CN102183366A - Device and method for vibration measurement and failure analysis of rolling bearing - Google Patents
Device and method for vibration measurement and failure analysis of rolling bearing Download PDFInfo
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Abstract
The invention relates to a device and method for vibration measurement and failure analysis of a rolling bearing. The device comprises a detected bearing mounting device, a speed sensor, a signal conditioning circuit, a data collection device and a computer, wherein a detected bearing is mounted on a mandrel of the detected bearing mounting device; a vibration rod of the speed sensor is arranged on a middle plane of an outer cylindrical surface of an outer ring of the detected bearing with prescribed pressure, the measurement direction is along the radial direction of the bearing and vertical to the axis of the bearing, and the signal conditioning circuit and the data collection device are connected to the computer; the speed sensor measures radial vibration speed signals of the outer ring of the bearing, the picked bearing radial vibration speed signals are converted into corresponding electric signals which are processed by the signal conditioning circuit and then transferred to the data collection device which carries out A/D conversion of the conditioned signals to convert the conditioned signals into digital signals capable of being processed by the computer, and finally the computer carries out analysis and processing of the digital signal. The device and the method are applicable to production test and user acceptance of finished bearings by laboratories and bearing manufacture factories.
Description
Technical field
The present invention relates to bearing detection and fail analysis device and method, particularly a kind of bearing vibration measurement and fail analysis device and method.
Background technology
Rolling bearing is Precision Machinery Elements, is widely used in national economy numerous areas and national defense construction such as Aero-Space, high ferro, lathe, vehicle, metallurgy.Bearing is the key foundation part, is the element of indispensable supporting of rotating machinery and transferring power.The bearing quality quality directly influences the precision and the performance of its matched host machine and equipment.Therefore, bearing quality is controlled, can be reduced economic loss and prevent the accident generation, increase the competitiveness of domestic bearing enterprise.
Vibration and noiseproof feature and life-span and reliability are the important quality and the performance index of rolling bearing.The life-span of rolling bearing and reliability theory are based upon on the material rolling contact fatigue theoretical foundation, along with material and improvement of Manufacturing Technology, a lot of application scenarios, as precision instrument, car and household electrical appliance, requirement to bear vibration and noisiness is strict day by day, has risen to the first important quality index.
At present, the widely used bearing velocity profile of domestic bearing industry vibration measuring set, as BVT series bear vibration (speed) measuring instrument of Hangzhou Bearing Experiment and Research Centre's development, the S07907V series velocity profile bearing vibration measuring instrument of Dalian Ke Hui bearing Instr Ltd. development all is to realize the bearing vibration rate signal is handled with mimic channel, only finish the measurement of single parameter (bear vibration speed effective value), and there is not corresponding analytic function, can only be quantitatively and can not qualitatively analyze bearing quality level.In addition, the very flexible of its product, the function expansion is difficult, upgrade cost is high.And state outer bearing company as SKF development MVH 90C/200C bear vibration tester, adopts digital quantity to come processing signals, and the realization multiparameter is differentiated bear vibration, and has the Digital Signal Analysis function.Domestic bearing vibration measuring instrument device still exists bigger gap with external similar advanced enterprise, and the achieved reliability of product remains further to be improved.Bearing vibration measurement and the fail analysis device and the method for invention, Digital Signal Processing is applied to bearing vibration to be measured and fault diagnosis, be microminiature deep groove ball bearing vibration and noise reducing, improving bearing accuracy, performance, life-span and reliability provides strong means.
Summary of the invention
The objective of the invention is to provides a kind of bearing vibration measurement and fail analysis device and method for satisfying the needs of bearing manufacturing plant and laboratory inspection and analysis bear vibration.Utilization virtual instrument technique and Digital Signal Processing carry out digital quantity to the bearing vibration signal after nursing one's health to be handled, accurately measure bearing vibration velocity effective value, vibration velocity peak value and vibration velocity crest factor, and can carry out time-domain analysis, fft analysis, envelope spectrum analysis, discrete wavelet analysis, wavelet packet analysis and HHT to the bearing vibration rate signal and analyze, effectively extract the bearing fault characteristic frequency, fault judgement is accurate, and achieved reliability is good.
The technical solution adopted for the present invention to solve the technical problems is:
The invention provides a kind of bearing vibration measurement and fail analysis device and comprise measured bearing erecting device, speed pickup, signal conditioning circuit, data acquisition equipment and computing machine, measured bearing is installed on the axle of described measured bearing erecting device, the vibration-sensing rod of described speed pickup places on the facial planes of measured bearing outer ring external cylindrical surface with the pressure of regulation, direction of measurement along bearing radially and perpendicular to the axis of bearing, signal conditioning circuit and data acquisition equipment are connected to computing machine; The radial vibration rate signal of speed pickup measurement axis bearing outer-ring, convert the bearing radial vibration rate signal that picks up to corresponding electric signal, this electric signal is after signal conditioning circuit is handled, be transported to data acquisition equipment, by data acquisition equipment the signal after nursing one's health is carried out the A/D conversion, convert the treatable digital signal of computing machine to, by computing machine digital signal is analyzed and handled at last.
The invention provides a kind of bearing vibration and measure and failure analysis methods, the bearing vibration rate signal after the conditioning is carried out digital quantity handle and analyze.Calculation bearing vibration velocity effective value, vibration velocity peak value and crest factor, and can carry out time-domain analysis, fft analysis, envelope spectrum analysis, wavelet analysis, wavelet packet analysis and HHT to the bearing vibration rate signal and analyze, bear vibration is carried out quantitatively and qualitatively analyze, accurately the failure cause of failure judgement bearing.
It is the root-mean-square value computing formula of utilizing discrete signal that bear vibration speed effective value calculates
, wherein
Be discrete bear vibration rate signal, N is a sampling number,
Be the bear vibration speed effective value that calculates.The bear vibration velocity peak values is utilized the peak counting method, from discrete signal
Find out n peak value in (sampling number is N)
, discrete signal then
The peak value index be:
, wherein
Be the bear vibration velocity peak values of calculating.Bear vibration speed crest factor utilizes formula
, wherein X is the bear vibration speed crest factor of calculating.
Hilbert amplitude demodulation method is adopted in the envelope spectrum analysis.The analytic signal real part that the Hilbert conversion obtains is a real signal itself, and imaginary part is its Hilbert conversion, and the amplitude of analytic signal is the envelope of signal, carries out spectrum analysis again, obtains envelope spectrum at last.Signal
The result of Hilbert conversion is
, the structure analytic signal
, wherein the amplitude function is
, to the amplitude function
Carry out spectrum analysis, obtain envelope spectrum.
The Mallat algorithm is adopted in the discrete wavelet analysis,
,
Wherein, j and k are integers.(DWT) transforms to time-scale domain with the bearing vibration rate signal by wavelet transform, and the wavelet coefficient of high band scale domain is carried out envelope refinement analysis of spectrum.When bearing breaks down when inner ring or rolling body fault (especially), detail signal on the restructuring graph of wavelet analysis shows that one group of impact took place with the fault characteristic frequency time corresponding cycle, the fault characteristic frequency that clearly shows bearing in the envelope spectrogram behind wavelet transform, accurately extract the bearing fault characteristic frequency, judge the position that bearing fault occurs.
Wavelet packet analysis also adopts the Mallat algorithm, it decomposes simultaneously to low frequency signal and the high-frequency signal after decomposing last time again, with the signal decomposition of different frequency range in corresponding frequency range, then can be as required with the signal reconstruction in the required frequency range, the signal of reconstruct is the same with original signal length, has played a kind of effect of filtering.The recursion formula of WAVELET PACKET DECOMPOSITION is:
,
Wherein,
Be that signal is at yardstick
, frequency band
Go up coefficient of dissociation for wavelet packet functions,
The time-domain position of representing this point; Function
It is a low-pass filter; Function
It is a Hi-pass filter.The wavelet package reconstruction formula is:
The coefficient of each group can be by two groups of coefficient reconstruction than the big one-level of its yardstick, as
Coefficient can be by than the big one-level of its yardstick
With
Two groups of coefficient reconstruction.In bearing fault is analyzed, if the bearing fault characteristic frequency that calculates is distributed in a certain frequency range, then can in the wavelet decomposition tree, find node corresponding, signal to this frequency range is reconstructed and analyzes its power spectrum again, diagnose bearing fault (the fault bearing to be arranged then, the peak value of frequency spectrum is corresponding with outer ring fault characteristic frequency or inner ring fault characteristic frequency or rolling body fault characteristic frequency respectively after its reconstruct, and matches with the physical fault type of bearing.The reconstruction signal frequency spectrum of non-fault bearing does not then have tangible peak value at the fault characteristic frequency place).
HHT analytical applications Empirical mode decomposition (EMD) decomposites several IMF components from bearing vibration signal, then each IMF component is carried out the Hilbert conversion, and then draws Hilbert time-frequency spectrum and Hilbert marginal spectrum.Diagnose the fault of rolling bearing and discern fault mode according to Hilbert analysis of spectrum result.At first determine signal
All Local Extremum (comprising maximum value and minimum point) couple together all local maximum points and local minizing point respectively then with cubic spline curve, obtain
Upper and lower envelope.The mean value of getting upper and lower envelope is designated as
Utilize
, obtain
Judge
Whether less than 0.1, if do not satisfy, then
As pending signal, repeat aforesaid operations, obtain envelope average up and down
, obtain
, judge again
Whether satisfy SD less than 0.1.Circulation k time, up to
Satisfy SD less than 0.1.Wherein
, note
,
It is signal
The 1st component that satisfies the IMF condition.The first rank IMF that from signal, decomposites
Afterwards, from
In deduct
, obtain the surplus value sequence
,
, will
Repeat above process as new " original " signal, can obtain the second rank IMF successively, the 3rd rank IMF ..., N rank IMF is designated as
, the remainder of remaining at last original signal
This processing procedure promptly stops in following any one criterion of chance:
When last intrinsic modal components
Or residual components
Enough little;
Work as residual components
Become monotonic quantity, therefrom can not rescreen and select till the IMF.With signal
Be decomposed into several intrinsic modal components IMF and a residual components and,
Respectively each IMF component is done the Hilbert conversion then, obtain
Construct analytic signal again
, wherein the amplitude function is
At last, to the amplitude function
Carry out spectrum analysis, obtain the Hilbert spectrum.
The present invention has following conspicuous outstanding substantive distinguishing features and significantly technical progress compared with prior art:
(1) the present invention, its design be in strict accordance with the regulation of standard GB/T 24610-2009 bearing vibration measuring method, is applicable to laboratory, bearing manufacturing plant production testing and the user acceptance to the finished product bearing.
(2) utilize virtual instrument technique and Digital Signal Processing, the bearing vibration rate signal after the conditioning is carried out digital quantity handle, antijamming capability data strong, that measure are more accurate.
(3) signal analysis function is abundant, can realize that discrete wavelet analysis, wavelet packet analysis and HHT (Hilbert-Huang conversion) analyze.
(4) realize lot of data storage and management, can onlinely check data and offline playback dynamic data, be convenient to the bearing quality management.
Description of drawings
Fig. 1 is that bearing vibration is measured and the fail analysis device structured flowchart;
Fig. 2 is a measured bearing erecting device structural representation;
Fig. 3 is the signal conditioning circuit structured flowchart;
Fig. 4 is the signal conditioning circuit schematic diagram;
Fig. 5 is that bearing vibration is measured and the failure analysis methods flow chart;
Embodiment
Details are as follows in conjunction with the accompanying drawings for the preferred embodiments of the present invention:
Embodiment one: this bearing vibration is measured and fail analysis device, referring to Fig. 1, comprise measured bearing erecting device (5), speed pickup (1), signal conditioning circuit (11), data acquisition equipment (10) and computing machine (9), it is characterized in that: at first bearing (2) is installed on the measured bearing erecting device (5).The vibration-sensing rod of speed pickup (1) places on the facial planes of bearing outer ring external cylindrical surface with the pressure of regulation, direction of measurement along bearing radially and perpendicular to the axis of bearing.By the radial vibration rate signal of speed pickup (1) measurement axis bearing outer-ring, convert the bearing radial vibration rate signal that picks up to corresponding electric signal.This electric signal is transported to data acquisition equipment (10) after signal conditioning circuit (11) is handled.By data acquisition equipment (10) signal after nursing one's health is carried out the A/D conversion, convert the treatable digital signal of computing machine (9) to.By computing machine (9) digital signal is analyzed and handled at last.
Embodiment two: present embodiment and embodiment one are basic identical, the feature part is as follows: described measured bearing erecting device, referring to Fig. 2, comprise main shaft (4), motor (7), frequency converter (8), axle (3), vertical slipper (13), vertical set lever (14), handwheel (12), horizontal gliding mass (16), horizontal set lever (17), knob (15), bearing (2) and axle correspondingly (3) are installed in main shaft (4) taper hole.Regulate main shaft (4) rotating speed by frequency converter (8), rotate with constant rotational speed thereby make main shaft (4) drive bearing (2).Unclamp vertical set lever (14) and horizontal set lever (17).Adjusting knob (15) moves forward and backward horizontal gliding mass (16), finishes the horizontal position adjustment of speed pickup (1).Rise or decline vertical slipper (13) with handwheel (12), the upright position of the sensor of regulating the speed (1) is adjusted, and the vibration-sensing rod of speed pickup (1) is placed on the facial planes of bearing (2) outer ring external cylindrical surface with the pressure of stipulating.After the sensor horizontal and vertical position is adjusted, lock vertical set lever (14) and horizontal set lever (17).
Described signal conditioning circuit, referring to Fig. 3 and Fig. 4, at first the bear vibration rate signal that picks up of speed pickup amplifies through isolated amplifier, amplify through operational amplifier IC1 then, operational amplifier IC1 output terminal 6 is by the signal input part INA of the integrated state variable filter MAX274 of resistance R 4 connections, and signal is connected the signal input part VIN of programmable amplifier PGA103 behind the filtering noise by the signal output part BPOD of integrated state variable filter MAX274.At last, the signal after the signal conditioning circuit conditioning is by the output terminal VOUT output of programmable amplifier PGA103.
Embodiment three: this bearing vibration is measured and failure analysis methods, adopt said apparatus to test and analyze, referring to Fig. 5, data collecting card is started working, signal after the signal conditioning circuit conditioning is carried out the A/D conversion, and data are stored in the user buffering district with magnitude of voltage; The bear vibration rate signal that collects is carried out digital filtering handle, obtain filtered low-frequency vibration rate signal, intermediate frequency vibration velocity signal and dither rate signal; Filtered bear vibration rate signal (50-10000hz) is calculated vibration velocity effective value, vibration velocity peak value and the crest factor of low frequency, intermediate frequency and high frequency respectively; Filtered bear vibration rate signal (50-10000hz) is carried out time-domain analysis, fft analysis, envelope spectrum analysis, discrete wavelet analysis, wavelet packet analysis and HHT to be analyzed.
Described bear vibration speed effective value
Calculating is the root-mean-square value computing formula of utilizing discrete signal
, wherein
Be discrete bear vibration rate signal, N is a sampling number,
Be the bear vibration speed effective value that calculates.
Described bear vibration velocity peak values
Utilize the peak counting method, from discrete signal
In find out n peak value
, discrete signal then
The peak value index be:
, wherein
Be the bear vibration velocity peak values of calculating, n is a peak value
Number.
Described bear vibration speed crest factor X utilizes formula
, wherein X is the bear vibration speed crest factor of calculating.
Hilbert amplitude demodulation method is adopted in described envelope spectrum analysis, the analytic signal real part that the Hilbert conversion obtains is a real signal itself, and imaginary part is its Hilbert conversion, and the amplitude of analytic signal is the envelope of signal, carry out spectrum analysis again, obtain envelope spectrum at last.
The Mallat algorithm is adopted in described discrete wavelet analysis,
,
Wherein, j and k are integers.(DWT) transforms to time-scale domain with the bearing vibration rate signal by wavelet transform, and the wavelet coefficient of high band scale domain is carried out envelope refinement analysis of spectrum.When bearing breaks down, detail signal on the restructuring graph of wavelet analysis shows that one group of impact took place with the fault characteristic frequency time corresponding cycle, the fault characteristic frequency that clearly shows bearing in the envelope spectrogram behind wavelet transform, accurately extract the bearing fault characteristic frequency, judge the position that bearing fault occurs.
Described wavelet packet analysis also adopts the Mallat algorithm, it decomposes simultaneously to low frequency signal and the high-frequency signal after decomposing last time again, with the signal decomposition of different frequency range in corresponding frequency range, then can be as required with the signal reconstruction in the required frequency range, the signal of reconstruct is the same with original signal length, has played a kind of effect of filtering; In bearing fault is analyzed, if the bearing fault characteristic frequency that calculates is distributed in a certain frequency range, then can in the wavelet decomposition tree, find node corresponding, signal to this frequency range is reconstructed and analyzes its power spectrum again, diagnose bearing fault then: the fault bearing is arranged, the peak value of frequency spectrum is corresponding with outer ring fault characteristic frequency or inner ring fault characteristic frequency or rolling body fault characteristic frequency respectively after its reconstruct, and matches with the physical fault type of bearing; The reconstruction signal frequency spectrum of non-fault bearing does not then have tangible peak value at the fault characteristic frequency place.
Described HHT analytical applications Empirical mode decomposition (EMD), from bearing vibration signal, decomposite several IMF components, then each IMF component is carried out the Hilbert conversion, and then draw Hilbert time-frequency spectrum and Hilbert marginal spectrum, diagnose the fault of rolling bearing and discern fault mode according to Hilbert analysis of spectrum result.
Claims (11)
1. a bearing vibration is measured and fail analysis device, comprise measured bearing erecting device (5), speed pickup (1), signal conditioning circuit (11), data acquisition equipment (10) and computing machine (9), it is characterized in that: measured bearing (2) is installed on the axle (3) of described measured bearing erecting device (5), the vibration-sensing rod of described speed pickup (1) places on the facial planes of measured bearing outer ring external cylindrical surface with the pressure of regulation, direction of measurement along bearing radially and perpendicular to the axis of bearing, signal conditioning circuit (11) and data acquisition equipment (10) are connected to computing machine (9); The radial vibration rate signal of speed pickup (1) measurement axis bearing outer-ring, convert the bearing radial vibration rate signal that picks up to corresponding electric signal, this electric signal is after signal conditioning circuit (11) is handled, be transported to data acquisition equipment (10), by data acquisition equipment (10) signal after nursing one's health is carried out the A/D conversion, convert the treatable digital signal of computing machine (9) to, by computing machine (9) digital signal is analyzed and handled at last.
2. bearing vibration according to claim 1 is measured and fail analysis device, it is characterized in that described measured bearing erecting device (5), comprise main shaft (4), motor (7), frequency converter (8), axle (3), vertical slipper (13), vertical set lever (14), handwheel (12), horizontal gliding mass (16), horizontal set lever (17), knob (15), connect main shaft (4) and motor (7) by shaft coupling, frequency converter (8) is linked to each other with motor (7) by cable; Measured bearing (2) and axle correspondingly (3) are installed in main shaft (4) taper hole, unclamp vertical set lever (14) and horizontal set lever (17), adjusting knob (15), horizontal gliding mass (16) is moved forward and backward, finish the horizontal position adjustment of speed pickup (1), rise or decline vertical slipper (13) with handwheel (12), the regulate the speed upright position of sensor (1) is adjusted, the vibration-sensing rod of speed pickup (1) is placed on the facial planes of measured bearing (2) outer ring external cylindrical surface with the pressure of stipulating, after the sensor horizontal and vertical position is adjusted, lock vertical set lever (14) and horizontal set lever (17), regulate main shaft (4) rotating speed by frequency converter (8), rotate with constant rotational speed thereby make main shaft (4) drive measured bearing (2).
3. bearing vibration according to claim 1 is measured and fail analysis device, it is characterized in that described signal conditioning circuit (11), is made of isolated amplifier concatenation operation amplifier successively, integrated state variable filter and integrated programmable amplifier; The bear vibration rate signal that speed pickup picks up is at first after isolated amplifier amplifies, after amplifying by operational amplifier then, flow to integrated state variable filter signal is carried out pre-filtering, give the programmable amplifier amplifying signal with filtered signal conveys again, the signal conveys after will amplifying is at last given data collecting card.
4. a bearing vibration is measured and failure analysis methods, adopt described bearing vibration measurement of claim 1 and fail analysis device to test and analyze, it is characterized in that the bearing vibration rate signal after the conditioning is carried out digital quantity analysis and processing, calculation bearing vibration velocity effective value
, the vibration velocity peak value
With crest factor X, and can carry out time-domain analysis, fft analysis, envelope spectrum analysis, wavelet analysis, wavelet packet analysis and HHT to the bearing vibration rate signal and analyze, bear vibration is carried out quantitatively and qualitatively analyze, accurately the failure cause of failure judgement bearing.
5. bearing vibration according to claim 4 is measured and failure analysis methods, it is characterized in that: described bear vibration speed effective value
Calculating is the root-mean-square value computing formula of utilizing discrete signal
, wherein
Be discrete bear vibration rate signal, N is a sampling number,
Be the bear vibration speed effective value that calculates.
6. bearing vibration according to claim 4 is measured and failure analysis methods, it is characterized in that: described bear vibration velocity peak values
Utilize the peak counting method, from discrete signal
In find out n peak value
, discrete signal then
The peak value index be:
, wherein
Be the bear vibration velocity peak values of calculating, n is a peak value
Number.
7. bearing vibration according to claim 4 is measured and failure analysis methods, and it is characterized in that: described bear vibration speed crest factor X utilizes formula
, wherein X is the bear vibration speed crest factor of calculating.
8. bearing vibration according to claim 4 is measured and failure analysis methods, it is characterized in that: Hilbert amplitude demodulation method is adopted in described envelope spectrum analysis, the analytic signal real part that the Hilbert conversion obtains is a real signal itself, imaginary part is its Hilbert conversion, the amplitude of analytic signal is the envelope of signal, carry out spectrum analysis again, obtain envelope spectrum at last.
9. bearing vibration according to claim 4 is measured and failure analysis methods, it is characterized in that: the Mallat algorithm is adopted in described discrete wavelet analysis,
,
Wherein, j and k are integers; (DWT) transforms to time-scale domain with the bearing vibration rate signal by wavelet transform, and the wavelet coefficient of high band scale domain is carried out envelope refinement analysis of spectrum; When bearing breaks down, detail signal on the restructuring graph of wavelet analysis shows that one group of impact took place with the fault characteristic frequency time corresponding cycle, the fault characteristic frequency that clearly shows bearing in the envelope spectrogram behind wavelet transform, accurately extract the bearing fault characteristic frequency, judge the position that bearing fault occurs.
10. bearing vibration according to claim 4 is measured and failure analysis methods, it is characterized in that: described wavelet packet analysis also adopts the Mallat algorithm, it decomposes simultaneously to low frequency signal and the high-frequency signal after decomposing last time again, with the signal decomposition of different frequency range in corresponding frequency range, then can be as required with the signal reconstruction in the required frequency range, the signal of reconstruct is the same with original signal length, has played a kind of effect of filtering; In bearing fault is analyzed, if the bearing fault characteristic frequency that calculates is distributed in a certain frequency range, then can in the wavelet decomposition tree, find node corresponding, signal to this frequency range is reconstructed and analyzes its power spectrum again, diagnose bearing fault then: the fault bearing is arranged, the peak value of frequency spectrum is corresponding with outer ring fault characteristic frequency or inner ring fault characteristic frequency or rolling body fault characteristic frequency respectively after its reconstruct, and matches with the physical fault type of bearing; The reconstruction signal frequency spectrum of non-fault bearing does not then have tangible peak value at the fault characteristic frequency place.
11. bearing vibration according to claim 4 is measured and failure analysis methods, it is characterized in that: described HHT analytical applications Empirical mode decomposition (EMD), from bearing vibration signal, decomposite several IMF components, then each IMF component is carried out the Hilbert conversion, and then draw Hilbert time-frequency spectrum and Hilbert marginal spectrum, diagnose the fault of rolling bearing and discern fault mode according to Hilbert analysis of spectrum result.
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