CN107831012A - A kind of Method for Bearing Fault Diagnosis based on Walsh conversion with Teager energy operators - Google Patents
A kind of Method for Bearing Fault Diagnosis based on Walsh conversion with Teager energy operators Download PDFInfo
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- CN107831012A CN107831012A CN201710941685.3A CN201710941685A CN107831012A CN 107831012 A CN107831012 A CN 107831012A CN 201710941685 A CN201710941685 A CN 201710941685A CN 107831012 A CN107831012 A CN 107831012A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
- G01M13/04—Bearings
- G01M13/045—Acoustic or vibration analysis
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Abstract
The invention belongs to mechanical fault diagnosis field, and the invention discloses a kind of Fault Diagnosis of Roller Bearings based on Walsh conversion with Teager energy operators, its particular content are as follows：Acceleration transducer is fixed in measured axis bearing first, and acceleration transducer is connected to obtain bearing vibration signal with data collecting instrument, then carries out bearing failure diagnosis, de-noising is converted by carrying out Walsh to signal；And demodulate extraction fault signature with Teager energy operators；And go out bearing fault type with calculated value contrast fixation and recognition.The present invention is using vibration signal as research object, and Walsh is converted into de-noising and is combined with the demodulation of Teager energy operators, it is proposed that a kind of new Method for Bearing Fault Diagnosis.The present invention can effectively diagnose the fault type of rolling bearing, have the advantages of accuracy rate of diagnosis is high.
Description
Technical field
It is especially a kind of based on Walsh conversion and Teager energy the invention belongs to mechanical fault diagnosis technical field
Measure the Method for Bearing Fault Diagnosis of operator.
Background technology
Under modernization industry working condition, the structure of plant equipment is more fine, automatization level more and more higher, operation
Operating mode is increasingly sophisticated, and requirement of the people to plant equipment is also more and more tighter.Rolling bearing is the strength member in machine, and it is extensive
Applied to each important department such as chemical industry, metallurgy, electric power, space flight.
Rolling bearing is also one of element for being easiest to damage simultaneously, and according to statistics, bearing fault accounts for rotating machinery event
As many as 40 the percent of barrier.Should be at this stage that bearing is periodically tieed up according to projected life to the major measure of bearing fault
Repair, on the one hand the bearing of the intact work more than projected life is removed as processing is scrapped, causes to waste；On the other hand,
Not up to projected life and the bearing that breaks down does not occur as soon as catastrophe failure to maintenance time, cause whole machine to stop fortune
Turn.From this, hard time maintenance is very unscientific for rolling bearing, status monitoring is carried out to rolling bearing, can be subtracted
Less or prevent accident, cut down expenses.But during to state monitoring of rolling bearing, the vibration signal actually obtained is often
The characteristics of ambient noise is big and fault signature is faint be present, be unfavorable for carrying out fast and accurately fault diagnosis.Therefore, bearing is weakened
The ambient noise of vibration signal simultaneously strengthens fault signature, and tool is of great significance.
Wavelet transformation is new transform analysis method a kind of in recent years, and it inherits and developed short time discrete Fourier transform office
The thought in portion, while the shortcomings of window size does not change with frequency is overcome again, wavelet transformation can more preferable observation signal
Local characteristicses, can simultaneously observation signal time and frequency information, this is that Fourier transformation does not reach.But use small echo
Conversion suppresses noise often causes oscillation effect when handling Low SNR signal, while needs hand when carrying out wavelet transformation
The suitable small echo of dynamic selection, so considerably increases the required time in the processing to Practical Project problem.
The content of the invention
For overcome the deficiencies in the prior art, the invention provides one kind based on Walsh conversion and Teager energy operators
Fault Diagnosis of Roller Bearings, it converts de-noising and Teager energy by simple vibration measurement, using Walsh
The operator method that is combined of demodulation weakens ambient noise and strengthens fault signature, realizes that fast and effectively rolling bearing fault is examined
It is disconnected.
To achieve these goals, the technical solution adopted by the present invention is：One kind is based on Walsh conversion and Teager energy
Measure the Method for Bearing Fault Diagnosis of operator, it is characterised in that including herein below：Acceleration transducer is fixed on test bearing
On seat, acceleration transducer output end is connected with AVANT-MI-7016 multi-Channels Data Acquisitions, the number that Acquisition Instrument will collect
According to computer is sent to, Walsh conversion de-noising, Teager energy operators demodulation extraction failure spy are carried out to signal with computer
Sign, and go out bearing fault type with calculated value contrast fixation and recognition；Concrete operation step is as follows：
(1) primary signal is gathered, using acceleration transducer and 16 channel data Acquisition Instrument gathered datas, and number will be measured
It is passed to according to during fructufy in computer；
(2) obtained real time data is subjected to Walsh conversion denoising Processings；Walsh converts noise-eliminating method：
Primary signal is handled with Walsh conversion first, obtains a series of Walsh coefficients being made up of square wave, institute
It is with transformation for mula：
In formula (1), fnFor primary signal, AnFor Walsh coefficients, N is signal length, and ψ (n, t) is Rademacher side
Journey, it is defined as：
φ (n+1, x)=Sgn (sin2 π 2nX), n=0,1,2 ... 0≤x ＜ 1 (4)
In formula (4), Sgn is jump function, and it is defined as：
Then the Walsh coefficients of gained are subjected to soft-threshold processing, its threshold formula is：
K=MAD (An)/0.6745 (6)
In formula (6)：K is soft-threshold, and MAD is mean absolute deviation；
The Walsh coefficients that finally soft-threshold is treated carry out Walsh inverse transformations, obtain the signal after de-noising；
(3) signal after de-noising is subjected to Teager energy operator demodulation process, it is related special extracts rolling bearing fault
Sign, Teager energy operator demodulation methods are：
For discrete-time signal x (n), Teager energy operators ψ is defined as:
ψ [x (n)]=[x (n)]2-x(n-1)x(n+1) (7)
(4) Rolling Bearing Fault Character will be extracted and go out bearing fault type with calculated value contrast fixation and recognition, had
The computational methods of body such as following equation calculates：Outer ring failure-frequency formula：
In formula (8)：F is gyrofrequency, and z is rolling element number, and α is bearing pressure angle, and d is rolling
Body diameter, E are bearing pitch diameter.
Using such scheme, Walsh transformation (Walsh Transform, WT) proposed by the present invention can translate the signals into for
A series of Walsh coefficients being made up of square wave, by soft-threshold de-noising and signal reconstruction, effectively weakening the same of ambient noise
When can reduce amount of calculation, save and calculate the time.Hilbert demodulating algorithm is the common tool of Digital Signal Analysis and Processing, can be with
Realization measures to signal power, narrow band signal is detected, instantaneous power is carried out the function such as to estimate.But Hilbert
Demodulating algorithm can not avoid adding window effect, and this makes demodulation result non-momentary response characteristic occur, i.e., in the modulated signal demodulated
Generation is modulated, shows as the fluctuation that amplitude exponentially decays by both ends and the middle part for having mutation, so that demodulation misses
Difference increase.Teager energy operators (Teager Energy Operator, TEO) proposed by the present invention are a non-linear calculations
Son, there are temporal properties, the instantaneous energy of signal can be tracked, estimation produces the total mechanical energy needed for signal, its hypersensitivity
Feature is highly beneficial for the fault signature for strengthening bearing.In actual applications, the present invention can weaken ambient noise, enhancing failure
Feature simultaneously saves the calculating time, and this method has good effect in rolling bearing fault diagnosis.
Compared with prior art, the present invention has following features：
1st, solve the not high problem of rolling bearing fault diagnosis precision, by simple vibration measurement, use
Walsh converts de-noising to weaken adverse effect of the ambient noise to Weak fault signal, then with Teager energy operators demodulate come
Strengthen fault signature, realize effective rolling bearing fault diagnosis.
2nd, fusion utilizes the complementary characteristic of Walsh conversion de-noisings and the demodulation of Teager energy operators, the rolling bearing of acquisition
Fault signature extraction recognition capability is high.
3rd, the rolling bearing of different model is applicable to, can be widely used in various kinds of equipment bearing monitoring.
The invention will be further described below in conjunction with the accompanying drawings.
Brief description of the drawings
Fig. 1 is a kind of Fault Diagnosis of Roller Bearings based on Walsh conversion with Teager energy operators of the present invention
Flow chart；
The walsh that Fig. 2 is the present invention converts de-noising flow chart；
Fig. 3 is the deep groove ball bearing outer ring fault-signal result that the present invention tests；
Fig. 4 is the cylinder roller bearing outer ring fault-signal result that the present invention tests；
Fig. 5 is a kind of Diagnosing System for Detecting of Antifriction Bearings based on Walsh conversion with Teager energy operators of the present invention
Figure.
Embodiment
Protection scope of the present invention is not limited to following embodiments, and persons skilled in the art are according to the present invention
Disclosure, other a variety of embodiments can be used to implement the present invention, or every design using the present invention
Structure and thinking, simple change or change are done, both falls within protection scope of the present invention.
The specific embodiment of the present invention is the axis of rolling based on Walsh conversion with Teager energy operators as Figure 1-5
Method for diagnosing faults is held, acceleration transducer is fixed on test bearing seat, acceleration transducer output end and AVANT-MI-
7016 multi-Channels Data Acquisitions connect, and Acquisition Instrument sends the data collected to computer, signal is carried out with computer
Walsh conversion de-noising, Teager energy operators demodulation extraction fault signature, and go out bearing with calculated value contrast fixation and recognition
Fault type, realizes the accurate detection to rolling bearing running status, and the bearing failure diagnosis system can realize bearing fault intelligence
Can diagnosis.
The procedure Procedure of the embodiment of specific Diagnosing System for Detecting of Antifriction Bearings refer to Fig. 1, and Walsh conversion disappears
Flow of making an uproar refer to Fig. 2.
Comprise the following steps that：
(1) primary signal is gathered, using acceleration transducer and 16 channel data Acquisition Instrument gathered datas, and number will be measured
It is passed to according to during fructufy in computer；
(2) obtained real time data is subjected to Walsh conversion denoising Processings；Walsh converts noise-eliminating method：
Primary signal is handled with Walsh conversion first, obtains a series of Walsh systems being made up of square wave
Number, transformation for mula used are：
In formula (1), fnFor primary signal, AnFor Walsh coefficients, N is signal length, and ψ (n, t) is
Rademacher equations, it is defined as：
φ (n+1, x)=Sgn (sin2 π 2nX), n=0,1,2 ... 0≤x ＜ 1 (4)
In formula (4), Sgn is jump function, and it is defined as：
Then the Walsh coefficients of gained are subjected to soft-threshold processing, its threshold formula is：
K=MAD (An)/0.6745 (6)
In formula (6)：K is soft-threshold, and MAD is mean absolute deviation；
The Walsh coefficients that finally soft-threshold is treated carry out Walsh inverse transformations, obtain the signal after de-noising；De-noising is grasped
It is as shown in Figure 2 to make flow.
(3) signal after de-noising is subjected to Teager energy operator demodulation process, it is related special extracts rolling bearing fault
Sign, Teager energy operator demodulation methods are：
For discrete-time signal x (n), Teager energy operators ψ is defined as:
ψ [x (n)]=[x (n)]2-x(n-1)x(n+1) (7)
(4) Rolling Bearing Fault Character will be extracted and go out bearing fault type with calculated value contrast fixation and recognition, had
The computational methods of body such as following equation calculates：
Outer ring failure-frequency formula：
In formula (8)：F is gyrofrequency, and z is rolling element number, and α is bearing pressure angle, and d is rolling element diameter, and E is bearing
Pitch diameter.
It is the result obtained by the fault type with the method actual verification deep-groove ball rolling bearing of the present invention as shown in Figure 3
Figure, upper figure is time-domain signal, and middle figure is the design sketch of Hilbert envelope spectrum, and figure below is the design sketch of this patent methods described,
Contrast can find that this patent methods described has higher accuracy rate.The information of the deep-groove ball rolling bearing is as follows：Gyrofrequency
29.87Hz, rolling element number are 8, bearing pressure angle is 0 degree, rolling element is a diameter of 7.93 millimeters, bearing pitch diameter is
44.12 millimeters.The failure-frequency that this experiment axis bearing outer-ring can be calculated by formula (8) is 91.15Hz, can be fast from figure
Distinguish that the frequency of failure is close with theoretical value for 87.5Hz fastly, it is possible to determine that the fault type of this rolling bearing is bearing outer ring
Failure.
It is the result obtained by the fault type with the method actual verification cylinder roller bearing of the present invention as shown in Figure 4
Figure, upper figure is time-domain signal, and middle figure is the design sketch of Hilbert envelope spectrum, and figure below is the design sketch of this patent methods described,
Contrast can find that this patent methods described has higher accuracy rate.The information of the cylinder roller bearing is as follows：Gyrofrequency
29.85Hz, rolling element number are 13, bearing pressure angle is 0 degree, rolling element is a diameter of 6.5 millimeters, bearing pitch diameter is
38.5 millimeters.The failure-frequency that this experiment axis bearing outer-ring can be calculated by formula (8) is 161.27Hz, can be fast from figure
Distinguish that the frequency of failure is close with theoretical value for 161.7Hz fastly, it is possible to determine that the fault type of this rolling bearing is outside bearing
Enclose failure.It can further illustrate that the present invention has preferable treatment effect by above-described embodiment, be worthy of popularization.
Claims (1)
1. a kind of Method for Bearing Fault Diagnosis based on Walsh conversion with Teager energy operators, it is characterised in that including following
Content：Acceleration transducer is fixed on test bearing seat, acceleration transducer output end and AVANT-MI-7016 multichannels
Data collecting instrument connects, and Acquisition Instrument sends the data collected to computer, carries out Walsh conversion to signal with computer and disappears
Make an uproar, Teager energy operators demodulation extraction fault signature, and go out bearing fault type with calculated value contrast fixation and recognition；Tool
Body operating procedure is as follows：
(1) primary signal is gathered, using acceleration transducer and 16 channel data Acquisition Instrument gathered datas, and by data measured knot
It is passed to during fruit in computer；
(2) obtained real time data is subjected to Walsh conversion denoising Processings；Walsh converts noise-eliminating method：
Primary signal is handled with Walsh conversion first, obtains a series of Walsh systems being made up of square wave
Number, transformation for mula used are：
In formula (1), fnFor primary signal, AnFor Walsh coefficients, N is signal length, and ψ (n, t) is
Rademacher equations, it is defined as：
<mrow>
<mi>&psi;</mi>
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<mo>(</mo>
<mi>n</mi>
<mo>,</mo>
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<msup>
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<mo>&lsqb;</mo>
<mi>&phi;</mi>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>+</mo>
<mn>1</mn>
<mo>,</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
</mrow>
<msub>
<mi>n</mi>
<mi>i</mi>
</msub>
</msup>
<mo>,</mo>
<msub>
<mi>n</mi>
<mi>i</mi>
</msub>
<mo>&Element;</mo>
<mo>{</mo>
<mn>0</mn>
<mo>,</mo>
<mn>1</mn>
<mo>}</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<mi>n</mi>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mi>N</mi>
</munderover>
<msup>
<mn>2</mn>
<mi>i</mi>
</msup>
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<mi>n</mi>
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<mo>-</mo>
<mo>-</mo>
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<mn>3</mn>
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φ (n+1, x)=Sgn (sin2 π 2nX), n=0,1,2 ... 0≤x ＜ 1 (4)
In formula (4), Sgn is jump function, and it is defined as：
<mrow>
<mi>S</mi>
<mi>g</mi>
<mi>n</mi>
<mrow>
<mo>(</mo>
<mi>y</mi>
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<mo>=</mo>
<mfenced open = "{" close = "">
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<mtr>
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<mo>+</mo>
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<mo>,</mo>
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<mi>y</mi>
<mo>&GreaterEqual;</mo>
<mn>0</mn>
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<mo>-</mo>
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<mo>)</mo>
</mrow>
</mrow>
Then the Walsh coefficients of gained are subjected to soft-threshold processing, its threshold formula is：
K=MAD (An)/0.6745 (6)
In formula (6)：K is soft-threshold, and MAD is mean absolute deviation；
The Walsh coefficients that finally soft-threshold is treated carry out Walsh inverse transformations, obtain the signal after de-noising；
(3) signal after de-noising is subjected to Teager energy operator demodulation process, extracts rolling bearing fault correlated characteristic,
Teager energy operator demodulation methods are：
For discrete-time signal x (n), Teager energy operators ψ is defined as:
ψ [x (n)]=[x (n)]2-x(n-1)x(n+1) (7)
(4) Rolling Bearing Fault Character will be extracted and go out bearing fault type with calculated value contrast fixation and recognition, specifically
Computational methods such as following equation calculates：
Outer ring failure-frequency formula：
<mrow>
<msub>
<mi>f</mi>
<mi>o</mi>
</msub>
<mo>=</mo>
<mn>0.5</mn>
<mi>Z</mi>
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<mo>(</mo>
<mn>1</mn>
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<mfrac>
<mi>d</mi>
<mi>E</mi>
</mfrac>
<mi>c</mi>
<mi>o</mi>
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<mi>&alpha;</mi>
<mo>)</mo>
</mrow>
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<mo>(</mo>
<mn>8</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula (8)：F is gyrofrequency, and z is rolling element number, and α is bearing pressure angle, and d is rolling element diameter, and E is bearing pitch circle
Diameter.
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| CN201710941685.3A CN107831012B (en) | 2017-10-11 | 2017-10-11 | A kind of Method for Bearing Fault Diagnosis based on Walsh transformation and Teager energy operator |
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| CN108444698A (en) * | 2018-06-15 | 2018-08-24 | 福州大学 | Epicyclic gearbox Incipient Fault Diagnosis method based on TEO demodulation accidental resonances |
| CN109101936A (en) * | 2018-08-21 | 2018-12-28 | 北京工业大学 | It is a kind of based on adaptive MED Fault Diagnosis of Rolling Element Bearings method |
| CN109443719A (en) * | 2018-11-01 | 2019-03-08 | 河南理工大学 | A kind of drill vibration signal on-line virtual testing method and its system |
| CN111256993A (en) * | 2018-11-30 | 2020-06-09 | 中国电力科学研究院有限公司 | Method and system for diagnosing fault type of main bearing of wind turbine generator |
| CN112183344A (en) * | 2020-09-28 | 2021-01-05 | 广东石油化工学院 | Large unit friction fault analysis method and system based on waveform and dimensionless learning |
| CN117871096A (en) * | 2024-03-11 | 2024-04-12 | 昆明理工大学 | Rolling bearing fault simulation experiment device and fault online diagnosis method |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108444698A (en) * | 2018-06-15 | 2018-08-24 | 福州大学 | Epicyclic gearbox Incipient Fault Diagnosis method based on TEO demodulation accidental resonances |
| CN108444698B (en) * | 2018-06-15 | 2019-07-09 | 福州大学 | Epicyclic gearbox Incipient Fault Diagnosis method based on TEO demodulation accidental resonance |
| CN109101936A (en) * | 2018-08-21 | 2018-12-28 | 北京工业大学 | It is a kind of based on adaptive MED Fault Diagnosis of Rolling Element Bearings method |
| CN109443719A (en) * | 2018-11-01 | 2019-03-08 | 河南理工大学 | A kind of drill vibration signal on-line virtual testing method and its system |
| CN109443719B (en) * | 2018-11-01 | 2020-05-19 | 河南理工大学 | Drill bit vibration signal online virtual test method and system thereof |
| CN111256993A (en) * | 2018-11-30 | 2020-06-09 | 中国电力科学研究院有限公司 | Method and system for diagnosing fault type of main bearing of wind turbine generator |
| CN112183344A (en) * | 2020-09-28 | 2021-01-05 | 广东石油化工学院 | Large unit friction fault analysis method and system based on waveform and dimensionless learning |
| CN117871096A (en) * | 2024-03-11 | 2024-04-12 | 昆明理工大学 | Rolling bearing fault simulation experiment device and fault online diagnosis method |
| CN117871096B (en) * | 2024-03-11 | 2024-06-18 | 昆明理工大学 | Rolling bearing fault simulation experiment device and fault online diagnosis method |
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| CN107831012B (en) | 2019-09-03 |
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