CN-121994488-A - Wind power bearing vibration control monitoring method and device based on piezoelectricity and metal rubber

CN121994488ACN 121994488 ACN121994488 ACN 121994488ACN-121994488-A

Abstract

The invention discloses a wind power bearing vibration control monitoring method and device based on piezoelectricity and metal rubber, and belongs to the technical field of wind power bearing health management. According to the wind power bearing vibration signal analysis method, the wind power bearing vibration signal is collected, the vibration characteristics of the bearing under the normal operation condition and the abnormal operation condition are distinguished and analyzed, the characteristic frequency interval is further subjected to self-adaptive expansion correction under the abnormal operation condition, the influence of complex load and rotation speed fluctuation on the bearing characteristic extraction is effectively reduced, and the accuracy of the bearing vibration monitoring result is improved. In addition, aiming at the complex load condition of the offshore wind turbine, the invention introduces a characteristic frequency verification and energy gain fusion mechanism to dynamically update the bearing characteristic frequency band, enhances the adaptability of the monitoring method to complex working conditions, and realizes the effective monitoring and control of the vibration state of the wind turbine bearing.

Inventors

WANG LEIZHI
Sheng Longyun
SUN FENG
ZHANG BO
PENG ZHIKE

Assignees

宁夏大学

Dates

Publication Date: 20260508
Application Date: 20260209

Claims (10)

1. The wind power bearing vibration control monitoring method based on the piezoelectric and metal rubber is characterized by comprising the following steps of: Collecting bearing vibration signals of a wind power bearing and working condition identifiers thereof, wherein the working condition identifiers comprise normal operation working conditions and abnormal operation working conditions, and the abnormal operation working conditions are used for representing working conditions that the output power or the main shaft rotating speed of the wind turbine generator is not in a corresponding limiting interval; Carrying out frequency domain feature extraction on the bearing vibration signal to obtain a bearing median frequency, obtaining a feature frequency reference interval from a pre-stored mapping relation based on the bearing median frequency, and dividing the bearing vibration signal by the feature frequency reference interval to obtain a bearing feature frequency band and a non-bearing feature frequency band; When the working condition identification of the bearing vibration signal corresponds to an abnormal operation working condition, firstly performing expansion correction on a characteristic frequency reference interval to obtain a characteristic frequency verification interval, then correcting a non-bearing characteristic frequency band according to the characteristic frequency verification interval to obtain a characteristic verification frequency band, updating the non-bearing characteristic frequency band, and fusing and updating the characteristic verification frequency band with the bearing characteristic frequency band after performing energy gain adjustment; and after blind source separation is carried out on the updated non-bearing characteristic frequency band, judging whether the bearing characteristic frequency band is updated or not, and outputting a bearing vibration monitoring result according to the bearing characteristic frequency band.
2. The method for monitoring vibration control of a wind power bearing based on piezoelectricity and metal rubber according to claim 1, wherein the step of collecting the vibration signal of the wind power bearing and the working condition identification thereof comprises the following steps: acquiring meteorological environment parameters for representing the running environment of the offshore wind turbine, wherein the meteorological environment parameters comprise meteorological wind speed, ambient air pressure and ambient noise intensity; performing weighted coupling after deviation treatment on meteorological environment parameters and corresponding meteorological environment set thresholds item by item to obtain a monitoring environment interference coefficient; judging whether the acquired monitoring environment interference coefficient is in a set interference control interval, if so, acquiring a bearing vibration signal by using initial fixed parameters of a piezoelectric sensor, wherein the initial fixed parameters comprise initial sampling frequency and initial filtering strength; Otherwise, respectively acquiring sampling adjustment frequency and filtering adjustment strength corresponding to the monitored environment interference coefficient from the pre-stored mapping relation so as to update the initial fixed parameters.
3. The method for monitoring vibration control of a wind power bearing based on piezoelectric and metal rubber according to claim 1, wherein the method further comprises the steps of: Introducing an equivalent load correction factor to update the obtained bearing median frequency after coupling correction, wherein the equivalent load correction factor is used for compensating the influence of vibration spectrum distribution change under different load conditions on the bearing median frequency; The equivalent load correction factor is a result of performing interactive operation with the damping characteristic adjusting coefficient after performing duty ratio processing on the bearing equivalent load and the reference equivalent load; the equivalent load of the bearing is the result of coupling evolution operation after weighting the radial load and the axial load of the bearing respectively; The limiting expression of the equivalent load correction factor is as follows: ; ; in the formula, Indicating the equivalent load of the bearing, The radial load weight is represented by a weight of the radial load, Representing the radial load of the bearing, Representing the weight of the axial load, Representing the axial load of the bearing, Representing the equivalent load correction factor, Representing the reference equivalent load of the load, Representing the damping characteristic adjustment coefficient.
4. The method for controlling and monitoring vibration of a wind power bearing based on piezoelectric and metal rubber according to claim 1, wherein the characteristic frequency reference interval is obtained by the following specific steps: inquiring a frequency upper boundary value and a frequency lower boundary value corresponding to the median frequency of the bearing from a pre-stored mapping relation; Judging whether the difference between the frequency upper boundary value and the frequency lower boundary value is in a set offset range, if so, constructing a characteristic frequency reference interval based on a closed interval corresponding to the frequency lower boundary value and the frequency upper boundary value; Otherwise, acquiring an upper boundary offset and a lower boundary offset of the frequency upper boundary value and the frequency lower boundary value which correspond to the median frequency of the bearing respectively; And obtaining an upper boundary buffer value and a lower boundary buffer value respectively corresponding to the upper boundary offset and the lower boundary offset according to a pre-stored mapping relation, and constructing a characteristic frequency reference interval based on the obtained lower boundary buffer value and a closed interval corresponding to the upper boundary buffer value.
5. The method for monitoring vibration control of a wind power bearing based on piezoelectric and metal rubber according to claim 1, wherein the step of dividing the vibration signal of the bearing by a characteristic frequency reference interval to obtain a bearing characteristic frequency band and a non-bearing characteristic frequency band, and further comprises the steps of: Acquiring a first frequency band energy value and a second frequency band energy value which correspond to a bearing characteristic frequency band and a non-bearing characteristic frequency band respectively, and recording the sum of the first frequency band energy value and the second frequency band energy value as total frequency band energy; The proportion of the total frequency band energy occupied by the first frequency band energy value is recorded as a bearing health index, and the numerical relation between the bearing health index and the set health early warning threshold is judged; and when the bearing health index is greater than the health early warning threshold value, sending a bearing health early warning prompt.
6. The method for monitoring vibration control of a wind power bearing based on piezoelectric and metal rubber according to claim 1, wherein the step of performing expansion correction on the characteristic frequency reference interval to obtain a characteristic frequency verification interval comprises the following specific steps: Respectively obtaining the output power of the wind turbine generator and the absolute deviation of the spindle rotating speed and the median value in the corresponding limiting interval, wherein the absolute deviation comprises the absolute power deviation and the absolute rotating speed deviation; Inputting the result of normalized coupling processing of the absolute deviation into a pre-stored mapping table to obtain an interval expansion ratio; and amplifying the characteristic frequency reference interval based on the acquired interval expansion proportion to obtain a characteristic frequency verification interval.
7. The method for monitoring vibration control of wind power bearing based on piezoelectric and metal rubber according to claim 5, wherein the characteristic verification frequency band is fused with the bearing characteristic frequency band and updated after energy gain adjustment, and the specific steps are as follows: Acquiring a third frequency band energy value corresponding to the first frequency band energy value and the characteristic verification frequency band, and marking a result of normalization processing of the ratio of the first frequency band energy value to the third frequency band energy value as a gain factor; And carrying out coupling adjustment on the amplitude of the characteristic verification frequency band based on the gain factor, and carrying out frequency domain superposition fusion on the characteristic verification frequency band subjected to coupling adjustment and the bearing characteristic frequency band so as to update the bearing characteristic frequency band.
8. The method for monitoring vibration control of a wind power bearing based on piezoelectric and metal rubber according to claim 1, wherein the method for judging whether to update the bearing characteristic frequency band after blind source separation of the updated non-bearing characteristic frequency band is specifically as follows: and acquiring a reconstruction error after blind source separation of the non-bearing characteristic frequency band, and updating the bearing characteristic frequency band when the reconstruction error is smaller than an error threshold value, otherwise, not updating.
9. The method for monitoring vibration control of a wind power bearing based on piezoelectric and metal rubber according to claim 1, wherein the step of outputting the monitoring result of vibration of the bearing according to the characteristic frequency band of the bearing further comprises the steps of: Sensing bearing vibration based on positive voltage effect of the piezoelectric sensor to obtain a vibration feedback signal; And generating a control signal according to the vibration feedback signal by adopting a PID algorithm, and driving the piezoelectric actuator to output vibration suppression force by utilizing the inverse piezoelectric effect so as to actively control the vibration of the bearing.
10. The wind power bearing vibration control monitoring device based on the piezoelectric and metal rubber is characterized by comprising a bearing vibration monitoring module, a characteristic frequency band dividing module, a frequency band dividing and correcting module and a monitoring result output module: The bearing vibration monitoring module is used for collecting bearing vibration signals of the wind power bearing and working condition identifiers thereof, the working condition identifiers comprise normal operation working conditions and abnormal operation working conditions, and the abnormal operation working conditions are used for representing working conditions that the output power or the main shaft rotating speed of the wind power generation set is not in a corresponding limiting interval; The characteristic frequency band dividing module is used for carrying out frequency domain characteristic extraction on the bearing vibration signals to obtain bearing median frequencies, obtaining characteristic frequency reference intervals from a pre-stored mapping relation based on the bearing median frequencies, and dividing the bearing vibration signals by the characteristic frequency reference intervals to obtain bearing characteristic frequency bands and non-bearing characteristic frequency bands; The frequency band division correction module is used for expanding and correcting the characteristic frequency reference interval to obtain a characteristic frequency verification interval when the working condition identification of the bearing vibration signal corresponds to an abnormal operation working condition, correcting the non-bearing characteristic frequency band according to the characteristic frequency verification interval to obtain a characteristic verification frequency band, updating the non-bearing characteristic frequency band, and fusing and updating the characteristic verification frequency band with the bearing characteristic frequency band after energy gain adjustment; and the monitoring result output module is used for judging whether the bearing characteristic frequency band is updated after blind source separation is carried out on the updated non-bearing characteristic frequency band, and outputting a bearing vibration monitoring result according to the bearing characteristic frequency band.

Description

Wind power bearing vibration control monitoring method and device based on piezoelectricity and metal rubber Technical Field The invention relates to the technical field of wind power bearing health management, in particular to a wind power bearing vibration control monitoring method and device based on piezoelectricity and metal rubber. Background At present, the wind generating set is developed towards the directions of high power density, long service life and complex environment adaptability, and key components such as a main shaft bearing, a variable pitch bearing, a yaw bearing and the like bear working conditions such as low-speed heavy load, alternating load, multisource coupling vibration and the like for a long time in the running process. Bearing vibration can cause the problems of raceway fatigue, pitting and peeling, lubrication state deterioration and the like, and can possibly lead to vibration amplification of a transmission chain, so that the running stability of the wind turbine generator is reduced, and the maintenance cost is increased. Therefore, vibration monitoring and control of the running state of the wind power bearing become important technical content in the field of running maintenance of wind power equipment. In the prior art, vibration control and monitoring of wind power bearings is generally performed by first arranging vibration sensors near a main shaft bearing, a pitch bearing or a yaw bearing of a wind power generator set for acquiring vibration signals of the bearings during operation. Secondly, by sampling and recording the vibration signal output by the sensor, the sampling frequency, the sampling period and the filtering parameter are usually required to be set in the acquisition process so as to obtain the original vibration data under the running state of the bearing. The raw vibration data collected is then pre-processed, including denoising, filtering, and signal segmentation, to reduce interference with the bearing vibration signal due to environmental noise, structural resonance, and other component vibrations. On the basis, time domain analysis, frequency domain analysis or envelope analysis is carried out on the processed original vibration data so as to extract parameters such as vibration amplitude, characteristic frequency and the like. And then, comparing and judging the extracted vibration characteristic parameters with a preset threshold value or an empirical model, and evaluating the running state of the bearing. When the vibration amplitude or the characteristic parameter exceeds the set range, judging that the bearing has an abnormal state, and outputting alarm information or operation advice. In the aspect of vibration control, a passive vibration reduction mode is mostly adopted in the prior art, and vibration energy is dissipated by arranging a rubber pad, an elastic support or a damping element in a bearing supporting structure. And finally, the operation and maintenance personnel perform maintenance, lubrication or replacement treatment on the wind power bearing according to the provided vibration data and alarm information and by combining with a manual inspection result so as to ensure the normal operation of the wind power generator set. A wind power bearing fault diagnosis method, device, electronic equipment and storage medium disclosed in China patent application with publication number of CN120293523A comprises the steps of obtaining circulation frequency corresponding to an original vibration signal of a wind power bearing to be diagnosed, carrying out channelized processing on the original vibration signal based on the circulation frequency through a frequency shift filter to obtain a sub-channel signal, determining a signal to be filtered based on the sub-channel signal, optimizing a filter coefficient of the frequency shift filter based on a maximum Versoria criterion by taking the original vibration signal as a reference signal to obtain an optimal filter corresponding to the original vibration signal, carrying out frequency shift filtering on the signal to be filtered through the optimal filter to obtain a bearing fault characteristic signal, and analyzing the bearing fault characteristic signal to obtain a fault diagnosis result of the wind power bearing. However, in the process of implementing the technical scheme of the embodiment of the application, the application discovers that the above technology has at least the following technical problems: In the running process of the offshore wind turbine, the turbine structure generates complex integral vibration under the action of wind load, wave load and running load, and further, the integral vibration is transmitted to a bearing part through a transmission chain and a supporting structure, so that a large amount of structural vibration components from a non-bearing body are inevitably overlapped in bearing vibration signals. In this case, the bearing vibration signal contains bot