CN112669804B - Noise reduction effect estimation method for active noise control system - Google Patents
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Abstract
The invention provides a noise reduction effect estimation method of an active noise control system, which comprises the following steps: determining a target measurement point, enabling the target measurement point to be spaced from the physical microphone, and setting a virtual microphone at the target measurement point; obtaining a physical path, and modeling a virtual path by combining the physical path to obtain a virtual path transfer function estimated value; estimating a primary sound field and a secondary sound field noise signal at the virtual microphone location; and estimating the current noise value and the noise reduction amount according to the estimated primary sound field and the estimated secondary sound field noise signal. Compared with the related art, the method for estimating the noise reduction effect of the active noise control system is simple and convenient to use, low in cost and high in accuracy.
Description
Technical Field
The invention relates to the technical field of noise reduction effect testing, in particular to a noise reduction effect estimation method of an active noise control system based on a virtual sensing technology.
Background
With the development of economy and industrialization, noise pollution has become a non-negligible environmental problem, and long-term exposure to high noise environment will cause harm to human hearing and physical and mental health. In recent years, active noise control (Active Noise Control, ANC) technology has evolved very rapidly. At present, almost all ANC systems adopt an adaptive control mode, that is, the secondary sound source output is adaptively adjusted by a control filter according to the monitoring signal output by an error sensor and fed back to the control filter, so as to achieve the expected control target.
On one hand, the current engineering application research only focuses on the performance, the applicable scene and the like of an algorithm, and has no good solution for the prediction and real-time display of the noise reduction effect. The noise reduction effect of a noise reduction system is generally evaluated by collecting noise before and after noise reduction of the system by using a special noise measurement device, and then calculating the noise pressure level and the noise reduction amount of the noise, and the effect is generally expressed in dB or dB (A). This requires that the system must collect noise data for the same period of time before and after noise reduction, which is difficult to achieve in practical engineering applications. Two periods of time with similar noise characteristics before and after noise reduction are usually selected, and noise data are consistent or very close in time domain so as to ensure that the calculation of the noise reduction effect is not influenced. In practice, noise cannot repeatedly appear over time, so that it is necessary to estimate the noise reduction effect in real time, and the control strategy can be changed according to the estimated noise reduction amount.
On the other hand, in practical engineering application, in order to know the noise value of a certain point or area, a microphone is often arranged in the area and used for picking up the noise signal at the area, so as to obtain noise information. However, in many application scenarios, it is often difficult to realize, for example, to know the noise value of the ear of the driver in the cockpit and the noise reduction effect after the noise reduction is turned on in real time, and a microphone must be placed on the ear. This can seriously affect the head activity of the driver, and the driving experience is poor and unsafe, and the solution is to place the microphone at a nearby mountable position which does not affect the head activity of the driver, and the measure solves the problem of inconvenient head activity of the driver, but also causes inaccurate detection data due to inaccurate acquisition positions.
Therefore, it is necessary to provide a new noise reduction effect estimation method for an active noise control system to solve the above-mentioned problems.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides the noise reduction effect estimation method of the active noise control system, which is simple and convenient to apply, low in cost and high in accuracy.
In order to solve the technical problems, the invention provides a noise reduction effect estimation method of an active noise control system, wherein the active noise control system comprises an active noise controller, a secondary sound source, a physical microphone and a virtual microphone; the secondary sound source is used for generating secondary sound, and the secondary sound is overlapped with the primary sound field noise signal to generate noise residual error so as to form a secondary sound field noise signal; the physical microphone is used for picking up the secondary sound field noise signal and inputting the secondary sound field noise signal to the active noise controller so as to update the output of the secondary sound source; the virtual microphone calculates the secondary sound field noise signal at the virtual microphone according to the secondary sound field noise signal picked up by the physical microphone, and the physical microphone is used for replacing the secondary sound field noise signal at the path modeling stage; the method comprises the following steps:
s1, determining a target measurement point, enabling the target measurement point to be spaced from the physical microphone, setting the virtual microphone at the target measurement point, and placing the physical microphone at the position point of the virtual microphone for virtual path modeling;
s2, acquiring a physical path, and modeling a virtual path by combining the physical path to obtain a virtual path transfer function estimated value; wherein modeling includes modeling a physical secondary path H p Virtual secondary path H v And virtual path H pv Performing actual modeling to obtain a corresponding physical secondary path estimation modelVirtual sub-path estimation model->And virtual channel estimation model->
S3, estimating a primary sound field sound signal and a secondary sound field noise signal at the position of the virtual microphone; and estimating the current noise value and the noise reduction amount according to the estimated primary sound field sound signal and the secondary sound field noise signal.
Preferably, in step S2, the number of secondary sound sources is defined as l, the number of physical microphones is defined as m, and the number of virtual microphones is defined as n; physical microphone E in primary sound field environment 1 、…、E m The signals are d respectively p1 (i)、…、d pm (i) Virtual microphone E v1 、…、E vn The signals are d respectively v1 (i)、…、d vn (i) Virtual path H pv11 、…、H pv1n 、…、H pvm1 、…、H pvmn The estimation models of (a) are respectivelyThe method specifically comprises the following steps:
modeling a secondary path, namely sequentially playing preset sound sources through the l secondary sound sources, simultaneously receiving signals of the preset sound sources by all physical microphones distributed at the physical microphone positions and the virtual microphone positions, and completing transfer function calculation from the secondary sound sources to the physical microphones and the virtual microphones, thereby completing modeling of the secondary path and obtaining a physical secondary path estimation modelAnd virtual sub-path estimation model->
Virtual path modeling, namely, real-time noise signals collected by all physical microphones and distributed at the physical microphone positions in an actual noise field are used for completing transfer function calculation from the physical microphones to the virtual microphones, and virtual path modeling is completed to obtain a virtual path estimation model
Preferably, in step S3, the method specifically includes:
in actual noise control, a physical microphone collects and acquires a sound field noise signal, and a physical secondary path estimation model is combinedVirtual sub-path estimation model->And virtual channel estimation model->Completing noise signal estimation of the virtual microphone position to obtain a primary sound field and a secondary sound field of the virtual microphone position;
in a baseE p 、/>Y represents a physical microphone primary sound field signal estimated value, a virtual microphone primary sound field signal estimated value, a physical microphone real-time noise signal, a virtual microphone noise signal estimated value and a secondary sound source output signal respectively;
1) Calculating physical microphone expected signals
Obtaining
2) Calculating virtual microphone expected signals
The virtual microphone signal estimation values obtained by the physical microphone signal and the virtual channel estimation model are respectivelyThen there is
Obtaining
3) Calculating an estimate of a virtual microphone noise signal
Calculating an estimated value of the output signal of the secondary sound source of the virtual microphone:
calculating a virtual microphone noise signal estimate:
i.e.
Thereby obtaining the following steps:
4) Calculating primary and secondary sound field sound pressure levels at virtual microphone locations
The calculation formula of the sound pressure level is:wherein p is ref ＝2.0×10 -5 Calculating noise sound pressure level L of primary sound field and secondary sound field at nth virtual microphone position dvn And L evn ：
Wherein the method comprises the steps ofd vn (i) The expected signal at a certain moment of the nth virtual microphone is the noise sound pressure level before noise reduction;
wherein e vn (i) An error signal at a certain moment of the nth virtual microphone, namely the noise sound pressure level after noise reduction;
5) Calculating sound pressure levels before and after noise reduction of the active noise control system
Noise reduction front sound pressure level
Sound pressure level after noise reduction
6) Calculating the noise reduction amount of the active noise control system
Calculating the noise reduction amount L at the nth virtual microphone Δn ：
Calculating the average noise reduction of the active noise control system:
compared with the related art, the method for estimating the noise reduction effect of the active noise control system can estimate the noise reduction amount of the active noise control system in real time, accurately predict the noise pressure level of the system before and after noise reduction, and is applicable to all active noise control systems based on virtual sensing technology and secondary path estimation; the noise reduction effect estimation method of the active noise control system is simple and convenient in engineering application, low in cost and high in accuracy, and does not involve additional installation of hardware.
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The present invention will be described in detail with reference to the accompanying drawings. The foregoing and other aspects of the invention will become more apparent and more readily appreciated from the following detailed description taken in conjunction with the accompanying drawings. In the accompanying drawings:
FIG. 1 is a block flow diagram of a method for estimating noise reduction in an active noise control system according to the present invention;
FIG. 2 is a schematic diagram of a system structure in a method for estimating noise reduction effect of an active noise control system according to the present invention;
fig. 3 is a block diagram of a noise reduction algorithm in the noise reduction effect estimation method of the active noise control system according to the present invention.
Detailed Description
The following describes in detail the embodiments of the present invention with reference to the drawings.
The detailed description/examples set forth herein are specific embodiments of the invention and are intended to be illustrative and exemplary of the concepts of the invention and are not to be construed as limiting the scope of the invention. In addition to the embodiments described herein, those skilled in the art will be able to adopt other obvious solutions based on the disclosure of the claims and specification of the present application, including those adopting any obvious substitutions and modifications to the embodiments described herein, all within the scope of the present invention.
1-3, FIG. 1 is a block flow diagram of a method for estimating noise reduction effect of an active noise control system according to the present invention; FIG. 2 is a schematic diagram of a system structure in a method for estimating noise reduction effect of an active noise control system according to the present invention; fig. 3 is a block diagram of a noise reduction algorithm in the noise reduction effect estimation method of the active noise control system according to the present invention. The invention provides a noise reduction effect estimation method of an active noise control system, which comprises the following steps:
referring to fig. 2, the active noise control system includes an active noise controller 1, a secondary sound source 3, a physical microphone 4, and a virtual microphone 5. The secondary sound source is used for generating secondary sound, and the secondary sound field is overlapped with the primary sound field noise signal to generate noise residual error so as to form a secondary sound field noise signal; the physical microphone 4 is used to pick up the secondary sound field noise signal and input to the active noise controller to update the output of the secondary sound source. The virtual microphone 5 calculates the secondary sound field noise signal at the virtual microphone from the secondary sound field noise signal picked up by the physical microphone 4, and replaces it with a physical microphone in the path modeling stage. The invention is based on the principle that in order to estimate the noise value and the noise reduction amount at the human ear of the head, one microphone, i.e. the virtual microphone, is virtualized at the human ear. The system is operated to calculate the desired signal and the error signal at the virtual microphone based on the known transfer function between the virtual microphone to the physical microphone and the secondary sound source.
The method comprises the following steps:
step S1, determining a target measuring point, enabling the target measuring point to be spaced from the physical microphone, setting the virtual microphone 5 at the target measuring point, and placing the physical microphone at the position point of the virtual microphone for virtual path modeling.
S2, acquiring a physical path, and modeling a virtual path by combining the physical path to obtain a virtual path transfer function estimated value; wherein modeling includes modeling a physical secondary path H p Virtual secondary path H v And virtual path H pv Performing actual modeling to obtain a corresponding physical secondary path estimation modelVirtual sub-path estimation model->And virtual channel estimation model->
In the system debugging stage, the actual microphone is arranged at the ear position, but the noise signal measured by the actual microphone does not enter the control system, and only the noise of the virtual microphone is monitored; after the system is debugged, the real microphone of the virtual microphone is disassembled, and a noise measurement stage of the system is entered; at this time, the microphone is not placed at the ear position, and the acoustic signal of the virtual microphone is estimated from the acoustic signal at the physical microphone, thereby obtaining a noise value and a noise reduction amount.
The step is a modeling and debugging stage, and is specific:
defining the number of secondary sound sources as l, the number of physical microphones as m and the number of virtual microphones as n; physical microphone E in primary sound field environment 1 、…、E m The signals are d respectively p1 (i)、…、d pm (i) Virtual microphone E v1 、…、E vn The signals are d respectively v1 (i)、…、d vn (i) Virtual path H pv11 、…、H pv1n 、…、H pvm1 、…、H pvmn The estimation models of (a) are respectivelyThe method specifically comprises the following two steps:
modeling a secondary path, namely sequentially playing preset sound sources through the l secondary sound sources, simultaneously receiving signals of the preset sound sources by all physical microphones distributed at the physical microphone positions and the virtual microphone positions, and completing transfer function calculation from the secondary sound sources to the physical microphones and the virtual microphones, thereby completing modeling of the secondary path and obtaining a physical secondary path estimation modelAnd virtual sub-path estimation model->
Virtual path modeling, namely real-time noise signals collected by all physical microphones distributed at physical microphone positions and virtual microphone positions in an actual noise field simultaneously, completing transfer function calculation from the physical microphones to the virtual microphones, and completing virtual path modeling to obtain a virtual path estimation model
S3, estimating a primary sound field sound signal and a secondary sound field noise signal at the position of the virtual microphone; and estimating the current noise value and the noise reduction amount according to the estimated primary sound field sound signal and the secondary sound field noise signal.
The step is a noise measurement stage, and specifically includes:
in actual noise control, a physical microphone at the physical microphone position acquires a sound field noise signal by acquisition, and combines a physical secondary path estimation modelVirtual sub-path estimation model->And virtual channel estimation model->Completing noise signal estimation of the virtual microphone position to obtain a primary sound field and a secondary sound field of the virtual microphone position;
order the
In a baseE p 、/>Y represents a physical microphone primary sound field signal estimated value, a virtual microphone primary sound field signal estimated value, a physical microphone real-time noise signal, a virtual microphone noise signal estimated value and a secondary sound source output signal respectively;
1) Calculating physical microphone position desired signals
Obtaining
2) Calculating virtual microphone position desired signals
The virtual microphone signal estimation values obtained by the physical microphone signal and the virtual channel estimation model are respectivelyThen there is
Obtaining
3) Calculating an estimate of a virtual microphone noise signal
Calculating an estimated value of the output signal of the secondary sound source of the virtual microphone:
calculating a virtual microphone noise signal estimate:
i.e.
Thereby obtaining the following steps:
that is, the signal at the virtual microphone location may be passed through the signal E at the physical microphone location p Pathway modelAnd->And estimating, calculating the noise value at the position of the virtual microphone and measuring the noise reduction amount.
4) Calculating primary and secondary sound field sound pressure levels at virtual microphone locations
The calculation formula of the sound pressure level is:wherein p is ref ＝2.0×10 -5 Calculating noise sound pressure level L of primary sound field and secondary sound field at nth virtual microphone position dvn And L evn ：
Wherein d is vn (i) Is the desired signal at a certain moment of the nth virtual microphone,i.e. the noise sound pressure level before noise reduction;
wherein e vn (i) The error signal at a certain moment of the nth virtual microphone is the noise sound pressure level after noise reduction.
5) Calculating sound pressure levels before and after noise reduction of the active noise control system
Noise reduction front sound pressure level
Sound pressure level after noise reduction
6) Calculating the noise reduction amount of the active noise control system
Calculating the noise reduction amount L at the nth virtual microphone Δn ：
Calculating the average noise reduction of the active noise control system:
therefore, the average noise reduction amount of the active noise control system and the current noise pressure level after the noise reduction function is started can be calculated.
The method for estimating the noise reduction effect of the active noise control system can estimate the noise reduction amount of the position where the microphone cannot be placed at the human ear in real time; the control strategy can be changed according to the estimated noise reduction, so that the method has strong engineering application value; the method is a noise reduction amount estimation method of an active noise control system based on a virtual sensing technology, does not need to add additional hardware facilities, and is low in implementation cost; aiming at a multichannel active noise control system, signal coupling among channels is considered, so that the estimation accuracy is high, and real-time and accurate are realized; the technology is suitable for people working at fixed points in a noisy environment for a long time, such as a noise reduction system arranged in a cab and a passenger cabin of an airplane, a locomotive, an automobile and the like, and is convenient for evaluating and feeding back the performance of the noise reduction system in real time.
Compared with the related art, the method for estimating the noise reduction effect of the active noise control system can estimate the noise reduction amount of the active noise control system in real time, accurately predict the noise pressure level of the system before and after noise reduction, and is applicable to all active noise control systems based on virtual sensing technology and secondary path estimation; the noise reduction effect estimation method of the active noise control system is simple and convenient in engineering application, low in cost and high in accuracy, and does not involve additional installation of hardware.
It should be noted that the above embodiments described above with reference to the drawings are only for illustrating the present invention and not for limiting the scope of the present invention, and it should be understood by those skilled in the art that modifications or equivalent substitutions to the present invention are intended to be included in the scope of the present invention without departing from the spirit and scope of the present invention. Furthermore, unless the context indicates otherwise, words occurring in the singular form include the plural form and vice versa. In addition, unless specifically stated, all or a portion of any embodiment may be used in combination with all or a portion of any other embodiment.
Claims (1)
1. A noise reduction effect estimation method of an active noise control system comprises an active noise controller, a secondary sound source, a physical microphone and a virtual microphone; the secondary sound source is used for generating secondary sound, and the secondary sound is overlapped with the primary sound field noise signal to generate noise residual error so as to form a secondary sound field noise signal; the physical microphone is used for picking up the secondary sound field noise signal and inputting the secondary sound field noise signal to the active noise controller so as to update the output of the secondary sound source; the virtual microphone calculates the secondary sound field noise signal at the virtual microphone according to the secondary sound field noise signal picked up by the physical microphone, and uses the physical microphone to replace the secondary sound field noise signal in a path modeling stage, and the method is characterized by comprising the following steps:
s1, determining a target measurement point, enabling the target measurement point to be spaced from the physical microphone, setting the virtual microphone at the target measurement point, and placing the physical microphone at the position point of the virtual microphone for virtual path modeling;
s2, acquiring a physical path, and modeling a virtual path by combining the physical path to obtain a virtual path transfer function estimated value; wherein modeling includes modeling a physical secondary path H p Virtual secondary path H v And virtual path H pv Performing actual modeling to obtain a corresponding physical secondary path estimation modelVirtual sub-path estimation model->And virtual channel estimation model->
S3, estimating a primary sound field sound signal and a secondary sound field noise signal at the position of the virtual microphone; estimating a current noise value and a noise reduction amount according to the estimated primary sound field sound signal and the secondary sound field noise signal; in the step S2, defining the number of secondary sound sources as l, the number of physical microphones as m and the number of virtual microphones as n; physical microphone E in primary sound field environment 1 、…、E m The signals are d respectively p1 (i)、…、d pm (i) Virtual microphone E v1 、…、E vn The signals are d respectively v1 (i)、…、d vn (i) Virtual path H pv11 、…、H pv1n 、…、H pvm1 、…、H pvmn The estimation models of (a) are respectively The method specifically comprises the following steps:
modeling a secondary path, namely sequentially playing preset sound sources through the l secondary sound sources, simultaneously receiving signals of the preset sound sources by all physical microphones distributed at the physical microphone positions and the virtual microphone positions, and completing transfer function calculation from the secondary sound sources to the physical microphones and the virtual microphones, thereby completing modeling of the secondary path and obtaining a physical secondary path estimation modelAnd virtual sub-path estimation model->
Virtual path modeling, namely, real-time noise signals collected by all physical microphones and distributed at the physical microphone positions in an actual noise field are used for completing transfer function calculation from the physical microphones to the virtual microphones, and virtual path modeling is completed to obtain a virtual path estimation model
In step S3, specifically, the method includes:
in actual noise control, a physical microphone collects and acquires a sound field noise signal, and a physical secondary path estimation model is combinedVirtual sub-path estimation model->And virtual channel estimation model->Completing noise signal estimation of the virtual microphone position to obtain a primary sound field and a secondary sound field of the virtual microphone position;
order the
In a baseE p 、/>Y represents a physical microphone primary sound field signal estimated value, a virtual microphone primary sound field signal estimated value, a physical microphone real-time noise signal, a virtual microphone noise signal estimated value and a secondary sound source output signal respectively;
1) Calculating physical microphone position desired signals
Obtaining
2) Calculating virtual microphone position desired signals
The virtual microphone signal estimation values obtained by the physical microphone signal and the virtual channel estimation model are respectivelyThen there is
Obtaining
3) Calculating an estimate of a virtual microphone noise signal
Calculating an estimated value of the output signal of the secondary sound source of the virtual microphone:
calculating a virtual microphone noise signal estimate:
i.e.
Thereby obtaining the following steps:
4) Calculating primary and secondary sound field sound pressure levels at virtual microphone locations
The calculation formula of the sound pressure level is:wherein p is ref ＝2.0×10 -5 Calculating noise sound pressure level L of primary sound field and secondary sound field at nth virtual microphone position dvn And L evn ：
Wherein d is vn (i) The expected signal at a certain moment of the nth virtual microphone is the noise sound pressure level before noise reduction;
wherein e vn (i) An error signal at a certain moment of the nth virtual microphone, namely the noise sound pressure level after noise reduction;
5) Calculating sound pressure levels before and after noise reduction of the active noise control system
Noise reduction front sound pressure level
Sound pressure level after noise reduction
6) Calculating the noise reduction amount of the active noise control system
Calculating the noise reduction amount L at the nth virtual microphone Δn ：
Calculating the average noise reduction of the active noise control system:
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