CN110501158A - Needing machine transmission mechanism vibration signal characteristics extracting method - Google Patents
Needing machine transmission mechanism vibration signal characteristics extracting method Download PDFInfo
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- CN110501158A CN110501158A CN201910418746.7A CN201910418746A CN110501158A CN 110501158 A CN110501158 A CN 110501158A CN 201910418746 A CN201910418746 A CN 201910418746A CN 110501158 A CN110501158 A CN 110501158A
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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
- G01M13/02—Gearings; Transmission mechanisms
- G01M13/028—Acoustic or vibration analysis
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Abstract
The needing machine transmission mechanism vibration signal processing method that the invention proposes a kind of based on MEEMD in conjunction with index wavelet threshold.The needing machine transmission mechanism vibration signal of acquisition is subjected to end extending processing by the adaptive end extending method of Waveform Matching, then wavelet decomposition is carried out, utilization index wavelet threshold function carries out noise reduction to the signal of acquisition and reconstructs, signal after obtaining noise reduction, envelope fitting is carried out to the vibration signal after noise reduction with cubic B-spline method, MEEMD decomposition is carried out to signal again, obtain the cross-correlation coefficient and kurtosis value of several IMF components with signal after noise reduction, correlation analysis is carried out to IMF and original signal, select useful IMF, Hilbert transform finally is carried out to IMF component, obtain the hilbert spectrum of signal, for the signal characteristic of needing machine transmission mechanism vibration signal.This method is suitable for the fault diagnosis of industrial circle needing machine transmission mechanism.
Description
Technical field
The application proposes needing machine drive failure characteristic signal processing side of the MEEMD in conjunction with index wavelet threshold
Method, the fault diagnosis suitable for machinery field needing machine transmission mechanism.
Background technique
With new technology, the continuous application of new material, every technical performance of domestic needing machine has improved a lot, but
Its basic principle be all it is identical, i.e., driven by eccentric wheel connecting rod mechanism and pumped equipped with the needle plate of pricker,
To achieve the purpose that pricker is implemented to reinforce to processed web.It is a difference in that the positioning that needle plate and needle plate beam move back and forth
In mechanism, there are mainly two types of mechanism forms in the design of high frequency needle punching machine at home: first is that box using main shaft；Second is that nothing
Case gear rocker-type.Liang Zhong mechanism has their own advantages, parallel development, and country's punch frequency is in 1000 thorns/min or more needle at present
Thorn machine majority is box using main shaft.
Currently, mainly realizing the monitoring of needing machine transmission mechanism using the method for Digital Signal Analysis and Processing both at home and abroad and examining
It is disconnected.Transmission mechanism is one kind of rotating machinery, can generate vibration in the process of running, and it is periodic for vibrating.If passed
Motivation structure breaks down, then vibration signal will appear periodically pulsing, the frequency of the pulse is exactly failure-frequency.Therefore,
The vibration signal for acquiring transmission mechanism, can extract signal characteristic by method appropriate, to obtain the fortune of needing machine indirectly
Row situation.
Currently, common feature extracting method has wavelet analysis method, empirical mode decomposition (EMD) method, local mean value
(LMD) method of decomposition etc..Wavelet analysis method is a kind of Time-Frequency Analysis Method, not only can carry out global analysis to signal, but also can
To realize partial analysis, but the selection of this and wavelet basis has much relations, and wavelet basis will be unable in the analysis process once selecting
Replacement, then the resolution ratio of signal analysis also just secures, this illustrates that wavelet analysis does not have adaptability to the partial analysis of signal.
EMD method is a kind of adaptive signal analysis method, it is and every by the sum of signal decomposition several intrinsic mode functions (IMF)
A IMF is the signal of approximate unifrequency ingredient, in this way, the Hilbert for combining each IMF composes the frequency of available entire signal
Spectrum.This method the problem is that, to IMF carry out Hilbert transformation when, unaccountable negative frequency can be generated, and
And end effect can be caused during signal decomposition, the chaff component unrelated with original signal is mixed in the IMF decomposited.
In conclusion analysis of vibration signal is the effective method that needing machine transmission mechanism is monitored and is diagnosed.Mesh
There is only discontinuous points for preceding common wavelet threshold function, but also there are problems that constant deviation.Secondly, EMD method is then deposited
Negative frequency, end effect and the chaff component the problems such as, need to study it is a kind of overcome asked present in wavelet function and EMD method
A kind of signal analysis method of topic.The needing machine transmission that present applicant proposes a kind of based on MEEMD in conjunction with index wavelet threshold
Mechanism-trouble characteristic signal processing method, can effectively analyze vibration signal.
Summary of the invention
In the presence of solving the problems, such as the above method, the application provides one kind based on MEEMD and index wavelet threshold
In conjunction with needing machine drive failure characteristic signal processing method, arrangement including sensor, data acquisition, signal analysis and
Four processing, feature extraction modules.The needing machine transmission mechanism vibration signal of acquisition is passed through to the adaptive endpoint of Waveform Matching
Continuation method carries out end extending processing, then carries out wavelet decomposition, and utilization index wavelet threshold function carries out the signal of acquisition
Noise reduction simultaneously reconstructs, the signal after obtaining noise reduction, carries out envelope fitting again to the vibration signal after noise reduction with B Spline Method three times
MEEMD decomposition is carried out to signal, obtains the cross-correlation coefficient and kurtosis value of signal after several IMF components and noise reduction, to IMF and
Original signal carries out correlation analysis, selects useful IMF, finally carries out Hilbert transformation to IMF component, obtains signal
Hilbert spectrum, the as signal characteristic of needing machine transmission mechanism vibration signal.
Index wavelet threshold function is handled to the wavelet coefficient for being less than threshold value and greater than the wavelet coefficient of threshold value, is solved
Discontinuously there is discontinuous point in entire wavelet field in hard threshold function, reduce the variance of de-noising signal, and solve
There is constant deviation in soft-threshold function of having determined.MEEMD is not only solved in conjunction with index wavelet threshold to be deposited in EMD decomposition
Mode confounding issues, also overcome EEMD decompose with CEEMD decompose present in the division of computationally intensive, mode, white noise
The problems such as remaining.The adaptive end of Waveform Matching is respectively adopted in the problems such as there is also end effects, chaff component in MEEMD
Point continuation method, cross-correlation analysis screening method are handled.
Specific step is as follows for needing machine transmission gear vibration signal characteristics extracting method:
(1) reasonable placement sensor, vibration signal when acquisition needing machine transmission gear is run；
(2) continuation is carried out to signal both ends using auto-correlation image method；
1) signal is setLength is, the corresponding time is followed successively by, left end point is, andIt is not extreme value
Point,Extreme point be followed successively by from left to right, the corresponding time is followed successively by, then mistakeThe waveform of this four points forms a signature waveform, is denoted as A, length L, includes at least one greatly
Value, minimum and zero crossing；
2) A is subjected to autocorrelation calculation, formula is as follows:
In formula, N is signal length, and n is time delay number；
3) it takesMirror image, continuation to signal left end point, then after continuation signal left end point be an extreme point；
4) right endpoint ibid carries out continuation；
(3) Threshold Denoising is improved
WhereinAndFor positive number；
1) it selects an appropriate small echo and determines the number of plies N of wavelet decomposition, N layers of wavelet decomposition then are carried out to signals and associated noises,
To obtain the decomposition coefficient of small echo；
2) to the wavelet coefficient after decompositionThreshold value quantizing is carried out, index threshold function is selected to carry out noise reduction to signals and associated noises
Processing obtains estimation wavelet coefficient；
3) signal after noise reduction is reconstructed i.e. to processed wavelet coefficientWavelet inverse transformation is carried out, is estimated
Signal after signal, that is, noise reduction；
(4) before carrying out MEEMD decomposition to de-noising signal, envelope is fitted using cubic Bézier curves method, specific steps are such as
Under:
A controlling polygon is constructed, controlling polygon is formed by connecting by each control vertex, ifFor control
The side length of polygon, side length total length are.The then knot vector of secondary B-spline curves
It is writeable are as follows:
In order to meet the local property requirement of B-spline curves, the side of controlling polygon when calculatingIt is corresponding by itSide and come
Instead of then standardizing to it.Calculate domain interior nodes siding-to-siding block length:
Using Setting signal extreme point as control vertex,Secondary B-spline interpolation curve controlling polygon
AccordinglyThe sum on sideAre as follows:
The knot vector standardization denominator of secondary B-spline interpolation curveAre as follows:
It can be obtained by analyzing aboveSecondary B-spline is fitted all nodal values of extremal are as follows:
Knot vector after then parameterizing can indicate are as follows:
It is defined by B-spline Curve and is substituted into nodal value and be fitted Envelope equation known to equation are as follows:
Envelope Equations are just acquired in this way；
(5) MEEMD decomposition is carried out, steps are as follows:
MEEMD decomposition be that one group of amplitude white noise consistent with standard deviation, contrary is added in original signal, repeat into
Row EEMD and EMD are decomposed, and are obscured and the EEMD calculation amount decomposed and residual components with reducing the mode of EMD decomposition；Specific steps
It is as follows:
1): the white noise root-mean-square value being added into original signal should be close to internal noise to be decomposed, or is no more than wait divide
Solve 0.3 times of signal root-mean-square value；
2): set one group of white noise that the absolute value being added into signal to be decomposed is equal, contrary asWith,
EEMD decomposition is carried out to it respectively:
In above formulaWithFor 2 groups of IMFs components obtained in EEMD decomposable process；
3): takingWithAverage value:
4): willIt is decomposed with following EMD isolation:
In above formulaIt indicatesThe IMF component obtained after EMD is decomposed；Indicate the superposition of remaining residual components；
5): after the decomposition of MEEMD, original signal be may be expressed as:
In above formulaIndicate finally obtained IMF component；Indicate finally obtained residual components；
(6) the IMF component for decomposing MEEMD carries out Hilbert transformation, obtains the Hilbert spectrum of signal, and as needle pierces
The signal characteristic of machine transmission gear vibration signal.
The application proposes needing machine drive failure characteristic signal processing side of the MEEMD in conjunction with index wavelet threshold
Method is fitted and eliminates the processing of chaff component by the improvement to wavelet threshold and to end effect, envelope, can be fast
Speed, the fault signature for accurately extracting vibration signal, easily can be monitored and diagnose to needing machine transmission mechanism, be
Enterprise saves a large amount of manpower and financial resources.
Detailed description of the invention:
Attached drawing 1 is Figure of abstract, and attached drawing 2 is point position schematic diagram.
Specific embodiment:
In attached drawing 2: the 1. horizontal 2. axial measuring points of vertical measuring point 3. of measuring point.
1. signal acquisition
Signal acquisition is carried out to needing machine transmission mechanism vibration signal using acceleration transducer.Sensor use herein is
DH186IEPE piezoelectric acceleration transducer, sensitivity are 0 ~ 10mV/ms-2, range 500m/s2, frequency range 0.5 ~
5kHz.Vasculum selects the DH-5923 dynamic signalling analysis instrument of east magnificent test company.Acceleration transducer is arranged in three
It on direction, is horizontally oriented respectively, vertical direction, axial direction.It is axially the centering degree in order to detect needing machine transmission mechanism, water
The signal of gentle vertical direction then reflects the fault signature of needing machine transmission mechanism.
3. carrying out endpoint processing to signal using auto-correlation image method
If signalLength is, the corresponding time is followed successively by, left end point is, andIt is not extreme point,Extreme point be followed successively by from left to right, the corresponding time is followed successively by, then mistakeThe waveform of this four points forms a signature waveform, is denoted as A, length L, includes at least one greatly
Value, minimum and zero crossing；A is subjected to autocorrelation calculation, formula is as follows:
In formula, N is signal length, and n is time delay number；It takesMirror image, continuation to signal left end point, then signal after continuation
Left end point is an extreme point；Right endpoint ibid carries out continuation.
4. being fitted envelope using cubic Bézier curves method.
Polygon is formed by connecting by each control vertex in cubic Bézier curves, using Setting signal extreme point as control vertex,
The distance between two control vertexs are the side length of polygon, acquire the sum of all side lengths of polygon, obtain B-spline song by formula
The knot vector of line, and then B-spline fitting all nodal values of extremal are obtained, the knot vector after finally acquiring parametrization,
It is defined according to B-spline Curve and nodal value substitution equation is acquired into Envelope equation.
A controlling polygon is constructed, controlling polygon is formed by connecting by each control vertex, ifFor control
The side length of polygon, side length total length are.The then knot vector of secondary B-spline curves
It is writeable are as follows:
In order to meet the local property requirement of B-spline curves, the side of controlling polygon when calculatingIt is corresponding by itThe sum on side
It replaces, then standardizes to it.Calculate domain interior nodes siding-to-siding block length:
Using Setting signal extreme point as control vertex,Secondary B-spline interpolation curve controlling polygon
AccordinglyThe sum on sideAre as follows:
The knot vector standardization denominator of secondary B-spline interpolation curveAre as follows:
It can be obtained by analyzing aboveSecondary B-spline is fitted all nodal values of extremal are as follows:
Knot vector after then parameterizing can indicate are as follows:
It is defined by B-spline Curve and is substituted into nodal value and be fitted Envelope equation known to equation are as follows:
Envelope Equations are just acquired in this way.
Claims (1)
1. a kind of needing machine transmission mechanism vibration signal characteristics extracting method, it is characterised in that by the needing machine transmission mechanism of acquisition
Vibration signal carries out end extending processing by the adaptive end extending method of Waveform Matching, then carries out wavelet decomposition, utilizes
Index wavelet threshold function carries out noise reduction to the signal of acquisition and reconstructs, the signal after obtaining noise reduction, with cubic B-spline method to drop
Vibration signal after making an uproar carries out envelope fitting and carries out MEEMD decomposition to signal again, obtains signal after several IMF components and noise reduction
Cross-correlation coefficient and kurtosis value, correlation analysis is carried out to IMF and original signal, selects useful IMF, finally, to IMF component into
Row Hilbert transform obtains the hilbert spectrum of signal, the as signal characteristic of needing machine transmission mechanism vibration signal；
Specific step is as follows for needing machine transmission mechanism vibration signal characteristics extracting method:
(1) reasonable Arrangement sensor, vibration signal when acquisition needing machine transmission mechanism is run；
(2) vibration signal both ends carry out continuation to it using auto-correlation image method；
1) signal is setLength is, the corresponding time is followed successively by；
WhereinLeft end point be(It is not extreme point), extreme point is(from left to right), when corresponding
Between be, cross this four pointsWaveform form a signature waveform, be denoted as A, length L；
It wherein include at least one maximum value minimum and zero crossing；
2) A is subjected to autocorrelation calculation, formula is as follows:
N in above formula is signal length, and n is time delay number；
3) it takesMirror image, the left end point of continuation to signal, after continuation the left end point of signal be an extreme point；
4) right endpoint ibid carries out continuation；
(3) index Threshold Denoising
WhereinAndFor positive number
1) it selects an appropriate small echo and determines the number of plies N of wavelet decomposition, N layers of wavelet decomposition then are carried out to signals and associated noises,
To obtain the decomposition coefficient of small echo；
2) to the wavelet coefficient after decompositionThreshold value quantizing is carried out, index threshold function is selected to carry out at noise reduction signals and associated noises
Reason obtains estimation wavelet coefficient；
3) signal after noise reduction is reconstructed i.e. to processed wavelet coefficientWavelet inverse transformation is carried out, estimation letter is obtained
Signal number i.e. after noise reduction；
(4) quasi- using cubic Bézier curves method before carrying out MEEMD decomposition to the needing machine transmission mechanism vibration signal of noise reduction
Close envelope, the specific steps are as follows:
By each control point connecting structure at a controlling polygon, if the side length of controlling polygon is, then more
Side shape Zhou Changwei, thenThe knot vector of secondary B-spline curves is writeable are as follows:
In order to meet the local property requirement of B-spline curves, the side of controlling polygon when calculatingIt is corresponding by itSide and come
Instead of then standardizing to it；
Calculate domain interior nodes siding-to-siding block length:
Using Setting signal extreme point as control vertex,Secondary B-spline interpolation curve controlling polygon is corresponding
The sum on sideAre as follows:
The knot vector standardization denominator of secondary B-spline interpolation curveAre as follows:
It can be obtained by analyzing aboveSecondary B-spline is fitted all nodal values of extremal are as follows:
Knot vector after then parameterizing can indicate are as follows:
It is defined by B-spline Curve and is substituted into nodal value and be fitted Envelope equation known to equation are as follows:
Envelope Equations are just acquired in this way；
(5) MEEMD decomposition is carried out, steps are as follows:
MEEMD decomposition be that one group of amplitude white noise consistent with standard deviation, contrary is added in original signal, repeat into
Row EEMD and EMD are decomposed, and are obscured and the EEMD calculation amount decomposed and residual components with reducing the mode of EMD decomposition；Specific steps
It is as follows:
1): the white noise root-mean-square value being added into original signal should be close to internal noise to be decomposed, or is no more than wait divide
Solve 0.3 times of signal root-mean-square value；
2): set one group of white noise that the absolute value being added into signal to be decomposed is equal, contrary asWith,
EEMD decomposition is carried out to it respectively:
In above formulaWithFor 2 groups of IMFs components obtained in EEMD decomposable process；
3): takingWithAverage value:
4): willIt is decomposed with following EMD isolation:
In above formulaIt indicatesThe IMF component obtained after EMD is decomposed；Indicate the superposition of remaining residual components；
5): after the decomposition of MEEMD, original signal be may be expressed as:
In above formulaIndicate finally obtained IMF component；Indicate finally obtained residual components；
(6) the IMF component for decomposing MEEMD carries out Hilbert transformation, obtains the Hilbert spectrum of signal, and as needle pierces
The signal characteristic of machine transmission mechanism vibration signal.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111289231A (en) * | 2020-01-21 | 2020-06-16 | 中国农业大学 | Rotor system health monitoring method and system based on incomplete B-spline data fitting |
| CN111982489A (en) * | 2020-08-27 | 2020-11-24 | 江苏师范大学 | Weak fault feature extraction method for selectively integrating improved local feature decomposition |
| CN112595514A (en) * | 2020-11-26 | 2021-04-02 | 上海航天控制技术研究所 | High-speed bearing assembly vibration signal noise reduction processing method |
| CN113970419A (en) * | 2021-10-13 | 2022-01-25 | 中国科学院力学研究所 | Shock tunnel force measurement balance signal data processing method based on time-frequency transformation |
| CN114298106A (en) * | 2021-12-29 | 2022-04-08 | 中国铁道科学研究院集团有限公司铁道建筑研究所 | Characteristic wave identification method in roadbed rolling, rolling state discrimination method and application thereof |
| CN115204243A (en) * | 2022-09-15 | 2022-10-18 | 西南交通大学 | LMD endpoint effect improvement method based on similar triangular waveform matching continuation |
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111289231A (en) * | 2020-01-21 | 2020-06-16 | 中国农业大学 | Rotor system health monitoring method and system based on incomplete B-spline data fitting |
| CN111289231B (en) * | 2020-01-21 | 2020-12-22 | 中国农业大学 | Rotor system health monitoring method and system based on incomplete B-spline data fitting |
| CN111982489A (en) * | 2020-08-27 | 2020-11-24 | 江苏师范大学 | Weak fault feature extraction method for selectively integrating improved local feature decomposition |
| CN111982489B (en) * | 2020-08-27 | 2022-05-06 | 江苏师范大学 | Weak fault feature extraction method for selectively integrating improved local feature decomposition |
| CN112595514A (en) * | 2020-11-26 | 2021-04-02 | 上海航天控制技术研究所 | High-speed bearing assembly vibration signal noise reduction processing method |
| CN113970419A (en) * | 2021-10-13 | 2022-01-25 | 中国科学院力学研究所 | Shock tunnel force measurement balance signal data processing method based on time-frequency transformation |
| CN113970419B (en) * | 2021-10-13 | 2022-05-13 | 中国科学院力学研究所 | Shock tunnel force measurement balance signal data processing method based on time-frequency transformation |
| CN114298106A (en) * | 2021-12-29 | 2022-04-08 | 中国铁道科学研究院集团有限公司铁道建筑研究所 | Characteristic wave identification method in roadbed rolling, rolling state discrimination method and application thereof |
| CN114298106B (en) * | 2021-12-29 | 2022-07-22 | 中国铁道科学研究院集团有限公司铁道建筑研究所 | Characteristic wave identification method in roadbed rolling |
| CN115204243A (en) * | 2022-09-15 | 2022-10-18 | 西南交通大学 | LMD endpoint effect improvement method based on similar triangular waveform matching continuation |
| CN115204243B (en) * | 2022-09-15 | 2023-02-07 | 西南交通大学 | LMD endpoint effect improvement method based on similar triangular waveform matching continuation |
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