parameters comprise the acceleration of an engine room and the rotating speed of the wind turbine generator; under the condition that the rotating speed is in a stable state, carrying out high-pass filtering on the acceleration of the engine room to obtain a target acceleration within a preset frequency range; extracting frequency domain characteristics of the target acceleration; and detecting whether the bearing of the wind turbine generator is in fault or not according to the frequency domain characteristics and the rotating speed. By the aid of the wind turbine bearing fault detection method, the wind turbine bearing fault detection device, the wind turbine bearing fault detection controller and the storage medium, power generation performance of the wind turbine can be improved, and service life of the wind turbine can be prolonged.

Description

Wind turbine generator bearing fault detection method and device, controller and storage medium

Technical Field

The application relates to the technical field of wind power generation, in particular to a wind turbine generator bearing fault detection method, a wind turbine generator bearing fault detection device, a wind turbine generator bearing fault detection controller and a storage medium.

Background

The bearing is used as an important component of the wind turbine generator, and once the bearing breaks down, the power generation performance and the service life of the wind turbine generator are affected. Therefore, it is also important to detect the fault of the bearing of the wind turbine.

At present, a temperature detection method is usually adopted for detecting the fault of the bearing. Specifically, a temperature sensor can be used for collecting the temperature of the bearing, and when the temperature reaches a set temperature threshold value, the fault occurrence of the overhigh temperature of the bearing is prompted. However, as the bearing wears more heavily, the temperature of the bearing will rise significantly. Therefore, the bearing can be detected to be out of order only after the bearing is abraded seriously, and therefore the wind turbine generator can be operated in a sub-health state for a long time, and the power generation performance and the service life of the wind turbine generator can be influenced.

Disclosure of Invention

The embodiment of the application aims to provide a wind turbine bearing fault detection method, a wind turbine bearing fault detection device, a wind turbine bearing fault detection controller and a storage medium, and aims to solve the technical problem that in the prior art, a bearing can only be detected to have a fault after the bearing is seriously worn, so that the wind turbine runs in a sub-health state for a long time, and the power generation performance and the service life of the wind turbine are further influenced.

The technical scheme of the application is as follows:

in a first aspect, a wind turbine generator bearing fault detection method is provided, including:

acquiring operation parameters of a wind turbine generator, wherein the operation parameters comprise cabin acceleration and rotating speed of the wind turbine generator;

under the condition that the rotating speed is in a stable state, carrying out high-pass filtering on the acceleration of the engine room to obtain a target acceleration within a preset frequency range;

extracting frequency domain characteristics of the target acceleration;

and detecting whether the bearing of the wind turbine generator has a fault or not according to the frequency domain characteristics and the rotating speed.

In a second aspect, a wind turbine generator bearing fault detection apparatus is provided, including:

the acquisition module is used for acquiring the operating parameters of the wind turbine generator, wherein the operating parameters comprise the acceleration of an engine room and the rotating speed of the wind turbine generator;

the filtering module is used for carrying out high-pass filtering on the acceleration of the engine room under the condition that the rotating speed is in a stable state to obtain a target acceleration within a preset frequency range;

the extraction module is used for extracting the frequency domain characteristics of the target acceleration;

and the detection module is used for detecting whether the bearing of the wind turbine generator fails or not according to the frequency domain characteristics and the rotating speed.

In a third aspect, a controller is provided, which may include:

a processor; and a memory storing computer program instructions;

the processor reads and executes the computer program instructions, and the processor reads and executes the computer program instructions to implement the wind turbine generator bearing fault detection method shown in any embodiment of the first aspect.

In a fourth aspect, a readable storage medium is provided, on which computer program instructions are stored, which when executed by a processor implement the wind turbine generator set bearing fault detection method as shown in any of the embodiments of the first aspect.

The technical scheme provided by the embodiment of the application at least has the following beneficial effects:

according to the method and the device, the operating parameters of the wind turbine generator, including the acceleration of the engine room and the rotating speed of the wind turbine generator, are obtained, high-pass filtering is conducted on the acceleration of the engine room under the condition that the rotating speed is in a stable state, the target acceleration in a preset frequency range is obtained, the frequency domain characteristics of the target acceleration are extracted, and whether the bearing of the wind turbine generator breaks down or not is detected according to the frequency domain characteristics and the rotating speed of the target acceleration. Therefore, the nacelle acceleration changes obviously when the bearing is slightly worn or foreign matters exist, so that the bearing of the wind turbine generator can be detected to break down when the bearing is slightly worn or foreign matters exist based on the nacelle acceleration, the bearing of the wind turbine generator can be maintained in early failure, the wind turbine generator can be prevented from operating in a sub-health state for a long time, and the power generation performance and the service life of the wind turbine generator are improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the application and are not to be construed as limiting the application.

FIG. 1 is a frequency spectrum diagram of an acceleration of a nacelle according to an embodiment of the present disclosure;

FIG. 2 is a frequency spectrum diagram of an acceleration of a nacelle according to an embodiment of the present disclosure;

FIG. 3 is a frequency spectrum diagram of an acceleration of a nacelle according to an embodiment of the present disclosure;

FIG. 4 is a frequency spectrum graph of the acceleration of the nacelle provided by the embodiment of the present application;

fig. 5 is a schematic flow chart of a wind turbine generator bearing fault detection method provided in an embodiment of the present application;

fig. 6 is a schematic flow chart of a wind turbine generator bearing fault detection method provided in an embodiment of the present application;

fig. 7 is a schematic flow chart of a wind turbine generator bearing fault detection method provided in an embodiment of the present application;

fig. 8 is a schematic flow chart of a wind turbine generator bearing fault detection method provided in an embodiment of the present application;

fig. 9 is a schematic structural diagram of a wind turbine generator bearing fault detection device provided in an embodiment of the present application;

fig. 10 is a schematic structural diagram of a controller according to an embodiment of the present application.

Detailed Description

In order to make the technical solutions of the present application better understood by those of ordinary skill in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be implemented in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples do not represent all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

Based on the background art, the fault detection of the bearing is carried out by adopting a temperature detection method in the prior art, and the bearing can be detected to have a fault only after the bearing is seriously worn, so that the wind turbine generator runs in a sub-health state for a long time, and the power generation performance and the service life of the wind turbine generator are influenced.

In addition, when the wind turbine generator is in a normal operation state, no impact exists between the bearing inner ring of the wind turbine generator and the rolling body. When a bearing of the wind turbine generator fails, if the bearing is subjected to uneven friction due to cracks or foreign matters on the bearing, periodic impact is generated between a bearing inner ring of the wind turbine generator and a rolling body, and characteristic frequency and frequency multiplication are reflected in a frequency spectrogram of the acceleration of the nacelle.

Specifically, as shown in fig. 1, in a normal operation state of the wind turbine, a frequency spectrogram of the acceleration of the nacelle usually only contains low-frequency components generated by the rotation frequency of the impeller. As shown in fig. 2,3, and 4, when a bearing of a wind turbine generator has failure characteristics such as wear, foreign matter, and cracks, which cause a failure of the bearing, an inner ring of the bearing collides with a rolling element, which causes characteristic frequency and frequency doubling in a frequency spectrum diagram of an acceleration of a nacelle.

Based on the above findings, the embodiment of the application provides a wind turbine generator bearing fault detection method, device, controller and storage medium, and the method and device can be used for performing high-pass filtering on the acceleration of the nacelle to obtain the target acceleration within the preset frequency range by acquiring the operating parameters of the wind turbine generator, including the acceleration of the nacelle and the rotating speed of the wind turbine generator, under the condition that the rotating speed is in a stable state, extracting the frequency domain characteristics of the target acceleration, and then detecting whether the bearing of the wind turbine generator is in fault according to the frequency domain characteristics and the rotating speed of the target acceleration. Therefore, the nacelle acceleration changes obviously when the bearing is slightly worn or foreign matters exist, so that the bearing of the wind turbine generator can be detected to break down when the bearing is slightly worn or foreign matters exist based on the nacelle acceleration, the bearing of the wind turbine generator can be maintained in early failure, the wind turbine generator can be prevented from operating in a sub-health state for a long time, and the power generation performance and the service life of the wind turbine generator are improved.

First, a method for detecting a bearing fault of a wind turbine generator provided by an embodiment of the present application is described below.

Fig. 5 shows a schematic flow diagram of a method for detecting a bearing fault of a wind turbine generator provided in an embodiment of the present application, where an execution main body of the method may be a controller of the wind turbine generator, or may be an industrial personal computer, a cloud server, and other devices of a wind farm. As shown in fig. 5, the wind turbine generator bearing fault detection method may include the following steps:

and S510, acquiring the operation parameters of the wind turbine generator.

The operating parameters may include, among other things, the acceleration of the nacelle and the speed of the wind turbine.

In the operation process of the wind turbine generator, a vibration sensor which is arranged in a cabin and used for detecting the vibration of the whole machine or a vibration sensor of a Content Management System (CMS) which is additionally arranged on a bearing of the wind turbine generator is arranged in the wind turbine generator, and the acceleration of the cabin of the wind turbine generator is collected; the rotating speed of the wind turbine generator is acquired by a rotating speed sensor of the wind turbine generator. Then, the operating parameters of the wind turbine may be obtained, for example, the operating parameters of the wind turbine may be periodically obtained, and the operating parameters may include the acquired cabin acceleration and the acquired rotational speed of the wind turbine.

And S520, carrying out high-pass filtering on the acceleration of the engine room under the condition that the rotating speed is in a stable state to obtain the target acceleration in a preset frequency range.

The preset frequency range may be a frequency range allowed to pass through in preset high-pass filtering, and the frequency range may be set to a higher frequency range, so that the high-pass filtering process may filter out low-frequency signals generated by the impeller and other components.

The target acceleration may be a cabin acceleration that falls within a preset frequency range among the cabin accelerations.

After the operation parameters of the wind turbine generator, including the acceleration of the engine room and the rotating speed of the wind turbine generator, are obtained, whether the rotating speed of the wind turbine generator is in a stable state or not can be judged, and if the rotating speed of the wind turbine generator is in the stable state or not, the rotating speed of the wind turbine generator can be judged according to the change amplitude of the rotating speed of the wind turbine generator. How to determine whether the rotating speed of the wind turbine generator is in a stable state is described in detail below, and is not described herein again.

Under the condition that the rotating speed of the wind turbine generator is in a stable state, high-pass filtering processing is carried out on the acceleration of the engine room, the acceleration of the engine room which does not belong to the preset frequency range is filtered, and if the acceleration of the engine room which does not belong to the preset frequency range can be blocked, weakened and the like, and the target acceleration which belongs to the preset frequency range in the acceleration of the engine room is obtained. For example, the high-pass filtering may be performed by a butterworth high-pass digital filter, a chebyshev filter, a bezier filter, or the like. Therefore, only the target cabin acceleration in the preset frequency range is reserved, the low-frequency noise in the cabin acceleration can be eliminated, and the influence of the low-frequency signal on the bearing fault detection is reduced.

And S530, extracting frequency domain characteristics of the target acceleration.

Where the frequency domain feature is a coordinate system used in describing the frequency-wise characteristics of the signal, for nacelle acceleration, the frequency domain feature may typically include the frequency and amplitude of the nacelle acceleration.

After the target acceleration within the preset frequency range is obtained, the frequency domain features of the target acceleration can be extracted. For example, Fast Fourier Transform (FFT) may be performed on the target acceleration, and the frequency domain feature of the target acceleration is extracted.

And S540, detecting whether the bearing of the wind turbine generator is in fault or not according to the frequency domain characteristics and the rotating speed.

After the frequency domain characteristic of the target acceleration is extracted, whether a bearing of the wind outlet generator set breaks down or not can be detected according to the frequency domain characteristic of the cabin acceleration and the rotating speed of the front-speed wind turbine set. Therefore, by utilizing the characteristic that the frequency domain characteristic of the acceleration of the nacelle is obviously changed when the bearing is slightly damaged or foreign matters exist, the fault condition of the bearing can be identified at an early stage, so that the maintenance can be carried out aiming at the fault condition at the early stage. For example, the health condition of the bearing can be continuously observed after the grease and the operation strategy are improved by improving the grease and the operation strategy, grease detection is carried out on the bearing at regular intervals, bearing spare parts can be prepared in advance, a replacement plan is made, the unplanned downtime is reduced, and the condition of long-time unplanned downtime caused by bearing jamming is avoided.

It can be understood that, in the wind turbine generator bearing fault detection method provided by the embodiment of the present application, after the bearing of the wind turbine generator is detected to have a fault, an early warning signal may also be output, so that a worker may receive the early warning signal, where the early warning signal may include at least one of bearing fault indication information and maintenance mode information. Therefore, whether the bearing of the wind turbine generator system breaks down or not can be detected in the early stage, and the early warning signal can be sent out when the bearing of the wind turbine generator system breaks down, so that the worker can receive the early warning signal to maintain the bearing of the wind turbine generator system based on the early warning signal, and therefore the reliability and the availability of the wind turbine generator system can be improved.

In addition, in the embodiment of the application, the vibration sensor which is installed in the cabin and used for detecting the vibration of the whole machine or the vibration sensor of the CMS (content management system) additionally installed on the bearing of the wind turbine generator is used for collecting the acceleration of the cabin of the wind turbine generator, so that the bearing fault detection of the wind turbine generator is realized based on the acceleration of the cabin. Therefore, on one hand, other equipment does not need to be independently installed, the existing equipment is utilized to acquire the acceleration of the engine room, and the method for detecting the bearing fault of the wind turbine generator set, provided by the embodiment of the application, is low in cost; on the other hand, the accuracy of the existing vibration sensor installed inside the nacelle or the accuracy of the vibration sensor of the CMS is generally high, and the accuracy of the acquired nacelle acceleration is also high, so that the accuracy of the wind turbine bearing fault detection method provided by the embodiment of the application can be improved.

In some embodiments, the frequency domain feature may include an amplitude and a frequency corresponding to the amplitude, and at this time, whether a bearing of the wind turbine generator fails may be detected according to the amplitude and the frequency in the frequency domain feature, a characteristic frequency determined based on the rotation speed, and a frequency multiplication, and accordingly, a specific implementation manner of the step S540 may be as follows:

obtaining M first target amplitudes with the largest numerical value in the amplitudes of the frequency domain characteristics, wherein M is a positive integer;

for the M first target amplitude values, determining a first target frequency corresponding to each first target amplitude value to obtain M first target frequencies;

calculating the characteristic frequency and frequency multiplication n of the bearing according to the rotating speed, wherein n is a positive integer;

and detecting whether the bearing of the wind turbine generator fails or not based on the M first target frequencies, the characteristic frequencies and the frequency multiplication.

In the case that the frequency domain feature of the nacelle acceleration includes an amplitude and a frequency, M amplitude values with the largest value, that is, M first target amplitude values, of all amplitude values of the frequency domain feature may be determined, where M may be a positive integer, such as 2. For the M first target amplitudes, a frequency corresponding to each first target amplitude, that is, a first target frequency, may be determined in all frequencies of the frequency domain feature, so as to obtain M first target frequencies. And then, calculating the characteristic frequency and the frequency multiplication of the bearing according to the rotating speed of the wind turbine generator, and detecting whether the bearing of the wind turbine generator fails or not according to the M first target frequencies and the characteristic frequency and the frequency multiplication.

As a specific example, the characteristic frequency X may be calculated based on equations (1) and (2):

X＝co_inne*freq_gs (1)

wherein, co_inneThe characteristic frequency coefficient of the bearing inner ring can be a bearing inner ring coefficient, a bearing outer ring coefficient, a rolling body coefficient, a retainer coefficient and the like. freq (total number of bits)_gsFor frequency conversion, freq_gsThe value of (b) is the average rotation speed/60 in the rotation speed steady state. n is a frequency multiplication, the value of n is 1,2,3, … … k, the value of k is closely related to the characteristic frequency coefficient of the bearing, and n X is less than or equal to the sampling frequency/2 of the acceleration of the cabin.

Taking M ═ 2 as an example, a specific implementation manner for determining M first target frequencies may be: first, from all the amplitudes of the nacelle acceleration, a first target amplitude with the largest amplitude is found, denoted as amp1, and a first target amplitude with the largest amplitude except amp1, denoted as amp 2. The first target frequency corresponding to each amp1 and amp2 is determined and is denoted as freq1 and freq 2. Note that, in order to avoid interference of adjacent frequency signals to the extraction of freqa (a is 1,2), before extracting freq2, the amplitudes in a preset number of neighborhoods around freq1 may be set to 0, and a preset number of typical values may be 10.

It will be appreciated that the frequencies corresponding to the first 2 amplitudes in the strict large-to-small permutation of amplitudes in the freq1, freq2 non-frequency domain features. In particular, interference from adjacent frequencies needs to be considered. For example, amp1 at 0.51Hz is 0.8g at freq 1Hz is the maximum amplitude in the frequency domain signature, if 0.75g at 0.52Hz is the second largest point of the amplitude next to amp1, but 0.52Hz and freq1 constitute a neighborhood relationship, so the frequency at 0.52Hz is not taken as freq 2. Based on the above consideration, a processing method of setting the frequency domain amplitude values in the neighborhood to 0 is made when the first target amplitude value is extracted.

Therefore, when the bearing of the wind turbine generator has failure characteristics of bearing failure caused by abrasion, foreign matters, cracks and the like, the characteristic frequency and the frequency multiplication can occur in the frequency domain characteristics of the acceleration of the engine room. Therefore, the fault condition of the bearing of the wind turbine generator is detected according to the frequency corresponding to the amplitude with the largest numerical value, the characteristic frequency and the frequency multiplication determined based on the rotating speed of the wind turbine generator, and the accuracy of the detection result can be further improved.

In some embodiments, when there is a preset amplitude threshold or more in the M first target amplitudes, the first target frequency corresponding to each first target amplitude is determined again, so as to obtain M first target frequencies.

After the M first target amplitude values are determined, the M first target amplitude values may be compared with a preset amplitude threshold value to determine whether there is a first target amplitude value greater than or equal to the preset amplitude threshold value in the M first target amplitude values, for example, the preset amplitude threshold value may be 0.02, and a specific value of the preset amplitude threshold value may be set according to an actual requirement. And under the condition that first target amplitudes larger than or equal to a preset amplitude threshold exist in the M first target amplitudes, determining a first target frequency corresponding to each first target amplitude to obtain M first target frequencies, subsequently determining the characteristic frequency and the frequency multiplication of the bearing according to the rotating speed, and detecting whether the bearing of the wind turbine generator fails or not based on the M first target frequencies, the characteristic frequency and the frequency multiplication. And under the condition that no first target amplitude which is greater than or equal to the preset amplitude threshold value exists in the M first target amplitudes, namely under the condition that any one of the M first target amplitudes is smaller than the preset amplitude threshold value, the step of judging whether the bearing of the subsequent wind turbine generator fails is not executed.

Therefore, the bearing of the wind turbine generator is low in failure probability under the condition that the M first target amplitude values are smaller than the preset amplitude threshold value, so that whether the bearing of the wind turbine generator fails or not can be detected only under the condition that the first target amplitude values larger than or equal to the preset amplitude threshold value exist in the M first target amplitude values. Therefore, the success rate and the efficiency of the wind turbine bearing fault detection method can be improved, unnecessary calculation amount can be reduced to a certain extent, and resource consumption is reduced.

In some embodiments, the frequency corresponding to the maximum amplitude of the nacelle acceleration in both directions may be combined to determine whether the wind turbine is malfunctioning. Accordingly, the specific implementation manner thereof may be as follows:

the cabin acceleration may include a spectral plot of a first cabin acceleration in a first direction and a spectral plot of a second cabin acceleration in a second direction.

The first direction may be perpendicular to the second direction, and the first direction and the second direction may be two mutually perpendicular directions in a coordinate system, for example, the first direction may be an x direction, and the second direction may be a y direction.

A spectrogram can be used to spectrally represent the frequency versus amplitude of the nacelle acceleration.

At this time, the specific implementation manner for detecting whether the bearing of the wind turbine generator fails based on the M first target frequencies, the characteristic frequencies, and the frequency multiplication may be as follows:

a first n-fold frequency is calculated based on the characteristic frequency and the frequency multiplication,

according to the first n-times frequency, determining a first target n-times frequency corresponding to the maximum amplitude in a first frequency interval in the spectrogram of the first cabin acceleration and a second target n-times frequency corresponding to the maximum amplitude in a second frequency interval in the spectrogram of the second cabin acceleration; a

And determining that the bearing of the wind turbine generator has a fault under the condition that the first target frequency which is the same as the first target n-times frequency or the second target n-times frequency exists in the M first target frequencies.

The first frequency interval is a frequency interval with a frequency deviation from the first n multiplied frequency nX within a first deviation range, namely a frequency interval with a frequency deviation from nX within the first deviation range. The second frequency interval is a frequency interval with a frequency deviation from the first n multiplied frequency within a second deviation range, that is, a frequency interval with a frequency deviation from nX within the second deviation range. The first deviation range may be the same as or different from the second deviation range.

The first n-fold frequency is an n-fold frequency calculated based on the calculated characteristic frequency X and the frequency n.

The acceleration of the nacelle may include a first nacelle acceleration in a first direction and a second nacelle acceleration in a second direction. At this time, the bearing n frequency multiplication nX, i.e., the first n frequency multiplication, may be calculated based on the above-described characteristic frequency X and frequency multiplication n. The maximum amplitude in the first frequency interval is determined in the spectrogram of the first nacelle acceleration, and then the frequency corresponding to the maximum amplitude is determined, i.e. the first target n-times frequency, which may also be referred to as n-times frequency in the first direction. The aforementioned formulas for calculating the first target n-times multiplication can be as in formulas (3) and (4).

nX_amp＝max(amp[nX-ε,nX+ε]) (3)

nX-ε<freq_max<nX+ε (4)

Wherein, nX_ampRepresenting the maximum amplitude in a preset frequency interval around the nX frequency in a spectrogram of the acceleration of the first cabin; epsilon represents the preset frequency interval; freq (total number of bits)_maxRepresenting the first target n-fold frequency.

Similarly, the maximum amplitude in the second frequency interval may also be determined in the spectrogram of the second cabin acceleration, and then the frequency corresponding to the maximum amplitude is determined, that is, the second target n-fold frequency, which may also be referred to as n-fold frequency in the second direction. The method for determining the second target n-times is similar to the method for determining the first target n-times, and is not repeated herein.

After the first target n-times frequency and the second target n-times frequency are determined, it may be determined whether a first target frequency that is the same as the first target n-times frequency or the second target n-times frequency exists in the M first target frequencies, that is, whether n-times frequencies in the first direction or the second direction exist in the first target frequency may be determined. And determining that the bearing of the wind turbine generator has a fault under the condition that the first target frequency which is the same as the first target n-times frequency or the second target n-times frequency exists in the M first target frequencies. That is, in the M first target frequencies, if at least one of the first target n-fold frequency or the second target n-fold frequency exists, it is determined that the bearing of the wind turbine generator has a fault.

Therefore, the first target n-times frequency and the second target n-times frequency are determined based on the first n-times frequency calculated by the characteristic frequency and the frequency multiplication, the determined first target n-times frequency and the second target n-times frequency can be more accurate, and whether the bearing of the wind turbine generator fails or not is determined based on the first target n-times frequency, the second target n-times frequency and the M first target frequencies, so that the accuracy of the bearing detection result of the wind turbine generator can be further improved.

In some embodiments, it may be detected whether a bearing of the wind turbine fails under the condition that no interference frequency exists in the third frequency interval and the fourth frequency interval, and accordingly, before determining that the bearing of the wind turbine fails under the condition that a first target frequency identical to the first target n-fold frequency or the second target n-fold frequency exists in the M first target frequencies, the following steps may be further performed:

and respectively determining whether the first interference frequency exists in the third frequency interval and the fourth frequency interval.

The third frequency interval is a frequency interval with frequency deviation multiplied by n with the first target within a third deviation range, the fourth frequency interval is a frequency interval with frequency deviation multiplied by n with the second target within a fourth deviation range, and the third deviation range and the fourth deviation range may be the same or different.

At this time, in the case that there is a first target frequency that is the same as the first target frequency n or the second target frequency n among the M first target frequencies, a specific implementation manner for determining that the bearing of the wind turbine generator has a fault may be as follows:

and in the third frequency interval and the fourth frequency interval, the first interference frequency does not exist, and the bearing of the wind turbine generator is determined to be in fault under the condition that the first target frequency which is the same as the first target n-times frequency or the second target n-times frequency exists in the M first target frequencies.

A third frequency interval with a deviation range multiplied by n from the first target being a third deviation range and a fourth frequency interval with a deviation range multiplied by n from the second target being a fourth deviation range may be determined, respectively. Then, it may be determined whether there is an interference frequency, i.e., the first interference frequency, within the third frequency interval and the fourth frequency interval, respectively. And under the condition that the first interference frequency does not exist in the third frequency interval and the fourth frequency interval, judging whether a first target frequency which is the same as the first target n-times frequency or the second target n-times frequency exists in the M first target frequencies. And determining that the bearing of the wind turbine generator fails under the condition that the first interference frequency does not exist in the third frequency interval and the fourth frequency interval, and the first target frequency which is the same as the first target n-fold frequency or the second target n-fold frequency exists in the M first target frequencies. And under the condition that the first interference frequency exists in the third frequency interval or the fourth frequency interval, not executing the step of detecting whether the wind turbine bearing fails.

The specific implementation manner of determining whether the first interference frequency exists in the third frequency interval may be: first, whether a first interference frequency exists in a frequency interval on the left side of a first target n-fold frequency in a third frequency interval is identified, wherein the frequency interval on the left side of the first target n-fold frequency may be a frequency interval of which the frequency value is smaller than the first target n-fold frequency and the difference between the first target n-fold frequency and the first target n-fold frequency is smaller than or equal to a third deviation range, and the first interference frequency may be nX_ampAnd/co, wherein co is a constant, such as 3. Then, the maximum amplitude in the frequency interval on the left side of the first target n-times in the third frequency interval may be determined, and recorded as left_ampIf left_amp＜nX_ampAnd/co, the first interference frequency is not present in the frequency interval on the left side of the first target n frequency multiplication in the third frequency interval. Similarly, the specific implementation manner of determining whether the first interference frequency exists in the frequency interval on the right side of the first target n-times in the third frequency interval and the specific implementation manner of determining whether the first interference frequency exists in the frequency intervals on the left side and the right side of the second target n-times in the fourth frequency interval are similar to the specific implementation manner of determining whether the first interference frequency exists in the frequency interval on the left side of the first target n-times in the third frequency interval, and here, the specific implementation manner is not limited to the specific implementation manner of determining whether the first interference frequency exists in the frequency interval on the left side of the first target n-times in the third frequency intervalAnd will be described in detail.

It should be noted that whether interference exists on the left and right sides of the frequency doubling may also be comprehensively determined according to the area under the curve of the n frequency doubling vicinity region or the corresponding amplitude of each frequency component of the vicinity region, and the implementation principle is similar to the method for determining whether the first interference frequency exists in the third frequency interval and the fourth frequency interval, and is not described herein again.

Therefore, it is considered that if the first interference frequency exists in the third frequency interval or the fourth frequency interval, the accuracy of the wind turbine bearing fault detection result may be affected. Therefore, the bearing of the wind turbine generator is determined to be in fault only under the condition that the first interference frequency does not exist in the third frequency interval and the fourth frequency interval, and the first target frequency which is the same as the first target n-times frequency or the second target n-times frequency exists in the M first target frequencies. Therefore, the accuracy of the wind turbine bearing fault detection result can be further improved.

In some embodiments, the frequency domain features may include a spectrogram of a first cabin acceleration in a first direction and a spectrogram of a second cabin acceleration in a second direction, the first direction being perpendicular to the second direction. The specific implementation manner of the step S540 may be as follows:

determining n frequency multiples of a third target corresponding to the maximum amplitude of each of n frequency multiples in the spectrogram of the first cabin acceleration and n frequency multiples of a fourth target corresponding to the maximum amplitude of each of n frequency multiples in the spectrogram of the second cabin acceleration based on the characteristic frequency and the frequency multiples;

and detecting whether the bearing of the wind turbine generator fails or not according to the n third target n-times and the n fourth target n-times.

The characteristic frequency and the frequency multiplication of the bearing can be calculated according to the rotating speed. After the characteristic frequency and the frequency multiplication of the bearing are determined, n frequency multiplications of third targets corresponding to respective maximum amplitudes of n frequency multiplications in a frequency spectrogram of the acceleration of the first nacelle can be determined based on the characteristic frequency and the frequency multiplication to obtain n frequency multiplications of the third targets, and n frequency multiplications of fourth targets corresponding to respective maximum amplitudes of n frequency multiplications in a frequency spectrogram of the acceleration of the second nacelle can be determined to obtain n frequency multiplications of the fourth targets. And detecting whether the bearing of the wind turbine generator fails or not according to the n third target n-times frequency and the n fourth target n-times frequency. It can be understood that a specific implementation manner of determining the n-times frequency of the third target corresponding to the maximum amplitude of each of the n-times frequencies in the spectrogram of the first nacelle acceleration and determining the n-times frequency of the fourth target corresponding to the maximum amplitude of each of the n-times frequencies in the spectrogram of the second nacelle acceleration is similar to the specific implementation manner of determining the n-times frequency of the first target corresponding to the maximum amplitude of the spectrogram of the first nacelle acceleration and determining the n-times frequency of the second target corresponding to the maximum amplitude of the spectrogram of the second nacelle acceleration in the above embodiment, and details are not repeated herein.

It should be noted that, in this embodiment, frequencies corresponding to respective maximum amplitudes at respective frequency multiples are determined, and if n is assumed to be 6, the frequency corresponding to the maximum amplitude at frequency 1, the frequency corresponding to the maximum amplitude at frequency 2, and the frequency corresponding to the maximum amplitude at frequency … … 6 are determined.

Therefore, according to the n third target n frequency multiplication and the n fourth target n frequency multiplication corresponding to the maximum amplitude of the first cabin acceleration and the second cabin acceleration under each frequency multiplication, the frequency characteristics under different frequency multiplication are comprehensively considered, and therefore the accuracy of the wind turbine bearing detection result can be further improved.

In some embodiments, the specific implementation manner for detecting whether the bearing of the wind turbine generator fails according to the n third target n multiplied frequencies and the n fourth target n multiplied frequencies may be as follows:

it is determined whether a second interference frequency exists in the ith fifth frequency interval and the ith sixth frequency interval, respectively.

Wherein i is a positive integer less than or equal to n. The ith fifth frequency interval is a frequency interval of which the frequency deviation multiplied by the ith third target n is within a fifth deviation range, and the ith sixth frequency interval is a frequency interval of which the frequency deviation multiplied by the ith fourth target n is within a sixth deviation range;

removing an ith third target n-multiplied frequency from n third target n-multiplied frequencies under the condition that a second interference frequency exists in an ith fifth frequency interval, and removing an ith fourth target n-multiplied frequency from n fourth target n-multiplied frequencies under the condition that a second interference frequency exists in an ith sixth frequency interval to obtain a first frequency set;

and detecting whether the bearing of the wind turbine generator is in fault or not according to the first frequency set.

After n third target n-multiplied frequencies and n fourth target n-multiplied frequencies are obtained, it may be determined whether an interference frequency exists in the ith fifth frequency interval and the ith sixth frequency interval, that is, whether a second interference frequency exists, where the second interference frequency may be the same as or different from the first interference frequency. It should be noted that, the foregoing judgment on whether the second interference frequency exists needs to be performed on each of the third target n-times and the fourth target n-times until it is determined whether the second interference frequency exists in each of the fifth frequency interval and the sixth frequency interval. The specific implementation manner for determining whether the second interference frequency exists in the ith fifth frequency interval and the ith sixth frequency interval is similar to the implementation manner for determining whether the first interference frequency exists in the third frequency interval and the fourth frequency interval, and is not repeated here.

In the case that the second interference frequency exists in the ith fifth frequency interval, the ith third target n-th multiplied frequency may be removed from the n third target n-th multiplied frequencies. Likewise, in case that the second interference frequency is present in the ith sixth frequency interval, the ith fourth target n-fold frequency may be removed from the n fourth target n-fold frequencies. And combining all the third target n-multiplied frequencies and the fourth target n-multiplied frequencies which are not removed into a set to obtain a first frequency set. And detecting whether the bearing of the wind turbine generator is in fault or not according to the first frequency set.

In this way, if the second interference frequency exists in any one of the fifth frequency interval or the sixth frequency interval, the accuracy of the wind turbine bearing fault detection result may be affected. Therefore, a first frequency set is formed only by the third target n-multiplied frequency and the fourth target n-multiplied frequency without the second interference frequency, and whether the bearing of the wind turbine generator fails or not is determined according to the first frequency set. Therefore, the accuracy of the wind turbine bearing fault detection result can be further improved.

In some embodiments, according to the first frequency set, a specific implementation manner of detecting whether a bearing of the wind turbine generator fails may be as follows:

acquiring a preset threshold and an amplitude corresponding to each frequency in a first frequency set;

determining a second target amplitude value of which the amplitude value is smaller than a preset threshold value in the first frequency set;

removing a second target frequency corresponding to a second target amplitude in the first frequency set to obtain a second frequency set;

performing duplicate removal processing on all frequencies in the second frequency set to obtain a third frequency set;

and detecting whether the bearing of the wind turbine generator fails or not according to the third frequency set.

After the first frequency set is obtained, a preset threshold c, which is a preset minimum value of the amplitude, may be obtained, and a specific value of c may be set according to an actual situation, and an amplitude corresponding to each frequency in the first frequency set may also be obtained. Then, an amplitude smaller than c, i.e. a second target amplitude, may be selected from all amplitudes corresponding to each frequency of the first set of frequencies. And removing the frequencies corresponding to all the second target amplitudes from the first frequency set to obtain a second frequency set. And then, performing duplicate removal processing on the second frequency set to obtain a third frequency set, and detecting whether the bearing of the wind turbine generator fails or not based on the third frequency set.

Therefore, whether the bearing of the wind turbine generator fails or not is detected based on the third frequency set which is obtained by removing the frequency corresponding to the amplitude smaller than the preset threshold and performing the past reprocessing, unnecessary calculated amount can be reduced to a certain extent, and therefore the efficiency of the wind turbine generator bearing failure detection method can be improved.

In some embodiments, according to the third frequency set, a specific implementation manner of detecting whether the bearing of the wind turbine fails may be as follows:

acquiring any two frequencies in a preset ratio set and a third frequency set;

calculating the ratio of any two frequencies;

and under the condition that the target ratio which belongs to the preset ratio set exists in all the ratios, determining that the bearing of the wind turbine generator is in fault.

The preset ratio set can be a ratio set preset according to historical data or experience and is recorded as ob_list。

When whether a bearing of the wind turbine generator fails is detected according to the first frequency set, a preset ratio set and any two frequencies in a third frequency set can be obtained, the ratio of any two frequencies is calculated, and the ratio of any two frequencies in the third frequency set is obtained. Then, it may be determined whether there is a ratio belonging to the preset ratio set, that is, a target ratio, among all ratios calculated based on the frequencies in the third frequency set. In the case that a target ratio belonging to the preset ratio set exists in all the ratios calculated based on the frequencies in the third frequency set, it can be considered that the bearing of the wind turbine generator is in a fault.

In calculating the ratio of any two frequencies in the third set of frequencies, it is necessary to use a frequency with a larger value than a frequency with a smaller value. And the elements in the preset ratio set are series elements with specific meanings larger than 1, and the elements in the preset ratio set can indicate that at least two frequency doubling exist in the cabin acceleration signal of the bearing. And the method provided by the embodiment is executed under the condition that the number of elements in the third frequency set is greater than 1.

Therefore, under the condition that the ratio of any two frequencies in the third frequency set belongs to the preset ratio set, at least two frequency doubling operations exist in the third frequency set, and the bearing of the wind turbine generator is indicated to be in fault. Therefore, the accuracy of the wind turbine bearing fault detection method can be further improved.

In some embodiments, the ac component of the high-pass filtered nacelle acceleration may be determined as the target acceleration, and accordingly, the specific implementation manner may be as follows:

removing the direct current component of the acceleration of the engine room to obtain the alternating current component of the acceleration of the engine room;

under the condition that the rotating speed is in a stable state, carrying out high-pass filtering on the alternating current component of the acceleration of the engine room to obtain a target alternating current component which belongs to a preset frequency range in the alternating current component of the acceleration of the engine room;

the target alternating current component is determined as a target acceleration.

The nacelle acceleration signal generally includes a dc component and an ac component, and an ac component parasitic on the dc component needs to be extracted, that is, the dc signal in the nacelle acceleration needs to be removed. Specifically, the mean value of the cabin acceleration may be obtained first, and the mean value is subtracted from the cabin acceleration at each sampling time, so as to complete the process of removing the dc component, as shown in equations (5) and (6).

s(t)＝x(t)-x₀ (5)

Wherein s (t) is the AC component of the cabin acceleration; x (t) is cabin acceleration; t represents a sampling instant; x is a radical of a fluorine atom₀The average value of the acceleration of the cabin is shown, and T is a sampling period.

After the direct-current component of the nacelle acceleration is removed to obtain the alternating-current component of the nacelle acceleration, high-pass filtering may be performed on the alternating-current component of the nacelle acceleration to obtain an alternating-current component, which belongs to a preset frequency range, in the alternating-current component of the nacelle acceleration, that is, a target alternating-current component, and the target alternating-current component may be determined as the target acceleration. The specific implementation principle of performing high-pass filtering on the alternating current component of the nacelle acceleration is similar to the above-mentioned specific implementation principle of performing high-pass filtering on the nacelle acceleration, and for the sake of brevity, the details are not described herein again.

In some embodiments, whether the rotation speed is in a steady state may be determined according to the fluctuation coefficient of the rotation speed, and accordingly, the processing may be as follows:

calculating the fluctuation coefficient of the rotating speed;

and under the condition that the fluctuation coefficient meets a preset fluctuation condition, determining that the rotating speed is in a stable state.

The fluctuation coefficient can be used to indicate the variation amplitude of the rotation speed, such as standard deviation, variation coefficient, extreme value, sunstroke, median difference, etc.

A fluctuation coefficient indicating the variation range of the rotation speed may be calculated, and it may be determined whether the fluctuation coefficient satisfies a preset fluctuation condition. And under the condition that the fluctuation coefficient meets the preset fluctuation condition, determining that the rotating speed is in a stable state. And otherwise, determining that the rotating speed is in an unstable state under the condition that the fluctuation coefficient does not meet the preset condition.

As a specific example, when the fluctuation coefficient is a standard deviation, the standard deviation may be calculated according to equation (7).

gs_std＝max(gs)-min(gs) (7)

Where gs represents the rotational speed and gs _ std represents the standard deviation.

When the fluctuation coefficient is the standard deviation, the preset fluctuation condition may be that the standard deviation is smaller than a preset standard deviation threshold a, for example, a may be 0.1. In the case where the standard deviation is smaller than a, the rotation speed can be considered to be in a steady state.

When the fluctuation coefficient is the variation coefficient, the variation coefficient can be calculated according to the formula (8)

Wherein, C_vThe coefficient of variation is shown, μ is the average value of the rotational speed, and σ is the standard deviation of the rotational speed.

In the case that the fluctuation coefficient is a variation coefficient, the preset fluctuation condition may be that the variation coefficient is smaller than a preset variation coefficient threshold. When the variation coefficient is smaller than the preset variation coefficient threshold, the rotating speed can be considered to be in a stable state.

A method for detecting a bearing fault of a wind turbine generator provided in an embodiment of the present application is described below with reference to fig. 6. As shown in fig. 6, the method for detecting a bearing fault of a wind turbine generator provided in the embodiment of the present application may include the following steps:

and S610, acquiring the operation parameters of the wind turbine generator.

Wherein the operating parameters include the acceleration of the nacelle and the rotational speed of the wind turbine.

And S620, calculating the fluctuation coefficient of the rotating speed.

And S630, judging whether the rotating speed is in a stable state or not.

Steps S640 to S690 are performed with the rotational speed in a steady state, otherwise, the process is ended.

And S640, calculating the characteristic frequency and the frequency multiplication of the bearing according to the rotating speed.

And S650, removing the direct current component of the acceleration of the cabin.

And S660, carrying out high-pass filtering on the alternating current component of the acceleration of the cabin to obtain the target acceleration.

And S670, extracting frequency domain characteristics of the target acceleration through FFT.

And S680, detecting whether the bearing of the wind turbine generator is in fault or not according to the frequency domain characteristics and the rotating speed.

And S690, outputting a detection result.

The specific implementation principle and technical effect of each step are similar to the wind turbine generator bearing fault detection method provided by each method embodiment, and are not described again for the sake of brevity.

Fig. 7 shows a wind turbine generator bearing fault detection method provided in an embodiment of the present application, where the method is a specific implementation process for detecting whether a bearing of a wind turbine generator has a fault based on M first target frequencies, a characteristic frequency, and a frequency multiplication, and as shown in fig. 7, the method may include the following steps:

s710, determining M first target amplitude values.

S720, judging whether the M first target amplitude values have first target amplitude values larger than or equal to a preset amplitude value threshold value.

In the case that there is more than or equal to the preset amplitude threshold value among the M first target amplitudes, step S730 is performed. Otherwise, S770 is executed to end the process.

S730, for the M first target amplitudes, determining a first target frequency corresponding to each first target amplitude to obtain M first target frequencies. And calculating a first n-times frequency multiplication based on the characteristic frequency and the frequency multiplication, and determining a first target n-times frequency corresponding to the maximum amplitude in a first frequency interval in the spectrogram of the first cabin acceleration and a second target n-times frequency corresponding to the maximum amplitude in a second frequency interval in the spectrogram of the second cabin acceleration.

S740, respectively determining whether the first interference frequency exists in the third frequency interval and the fourth frequency interval.

If the first interference frequency does not exist in the third frequency interval and the fourth frequency interval, step S750 is executed. Otherwise, S770 is executed to end the process.

S750, determining whether there is a first target frequency that is the same as the first target frequency n or the second target frequency n in the M first target frequencies.

In the case that there is a first target frequency identical to the first target n-fold frequency or the second target n-fold frequency among the M first target frequencies, step S760 is performed. Otherwise, S770 is executed to end the process.

And S760, determining that the bearing of the wind turbine generator fails.

The specific implementation principle and technical effect of each step are similar to those of the wind turbine generator bearing fault detection method provided by each method embodiment, and are not repeated herein for the sake of brevity.

Fig. 8 shows a wind turbine generator bearing fault detection method provided in an embodiment of the present application, where the method is a specific implementation process for detecting whether a bearing of a wind turbine generator has a fault according to n third frequencies and n fourth frequencies, and as shown in fig. 8, the method may include the following steps:

and S810, determining n times of frequency of a third target corresponding to the maximum amplitude of each of n times of frequency in the spectrogram of the first cabin acceleration and n times of frequency of a fourth target corresponding to the maximum amplitude of each of n times of frequency in the spectrogram of the second cabin acceleration based on the characteristic frequency and the frequency multiplication.

S820, removing the ith third target n-fold frequency from the n third target n-fold frequencies when the second interference frequency exists in the ith fifth frequency interval, and removing the ith fourth target n-fold frequency from the n fourth target n-fold frequencies when the second interference frequency exists in the ith sixth frequency interval, so as to obtain the first frequency set.

And S830, removing a second target frequency corresponding to a second target amplitude in the first frequency set to obtain a second frequency set.

And S840, performing deduplication processing on all the frequencies in the second frequency set to obtain a third frequency set.

And S850, judging whether the number of elements in the third frequency set is more than 1.

If the number of elements in the third frequency set is greater than 1, step S860 is executed. Otherwise, S880 end processing is executed.

And S860, judging whether a target ratio which belongs to a preset ratio set exists in all ratios.

In the case where there is a target ratio belonging to the preset ratio set among all ratios, step S870 is executed. Otherwise, S880 end processing is executed.

And S870, determining that the bearing of the wind turbine generator fails.

Based on the same inventive concept, the application also provides a wind turbine generator bearing fault detection device.

Fig. 9 is a schematic structural diagram illustrating a wind turbine bearing fault detection apparatus according to an exemplary embodiment. As shown in fig. 9, the wind turbine generator bearing fault detection apparatus 900 may specifically include:

the obtaining module 910 is configured to obtain operation parameters of the wind turbine, where the operation parameters include an acceleration of the nacelle and a rotation speed of the wind turbine;

the filtering module 920 is configured to perform high-pass filtering on the cabin acceleration under the condition that the rotation speed is in a stable state, so as to obtain a target acceleration within a preset frequency range;

an extracting module 930, configured to extract a frequency domain feature of the target acceleration;

and the detection module 940 is used for detecting whether the bearing of the wind turbine generator fails according to the frequency domain characteristics and the rotating speed.

In some embodiments, the frequency domain features may include amplitudes and frequencies to which the amplitudes correspond;

the detection module 940 may include:

the first obtaining unit is used for obtaining M first target amplitude values with the largest numerical value in the amplitude values of the frequency domain characteristics, wherein M is a positive integer;

the first determining unit is used for determining a first target frequency corresponding to each first target amplitude to obtain M first target frequencies;

the second determining unit is used for calculating the characteristic frequency and the frequency multiplication n of the bearing according to the rotating speed, wherein n is a positive integer;

and the first detection unit is used for detecting whether the bearing of the wind turbine generator fails or not based on the M first target frequencies, the characteristic frequencies and the frequency multiplication.

In some embodiments, the cabin acceleration comprises a spectrogram of a first cabin acceleration in a first direction and a spectrogram of a second cabin acceleration in a second direction, the first direction being perpendicular to the second direction;

the first detection unit may include:

a calculating subunit operable to calculate a first n-fold frequency based on the characteristic frequency and the fold frequency;

the first determining subunit may be configured to determine, according to the first n-fold frequency, a first target n-fold frequency corresponding to a maximum amplitude within a first frequency interval in a spectrogram of the first nacelle acceleration, and a second target n-fold frequency corresponding to a maximum amplitude within a second frequency interval in a spectrogram of the second nacelle acceleration;

the second determining subunit may be configured to determine that a bearing of the wind turbine generator has a fault when a first target frequency that is the same as the first target frequency n or the second target frequency n exists among the M first target frequencies.

In some embodiments, the wind turbine bearing fault detection apparatus 900 may further include:

a third determining unit, configured to determine whether the first interference frequency exists in a third frequency interval and a fourth frequency interval, respectively, where the third frequency interval is a frequency interval in which a frequency deviation of n-times frequency multiplication with the first target is within a first deviation range, and the fourth frequency interval is a frequency interval in which a frequency deviation of n-times frequency multiplication with the second target is within a second deviation range;

the second determining subunit may be specifically configured to:

In some embodiments, the frequency domain features include a spectrogram of a first cabin acceleration in a first direction and a spectrogram of a second cabin acceleration in a second direction, the first direction being perpendicular to the second direction;

the detection module 940 may include:

a fourth determining unit, configured to determine, based on the characteristic frequency and the frequency multiplication, n frequency multiplications of a third target corresponding to respective maximum amplitudes at n frequency multiplications in a spectrogram of the first cabin acceleration, and n frequency multiplications of a fourth target corresponding to respective maximum amplitudes at n frequency multiplications in a spectrogram of the second cabin acceleration;

and the second detection unit is used for detecting whether the bearing of the wind turbine generator fails or not according to the n third target n-times frequency and the n fourth target n-times frequency.

In some embodiments, the second detection unit may include:

a determining subunit, configured to determine whether a second interference frequency exists in an ith fifth frequency interval and an ith sixth frequency interval, respectively, where i is a positive integer less than or equal to n;

the removing subunit is configured to remove an ith third target n-fold frequency from the n third frequencies when the second interference frequency exists in the ith fifth frequency interval, and remove an ith fourth target n-fold frequency from the n fourth target n-fold frequencies when the second interference frequency exists in the ith sixth frequency interval, so as to obtain a first frequency set;

and the detection subunit is used for detecting whether the bearing of the wind turbine generator fails or not according to the first frequency set.

In some embodiments, the detection subunit may include:

the amplitude acquisition subunit is used for acquiring a preset threshold and an amplitude corresponding to each frequency in the first frequency set;

the amplitude determining subunit is configured to determine a second target amplitude, of which the amplitude is smaller than a preset threshold, in the first frequency set;

the frequency removing subunit is configured to remove a second target frequency corresponding to a second target amplitude in the first frequency set, so as to obtain a second frequency set;

the duplication removing subunit is configured to perform duplication removing processing on all the frequencies in the second frequency set to obtain a third frequency set;

and the fault detection subunit is used for detecting whether the bearing of the wind turbine generator fails or not according to the third frequency set.

In some embodiments, the failure detection subunit is specifically configured to:

acquiring any two frequencies in a preset ratio set and a third frequency set;

calculating the ratio of any two frequencies;

In some embodiments, the wind turbine generator bearing fault detection apparatus 900 may further include:

the direct current removing module is used for removing a direct current component of the acceleration of the engine room to obtain an alternating current component of the acceleration of the engine room;

the filtering module 920 may include:

the filtering subunit is used for carrying out high-pass filtering on the alternating current component of the acceleration of the engine room to obtain a target alternating current component which belongs to a preset frequency range in the alternating current component of the acceleration of the engine room;

a fifth determination unit for determining the target alternating current component as the target acceleration.

the calculating module is used for calculating a fluctuation coefficient of the rotating speed, and the fluctuation coefficient is used for indicating the change amplitude of the rotating speed;

and the judging module is used for determining that the rotating speed is in a stable state under the condition that the fluctuation coefficient meets the preset fluctuation condition.

The wind turbine generator bearing fault detection device provided by this embodiment may be used to execute the wind turbine generator bearing fault detection method provided by each of the above method embodiments, and its implementation method and technical effect are similar, and are not described herein again.

Based on the same inventive concept, the present application also provides a controller, as shown in fig. 10, which may include a processor 1001 and a memory 1002 storing computer program instructions.

Specifically, the processor 1001 may include a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or may be configured as one or more Integrated circuits implementing an embodiment of the present invention.

Memory 1002 may include mass storage for data or instructions. By way of example, and not limitation, memory 1002 may include a Hard Disk Drive (HDD), a floppy Disk Drive, flash memory, an optical Disk, a magneto-optical Disk, magnetic tape, or a Universal Serial Bus (USB) Drive or a combination of two or more of these. Memory 1002 may include removable or non-removable (or fixed) media, where appropriate. The memory 1002 may be internal or external to the integrated gateway disaster recovery device, where appropriate. In a particular embodiment, the memory 1002 is non-volatile solid-state memory. In a particular embodiment, the memory 502 includes Read Only Memory (ROM). Where appropriate, the ROM may be mask-programmed ROM, Programmable ROM (PROM), Erasable PROM (EPROM), Electrically Erasable PROM (EEPROM), electrically rewritable ROM (EAROM), or flash memory or a combination of two or more of these.

The processor 1001 reads and executes the computer program instructions stored in the memory 1002 to implement any one of the wind turbine generator bearing fault detection methods in the above embodiments.

In one example, the host controller may also include a communication interface 1003 and a bus 1010. As shown in fig. 10, the processor 1001, the memory 1002, and the communication interface 1003 are connected to each other via a bus 1010 to complete communication therebetween.

The communication interface 1003 is mainly used to implement communication between modules, devices, units and/or devices in the embodiment of the present invention.

The bus 1010 includes hardware, software, or both to couple the components of the host controller to each other. By way of example, and not limitation, a bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hypertransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus or a combination of two or more of these. Bus 1010 may include one or more buses, where appropriate. Although specific buses have been described and shown in the embodiments of the invention, any suitable buses or interconnects are contemplated by the invention.

The controller may execute the wind turbine bearing fault detection method in the embodiment of the present invention, so as to implement the wind turbine bearing fault detection method and apparatus described in fig. 1 to 9.

In addition, in combination with the wind turbine generator bearing fault detection method in the above embodiment, an embodiment of the present invention may provide a computer-readable storage medium to implement the method. The computer readable storage medium having stored thereon computer program instructions; when executed by a processor, the computer program instructions implement any one of the wind turbine bearing fault detection methods in the above embodiments.

It is to be understood that the invention is not limited to the specific arrangements and instrumentality described above and shown in the drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present invention are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications and additions or change the order between the steps after comprehending the spirit of the present invention.

The functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the invention are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, Erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, Radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.

It should also be noted that the exemplary embodiments mentioned in this patent describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.

As described above, only the specific embodiments of the present invention are provided, and it can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the module and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. It should be understood that the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present invention, and these modifications or substitutions should be covered within the scope of the present invention.

Claims

1. A wind turbine generator bearing fault detection method is characterized by comprising the following steps:

under the condition that the rotating speed is in a stable state, performing high-pass filtering on the acceleration of the engine room to obtain a target acceleration within a preset frequency range;

extracting frequency domain characteristics of the target acceleration;

and detecting whether the bearing of the wind turbine generator is in fault or not according to the frequency domain characteristics and the rotating speed.

2. The method of claim 1, wherein the frequency domain features comprise amplitudes and frequencies to which the amplitudes correspond;

the detecting whether the bearing of the wind turbine generator is in fault or not according to the frequency domain characteristics and the rotating speed comprises the following steps:

and detecting whether the bearing of the wind turbine generator fails or not based on the M first target frequencies, the characteristic frequency and the frequency multiplication.

3. The method of claim 2, wherein the cabin acceleration comprises a spectrogram of a first cabin acceleration in a first direction and a spectrogram of a second cabin acceleration in a second direction, the first direction being perpendicular to the second direction;

the detecting whether the bearing of the wind turbine generator fails based on the M first target frequencies, the characteristic frequency and the frequency multiplication comprises:

calculating a first n-fold frequency based on the characteristic frequency and the frequency multiplication,

according to the first n-times frequency, determining a first target n-times frequency corresponding to the maximum amplitude in a first frequency interval in the spectrogram of the first cabin acceleration and a second target n-times frequency corresponding to the maximum amplitude in a second frequency interval in the spectrogram of the second cabin acceleration;

and determining that the bearing of the wind turbine generator has a fault when a first target frequency identical to the first target n-times frequency or the second target n-times frequency exists in the M first target frequencies.

4. The method according to claim 3, wherein the determining before the bearing of the wind turbine generator fails in the case that there is a first target frequency, which is the same as the first target n-fold frequency or the second target n-fold frequency, among the M first target frequencies further comprises:

respectively determining whether a first interference frequency exists in a third frequency interval and a fourth frequency interval, wherein the third frequency interval is a frequency interval of frequency deviation multiplied by n with the first target within a third deviation range, and the fourth frequency interval is a frequency interval of frequency deviation multiplied by n with the second target within a fourth deviation range;

the determining that the bearing of the wind turbine generator has a fault when a first target frequency identical to the first target n-fold frequency or the second target n-fold frequency exists in the M first target frequencies includes:

and in the third frequency interval and the fourth frequency interval, the first interference frequency does not exist, and the bearing of the wind turbine generator is determined to be in fault under the condition that the first target frequency which is the same as the first target n-fold frequency or the second target n-fold frequency exists in the M first target frequencies.

5. The method of claim 1, wherein the frequency domain features comprise a spectrogram of a first cabin acceleration in a first direction and a spectrogram of a second cabin acceleration in a second direction, the first direction being perpendicular to the second direction;

determining, based on the characteristic frequency and the frequency multiplication, a third target n-times frequency corresponding to the maximum amplitude of each of n-times frequencies in the spectrogram of the first cabin acceleration, and a fourth target n-times frequency corresponding to the maximum amplitude of each of n-times frequencies in the spectrogram of the second cabin acceleration;

and detecting whether the bearing of the wind turbine generator fails or not according to the n third target n-times frequency and the n fourth target n-times frequency.

6. The method according to claim 5, wherein the detecting whether the bearing of the wind turbine generator fails according to the n third target n multiplied frequencies and the n fourth target n multiplied frequencies comprises:

respectively determining whether a second interference frequency exists in an ith fifth frequency interval and an ith sixth frequency interval, wherein i is a positive integer less than or equal to n;

removing the ith third target n-fold frequency from the n third target n-fold frequencies under the condition that the second interference frequency exists in the ith fifth frequency interval, and removing the ith fourth target n-fold frequency from the n fourth target n-fold frequencies under the condition that the second interference frequency exists in the ith sixth frequency interval to obtain a first frequency set;

7. The method of claim 6, wherein detecting whether a bearing of the wind turbine is malfunctioning according to the first set of frequencies comprises:

acquiring a preset threshold value and an amplitude value corresponding to each frequency in the first frequency set;

determining a second target amplitude value of which the amplitude value is smaller than the preset threshold value in the first frequency set;

removing a second target frequency corresponding to the second target amplitude in the first frequency set to obtain a second frequency set;

performing deduplication processing on all frequencies in the second frequency set to obtain a third frequency set;

and detecting whether the bearing of the wind turbine generator is in fault or not according to the third frequency set.

8. The method of claim 7, wherein the detecting whether a bearing of the wind turbine fails according to the third set of frequencies comprises:

acquiring a preset ratio set and any two frequencies in the third frequency set;

calculating the ratio of any two frequencies;

9. The method according to any one of claims 1 to 8, wherein before the high-pass filtering the nacelle acceleration with the rotating speed in a steady state to obtain the target acceleration in a preset frequency range, the method further comprises:

removing the direct current component of the cabin acceleration to obtain the alternating current component of the cabin acceleration;

the high-pass filtering is performed on the acceleration of the engine room under the condition that the rotating speed is in a stable state, so that the target acceleration in a preset frequency range is obtained, and the method comprises the following steps:

under the condition that the rotating speed is in a stable state, carrying out high-pass filtering on the alternating current component of the cabin acceleration to obtain a target alternating current component which belongs to the preset frequency range in the alternating current component of the cabin acceleration;

determining the target alternating current component as the target acceleration.

10. The method according to any one of claims 1 to 8, wherein before the high-pass filtering the nacelle acceleration with the rotating speed in a steady state to obtain the target acceleration in a preset frequency range, the method further comprises:

calculating a fluctuation coefficient of the rotation speed, wherein the fluctuation coefficient is used for indicating the change amplitude of the rotation speed;

and determining that the rotating speed is in the stable state under the condition that the fluctuation coefficient meets a preset fluctuation condition.

11. The utility model provides a wind turbine generator system bearing fault detection device which characterized in that includes:

12. A controller, characterized in that the controller comprises: a processor, and a memory storing computer program instructions;

the processor reads and executes the computer program instructions to implement the wind turbine generator bearing fault detection method according to any one of claims 1 to 10.

13. A readable storage medium, characterized in that the readable storage medium has stored thereon computer program instructions, which when executed by a processor, implement the wind turbine generator set bearing fault detection method according to any one of claims 1 to 10.