Active noise reduction system

Abstract

An IMC type active noise reduction system includes a cancellation sound output device, an error microphone, and a controller. The error microphone is configured to generate an error signal. The controller includes a control filter and a secondary path filter. The secondary path filter is configured to generate a cancellation sound estimation signal. The control filter is configured to generate a control signal based on a reference signal generated based on both the error signal and the cancellation sound estimation signal. The controller also includes a main path filter configured to generate a noise estimation signal based on the reference signal. The secondary path filter and the primary path filter are configured to adaptively update based on a virtual error signal generated based on both the reference signal and the noise estimation signal.

Description

Technical Field

[0001] The present invention relates to an active noise reduction system that reduces noise by causing a cancelling sound in an opposite phase to the noise to interfere with the noise. Background Art

[0002] In recent years, considering the vulnerable groups such as the elderly and children among traffic participants, efforts have been actively made to provide sustainable transportation systems for these people. To achieve this goal, research and development on further improving traffic safety and convenience through the development of vehicle comfort is attracting attention.

[0003] In order to improve the comfort of a vehicle, it is desirable to reduce the noise inside the vehicle. Therefore, research and development of an active noise reduction system that reduces noise by interfering with a canceling sound in a phase opposite to that of the noise is actively conducted.

[0004] Conventionally, an internal model control type (IMC type) active noise reduction system is called a feedback control type active noise reduction system. The IMC type active noise reduction system is configured to generate a reference signal inside a controller based on an error signal generated by an error microphone and a cancellation sound estimation signal generated by a secondary path filter.

[0005] For example, JPH8-221079A discloses an IMC type active noise reduction system configured to generate white noise through a white noise generation unit and adaptively update a secondary path filter based on the white noise and an error signal (see "ADF 25" of JPH8-221079A).

[0006] In JPH8-221079A, the white noise used for adaptive update of the auxiliary path filter is output from the cancelling sound output device (see "speaker 4" in JPH8-221079A) together with the cancelling sound. Therefore, the occupants in the vehicle cabin may hear the white noise, which may make the occupants feel uncomfortable. On the other hand, if the white noise is reduced so that the occupants in the vehicle cabin cannot hear the white noise, the adaptive update of the auxiliary path filter may not be accurately performed. Summary of the invention

[0007] In view of the above background, an object of the present invention is to provide an IMC type active noise reduction system that can accurately perform adaptive updating of the auxiliary path filter without causing discomfort to the occupants by adding noise such as white noise. In addition, another object of the present invention is to contribute to the development of sustainable transportation systems.

[0008] To achieve this purpose, one aspect of the present invention provides an IMC type active noise reduction system (1 and 71), which includes: a cancellation sound output device (21), which is configured to output a cancellation sound for canceling noise; an error microphone (22), which is configured to generate an error signal (e) based on noise and the cancellation sound; and a controller (23 and 73), which is configured to control the cancellation sound output device based on the error signal, wherein the controller includes: a control filter (W), which is configured to generate a control signal (u) for controlling the cancellation sound output device; and an auxiliary path filter (C^), which is configured to generate a control signal (u) for controlling the cancellation sound output device. The controller further comprises a main path filter (P^), which represents an estimated value of a transfer function from a noise source to an error microphone; the auxiliary path filter is configured to generate a cancellation sound estimation signal (y^) based on a control signal; the control filter is configured to generate a control signal based on a reference signal (r) generated based on both the error signal and the cancellation sound estimation signal; the controller further comprises a main path filter (P^), which represents an estimated value of a transfer function from a noise source to an error microphone; the main path filter is configured to generate a noise estimation signal (d^) based on a reference signal; and the auxiliary path filter and the main path filter are configured to generate a virtual error signal (e^) based on both the reference signal and the noise estimation signal. v ) for adaptive update.

[0009] According to this aspect, the secondary path filter can be adaptively updated using the primary path filter instead of using noise such as white noise. Therefore, adaptive updating of the secondary path filter can be accurately performed without causing discomfort to the occupant due to the addition of noise such as white noise.

[0010] In the above aspect, preferably, the controller is configured to normalize the adaptive update amount of the auxiliary path filter and the adaptive update amount of the main path filter using a common normalization divisor.

[0011] Even if one of the auxiliary path filter or the main path filter is close to convergence, its convergence may be delayed due to the influence of the fluctuation of the other. According to the above aspect, a common normalization divisor is used to normalize the adaptive update amount of the auxiliary path filter and the adaptive update amount of the main path filter. Therefore, the change between the convergence speed of the auxiliary path filter and the convergence speed of the main path filter can be suppressed. Therefore, the convergence of one of the auxiliary path filter and the main path filter can be prevented from being delayed due to the fluctuation of the other, and the auxiliary path filter and the main path filter can be made to converge quickly.

[0012] In the above aspect, preferably, the auxiliary path filter is configured to be adaptively updated based on the control signal and the virtual error signal; the main path filter is configured to be adaptively updated based on the reference signal and the virtual error signal; and the common normalized divisor includes the norm of the signal vector of the reference signal and the norm of the signal vector of the control signal.

[0013] When the initial value of the control signal is zero, the initial value of the reference signal has a certain amplitude (i.e., the initial value of the reference signal is not zero). Therefore, if the adaptive update amount of the auxiliary path filter is normalized based on the control signal, and the adaptive update amount of the main path filter is normalized based on the reference signal, a large difference may be caused between the adaptive update amounts of the two filters in the early stage of convergence. According to the above aspect, the adaptive update amount of the auxiliary path filter and the adaptive update amount of the main path filter are both normalized based on the reference signal and the control signal. Therefore, it is possible to prevent a large difference between the adaptive update amounts of the two filters in the early stage of convergence. Therefore, the auxiliary path filter and the main path filter can be made to converge faster.

[0014] In the above aspect, preferably, the auxiliary path filter is composed of a finite impulse response filter; and the controller is configured to adjust the adaptive update amount of the auxiliary path filter using a weighting coefficient corresponding to the characteristics of the impulse response of the auxiliary path filter.

[0015] According to this aspect, the weighting coefficient can increase as the amplitude of the impulse response of the auxiliary path filter (i.e., the coefficient of the auxiliary path filter) increases, and the weighting coefficient can decrease as the amplitude of the impulse response of the auxiliary path filter decreases. Therefore, the auxiliary path filter can be made to converge quickly. Moreover, the shape of the impulse response of the auxiliary path filter can be maintained in the auxiliary path filter after the adaptive update of the auxiliary path filter. Therefore, the stability of the noise reduction control can be improved.

[0016] In the above aspect, preferably, the controller is configured to set the weighting coefficient so that the weighting coefficient is maximized with a delay time of an impulse response of the auxiliary path filter according to a distance from the cancellation sound output device to the error microphone.

[0017] According to this aspect, the secondary path filter can be made to converge faster.

[0018] In the above aspect, preferably, the controller is configured to set the weighting coefficient so that the weighting coefficient becomes smaller as time elapses from the delay time.

[0019] According to this aspect, the auxiliary path filter can be made to converge more quickly.

[0020] In the above aspect, preferably, the control filter is configured to be adaptively updated based on the error signal; and the controller is configured to use a weighting coefficient to adjust the adaptive update amount of the control filter, and the weighting coefficient decreases in a step shape after a specified time has passed since the cancellation sound output device outputs the cancellation sound.

[0021] According to this aspect, in the case where the shape of the impulse response of the filter is difficult to predict, a weighting coefficient having a simple form can be used to adjust the adaptive update amount of the control filter.

[0022] In the above aspect, preferably, the controller also includes a bandpass filter (B), which is configured to generate an extracted error signal by extracting a component within a specified control target frequency band from the error signal, and the reference signal is configured to be generated based on the extracted error signal and the cancellation sound estimation signal.

[0023] Normally, in an IMC type active noise reduction system, noise can be reduced in a narrow frequency band. Therefore, when an IMC type active noise reduction system is used to reduce noise in a vehicle cabin, it is usually preferred to reduce noise with a relatively large peak in a low frequency band. In contrast, when considering the hearing characteristics of a person, there is a situation where it is desired to preferentially reduce noise in a high frequency band that is easily detected by the human ear. According to the above aspect, by switching the control target frequency band, the frequency band for which noise reduction is prioritized can be easily switched. Therefore, the optimal noise reduction effect can be obtained according to various needs.

[0024] In the above aspect, preferably, the controller also includes: a noise generating unit (77), which is configured to generate random noise; and a band stop filter (BS), which is configured to generate a noise signal by attenuating the component of the random noise that is within the control target frequency band; and the control filter is configured to be adaptively updated based on the extracted error signal and the noise signal.

[0025] According to this aspect, the control filter is adaptively updated based on random noise in other frequency bands than the control target frequency band.

[0026] As a result, the controller reduces the coefficient of the control filter in the frequency band other than the control target frequency band. Therefore, the increase of noise can be suppressed.

[0027] Therefore, according to the above aspects, it is possible to provide an IMC type active noise reduction system that can accurately perform adaptive updating of the secondary path filter without causing discomfort to the occupant due to the addition of noise such as white noise. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1is a schematic diagram showing a vehicle to which the active noise reduction system according to the first embodiment is applied;

[0029] Figure 2 is a functional block diagram showing an active noise reduction system according to a first embodiment;

[0030] Figure 3 is a flowchart showing the flow of signal processing of the controller according to the first embodiment;

[0031] Figure 4 is a graph showing characteristics of the bandpass filter according to the first embodiment;

[0032] Figure 5 is a graph showing the amplitude of the impulse response of the auxiliary path filter and the setting value of the first weighting coefficient according to the second embodiment;

[0033] Figure 6 is a graph showing setting values ​​of the third weighting coefficient according to the second embodiment; and

[0034] Figure 7 is a functional block diagram showing an active noise reduction system according to a third embodiment. DETAILED DESCRIPTION

[0035] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. Note that in the following description, "^" (diacritic symbol) added to various symbols indicates an identified value or an estimated value. "^" is added above each symbol in the accompanying drawings, but is added after each symbol in the specification.

[0036] (First Embodiment)

[0037] First, refer to Figures 1 to 4 A first embodiment of the present invention is described.

[0038] <Vehicle 3>

[0039] Figure 1 1 is a schematic diagram showing a vehicle 3 to which an active noise reduction system 1 according to a first embodiment (hereinafter referred to as "noise reduction system 1") is applied. The vehicle 3 is, for example, a four-wheeled automobile.

[0040] Inside the cabin 4 of the vehicle 3, a plurality of passenger seats 6 are disposed below the roof lining 5. Each passenger seat 6 (hereinafter simply referred to as "passenger seat 6") includes a seat cushion 7 and a reclining portion 8 disposed above and behind the seat cushion 7 and configured to rotate relative to the seat cushion 7. The reclining portion 8 includes a seat back 9 and a headrest 10 fixed to an upper end of the seat back 9.

[0041] <Noise reduction system 1>

[0042] The noise reduction system 1 is an active noise control device (ANC device) configured to reduce noise d generated in a cabin 4 of a vehicle 3. More specifically, the noise reduction system 1 reduces noise d by generating a cancelling sound y in a phase opposite to the noise d and causing the generated cancelling sound y to interfere with the noise d.

[0043] For example, the noise d to be reduced by the noise reduction system 1 is road noise caused by the vibration of the wheel 15 due to the force from the road surface S. The noise d to be reduced by the noise reduction system 1 may be noise other than the road noise mentioned above, for example, driving noise caused by the vibration of a driving source such as an internal combustion engine and an electric motor.

[0044] Reference Figure 1 and Figure 2 The noise reduction system 1 includes: a plurality of speakers 21 (an example of a cancellation sound output device), each of which is configured to output a cancellation sound y to cancel the noise d; a plurality of error microphones 22, each of which is configured to generate an error signal e based on the noise d and the cancellation sound y; and a controller 23, which is configured to control the plurality of speakers 21 based on the error signal e.

[0045] <Speaker 21>

[0046] Reference Figure 1 , each speaker 21 (hereinafter referred to as "speaker 21") is installed in the headrest 10 of the reclining portion 8 of the passenger seat 6. In another embodiment, the speaker 21 may be installed in a portion other than the headrest 10 of the reclining portion 8 of the passenger seat 6 (e.g., the seat back 9), or in a portion other than the reclining portion 8 of the passenger seat 6. In yet another embodiment, the speaker 21 may be installed in a portion other than the passenger seat 6 of the vehicle 3.

[0047] <Error microphone 22>

[0048] Each error microphone 22 (hereinafter simply referred to as "error microphone 22") is installed in a portion other than the passenger seat 6 of the vehicle 3. For example, the error microphone 22 is installed in the headliner 5. In another embodiment, the error microphone 22 may be installed in a B-pillar (not shown) or the like, or in the passenger seat 6.

[0049] <Controller 23>

[0050] The controller 23 is constituted by a computer including an arithmetic processing unit (processor such as CPU, MPU, etc.) and a storage device (memory such as ROM, RAM, etc.) The controller 23 may be configured as one piece of hardware or may be configured as a unit including a plurality of hardware.

[0051] Reference Figure 2 The controller 23 includes the following functional components: an extraction error signal generating unit 31, a control signal generating unit 32, a cancellation sound estimation signal generating unit 33, a reference signal generating unit 34, a reference signal correction unit 35, a noise estimation signal generating unit 36, and a virtual error signal generating unit 37.

[0052] <Extraction Error Signal Generating Unit 31>

[0053] The extraction error signal generating unit 31 of the controller 23 includes a bandpass filter B. The bandpass filter B is a filter that extracts a component in a control target frequency band (a frequency band to be a control target of the controller 23) from an input signal. The control target frequency band can be switched at any time.

[0054] The error signal e from the error microphone 22 is input to the extracted error signal generating unit 31. As the bandpass filter B of the extracted error signal generating unit 31 extracts the component in the control target frequency band from the error signal e, the extracted error signal generating unit 31 generates the extracted error signal e. b The extraction error signal generation unit 31 generates the generated extraction error signal e b The signal is output to the control signal generating unit 32 and the reference signal generating unit 34 .

[0055] <Control Signal Generating Unit 32>

[0056] The control signal generating unit 32 of the controller 23 includes a control filter unit 41 and a control updating unit 42 .

[0057] The control filter unit 41 includes a control filter W. The control filter W is composed of, for example, a finite impulse response filter (FIR filter). In another embodiment, the control filter W may be composed of a single frequency adaptive notch filter (SAN filter) or the like.

[0058] As the control filter W of the control filter unit 41 filters the reference signal r (to be described later), the control filter unit 41 generates a control signal u for controlling the speaker 21. The control filter unit 41 outputs the generated control signal u to the speaker 21 and the canceling sound estimation signal generation unit 33. Therefore, the speaker 21 generates the canceling sound y according to the control signal u output from the control filter unit 41.

[0059] The control update unit 42 adaptively updates the control filter W using an adaptive algorithm such as the least mean square algorithm (LMS algorithm). More specifically, the control update unit 42 updates the control filter W so that the extraction error signal e output from the extraction error signal generation unit 31 is b minimize.

[0060] <Cancelling Sound Estimation Signal Generating Unit 33>

[0061] The canceling sound estimation signal generating unit 33 of the controller 23 includes a secondary path filtering unit 44 and a secondary path updating unit 45 .

[0062] The auxiliary path filter unit 44 includes an auxiliary path filter C^. The auxiliary path filter C^ is a filter that represents an estimated value of a transfer function C of an auxiliary path from the speaker 21 to the error microphone 22. The auxiliary path filter C^ is, for example, composed of an FIR filter. In another embodiment, the auxiliary path filter C^ may be composed of a SAN filter or the like.

[0063] As the secondary path filter C^ of the secondary path filter unit 44 filters the control signal u, the secondary path filter unit 44 generates a cancellation sound estimation signal y^ indicating an estimated value of the cancellation sound y. The secondary path filter unit 44 outputs the generated cancellation sound estimation signal y^ to the reference signal generation unit 34.

[0064] The auxiliary path updating unit 45 adaptively updates the auxiliary path filter C^ using an adaptive algorithm such as an LMS algorithm. More specifically, the auxiliary path updating unit 45 adaptively updates the auxiliary path filter C^ so that the virtual error signal output from the virtual error signal generating unit 37 is v (to be described later) Minimization.

[0065] <Reference Signal Generating Unit 34>

[0066] The reference signal generating unit 34 of the controller 23 includes a first polarity inverting unit 47 and a first adder 48 .

[0067] The first polarity inverting unit 47 inverts the polarity of the canceling sound estimated signal ŷ output from the canceling sound estimated signal generating unit 33 .

[0068] The first adder 48 adds the extraction error signal e output from the extraction error signal generating unit 31 to the b The reference signal r indicating the estimated value of the noise d is added to the cancellation sound estimation signal y^ after passing through the first polarity inversion unit 47. The first adder 48 outputs the generated reference signal r to the control signal generation unit 32, the reference signal correction unit 35, the noise estimation signal generation unit 36, and the virtual error signal generation unit 37.

[0069] <Reference Signal Correction Unit 35>

[0070] The reference signal correction unit 35 of the controller 23 includes an auxiliary path filter C^, which is similar to the auxiliary path filter unit 44 of the cancellation sound estimation signal generation unit 33. When the auxiliary path filter C^ is updated in the cancellation sound estimation signal generation unit 33, the updated auxiliary path filter C^ is output to the reference signal correction unit 35, and the auxiliary path filter C^ is updated in the reference signal correction unit 35. That is, the auxiliary path filter C^ set in the reference signal correction unit 35 is not a fixed value, but a value updated at any time based on the signal from the cancellation sound estimation signal generation unit 33.

[0071] As the auxiliary path filter C ^ of the reference signal correction unit 35 corrects the reference signal r, the reference signal correction unit 35 generates a corrected reference signal r'. The reference signal correction unit 35 outputs the generated corrected reference signal r' to the control signal generation unit 32.

[0072] <Noise estimation signal generating unit 36>

[0073] The noise estimation signal generation unit 36 ​​of the controller 23 includes a main path filter unit 50 and a main path update unit 51 .

[0074] The main path filter unit 50 includes a main path filter P^. The main path filter P^ is a filter that represents an estimated value of a transfer function P of a main path from a noise source to the error microphone 22. The main path filter P^ is, for example, composed of an FIR filter. In another embodiment, the main path filter P^ may be composed of a SAN filter or the like.

[0075] As the main path filter P^ of the main path filter unit 50 filters the reference signal r, the main path filter unit 50 generates a noise estimation signal d^ representing an estimated value of the noise d (more specifically, a component of the noise d reaching the error microphone 22). The main path filter unit 50 outputs the generated noise estimation signal d^ to the virtual error signal generation unit 37.

[0076] The main path updating unit 51 adaptively updates the main path filter P^ using an adaptive algorithm such as an LMS algorithm. More specifically, the main path updating unit 51 adaptively updates the main path filter P^ so that the virtual error signal e output from the virtual error signal generating unit 37 is v minimize.

[0077] <Virtual Error Signal Generating Unit 37>

[0078] The virtual error signal generating unit 37 of the controller 23 includes a second polarity inverting unit 53 and a second adder 54 .

[0079] The second polarity inverting unit 53 inverts the polarity of the noise estimation signal d ̂ output from the noise estimation signal generating unit 36 ​​.

[0080] The second adder 54 generates a virtual error signal e by adding the reference signal r output from the reference signal generating unit 34 and the noise estimation signal d t that has passed through the second polarity inverting unit 53. v . Virtual error signal e v is a signal used to learn the sound field (the transfer function C of the auxiliary path and the transfer function P of the main path) in the vehicle cabin 4. In other words, the virtual error signal e v is a signal used to adaptively update the auxiliary path filter C^ and the main path filter P^. The second adder 54 generates the virtual error signal e v The signal is output to the canceling sound estimated signal generating unit 33 and the noise estimated signal generating unit 36 ​​.

[0081] <Flow of Signal Processing by Controller 23>

[0082] Reference Figure 2 and Figure 3 When the error signal e from the error microphone 22 is input to the extraction error signal generating unit 31, the bandpass filter B of the extraction error signal generating unit 31 extracts the component in the control target frequency band from the error signal e. Therefore, the extraction error signal generating unit 31 generates the extraction error signal e b (Step ST1). Extract the error signal e b It is represented by the following formula (1).

[0083] e b (t) = e(t)*B…(1)

[0084] Next, the reference signal generating unit 34 generates a reference signal based on the extracted error signal e output from the extracted error signal generating unit 31. b The reference signal r is generated from the cancelling sound estimated signal ŷ output from the cancelling sound estimated signal generating unit 33 (step ST2). The reference signal r is represented by the following equation (2).

[0085]

[0086] Next, the virtual error signal generating unit 37 generates a virtual error signal e based on the reference signal r output from the reference signal generating unit 34 and the noise estimation signal d t output from the noise estimation signal generating unit 36. v (Step ST3). Virtual error signal e v It is expressed by the following formula (3).

[0087]

[0088] Next, the cancellation sound estimation signal generating unit 33 adaptively updates the auxiliary path filter C^ according to the following equation (4), and the noise estimation signal generating unit 36 ​​adaptively updates the main path filter P^ according to the following equation (5) (step ST4). 1 " represents the first weighting coefficient (the first step length parameter) for adjusting the adaptive update amount of the auxiliary path filter C^. In the following formula (5), "μ 2 " represents the second weighting coefficient (second step size parameter) for adjusting the adaptive update amount of the main path filter P^. In the following equations (4) and (5), "N 1 " represents the first normalized divisor used to normalize the adaptive update amount of the auxiliary path filter C^ and the main path filter P^.

[0089]

[0090] As is clear from the above equations (4) and (5), by the common first normalization divisor N 1 The adaptive update amount of the auxiliary path filter C^ and the adaptive update amount of the main path filter P^ are normalized. The first normalization divisor N 1 It is represented by the following equation (6). In the following equation (6), "||r(t)||" represents the norm of the signal vector of the reference signal r, and "||u(t)||" represents the norm of the signal vector of the control signal u. In addition, in the following equation (6), "σ" represents the first normalization divisor N 1 A constant (a small positive number) that becomes zero.

[0091] N 1 =‖r(t)‖+‖u(t)‖+σ...(6)

[0092] "||r(t)||" and "||u(t)||" in the above equation (6) are respectively expressed by the following equations (7) and (8). In the following equation (7), "L1" represents the number of data of the signal vector of the reference signal r. In the following equation (8), "L2" represents the number of data of the signal vector of the control signal u.

[0093]

[0094] Next, the control signal generating unit 32 adaptively updates the control filter W according to the following equation (9) (step ST5). In the following equation (9), “μ 3 " represents the third weighting coefficient (third step size parameter) used to adjust the adaptive update amount of the control filter W. In the following equation (9), "N 2 ” represents the second normalization divisor used to normalize the adaptive update amount of the control filter W.

[0095]

[0096] The second normalized divisor N in the above formula (9) is 2 It is represented by the following equation (10). In the following equation (10), "||r(t)*C^(t)||" represents the norm of the signal vector of "r(t)*C^(t)", and "σ" represents the second normalization divisor N used to prevent 2 A constant (small positive number) that becomes zero. The definition of "||r(t)*C^(t)||" in the following equation (10) is similar to the definitions of "||r(t)||" and "||u(t)||" in the above equation (6).

[0097]

[0098] Next, the control signal generating unit 32 generates a control signal u according to the following equation (11) (step ST6 ).

[0099] u(t+1)=W(t)*r(t)…(11)

[0100] <Adaptive Update of Auxiliary Path Filter C^ and Main Path Filter P^>

[0101] The error signal e is a signal obtained by adding the cancellation sound y and the noise d, and the cancellation sound y is represented by the control signal u and the transfer function C of the auxiliary path. Therefore, the error signal e is represented by the following equation (12).

[0102] e(t)=y(t)+d(t)=u(t)*C(t)+d(t)…(12)

[0103] According to the above equations (1), (3), and (12), the following equation (13) is obtained.

[0104]

[0105] The second term on the right side of the above equation (13) represents the error in the adaptive update of the auxiliary path filter C^. The cancellation sound estimation signal generation unit 33 adaptively updates the auxiliary path filter C^ so that the virtual error signal e v When the virtual error signal e v When minimized, the second term on the right side of the above equation (13) approaches zero. Therefore, the adaptive update value of the auxiliary path filter C^ converges to "the transfer function C of the auxiliary path × the characteristics of the bandpass filter B".

[0106] The first term on the right side of equation (13) above represents the error in the adaptive update of the main path filter P^. The adaptive update of the main path filter P^ is performed to extract the noise estimation signal d^ from the reference signal r, and the extracted noise estimation signal d^ is used to generate the virtual error signal e v The noise estimation signal generation unit 36 ​​adaptively updates the main path filter P^ so that the virtual error signal e v When the virtual error signal e v When minimized, the first term on the right side of equation (13) approaches zero. Therefore, the adaptive update value of the main path filter P^ converges to the characteristics of the bandpass filter B.

[0107] <Characteristics of Bandpass Filter B>

[0108] Figure 4 There is shown a characteristic of the band-pass filter B. The characteristic of the band-pass filter B is switched in accordance with a control target frequency band (a frequency band to be a control target of the controller 23 ).

[0109] For example, when the control target frequency band is the first frequency band f 1 In the case of , the characteristic of the bandpass filter B is set to characteristic 1. Therefore, the first frequency band f can be effectively reduced. 1 The noise with peak value d in the control target frequency band is greater than the first frequency band f 1 High second frequency band f 2 In the case of , the characteristic of the bandpass filter B is set to characteristic 2. Therefore, the second frequency band f can be effectively reduced. 2 The noise with peak value d in the control target frequency band is greater than the second frequency band f 2 High third frequency band f 3 In the case of , the characteristic of the bandpass filter B is set to characteristic 3. Therefore, the third frequency band f can be effectively reduced. 3 Noise d with peak value in .

[0110] <Effect>

[0111] As described above, the main path filter P^ generates the noise estimation signal d^ based on the reference signal r, and the auxiliary path filter C^ and the main path filter P^ generate a virtual error signal e^ based on both the reference signal r and the noise estimation signal d^. v According to such a configuration, the auxiliary path filter C^ can be adaptively updated using the main path filter P^ instead of using noise such as white noise. Therefore, the adaptive update of the auxiliary path filter C^ can be accurately performed without causing discomfort to the occupant due to the addition of noise such as white noise.

[0112] In addition, the auxiliary path filter C^ and the main path filter P^ are adaptively updated. Therefore, the occurrence of a difference between the sound field inside the car 4 (the transfer function C of the auxiliary path and the transfer function P of the main path) and the auxiliary path filter C^ and the main path filter P^ which are estimated values ​​of the above-mentioned sound field can be prevented. Therefore, the amplification of the noise d and the generation of abnormal sounds due to the above-mentioned differences can be prevented. In addition, the auxiliary path filter C^ and the main path filter P^ are adaptively updated so that these filters follow the changes in the sound field inside the car 4. Therefore, the peak value of the noise d caused by the resonance inside the car 4 can be stably reduced.

[0113] In addition, the noise reduction system 1 is a feedback control type noise reduction system. More specifically, the noise reduction system 1 is an internal model control type (IMC type) noise reduction system that generates a reference signal r inside the controller 23. Therefore, a reference microphone for generating a reference signal r based on noise d and an acceleration sensor for generating a reference signal r based on vibration are not required. Therefore, a reasonable noise reduction system 1 can be provided.

[0114] <Modification example>

[0115] In the above-mentioned first embodiment, only one bandpass filter B is provided. In another embodiment, a plurality of bandpass filters B having different characteristics may be provided in parallel, and a plurality of control filters W may be provided so as to respectively correspond to the plurality of bandpass filters B. According to such a configuration, noise d having peaks in a plurality of frequency bands may be reduced simultaneously.

[0116] (Second Embodiment)

[0117] Next, we will refer to Figure 5 and Figure 6 A second embodiment of the present invention is described. The configuration of the noise reduction system 1 is the same as that of the first embodiment, and thus a description thereof is omitted.

[0118] <Adaptive Update of Auxiliary Path Filter C^>

[0119] Reference Figure 5 , as the speaker 21 outputs the cancellation sound y at the sample number 0, the absolute value of the amplitude of the impulse response of the auxiliary path filter C^ (i.e., the coefficient of the auxiliary path filter C^) becomes maximum at the sample number D1. Thereafter, as the sample number increases from the sample number D1, the amplitude of the impulse response of the auxiliary path filter C^ decays.

[0120] The cancellation sound estimation signal generating unit 33 uses the following formula (14) to calculate the number of samples D1. In the following formula (14), "L" represents the distance from the speaker 21 to the error microphone 22 (hereinafter referred to as "propagation distance L"), "c" represents the speed of sound (about 340m / s), "Te" represents the processing time of the electronic circuit constituting the controller 23, and "Fs" represents the sampling frequency. For example, the cancellation sound estimation signal generating unit 33 calculates the propagation distance L based on the position of the passenger seat 6 or the auxiliary path filter C^. In the following formula (14), "c", "Te", and "Fs" are known values.

[0121]

[0122] Reference Figure 5 , the cancelling sound estimation signal generating unit 33 sets the first weighting coefficient μ 1 , so that the first weighting coefficient μ 1 The cancellation sound estimation signal generation unit 33 sets the first weighting coefficient μ to be maximized at the number of samples D1 (the number of samples that maximizes the absolute value of the amplitude of the impulse response of the auxiliary path filter C^) according to the propagation distance L and the processing time of the electronic circuit. 1 , so that the first weighting coefficient μ 1 The delay time of the impulse response of the auxiliary path filter C^ (the time when the absolute value of the amplitude of the impulse response of the auxiliary path filter C^ becomes the maximum) according to the propagation distance L and the processing time of the electronic circuit is maximized.

[0123] The canceling sound estimated signal generating unit 33 sets the first weighting coefficient μ 1 , so that the first weighting coefficient μ 1 As the number of samples increases from the number of samples D1, the weighting coefficient μ is gradually reduced. 1 , so that the first weighting coefficient μ 1 It gradually decreases as the time elapses from the delay time of the impulse response of the auxiliary path filter C^.

[0124] The canceling sound estimated signal generating unit 33 uses the first weighting coefficient μ set in the above manner. 1 , the auxiliary path filter C^ is adaptively updated according to the following formula (15). Therefore, the first weighting coefficient μ is used 1 To adjust the adaptive update amount of the auxiliary path filter C^.

[0125]

[0126] <Adaptive Update of Main Path Filter P^>

[0127] Similar to the canceling sound estimation signal generating unit 33, the noise estimation signal generating unit 36 ​​calculates the number of samples D1 using the above equation (14). The noise estimation signal generating unit 36 ​​sets the second weighting coefficient μ 2 , so that the second weighting coefficient μ 2 The second weighting coefficient μ is maximized at the sample number D1, and gradually decreases as the sample number increases from the sample number D1. That is, the noise estimation signal generation unit 36 ​​sets the second weighting coefficient μ 2 , so that the second weighting coefficient μ 2 The delay time of the impulse response of the main path filter P^ is maximized, and gradually decreases with the time elapsed from the delay time of the impulse response of the main path filter P^.

[0128] The noise estimation signal generating unit 36 ​​uses the second weighting coefficient μ set in the above manner. 2 , according to the following formula (16), the main path filter P^ is adaptively updated. Therefore, the second weighting coefficient μ is used 2 To adjust the adaptive update amount of the main path filter P^.

[0129]

[0130] <Adaptive Update of Control Filter W>

[0131] Reference Figure 6 , the control signal generating unit 32 sets the third weighting coefficient μ 3 , so that the third weighting coefficient μ 3 is maximized at the sample number 0. That is, the control signal generation unit 32 sets the third weighting coefficient μ 3 , so that the third weighting coefficient μ 3 It is maximized when the speaker 21 outputs the canceling sound y.

[0132] The control signal generating unit 32 sets the third weighting coefficient μ 3 , so that the third weighting coefficient μ 3 The control signal generating unit 32 sets the third weighting coefficient μ to 3 , so that the third weighting coefficient μ 3 After a predetermined time has passed since the canceling sound y is output from the speaker 21, the sound y decreases in a step-like manner.

[0133] The control signal generating unit 32 uses the third weighting coefficient μ set in the above manner. 3 , according to the following formula (17), the control filter W is adaptively updated. Therefore, the third weighting coefficient μ is used 3 To adjust the adaptive update amount of the control filter W.

[0134]

[0135] <Effect>

[0136] The controller 23 uses the first weighting coefficient μ corresponding to the characteristics of the impulse response of the auxiliary path filter C^. 1 , to adjust the adaptive update amount of the auxiliary path filter C^, and use the second weighting coefficient μ corresponding to the characteristics of the impulse response of the main path filter P^ 2 , to adjust the adaptive update amount of the main path filter P^. According to such a configuration, the auxiliary path filter C^ and the main path filter P^ can converge quickly.

[0137] In addition, the controller 23 uses the third weighting coefficient μ 3 To adjust the adaptive update amount of the control filter W, the third weighting coefficient μ 3 After a predetermined time has passed since the cancellation sound y is output from the speaker 21, the value decreases in a step shape. According to such a configuration, in view of the difficulty in predicting the shape of the impulse response of the filter, a third weighting coefficient μ having a simple form can be used. 3 To adjust the adaptive update amount of the control filter W.

[0138] <Modification example>

[0139] In the second embodiment described above, the controller 23 sets the first weighting coefficient μ 1 , so that the first weighting coefficient μ 1 The delay time of the impulse response of the auxiliary path filter C^ is maximized according to the propagation distance L and the processing time of the electronic circuit. In another embodiment, the controller 23 may set the first weighting coefficient μ 1 , so that the first weighting coefficient μ 1 The delay time of the impulse response of the auxiliary path filter C^ is maximized based only on the propagation distance L. That is, the controller 23 can set the delay time of the impulse response of the auxiliary path filter C^ based only on the propagation distance L or based on both the propagation distance L and the processing time of the electronic circuit.

[0140] In the above second embodiment, the controller 23 maximizes the absolute value of the amplitude of the impulse response of the auxiliary path filter C^ (with respect to Figure 5 The time corresponding to the number of samples D1 in the auxiliary path filter C^ is set as the delay time of the impulse response of the auxiliary path filter C^, and the first weighting coefficient μ is set 1 , so that the first weighting coefficient μ 1 In another embodiment, the controller 23 may set the time (with the same delay time) at which the absolute value of the amplitude of the direct wave (first wave) in the impulse response of the auxiliary path filter C^ is maximized. Figure 5The time corresponding to the number of samples D1′ in the auxiliary path filter C is set as the delay time of the impulse response of the auxiliary path filter C^, and the first weighting coefficient μ is set. 1 , so that the first weighting coefficient μ 1 Maximize this delay time.

[0141] In the second embodiment described above, the controller 23 uses the first weighting coefficient μ corresponding to the characteristics of the impulse response of the auxiliary path filter C 2 . 1 , to adjust the adaptive update amount of the auxiliary path filter C^, and use the second weighting coefficient μ corresponding to the characteristics of the impulse response of the main path filter P^ 2 , to adjust the adaptive update amount of the main path filter P^. In another embodiment, the controller 23 may apply the above method for adjusting the adaptive update amount to only one of the auxiliary path filter C^ and the main path filter P^.

[0142] In the above second embodiment, the controller 23 gradually reduces the first weighting coefficient μ 1 and the second weighting coefficient μ 2 In another embodiment, the controller 23 may reduce the first weighting coefficient μ exponentially or linearly. 1 and the second weighting coefficient μ 2 .

[0143] <Third Embodiment>

[0144] Next, refer to Figure 7 , an active noise reduction system 71 according to a third embodiment of the present invention (hereinafter referred to as "noise reduction system 71") is described. The components of the controller 73 other than the noise signal generating unit 75 are the same as those in the first embodiment. Therefore, the same reference numerals as those in the first embodiment are given to these components in the drawings, and their description is omitted.

[0145] <Noise Signal Generating Unit 75>

[0146] The noise signal generating unit 75 of the controller 73 includes a noise generating unit 77 , a filter unit 78 , and an amplitude adjusting unit 79 .

[0147] The noise generating unit 77 generates random noise x. The noise generating unit 77 outputs the generated random noise x to the filter unit 78.

[0148] The filter unit 78 includes a band stop filter BS. The band stop filter BS is a filter that attenuates a component in a control target frequency band of an input signal (a frequency band to be a control target of the controller 73).

[0149] As the band stop filter BS of the filter unit 78 attenuates the component in the control target frequency band of the random noise x, the filter unit 78 generates a noise signal x. n The filter unit 78 converts the generated noise signal x n Output to the amplitude adjustment unit 79.

[0150] The amplitude adjustment unit 79 has an amplitude adjustment coefficient β. The amplitude adjustment unit 79 adjusts the noise signal x output from the filter unit 78 by n Multiply by the amplitude adjustment coefficient β to adjust the noise signal x n The amplitude adjustment unit 79 adjusts the noise signal x with the adjusted amplitude n Output to the control signal generating unit 32.

[0151] <Adaptive Update of Control Filter W>

[0152] The control signal generating unit 32 generates a control signal based on the extraction error signal e output from the extraction error signal generating unit 31. b , a corrected reference signal r' output from the reference signal correction unit 35 (a signal generated by the auxiliary path filter C^ from the reference signal r), and a noise signal x output from the noise signal generation unit 75 n , adaptively updating the control filter W. For example, the control signal generating unit 32 adaptively updates the control filter W according to the following equation (18).

[0153]

[0154] <Effect>

[0155] The control signal generating unit 32 generates a virtual error signal e' according to the following equation (19). In the following equation (19), "·" represents an inner product operation, and "W·xn" represents a noise signal xn only related to the control filter W (hereinafter referred to as "correlated noise signal W·xn").

[0156] e′=d+y+W·x n …(19)

[0157] The control signal generating unit 32 adaptively updates the control filter W so that the square of the virtual error signal e' is minimized. In order to minimize the square of the virtual error signal e', it is necessary to make the actual sound pressure d+y (the sum of the noise d and the cancellation sound y) and the related noise signal W·x n Minimize. Noise signal x n is a signal that is in a frequency band other than the control target frequency band and is uncorrelated with the noise d generated in the vehicle compartment 4. Therefore, in order to make the correlated noise signal W·x nTo minimize, the control signal generating unit 32 reduces the value of the control filter W in the frequency band other than the control target frequency band. Therefore, the increase of the noise d can be suppressed.

[0158] <Modification example>

[0159] In the above-described first to fifth embodiments, the noise reduction systems 1 and 71 are applied to the cabin 4 of the vehicle 3. In another embodiment, the noise reduction systems 1 and 71 may be applied to the interior space of a moving body other than the vehicle 3 (e.g., a ship or an airplane), or to the interior space of a fixed object (e.g., a house).

[0160] The specific embodiments of the present invention have been described above, but the present invention should not be limited to the foregoing embodiments, but various modifications and changes may be made within the scope of the present invention.

Claims

1. An IMC type active noise reduction system, the active noise reduction system comprising: a cancelling sound output device, the cancelling sound output device being configured to output a cancelling sound for cancelling noise; an error microphone configured to generate an error signal based on the noise and the canceling sound; as well as a controller configured to control the cancellation sound output device based on the error signal, Wherein, the controller comprises: a control filter configured to generate a control signal for controlling the canceling sound output device; and a secondary path filter, the secondary path filter representing an estimate of a transfer function from the cancellation sound output device to the error microphone, The auxiliary path filter is configured to generate a canceling sound estimation signal based on the control signal, The control filter is configured to generate the control signal based on a reference signal generated based on both the error signal and the canceling sound estimation signal, The controller also includes a main path filter representing an estimate of a transfer function from a noise source to the error microphone, The main path filter is configured to generate a noise estimation signal based on the reference signal, and The auxiliary path filter and the main path filter are configured to be adaptively updated based on a virtual error signal generated based on both the reference signal and the noise estimation signal.

2. The active noise reduction system according to claim 1, wherein: The controller is configured to normalize an adaptive update amount of the auxiliary path filter and an adaptive update amount of the primary path filter using a common normalization divisor.

3. The active noise reduction system according to claim 2, wherein: The auxiliary path filter is configured to be adaptively updated based on the control signal and the virtual error signal, The main path filter is configured to be adaptively updated based on the reference signal and the virtual error signal, and The common normalization divisor includes a norm of a signal vector of the reference signal and a norm of a signal vector of the control signal.

4. The active noise reduction system according to claim 1, wherein: The auxiliary path filter is composed of a finite impulse response filter, and The controller is configured to adjust an adaptive update amount of the secondary path filter using a weighting coefficient corresponding to a characteristic of an impulse response of the secondary path filter.

5. The active noise reduction system according to claim 4, wherein: The controller is configured to set the weighting coefficient so that the weighting coefficient is maximized with a delay time of the impulse response of the auxiliary path filter according to a distance from the cancellation sound output device to the error microphone.

6. The active noise reduction system according to claim 5, wherein: The controller is configured to set the weighting coefficient so that the weighting coefficient becomes smaller as time elapses from the delay time.

7. The active noise reduction system according to claim 1, wherein: The control filter is configured to be adaptively updated based on the error signal, and The controller is configured to adjust the adaptive update amount of the control filter using a weighting coefficient that decreases in a step shape after a prescribed time has passed from a time when the cancelling sound output device outputs the cancelling sound.

8. The active noise reduction system according to any one of claims 1 to 7, wherein: The controller further includes a bandpass filter configured to generate an extracted error signal by extracting a component within a prescribed control target frequency band from the error signal, and The reference signal is configured to be generated based on the extracted error signal and the canceling sound estimation signal.

9. The active noise reduction system according to claim 8, wherein: The controller further comprises: a noise generating unit configured to generate random noise; and a band stop filter configured to generate a noise signal by attenuating a component of the random noise within the control target frequency band, and The control filter is configured to be adaptively updated based on the extracted error signal and the noise signal.

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