CN104899409B - A kind of engineering machinery driven load signal antinoise method based on wavelet analysis - Google Patents
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Abstract
The invention discloses a kind of engineering machinery actuating signal denoising method based on wavelet analysis, based on Wavelet Analysis Theory, vehicle running state is divided into idling operation and random operating mode so that the denoising experience of idling operation provides reference for the denoising of random operating mode.First, under idling operation, obtain load data and calculate wavelet coefficient and threshold value on each decomposition scale, threshold value quantizing processing is carried out to wavelet coefficient with threshold value, removes the wavelet coefficient less than threshold value, retains remaining wavelet coefficient；One-dimensional wavelet reconstruction is carried out to load data using the wavelet coefficient of reservation, completes denoising.Secondly, under random operating mode, obtain load data and calculate the wavelet coefficient on each decomposition scale, threshold value quantizing processing is carried out to wavelet coefficient using the threshold value in idling operation, removes the wavelet coefficient less than threshold value, retains remaining wavelet coefficient；One-dimensional wavelet reconstruction is carried out to load data using the wavelet coefficient of reservation, completes denoising.
Description
Technical field
The present invention relates to field of signal processing, and in particular to a kind of engineering machinery actuating signal denoising based on wavelet analysis
Method.
Background technology
Loading spectrum is the legacy system Parts life-span to be estimated and the basis of fail-safe analysis.Engineering machinery by
Complicated in driving cycle, running environment is severe and purposes is special, and its load born belongs to random load, such as engine fortune more
Caused vibration, each parts of transmission system bear the impact from external loads such as roads, produced in transmission process during turning
Caused shock and vibration etc. in raw torsion additional load, shift process, these load belong to high frequency signal load more.By
Acted on for a long time by random additional load in each parts of transmission system, easily produce fatigue rupture, in addition it is cracked or
Person is broken, and has a strong impact on the reliability and durability of system.
At present, in system of vehicle transmission load data processing procedure, the external load from road etc. is often only focused on, and is neglected
Slightly transmission system is acted on and the influence of caused additional load by other.This processing mode causes in reliability fatigue experiment
Result and actual state have bigger difference, meanwhile, in system of vehicle transmission load signal data acquisition, due to by road
The external environmental interferences such as face, temperature, and other vehicle-mounted electrical equipments are to the electromagnetic interference of test circuit so that useful load is believed
Mixing noise signal in number, signal to noise ratio reduces, thus, in engineering machinery load signal gatherer process being frequently present of noise does
The problem of disturbing.
Therefore, in load signal data handling procedure, the load signal analyzed includes many spikes or Mutational part,
And noise contribution is complicated, more than stationary white noise, so finding a kind of good denoising method remained with load signal
It is very important so that failtests is closer to reality.
Have in the prior art and denoising is carried out to vehicle time domain load signal using small wave fractal theory, this method is to establish
On the basis of the phase space reconfiguration to time domain load signal, three chis are carried out to the time domain load signal of actual measurement using wavelet method
Degree decomposes, and calculates the correlation dimension of signal on a decomposition scale, to consider several factors during calculating correlation dimension, such as adopt
Sample time, length of time series, time delay, Embedded dimensions, noise etc., if the correlation dimension being calculated is tieed up with embedded
Number increases and decreases and increased, it is believed that signal less contains noise, conversely, then selecting threshold denoising, believes after calculating denoising again after denoising
Number correlation dimension, until correlation dimension with Embedded dimensions increase and decrease and increase.As can be seen here, the method amount of calculation of this denoising
Greatly, and in correlation dimension calculating process, the factor of consideration is more, and the wherein sampling time is empirically determined, time delay
Determined with heuristic.It can be seen that denoising method of the prior art is computationally intensive and denoising is not accurate enough.
The content of the invention
In view of this, will be the invention provides a kind of engineering machinery actuating signal denoising method based on wavelet analysis
The threshold value being calculated under idling operation with simple method, which is directly used under the random operating mode of complexity, carries out denoising, reduces and calculates
Good denoising effect is ensure that while amount.
Operating mode in vehicle travel process is divided into idling operation and random operating mode, this method comprises the following steps：
Step 1, under idling operation, obtain load data and simultaneously calculate the wavelet coefficient under idling operation on each decomposition scaleWith threshold value λ, with threshold value λ to wavelet coefficientThreshold value quantizing processing is carried out, removes the wavelet coefficient less than threshold value,
Retain remaining wavelet coefficient to be designated asUtilize the wavelet coefficient of reservationLoad data under idling operation is entered
The one-dimensional wavelet reconstruction of row, completes denoising；
Step 2, under random operating mode, obtain load data and simultaneously calculate the wavelet coefficient on each decomposition scaleProfit
With the idling operation lower threshold value λ calculated in step 1 to wavelet coefficientThreshold value quantizing processing is carried out, is removed less than threshold value
Wavelet coefficient, retain remaining wavelet coefficient and be designated asUtilize the wavelet coefficient of reservationTo under random operating mode
Load data carries out one-dimensional wavelet reconstruction, completes denoising.
Threshold value λ calculating process includes in the step 1：
Calculate the wavelet coefficient under each decomposition scale
Wherein, j is Decomposition order, and k is translation parameters, and t represents time, x1(t) it is primary signal, ψ [2-j(k-t)] it is base
Small echo；
Calculating noise variance σ：
Wherein, the median meaning is to take the intermediate value of the set of wavelet coefficient under each decomposition scale；
Finally, each decomposition scale upper threshold value λ is calculated：
Wherein, N represents signal sampling points.
Beneficial effect：
(1) present invention combines the characteristic of vehicle drive system based on Wavelet Analysis Theory, by vehicle travel process
Operating mode be divided into idling operation and random operating mode, due in same secondary data acquisition noise characteristic be it is the same, therefore
The threshold value under idling operation is only calculated, and threshold value is directly used in random operating mode, you can completes denoising, this denoising method
The calculating of random operating mode lower threshold value is eliminated, has reached good denoising effect while simplifying denoising process.
(2) under idling operation, output shaft of gear-box by one close to the moment of torsion of steady state value or near a certain value it is small
The moment of torsion of scope fluctuation, shows as smooth horizontal near linear or the curve of fluctuating very little on torsion-time figure, it is believed that
Signal noise is simpler, easily extracts noise variance, so as to carry out idling operation lower threshold value using the method used in the present invention
Calculating, this method not only simple accuracy but also high.
Brief description of the drawings
Fig. 1 is the engineering machinery driven load signal antinoise method flow chart based on wavelet analysis.
Fig. 2 is Construction Machinery Transmissions composition and basic layout.
Wherein, Z- steering mechanism, B- gearboxes, D- driving wheels, C- measuring points, the input of S- power.
Fig. 3 is the preceding 100s initial data collected under idling operation.
Fig. 4 is Wavelet Denoising Method result under idling operation.
Fig. 5 is initial data Fourier transformation spectrogram under random operating mode.
Fig. 6 is Wavelet Denoising Method result under random operating mode.
Fig. 7 is Wavelet Denoising Method result Fourier transformation spectrogram under random operating mode.
Fig. 8 is for Wavelet Denoising Method result under random operating mode with initial data Frequency spectrum ratio compared with enlarged drawing.
Fig. 9 is speed changer executive component oil pressure variation diagram under random operating mode.
Figure 10 is shift of transmission procedure chart under random operating mode.
Figure 11 is certain the 300s initial data collected under random operating mode.
Figure 12 is initial data and Wavelet Denoising Method results contrast enlarged drawing under random operating mode.
Embodiment
The invention provides a kind of engineering machinery actuating signal denoising method based on wavelet analysis, its core concept is：
Vehicle drive system characteristic is combined based on Wavelet Analysis Theory, takes the mode of divided working status to carry out at load signal denoising
Reason, due in same secondary data acquisition, onboard measure system working condition and external environment and other interference because
Element is essentially identical, and noise characteristic is the same in same secondary data acquisition, therefore vehicle running state is divided into stand under load
Simple idling operation and except idling operation and other stand under load complex working conditions are referred to as random operating mode so that idling operation
Denoising experience provides reference for the denoising of random operating mode, makes denoising process evidence-based, so as to reach good denoising effect.
The present invention will now be described in detail with reference to the accompanying drawings and examples.
A kind of engineering machinery actuating signal denoising method based on wavelet analysis, its step specifically include：
Step 1, under idling operation, obtain load data and simultaneously calculate the wavelet coefficient under idling operation on each decomposition scale
ω1With threshold value λ, denoising is carried out to the signal under idling operation with threshold value λ；
As shown in Fig. 2 intelligent object data collecting system of the present invention using German IMC companies, to driveline gear
Case output shaft idling operation load is tested, and test point is C points shown in Fig. 2；Gather idling operation output shaft of gear-box moment of torsion
T1, and output shaft torque T is extracted by signal analysis and processing software1Corresponding primary signal x1(t)。
In the signal processing, we are usually using binary system discrete wavelet sequence：
Wherein, j is Decomposition order, and k is translation parameters, and j, k take positive integer, and t represents time, ψ [2-j(k-t) it is] small for base
Ripple.
Under idling operation, interaction force (residual force after previous operating mode) is there may be between gearbox itself part,
It is not exclusively horizontal there is also road and as caused by Action of Gravity Field power so that output shaft of gear-box is by one close to steady state value
Moment of torsion or the moment of torsion that small range fluctuates near a certain value, show as smooth horizontal near linear on torsion-time figure
Or the curve of fluctuating very little.
Calculate the wavelet coefficient obtained under each decomposition scale
x1(t) it is primary signal, can be taken according to the Donoho variance evaluations proposed during noise variance σ denoising Processings：
Wherein, the median meaning is to take the intermediate value of the set of wavelet coefficient under each decomposition scale.
Threshold value should be taken by calculating on each decomposition scale：
Wherein, N represents signal sampling points, the output shaft of gear-box torque T obtained when as measuring1Number.
By the threshold value λ being calculated to the wavelet coefficient under each decomposition scaleThreshold value quantizing processing is carried out, is removed
Less than the wavelet coefficient of threshold value, retain remaining wavelet coefficientFinally according to the wavelet coefficient of reservationCarry out
One-dimensional wavelet reconstruction obtains Wavelet Denoising Method signal
Wherein, A is the constant unrelated with signal.
The denoising effect of this step is analyzed below：
Idling operation load noise mainly includes ambient noise, collecting device and its produced with vehicle electronic circuit electromagnetic interference etc.
Noise.In order to more accurately represent denoising effect, can be described with signal to noise ratio (SNR) and mean square error (MSE).It is if former
Beginning signal theory value is X1(t)：
X1(t)=T (6)
T=ir Mg sin θs (7)
Wherein, i is wheel side gearratio, and r is radius of wheel, and M is vehicular gross combined weight, and g is acceleration of gravity, 9.8N/kg, θ
For road grade angle.
Signal after Wavelet Denoising Method isThen signal to noise ratio is defined as：
Primary signal theoretical value and the mean square deviation of Wavelet Denoising Method signal are defined as：
Denoising quality can be evaluated by signal to noise ratio and mean square deviation.In general, signal to noise ratio is higher, mean square deviation is smaller,
Then for denoised signal closer to primary signal, denoising quality is higher, and denoising quality is evaluated with this.As shown in Figure 4, it can be seen that idle
Denoising works well under fast operating mode, therefore the threshold value λ calculated under idling operation is suitable, due to idling operation and random work
Data gather in same process under condition, thus noise characteristic be it is the same, can by the threshold value λ under idling operation be used for
Machine operating mode, reference is provided for random operating mode.
Step 2, under random operating mode, calculate wavelet coefficientAnd utilize threshold under the idling operation calculated in step 1
Value λ is to wavelet coefficientThreshold value quantizing processing is carried out, denoising is carried out to the primary signal under random operating mode；
The random operating loading of driveline gear case output shaft is tested, test point is C points shown in Fig. 2；Collection with
Machine operating loading data：Output shaft of gear-box torque T2, and output shaft torque T is extracted by signal analysis and processing software2It is corresponding
Primary signal x2(t)。
Fourier transformation frequency spectrum calculating is carried out to the data collected, obtains the spectrogram of random operating mode, as shown in figure 5,
As can be seen that signal collected frequency distribution scope and concentration scope from spectrogram.
Binary system discrete wavelet sequence is selected, as shown in formula (1), and is calculated under each decomposition scale under random operating mode
Wavelet coefficient
Next with the threshold value λ being calculated under idling operation to the wavelet coefficient under each decomposition scale under random operating modeThreshold value quantizing processing is carried out, removes the wavelet coefficient less than threshold value, retains remaining wavelet coefficientFinally
One-dimensional wavelet reconstruction is carried out according to the wavelet coefficient of reservation, obtains Wavelet Denoising Method signal
Wherein, A is the constant unrelated with signal.
Below to the denoising result of this stepWith primary signal x2(t) contrasted：
To Wavelet Denoising Method signalFourier transformation is carried out, spectrogram is obtained, as shown in fig. 7, again with being obtained in step 2
Spectrogram (Fig. 5) contrasted, as shown in Figure 8, it can be seen that the useful signal of low frequency section can almost be fully retained, intermediate frequency
Rate segment signal suitably removes part such as spike, singular value, trend term signal compared with initial data, it is believed that is noise signal, protects
Most of useful intermediate-freuqncy signal is stayed；High-frequency segment signal eliminates most of such as high-frequency electromagnetic interference or carried higher than transmission
The signal of lotus maximum change frequency, it is believed that it is noise signal, while useful high frequency load letter caused by appropriate reservation such as gearshift
Number, it is believed that it is useful high-frequency signal.
In order to verify denoising effect under random operating mode, in collection output shaft of gear-box torque T2When simultaneously gather gearshift letter
Number, executive component oil pressure data, and be depicted as shift logic and each executive component oil pressure variation diagram, as shown in Figure 9.It is general and
Speech, gear is unchanged, vehicle smooth-ride, and the change of gearbox output torque is gentle, and fluctuation is smaller；During lifting gear, speed change
The change of case output torque is violent, and fluctuation is larger.It can be seen in figure 9 that transmission system is in shift process and gear change
When, it can be seen that the change of gearbox output torque and change in torque and Wavelet Denoising Method in shift process under each driving cycle
As a result match, reference can be provided for random operating mode by showing the denoising experience of idling operation.
Instance analysis：
Idling operation：
During experiment, basic horizontal road surface is selected, before vehicle traveling, engine ignition is started, and collecting device is opened, vehicle
First remains stationary, start acquisition noise signal, put into gear and start running after 60s, intercept the preceding 100s data collected and preserve, such as scheme
Shown in 3.
The threshold value λ that should be taken on each decomposition scale can be calculated according to formula (1)~(2), wherein Decomposition order takes 4 layers,
Result of calculation is as shown in table 1.Meet change of the noise wavelet coefficients with decomposition scale, show the trend being gradually reduced.Again
Wavelet transformation is carried out to the data obtained by gathering, the result obtained after denoising is as shown in Figure 4.
Threshold value λ should be taken on 1 each decomposition scale of table
Understand that, in 0~60s, due to stationary vehicle, in theory, gearbox is due to mutual between part itself through analysis
Active force and from the caused power of road, output shaft of gear-box should be by one close to constant torque value, Huo Zhe
The fluctuation of small range, shows as smooth horizontal near linear, or the curve of fluctuating very little on the diagram near a certain torque value,
And preceding 60s figure line is consistent with this just in Fig. 4.Signal to noise ratio (SNR) before table 2 lists after the processing of 60s Wavelet Denoising Methods and equal
Variance (MSE).
The signal to noise ratio of table 2 and mean square deviation
Random operating mode：
The random load signal of a length of 5 minutes when gathering project machinery is in certain traveling work, as shown in figure 11.First
Fourier transformation is carried out to initial data and obtains its spectrogram, as shown in Figure 5.From fig. 5, it can be seen that signal collected frequency
0~10Hz is distributed in mostly, and is concentrated the most with 0~5Hz.
Signal denoising processing is carried out using the wavelet toolbox Wavelet Toolbox of MATLAB softwares.With reference to idling work
The denoising experience of wavelet analysis under condition, Wavelet Denoising Method under random operating mode, select db4 small echos, Decomposition order 4；Again to each point
The wavelet coefficient adjustment threshold size solved under yardstick carries out threshold value quantizing processing；Finally according to the bottom low frequency coefficient of wavelet decomposition
One-dimensional wavelet reconstruction is carried out with each layer high frequency coefficient, denoising result is as shown in Figure 6.
Initial data and Wavelet Denoising Method result are compared, such as Figure 12, it can be seen that the method for wavelet analysis denoising it
After can retain substantially with initial data similar in fluctuation tendency.Fourier transformation is carried out to wavelet analysis result again, such as Fig. 7 can
To find out that more than 10Hz frequency information (being considered noise signal herein) there's almost no.The spectrogram of the two is carried out pair again
Than such as Fig. 8, it can be seen that 0~1Hz frequency information can almost be fully retained, and 1~5Hz frequency information is compared with initial data
It is decreased, but major part is remained, and 5~10Hz frequency information has also retained, and thus illustrates, the method for wavelet analysis
It is to carry out denoising on the premise of remaining with high-frequency information, close to practical application.
Dynamic characteristics based on vehicle drive system is further analyzed to the result of Wavelet Denoising Method again.Vehicle is incorporated herein
Shift logic and each executive component oil pressure variation diagram in traveling process, as shown in table 3 and Fig. 9.With reference to Figure 10,
In the past, gear is unchanged by 4826s, vehicle smooth-ride, and now gearbox output torque change is gentle, and fluctuation is smaller；In 4826s
To vehicle between 4831s experienced from three gear drop to two gears and two gear be raised to three gears, two processes, it can be seen that gearbox is defeated
It is violent to go out change in torque, fluctuation is larger, meets the change in torque situation in shift process, therefore understood through this analysis, wavelet analysis
Denoising mode can effectively be remained with while noise is removed with high-frequency information, suitable for the denoising of system of vehicle transmission loading spectrum
It is required that.
The gear of table 3 and executive component graph of a relation (part)
Note：О is work
In summary, presently preferred embodiments of the present invention is these are only, is not intended to limit the scope of the present invention.
Within the spirit and principles of the invention, any modification, equivalent substitution and improvements made etc., it should be included in the present invention's
Within protection domain.
Claims (2)
- A kind of 1. engineering machinery actuating signal denoising method based on wavelet analysis, it is characterised in that：By in vehicle travel process Operating mode be divided into idling operation and random operating mode；This method comprises the following steps：Step 1, under idling operation, obtain load data and simultaneously calculate the wavelet coefficient under idling operation on each decomposition scaleWith threshold value λ, with threshold value λ to wavelet coefficientThreshold value quantizing processing is carried out, removes the wavelet coefficient less than threshold value, Retain remaining wavelet coefficient to be designated asUtilize the wavelet coefficient of reservationLoad data under idling operation is entered The one-dimensional wavelet reconstruction of row, completes denoising；Step 2, under random operating mode, obtain load data and simultaneously calculate the wavelet coefficient on each decomposition scaleUtilize step The idling operation lower threshold value λ calculated in 1 is to wavelet coefficientThreshold value quantizing processing is carried out, removes the wavelet systems less than threshold value Number, retains remaining wavelet coefficient and is designated asUtilize the wavelet coefficient of reservationTo the charge number under random operating mode According to one-dimensional wavelet reconstruction is carried out, denoising is completed.
- 2. the engineering machinery actuating signal denoising method based on wavelet analysis as claimed in claim 1, it is characterised in that described Threshold value λ calculating process includes in step 1：Calculate the wavelet coefficient under each decomposition scale<mrow> <msub> <mi>&omega;</mi> <msup> <mn>2</mn> <mi>j</mi> </msup> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <msup> <mn>2</mn> <mrow> <mo>-</mo> <mi>j</mi> <mo>/</mo> <mn>2</mn> </mrow> </msup> <msubsup> <mo>&Integral;</mo> <mrow> <mo>-</mo> <mi>&infin;</mi> </mrow> <mrow> <mo>+</mo> <mi>&infin;</mi> </mrow> </msubsup> <msub> <mi>x</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mi>&psi;</mi> <mo>&lsqb;</mo> <msup> <mn>2</mn> <mrow> <mo>-</mo> <mi>j</mi> </mrow> </msup> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>&rsqb;</mo> <mi>d</mi> <mi>t</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>Wherein, j is Decomposition order, and k is translation parameters, and t represents the time；Calculating noise variance σ：<mrow> <mi>&sigma;</mi> <mo>=</mo> <mi>m</mi> <mi>e</mi> <mi>d</mi> <mi>i</mi> <mi>a</mi> <mi>n</mi> <mo>|</mo> <msub> <mi>&omega;</mi> <msup> <mn>2</mn> <mi>j</mi> </msup> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>,</mo> <msub> <mi>&omega;</mi> <msup> <mn>2</mn> <mi>j</mi> </msup> </msub> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>,</mo> <mn>...</mn> <msub> <mi>&omega;</mi> <msup> <mn>2</mn> <mi>j</mi> </msup> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>/</mo> <mn>0.675</mn> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow>Wherein, the median meaning is to take the intermediate value of the set of wavelet coefficient under each decomposition scale；Finally, each decomposition scale upper threshold value λ is calculated：<mrow> <mi>&lambda;</mi> <mo>=</mo> <mi>&sigma;</mi> <msqrt> <mrow> <mn>2</mn> <mi>ln</mi> <mi>N</mi> </mrow> </msqrt> <mo>/</mo> <mi>l</mi> <mi>n</mi> <mrow> <mo>(</mo> <mi>j</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> </mrow>Wherein, N represents signal sampling points.
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| CN110244148B (en) * | 2019-07-01 | 2021-04-16 | 华南理工大学 | New energy automobile dynamic working condition EMI testing method based on FFT and point frequency scanning |
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| CN111640519B (en) * | 2020-05-07 | 2022-04-05 | 中国工程物理研究院核物理与化学研究所 | Reactor neutron noise spectrum analysis method based on improved wavelet fractal algorithm |
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