JPH0540481A - Active type noise controller - Google Patents

Abstract

PURPOSE:To self-diagnose whether model space transfer function of the active type noise controller is proper or not. CONSTITUTION:At the time of self-diagnosis, a sweep sine wave signal generated by a sweep generator 8 is supplied to loudspeakers 5a, 5b. Therefore the sweep sine wave signal propagated through a space of a real space transfer function Ckm is detected by microphones 6a-6c, this detecting signal ek and the sweep sine wave signal generated by the sweep generator 8 are inputted to a microcomputer 26, and by this microcomputer 26, the sweep sine wave signal is processed by a digital filter in which a model space transfer function Ckm' obtained by modeling a real space transfer function, a sweep sine wave filter signal rk corresponding to the detecting signal ek is calculated, and an amplitude difference DELTADk and a phase difference DELTAthetak of the detecting signal ek and the sweep sine wave filter signal rk are calculated. When one of them exceeds an amplitude threshold DELTADT or a phase threshold DELTAthetaT set in advance, it is self-diagnosed that the model transfer function is unsuitable.

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 suppressing noise by interfering noise from a noise source with a noise suppression signal generated by a control sound source, and more particularly to a spatial transfer function and the spatial transfer function. The present invention relates to an active noise control device capable of self-diagnosing a system abnormality due to a deviation of a modeled space transfer function.

[0002]

2. Description of the Related Art Conventionally, as this type of active noise control device, for example, there is one disclosed in Japanese Patent Application Publication No. 1-501344. This conventional example is an active noise control device that reduces a noise transmitted from a noise source into a vehicle compartment by emitting a control sound from a loudspeaker. The residual noise in the vehicle compartment is detected by a plurality of microphones. And adaptively filtering the reference signal by generating at least one reference signal containing arbitrarily selectable harmonics of the noise source and supplying the residual noise detection signal and the reference signal to a processor / storage unit. Then, the drive signal of the loudspeaker is formed. Here, in the adaptive filter processing, the i-th filter coefficient W _mi (n + 1) is set to minimize the evaluation function J set as the sum of mean squares of the detection signals V _ek of the plurality of microphones according to the LMS algorithm. In addition, the update is performed sequentially according to the following equation (1).

[0003] Here, W _mi (n) is the filter coefficient at the previous time, that is, the n-th sample, μ is the convergence coefficient, V _ek is the k-th microphone output, x is the reference signal correlated to the noise source, and C _km is m.
Is the real space transfer function between the th speaker and the kth microphone.

[0004]

However, in the above-mentioned conventional active noise control device, the actual spatial transfer function C _km itself between the loudspeaker and the microphone is controlled by the control algorithm for updating the filter coefficient of the adaptive filter. Instead of using a model space transfer function C _km ′ that models this,
When the actual transfer function changes due to the deterioration of the microphone, the temperature change of the closed space, the opening and closing of the door, etc., the filter coefficient W _{mi of the} adaptive filter calculated by the above formula (1).
An error occurs in (n + 1) and the evaluation function J diverges without converging,
There is an unsolved problem that abnormal noise may occur.

Therefore, the present invention has been made by paying attention to the unsolved problem of the above-mentioned conventional example, and by using a sine wave signal, an actual spatial transfer function and a modeling space obtained by modeling the actual spatial transfer function. It is an object of the present invention to provide an active noise control device capable of detecting a shift in transfer function and performing self-diagnosis.

[0006]

In order to achieve the above object, an active noise control device according to a first aspect of the present invention, as shown in FIG. 1, responds to a noise generation state of a noise source from a reference signal generating means. The reference sound signal is input to the control sound source through the adaptive filter means, the combined sound pressure of the sound pressure sent from the control sound source and the ambient noise sound pressure is detected by the residual noise detecting means, and the reference signal is controlled. Based on the residual noise detection signal and the signal filtered by the filter means having the model space transfer function as a filter coefficient, which models the spatial transfer function between the sound source and the residual noise detection means, the adaptive coefficient of the adaptive filter is updated by the filter coefficient updating means. In an active noise control device in which a filter coefficient is updated by using a steepest descent method, a swept sine wave signal is supplied to the control sound source and filter means instead of the reference signal. Determination of whether the model space transfer function of the filter means is appropriate by comparing the sweep sine wave signal detected by the residual noise detection means with the sweep sine wave signal filtered by the filter means And means are provided.

Further, as shown in FIG. 2, the active noise control device according to the second aspect of the present invention controls the reference sound source from the reference signal generating means to the control sound source through the adaptive filter means according to the noise generation state of the noise source. The residual noise detection means detects the combined sound pressure of the sound pressure transmitted from the control sound source and the ambient noise sound pressure, and the reference signal is used to determine the spatial transfer function between the control sound source and the residual noise detection means. The filter coefficient updating means updates the filter coefficient of the adaptive filter by the steepest descent method based on the signal filtered by the filter means having the modeled model space transfer function as the filter coefficient and the residual noise detection signal. In the active noise control device described above, a sweep signal supply means for supplying a sweep sine wave signal to the control sound source and the filter means instead of the reference signal,
Judgment means for comparing the swept sine wave signal detected by the residual noise detection means with the swept sine wave signal filtered by the filter means to judge the suitability of the model space transfer function of the filter means, and the judgment means. And an identifying means for identifying the filter coefficient when the model space transfer function is judged to be proper and there is a deviation between the model space transfer function and the real space transfer function.

Here, as the judgment means, is the amplitude difference or the phase difference between the swept sine wave signal detected by the residual noise detection means and the swept sine wave signal filtered by the filter section equal to or greater than a preset threshold value? It is desirable to judge the suitability of the model space transfer function depending on whether or not it is. Further, as the identification means, reidentification is performed when the phase difference and the gain difference between the swept sine wave signal detected by the residual noise detection means and the swept sine wave signal filtered by the filter unit are within preset ranges, respectively. It is desirable to do.

[0009]

In the active noise control device according to the present invention, the sweep signal supplying means supplies the sweep sine wave signal to the control sound source and the filter means in place of the reference signal, and the judging means detects the residual signal. By comparing the swept sine wave signal containing the real space transfer function between the actual control sound source detected by the means and the residual noise detection means with the swept sine wave signal containing the model space transfer function filtered by the filtering means When there is an amplitude difference or phase difference equal to or greater than the preset amplitude threshold value or phase threshold value between both sine wave signals, self-diagnosis is performed to determine that the abnormality is due to the deviation of the model space transfer function and the real space transfer.

In the active noise control device according to the second aspect of the invention, in addition to the above-mentioned action, when it is judged to be appropriate by the judging means and the model space transfer function and the real space transfer function are deviated. By identifying the model space transfer function by the identifying means, the deviation between the two is eliminated.

[0011]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 3 is a schematic configuration diagram showing an embodiment in which the present invention is applied to a vehicle. In FIG. 3, reference numeral 1 denotes a vehicle body, and a four-cylinder engine 3 as a noise source is provided in front of the passenger compartment 2.
Are arranged. A front seat 4F and a rear seat 4R are arranged in the passenger compartment 2, and, for example, a loudspeaker that also serves as a control sound source that outputs an audio signal as a control sound source to the lower part of the dashboard and the rear side of the rear seat 4R. Speakers 5a and 5b are provided, and microphones 6a, 6b and 6c as residual noise detecting means are provided at the front, center and rear of the ceiling, respectively.

A crank angle sensor 7 is attached to the engine 3, and a noise generation state detection signal X which is a sine wave signal for one cycle is output from the crank angle sensor 7 each time the crankshaft rotates 180 degrees. It Further, the vehicle generates a sine wave signal for self-diagnosis by a sweep generator 8 generated by a control signal CB from a controller 15 described later, and white noise for identification is similarly generated by a control signal CC from the controller 15. A white noise generator 9 and a self-diagnosis switch 10 for starting self-diagnosis are installed.

Then, the microphones 6a to 6c are output.
Forced residual noise detection signal e₁~ E ₃Is the controller 1
5 and the detection signal of the crank angle sensor 7
X, sine wave signal of sweep generator 8, white
White noise of noise generator 9 and self-diagnosis switch
The switch signal of 10 is also input to the controller 15.

The controller 15 is, as shown in FIG.
A / D for A / D converting the input reference signal X and outputting
A conversion circuit 21, an amplifier 22a~22c for amplifying the residual noise detecting signals e ₁ to e ₃ microphones 6a~6c
And A / D conversion circuits 23a to 23c for A / D converting and outputting the amplified outputs of these amplifiers 22a to 22c, and an A / D conversion circuit for A / D converting the sine wave signal of the sweep generator 8. 24 and white noise generator 9
A / D conversion circuit 25 for A / D converting and outputting the white noise, and A / D conversion circuits 21, 23a to 23c,
The microcomputer 26 to which the converted outputs of 24 and 25 and the switch signal of the self-diagnosis switch 10 are input, and the drive signals y _{1 and} y ₂ of the loudspeakers 5a and 5b output from the microcomputer 26 are D / A converted. D / A conversion circuits 27a and 27b for outputting
The outputs of the conversion circuits 27a and 27b, the sine wave signal of the sweep generator 8 and the white noise of the white noise generator 9 are input, and these are input to the microcomputer 2
The analog multiplexers 28a and 28b selected by the control signal CA from 6 and the amplifier 29 which amplifies the analog signals output from the analog multiplexers 28a and 28b and supplies the amplified analog signals to the loudspeakers 5a and 5b.
a and 29b, and a display device 30 configured to display the display data output from the microcomputer 26, which is composed of, for example, a liquid crystal display.

Here, the microcomputer 26 is
And the filter coefficient W that is sequentially updated _miBased on the standard
The convolution operation of No. X is performed and the loudspeakers 5a, 5
drive signal y for b_1,y₂Adaptive digital to calculate
Filtering and microphone and microphone based on reference signal X
Model and the number of spatial transfer function combinations between speakers.
Filter coefficients corresponding to the model space transfer function
Filtered reference signal r_km(Equations (6) and (7) described later
Digital filtering to generate
Filtered reference signal r_kmAnd residual noise detection signal e₁ ~
e₃Based on
Filter coefficient W_miLMS (Least Mean Square) algorithm
And update the filter coefficient
And turn on the self-diagnosis switch 10
Self-diagnosis process and identification process if necessary
To do.

Here, the control principle of the microcomputer 26 will be described using a general formula. Now, the residual noise detecting signals the k-th microphone 6a~6c detects e _k
(n), the k-th microphone 6a to 6c when there is no control sound (secondary sound) from the loudspeakers 5a and 5b
Represents the residual noise detection signal detected by e _pt (n), and the transfer function H _km between the mth loudspeakers 5a and 5b and the kth microphones 6a to 6c is represented by a FIR (finite impulse response) function. J-th (j = 0, 1,
2, ──I _{c -} a first filter coefficient corresponding to the section) C
_kmj ', the reference signal is X (n), and the i-th (i = 0,1,2, -I) of the adaptive digital filter for inputting the reference signal X (n) to drive the m-th loudspeakers 5a and 5b
_When the coefficient of _F −1) is W _mi , the following equation (2) is established.

[0017] Here, the terms with (n) are all sample values at the sampling time n, and K is the microphone 6
a to 6c (three in this embodiment), M is the number of loudspeakers 5a and 5b (two in this embodiment), and I _C is FI.
Filter coefficient C _km ′ represented by R digital filter
Is the tap number (filter order) of I _F , and I _F is the tap number (filter order) of the filter coefficient W _mi represented by the adaptive digital filter.

[{ΣW on the right side of the above equation (2)]_mi・ X (n-j
-i)} ”(= y_m), The reference signal X is an adaptive digit
Is the output when the filter processing is performed._kmj・
{ΣW _mi"X (n-j-i)}" is the m-th speaker 5
The signal energy input to a and 5b is generated by these speakers.
Output as acoustic energy from 5a and 5b,
Spatial transfer function C of_kmVia the k-th microphone 6
a represents the signal when reaching a to 6c, and
_kmj・ {ΣW_mi.. (X (n-j-i)} ”, the entire second term on the right-hand side is
All the arrival signals to the kth microphones 6a to 6c
Since the speakers are added together, the k-th
Shows the total sum of secondary sounds that reach the icrophones 6a-6c
You

Next, the evaluation function J is set as in the following equation (3).

[0020] Then, in the present embodiment, the LMS algorithm is adopted to obtain the filter coefficient W _mi that minimizes the evaluation function J,
Each filter coefficient W _mi of the adaptive digital filter processing is updated. The LMS algorithm, which is the steepest descent method, uses the n-th value W _mi (n) as the filter coefficient of the adaptive digital filtering process, calculates the mean square error gradient ∂J / ∂W _mi, and multiplies this by α. (N + 1) th value W _mi (n + 1)
Is calculated and the calculation is executed so as to reduce the value of the evaluation function J.

The calculation formula of this gradient ∂J / ∂W _mi is

[0022] And from the above equation (2),

[0023] Therefore,

[0024] Where the right side of equation (5) is

[0025] Then, the gradient of the evaluation function with respect to the filter coefficient ∂J /
∂W _mi is

[0026] Can be expressed as

Therefore, the updating formula of the filter coefficient is given by the following formula (9) including the weighting coefficient γ _k .

[0028] Here, α is a convergence coefficient, and is involved in the speed at which the adaptive digital filter processing converges optimally and the stability at that time.

As described above, the filter coefficient W _mi (n + 1) in the adaptive digital filter processing is set to the microphone 6
residual noise detection signals e ₁ (n) to e output from a to 6c
₃ (n) and the reference signal X (n) from the crank angle sensor 7 are sequentially updated according to the LMS algorithm to minimize the input residual noise detection signals e ₁ (n) to e ₃ (n). Drive signals y ₁ (n) and y ₂ (n) are formed, are supplied to the loudspeakers 5a and 5b, and the control sound output from the loudspeakers 5a and 5b cancels the noise in the vehicle interior 2.

Next, the operation of the above embodiment will be described with reference to the flowchart of FIG. 5 showing the processing procedure of the microcomputer 26. In the entire system, when the key switch is turned on, the power is turned on and the microcomputer 26 executes the timer interrupt process shown in FIG. 5 every predetermined time (for example, 1 msec). It should be noted that the control signal CA is generated by the initialization processing by the main program when the power is turned on.
Is set to "00" so that the analog multiplexers 28a and 28b cause the microcomputer 26 to
The drive signals y _{1 and} y ₂ output from are selected.

That is, in step S1, it is determined whether or not the self-diagnosis mode is set. This determination is made based on whether or not the self-diagnosis switch 10 arranged near the driver's seat is in the ON state. When the self-diagnosis switch 10 is in the OFF state, the process proceeds to step S2 and the normal noise shown in FIG. When the suppression control process is executed and the self-diagnosis switch 10 is in the ON state, the process proceeds to step S3 and the self-diagnosis process shown in FIG. 7 is executed.

The normal noise suppression control process is as shown in FIG.
First, in step S21, the residual noise detection signal e₁~ E₃
And reference signal X (n) are read, and then step S22 is performed.
Then, the digital filter processing corresponding to the equation (7) is transferred.
And the filtered reference signal r_kmAnd calculate
Then, the filter processing calculated in step S23 is performed.
Processed reference signal r_kmAnd residual noise detection signal e₁~ E₃When
The filter coefficient update processing according to the above equation (9)
Go to filter coefficient W_miCalculate (n + 1), then step
Filter coefficient W calculated after shifting to step S24_mi(n + 1)
The adaptive digital filter processing based on
Drive signal y for the speakers 5a and 5b _1,y₂Calculate
Drive signal calculated by moving to step S25
y_1,y₂Is output to the D / A conversion circuits 27a and 27b.
End normal noise suppression control processing: End timer interrupt processing
After that, the program returns to the predetermined main program.

In the self-diagnosis processing, as shown in FIG. 7, first, in step S31, the control signal CA is set to "01", so that the analog multiplexers 28a and 28a.
The input sides of 8b are switched to the sweep generator 8 side, respectively, and then the process proceeds to step S32 to output the control signal CB of the logical value "1" to the sweep generator 8 and to start the sweep generator 8 before starting step S32.
In step 33, the oscillation frequency setting value f is output to the sweep generator 8 to generate the sweep signal XS having the oscillation frequency setting value f.

Next, in step S34, the swept sine wave signal X output from the sweep generator 8 is output.
S and respectively read the residual noise detecting signals e ₁ to e ₃ detected by the microphone 6 a to 6 c, then step S3
5, the swept sine wave signal XS is digitally filtered using the model space transfer function C _km ′ as a filter coefficient, and the filtered sine wave signals r _{1m to} r _3m (= C
_km ′ × XS) and adding filtered sine wave signals for each speaker to obtain a filtered sine wave corresponding to the residual noise detection signals e _{1 to} e ₃ of each microphone 6a to 6c. The signals r _{1 to} r ₃ are calculated, and then the process proceeds to step S36, where the filtered sine wave signals r _{1 to} r ₃ and the residual noise detection signal e ₁ to
The average values M _{r1 to} M _r3 and M _{e1 to} M _e3 of e ₃ are calculated.

Then, the process proceeds to step S37, where
The equations (10) to (12) are calculated to calculate the average deviation ΔD _k , which is the absolute value of the difference between the average value M _rk of the corresponding sine wave signals and the average value M _ek of the residual noise detection signal. ΔD ₁ = | M _r1 −M _e1 ｜ ………… (10) ΔD ₂ = | M _r2 −M _e2 ｜ ………… (11) ΔD ₃ = | M _r3 −M _e3 ｜ ………… (12 Next, the process proceeds to step S38, and it is determined whether the calculated average deviation ΔD _k is greater than or equal to a preset deviation threshold ΔS. This determination is to determine whether or not there is an abnormal state in which the amplitude difference between the filtered sine wave signal r _k and the residual noise detection signal e _k detected by the actual microphones 6a to 6c is large, and ΔD _{When k} ≧ ΔS, it is determined that the state is abnormal, the process proceeds to step S39, the defect display data is output to the display device 30 to display the defect, and then the process proceeds to step S44 to be described later, where ΔD _k
When <ΔS, it is judged as a normal state and step S4
Move to 0.

In step S40, the zero cross points of the filtered sine wave signal r _k and the residual noise detection signal e _k are detected to measure the time difference between the two zero cross points, and the measured time difference is set to the above-mentioned time difference. By multiplying the frequency f set in step S33, the phase difference Δθ between the sine wave signal r _k and the residual noise detection signal e _{k is obtained} by the number of wavelengths.

Next, in step S41, it is determined whether the calculated phase difference Δθ is greater than or equal to a preset phase threshold Δθ _T. This determination is originally based on the sine wave signal r _k.
And the phase of the residual noise detection signal e _k is the model space transfer function C
_{Although km} ′ and the real space transfer function C _km should match, the phase difference between them is caused only by the deviation of both space transfer functions, and this phase difference Δθ is the phase threshold value. When Δθ _T or more, it is determined that the state is abnormal, and the process proceeds to step S39, where the phase difference Δθ is the phase threshold Δ
When it is less than θ _T , it is determined to be in a normal state, and the process proceeds to step S42.

In step S42, the current frequency f
Is above a preset upper limit frequency f _L , and if f ≦ f _L , the process proceeds to step S43, and the value obtained by adding the preset frequency Δf to the current frequency f is added to the new frequency f. After updating as
Returning to step 33, when f> f _L , it is determined that all the set silencing frequency ranges are normal, and step S
44, the sweep generator 8 is stopped, then the process proceeds to step S45, and the control signal C of "00" C
A is output to the analog multiplexers 28a and 28b,
The drive signals y _{1 and} y ₂ are selected by these, and then the process proceeds to step S46.

In this step S46, it is judged whether or not the phase difference Δθ is within the allowable phase difference Δθ ₁ for normal muffling, and when Δθ ≦ Δθ ₁ , an effective silencing action is performed. In step S47, it is determined whether the gain difference ΔG between the sine wave signal r _K and the residual noise detection signal e _k is within a preset allowable gain difference ΔG _1. , ΔG ≦ ΔG ₁ , it is determined that the normal state in which the effective silencing action can be performed, and the self-diagnosis process is ended as it is,
Returning to the processing of FIG.

Further, the determination result of step S46 is Δθ>
When Δθ ₁ and the determination result of step S47 are ΔG
If> ΔG ₁ , the process proceeds to step S48, and it is determined whether or not the phase difference Δθ exceeds a limit phase difference Δθ ₂ that can be repaired by identification. If Δθ> Δθ ₂ , it is determined that repair is impossible. Then, the process proceeds to step S49, the unrepairable data is output to the display device 30 and is displayed, and then the self-diagnosis process is ended as it is, and the process returns to the process of FIG. 5. If Δθ ≦ Δθ ₂ , then step S50 Then, it is determined whether or not the gain difference ΔG exceeds the limit gain difference ΔG ₂ that can be repaired by identification. If ΔG> ΔG ₂ , it is determined that the repair is impossible and the step S49 is performed.
Proceeds to, performs identification processing proceeds to step S51 it is determined that repairable when a ΔG ≦ ΔG _2.

In this identification processing, as shown in FIG. 8, first, in step S52, the control signal CA of "11" is output to the analog multiplexers 28a and 28b to switch the input side thereof to the white noise generator 9 side. .. Then, the process proceeds to step S53, and the control signal CC having the logical value "1"
Is output to the white noise generator 9 to activate it, and the process proceeds to step S54.

[0042] In the step S54, the residual noise detecting signals e ₁ to e ₃ from each microphone 6a~6c with read No, the process proceeds to white noise XW from the white noise generator 9 reads, then to step S55, Similar to the process of step S35 in FIG. 7 described above, the white noise signals r _{1m to} r _3m (r _{1m to} r _3m (r) are filtered by performing the digital filtering process using the white noise XW as the filter coefficient of the model space transfer function C _km ′. =
C _km ′ × XW) and calculate each speaker 5a, 5
by adding the filtered white noise signal about the b, calculates the white noise signal r ₁ ~r ₃ which is filtered corresponding to the residual noise detecting signals e ₁ to e ₃ of each microphone 6a~6c ..

[0043] Then, the processing proceeds to step S56, the actual speakers 5a, 5b and white noise signal r ₁ ~ from the residual noise detecting signals e ₁ to e ₃ which includes a spatial transfer function is filtered between the microphone 6a~6c r ₃ is subtracted to calculate the deviations ε _{1 to} ε ₃ between the two. Then, the process proceeds to step S57, the following equation (13) is calculated to calculate the filter coefficient C _km ′ in the digital filter processing of step S55, and the calculated filter coefficient C _km ′ is updated, and then step S58. Move to.

C _km ′ (n + 1) = C _km ′ (n) −α · ε _km (n) · X (ni) (13) This filter coefficient update formula is a filter for digital filter processing. The evaluation function J of the coefficient C _km ′ is set as shown in the following formula (14), and the LMS algorithm is adopted to obtain the filter coefficient C _km ′ that minimizes the evaluation function J. J = E {ε _k (n) ² } (14) However, E {} is an expected value.

Then, the filter coefficient C at time n_km'of
Value C_km′ (N) is the value obtained by differentiating the evaluation function J, that is, proportional to the gradient
The amount of C_kmBy subtracting from ′ (n), the filter coefficient
C_kmBy sequentially updating ′ (n), the evaluation function J is maximized.
Target filter coefficient C to be small _optApproach. Concrete
Specifically,And the LMS algorithm uses ε instead of the expected value._k
(n) By using the instantaneous value of X (n-i) as it is,
Filter coefficient C of equation (13)_km′ (N) can be obtained.

In step S58, the filter coefficient C _km '
For updating the second term on the right side of the equation (13), that is, the gradient of the evaluation function J with respect to the filter coefficient (αε _k (n) XW (ni)
) Is less than or equal to a predetermined value ΔJ and the target filter coefficient C _opt at which the evaluation function J is minimized is determined, and αε
_{When k} (n) XW (ni) ≧ ΔJ, it is determined that the filter coefficient C _km ′ (n) has not reached the target filter coefficient C _opt , the process returns to step S54, and αε _k (n)
When XW (ni) <ΔJ, the target filter coefficient C
_When it is judged that the identification has been completed after reaching _opt , step S
59, the control signal CC having the logical value "0" is output to the white noise generator 9, the white noise generator 9 is stopped, and then the process proceeds to step S60 to control the control signal CA "00". Analog multiplexer 28
a, and outputs the 28b, the drive signal y ₁ the input side, y ₂
After that, the identification process ends and the process returns to FIG. 7.

Here, the processing of step S22 of FIG. 6 corresponds to the filter means, the processing of step S23 corresponds to the filter coefficient updating means, the processing of steps S24 and S25 corresponds to the adaptive filter processing, and the processing of FIG. Step S31-
34, the processing of S42 to S45, the sweep generator 8, and the analog multiplexers 28a and 28b correspond to the sweep signal supply means, and the processing of steps S46 to S51 of FIG. 7 and steps S52 to S60 of FIG. 8 correspond to the identification means. There is.

Therefore, assuming that the self-diagnosis switch 10 is off now, in the process of FIG. 5, the routine proceeds from step S1 to step S2, and the normal noise suppression control of FIG. 6 is executed. Therefore, the loudspeaker 5
a, 5b and the microphones 6a to 6c are not deteriorated,
If it is assumed that the actual space transfer function C _km between them and the model space transfer function C _km ′ in the digital filter process are substantially in agreement with each other in a normal state, the microcomputer 26 performs the filter in the adaptive digital filter process according to the LMS algorithm. The coefficients are sequentially updated, and the drive signals y _{1 and} y ₂ for the loudspeakers 5a and 5b are calculated so that the evaluation function J becomes the minimum, which are D / A conversion circuits 27a and 27b and the analog multiplexer 28.
It is supplied to the loudspeakers 5a and 5b via a and 28b. Therefore, loudspeaker 5a, the control sound corresponding to the drive signal y _1, y ₂ from 5b is emitted by this interfering with the noise, and residual noise detecting signals e ₁ to e ₃ microphones 6a~6c minimum The muffling is controlled so that

Arranged near the driver's seat from the silence control state
When the self-diagnosis switch 10 is turned on, the state shown in FIG.
When the processing of step S1 is started, the self-diagnosis mode is selected in step S1.
Since it is determined that the
The self-diagnosis process of 7 is executed. For this reason, first
Sweep on the input side of the multiplexers 28a and 28b
It is switched to the generator 8 side (step S31).
In this state, the sweep generator 8 is started and
Output the swept sine wave signal XS in the lower limit frequency range set for
(Steps S32 and S33), this swept sine wave signal
XS is an analog multiplexer 28a, 28b, an amplifier
Provided to loudspeakers 5a and 5b via 29a and 29b.
Supplied, and this is electroacoustic converted and output, and the microphone
These microphones are input to the microphones 6a to 6c.
6a, 6b and 6c and the loudspeaker 5a,
Spatial transfer function C between 5b_kmResidual noise detection signal including
e ₁(= C₁₁・ XS + C₁₂・ XS), e₂(= C_{twenty one}・ X
S + C_{twenty two}・ XS) and e₃(= C₃₁・ XS + C₃₂・ X
S) is output, and these are A / D converters 23a to 23c.
When input to the microcomputer 26 via
And the swept sine wave signal XS of the sweep generator 8
A / D converter 24 converts it to a digital value
It is input to the computer 26.

Therefore, the swept sine wave signal XS is digitized.
Real loudspeaker by filtering
Real space between 5a, 5b and microphones 6a-6c
Transfer function C_kmModel space transfer function C modeling_km′
Sinusoidal filter signal r containing ₁~ R₃Is calculated (
Step S35). Then, the input residual noise detection signal
e₁~ E₃And the calculated sinusoidal filter signal r₁~ R
₃Are averaged respectively and the average value M_r1~ M_r3And M_e1~ M_e3To
Calculated (step S36), average of both corresponding
Deviation ΔD₁~ ΔD₃Is calculated (step S37).

Here, the real space transfer function C _km between the loudspeakers 5a and 5b and the microphones 6a to 6c,
Model space transfer function C in digital filtering
_In a normal state in which _km 'substantially matches, the residual noise detection signals e _{1 to} e ₃ and the swept sine wave filter signals r _{1 to} r _{3 obtained} by digitally filtering the swept sine wave signal XS have amplitudes and phases thereof. Are substantially the same, so step S3
Input residual noise detection signals e _{1 to} e ₃ calculated in 7.
And the average deviation representing the calculated amplitude differences of the sine wave filter signals r _{1 to} r ₃ becomes a value close to zero, it is determined in step S38 that ΔD _k <ΔD _T, and the process proceeds to step S40.
Since the phase difference Δθ calculated here is a value close to zero,
After step S42 and step S43, step S33
By returning to step 3, the sweep generator 8 outputs the swept sine wave signal XS in the next sweep frequency range and the above operation is repeated. When the diagnosis in all frequency ranges is completed, the sweep generator 8 is stopped (step S44). Together with the analog multiplexer 28a,
28b is switched to the drive signal y _1, y ₂ side (step S4
5).

After that, the identification processing after step S46 is performed, but the real space transfer function C _km and the model space transfer function C
_{In the} normal state where _km 'substantially matches, as described above, the swept sine wave filter signal r _{1 obtained} by digitally filtering the residual noise detection signals e _{1 to} e ₃ and the swept sine wave signal XS is used.
Since the amplitude difference and the phase difference with respect to r ₃ are substantially zero, the self-diagnosis processing is terminated without performing the identification processing of FIG.

However, when a slight deviation occurs between the real space transfer function C _km and the model space transfer function C _km ′ due to a temperature change in the passenger compartment 2 or the like, residual noise detection signals e _{1 to} e
_Although the amplitude difference ΔD _k and the phase difference Δθ _k between ₃ and the swept sine wave filter signals r _{1 to} r _{3 obtained} by digitally filtering the swept sine wave signal XS are slightly larger than the amplitude threshold ΔD _T and the phase threshold Δθ _T. In the small state, step S3
8 and step S41 are determined to be normal, but it is determined to be identifiable in the processing of steps S46 to S48 and S50, the process proceeds to step S51, and the identification processing of FIG. 8 is performed. In this identification processing, first, the analog multiplexers 28a and 28b are switched to the white noise generator 9 side (step S52), and then the white noise generator 9 is activated to generate the white noise signal XW.
As a result, the white noise signal XW is supplied to the loudspeakers 5a and 5b via the analog multiplexers 28a and 28b and the amplifiers 29a and 29b, and white noise is output from these loudspeakers 5a and 5b.
These are collected by the microphones 6a to 6c, and the residual noise detection signals e are output from the microphones 6a to 6c.
_{1 to} e ₃ are output, and these are A / D converters 23 a to 2
It is converted into a digital value at 3c and input to the microcomputer 26.

Therefore, in the microcomputer 26, the white noise signal X output from the white noise generator 9 and converted into a digital value by the A / D converter 25 is output.
Residual noise detection signals e _{1 to} e _{3 of} the microphones 6a to 6c, which have been filtered by performing digital filtering on W, using the model space transfer function C _km ′ as a filter coefficient.
The white noise filter signals r _{1 to} r ₃ corresponding to are calculated (step S55). Then, calculates the deviation ε ₁ ~ε ₃ with white noise filtered signal r ₁ ~r ₃ and the calculated residual noise detecting signals e ₁ to e ₃ which is input (step S56), these deviations ε ₁ ~ε ₃ Based on the above
(13) by performing the calculation of equation, the filter coefficients C _miles in the digital filtering step S55 'to update the filter coefficients C _miles the operation to the evaluation function J'
Is repeatedly executed until the gradient reaches a set value ΔJ or less and reaches the target filter coefficient C _opt that minimizes the evaluation function. When the target filter coefficient C _opt is reached, the white noise generator 9 is stopped and the analog multiplexer 28a , 28b are returned to the drive signal y _1, y ₂ side, and the identification processing ends.

Furthermore, when a large deviation occurs between the real space transfer function C _km and the model space transfer function C _km ′ due to deterioration of the characteristics of the loudspeakers 5a and 5b or the microphones 6a to 6c, residual noise detection is performed. Signal e ₁
.About.e ₃ and the swept sine wave filter signals r _{1 to} r _{3 obtained} by digitally filtering the swept sine wave signal XS produce large amplitude difference ΔD _k and phase difference Δθ _k, as shown in FIG. One is the amplitude threshold ΔD _T or the phase threshold Δθ _T
If it becomes above, it will move to step S39 from step S38 or step S41, and the failure display data which urges replacement | exchange of loudspeakers 5a, 5b or microcomputers 6a-6c are output to the display device 30,
A defect display is made, and then the process proceeds to the identification process after step S46, and it is determined whether the phase difference Δθ or the gain difference ΔG exceeds the identifiable upper limit value Δθ ₂ or ΔG ₂ .
Upper limit value Δθ _{2 with which the} phase difference Δθ and the gain difference ΔG can be identified
And ΔG ₂ or less, it is judged that the model space transfer function C _km ′ is reidentified by the identification processing of FIG.
Upper limit value Δθ ₂ or ΔG with which θ or gain difference ΔG can be identified
When the number exceeds ₂ , it is determined that the identification is impossible, and the process proceeds to step S49, where the identification is not possible and the loudspeaker 5a,
5b or microphones 6a to 6c is output to the display device 30 to display the unidentifiable display data prompting replacement of the deteriorated parts, and the unidentifiable display is performed.

In the first embodiment described above, the case where the identification process is performed after the self-diagnosis process has been described, but the present invention is not limited to this, and the self-diagnosis process and the identification process are separated. You may do it by doing. next,
A second embodiment of the present invention will be described with reference to FIGS. In the second embodiment, the suitability of the model space transfer function C _km ′ is determined by the phase difference Δθ _k and the average deviation ΔD _k representing the amplitude.
Alternatively, the residual noise detection signal e _k corresponding to the swept sine wave signal and the swept sine wave filter signal r _{k obtained} by digitally filtering the swept sine wave signal with a filter coefficient corresponding to the model space transfer function C _km ′ The suitability of the model space transfer function C _km ′ is determined based on the deviation between and.

That is, as shown in FIG. 10, steps S36 to S38 and S4 in the self-diagnosis processing of FIG.
0, in place of the processing of S41, residual noise detection signals e _{1 to} e
₃ swept sine wave filtered signal r ₁ ~r ₃ was filtered calculated in step S35 from the step S61 to each subtraction to calculate both the deviation ε ₁ ~ε _3, calculated absolute deviation ε ₁ ~ε ₃ A step S62 of performing a full-wave rectification process as a value, a step S63 of calculating a moving average value ε _M by performing a moving average of the full-wave rectification value by, for example, a low-pass filter process, and a calculated moving average value ε _M are preset. Step S64 of determining whether or not the threshold is equal to or greater than the threshold ε _T
And the determination result of step S64 is ε _M ≧ ε _T
If it is, it is determined that the model space transfer function C _km ′ is abnormal, and the process proceeds to step S39 and the display device 30
In step S, it is determined that the model space transfer function C _km ′ is normal when ε _M <ε _T.
Move to 42.

According to the second embodiment, the real space transfer function C _km and the model space transfer function C _km ′ substantially match, and the residual noise detection signal e _k and the filtered swept sine wave filter signal r _k are obtained. , When they are substantially the same, the deviation ε
_{Since k} becomes substantially zero, it can be determined as normal in step S64, the real space transfer function C _km and the model space transfer function C _km ′ are deviated, and the residual noise detection signal e _k and the filtered swept sine For the wave filter signal r _k , for example, FIG.
When there is a phase difference as shown by the solid line, the deviation ε _k between the two becomes a sine wave having an amplitude corresponding to the phase difference as shown by the broken line. Therefore, this is full-wave rectified and the average value ε
_{When M} is calculated, if it exceeds the threshold value ε _T , it is determined to be abnormal in step S64 and a defect display is performed, and the same effect as that of the first embodiment described above can be obtained.

In each of the above embodiments, the case where the loudspeaker is applied as the control sound source has been described. However, the present invention is not limited to this, and a vibrator can be applied, and the residual noise detecting means can be used. An acceleration vibration sensor can also be applied to the microphone. Further, in each of the above-described embodiments, the case where the self-diagnosis switch 10 is in the self-diagnosis mode when it is in the ON state has been described.
The self-diagnosis processing may be performed at the time of turning off or at every predetermined time.

Furthermore, the number of loudspeakers and microphones installed is not limited to the number in the above embodiment, but 1
It can be any number above. Furthermore, in each of the above-described embodiments, the case where engine noise is suppressed has been described, but the present invention is not limited to this. It is possible to suppress road noise by detecting a vibration input from the road surface to the wheel or to vibrate the window glass. Can be detected and the wind noise can be suppressed, and these complex sounds can also be suppressed.

In each of the above embodiments, the case where the microcomputer 26 performs the adaptive digital filter processing and the digital filter processing of the filter coefficient according to the model space transfer function has been described. However, instead of these, an independent adaptive digital filter processing is performed. Filters and digital filters can also be applied. Furthermore, in each of the above-described embodiments, the case where the present invention is applied to the vehicle has been described, but the present invention is not limited to this and can be applied to the case of reducing noise in the interior of an aircraft.

[0062]

As described above, according to the active noise control apparatus of the first aspect, the model space transfer function that models the actual space transfer function between the control sound source and the residual noise detecting means is used. When performing active noise control by means of a sweep function, the propriety of the model space transfer function is output as an acoustic signal by supplying a sweeping sine wave signal to the control sound source, and this is detected by the residual noise detecting means and the sweep signal. A self-diagnosis can be made by comparing a sine wave signal with a filter output processed by a filter means having a model space transfer function as a filter coefficient, and a self-diagnosis can be made, and a noise suppression control system such as a control sound source or a residual noise detecting means. The effect of being able to reliably detect an abnormality due to the characteristic deterioration of

According to the active noise control device of the second aspect, in addition to the above effect, the model space transfer function is identified by the identifying means when the deviation of the model space transfer function is detected. Therefore, it is possible to obtain an effect that the deviation of the model space transfer function is corrected to perform optimum silencing control. Further, according to the active noise control device of the third aspect, the determination unit presets the amplitude difference between the swept sine wave signal detected by the residual noise detection unit and the swept sine wave signal filtered by the filter unit. Since it is configured to judge the suitability of the model space transfer function depending on whether it is equal to or larger than the amplitude threshold, it is possible to easily judge the suitability of the model space transfer function due to the characteristic deterioration of the noise suppression control system without using a complicated calculation. In addition, it can be accurately determined.

Further, according to the active noise control apparatus of the fourth aspect, the phase difference between the swept sine wave signal detected by the residual noise detecting means by the judging means and the swept sine wave signal filtered by the filtering means. Is configured to determine the suitability of the model space transfer function depending on whether or not is equal to or larger than a preset phase threshold, so that the suitability of the model space transfer function due to a temperature change or the like can be easily and without using a complicated calculation. You can judge accurately.

According to the active noise control device of the fifth aspect, the phase difference and the gain difference between the swept sine wave signal detected by the residual noise detection means and the swept sine wave signal filtered by the filter means are obtained. Reidentification is performed when each is within a preset range, and when the filter coefficient representing the model space transfer function of the filter means is updated by the identification, the identification is performed only when the normal state can be restored. When the identification is impossible, it is possible to prompt the replacement of the characteristic deterioration component of the noise suppression control system.

[Brief description of drawings]

FIG. 1 is a functional block diagram showing a basic configuration of the present invention.

FIG. 2 is another functional block diagram showing the basic configuration of the present invention.

FIG. 3 is a schematic configuration diagram of a first embodiment of the present invention.

FIG. 4 is a block diagram of a controller according to the first embodiment.

FIG. 5 is a flowchart of the first embodiment.

FIG. 6 is a flowchart showing a normal noise suppression process of the first embodiment.

FIG. 7 is a flowchart showing a self-diagnosis process of the first embodiment.

FIG. 8 is a flowchart showing an identification process of the first embodiment.

FIG. 9 is a waveform diagram for explaining the operation of the first embodiment.

FIG. 10 is a flowchart showing a self-diagnosis process in the second embodiment of the present invention.

FIG. 11 is a waveform chart for explaining the operation of the second embodiment.

[Explanation of symbols]

 5a, 5b Loudspeakers 6a-6c Microphone 8 Sweep generator 9 White noise generator 10 Self-diagnosis switch 15 Controller 26 Microcomputer 28a, 28b Analog multiplexer 30 Display device

Claims (5)

[Claims] 1. A sound pressure sent from the control sound source and ambient noise sound pressure by inputting a reference signal according to the noise generation state of the noise source from the reference signal generation means to the control sound source via the adaptive filter means. A signal obtained by detecting the combined sound pressure of the above with the residual noise detecting means, and filtering the reference signal with a filter means having a model spatial transfer function obtained by modeling the spatial transfer function between the control sound source and the residual noise detecting means. In the active noise control device, which is configured to update the filter coefficient of the adaptive filter by the steepest descent method by the filter coefficient updating means based on the residual noise detection signal and
Sweep signal supply means for supplying a swept sine wave signal instead of the reference signal to the control sound source and filter means, a swept sine wave signal detected by the residual noise detection means, and a swept sine wave signal filtered by the filter means Compare with
An active noise control device comprising: a determining unit that determines whether or not the model space transfer function of the filter unit is appropriate. 2. A sound pressure sent from the control sound source and ambient noise sound pressure by inputting a reference signal according to the noise generation state of the noise source from the reference signal generation means to the control sound source via the adaptive filter means. A signal obtained by detecting the combined sound pressure of the above with the residual noise detecting means, and filtering the reference signal with a filter means having a model spatial transfer function obtained by modeling the spatial transfer function between the control sound source and the residual noise detecting means. In the active noise control device, which is configured to update the filter coefficient of the adaptive filter by the steepest descent method by the filter coefficient updating means based on the residual noise detection signal and
Sweep signal supply means for supplying a swept sine wave signal instead of the reference signal to the control sound source and filter means, a swept sine wave signal detected by the residual noise detection means, and a swept sine wave signal filtered by the filter means Compare with
Judgment means for judging the suitability of the model space transfer function of the filter means, and the filter coefficient when the judgment means judges that the model space transfer function is proper and there is a deviation between the model space transfer function and the real space transfer function. And an identifying means for identifying the active noise control device. 3. The determination means determines whether or not the amplitude difference between the swept sine wave signal detected by the residual noise detection means and the swept sine wave signal filtered by the filtering means is equal to or more than a preset amplitude threshold value. The active noise control device according to claim 1, wherein the determination is made. 4. The determination means determines whether or not the phase difference between the swept sine wave signal detected by the residual noise detection means and the swept sine wave signal filtered by the filter means is equal to or more than a preset phase threshold value. The determination is performed according to claim 1.
4. The active noise control device according to any one of 3 to 3. 5. The identifying means, when the phase difference and the gain difference between the swept sine wave signal detected by the residual noise detection means and the swept sine wave signal filtered by the filter means are within preset ranges, respectively. An active noise control device characterized by performing re-identification.