JP3500643B2 - Active noise control device - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an active noise control device for reducing noise by causing a control sound generated from a control sound source to interfere with noise transmitted from a noise source,
In particular, by eliminating the influence of noise components other than the noise to be reduced on the noise reduction control, good noise reduction control can be performed.

[0002]

2. Description of the Related Art As a conventional active noise control device, British Patent No. GB2149614 and Japanese Patent Publication No. 1-501344.
There is one described in Japanese Patent Publication. These conventional devices are noise reduction devices applied to, for example, a closed space such as a cabin of an aircraft, and microphones installed at a plurality of positions in such a closed space to detect sound pressure, and the closed space. It is equipped with a plurality of loudspeakers that generate control sounds, detects the noise generation state of the noise source as a reference signal, and executes predetermined arithmetic processing based on the noise in the space detected by the microphone and the reference signal, and then closes it. A signal for driving the loudspeaker is generated so that a control sound having a phase opposite to that of the noise transmitted to the space is emitted.

As a method of generating the drive signal,
In the specification of the above patent, MULTIPLE ERROR FILTERED X LM
S ALGORITHM (S. J. ELLIOTT and others, "A Multip
le Error LMS Algorithm and Its Application to The
Active Control of Sound and Vibration ”, IEEE Tra
ns. Acoust. , Speech, Signal Prosessing, vol, AS
SP-35, pp. 1423-1434, 1987).

A conventional active noise control device other than the above is described in US Pat. No. 4,490,841, which is characterized in that a signal for driving a loudspeaker is generated in the frequency domain.

[0005]

However, in the conventional active noise control device as described above, when a noise component having no correlation with the reference signal is mixed in the microphone, the noise component having no correlation is generated. Due to the influence, a good noise reduction effect cannot be obtained, and the control may become unstable in some cases.

As a conventional solution to such a problem, Japanese Patent Application No. 3-171991 previously proposed by the present applicant.
No. 3, the technique described in Japanese Patent Application No. 3-220684 and R. W. Calculation method proposed by HARRIS and others ("A
Variable Step (VS) Adaptive Filter Algorithm ”,
IEEE Trans. Acoust. , Speech, Signal Prosessing, v
ol. ASSP-34, pp. 309-316, 1986 ”), etc., but none of the technologies considers the frequency domain in particular, so although stabilization of control and shortening of convergence time can be expected, noise that is uncorrelated to the reference signal is identified. When it occurs in the frequency region of, it is not possible to perform the control corresponding only to the specific frequency region.

The present invention has been made by paying attention to the unsolved problems of the prior art as described above, and is excellent even under the condition that noise uncorrelated with the reference signal exists in the control space. An object is to provide an active noise control device capable of noise reduction control.

[0008]

In order to achieve the above object, an active noise control device according to the invention of claim 1 is
A control sound source capable of generating a control sound in a space where the noise is transmitted from the noise source, a noise generation state detecting means for detecting a noise generation state of the noise source and outputting it as a reference signal, and a residual at a predetermined position in the space. Residual noise detection means for detecting noise, active control means for driving the control sound source so as to reduce noise in the space based on the reference signal and the residual noise, and coherence of the reference signal and the residual noise And a processing content adjusting means for adjusting the processing content of the active control means according to the coherence found by the coherence computing means , wherein the active control means is a successive approximation algorithm.
Based on which it will generate a signal to drive the controlled sound source
Therefore, the processing content adjusting means can improve the coherence.
Is involved in the approximation speed of the successive approximation algorithm
The control variables that are set are adjusted .

In order to achieve the above object, the present invention according to claim 2 provides a control sound from a noise source to a space where the noise is transmitted.
The control sound source that can be generated and the noise generation state of the noise source are detected.
Noise generation state detection means for outputting as a reference signal for output,
Residue for detecting residual noise at a predetermined position in the space
Noise detection means based on the reference signal and the residual noise
The control sound source to reduce the noise in the space.
Active control means for driving, the reference signal and the residual
Coherence calculation means for obtaining the coherence of noise,
Depending on the coherence calculated by this coherence calculation means
Adjusting the processing content of the active control means
And means, wherein the processing content adjusting means adjusts the pass characteristic variable filter provided corresponding to each of the pass characteristics of the filter according to the coherence of the reference signal and the residual noise pass Characteristic adjustment means,
Have.

[0010]

According to the first aspect of the present invention, based on the reference signal detected by the noise generation state detection means and the residual noise detected by the residual noise detection means, the active control means detects the noise in the space. Since the control sound source is driven so as to be reduced, the noise transmitted from the noise source to the space is canceled by the control sound emitted from the control sound source, and the noise in the space is reduced.

Then, the coherence computing means finds the coherence between the reference signal and the residual noise. Since the coherence represents the degree of linear dependence of each of the two fluctuation phenomena for each frequency component, the coherence computing means finds the coherence. The coherence represents the degree of linear dependence of each frequency component of the reference signal and the residual noise. Therefore, when the processing content adjusting means adjusts the processing content of the active control means in accordance with the coherence obtained by the coherence computing means, the degree of linear dependence of the reference signal and the residual noise for each frequency component is processed by the active control means. It will be reflected in the content.

[0012] Therefore, as in the invention of claim 1, wherein, when the active control means is configured to generate a signal for driving the control sound source sequentially based on approximation algorithm such as the LMS algorithm, the processing content adjusting means Has a configuration in which the control variable (convergence coefficient in the case of the LMS algorithm) involved in the approximation speed of the successive approximation algorithm is adjusted according to the coherence, the larger the control variable, the more easily the control becomes unstable. , For example, if adjustment is made to reduce the control variable when the coherence is small, the control variable becomes large and the convergence time is shortened in a situation where the level of the noise component that is not correlated with the reference signal is low. In such a situation where the level of the noise component is high, the control variable becomes small and instability of control is avoided. .

According to the second aspect of the present invention, the passage characteristic adjusting means corresponds to each of the reference signal and the residual noise .
In order to adjust the pass characteristic of the filter provided in response to it according to the coherence of the reference signal and the residual noise, for example, if the coherence is used as it is, the signal in the frequency band with a small coherence is taken into the active control means. Therefore, destabilization of control can be avoided.

[0014]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a diagram showing an overall configuration of a first embodiment of the present invention. In this embodiment, a road / wheel is transmitted from a noise source between wheels 2a to 2d into a vehicle interior 6 as a space.
The present invention is applied to an active noise control device 1 for reducing noise.

First, the structure will be described. The vehicle body 3 is supported by front wheels 2a, 2b, rear wheels 2c, 2d and suspensions (not shown) interposed between the wheels 2a-2d and the vehicle body 3. . Acceleration sensors 5a, 5b, 5c and 5 as noise generation state detecting means are provided on the suspensions interposed between the wheels 2a to 2d and the vehicle body 3, respectively.
Loaded from the road surface with d attached
Reference signal x _k (k = which is an acceleration signal corresponding to noise)
1 to k _n: k _n is a number of acceleration sensors 5a to 5d, in this embodiment, a k _n = 4. ) Is supplied to the controller 10.

In the vehicle interior 6 as a space inside the vehicle body 3, loudspeakers 7a, 7b, 7c as control sound sources are provided.
And 7d are front seats S ₁ , S ₂ and rear seats S ₃ , S
It is arranged in the door section facing each of the _four . In addition, the head restraint position of the seat S ₁ to S _4, and a microphone 8a~8h as residual noise detecting means, are respectively disposed two by two, these microphones 8
The residual noise signal e _l (l = l = 8 to 8h) is measured as the sound pressure.
1 to L: L is the number of microphones 8a to 8h, and in the present embodiment, L = 8. ) Is supplied to the controller 10.

The controller 10 is composed of necessary interface circuits, a microprocessor, etc., and has a reference signal x _k supplied from the acceleration sensors 5a to 5d,
Based on the residual noise signal e _l supplied from the microphones 8a to 8h, the arithmetic processing described later is executed to
The drive signals y _m (m = 1) are applied to the loudspeakers 7a to 7d so that control sounds for canceling the road noise transmitted therein are emitted from the loudspeakers 7a to 7d.
~ M: M is the number of loudspeakers 7a to 7d,
In this embodiment, M = 4. ) Is output.

In the present embodiment, the arithmetic processing in the controller 10 is an LMS algorithm (more specifically, a Filter) which is one of successive approximation algorithms.
2 is a block diagram showing a functional configuration of the controller 10 based on the red-X LMS algorithm).
As shown in FIG.
a to 7d and microphones 8a to 8h, which correspond to the number of L × M digital filters C _lm that model the transfer function between finite impulse response functions, acceleration sensors 5a to 5d, and loudspeakers 7a to 7d. k _n × M
A number of adaptive digital filters W _km with variable filter coefficients, convolution of the reference signal x _k and the adaptive digital filter W _km , and the convolution results of the loudspeakers 7a to 7d (that is, subscript m). Each of them is added to generate a drive signal y _m , which is output.

Further, the controller 10 responds to the processed signal r _klm generated by convolving the digital filter C _lm and the reference signal x _k and the residual noise signal e _l supplied from the microprocessors 8a to 8h. A filter coefficient updating unit 11 is provided for updating each filter coefficient W _kmi of the adaptive digital filter W _km based on the LMS algorithm so that the road noise transmitted to the vehicle interior 6 is reduced.

Explaining the LMS algorithm, the residual noise signal detected by the l-th microphone is e _l (n), and the residual noise detected by the l-th microphone when no control sound is generated from the loudspeaker. The signal is d _l (n), the filter coefficient of the j-th digital filter C _lm (j = 0, 1, 2, ..., J-1: J is the number of taps of the digital filter C _lm ) is C _lmj , and the reference signal is the reference signal. x _k (n), the adaptive digital filter W for driving the m-th loudspeaker to which the reference signal x _k (n) is input
The filter coefficient of the i-th _km (i = 0, 1, 2, ..., I-1: I is the number of taps of the adaptive digital filter W _km ) is W.
_kmi , Is established.

The terms with (n) are all sumps.
The sample value at the ring time n is shown. Formula (1) above
"ΣΣW" in the middle and right side_kmix_kThe term “(n−j−i)” is appropriate.
Reference signal x to digital filter_kM when you input
Output y to the th loudspeaker _miIs represented as “ΣC_lmj
{ΣΣW_kmix_k(N−j−i)} ”is the m-th
Signal y input to the loudspeaker_miFrom there is a control sound
Then output to space and transfer function C_lmThrough the l-th microphone
It shows the signal when it reaches the ruffon, and
_lmj{ΣΣW_kmix_k(N−j−i)} ”is the l-th item
Are the signals reaching the microphones of
The sum of control sounds reaching the l-th microphone
It represents.

Next, the evaluation function Je is And

Then, the LMS algorithm finds the filter coefficient W _kmi that minimizes the evaluation function Je. Specifically, the evaluation function Je is calculated for each filter coefficient W _kmi.
The filter coefficient W _kmi is updated with the value obtained by partial differentiation. Therefore, from equation (2) above, From equation (1) above, Therefore, if the right side of the equation (4) is set to r _klm (n−i), the update of the filter coefficient is as shown in the following equation (5).

[0024] That is, the filter coefficient updating unit 11 _calculates the filter coefficient W of the adaptive digital filter W _km based on the above equation (5).
Update _kmi sequentially.

The coefficient α in the above equation (5) is LMS
It is a convergence coefficient as a control variable related to the approximate speed of the algorithm. Furthermore, the controller 10 appropriately sets the processing content of the filter coefficient updating unit 11 according to the calculation result of the coherence calculation unit 12 that calculates the coherence of the reference signal x _k and the residual noise signal e _l and the coherence calculation unit 12. And a processing content adjusting unit for adjusting.

Here, coherence gives a measure of the degree of linear dependence between two signals as a function of frequency, the frequency f between the two signals x _k (n) and e _l (n). The coherence γ ² (f) in the respective auto spectra S _xx and S _ee and the cross spectrum S _xe
Can be calculated based on the following equation (6). γ ² (f) = | S _xe (f) | ² / {S _xx (f) S _ee (f)} (6) Then, the auto spectra S _xx and S _ee and the cross spectrum S _xe are It can be calculated from the Fourier transforms X _k (f) and E _l (f) of the reference signal x _k (n) and the residual noise signal e _l (n) based on the following equations (7) to (9).

[0027]   S_xx(F) = X_k ^*(F) X_k(F) …… (7)   S_ee(F) = E_l ^*(F) E_l(F) …… (8)   S_xe(F) = X_k ^*(F) E_l(F) …… (9) In addition, "^*"Indicates a complex conjugate. Equation (6) above
Reference signal x obtained by measurement_k(N) and residual noise signal e
_lWhen calculated by (n), the above (7) to (9)
Coherence γ²(F) = 1.

However, the coherence γ ² (f) is calculated from the auto spectra S _xx , S _ee and the cross spectrum S _xe obtained by measuring the reference signal x _k (n) and the residual noise signal e _l (n) a plurality of times and averaging them. Is calculated, the coherence γ ² (f) <1 is normally obtained due to the uncorrelated components between the reference signal x _k (n) and the residual noise signal e _l (n). Now
Let E be represented as E = HX + Y by some frequency response functions H, X and a component Y that is uncorrelated with X. In addition,
In order to simplify the description, the frequency parameter f is omitted.

At this time, the auto spectrum S _ee and the cross spectrum S _xe are expressed by the following equations (10) and (11), respectively. ^{_{S ee = E * E = (}} H * X * + Y *) (HX + Y) = S hh S xx + S yy ...... (10) | S xe | 2 = | X * E | 2 = | X * (HX + Y) | ² = | HS _xx | ² = S _hh S _xx ² (11) Note that S _hh = H ^* H, S _yy = Y ^* Y, and (10) above.
(11) and (11) utilize that X and Y are uncorrelated, that is, S _xy = X ^* Y = 0. At this time, coherence γ
² is γ ² = | S _xe | ² / {S _xx S _ee } = S _hh S _xx ² / {S _xx (S _hh S _xx + S _yy )} = 1 / {1 + S _yy / (S _hh S _xx ). } ... (12), which is always 1 or less. Also, from the above formula (12),
Ratio of component Y that is uncorrelated with X in E S _yy / (S
_It can be seen that the larger _hh S _xx ) is, the smaller the coherence γ ² is.

That is, the coherence γ ² (f) calculated by the coherence calculator 12 in the controller 10 is
It represents the degree of linear dependence between the reference signal x _k (n) and the residual noise signal e _l (n). Then, in the present embodiment, the coherence γ ² (f) is reflected in the process of generating the drive signal y _m , thereby improving the control stability.

Specifically, as shown in FIG. 3, the processing content adjusting unit 13 determines the filter coefficient updating unit 1 according to the coherence γ ² (f) calculated by the coherence calculating unit 12.
When the degree of linear dependence between the reference signal x _k (n) and the residual noise signal e _l (n) is high, the convergence coefficient α (see the equation (5) above) used in 1 is changed. LMS
While the approximation speed of the algorithm is increased to shorten the convergence time, when the degree of linear dependence is low, the approximation speed of the LMS algorithm is decreased to avoid destabilization of control.

The determination of the convergence coefficient α in the processing content adjusting unit 13 is performed according to the following equation (13) in this embodiment. α = α ₀ (1-μ (1- (1 / T) Σβ (f) γ ² (f))) (13) α ₀ is a constant and corresponds to the maximum value of the convergence coefficient α.
Further, μ is a constant selected within the range of 0 <μ <1, and the larger it is, the larger the coherence γ in the convergence coefficient α.
² (f) has a large effect. “Σβ (f) γ
The range of the sum of “ ² (f)” is the range of the frequency component of interest, and β (f) is the weight for each frequency component.

Then, T is the number of frequency components for which the sum is obtained. If T is set so that the sum of β (f) is T,
When the coherence γ ² (f) is all 1, the convergence coefficient α has the maximum value α ₀ . 4 and 5 show the controller 10
6 is a flowchart showing an outline of processing executed in the following, and the operation of the present embodiment will be described below with reference to FIGS. 4 and 5. Note that FIG. 4 corresponds to the processing in the adaptive digital filter W _km , the digital filter C _lm, and the filter coefficient updating unit 11, and FIG. 5 corresponds to the processing in the coherence operation unit 12 and the processing content adjusting unit 13, both of which are It is executed as an interrupt process in synchronization with the sampling clock.

First, the processing of FIG. 4 will be described. In step 101, the reference signal x _k (n) and the residual noise signal e _l (n) at the present time are read, and then step 10
2, the reference signal x _k (n) and the digital filter C _lm are convoluted to calculate the processed signal r _klm (n).
Then, the process proceeds to step 103, and the convergence coefficient α stored in a predetermined storage area is read. It should be noted that this convergence coefficient α is appropriately updated in the process of FIG. 5 described later.

Then, the _{process proceeds} to step 104, the filter coefficient W _kmi is calculated according to the above equation (5) to update the filter coefficient W _kmi of the adaptive digital filter W _km ,
Next, in step 105, the reference signal x _k (n) and the adaptive digital filter W _km are convoluted to generate the drive signal y.
_m is generated, and this drive signal y _m is output to each of the loudspeakers 7a to 7d in step 106.

[0036] Then, the control sound into the passenger compartment 6 from loudspeakers 7a~7d occurs immediately after start of control is limited to the filter coefficient W _KMI of the adaptive digital filter W _miles converges to an optimal value Since it is not present, it cannot be said that the road noise transmitted to the vehicle interior 6 is necessarily reduced.
However, when the process of FIG. 4 is repeatedly executed, each filter coefficient W _kmi of the adaptive digital filter W _km is updated appropriately according to the above equation (5), so that each filter coefficient W _kmi converges toward the optimum value. As a result, the road noise transmitted to the passenger compartment 6 is reduced to loudspeakers 7a to 7a.
It is canceled by the control sound emitted from d, and the noise in the passenger compartment 6 is reduced.

Next, the process shown in FIG. 5 will be described. In step 110, the counter variable N is incremented,
Next, at step 111, the counter variable N is a constant N _0.
If it has not reached the constant N ₀ , the processing after step 112 is not executed and sampling (the processing of step 101 in FIG. 4) is continued. For this constant N ₀ , a power of 2 such as 256 or 1024 is selected. This is because in FFT (Fast Fourier Transform) used for the calculation process of coherence γ ² (f), the number of points that is a power of 2 is usually the calculation target.

When the determination in step 111 is "YES", the process proceeds to step 112, the counter variable N is reset, and then the process proceeds to step 113, where the past N ₀ reference signals x _k (n), x. _k (n-1), ..., _xk (n
-N ₀ +1) and residual noise signals e _l (n), e _l (n-
Based on 1), ..., _El (n-N ₀ +1), the coherence γ ² (f) is calculated according to the equations (7) to (12) described above.

Then, in step 114, the coherence γ ² (f) is averaged, the counter variable P is incremented in step 115, and it is determined in step 116 whether the counter variable P has reached the constant P _0. determined, it does not reach the constant P _0, sampling, calculation and coherence of the coherence ^{γ 2 (f) γ 2 (} f)
The averaging process of is repeatedly executed. The constant P ₀ is 10
It is a value of the degree.

When the determination in step 116 is "YES", the process proceeds to step 117, the counter variable P is reset, the process proceeds to step 118, the convergence coefficient α is calculated based on the equation (13), and the predetermined value is obtained. The convergence coefficient α stored in the storage area of is updated. Since the amount of calculation in the process after step 112 is large, it is not always necessary to complete the calculation within one sampling time.

Now, considering the case where the noise other than the road noise in the passenger compartment 6 is at a relatively low level, since the control sound has not yet been generated immediately after the control is started, the reference signal x
Coherence γ between _k (n) and residual noise e _l (n)
² (f) is almost 1, and the convergence coefficient α is approximately the maximum value α
It becomes ₀ . Therefore, in this situation, the filter coefficient W _kmi of the adaptive digital filter W _km converges to the optimum value relatively quickly.

When the control sounds are generated from the loudspeakers 7a to 7d, the road noise transmitted to the passenger compartment 6 is reduced, and the reference signal x _k (n) in the residual noise e _l (n) is reduced. Since the component having no correlation with becomes relatively large, the coherence γ ² (f) becomes small, and the convergence coefficient α becomes gradually small. Therefore, the filter coefficient W _kmi of the adaptive digital filter W _km does not greatly change, and the control proceeds in a more accurate direction.

On the other hand, noise other than road noise is relatively
At high levels, the coherence is small from the beginning,
Control is unstable because the convergence coefficient α takes a relatively small value.
You can avoid becoming. Here, in this embodiment
Is an adaptive digital filter W_km, Digital filter
C _lm, The filter coefficient updating unit 11 and the processing shown in FIG.
The active control means is configured by the coherence calculation unit 12
And the coherence by the processing of step 113 in FIG.
Computation means is configured, and the processing content adjusting unit 13 and the screen of FIG.
The processing of step 118 constitutes a processing content adjusting means.
Be done.

6 to 8 are views showing a second embodiment of the present invention. Note that this embodiment also applies the active noise control device according to the present invention to a device for reducing road noise transmitted to the interior of a vehicle, as in the first embodiment. The structure is similar to that of the first embodiment. Then, in the present embodiment, as shown in FIG. 6 which is a block diagram showing the functional configuration of the controller 10, the reference signal x _k (n) input to the adaptive digital filter W _km and the digital filter C _lm and the filter coefficient are input. Update unit 11
The bandpass filters 20 and 21 as filters having variable pass characteristics are provided corresponding to the residual noise signals e _l (n) input to the coherence γ ² (calculated by the coherence calculator 12). A bandpass filter design unit 22 is provided for designing and updating the pass characteristics of the bandpass filters 20 and 21 in accordance with f).

The bandpass filter design unit 22 has a coherence γ ² (f) between the reference signal x _k (n) calculated by the coherence calculation unit 12 and the residual noise signal e _l (n).
To design a bandpass filter in which is the pass level of each frequency component. Therefore, the bandpass filter 20 processes the reference signal x _k (n),
By processing the residual noise signal e _l (n) with the filter 21, the component of the frequency band with a small coherence γ ² (f) is not taken in by the process of generating the drive signal y _m .

7 and 8 are implemented in the controller 10.
It is the flowchart which shows the outline of the processing which is done,
FIG. 7 shows an adaptive digital filter W_km, Digital fill
Ta C _lm, The filter coefficient updating unit 11 and the bandpass filter
Corresponding to the processing in the filters 20 and 21, FIG.
To the impedance calculation unit 12 and the bandpass filter design unit 22.
It corresponds to the processing in. In addition, shown in FIG. 7 and FIG.
The processing is the processing shown in FIGS. 4 and 5 in the first embodiment.
The same step number for the same processing content
No., and duplicate description is omitted.

That is, in step 101 of FIG. 7, the reference signal x
_After reading _k (n) and the residual noise signal e _l (n),
In step 201, the reference signal x _k (n) and the residual noise signal e _l (n) are filtered by the bandpass filter designed in the process shown in FIG. Then, in step 102, the processed signal r _klm (n)
_Is calculated, the filter coefficient W _kmi is updated in step 104, the drive signal y _m is calculated in step 105, and the drive signal y _m is output in step 106.

On the other hand, in the processing of FIG.
The processing of 117 is similar to that of the first embodiment, and the processing proceeds from step 117 to step 211 to design a bandpass filter in which the averaged coherence γ ² (f) is used as the pass level of each frequency component. Is. As a method of designing the bandpass filter in step 211, for example, a method using FFT (Fast Fourier Transform) can be applied. Specifically, coherence γ ² (f)
An inverse FFT in the time domain of the amplitude characteristic in which the value of is used as it is and the linear phase characteristic corresponding to half the filter length may be used as a FIR (finite impulse response) filter. For example, sampling clock 1kHz
Assuming that a 100-tap FIR filter is designed for z, a delay of 1/1000 (second) × 100/2 = 50 ms may be used as the phase characteristic at each frequency. Since the filter designed in this way has a delay of a constant time regardless of the frequency, it has the same phase characteristic before and after the pass characteristic is updated, and it is not necessary to adversely affect the subsequent control.

That is, according to the configuration of the present embodiment, the coherence γ is obtained by the filter processing in step 201.
^Since the small frequency component of ² (f) is cut, the processes of steps 102 to 105 are performed only on the basis of the high frequency component of coherence γ ² (f), and stable noise reduction control is executed. Like Further, in the present embodiment, since tuning can be performed in the frequency domain, it is also possible to perform tuning in consideration of the human auditory perception characteristic that the feeling is different for each frequency.

[0050] In here, in this embodiment, is constituted pass characteristic adjustment means by the processing of the bandpass filter design unit 22 and step 211.

FIGS. 9 to 12 are views showing a third embodiment of the present invention. In this embodiment as well, as in the first embodiment, the active noise control device according to the present invention is applied to a vehicle. It is applied to a device that reduces the road noise transmitted to the passenger compartment. That is, in this embodiment, the frequency domain LMS
Control is performed by applying an algorithm.

For details of the frequency domain LMS algorithm, see "R. FERRARA," Fast Implementatio ".
n of LMS Adaptive Filters ”, IEEE Trans.Acous
t. , Speech, Signal Processing, vol. ASSP-28, p
p. 474-475, 1980 ”. When this frequency domain LMS algorithm is applied to the present invention,
The functional configuration of the controller 10 is as shown in FIG.

That is, the controller 10 controls the reference signal x_k
(N) is subjected to fast Fourier transform to obtain a frequency domain reference signal x
_kFourier transform unit 31 for generating (f) and residual noise signal
Issue e _lFast Fourier transform of (n) and residual in frequency domain
Noise signal E_lA Fourier transform unit 32 for generating (f),
Frequency domain drive signal Y_mInverse Fourier transform of (f)
Time domain drive signal y_mAn inverse Fourier transform that produces (n)
And a digital filter C._lmGo around
Filter C expressed in the wavenumber domain_lm(F) and the convergence coefficient α
Is expressed in the frequency domain using the convergence coefficient α (f) and
The sound reduction control is executed.

Then, the processing content adjusting unit 13
Reference signal x calculated by the impedance calculator 12 _k(N) and residual noise
Sound signal e_lCoherence γ between (n)²Based on (f)
Then, the convergence coefficient α (f) at the frequency f is
4) Update according to the formula.   α (f) = α₀(F) (1-μ (f) (1-γ²(F))) (14) 10 to 12 are executed in the controller 10.
It is a flow chart which shows an outline of processing.

That is, in this embodiment, since the algorithm is in the frequency domain, first, the reference signal x _k (n) and the residual noise signal e _l (n) are read in step 301 in FIG. 10, and the counter variable is read in step 302. N is incremented, and the counter variable N is a constant N in step 303.
The processing of step 301 is repeatedly executed until reaching ₀ , and N ₀ reference signals x _k (n) and residual noise signals e _l
Take in (n). The value of the constant N ₀ is a power of 2 for the same reason as described above.

When the determination in step 303 of FIG. 10 is "YES", the counter variable N is reset to zero in step 113, and then the processes of FIGS. 11 and 12 are executed. In step 304 of FIG. 11, the N ₀ reference signals x _k (n) and the residual noise signal e _l (n) are subjected to fast Fourier transform to obtain the frequency domain reference signal X _k (f) and the residual noise signal E _l. (F) is obtained, and then the process proceeds to step 305 to obtain the processed signal R _klm (f) by processing the reference signal X _k (f) with the filter C _lm (f).

Then, in step 306, the convergence coefficient α (f) is read, and in step 307, the filter coefficient W _kmi (f) of the adaptive digital filter W _km (f) represented in the frequency domain is calculated. Update. Then
In step 308, the reference signal X _k (f) is filtered by the adaptive digital filter W _km (f) to calculate the drive signal Y _m (f). Then, in step 309, the drive signal Y _m (f) is subjected to inverse Fourier transform to obtain N ₀ drive signals y _m (n), and in step 310, the drive signal y _m (f) is obtained.
Output _m (n).

Of the processing shown in FIG. 12, steps 113-
The processing of 117 is the same as steps 113 to 117 of FIG. 5 in the first embodiment. And in this embodiment,
From step 117 to step 311, the convergence coefficient α (f) is calculated and updated according to the equation (14) based on the averaged coherence γ ² (f). With such a configuration, each convergence coefficient α (f) becomes large in the frequency band where the coherence γ ² (f) is large, so that the convergence to the optimum value is quick and the frequency where the coherence γ ² (f) is small. Since it becomes smaller in the band, instability of control can be avoided. Further, even in the present embodiment, since tuning can be performed in the frequency domain, it is also possible to perform tuning in consideration of human auditory perception characteristics that, for example, the feeling is different for each frequency.

In this embodiment, the processing content adjusting unit 13 and the processing of step 311 in FIG. 12 constitute processing content adjusting means. In each of the above-described embodiments, the case where the present invention is applied to the active noise control device 1 for reducing the road noise transmitted to the vehicle interior 6 is explained. However, the present invention is not limited to this, and for example, if the crank angle signal of the engine is used as the reference signal, it becomes a device for reducing engine noise, or a device applied to other than the vehicle.

[0060]

As described above, according to the present invention,
Since the coherence between the reference signal indicating the noise generation state and the residual noise is obtained and the processing content of the active control means is updated according to the coherence, the residual noise signal contains a noise component that does not correlate with the reference signal. Even if so, the effect that stable noise reduction control can be performed can be obtained.

[Brief description of drawings]

FIG. 1 is a diagram showing an overall configuration of a first embodiment.

FIG. 2 is a block diagram showing a functional configuration of a controller according to the first embodiment.

FIG. 3 is a block diagram showing details of a functional configuration of a controller according to the first embodiment.

FIG. 4 is a flowchart showing an outline of processing of the first embodiment.

FIG. 5 is a flowchart showing an outline of processing of the first embodiment.

FIG. 6 is a block diagram showing a functional configuration of a controller according to a second embodiment.

FIG. 7 is a flowchart showing an outline of processing of the second embodiment.

FIG. 8 is a flowchart showing an outline of processing of the second embodiment.

FIG. 9 is a block diagram showing a functional configuration of a controller according to a third embodiment.

FIG. 10 is a flowchart showing an outline of the processing of the third embodiment.

FIG. 11 is a flowchart showing an outline of processing of the third embodiment.

FIG. 12 is a flowchart showing an outline of processing of the third embodiment.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 Active noise control device 2a-2d Wheel (noise source) 5a-5d Acceleration sensor (noise generation state detection means) 6 Vehicle compartment (space) 7a-7d Loudspeaker (control sound source) 8a-8h Microphone (residual noise detection means) ) 10 controller 11 filter coefficient updating unit 12 coherence calculating unit (coherence calculating unit) 13 processing content adjusting unit (processing content adjusting unit) 20 and 21 bandpass filter (filter with variable transmission characteristics) 22 bandpass filter designing unit ( Passing characteristic adjusting means)

Claims (2)

(57) [Claims] 1. A control sound source capable of generating a control sound in a space in which noise is transmitted from a noise source, a noise generation state detecting means for detecting a noise generation state of the noise source and outputting it as a reference signal, and in the space. Residual noise detecting means for detecting residual noise at a predetermined position, active control means for driving the control sound source so as to reduce noise in the space based on the reference signal and the residual noise, the reference signal, and The coherence calculation means for obtaining the coherence of the residual noise, and the processing content adjustment means for adjusting the processing content of the active control means in accordance with the coherence obtained by the coherence calculation means , wherein the active control means comprises successive approximation Based on type algorithm
To generate a signal to drive the control sound source.
Ri, the process content adjusting means, before according to the coherence
Control variables related to the approximation speed of the successive approximation algorithm
The active noise control device is characterized by adjusting the number . 2. Control to a space where noise is transmitted from a noise source
Control sound source that can generate sound and noise generation state of the noise source
Noise generation state detection means for detecting noise and outputting it as a reference signal
And detecting residual noise at a predetermined position in the space
The residual noise detection means, the reference signal and the residual noise
Based on the control sound to reduce the noise in the space
An active control means for driving a source, said reference signal and said
Coherence calculation means for obtaining coherence of residual noise
And the coherence calculated by this coherence calculation means
Processing contents for adjusting the processing contents of the active control means according to
Adjusting means, wherein the processing content adjusting means comprises the reference signal and the residual noise.
A variable passage characteristic filter provided for each sound.
And filter, passage of the filter according to the coherence
And a passage characteristic adjusting means for adjusting the characteristic.
Active noise control equipment to symptoms.