CN106849910A - It is applied to the secondary channel Fast Identification Method of Studies on Active Duct Noise control - Google Patents
It is applied to the secondary channel Fast Identification Method of Studies on Active Duct Noise control Download PDFInfo
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- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
- H03H21/00—Adaptive networks
- H03H21/0012—Digital adaptive filters
- H03H21/0043—Adaptive algorithms
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Abstract
The invention discloses the secondary channel Fast Identification Method for being applied to Studies on Active Duct Noise control, the openness feature that the method has for secondary sound channel impulse response in pipeline, ratio thought is introduced in Adaptive Identification algorithm, the step size controlling matrix of use ratio, the size according to power system change assigns its corresponding step factor;The renewal of step-length simultaneously is introduced into variable to weigh distance of the weight coefficient in identification process apart from current optimum weight coefficient, so that for the renewal of step factor provides more preferable foundation using the method for like error signal correction function.Maximum feature of the invention is the performance that improve secondary channel identification system, accelerates identification speed, identification precision is improved, while effectively prevent interference of the operating noise of Studies on Active Duct Noise control system to identification system.
Description
Technical field
The present invention relates to Technique of Active Noise Control field, and in particular to a kind of to be applied to the secondary of Studies on Active Duct Noise control
Level passage Fast Identification Method.
Background technology
Technique of Active Noise Control has good noise reduction to low frequency range noise.The key point of control is by by mistake
The change of difference microphone real-time tracking initial noisc is with dynamic regulation controller parameter.Filtering-X least-mean-square error algorithms
(Filtered-X Least mean square, FXLMS) is control algolithm the most typical, comprising a filter in the algorithm
The signal phasor of ripple-X, it is the convolution of input signal vector and secondary channel impulse response function.Secondary channel
(secondary path) refers to the signal path between secondary sound source to error microphone in system, and it is active for whole
Noise control system has very important influence.Accurate recognition secondary channel model and obtain accurate transmission function be realize
One of key of Active noise control.
Although existing effective secondary channel discrimination method, due to introducing additional noise, causes active noise now
Control process is produced with secondary channel identification process and interfered so that the hydraulic performance decline of whole system.Also have by using 3
Intersect the sef-adapting filter of renewal to avoid interfering between Active control part and secondary channel identification process.But with
Upper way adds additional sef-adapting filter or have ignored the influence of control wave filter and additional noise to recognizing, and algorithm
The control of step-length scope is dfficult to apply to reality.Cut so that computational complexity is increased substantially, produce unnecessary amount of calculation, very
Hardly possible meets actual engineering requirement of real-time.
The content of the invention
Instant invention overcomes the deficiencies in the prior art, there is provided one kind identification speed is fast, identification precision is high, and noise resisting ability
The strong secondary channel Fast Identification Method for being applied to Studies on Active Duct Noise control.
In view of the above mentioned problem of prior art, according to one side disclosed by the invention, the present invention uses following technology
Scheme:
A kind of secondary channel Fast Identification Method for being applied to Studies on Active Duct Noise control, including:
The step size controlling matrix of use ratio, is small in the updating for big weight coefficient assigns big step factor
Weight coefficient assigns small step factor;
And during step iteration incorporated into adaptive targets function, the common quick accurate identification for completing secondary channel is used
In avoiding influence of the Studies on Active Duct Noise control system noise to secondary channel identification system.
In order to the present invention is better achieved, further technical scheme is:
An embodiment of the invention, introduces a step size controlling matrix in the identification process of self adaptation:
K (n)=diag { k0(n),k1(n),…,kM-1(n)}
Wherein, M is the length of wave filter;M values are from 0 to M-1;S (n) is the coefficient of impulse response,ε
Set to avoid initial coefficients from causing algorithm frozen problem when being defined as zero it is minimum on the occasion of.
Another embodiment of the invention, in actual applications α values be typically in the range of between 0 to -0.5.
The present invention can also be:
Another embodiment of the invention, it is very fast to obtain to use larger step factor in the algorithmic statement stage
Convergence rate;Less steady misadjustment is obtained using less step factor after algorithmic statement, using error signal
A new Optimal condition criterion is built with step function and then obtain step change rule:
μ (n)=β τ e (n) X of κ μ (n-1)+4T(n)e(n-1)X(n-1)
Wherein, X (n) is input signal;E (n) is error signal;β is the object function and step-length in traditional identification algorithm
Equilibrium quantity between function, normally close in 1;τ be one it is minimum on the occasion of;κ=1-2 (1- β) τ.
Another embodiment of the invention, by the optimization of the identification process of claim 2,3, obtains self adaptation and distinguishes
Weight coefficient during knowledge is:
Wherein, δ for avoid system dissipate take one it is minimum on the occasion of.
Compared with prior art, one of beneficial effects of the present invention are:
A kind of secondary channel Fast Identification Method for being applied to Studies on Active Duct Noise control of the invention, can be quickly accurate
The transmission function weight coefficient of secondary channel is obtained, Studies on Active Duct Noise control effect is improved.
Brief description of the drawings
For clearer explanation present specification embodiment or technical scheme of the prior art, below will be to embodiment
Or the accompanying drawing to be used needed for the description of prior art is briefly described, it should be apparent that, drawings in the following description are only
It is the reference to some embodiments in present specification, for those skilled in the art, is not paying creative work
In the case of, other accompanying drawings can also be obtained according to these accompanying drawings.
Fig. 1 is the Active noise control theory diagram of secondary channel on-line identification.
Fig. 2 is Studies on Active Duct Noise control principle structural representation.
Fig. 3 is secondary channel Fast Identification Method simulation flow block diagram.
Fig. 4 is secondary channel Fast Identification Method simulation result schematic diagram.
Fig. 5 is that Studies on Active Duct Noise controls secondary channel discrimination method performance comparison schematic diagram.
Fig. 6 is Studies on Active Duct Noise control secondary channel identification actual result schematic diagram.
Fig. 7 is the noise reduction schematic diagram of Studies on Active Duct Noise control.
Specific embodiment
The present invention is described in further detail with reference to embodiment, but embodiments of the present invention not limited to this.
Embodiment 1
As shown in figure 1, accompanying drawing 1 is general secondary channel identification block diagram.Signal source is noise generator, and x (n) is actual
Noise signal, S (z) is unknown secondary acoustic path transfer function, and Sh (z) is the simulation picked out by adaptive algorithm
Secondary acoustic path transfer function, e (n) is residual signals.
According to the least-mean-square error algorithm of self adaptation, weight coefficient is updated to:Sh (n+1)=Sh (n)+μ e (n) X (n)
Wherein, Sh (n+1) is weight coefficient, and X (n) is to the expression matrix to input signal x (n);
In order to improve the Fast Convergent performance of algorithm, to the more new work normalized of weight vector, weight coefficient is updated to:
Wherein, XTThe transposition of representing matrix;
δNLMSFor one minimum on the occasion of preventing in initialization denominator for zero causes the algorithm cannot to run.
Active noise control with pipeline as application background, the impulse response of its secondary channel has openness feature,
Especially when to ensure that system has enough high accuracy using exponent number higher.The thought of ratio is incorporated into Adaptive Identification algorithm
In, keep less steady misadjustment while algorithm the convergence speed is accelerated.A step-length control is introduced in adaptive process
Matrix K (n) processed, is that each weight coefficient assigns different step-lengths.
K (n)=diag { k0(n),k1(n),…,kM-1(n)}
M is the exponent number (length of wave filter) of secondary channel;M values are from 0 to M-1;S (n) is the coefficient (power of impulse response
Coefficient),ε is minimum for avoid initial coefficients from causing that algorithm frozen problem sets when being defined as zero
On the occasion of value is typically in the range of between 0 to -0.5 in actual applications.Influence in order to avoid interference noise to steady-state behaviour, step
The method that renewal long uses like error signal correction function.Using error signal and step function build one it is new optimal
Criterion and then obtain step change rule.
J (n)=β e2(n)+(1-β)μ2(n-1)
Above formula the right Section 2 is that β is the equilibrium between two to ensure step change stabilization.Using steepest descent method,
Step-length is obtained to be updated to:
μ (n)=β τ e (n) X of κ μ (n-1)+4T(n)e(n-1)X(n-1)
κ=1-2 (1- β) τ, value is between 0 to 1.
Step-length more new formula access term is hoped, is obtained
E [μ (n)]=κ E [μ (n-1)]+4 β τ E [e (n) e (n-1)] E [XT(n)X(n-1)]
Assuming that the interference noise in adaptive process is ξ (n), optimum weight coefficient is Sh* (n), then desired signal is expressed as:
D (n)=XT(n)Sh*(n)+ξ(n)
With reference to the calculation of error signal, can obtain
E [e (n) e (n-1)]=E [VT(n)X(n)XT(n)V(n)]
Wherein V (n)=Sh (n)-Sh*N (), this variable has weighed the current optimal power of weight coefficient distance in adaptive process
The distance of coefficient.The purpose that this variable is introduced into step-length renewal function is the optimal step size in seeking convergence process.It is most important
Be to have eliminated interference noise ξ (n) in above-mentioned calculating, effectively increase the anti-noise jamming ability of whole system.
Foregoing description is summarized, the weight coefficient during secondary channel Adaptive Identification is updated to:
Embodiment 2
Studies on Active Duct Noise control principle is as shown in Fig. 2 the identification of secondary channel employs the mode of line modeling.It is secondary
The specific path of passage is the complete physical path between sub-loudspeaker to error microphone, there is sound field, electro-acoustic element, electronics
The part of circuit three constitutes.
Sub-loudspeaker is small with the distance between error microphone, can effectively reduce the calculating in Studies on Active Duct Noise control
Amount.But when Practical Project is implemented, this distance can all be subject to larger limitation.
Assuming that secondary channel is linear in Studies on Active Duct Noise control, its transmission function can use finite impulse response
(FIR) represent.By the sound field in duct sound propagation direction be treated simply as spread sound field, its channel modeling filter length will with adopt
Sample frequency, reverberation time are relevant.
Secondary channel modeling filter order is higher, and Active noise control effect is better, but the amount of calculation brought simultaneously
Bigger, the requirement to real-time is also higher.
In the practical application of Studies on Active Duct Noise control, the impulse response of secondary channel has openness structure special
Levy.For this feature, the method for adoption rate can also meet when ensure that secondary channel modeling filter order is higher should
With requirement of real-time, while steady output rate performance also has certain improvement.
In the application of Studies on Active Duct Noise control, the acoustical signal (such as secondary noise) in control process is come for identification process
Say it is noise, the white noise sent by noise generator in identification process is also noise for control process.This noise
The main renewal that have impact on weight coefficient in adaptive process.
Using the method for like error signal correction function, using error signal and step function build one it is new optimal
Criterion and then step change rule is obtained so as to avoid mutual noise jamming between system.
Below to the tool of the method by taking the Studies on Active Duct Noise control secondary channel identification that a certain internal diameter is 200 millimeters as an example
Body implementation method elaborates.
The secondary channel actual range constituted between sub-loudspeaker and error microphone is 60 centimetres, selects finite impulse
Response filter is 512 ranks as secondary channel modeling wave filter, exponent number, and secondary channel modeling wave filter is given tacit consent under original state
Each level number is zero.
As shown in Figure 3, the secondary channel discrimination method is according to following steps:
Step 1, input signal initialization, step size controlling matrix initialisation, secondary channel transmission function initialization, it is determined that power
Each term coefficient needed for coefficient update.
Step 2, the excitation input signal of secondary channel is white noise, is generated by the random noise generator in accompanying drawing 1.Should
White noise is uncorrelated to the primary noise in control system, for fully exciting each frequency response in secondary channel, and its sound
Energy is unlikely to cause excessive interference to the output of actual sub-loudspeaker.The acoustical signal that sub-loudspeaker sends is used as identification
Input signal x (n) of system.
Input signal vector X (n)=[x (n), x (n-1) ..., x (n-M+1)], equation right-hand member represents list entries, input
Signal x (n) is input into by sequence left end successively, and right-hand member is deleted.
Step 3, weight coefficient Sh (n) of the secondary channel according to obtained by the last time updates, with reference to step size controlling matrix:
K (n)=diag { k0(n),k1(n),…,kM-1(n)}
Calculate the step-length corresponding to each rank weight coefficient.
Step 4, in described secondary channel identification system, input signal x (n) for receiving is filtered with secondary channel modeling
Each level number of ripple device does the result of convolution as output signal.
Output signal makees difference gained as error signal e (n) with the signal of error microphone collection.
Step 5, resulting step function μ (n-1) is updated using error signal e (n) with last, is substituted into
J (n)=β e2(n)+(1-β)μ2(n-1)
Use steepest descent method
Arrangement obtains new step function
μ (n)=β τ e (n) X of κ μ (n-1)+4T(n)e(n-1)X(n-1)
Secondary channel modeling wave filter weight coefficient it is not converged to optimal value when, error signal e (n-1) is larger, step-length letter
Number equation right-hand member Section 2 is accordingly larger, and weight coefficient is with fast speed convergence optimal value, it is meant that identification speed is fast;It is logical in secondary
Road modeling wave filter weight coefficient is approached when converging on optimal value, and error signal e (n-1) is smaller, step function equation right-hand member second
Item is corresponding smaller, and weight coefficient fluctuates also smaller near optimal value, it is meant that identification precision is high.
Brought into obtained as above
The identification that secondary channel modeling wave filter successively can be completed updates.
Contrasted using identification algorithm proposed by the invention and traditional algorithm.Accompanying drawing 4 is comparing result, can be seen
Go out:For the secondary channel identification that Studies on Active Duct Noise is controlled, the identification result of 3 kinds of methods is substantially all the reality with secondary channel
Border impulse response coincide.But the position changed greatly in impulse response coefficient, the goodness of fit of method proposed by the invention is better than it
His two methods.It is therefore contemplated that IPNLMS algorithms more can accurately pick out actual secondary sound passage.
To further illustrate superiority of the method proposed by the invention in secondary channel identification, to the speed, the essence that recognize
Degree have also been made contrast.As shown in Figure 5, it can be seen that the effective quickening identification speed of method energy proposed by the invention,
Improve identification precision.
Effect of the further description method proposed by the invention in Studies on Active Duct Noise control practical application, uses
Constructional device carries out Studies on Active Duct Noise Control experiment as shown in Figure 2, as a result as shown in Figure 7.
To sum up, the step size controlling matrix of use ratio of the present invention, in the updating for big weight coefficient assigns big step-length
The factor, is that small weight coefficient assigns small step factor (μ (n)=β τ e (n) X of κ μ (n-1)+4T(n)e(n-1)X(n-1));With
And step iteration is incorporated into adaptive targets functionIn, it is common to complete
The quick accurate identification of secondary channel, for avoiding Studies on Active Duct Noise control system noise to the shadow of secondary channel identification system
Ring.
Each embodiment is described by the way of progressive in this specification, and what each embodiment was stressed is and other
The difference of embodiment, identical similar portion cross-reference between each embodiment.
" one embodiment ", " another embodiment ", " embodiment " for being spoken of in this manual, etc., refer to knot
Specific features, structure or the feature for closing embodiment description are included at least one embodiment of the application generality description
In.It is not necessarily to refer to same embodiment that statement of the same race occur in multiple places in the description.Furthermore, it is understood that with reference to appoint
When one embodiment describes specific features, structure or a feature, what is advocated is this to realize with reference to other embodiment
Feature, structure or feature also fall within the scope of the present invention.
Although reference be made herein to invention has been described for multiple explanatory embodiments of the invention, however, it is to be understood that
Those skilled in the art can be designed that a lot of other modification and implementation methods, and these modifications and implementation method will fall in this Shen
Please be within disclosed spirit and spirit.More specifically, in the range of disclosure and claim, can be to master
The building block and/or layout for inscribing composite configuration carry out various variations and modifications.Except what is carried out to building block and/or layout
Outside variations and modifications, to those skilled in the art, other purposes also will be apparent.
Claims (5)
1. it is a kind of to be applied to the secondary channel Fast Identification Method that Studies on Active Duct Noise is controlled, it is characterised in that including:
The step size controlling matrix of use ratio, is small power system in the updating for big weight coefficient assigns big step factor
Number assigns small step factor;
And during step iteration incorporated into adaptive targets function, the common quick accurate identification for completing secondary channel, for keeping away
Exempt from influence of the Studies on Active Duct Noise control system noise to secondary channel identification system.
2. it is according to claim 1 to be applied to the secondary channel Fast Identification Method that Studies on Active Duct Noise is controlled, its feature
It is that a step size controlling matrix is introduced in the identification process of self adaptation:
K (n)=diag { k0(n),k1(n),…,kM-1(n)}
Wherein, M is the length of wave filter;M values are from 0 to M-1;S (n) is the coefficient of impulse response,ε
Set to avoid initial coefficients from causing algorithm frozen problem when being defined as zero it is minimum on the occasion of.
3. it is according to claim 2 to be applied to the secondary channel Fast Identification Method that Studies on Active Duct Noise is controlled, its feature
It is that α values are typically in the range of between 0 to -0.5 in actual applications.
4. it is according to claim 2 to be applied to the secondary channel Fast Identification Method that Studies on Active Duct Noise is controlled, its feature
It is to use larger step factor to obtain convergence rate faster in the algorithmic statement stage;Using smaller after algorithmic statement
Step factor to obtain less steady misadjustment, build a new Optimal condition using error signal and step function accurate
Then and then obtain step change rule:
μ (n)=β τ e (n) X of κ μ (n-1)+4T(n)e(n-1)X(n-1)
Wherein, X (n) is input signal;E (n) is error signal;β is the object function and step function in traditional identification algorithm
Between equilibrium quantity, normally close in 1;τ be one it is minimum on the occasion of;κ=1-2 (1- β) τ.
5. it is according to claim 1 to be applied to the secondary channel Fast Identification Method that Studies on Active Duct Noise is controlled, its feature
It is that, by the optimization of the identification process of claim 2,3, obtaining the weight coefficient during Adaptive Identification is:
Wherein, δ for avoid system dissipate take one it is minimum on the occasion of.
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CN116127266A (en) * | 2022-12-28 | 2023-05-16 | 宿迁学院 | Secondary coefficient sparse method based on maximum inter-class variance |
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