CN113865860A - Gear tooth breakage fault diagnosis method based on frequency conversion sideband RMS trend analysis - Google Patents
Gear tooth breakage fault diagnosis method based on frequency conversion sideband RMS trend analysis Download PDFInfo
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Abstract
The invention discloses a gear tooth breakage fault diagnosis method based on frequency conversion sideband RMS trend analysis, which comprises the following steps of: step S1: acquiring gear fault test data, and preprocessing the test data; step S2: acquiring the rotating speed of the gear through a rotating speed sensor, and calculating to obtain related frequency; step S3: performing band-pass filtering on the full-band signal to obtain a front 3-order gear meshing frequency signal and a fault gear frequency conversion modulation signal; step S4: filtering and removing the meshing frequency signal of the first 3-order gear to obtain a fault gear frequency conversion sideband signal near the meshing frequency of the first 3-order gear; step S5: calculating the RMS value of a fault gear frequency conversion sideband filtering signal near the meshing frequency of the first 3-order gear, and drawing a trend graph; the method can better solve the problem that the gear tooth breakage characteristic signal is easy to be submerged in a full-band non-principal component signal, can effectively identify the fault burst and the fault degradation stage, and has certain engineering practice significance.
Description
Technical Field
The invention relates to the technical field of gear fault diagnosis, in particular to a gear broken tooth fault diagnosis method based on frequency conversion sideband RMS trend analysis.
Background
In the practical application of the current engineering, a time domain spectrogram and a frequency domain spectrogram are combined for fault diagnosis of the gear to judge the fault type, and the severity of the fault is determined by referring to the trend of RMS (root Mean square) root Mean square values, but the traditional RMS trend analysis is to be carried out on full-band vibration signals, wherein the full-band vibration signals comprise main shaft rotating frequency, gear meshing frequency of each stage, gear rotating frequency, bearing fault frequency, fault frequency side frequency of each bearing, random noise and the like, and a full-band RMS trend analysis method cannot effectively display the fault trend analysis of fault characteristic signals with smaller energy proportion in the full band, and based on the rotating frequency side frequency RMS trend analysis method, the problems can be overcome, and the fault development trend [1] of gear tooth breakage can be effectively identified.
The full-band RMS trend analysis method calculates the RMS of each data by collecting vibration time domain signals of the gear without filtering, draws an RMS trend chart according to a time sequence and reflects the development trend of the tooth breakage fault of the gear. However, the actual working condition is complex, the vibration time domain signal contains a lot of information which is useless to the tooth breaking fault, the calculation of the RMS value of the tooth breaking characteristic signal is influenced, and the RMS value of the full frequency band cannot effectively reflect the tooth breaking characteristic. Through filtering processing, the meshing frequency of the broken tooth gear and a frequency conversion modulation signal thereof are obtained, and the broken tooth fault characteristics can be effectively reflected.
A frequency conversion sideband analysis method is applied to the broken tooth fault diagnosis of a gear pair, and the broken tooth fault is characterized in that the meshing frequency of the fault gear pair is accompanied with the frequency conversion modulation of a broken tooth gear, and the meshing frequency, the amplitude of the frequency conversion and the modulation number of the frequency conversion show an ascending trend along with the fault deterioration. In the broken tooth fault, the multi-order meshing frequency in the excitation period, the first 3-order meshing frequency and the fault gear frequency conversion modulation signal can effectively reflect the fault characteristics [2 ].
A gear fault diagnosis method disclosed in Chinese patent literature, whose publication number is CN1128810006A, includes the problem that it is not possible to accurately distinguish the signal which is easy to be "submerged" in the full-band non-main component in the gear tooth breaking characteristic signal, and it is not possible to effectively identify the fault burst and fault degradation stage.
Disclosure of Invention
In view of the above problems, the invention provides a gear tooth breakage fault diagnosis method based on frequency conversion sideband RMS trend analysis, which is used for solving the problem that the traditional full-frequency-band RMS trend analysis cannot reflect the development trend of the tooth breakage fault when the gear tooth breakage fault is diagnosed in the prior art.
A gear tooth breakage fault diagnosis method based on conversion sideband RMS trend analysis comprises the following steps:
step S1: acquiring gear fault test data, and preprocessing the test data;
step S2: acquiring the rotating speed of the gear through a rotating speed sensor, and calculating to obtain related frequency;
step S3: the full-band signal is subjected to multiple times of band-pass filtering to respectively obtain a first 3-order gear meshing frequency signal and a fault gear frequency conversion modulation signal, and the 3 times of filtering results are accumulated to obtain a first 3-order meshing frequency and a fault gear frequency conversion modulation signal;
step S4: the full-band signal is subjected to multiple times of band-pass filtering to obtain a first 3-order gear meshing frequency signal and a fault gear frequency conversion sideband signal, a first 3-order meshing frequency and a fault gear frequency conversion sideband time domain signal are obtained, and the time domain signal is converted into a frequency domain signal by performing fast Fourier transform on the frequency domain signal;
step S5: and (3) performing inverse Fourier transform on the frequency domain data after the first 3-order meshing frequency is set to zero to obtain a time domain signal of the frequency conversion sideband of the fault gear, calculating the RMS value of the time domain signal, drawing the RMS trend of the frequency conversion sideband according to a time sequence and drawing a trend graph.
Further, in step S1, the gear failure data is researched to be a pair of gear pairs, the failure position and the characteristic are broken teeth of the pinion, a plurality of data are selected and sorted according to time, the preprocessing includes screening data with similar working conditions, the rotational speed of the gear pair has a linear relationship with the RMS value, the data with similar rotational speed is preferably selected, the similar data are compared, the linear relationship between the rotational speed of the gear pair and the RMS value can be reflected, and data calculation is facilitated.
Further, in step S2, the gear rotation speed is acquired by the rotation speed sensor, so as to calculate the relevant meshing frequency and gear rotation frequency.
Further, in step S3, a butterworth filter with a small influence on the vibration amplitude is selected to filter the full-band signal, the first 3-order meshing frequency is selected as the center in the filtering range, the bandwidth is the frequency range [3] of the multiple-time fault gear frequency conversion, the fault gear frequency conversion modulation signal displays the gear tooth breakage characteristic, and the signal which is easily submerged in the full-band non-main component in the gear tooth breakage characteristic signal can be identified more effectively.
Further, in step S4, the test data is converted into a spectrogram by fast fourier transform, the first 3-order gear meshing frequency signal is filtered and removed, only the faulty gear frequency conversion sideband signal of the first 3-order gear meshing frequency is retained, and the fault burst and the fault degradation stage can be effectively identified.
Further, step S5 is to perform inverse fourier transform on the processed spectrum data to time domain data, calculate the RMS value of the frequency conversion sideband filtered signal of the faulty gear near the meshing frequency of the previous 3-step gear, and plot a trend graph of the RMS value over time.
The beneficial technical effects of the invention are as follows:
compared with the traditional full-band RMS trend analysis and meshing frequency and frequency conversion sideband combined RMS trend analysis, the method can better solve the problem that a gear tooth breaking characteristic signal is easy to be submerged in a full-band non-principal component signal, can effectively identify a fault burst and a fault degradation stage, and has certain engineering practice significance.
Drawings
The present invention may be better understood by reference to the following description taken in conjunction with the accompanying drawings, which are incorporated in and form a part of this specification, and which are used to further illustrate preferred embodiments of the present invention and to explain the principles and advantages of the present invention.
FIG. 1 is a schematic gear pair mesh;
FIG. 2 is a schematic view of a gearbox drive train;
FIG. 3 is a plot of full band, mesh frequency and transition sideband combinations and transition sideband RMS trends;
fig. 4 is a graph of the spectrum of various points of test data.
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.
Example (b):
the invention provides a gear broken tooth fault diagnosis method based on frequency conversion sideband RMS trend analysis, which extracts a gear front 3-order meshing frequency signal and a fault gear frequency conversion sideband signal through band-pass filtering, sets the gear front 3-order meshing frequency to zero, removes frequency interference irrelevant to the diagnosis broken tooth fault in a frequency spectrum, only keeps the broken tooth gear frequency conversion sideband signal to perform RMS trend drawing, and realizes the development of the gear broken tooth fault and the identification of a degradation stage.
Firstly, test data are obtained, a pair of gear pairs are selected as research objects, the fault positions and the characteristics are gear broken teeth, a plurality of data are selected and sorted according to time, the change trend of RMS along with time is concerned, the actual running state of the gear changes along with the working condition, the rotating speed of the gear pairs and the RMS value belong to a linear relation, vibration data under the similar working condition are selected to ensure that the energy of the gear train is basically consistent when the gear runs, and the data with the similar rotating speed are preferably selected. Fig. 1 shows a meshing schematic diagram of the gear pair.
The broken gear of the gear is generally characterized in that a plurality of groups of fault gear frequency conversion sidebands are generated near the meshing frequency of the first few-order gear, the gear rotating speed is required to be obtained according to a rotating speed sensor, so that the meshing frequency of the first 3-order gear and the fault gear frequency conversion are calculated, and the calculation formula is shown as (1), (2) and (3) [4 ]:
in formula (1): f. ofm1Is the 1 st order mesh frequency (unit: Hz) and R of the gear pair1Is the pinion shaft speed (unit: rpm), N1Is the number of pinion teeth, R2Is the rotation speed (unit: rpm) of the big gear shaft, N2Is the large gear tooth count.
fm1＝fm2/2＝fm3/3 (2)
In formula (2): f. ofm2Is the 2 nd order mesh frequency (unit: Hz), f of the gear pairm3Is the 3 rd order mesh frequency (unit: Hz) of the gear pair.
In formula (3): f. ofband1Is the pinion frequency (unit: Hz), fband2The large gear rotates frequency (unit: Hz), and the broken gear is a small gear.
For data filtering, the first 3-order meshing frequency is preferably used as the center frequency, the multiple pinion rotating frequency sideband is used as the filtering bandwidth, and the Butterworth filter with good equal ripple effect is selected as the filter. During the first filtering, only retaining the data in the range of the 1 st order meshing frequency and the multiple gear frequency conversion sideband, during the second filtering, only retaining the data in the range of the 2 nd order meshing frequency and the multiple gear frequency conversion sideband, during the 3 rd filtering, only retaining the data in the range of the 3 rd order meshing frequency and the multiple gear frequency conversion sideband, and accumulating the 3 times of filtering results to obtain the previous 3 th order meshing frequency and the pinion sideband time domain signal.
And acquiring the first 3-order meshing frequency and pinion sideband time domain signals, and performing fast Fourier transform on the signals to convert the time domain signals into frequency domain signals. Due to signal sampling, software calculation processing, spectrum resolution and other reasons, the meshing frequency in the actual spectrum is not a single spectral line but has a certain bandwidth, and signals in the certain bandwidth of each spectral line need to be removed [3 ]. In order to ensure that the meshing frequency is completely set to zero, the value of a spectral line occupied by 1 small gear rotating frequency bandwidth on the left side and the right side of the meshing frequency respectively in a frequency spectrum is set to zero by taking the meshing frequency as a center, and the number of sampling points occupied by the gear rotating frequency bandwidth is calculated as shown in (4) and (5):
in formula (4): f. ofbeltIs the spectral resolution (unit: Hz), fsIs the sampling frequency (unit: Hz), and n is the number of sampling points.
In formula (5): f. ofnum isThe pinion rotates the number of sampling points occupied by the frequency bandwidth.
And (3) performing inverse Fourier transform on the frequency domain data after the first 3-order meshing frequency is set to zero to obtain a time domain signal of the frequency conversion sideband of the pinion, calculating the RMS value of the time domain signal, and drawing the RMS trend of the frequency conversion sideband according to time sequence.
The specific implementation mode is as follows:
the gear broken tooth vibration data used by the invention is derived from the broken tooth radial vibration acceleration data of the pinion of the speed shaft in a gear box of a certain wind power generation project, and the data information is shown in table 1.
Table 1 analytical data details
| Sensor measuring point | Radial direction of medium speed shaft of gear box |
| Gear train high speed shaft speed R | 1650-1750 rpm |
| Time of data | 2020.10.01-2021.01.15 |
| Sampling frequency | 25600Hz |
| Single data length | 102400 Point |
| Total amount of data | 310 points 102400 |
The transmission of the gear box is a one-stage planetary two-stage parallel 3-stage transmission, 3-stage speed increasing is carried out by a 1-stage low-speed planetary gear train, a 2-stage medium-speed gear train and a 3-stage high-speed gear train, and a schematic diagram of a transmission chain of the gear box is shown in figure 2. TABLE 2 Transmission parameters for a 3-stage gearbox
TABLE 2 three-stage gearbox drive parameters
| Z1 | Grade-1 planetary-grade inner gear ring | 92/helical teeth |
| Z2 | 1-stage planetary gear | 36/helical tooth |
| Z3 | 1-level planetary sun gear | 20/helical tooth |
| Z4 | 2-stage parallel shaft low-speed gear | 94/helical tooth |
| Z5 | 2-stage parallel shaft medium- |
21/helical teeth |
| Z6 | 2-stage parallel shaft medium-speed large gear | 125/helical tooth |
| Z7 | 2-stage parallel shaft high-speed gear | 24/helical teeth |
The rotating speed sensor is arranged at a high-speed shaft measuring point of the gear box, the rotating speed data of the high-speed shaft of the gear box is read, the meshing frequency of a gear train of a middle-speed shaft and the rotating frequency of a pinion of the middle-speed shaft can be calculated according to the rotating speed data of the high-speed shaft of the gear box, and the calculation formulas are shown as (6) and (7):
fm1＝fband×Z5 (7)
in formula (6): f. ofbandThe rotation frequency (unit: Hz) of the pinion of the medium speed shaft, the rotation speed (unit: rpm) of the high speed shaft, and Z7Is the number of teeth, Z, of the high-speed shaft gear6The number of teeth of the large gear of the medium speed shaft.
In formula (7): f. ofm1Is the 1 st order meshing frequency (unit: Hz) and Z of the gear train of the medium speed shaft5Is the number of teeth of the pinion of the medium speed shaft.
2 nd order meshing frequency f of medium speed shaft gear trainm2And a meshing frequency f of order 3m3Can be calculated according to equation (2) with the high gear train speed R being 1700 rpm for exampleband＝(1700*24)/(60*125)＝5.44Hz，fm1＝5.44*21＝114.24Hz，fm2＝fm1*2＝228.48Hz，fm3＝fm1*3＝342.72Hz。
And filtering each data for 3 times, taking the front 3-order meshing frequency as the center frequency and the 5-time pinion frequency conversion sideband as the filtering range, accumulating the filtered data, and sequencing the data according to the time sequence to obtain the meshing frequency and frequency conversion sideband combined RMS trend.
And performing fast Fourier transform on the meshing frequency and frequency conversion sideband combined data to a frequency domain, setting spectral line amplitudes of rotating frequency bandwidths of 1 medium-speed-axis pinion gear on two sides of the first 3-order meshing frequency to zero, converting the spectral line amplitudes into time domain data through inverse Fourier transform, and sequencing according to time sequence to obtain the RMS trend of the rotating frequency sidebands of the first 3-order medium-speed-axis pinion gear.
The results of full-band, first 3-order, medium-speed shaft pinion meshing frequency and frequency-conversion sideband combination and frequency-conversion sideband RMS trend analysis are shown in FIG. 3, and FIG. 3.a is an RMS trend graph of a full-band signal. FIG. 3.b is a plot of the combined RMS trend of the mesh frequency and the transition frequency sideband. FIG. 3.c is a plot of the transition frequency sideband RMS trend. FIG. 3.a shows no significant gear tooth breakage trend effective information; in the BC region of fig. 3.b, the RMS floor present rises overall, but not significantly.
C, analyzing the trend of the frequency conversion sideband RMS in detail, and gradually increasing the RMS value between the mark point A and the mark point B; RMS values between the mark point B and the mark point C are basically kept stable; the RMS value between the mark point C and the mark point D is linearly decreased; the RMS value of the region after the marker D remains stable and substantially matches the region before the marker A. The CD section has a straight line descending and is stopped for maintenance.
Detailed analysis was performed for the transition frequency sideband RMS trend of the first 3 order medium speed shaft mesh frequency points selected before point a, AB segment, BC segment and D point after point a of fig. 3. c. The specific selection points are shown in table 3, and the spectrograms of points a to f are shown in fig. 4, which are analyzed in detail as follows.
TABLE 3 Trans-frequency sideband RMS Trend graph analysis Point information
| Selecting interval | Data points | Number of |
| Before point A | Point a (2020.10.08) | 1 |
| AB rising zone | Point b (2020.10.20); point c (2020.10.25); | 2 |
| BC plateau | Point d (2020.11.10); point e (2020.11.27); | 2 |
| after point D | Point f (2020.12.20); | 1 |
1) fig. 4.a is a frequency spectrum before a trend rising point A, the frequency spectrum is mainly based on the 3-step meshing frequency in front of a medium-speed shaft gear, no obvious pinion rotation frequency is found in a rotation frequency sideband, and random noise is mainly used;
2) FIGS. 4.b and 4.c are spectrum diagrams of an AB interval, the amplitudes of the meshing frequency signals of the first 3-order medium-speed shaft gear are increased, and the frequency number and the amplitudes of the medium-speed shaft pinion gears in the frequency conversion sideband are increased;
3) 4.d and 4.e are spectrum diagrams of the BC interval, the amplitude of the meshing frequency signal of the first 3-order medium-speed shaft gear is basically stable, the number of the pinion rotating frequencies and the 2-order before the amplitude are increased, and the 3 rd order is decreased;
4) and f is a frequency spectrum after the point D, the frequency spectrum is mainly based on the meshing frequency of the front 3 orders of the medium-speed shaft gear, the obvious pinion rotation frequency is not found in the rotation frequency sideband, and random noise is mainly used.
In conclusion, the front 3-order meshing frequency signals of the intermediate speed shaft gear before and after the gear fault are the main signals; in the AB interval of FIG. 3.C, the front 3-order meshing frequency signal amplitude of the intermediate speed shaft gear and the number and amplitude of the rotating frequency sidebands of the pinion both show rising trends, and belong to the failure burst stage; in the BC stable interval, the amplitude of the front 3-order meshing frequency signal of the medium-speed shaft gear is basically kept unchanged, and the number and the amplitude of the rotating frequency sidebands of the pinion gear show an ascending trend, belonging to a fault degradation stage.
Therefore, the gear tooth breakage fault diagnosis method based on the frequency conversion sideband RMS trend analysis can effectively identify the gear tooth breakage fault burst and the fault degradation stage.
The above-described embodiment is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and other variations and modifications may be made without departing from the spirit of the invention as set forth in the claims.
Claims (7)
1. A gear tooth breakage fault diagnosis method based on frequency conversion sideband RMS trend analysis is characterized by comprising the following steps:
step S1: acquiring gear fault test data, and preprocessing the test data;
step S2: acquiring the rotating speed of the gear through a rotating speed sensor, and calculating to obtain related frequency;
step S3: performing band-pass filtering on the full-band signal to obtain a front 3-order gear meshing frequency signal and a fault gear frequency conversion modulation signal;
step S4: filtering and removing the meshing frequency signal of the first 3-order gear to obtain a fault gear frequency conversion sideband signal near the meshing frequency of the first 3-order gear;
step S5: and calculating the RMS value of the fault gear frequency conversion sideband filtering signal near the meshing frequency of the first 3-step gear, and drawing a trend graph.
2. The method for diagnosing the gear tooth breakage fault based on the frequency conversion sideband RMS trend analysis as claimed in claim 1, wherein the gear fault data in step S1 is researched to be a pile of gear pairs, the fault position is the gear tooth breakage of the characteristic position of one of the gears, a plurality of data are selected and sorted according to time, and the preprocessing comprises screening vibration data with similar working conditions, preferably data with similar rotating speed.
3. The method as claimed in claim 2, wherein a plurality of data are selected and sorted according to time, and the change trend of RMS along with time is concerned.
4. The method as claimed in claim 1, wherein the step S2 is implemented by obtaining gear input shaft speed data through a rotation speed sensor, and calculating the gear pair meshing frequency and the gear rotation frequency.
5. The method as claimed in claim 1, wherein in step S3, the bandwidth is a frequency range of multiple times of the fault gear frequency conversion, and the fault gear frequency conversion modulation signal displays the gear tooth breaking characteristics.
6. The method for diagnosing the gear tooth breakage fault based on the conversion sideband RMS trend analysis as claimed in claim 1, wherein in step S4, the test time domain vibration data is converted into frequency spectrum data by fast Fourier transform, the meshing frequency signal of the first 3-order gear is filtered and removed, and only the conversion sideband signal of the fault gear near the meshing frequency of the first 3-order gear is reserved.
7. The method for diagnosing the gear tooth breakage fault based on the frequency conversion sideband RMS trend analysis as claimed in claim 1, wherein step S5 inverse Fourier transforms the processed frequency spectrum data into time domain data, calculates the RMS value of the fault gear frequency conversion sideband filtering signal near the previous 3-order gear meshing frequency, and draws a trend graph.
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