CN113488014A - Control method of microphone-free feedforward local active noise control system - Google Patents
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- G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
- G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
- G10K11/1787—General system configurations
- G10K11/17873—General system configurations using a reference signal without an error signal, e.g. pure feedforward
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- G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
- G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
- G10K11/1781—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions
- G10K11/17813—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the acoustic paths, e.g. estimating, calibrating or testing of transfer functions or cross-terms
- G10K11/17815—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the acoustic paths, e.g. estimating, calibrating or testing of transfer functions or cross-terms between the reference signals and the error signals, i.e. primary path
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- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
- G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
- G10K11/1781—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions
- G10K11/17813—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the acoustic paths, e.g. estimating, calibrating or testing of transfer functions or cross-terms
- G10K11/17817—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the acoustic paths, e.g. estimating, calibrating or testing of transfer functions or cross-terms between the output signals and the error signals, i.e. secondary path
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- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
- G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
- G10K11/1785—Methods, e.g. algorithms; Devices
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
- G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
- G10K11/1785—Methods, e.g. algorithms; Devices
- G10K11/17853—Methods, e.g. algorithms; Devices of the filter
- G10K11/17854—Methods, e.g. algorithms; Devices of the filter the filter being an adaptive filter
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- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
- G10K2210/30—Means
- G10K2210/301—Computational
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
- G10K2210/30—Means
- G10K2210/301—Computational
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- G—PHYSICS
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- G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
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- G10K2210/3028—Filtering, e.g. Kalman filters or special analogue or digital filters
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Abstract
The invention relates to the field of vibration noise control, in particular to a control method of a microphone-free feedforward local active noise control system, which does not need to use a physical microphone to monitor the noise of a target control point beside an ear and comprises a debugging stage and a control stage; in the debugging stage, a primary path and a secondary path are identified by adopting a self-adaptive filtering algorithm; in the debugging stage, the convolution of a primary path and a reference signal is used for estimating an interference signal, the convolution of the output of a control filter and a secondary path is used for estimating cancellation noise, the difference between the estimated interference signal and the cancellation noise is the estimated value of an error signal of the target control point beside the ear, and the estimated value is input into the control filter for iteration of weight coefficients, so that the active noise control of the target control point beside the ear is realized under the condition of no physical microphone. The method is low cost and more stable because of the absence of non-causal problems caused by physical microphones being further away relative to the primary sound source than virtual microphones.
Description
Technical Field
The invention belongs to the technical field of vibration noise control, and particularly relates to a control method of a microphone-free feedforward local active noise control system.
Background
A typical feed-forward active noise control system, based on the principle of sound wave superposition, collects reference signals (e.g., rotational speed, sound pressure, and acceleration signals) associated with a primary sound source and error signals measured by microphones located at target control points near the ear, and inputs them to a control filter. The control filter then generates a control signal to drive an auxiliary source (e.g., a speaker) to generate cancellation noise, creating a mute region in a target control region (e.g., a listener's ear). In the implementation of global active noise control, which minimizes the total acoustic potential in an enclosed space (e.g., a car cab), the control performance decreases as the frequency of the primary noise increases, because the sound pressure of a single frequency point is usually contributed by multiple modes, and the number of secondary sources is required to be no less than the number of contributing modes to achieve significant noise reduction. To achieve active noise control in higher frequency bands, a local noise control system (e.g., an active headrest system) is required that integrates secondary sound sources into the headrest and creates a local quiet zone around the listener's ears. However, this system requires the user to wear a binaural microphone to measure the error signal for updating the control filter coefficients, which limits the application of the active headrest system.
Virtual sensing technology arose. Instead of placing the error microphone at a target control point beside the ear, a plurality of monitoring microphones are placed at locations away from the listener's ear to estimate the error signal. The removed microphone is referred to as a virtual error microphone. The virtual sensing technology is mainly divided into two main categories, including Remote Microphone (RM) technology and Auxiliary Filtering (AF) technology. They have in common that both methods comprise two phases, namely a debugging phase and a control phase. Before implementing both methods, the system needs to be debugged to obtain the observation filter and the auxiliary filter. The difference is that the observation filter is used for filtering the interference signal collected by the monitoring microphone, calculating the interference signal at the virtual error microphone, then estimating the error signal of the target control point beside the ear, and driving and controlling the update iteration of the filter weight coefficient. The auxiliary filter is used for filtering the reference signal. When the filtering result is equal to the error signal measured by the monitoring microphone, the controller filtering weight coefficients converge to an optimal solution. The RM technique suffers from the spatial correlation of the monitor and virtual error microphones with respect to the primary sound source. When the primary sound source arrives at the virtual microphone earlier than the monitoring microphone, the causal relationship of the system is reduced, because it is not feasible to predict the virtual microphone 'future' interfering signal from the interfering signal of the monitoring microphone. This will result in a reduced control performance of the local active noise control system for broadband random noise. Another difficulty of the remote microphone method is to monitor the optimal solution of the positions and numbers of the microphones, i.e. how many microphones and how the microphones are arranged, so as to estimate the error signals from the virtual error microphones more accurately, thereby achieving better noise reduction effect.
In contrast, the AF technique does not involve these problems because the auxiliary filter obtained in the debugging phase already contains the relative position information between the monitor microphone and the virtual error microphone. The updating of the control filter coefficients is driven by the error signal between the output of the auxiliary filter and the signal measured by the monitoring microphone, rather than the estimated error signal of the virtual error microphone. It is readily seen that both of the above approaches still require a physical microphone to monitor the interfering signal.
Disclosure of Invention
In view of the problems of the background art, the present invention provides a control method of a feedforward local active control system without a physical microphone.
In order to solve the technical problems, the invention adopts the following technical scheme: a control method of a microphone-free feedforward local active noise control system comprises a primary sound source, a reference sensor, a listener, a controller and two secondary sound sources, wherein the controller and the two secondary sound sources are sequentially connected with the reference sensor; the control method comprises a control stage and a debugging stage; a debugging stage identifies a primary path and a secondary path; the method comprises the steps that a reference sensor collects a primary sound source signal and inputs the primary sound source signal as a reference signal into a controller, the controller calculates the convolution of the reference signal and a primary path and the convolution of the controller output and a secondary path, then the difference value of the reference signal and the primary path is calculated to obtain an error signal of a target control point beside an ear, the error signal is input into the controller, and the least mean square LMS algorithm is adopted to update and iterate the weight coefficient of a filter in the controller, so that the feedforward active noise control without a microphone is realized.
In the above control method of the microphone-less feedforward local active noise control system, the identification of the primary path and the secondary path includes: a primary path between the reference signal and the target control point at the ear side, and a secondary path between the secondary sound source and the target control point at the ear side are estimated using finite impulse response FIR filter lengths, the identified FIR filter lengths being stored in the controller.
In the above control method of the microphone-less feedforward local active noise control system, the specific steps of the control method are as follows:
1) a debugging stage: arranging a physical microphone beside the listener, inputting a reference signal acquired by a reference sensor and an interference signal acquired by the physical microphone into a controller, estimating the length of an FIR filter by using a primary path from the reference signal to target control points of the listener's left ear and right ear by using a Least Mean Square (LMS) algorithm, and storing the length in the controller;
the controller drives a secondary sound source by using a random noise generator, obtains the length of a secondary channel estimation FIR filter by adopting a least mean square LMS algorithm, and stores the length in the controller;
2) and (3) a control stage: removing the physical microphone near the listener's ear; the reference sensor collects a reference signal and inputs the reference signal into the controller, the controller calculates the convolution of the reference signal and the length of the primary path estimation FIR filter, the convolution of the output of the controller and the length of the secondary path estimation FIR filter, the difference of the two is obtained to obtain an error signal of a target control point beside the ear, and the error signal is input into the controller to participate in the iteration of the weight coefficient of the FIR filter in the controller.
Compared with the prior art, the invention does not need to consider the problems of the optimal number and the optimal arrangement of the monitoring microphones in the RM technology and the position of the monitoring microphones relative to the virtual microphone and the primary sound source. The system is more robust because of the non-causal problems caused by physical microphones being further away from the primary sound source than virtual microphones. Compared with the AF technology, the system of the invention has simpler structure and lower cost, and the noise control effect is similar to that of the AF method.
Drawings
FIG. 1 is a schematic diagram of a microphone-less feedforward local active noise control system according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating an exemplary process for identifying a primary path during a debug phase according to an embodiment of the present invention;
FIG. 3(a) is a diagram illustrating the identification result of the primary path from the reference signal to the right ear in the debugging stage according to an embodiment of the present invention;
FIG. 3(b) is a diagram illustrating the identification result of the primary path from the reference signal to the left ear during the debugging phase according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating the identification of a secondary path during a debug phase according to an embodiment of the present invention;
FIG. 5(a) is a diagram illustrating the recognition result of the secondary path from the left secondary sound source to the right ear in the debugging stage according to an embodiment of the present invention;
FIG. 5(b) is a diagram illustrating the recognition result of the secondary path from the right secondary sound source to the right ear in the debugging stage according to an embodiment of the present invention;
FIG. 5(c) is a diagram illustrating the recognition result of the secondary path from the left secondary sound source to the left ear in the debugging stage according to an embodiment of the present invention;
FIG. 5(d) is a diagram illustrating the recognition result of the secondary path from the right secondary sound source to the left ear in the debugging stage according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of the operation of one embodiment of the present invention during the control phase;
FIG. 7(a) is a diagram illustrating the control effect of the front and rear right ears of the active noise control stage during the control phase according to an embodiment of the present invention;
fig. 7(b) is a control effect diagram of the front and rear left ears of the active noise control being turned on in the control stage according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the following embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
The present invention is further illustrated by the following examples, which are not to be construed as limiting the invention.
This embodiment differs from conventional feedforward local active noise control systems in that the system does not require the use of a physical microphone to monitor the noise of the target control point beside the ear. The control comprises two stages: a debugging phase and a control phase. In the debugging stage, a primary path and a secondary path are identified by using an adaptive filtering algorithm; in the debugging stage, the convolution of a primary path and a reference signal is used for estimating an interference signal, the convolution of the output of a control filter and a secondary path is used for estimating cancellation noise, the difference between the estimated interference signal and the cancellation noise is the estimated value of an error signal of the target control point beside the ear, and the estimated value is input into the control filter for iteration of weight coefficients, so that the active noise control of the target control point beside the ear is realized under the condition of no physical microphone. The non-microphone feedforward local active noise control system provided by the invention has lower cost because of no physical microphone. Also, the system is more stable because of the non-causal issues caused by the physical microphones being further away from the primary sound source than the virtual microphones.
The control method of the microphone-free feedforward local active noise control system comprises a reference sensor (generally an acceleration sensor, a sound pressure sensor or a rotating speed sensor), a primary sound source, two secondary sound sources (generally loudspeakers), a controller and a listener. The method comprises the steps that a reference sensor collects a signal of a primary sound source as a reference signal and inputs the reference signal into a controller, the controller calculates the convolution of the reference signal and a primary path and the convolution of the controller output and a secondary path, then an error signal of a target control point beside an ear is obtained by calculating the difference value of the reference signal and the secondary path, the error signal is input into the controller, and filter weight coefficients in the controller are updated and iterated by using a filtering-x least mean square (FxLMS) algorithm, so that the feedforward active noise control without a microphone is realized.
And, there is no need to use a physical microphone that collects the target control point error signal near the ear.
The control method comprises a debugging phase and a control phase.
And, the control system identifies the primary and secondary long paths of the system using a Least Mean Square (LMS) algorithm.
Also, the system uses Finite Impulse Response (FIR) filter lengths to estimate a primary path between the reference signal and the target control point at the ear-side, and a secondary path between the secondary source and the target control point at the ear-side, the identified FIR filter lengths being stored in the controller.
The working process of the microphone-free feedforward local active noise control system is as follows:
(1) in the debugging phase, physical microphones are arranged near the listener's ears to pick up the interference signals. The identification of the system response is performed using an LMS algorithm, including a primary path between the reference signal and the target control point at the ear side, and a secondary path between the secondary sound source and the target control point at the ear side. Their recognition results are estimated using FIR filter lengths, which are stored in the controller.
(2) In the control phase, the physical microphones are removed near the listener's ears. The reference sensor collects a reference signal of a primary sound source and inputs the reference signal into the controller, the controller calculates convolution of the reference signal and the primary path to estimate an interference signal of a target control point beside an ear, a cancellation signal is estimated by using convolution of the output of the controller and the secondary path, the difference between the interference signal and the cancellation signal is an error signal of the estimated target control point beside the ear, and the error signal is input into the controller to participate in iteration of a control filter weight coefficient in the controller.
In specific implementation, as shown in fig. 1, the microphone-less feedforward local active noise control system includes 1 reference sensor, 2 secondary sound sources, and 1 controller.
The control method of the microphone-free feedforward local active noise control system comprises the following steps:
as shown in fig. 2, in the debugging phase, a physical microphone is arranged near the listener's ear to identify the interfering signal. The sampling frequency of the system is 8192Hz, the primary sound source is Gaussian white noise, and the length of the FIR filter of the primary path estimation is 128. The reference signal collected by the reference sensor and the interference signal collected by the physical microphone are input into the controller, and the coefficients of the FIR filter are estimated by using an LMS algorithm to identify the primary path of the reference signal to the target control points of the left ear and the right ear and are stored in the controller. The primary path identification results of the reference signal to the left ear target control point and the right ear target control point are respectively shown in fig. 3(a) and 3 (b).
As shown in fig. 4, during the commissioning phase, the controller drives the secondary source using a random noise generator, identifies 4 secondary paths using the LMS algorithm and estimates the FIR filter length, which is stored in the controller. The system sampling frequency is 8192Hz and the sub-path estimation FIR filter length is 128. Fig. 5(a), 5(b), 5(c), and 5(d) show the 4 secondary path recognition results.
As shown in fig. 6, in the control phase, the physical microphones are removed near the listener's ears. The reference sensor collects a reference signal and inputs the reference signal into the controller, the controller calculates the convolution of the reference signal and the length of the primary path estimation FIR filter and the convolution of the output of the controller and the length of the secondary path estimation FIR filter, the difference between the two is calculated to obtain the estimation value of the error signal at the control point of the target beside the ear, and the estimation value is used for the iteration of the weight coefficient of the controller filter in the controller. The control effect of turning on the active noise control rear right ear and left ear is shown in fig. 7(a), 7(b), respectively.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.
Claims (3)
1. A control method of a microphone-free feedforward local active noise control system comprises a primary sound source, a reference sensor, a listener, a controller and two secondary sound sources, wherein the controller and the two secondary sound sources are sequentially connected with the reference sensor; the method is characterized in that: the control method comprises a control stage and a debugging stage; a debugging stage identifies a primary path and a secondary path; the method comprises the steps that a reference sensor collects a primary sound source signal and inputs the primary sound source signal as a reference signal into a controller, the controller calculates the convolution of the reference signal and a primary path and the convolution of the controller output and a secondary path, then the difference value of the reference signal and the primary path is calculated to obtain an error signal of a target control point beside an ear, the error signal is input into the controller, and the least mean square LMS algorithm is adopted to update and iterate the weight coefficient of a filter in the controller, so that the feedforward active noise control without a microphone is realized.
2. A control method of a mic-less feedforward local active noise control system as in claim 1, wherein: the identification of the primary and secondary paths includes: a primary path between the reference signal and the target control point at the ear side, and a secondary path between the secondary sound source and the target control point at the ear side are estimated using finite impulse response FIR filter lengths, the identified FIR filter lengths being stored in the controller.
3. A control method for a microphone-less feedforward local active noise control system as claimed in claim 2, characterized in that: the control method comprises the following specific steps:
1) a debugging stage: arranging a physical microphone beside the listener, inputting a reference signal acquired by a reference sensor and an interference signal acquired by the physical microphone into a controller, estimating the length of an FIR filter by using a primary path from the reference signal to target control points of the listener's left ear and right ear by using a Least Mean Square (LMS) algorithm, and storing the length in the controller;
the controller drives a secondary sound source by using a random noise generator, obtains the length of a secondary channel estimation FIR filter by adopting a least mean square LMS algorithm, and stores the length in the controller;
2) and (3) a control stage: removing the physical microphone near the listener's ear; the reference sensor collects a reference signal and inputs the reference signal into the controller, the controller calculates the convolution of the reference signal and the length of the primary path estimation FIR filter, the convolution of the output of the controller and the length of the secondary path estimation FIR filter, the difference of the two is obtained to obtain an error signal of a target control point beside the ear, and the error signal is input into the controller to participate in the iteration of the weight coefficient of the FIR filter in the controller.
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