CN106017925A - Rotary kiln holder wheel bearing fault diagnosis method based on wavelet packet decomposition - Google Patents
Rotary kiln holder wheel bearing fault diagnosis method based on wavelet packet decomposition Download PDFInfo
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- CN106017925A CN106017925A CN201610304684.3A CN201610304684A CN106017925A CN 106017925 A CN106017925 A CN 106017925A CN 201610304684 A CN201610304684 A CN 201610304684A CN 106017925 A CN106017925 A CN 106017925A
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- bearing
- wavelet packet
- storing things
- fault
- cellar
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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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- General Physics & Mathematics (AREA)
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
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Abstract
The invention discloses a rotary kiln holder wheel bearing fault diagnosis method based on wavelet packet decomposition. The method comprises the following steps: establishing a bearing diagnosis model, and according to an actual running condition, classifying bearing faults; obtaining vibration signals of bearings; and performing denoising processing on the vibration signals; selecting a packet primary function, performing four-layer wavelet packet decomposition and reconstruction on each obtained vibration signal, and extracting signals of each frequency scope; solving fourth-layer wavelet packet frequency band energy of the vibration signals after the decomposition and calculating its maximum value, and taking a frequency band as a feature component; performing Hilbert demodulation analysis on the feature fault, and obtaining an envelope spectrogram of modulation signals; and making a comparison with an envelope spectrogram corresponding to a bearing normal running state so as to determine bearing fault types and fault positions. The rotary kiln holder wheel bearing fault diagnosis method based on the wavelet packet decomposition, provided by the invention, overcomes the disadvantages of low manual detection efficiency and inaccurate detection positions, can rapidly and accurately diagnosis the fault positions, reduces equipment fault time and improves the equipment integrated utilization rate.
Description
Technical field
The present invention relates to Fault Diagnosis of Construction Machinery field, particularly relate to revolution based on WAVELET PACKET DECOMPOSITION cellar for storing things bearing of conveyor idler fault and examine
Disconnected method.
Background technology
Revolution cellar for storing things belongs to building equipment, and it is divided into cement revolution cellar for storing things, chemical metallurgy revolution cellar for storing things and Calx to return according to processing material difference
Turn cellar for storing things.Revolution cellar for storing things is mainly made up of parts such as actuating device, cylinder, support means and movable kiln hoods.
Owing to rotary kiln is for sealing structure, overall structure is numerous and diverse, it is impossible to use the accurate diagnostic methods such as founding mathematical models to find
Trouble point, has carried out certain difficulty to the diagnosis of fault.
The fault type of rotary kiln is more, and many fault type features are the fuzzyyest, it is difficult to differentiates and processes the most in time；Mostly
In the case of number, need manually to detect, get rid of mechanical breakdown one by one.
Owing to manual detection efficiency is the highest, the utilization rate at cellar for storing things is turned round in impact, and some fault can not effectively be prevented, impact
The comprehensive utilization ratio at revolution cellar for storing things, causes certain economic loss to the user at revolution cellar for storing things.
Summary of the invention
It is an object of the invention to for above-mentioned technical problem, it is provided that revolution based on WAVELET PACKET DECOMPOSITION cellar for storing things bearing of conveyor idler fault diagnosis
Method, it overcomes manual detection efficiency low and the inaccurate deficiency in detection position, it is possible to quick, Accurate Diagnosis abort situation, carries
High fault diagnosis efficiency, reduces the equipment fault time, improves the rate of comprehensive utilization of equipment.
Technical scheme
For solving above-mentioned technical problem, revolution based on the WAVELET PACKET DECOMPOSITION cellar for storing things bearing of conveyor idler method for diagnosing faults that the present invention provides,
The step of this diagnostic method is:
S1: set up revolution cellar for storing things bearing of conveyor idler diagnostic cast, according to the situation of actual motion to bearing failure modes；
S2: obtain vibration signal x (t) of revolution cellar for storing things bearing of conveyor idler；
S3: vibration signal is carried out denoising；
S4: choose parcel basic function, carries out 4 layers of WAVELET PACKET DECOMPOSITION and reconstruct to each vibration signal of gained, extracts each frequency
Signal with scope；
S5: seek the 4th layer of Wavelet Packet Frequency Band Energy of the vibration signal after decomposition, calculate its maximum, and using this frequency band as treating
The characteristic component analyzed；
S6: the characteristic component in step S5 carries out Hilbert Modulation analysis, obtains the envelope spectrogram of Hilbert modulated signal；
S7: the envelope spectrogram that contrast revolution cellar for storing things bearing of conveyor idler is corresponding, determines revolution cellar for storing things bearing of conveyor idler fault type and abort situation.
It is further preferred that revolution cellar for storing things bearing of conveyor idler fault totally two class described in step S1, it is bearing inner race fault, bearing
Outer ring fault.
It is further preferred that the denoising method of vibration signal described in step S3 is soft-threshold Wavelet noise-eliminating method.
It is further preferred that be { x after vibration signal x (t) WAVELET PACKET DECOMPOSITION described in step S4j,m(i)}；Wherein, j is
The number of times decomposed, m is the position number of wavelet packet, and it takes 1,2,3 ... 2k.
It is further preferred that the computing formula of frequency band energy described in step S5 is
The method have the benefit that
The present invention provide revolution based on WAVELET PACKET DECOMPOSITION cellar for storing things bearing of conveyor idler method for diagnosing faults, overcome manual detection efficiency low and
The inaccurate deficiency in detection position, it is possible to quick, Accurate Diagnosis abort situation, improves fault diagnosis efficiency, reduces equipment event
Downtime, improves the rate of comprehensive utilization of equipment.
Accompanying drawing explanation
Fig. 1 is the flow chart of the present invention；
Fig. 2 be revolution cellar for storing things bearing of conveyor idler properly functioning time vibration signal time domain beamformer；
Fig. 3 be revolution cellar for storing things bearing of conveyor idler properly functioning time vibration signal WAVELET PACKET DECOMPOSITION and the oscillogram of reconstruct；
Fig. 4 be revolution cellar for storing things bearing of conveyor idler properly functioning time four layers of WAVELET PACKET DECOMPOSITION of vibration signal after the Energy distribution of each frequency band；
Fig. 5 be revolution cellar for storing things bearing of conveyor idler properly functioning time vibration signal Hilbert modulation envelope spectrogram；
Vibration signal time domain beamformer when Fig. 6 is revolution cellar for storing things bearing of conveyor idler inner ring fault；
Vibration signal WAVELET PACKET DECOMPOSITION and the oscillogram of reconstruct when Fig. 7 is revolution cellar for storing things bearing of conveyor idler inner ring fault；
The Energy distribution of each frequency band after four layers of WAVELET PACKET DECOMPOSITION of vibration signal when Fig. 8 is revolution cellar for storing things bearing of conveyor idler inner ring fault；
The envelope spectrogram of vibration signal Hilbert modulation when Fig. 9 is revolution cellar for storing things bearing of conveyor idler inner ring fault；
Vibration signal time domain beamformer when Figure 10 is revolution cellar for storing things bearing of conveyor idler outer ring fault；
Vibration signal WAVELET PACKET DECOMPOSITION and the oscillogram of reconstruct when Figure 11 is revolution cellar for storing things bearing of conveyor idler outer ring fault；
The Energy distribution of each frequency band after four layers of WAVELET PACKET DECOMPOSITION of vibration signal when Figure 12 is revolution cellar for storing things bearing of conveyor idler outer ring fault；
The envelope spectrogram of vibration signal Hilbert modulation when Figure 13 is revolution cellar for storing things bearing of conveyor idler outer ring fault.
Detailed description of the invention
Below in conjunction with specific embodiments and the drawings, bearing of conveyor idler method for diagnosing faults is stored in the revolution based on WAVELET PACKET DECOMPOSITION of the present invention
It is described in detail.
The embodiment recorded at this is the specific detailed description of the invention of the present invention, for the design of the present invention is described, is all to explain
Property and exemplary, should not be construed as the restriction to embodiment of the present invention and the scope of the invention.In addition to the embodiment recorded at this,
Those skilled in the art can also use other skill obvious based on the application claims and description disclosure of that
Art scheme, these technical schemes include using the skill making any obvious substitutions and modifications to the embodiment recorded at this
Art scheme.
Fig. 1 is that bearing of conveyor idler Troubleshooting Flowchart is stored in revolution based on WAVELET PACKET DECOMPOSITION, and it specifically includes following steps:
S1: set up revolution cellar for storing things bearing of conveyor idler diagnostic cast, according to the situation of actual motion to bearing failure modes；
Concrete, described revolution cellar for storing things bearing of conveyor idler fault totally two class, it is bearing inner race fault, bearing outer ring fault；Set up
During the bearing of conveyor idler diagnostic cast of revolution cellar for storing things, in addition it is also necessary to set up the operating mode that revolution cellar for storing things bearing of conveyor idler is properly functioning.
S2: obtain vibration signal x (t) of revolution cellar for storing things bearing of conveyor idler；
Concrete, obtain that revolution cellar for storing things bearing of conveyor idler is properly functioning, bearing inner race fault and vibration signal x during bearing outer ring fault
(t)；Fig. 2 be revolution cellar for storing things bearing of conveyor idler properly functioning time vibration signal time domain beamformer, by Fig. 2 cannot judge revolution cellar for storing things support roller
Bearing whether fault and fault type.
S3: vibration signal is carried out denoising；
Concrete, the denoising method of described vibration signal is soft-threshold Wavelet noise-eliminating method.Its soft threshold function is:
W represents wavelet coefficient, and T is given threshold value, and sign (w) is sign function.
S4: choose parcel basic function, carries out 4 layers of WAVELET PACKET DECOMPOSITION and reconstruct to each vibration signal of gained, extracts each frequency
Signal with scope；
Concrete, it is { x after described vibration signal x (t) WAVELET PACKET DECOMPOSITIONj,m(i)}；Wherein, j is the number of times decomposed, and m is
The position number of wavelet packet, it takes 1, and 2,3 ... 2k.
Fig. 3 be revolution cellar for storing things bearing of conveyor idler properly functioning time vibration signal WAVELET PACKET DECOMPOSITION and the oscillogram of reconstruct；Fig. 4 is revolution cellar for storing things
The Energy distribution of each frequency band after four layers of WAVELET PACKET DECOMPOSITION of vibration signal when bearing of conveyor idler is properly functioning, as shown in Figure 4, four layers of small echo
The energy size of each frequency band after decomposition.
S5: seek the 4th layer of Wavelet Packet Frequency Band Energy of the vibration signal after decomposition, calculate its maximum, and using this frequency band as treating
The characteristic component analyzed；
Concrete, the computing formula of described frequency band energy isIts maximum is to utilize in MATLAB
Max (E (m)) solves.
S6: the characteristic component in step S5 carries out Hilbert Modulation analysis, obtains the envelope spectrogram of Hilbert modulated signal；
Fig. 5 be revolution cellar for storing things bearing of conveyor idler properly functioning time vibration signal Hilbert modulation envelope spectrogram, it is to the maximum frequency of energy
Band carries out Envelope Analysis gained after carrying out Hilbert conversion, as shown in Figure 5: when revolution cellar for storing things bearing of conveyor idler is properly functioning, each frequency
Energy distribution difference in band strengthens, and knowable to envelope spectrogram, 0 amplitude maximum occurs in the position that frequency is relatively low, by this frequency
Rate and amplitude are as the mark differentiating normal condition.
S7: the envelope spectrogram that contrast revolution cellar for storing things bearing of conveyor idler normal operating condition is corresponding, determines revolution cellar for storing things bearing of conveyor idler fault type
And abort situation.
The envelope spectrogram of vibration signal Hilbert modulation when Fig. 9 is revolution cellar for storing things bearing of conveyor idler inner ring fault, in the bearing of conveyor idler of revolution cellar for storing things
During circle fault, Energy distribution difference in each frequency band strengthens, and with under bearing normal condition or bearing outer ring malfunction point
Cloth obvious difference, and knowable to envelope spectrogram, amplitude is relatively low in frequency and 1000Hz place is obvious, and this deposits with other two states
At notable difference, using this frequency and amplitude as the mark of differentiation bearing inner race fault.
Fig. 9 gained envelope spectrogram as a result, it is desirable to from step S1 to step S7.Fig. 6 is revolution cellar for storing things bearing of conveyor idler inner ring fault
Time vibration signal time domain beamformer, by Fig. 6, it is impossible to judge location of fault；Vibration signal time domain beamformer in Fig. 6 is entered
Row WAVELET PACKET DECOMPOSITION, obtains vibration signal WAVELET PACKET DECOMPOSITION and reconstruct when Fig. 7, Fig. 7 are revolution cellar for storing things bearing of conveyor idler inner ring faults
Oscillogram；The Energy distribution of each frequency band after four layers of WAVELET PACKET DECOMPOSITION of vibration signal when Fig. 8 is revolution cellar for storing things bearing of conveyor idler inner ring fault,
Can be seen that the energy size of four layers of each frequency band of WAVELET PACKET DECOMPOSITION, at this point it is possible to corresponding with revolution cellar for storing things bearing of conveyor idler normal condition
Energy maximum band contrasts；The envelope spectrogram of vibration signal Hilbert modulation when Fig. 9 is revolution cellar for storing things bearing of conveyor idler inner ring fault, its
The envelope diagram existence corresponding with revolution cellar for storing things bearing of conveyor idler normal condition is clearly distinguished from, in may determine that bearing from its power spectral energies
Circle fault.
The envelope spectrogram of vibration signal Hilbert modulation when Figure 13 is revolution cellar for storing things bearing of conveyor idler outer ring fault, revolution cellar for storing things bearing of conveyor idler
During the fault of outer ring, the Energy distribution difference in each frequency band strengthens, and obvious with the distributional difference under normal condition；From envelope spectrum
Figure understands, and frequency 50Hz that amplitude maximum occurs in and 800Hz place, under compared with normal state, change is obvious, with this frequency and width
It is worth as the mark differentiating bearing outer ring fault.
The result of Figure 13 gained envelope spectrogram, needs also exist for from step S1 to step S7.Figure 10 is outside the bearing of conveyor idler of revolution cellar for storing things
Vibration signal time domain beamformer during circle fault, thus schemes, it is impossible to judge location of fault；It is carried out WAVELET PACKET DECOMPOSITION, obtains
Vibration signal WAVELET PACKET DECOMPOSITION and the oscillogram of reconstruct when Figure 11, Figure 11 are revolution cellar for storing things bearing of conveyor idler outer ring faults；Figure 12 is back
The Energy distribution of each frequency band after four layers of WAVELET PACKET DECOMPOSITION of vibration signal when turning cellar for storing things bearing of conveyor idler outer ring fault, it can be seen that four layers of small echo
Bag decomposes the energy size of each frequency band, at this point it is possible to the energy maximum band contrast corresponding with revolution cellar for storing things bearing of conveyor idler normal condition；
The envelope spectrogram of vibration signal Hilbert modulation when Figure 13 is revolution cellar for storing things bearing of conveyor idler outer ring fault, itself and revolution cellar for storing things bearing of conveyor idler
The envelope diagram existence that normal condition is corresponding is clearly distinguished from, and may determine that it is bearing outer ring fault from its power spectral energies.
By contrast with the difference of the envelope spectrogram of upper rotary cellar for storing things bearing of conveyor idler vibration signal Hilbert modulation, can accurately judge bearing
Whether fault and fault type, diagnosis is quick, accurately, greatly reduces the device Diagnostic time, improves diagnosis efficiency, reduces
The equipment fault time, improve the rate of comprehensive utilization of equipment.
The present invention provide revolution based on WAVELET PACKET DECOMPOSITION cellar for storing things bearing of conveyor idler method for diagnosing faults, overcome manual detection efficiency low and
The inaccurate deficiency in detection position, it is possible to quick, Accurate Diagnosis abort situation, reduces the equipment fault time, improves equipment complex
Utilization rate.
The present invention is not limited to above-mentioned embodiment, and anyone can draw other various forms of products under the enlightenment of the present invention,
Though but in its shape or structure, make any change, every have same as the present application or akin technical scheme, all falls within
Within protection scope of the present invention.
Claims (5)
1. revolution based on WAVELET PACKET DECOMPOSITION cellar for storing things bearing of conveyor idler method for diagnosing faults, it is characterised in that this diagnostic method
Step be:
S1: set up revolution cellar for storing things bearing of conveyor idler diagnostic cast, according to the situation of actual motion to bearing failure modes；
S2: obtain vibration signal x (t) of revolution cellar for storing things bearing of conveyor idler；
S3: vibration signal is carried out denoising；
S4: choose parcel basic function, carries out 4 layers of WAVELET PACKET DECOMPOSITION and reconstruct to each vibration signal of gained, extracts
The signal of each frequency band range；
S5: seek the 4th layer of Wavelet Packet Frequency Band Energy of the vibration signal after decomposition, calculate its maximum, and by this frequency band
As characteristic component to be analyzed；
S6: the characteristic component in step S5 carries out Hilbert Modulation analysis, obtains Hilbert modulated signal
Envelope spectrogram；
S7: the envelope spectrogram that contrast revolution cellar for storing things bearing of conveyor idler is corresponding, determines revolution cellar for storing things bearing of conveyor idler fault type and fault
Position.
Revolution based on WAVELET PACKET DECOMPOSITION the most according to claim 1 cellar for storing things bearing of conveyor idler method for diagnosing faults, its
Be characterised by, revolution described in step S1 cellar for storing things bearing of conveyor idler fault totally two class, its be bearing inner race fault,
Bearing outer ring fault.
Revolution based on WAVELET PACKET DECOMPOSITION the most according to claim 1 cellar for storing things bearing of conveyor idler method for diagnosing faults, its
Being characterised by, the denoising method of vibration signal described in step S3 is soft-threshold Wavelet noise-eliminating method.
Revolution based on WAVELET PACKET DECOMPOSITION the most according to claim 1 cellar for storing things bearing of conveyor idler method for diagnosing faults, its
It is characterised by, is { x after vibration signal x (t) WAVELET PACKET DECOMPOSITION described in step S4j,m(i)}；Wherein,
J is the number of times decomposed, and m is the position number of wavelet packet, and it takes 1,2,3 ... 2k。
Revolution based on WAVELET PACKET DECOMPOSITION the most according to claim 1 cellar for storing things bearing of conveyor idler method for diagnosing faults, its
Being characterised by, the computing formula of frequency band energy described in step S5 is
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| CN201610304684.3A CN106017925B (en) | 2016-05-09 | 2016-05-09 | Bearing of conveyor idler method for diagnosing faults is stored in revolution based on WAVELET PACKET DECOMPOSITION |
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| CN201610304684.3A CN106017925B (en) | 2016-05-09 | 2016-05-09 | Bearing of conveyor idler method for diagnosing faults is stored in revolution based on WAVELET PACKET DECOMPOSITION |
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Cited By (7)
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| CN107153748A (en) * | 2017-06-07 | 2017-09-12 | 北京信息科技大学 | Based on weighting core pivot element analysis（WKPCA）Rotary kiln method for diagnosing faults |
| CN107202952A (en) * | 2017-07-06 | 2017-09-26 | 北京信息科技大学 | Rotary kiln method for diagnosing faults, fault diagnosis GUI and system based on wavelet neural network |
| CN108458875A (en) * | 2018-04-10 | 2018-08-28 | 上海应用技术大学 | A kind of method for diagnosing faults of supporting roller of rotary kiln bearing |
| CN108776031A (en) * | 2018-03-21 | 2018-11-09 | 南京航空航天大学 | A kind of rotary machinery fault diagnosis method based on improved synchronous extruding transformation |
| CN110057583A (en) * | 2019-03-01 | 2019-07-26 | 西人马(西安)测控科技有限公司 | A kind of bearing fault recognition methods, device and computer equipment |
| CN110530623A (en) * | 2019-09-12 | 2019-12-03 | 天津华春智慧能源科技发展有限公司 | Fault diagnosis method applied to heat exchange unit |
| CN113739567A (en) * | 2021-07-28 | 2021-12-03 | 西安交通大学 | Method and system for evaluating state of rotary kiln body |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107153748A (en) * | 2017-06-07 | 2017-09-12 | 北京信息科技大学 | Based on weighting core pivot element analysis（WKPCA）Rotary kiln method for diagnosing faults |
| CN107202952A (en) * | 2017-07-06 | 2017-09-26 | 北京信息科技大学 | Rotary kiln method for diagnosing faults, fault diagnosis GUI and system based on wavelet neural network |
| CN108776031A (en) * | 2018-03-21 | 2018-11-09 | 南京航空航天大学 | A kind of rotary machinery fault diagnosis method based on improved synchronous extruding transformation |
| CN108458875A (en) * | 2018-04-10 | 2018-08-28 | 上海应用技术大学 | A kind of method for diagnosing faults of supporting roller of rotary kiln bearing |
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| CN110530623A (en) * | 2019-09-12 | 2019-12-03 | 天津华春智慧能源科技发展有限公司 | Fault diagnosis method applied to heat exchange unit |
| CN113739567A (en) * | 2021-07-28 | 2021-12-03 | 西安交通大学 | Method and system for evaluating state of rotary kiln body |
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