A method and system for monitoring high response of a fan gearbox planetary wheel bearing wear

Abstract

The application discloses a high-response monitoring method and system for gear box planetary wheel bearing wear of a fan, and the method comprises the following steps: collecting acoustic emission signals generated by gear meshing and rolling bearing operation in the gear box of the fan; extracting feature values after the acoustic emission signals are preprocessed; and when the feature values suddenly change and cross a threshold value, the planetary wheel bearing is worn out; the system comprises a collection system composed of a wideband acoustic emission sensor, a low-noise signal line, a signal amplifier and a general collection card, and a signal processing monitoring module; the output end of the wideband acoustic emission sensor is connected to the input end of the general collection card through the low-noise signal line and the signal amplifier, and is used for collecting, amplifying, AD converting and storing the acoustic emission signals of the gear box; and the signal processing monitoring module is used for processing the acoustic emission signals of the gear box and warning and reminding the wear of the planetary wheel bearing. The application realizes fast response when the planetary wheel bearing is worn, thereby protecting the sliding bearing of the gear box of the fan and improving the service life of the sliding bearing.

Description

Technical Field

[0001] This invention belongs to the field of sliding bearings, specifically relating to a method and system for monitoring the high-response wear of planetary gear bearings in a wind turbine gearbox. Background Technology

[0002] Previously, rolling bearings were used for planetary gear bearings in wind turbine gearboxes. Rolling bearing failures account for 10%-20% of all wind turbine failures, primarily due to gear meshing vibrations. Sliding bearings, however, are less susceptible to gear meshing vibrations, have a longer service life, and require less space, significantly reducing the size of wind turbine gearboxes. Therefore, many manufacturers began using sliding bearings instead of rolling bearings. However, planetary gear bearings in gearboxes are prone to edge loads due to vertical bending moments, leading to wear. While methods such as bearing reshaping exist to mitigate bearing wear, the frequent start-stop cycles of wind turbines and the relatively slow rotation speed of gearbox bearings mean that planetary gear bearings may still experience wear issues.

[0003] Current methods for monitoring sliding bearing wear mainly include oil-metal particle monitoring, radioactive isotope analysis, and acoustic emission monitoring. The first two methods, which detect wear by monitoring metal particles generated during wear in the oil circuit or the content of radioactive elements pre-added to the bearing and worn away, suffer from significant latency. While acoustic emission monitoring can detect wear by analyzing the acoustic emission signals generated by the bearing and extracting root-mean-square characteristics, requiring a 1-2 second response time, its resolution and response time are further reduced by noise generated by the sun gear rolling bearing and gear meshing in wind turbine gearboxes. Furthermore, the bearing profile in wind turbine gearboxes is extremely small; wear will disrupt this profile, leading to an increase in the bearing wear rate. Summary of the Invention

[0004] The purpose of this invention is to provide a high-response monitoring method and system for planetary gear bearing wear in wind turbine gearboxes. Compared with other wear monitoring methods, it has a higher response speed and stronger anti-interference ability, achieving rapid response to wear of planetary gear sliding bearings in wind turbine gearboxes, reducing bearing wear, and improving the service life of planetary gear bearings.

[0005] This invention is achieved through the following technical solution:

[0006] A method for monitoring high-response wear of planetary gear bearings in a wind turbine gearbox includes:

[0007] Acoustic emission signals generated by gear meshing and rolling bearing operation in the wind turbine gearbox are collected. After preprocessing, feature values ​​are extracted from the acoustic emission signals. When the feature value changes abruptly and exceeds the threshold, it indicates that the planetary gear bearing is worn.

[0008] A further improvement of this invention is that the feature extraction uses the number of acoustic emission event intervals exceeding a threshold per unit time as the judgment feature, which is defined as the window density, and specifically includes the following steps:

[0009] 1) Window the continuous acoustic emission signal and extract a 0.02s time segment for high-pass filtering;

[0010] 2) An acoustic emission time-domain signal exceeding a threshold is considered an acoustic emission event;

[0011] 3) Calculate the time interval between adjacent events. Each time the interval exceeds the spacing threshold, it is recorded as a blank window. The number of blank windows divided by the time is the blank window density.

[0012] A further improvement of this invention is that the method uses kurtosis as an auxiliary feature for judging the wear of sliding bearings. The continuous acoustic emission signal is windowed and the signal with a time length of 0.1s is extracted, and the kurtosis value is calculated after high-pass filtering.

[0013] A further improvement of this invention is that the specific formula is as follows:

[0014]

[0015]

[0016]

[0017] Where Kurtosis is the kurtosis, N is the number of signal data points, y(n) is the amplitude of the nth signal point, and σ is the standard deviation of the signal. This represents the average value of the signal.

[0018] A further improvement of this invention is that it uses changes in acoustic emission characteristic values ​​to determine whether the sliding bearing of the wind turbine gearbox is worn. When the density of the signal segment window decreases below the threshold or the kurtosis increases above the threshold, the bearing is worn.

[0019] A further improvement of the present invention is that the threshold for wear occurrence is obtained by wear testing of the prototype.

[0020] A high-response monitoring system for wear of planetary gear bearings in a wind turbine gearbox includes an acquisition system consisting of a wideband acoustic emission sensor, a low-noise signal line, a signal amplifier, and a universal acquisition card, as well as a signal processing and monitoring module.

[0021] The output of the wideband acoustic emission sensor is connected to the input of a general-purpose acquisition card via a low-noise signal line and a signal amplifier. This is used to acquire the acoustic emission signal from the gearbox and perform amplification, AD conversion, and storage.

[0022] The signal processing and monitoring module is used for gearbox acoustic emission signal processing and planetary gear bearing wear warning alerts.

[0023] A further improvement of the present invention is that the signal processing and monitoring module extracts the window and kurtosis features after preprocessing the signal, compares them with the threshold to determine whether the planetary gear bearing has worn, and issues an alarm when wear occurs.

[0024] The present invention has at least the following beneficial technical effects:

[0025] This invention provides a high-response monitoring method and system for planetary gear bearing wear in wind turbine gearboxes. It determines whether planetary gear bearing wear has occurred based on characteristic values ​​and proposes a novel acoustic emission feature window density. This feature improves the temporal resolution and anti-interference characteristics of acoustic emission technology, enabling monitoring of planetary gear bearing wear in the high-noise environment of wind turbine gearboxes. Simultaneously, this feature also improves the temporal resolution of acoustic emission technology, shortening the response time of planetary gear bearing wear and thus extending bearing life. Kulkerity features are introduced as an auxiliary judgment feature, which has strong anti-interference characteristics, improving the accuracy of the monitoring method and enabling accurate high-response monitoring of sliding bearing wear in complex noise environments. Attached Figure Description

[0026] Figure 1 This is a time-domain diagram of the high-frequency noise signal in the wind turbine gearbox.

[0027] Figure 2 This is a time-domain diagram of the high-frequency acoustic emission signal caused by the wear of planetary gears in the wind turbine gearbox.

[0028] Figure 3 This is a diagram illustrating the definition of an empty window.

[0029] Figure 4 It is a wind turbine sliding bearing test bench and acoustic emission test system, wherein 1 is a loading device, 2 is a sliding bearing, 3 is a tapered roller bearing, 4 is a main shaft, 5 is a torque sensor, 6 is a gearbox, 7 is a drive motor, and 8 is a broadband acoustic emission sensor.

[0030] Figure 5 This is a comparison chart of the difference in window density between worn and non-worn signals under different spacing thresholds.

[0031] Figure 6 This is a comparison chart showing the differences in acoustic emission characteristics between worn and unworn signals.

[0032] Figure 7 A time-resolution comparison of different acoustic emission characteristics of worn and unworn signals. Detailed Implementation

[0033] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0034] Figure 1 As shown, the meshing of gears and the operation of rolling bearings in the wind turbine gearbox generate high-frequency acoustic emission signals. Figure 2 As shown, the acoustic emission signal when the planetary gear bearing wears out is related to... Figure 1 The small difference in signal strength leads to low accuracy in monitoring sliding bearing wear using traditional acoustic emission technology. Furthermore, current methods for monitoring sliding bearing wear based on acoustic emission technology require a response time of 1-2 seconds, which is even longer in high-noise environments such as wind turbine gearboxes.

[0035] like Figure 3 As shown, an acoustic emission event is defined as a signal exceeding a threshold voltage and persisting for a certain period of time. The time interval between adjacent acoustic emission events varies, and an interval exceeding the threshold is defined as a window. The number of windows per unit time is defined as the window density. The window density is used as the primary characteristic for determining whether a planetary gear bearing is worn. The specific steps include:

[0036] 1) Collect ambient noise in the field and determine the threshold voltage for the number of events. The threshold voltage should be greater than or equal to the ambient sound emission signal in the field.

[0037] 2) Determine the interval threshold through prototype testing. Acoustic emission signals were collected multiple times under normal operation and planetary gear bearing oil cut-off conditions of the prototype. After preprocessing, the difference in the gap density of the normal operation and wear signals under different interval thresholds was analyzed, and the interval with the largest difference was selected as the interval threshold.

[0038] 3) Window the continuous acoustic emission signal and extract a 0.02s time length signal for high-pass filtering.

[0039] 4) An acoustic emission time-domain signal exceeding the threshold and lasting for a period of time is considered an acoustic emission event.

[0040] 5) Calculate the time interval between adjacent events. Each time the interval exceeds the preset spacing, it is recorded as a blank window. The number of blank windows divided by the time is the blank window density.

[0041] Kurtosis is used as an auxiliary feature for judging the wear of sliding bearings. The continuous acoustic emission signal is windowed and truncated to a time length of 0.1s. After high-pass filtering, the kurtosis value is calculated. The formula is as follows:

[0042]

[0043]

[0044]

[0045] Where N is the number of signal data points, y(n) is the amplitude of the nth signal point, and σ is the signal standard deviation. This represents the average value of the signal.

[0046] Prototype testing was conducted to determine the threshold value for the characteristic value. Acoustic emission signals were collected multiple times under both normal operation and planetary gear bearing lubrication interruption conditions. The average value of the characteristic value under both conditions was used as the threshold. Changes in the acoustic emission characteristic value were used to determine whether the sliding bearing of the wind turbine gearbox had worn down. When the density of the signal segment window decreased to below the threshold or the kurtosis increased to above the threshold, bearing wear was indicated.

[0047] The signal processing and monitoring module inputs the previously obtained event number threshold voltage, interval threshold, and feature value threshold. The acquisition system collects the acoustic emission signal of the sliding bearing of the wind turbine gearbox in real time. After preprocessing the signal, the signal processing and monitoring module extracts the window and kurtosis features, compares them with the threshold to determine whether the planetary gear bearing has worn, and issues an alarm when wear occurs.

[0048] Experimental verification example:

[0049] The effectiveness of the method was verified using a wind turbine sliding bearing test bench, such as... Figure 4 As shown, the test setup includes a wind turbine sliding bearing friction test bench and an acoustic emission acquisition and analysis system. The test bench mainly consists of a sliding bearing 2 (diameter 100 mm, width 80 mm, radial clearance 0.1 mm), a tapered roller bearing 3 (providing interference noise), a main shaft 4, a torque sensor 5 (for measuring bearing friction torque), a gearbox 6 (providing interference noise), a loading device 1, a drive motor 7, and a support structure. The acquisition and analysis system mainly includes a broadband acoustic emission sensor 8 (response frequency 50 kHz - 1300 kHz), an amplifier (amplification factor 60 dB), a general-purpose acquisition card (sampling frequency 4 MHz), and a signal processing module.

[0050] An acoustic emission sensor was installed at the bottom of the sliding bearing where wear might occur. The sensor was connected sequentially to an amplifier, a data acquisition card, and a signal processing and monitoring module. Ambient noise was collected when the test bench was off, with high-frequency signals not exceeding 0.05V and an event threshold voltage of 0.05V. Acoustic emission signals were continuously collected from the sliding bearing under a load of 2KN / 4KN, a speed of 320rpm, and with sufficient lubrication. Simulation calculations indicated that the sliding bearing was under fluid lubrication and there was no wear. The lubrication supply was then stopped, causing a mixed lubrication state. Wear occurred in the sliding bearing, and acoustic emission signals were continuously collected. The signal processing and monitoring module processed the two states of signals, calculating the difference in window density between the two states under different spacing thresholds, such as... Figure 5 As shown, the difference is largest at a spacing threshold of 0.2125ms, and the load has almost no effect on it; therefore, a spacing threshold of 0.2125ms is chosen. Windowing and truncation of the continuous signal with different time widths are performed. The average difference and temporal resolution of features such as root mean square value, kurtosis, empty window, and Shannon entropy under different time widths in the two states are analyzed. Figure 6 and Figure 7 As shown, there is a large difference between kurtosis and the empty window, making them easier to distinguish and judge. The empty window time resolution reaches 0.02s, which is several times higher than other features, enabling a fast response.

[0051] Although the present invention has been described in detail above with general descriptions and specific embodiments, modifications or improvements can be made to it, which will be obvious to those skilled in the art. Therefore, all such modifications or improvements made without departing from the spirit of the present invention fall within the scope of protection claimed by the present invention.

Claims

1. A method for monitoring high-response wear of planetary gear bearings in a wind turbine gearbox, characterized in that, include: Acoustic emission signals generated by gear meshing and rolling bearing operation in the wind turbine gearbox are collected. After preprocessing, the acoustic emission signals are used for feature value extraction. When the feature value changes abruptly and exceeds the threshold, it indicates that the planetary gear bearing is worn. Feature extraction uses the number of acoustic emission events exceeding a threshold within a unit of time as a judgment feature, defined as the window density, and specifically includes the following steps: 1) Window the continuous acoustic emission signal and extract a 0.02s time segment for high-pass filtering; 2) An acoustic emission time-domain signal exceeding a threshold is considered an acoustic emission event; 3) Calculate the time interval between adjacent events. Each time the interval exceeds the spacing threshold, it is recorded as a blank window. The number of blank windows divided by the time is the blank window density. This method uses kurtosis as an auxiliary feature for judging the wear of sliding bearings. The continuous acoustic emission signal is windowed and the signal with a time length of 0.1s is extracted. After high-pass filtering, the kurtosis value is calculated. The wear of the sliding bearing in the wind turbine gearbox is determined by the change in acoustic emission characteristic value. When the density of the signal segment window decreases below the threshold or the kurtosis increases above the threshold, the bearing is considered to be worn.

2. The method for monitoring high-response wear of planetary gear bearings in a wind turbine gearbox according to claim 1, characterized in that, The specific formula is as follows: Where Kurtosis is the kurtosis and N is the number of signal data points. The amplitude of the nth signal point. The standard deviation of the signal. This represents the average value of the signal.

3. The method for monitoring high-response wear of planetary gear bearings in a wind turbine gearbox according to claim 1, characterized in that, The threshold for wear was obtained from prototype wear tests.

4. A high-response monitoring system for wear of planetary gear bearings in a wind turbine gearbox, characterized in that, The system is based on the high-response monitoring method for wear of planetary gear bearings in a wind turbine gearbox as described in claim 1, and includes an acquisition system consisting of a wideband acoustic emission sensor, a low-noise signal line, a signal amplifier and a general acquisition card, as well as a signal processing and monitoring module; The output of the wideband acoustic emission sensor is connected to the input of a general-purpose acquisition card via a low-noise signal line and a signal amplifier. This is used to acquire the acoustic emission signal from the gearbox and perform amplification, AD conversion, and storage. The signal processing and monitoring module is used for gearbox acoustic emission signal processing and planetary gear bearing wear warning alerts.

5. The high-response monitoring system for wear of planetary gear bearings in a wind turbine gearbox according to claim 4, characterized in that, After preprocessing the signal, the signal processing and monitoring module extracts the window and kurtosis features, compares them with the threshold to determine whether the planetary gear bearing is worn, and issues an alarm when wear occurs.

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