CN107271181B - A kind of weak impact component extracting method of epicyclic gearbox - Google Patents
A kind of weak impact component extracting method of epicyclic gearbox Download PDFInfo
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- G01M13/00—Testing of machine parts
- G01M13/02—Gearings; Transmission mechanisms
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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Abstract
A kind of weak impact component extracting method of epicyclic gearbox, steady modulation ingredient abundant is isolated from original vibration signal by DRS method first, improve impact signal frequency band signal-to-noise ratio, obtain residual signal, then frequency band is most preferably impacted using SK method identification residual signal and obtain its centre frequency and filter bandwidth parameters, residual signal is filtered according to the filter of this parameter designing and carries out Envelope Analysis, to realize epicyclic gearbox fault identification and diagnosis；Compared with spectrum kurtosis identification impact frequency band is used alone, this method more accurate can position best frequency band, it is more obvious filter shock characteristic in time-domain signal, and failure-frequency more highlights in envelope spectrogram, and the epicyclic gearbox source of trouble can effectively be accurately positioned.
Description
Technical field
The present invention relates to epicyclic gearbox fault diagnosis technology field, in particular to a kind of weak impact ingredient of epicyclic gearbox
Extracting method.
Background technique
Planetary gear transmission mechanism has the advantages that small in size, light-weight and transmission ratio is big, is therefore widely used in boat
It, wind-powered electricity generation and other large complicated mechanical equipments.The harsh environments of low-speed heave-load frequently result in its sun gear, planetary gear etc.
Key components and parts are seriously worn with failures such as fatigue cracks, seriously affect the reliability of mechanical equipment, and bury great peace
Full hidden danger.Due to the special construction and complex working condition of epicyclic gearbox, its vibratory response is caused to show as strong nonlinearity, non-stationary
Property with multi-mode aliasing, it is existing in relation to fixed axis gear box fault diagnosis theory and technology often to epicyclic gearbox failure
It is helpless, therefore be always the field hot spot and difficult point for the research in terms of its fault diagnosis.
Usually there is multi-mode aliasing in the vibratory response due to caused by local fault, response signal is by steadily modulating
Ingredient is coupled to form with impact modulation ingredient, but existing some diagnostic methods often ignore the coupling phenomenon of the two, only
Type is diagnosed fault by extracting its steady modulation ingredient, such as directly passes through sideband information or envelope demodulation method.
But due to the vibration transfer path of its time-varying and multipair gear meshing characteristic simultaneously, it is steady modulate ingredient be usually relatively complex and
It is chaotic.The modulation of the Dynamic Signal caused by the component failure is outer, the change of multipair planetary gear engagement and sensor relative position
Also steady modulation ingredient can be generated.In addition, mesh vibration intercouples and increases and is steadily modulated into while multipair gear pair
The complexity divided, abundant and complicated sideband information are usually that the accurate positionin of the source of trouble brings difficulty.In contrast, impact at
Divide often fairly simple and include fault message abundant, by extracting impact ingredient come trouble-shooting feature, tends to standard
Determine that the position source of trouble, spectrum kurtosis (Spectral Kurtosis, write a Chinese character in simplified form SK) method are widely used in impact signal and extract and know
Not, it can be achieved that preferable fault location.But in early-stage weak fault, impact ingredient is usually fainter and is easy to be submerged in
In noise and steady modulated signal abundant, cause SK method that cannot accurately identify impact frequency band.J.Antoni propose it is discrete with
Machine separates (Discrete random separation, write a Chinese character in simplified form DRS) method, it can be achieved that the steadily separation of modulated signal, the side DRS
Method can not directly obtain impact signal, still can there is much noise in the residual signal after filtering out steady modulated signal, but
This method can effectively improve impact frequency band signal-to-noise ratio, provide an accurately spectrum kurtosis distribution for SK method.
Summary of the invention
In order to overcome the disadvantages of the above prior art, the object of the present invention is to provide a kind of weak impacts of epicyclic gearbox
Component extracting method first passes through DRS method and removes steady modulated signal, improves impact frequency band signal-to-noise ratio, then by SK from surplus
Impulse fault feature is extracted in remaining signal, can effectively realize that weak impact feature extraction and the source of trouble position.
In order to achieve the above object, the technical scheme adopted by the invention is as follows:
A kind of weak impact component extracting method of epicyclic gearbox, comprising the following steps:
Step 1: using the high frequency sampling epicyclic gearbox original vibration signal x (t) of acceleration transducer；
Step 2: for original vibration signal x (t) design DRS filtering frequency response function H (f), then to original vibration signal x
(t) product calculation is done in frequency with DRS filtering frequency response function H (f), obtains residual signal r (t) and steady modulated signal x (t)-r
(t)；
Step 3: by the optimal impact frequency band of SK method identification residual signal r (t), obtaining centre frequency fcWith filter band
Wide parameter Bw；
Step 4: by centre frequency fc, filter bandwidth parameters BwFilter is designed, then residual signal r (t) is filtered
Wave obtains filtering signal a (t)；
Step 5: Envelope Demodulation Analysis being carried out to filtering signal a (t), envelope signal b (t) is obtained, then to envelope signal b
(t) Fast Fourier Transform (FFT) is done, envelope signal frequency spectrum b (f) is obtained；Finally according to filtering signal a (t) and envelope signal frequency spectrum b
(f) planetary gear fault identification and classification are realized.
It is as follows to filter frequency response function H (f) expression formula by DRS in the step 2:
Wherein, ρ represents original vibration signal signal-to-noise ratio, and N represents filter length, and W (f) represents the frequency domain of rectangular window function
Expression.
The invention has the benefit that
The present invention passes through DRS method first and isolates steady modulation ingredient abundant from original vibration signal x (t), mentions
HI high impact signal band signal-to-noise ratio, obtains residual signal r (t), is then most preferably impacted using SK method identification residual signal r (t)
Frequency band simultaneously obtains its centre frequency fcWith filter bandwidth parameters Bw, residual signal is filtered according to the filter of this parameter designing
And Envelope Analysis is carried out, to realize epicyclic gearbox fault identification and diagnosis.Frequency band is impacted with spectrum kurtosis identification is used alone
It compares, this method more accurate can position best frequency band, it is more obvious filter shock characteristic in time-domain signal, and in envelope spectrogram
Failure-frequency more highlights, and the epicyclic gearbox source of trouble can effectively be accurately positioned.
Detailed description of the invention
Fig. 1 is the flow chart of present invention method.
Fig. 2 is embodiment planetary gear box structure schematic diagram.
Fig. 3 is embodiment original vibration signal by the DRS steady modulated signal filtered and residual signal time domain wave
Shape.
Fig. 4 is that embodiment residual signal composes kurtosis figure.
Fig. 5 is that embodiment original vibration signal composes kurtosis figure.
Fig. 6 is the optimal filter time domain waveform of embodiment residual signal and original vibration signal, corresponding filtered band point
It is not determined by the optimal frequency band of Fig. 4 and Fig. 5 spectrum kurtosis positioning.
Fig. 7 is the optimal filter envelope spectrum of embodiment residual signal and original vibration signal.
Specific embodiment
The present invention is described in more detail with embodiment with reference to the accompanying drawing.
As shown in Figure 1, a kind of weak impact component extracting method of epicyclic gearbox, comprising the following steps:
Step 1: passing through the high frequency sampling epicyclic gearbox original vibration signal x (t) of vibration acceleration sensor, sampling frequency
Rate is 20KHz, the gearbox fault type be planetary gear spot corrosion, the planetary gear box structure schematic diagram such as Fig. 2, structural parameters with
Fault characteristic frequency is as follows: input speed fn=3000rmp, the sun gear number of teeth: z1=12, the planetary gear number of teeth: z2=48, gear ring
The number of teeth: z3=108, sun gear fault characteristic frequency: f1=45Hz, planetary gear fault characteristic frequency: f2=11.25Hz, gear ring event
Hinder characteristic frequency: f3=5Hz；
Step 2: filtering frequency response letter for original vibration signal x (t) design DRS filtering frequency response function H (f), and by DRS
Number H (f) separates steady modulated signal, obtains residual signal r (t)；Its original vibration signal x (t), steady modulated signal and residue
Signal r (t) time domain waveform is shown in Fig. 3；
Step 3: by the optimal impact frequency band of SK method identification residual signal r (t), obtaining centre frequency fcWith filter band
Wide parameter Bw；
Spectrum kurtosis is solved to residual signal r (t), which determines that an optimal impact frequency band, Fig. 4 are residual signal r
(t) spectrum kurtosis determines one using 7187Hz as center frequency, using 208Hz as the frequency band of bandwidth；5 vibration signal x of comparison diagram
(t) spectrum kurtosis, using 1197Hz as center frequency, using 104Hz as the frequency band of bandwidth；By the steady modulation letter of DRS filtering removal
After number, the signal-to-noise ratio that impact signal corresponds to frequency band is improved, and the optimal frequency band of spectrum kurtosis method positioning is more accurate；
Step 4: according to centre frequency fcWith filter bandwidth parameters Bw, design filter and residual signal r (t) carried out
Filtering, obtains filtering signal a (t)；6 time domain waveform of analysis chart, the optimal filter of residual signal r (t) and original vibration signal x (t)
Wave time domain waveform is compared, and there are apparent planetary gear failure shock characteristic, impact intervals 0.089 second, with failure-frequency
11.25Hz is corresponding；
Step 5: Envelope Demodulation Analysis being carried out to filtering signal a (t), obtains envelope signal b (t), and to envelope signal b
(t) Fast Fourier Transform (FFT) is done, envelope signal frequency spectrum b (f) is obtained, spectrogram is shown in Fig. 7；Compare residual signal r (t) with it is original
The optimal filter envelope spectrogram of vibration signal x (t), more preferably, planetary gear failure is special for the envelope spectrum signal-to-noise ratio of residual signal r (t)
Levy frequency and its frequency multiplication clearly, although can also find corresponding failure feature in original vibration signal x (t) envelope spectrum,
Its interfering frequency is larger, influences the accurate positionin of the source of trouble.
It being found in conjunction with Fig. 6 and Fig. 7, tradition spectrum kurtosis diagnostic method is enriched modulation intelligence by epicyclic gearbox and is influenced,
Its envelope spectrum frequency component is complicated, cannot accurately identify the source of trouble.And the present invention can effectively identify the faint punching of epicyclic gearbox
Ingredient is hit, the envelope spectrum obtained by this method can clearly disclose fault characteristic frequency and its frequency multiplication, eliminate complicated and abundant
Influence of the modulation intelligence to fault identification, trouble location can be accurately positioned.
Present invention is generally applicable to epicyclic gearboxes to impact constituents extraction, and the above is only preferred implementation side of the invention
Formula, it is noted that for the ordinary person of the art, without departing from the principle of the present invention, can also make
Several improvement out, these improvement also should be regarded as protection scope of the present invention.
Claims (1)
1. a kind of weak impact component extracting method of epicyclic gearbox, which comprises the following steps:
Step 1: using the high frequency sampling epicyclic gearbox original vibration signal x (t) of acceleration transducer；
Step 2: for original vibration signal x (t) design DRS filtering frequency response function H (f), then to original vibration signal x (t)
Product calculation is done in frequency with DRS filtering frequency response function H (f), obtains residual signal r (t) and steady modulated signal x (t)-r
(t)；
Step 3: by the optimal impact frequency band of SK method identification residual signal r (t), obtaining centre frequency fcJoin with filter bandwidht
Number Bw；
Step 4: by centre frequency fc, filter bandwidth parameters BwFilter is designed, then residual signal r (t) is filtered,
Obtain filtering signal a (t)；
Step 5: Envelope Demodulation Analysis being carried out to filtering signal a (t), envelope signal b (t) is obtained, then to envelope signal b (t)
Fast Fourier Transform (FFT) is done, envelope signal frequency spectrum b (f) is obtained；Finally according to filtering signal a (t) and envelope signal frequency spectrum b (f)
Realize planetary gear fault identification and classification；
It is as follows to filter frequency response function H (f) expression formula by DRS in the step 2:
Wherein, ρ represents original vibration signal signal-to-noise ratio, and N represents filter length, and W (f) represents the frequency domain table of rectangular window function
It reaches.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109460736B (en) * | 2018-11-12 | 2022-04-05 | 华南师范大学 | Mixed signal separation method |
| CN109724802B (en) * | 2019-03-05 | 2020-07-10 | 西安交通大学 | Motor bearing weak fault diagnosis method based on spectrogram evaluation and optimization |
| CN113297697B (en) * | 2021-05-27 | 2022-07-01 | 清华大学 | Fixed-axis gearbox fault visualization method and system |
| CN113567127B (en) * | 2021-07-23 | 2022-06-07 | 西安交通大学 | Rolling bearing degradation index extraction method based on time-frequency feature separation |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101275702B1 (en) * | 2012-02-15 | 2013-06-17 | 목포대학교산학협력단 | Method and apparatus for fault diagnosis and fault detection of gearbox using vibration signal |
| CN104483127A (en) * | 2014-10-22 | 2015-04-01 | 徐州隆安光电科技有限公司 | Method for extracting weak fault characteristic information of planetary gear |
| CN104792523A (en) * | 2015-04-22 | 2015-07-22 | 电子科技大学 | Vibration spectrum feature analysis method based on planetary gear structure equivalent bearing model |
| CN106053061A (en) * | 2016-06-29 | 2016-10-26 | 潍坊学院 | Envelope analysis method based on non-linear mode decomposition and spectrum kurtosis |
| CN106525223A (en) * | 2016-11-01 | 2017-03-22 | 苏州微著设备诊断技术有限公司 | Offline detection method for abnormal noise of gear assembly |
-
2017
- 2017-06-19 CN CN201710464698.6A patent/CN107271181B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101275702B1 (en) * | 2012-02-15 | 2013-06-17 | 목포대학교산학협력단 | Method and apparatus for fault diagnosis and fault detection of gearbox using vibration signal |
| CN104483127A (en) * | 2014-10-22 | 2015-04-01 | 徐州隆安光电科技有限公司 | Method for extracting weak fault characteristic information of planetary gear |
| CN104792523A (en) * | 2015-04-22 | 2015-07-22 | 电子科技大学 | Vibration spectrum feature analysis method based on planetary gear structure equivalent bearing model |
| CN106053061A (en) * | 2016-06-29 | 2016-10-26 | 潍坊学院 | Envelope analysis method based on non-linear mode decomposition and spectrum kurtosis |
| CN106525223A (en) * | 2016-11-01 | 2017-03-22 | 苏州微著设备诊断技术有限公司 | Offline detection method for abnormal noise of gear assembly |
Non-Patent Citations (2)
| Title |
|---|
| Fast computation of the kurtogram for the detection of transient faults;J.Antoni;《Mechanical Systems and Signal Processing》;20060131(第21期);第108-124页 |
| Order tracking for discrete-random separation in variable speed conditions;P.Borghesani,et al;《Mechanical Systems and Signal Processing》;20120229(第30期);第1-22页 |
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Effective date of registration: 20231208 Address after: 201400 floor 1, building 2, No. 1876, CHENQiao Road, Fengxian District, Shanghai Patentee after: Shanghai Zhengtongan Technology Service Co.,Ltd. Address before: 215211 558 FENHU Road, Wujiang District, Suzhou, Jiangsu Patentee before: SUZHOU VEIZU EQUIPMENT DIAGNOSIS TECHNOLOGY CO.,LTD. |