CN115267670A - Method and system for identifying rotating dynamic sound source in non-uniform flow field - Google Patents
Method and system for identifying rotating dynamic sound source in non-uniform flow field Download PDFInfo
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Abstract
The invention provides a method for identifying a rotary moving sound source in a non-uniform flow field, which comprises the steps of firstly, collecting and storing a sound source signal in rotary motion in the non-uniform flow field by using a microphone array, then calculating signal interpolation weight according to the rotating speed of the sound source signal to perform linear interpolation on the sound signal collected by a microphone to form an interpolation signal, converting the interpolation signal into a moving coordinate system synchronously rotating with the sound source signal to form a sound pressure vector, constructing a rotary sound source acoustic inverse problem under the non-uniform flow condition based on the sound pressure vector, and then solving the acoustic inverse problem based on a predetermined regularization parameter to obtain the position and the strength of the sound source signal so as to realize the identification of the rotary moving sound source under the non-uniform flow condition; therefore, the high-resolution rotary motion sound source identification is realized, and an accurate result can be obtained under the condition of containing noise.
Description
Technical Field
The invention relates to the technical field of acoustic signal processing, in particular to a method and a system for identifying a rotating moving sound source in a non-uniform flow field.
Background
The sound source identification technology based on the microphone array measurement has wide application prospects, such as noise source positioning, mechanical health monitoring, aerodynamic performance experiments and the like, can generate visual sound images through array signal processing and reflect the spatial information of a sound source, and the common sound source identification technology comprises a wave beam forming method, a deconvolution method, a subspace method and the like. However, these techniques are all established based on the assumption of stationarity of the sound source, and the sound source is considered to be stationary without considering factors such as the movement of the sound source and the influence of an external flow field on a sound-transmitting medium, so that an erroneous result is obtained when the moving sound source in a non-uniform flow field is identified, and the characteristics such as the position and the intensity of the sound source cannot be correctly identified.
The rotary motion sound source is a typical motion sound source, rotates around a fixed center, and is widely used in rotary machines such as wind driven generators, axial flow fans, gear boxes and the like, so that identification of the rotary motion sound source is of great significance, but the rotary motion sound source cannot be effectively identified only by adopting the technology. In order to solve the problem, a transient signal segmentation processing technology is proposed, which divides a multichannel signal to be processed into a series of subsections, considers that a sound source in each subsection is approximately static, and then performs acoustic imaging by adopting a conventional sound source identification method. The modal decomposition method decomposes an acoustic signal generated by a rotary motion sound source into superposition of a series of modes, frequency deviation is carried out on signal components corresponding to each mode in a modal domain according to the rotating speed of the sound source, and signal non-stationarity caused by the rotation of the sound source is attempted to be eliminated. Another technique for identifying a rotating sound source is a virtual rotating array method, which converts signals collected by a microphone array into a moving coordinate system rotating synchronously with the sound source, and identifies the signals in the moving coordinate system in which the sound source and the microphone array are relatively static, so as to overcome the adverse effect of the motion of the sound source on the identification of the sound source. In addition, in the prior art, the condition of a sound source in a uniform flow field is considered, and a transmission function can be corrected according to a sound field modeling and decomposition theory under the condition of uniform flow so as to eliminate the influence of the uniform flow field in a medium on sound propagation. However, the uniform flow field is an idealized mathematical model, and in real conditions, the ideal conditions are almost not completely met, and most of the actually existing flow field flows are non-uniform, so that the identification of the rotary motion sound source in the non-uniform flow field has strong practical significance. On the other hand, the prior art is not suitable for a wider non-uniform flow field in reality, and the widely adopted deconvolution method has the defects of low identification resolution and poor sound source identification accuracy under a noise condition. Therefore, the existing rotary sound source identification technology still has many defects, and the requirement for accurately identifying the rotary sound source cannot be completely met under the condition of the existence of the non-uniform flow field.
Therefore, a method and a system for identifying a rotational motion sound source in a non-uniform flow field, which are capable of eliminating the influence of the motion of the sound source on the signal stability, improving the identification performance of the rotational motion sound source, improving the accuracy of sound source identification under actual conditions, realizing high-resolution rotational motion sound source identification and obtaining accurate results under the condition of noise, are urgently needed.
Disclosure of Invention
In view of the above problems, the present invention provides a method for identifying a rotating dynamic sound source in a non-uniform flow field, so as to solve the following problems in the prior art: the length of a suitable signal segment under practical conditions is difficult to determine by one method, and particularly when a sound source moving at high speed is identified, the assumption that the sound source is approximately static in the method is difficult to satisfy, so that the first method has great limitation on identifying a rotary motion sound source; in the other method, a special function is used for approximating the transmission function of the sound field in modal decomposition, so that the approximation accuracy is influenced by the number of function expansion terms, and the second method has low efficiency of numerical calculation and insufficient practicability for practical scenes such as mechanical health monitoring, pneumatic acoustic testing and the like; the third method is almost free from the situation that the uniform flow field completely meets the ideal condition in the real condition, and the flow of most of the actually existing flow fields is non-uniform, so that the method is not suitable for the real wider non-uniform flow field, and the widely adopted deconvolution method has the defects of low identification resolution and poor sound source identification accuracy under the noise condition.
The invention provides a method for identifying a rotary dynamic sound source in a non-uniform flow field, which comprises the following steps:
collecting and storing sound source signals in a rotary motion in a non-uniform flow field by using a microphone array;
calculating an angle compensation value of a microphone in the microphone array according to the rotating speed of the sound source signal; acquiring a signal interpolation weight according to the angle compensation value, performing linear interpolation on the sound signal acquired by the microphone according to the signal interpolation weight to form an interpolation signal, and converting the interpolation signal into a dynamic coordinate system which rotates synchronously with the sound source signal;
converting the interpolation signal in the moving coordinate system to a frequency domain by utilizing discrete Fourier transform to form a sound pressure vector, and constructing a rotary sound source acoustic inverse problem under the non-uniform flow condition based on the sound pressure vector;
and solving the acoustic inverse problem based on the predetermined regularization parameters to obtain the position and the strength of the sound source signal, so as to realize the identification of the rotary moving sound source under the non-uniform flow condition.
Preferably, the microphone array comprises a microphone array with M microphones; wherein the content of the first and second substances,
time domain signals p with the same length collected by each microphone in the microphone arraym(t) (M =1,2, \8230;, M) constitutes a sound pressure matrix P = [ P ]1(t),p2(t),…,pM(t)]T(ii) a m represents each microphone in the microphone array.
Preferably, an angle compensation value of a microphone is calculated according to the rotation speed of the sound source signal; the process of obtaining the signal interpolation weight according to the angle compensation value comprises the following steps:
defining a position right above the microphone array as an initial position, and taking a clockwise direction of the microphone array as a positive direction to calculate a position angle of each microphone in the microphone array
Calculating the sound source from the collection time t according to the rotation angular velocity Lambda of the sound source signal0To the sampling instant t1Angle of rotation of the middle
And calculating an angle compensation value theta of each microphone according to the angle and the rotation anglem＝θm0+ α; and, determining a microphone number required for signal interpolation according to the periodicity of the rotation angle:
wherein the content of the first and second substances,
meaning taking the largest integer no greater than x,
representing that the minimum integer not less than x is taken, mod represents the remainder;
calculating a signal interpolation weight p of the microphone acquisition signal at each sampling instant based on the angle compensation value and the rotation angle2：
ρ2＝1-ρ1。
Preferably, in the process of linearly interpolating the acoustic signal collected by the microphone based on the signal interpolation weight to form an interpolated signal, and converting the interpolated signal into a moving coordinate system rotating in synchronization with the sound source signal,
the interpolation signal under the moving coordinate system is: p is a radical ofmV(t)＝ρ1pm2(t)+ρ2pm1(t)；
Wherein p ism1(t) is a microphone m1The collected signal, pm2(t) is a microphone m2The collected signals.
Preferably, the process of converting the interpolated signal in the moving coordinate system into a frequency domain by using a discrete fourier transform to form a sound pressure vector includes:
converting the interpolated signal to the frequency domain using a discrete fourier transform to form a frequency domain signal:
according to a preselected frequency fcExtracting corresponding frequency components in the frequency domain signal to form a sound pressure vector:
preferably, the process of constructing the inverse acoustic problem of the rotating sound source under the non-uniform flow condition based on the sound pressure vector comprises:
determining a sound source reconstruction area based on the microphone array and discretizing to form a reconstruction network;
performing series expansion on the velocity potentials of the position of the microphone and the position of the reconstruction grid to obtain a Fourier expansion;
and calculating equivalent wave number and harmonic coefficient based on the Fourier expansion, establishing a transmission matrix, and forming a rotary sound source acoustic inverse problem under the condition of non-uniform flow.
Preferably, a sound source reconstruction area is determined based on the microphone array and discretized to form a reconstruction network; the process of performing series expansion on the velocity potentials of the position of the microphone and the position of the reconstruction grid to obtain a fourier expansion includes:
creating a coordinate system based on the microphone array, and taking the center of the microphone array as the origin of the coordinate system to obtain the position coordinate r of each microphonem＝(Xmcosθmsinφm,Xmcosθmcosφm,Xmsinθm)；
Determining a position coordinate r of a reconstruction network based on the position coordinates of the individual microphonesn＝(X’ncosθ’nsinφ’n,X’ncosθ’ncosφ’n,X’nsinθ’n) (N =1,2, \ 8230;, N), and performing a series expansion of the velocity potentials at the location of the microphone and at the location of the reconstruction grid to obtain a microphone fourier expansion and a reconstruction grid fourier expansion, respectively; wherein, the first and the second end of the pipe are connected with each other,
the microphone fourier expansion is:
wherein the coefficient of the number of stages
Is an imaginary unit.
The reconstructed network fourier expansion is:
wherein the coefficient of the number of stages
Preferably, in the process of calculating equivalent wave number and harmonic coefficient based on the fourier expansion to establish a transmission matrix to form a rotating sound source acoustic inverse problem under the non-uniform flow condition, the method includes:
establishing an acoustic inverse problem under non-uniform flow conditions in a pre-acquired rotational coordinate system based on the Fourier expansion:
p＝Gq+k
wherein q = [ q ]1,q2,…,qN]TIs a sound source intensity vector, each element in the sound source intensity vector representing the sound source intensity of each reconstruction grid point in the reconstruction grid; k = [ k =1,k2,…,kM]TIs a noise vector; the transmission matrix G of size mxn comprises the elements:
wherein the equivalent wave number is
Harmonic coefficient of
ξn() Is a Bessel function of a first ball of order n;
Preferably, the process of solving the acoustic inverse problem based on the predetermined regularization parameter to obtain the position and the strength of the sound source signal to identify the rotating moving sound source under the condition of non-uniform flow includes:
determining a regularization parameter λ>0, rewriting the acoustic inverse problem by a 1-norm sparse regularization method to form a normalized inverse problem
Solving the standardized inverse problem by adopting a CVX optimization tool box based on an MATLAB platform to obtain a value of a sound source intensity vector q; wherein the non-zero element index in the values of the sound source intensity vector q represents the position where the sound source signal is located, and the numerical value of the element represents the intensity of the sound source signal.
On the other hand, the invention also provides a system for identifying the rotary motion sound source in the non-uniform flow field, which realizes the method for identifying the rotary motion sound source in the non-uniform flow field, and comprises the following steps:
the signal acquisition unit is used for acquiring and storing sound source signals which rotate in the non-uniform flow field by using the microphone array;
the signal compensation unit is used for calculating an angle compensation value of a microphone in the microphone array according to the rotating speed of the sound source signal; acquiring a signal interpolation weight according to the angle compensation value, performing linear interpolation on the sound signal acquired by the microphone according to the signal interpolation weight to form an interpolation signal, and converting the interpolation signal into a dynamic coordinate system which rotates synchronously with the sound source signal;
the inverse problem construction unit is used for converting the interpolation signal in the moving coordinate system into a frequency domain by utilizing discrete Fourier transform to form a sound pressure vector and constructing a rotary sound source acoustic inverse problem under the non-uniform flow condition based on the sound pressure vector;
and the inverse problem solving unit is used for solving the acoustic inverse problem based on the predetermined regularization parameters so as to obtain the position and the strength of the sound source signal, and realizing the identification of the rotary moving sound source under the non-uniform flow condition.
According to the technical scheme, the method for identifying the rotating dynamic sound source in the non-uniform flow field comprises the steps of firstly collecting and storing a sound source signal which rotates in the non-uniform flow field by using a microphone array, and then calculating an angle compensation value of a microphone according to the rotating speed of the sound source signal; acquiring a signal interpolation weight according to the angle compensation value, performing linear interpolation on an acoustic signal acquired by a microphone according to the signal interpolation weight to form an interpolation signal, converting the interpolation signal into a moving coordinate system which rotates synchronously with the acoustic source signal, converting the interpolation signal in the moving coordinate system into a frequency domain by using discrete Fourier transform to form a sound pressure vector, constructing a rotary acoustic source acoustic inverse problem under the non-uniform flow condition based on the sound pressure vector, and solving the acoustic inverse problem based on a predetermined regularization parameter to acquire the position and the intensity of the acoustic source signal to realize the identification of the rotary moving acoustic source under the non-uniform flow condition; therefore, the signals collected by the microphones in the array are subjected to synchronous motion conversion in an interpolation mode, the discrete signals can be conveniently subjected to numerical calculation, the influence of the motion of the sound source on the signal stability is eliminated, the rotary motion sound source is favorably identified, and conditions are created for the application of the sound source identification method under the existing stable conditions; the potential function of the non-uniform flow field is decomposed by using a special function and a series expansion mode, so that a sound source item and other items in the acoustic inverse problem are decoupled, the problem that the prior art is not suitable for sound source identification in the non-uniform flow field condition is solved, and the accuracy of sound source identification in the actual condition is improved; meanwhile, the method can be used for observing signals in a non-uniform flow field which widely exists in practical conditions, and the acoustic inverse problem is solved by a sparse regularization method, so that the high-resolution rotary motion sound source identification is realized, and an accurate result can be obtained under the condition of noise.
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Other objects and results of the present invention will become more apparent and readily appreciated by reference to the following specification taken in conjunction with the accompanying drawings, and as the invention becomes more fully understood. In the drawings:
FIG. 1 is a flow chart of a method for identifying a source of a rotational motion sound in a non-uniform flow field according to an embodiment of the present invention;
FIG. 2 is a flow chart of an embodiment of a method for identifying a source of a rotational motion in a non-uniform flow field according to the present invention;
FIG. 3 is a schematic diagram of an acoustic inverse problem model in a method for identifying a rotating moving sound source in a non-uniform flow field according to an embodiment of the present invention;
FIG. 4 is a numerical simulation condition in an embodiment of a method for identifying a rotational motion sound source in a non-uniform flow field according to the present invention;
fig. 5 is a numerical simulation result in an embodiment of a method for identifying a rotational motion sound source in a non-uniform flow field according to an embodiment of the present invention;
fig. 6 is a block diagram of a system for identifying a rotating sound source in a non-uniform flow field according to an embodiment of the present invention.
Detailed Description
At present, the prior art has the following problems: the length of a suitable signal segment under actual conditions is difficult to determine by one method, especially when identifying a sound source moving at a high speed, the assumption that the sound source is approximately static in the method is difficult to satisfy, so that the first method has great limitation in identifying a sound source moving in a rotating manner; in the other method, a special function is used for approximating the transmission function of the sound field in modal decomposition, so that the approximation accuracy is influenced by the number of function expansion terms, and the second method has low efficiency of numerical calculation and insufficient practicability for practical scenes such as mechanical health monitoring, pneumatic acoustic testing and the like; the third method is almost free from the situation that the uniform flow field completely meets the ideal condition in the real condition, and the flow of most of the actually existing flow fields is non-uniform, so that the method is not suitable for the real wider non-uniform flow field, and the widely adopted deconvolution method has the defects of low identification resolution and poor sound source identification accuracy under the noise condition.
In view of the above problems, the present invention provides a method for identifying a rotating moving sound source in a non-uniform flow field, and the following describes in detail a specific embodiment of the present invention with reference to the accompanying drawings.
In order to illustrate the method and system for identifying a rotational motion sound source in a non-uniform flow field provided by the present invention, fig. 1-5 exemplarily mark the method for identifying a rotational motion sound source in a non-uniform flow field according to the embodiment of the present invention; fig. 6 shows an exemplary identification of a system for identifying a rotating sound source in a non-uniform flow field according to an embodiment of the present invention.
The following description of the exemplary embodiment(s) is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses. Techniques and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail, but are intended to be part of the specification where appropriate.
As shown in fig. 1, fig. 2, fig. 3, fig. 4, and fig. 5, the present invention provides a method for identifying a rotating dynamic sound source in a non-uniform flow field, including:
s1: collecting and storing sound source signals in a rotary motion in a non-uniform flow field by using a microphone array;
s2: calculating an angle compensation value of a microphone in a microphone array according to the rotating speed of the sound source signal; acquiring a signal interpolation weight according to the angle compensation value, performing linear interpolation on the sound signal acquired by the microphone according to the signal interpolation weight to form an interpolation signal, and converting the interpolation signal into a dynamic coordinate system synchronously rotating with the sound source signal;
s3: converting the interpolation signal in the moving coordinate system to a frequency domain by utilizing discrete Fourier transform to form a sound pressure vector, and constructing a rotary sound source acoustic inverse problem under the non-uniform flow condition based on the sound pressure vector;
s4: and solving the acoustic inverse problem based on the predetermined regularization parameters to obtain the position and the strength of the sound source signal, so as to realize the identification of the rotary motion sound source under the condition of non-uniform flow.
In the embodiments shown in fig. 1, fig. 2, fig. 3, fig. 4, and fig. 5, step S1 is a process of collecting and storing a sound source signal that rotates in a non-uniform flow field by using a microphone array, in this embodiment, the microphone array includes M microphones, and the microphone array collects and stores the sound source signal that rotates in the non-uniform flow field; wherein, the first and the second end of the pipe are connected with each other,
time domain signals p with the same length collected by each microphone in the microphone arraym(t) (M =1,2, \8230;, M) constitutes a sound pressure matrix P = [ P ]1(t),p2(t),…,pM(t)]T(ii) a m represents each microphone in the microphone array.
More specifically, step S1 is to collect and store a sound source signal of a rotational motion in the non-uniform flow field by using a microphone array including M microphones, and time domain signals p with the same length collected by each microphonem(t) (M =1,2, \8230;, M) constitutes a sound pressure matrix P = [ P ]1(t),p2(t),…,pM(t)]T。
In the embodiments shown in fig. 1,2, 3, 4, and 5, step S2 is to calculate an angle compensation value of a microphone according to the rotation speed of the sound source signal; a process of obtaining a signal interpolation weight according to the angle compensation value, performing linear interpolation on the sound signal collected by the microphone according to the signal interpolation weight to form an interpolation signal, and converting the interpolation signal into a dynamic coordinate system rotating synchronously with the sound source signal; wherein, the first and the second end of the pipe are connected with each other,
calculating an angle compensation value of a microphone according to the rotating speed of the sound source signal; the process of obtaining the signal interpolation weight according to the angle compensation value comprises the following steps:
s21: defining a position right above the microphone array as an initial position, and taking a clockwise direction of the microphone array as a positive direction to calculate a position angle of each microphone in the microphone array
S22: calculating the sound source from the collection time t according to the rotation angular velocity Lambda of the sound source signal0To the sampling instant t1Angle of rotation of the middle
And calculating an angle compensation value theta of each microphone according to the angle and the rotation anglem＝θm0+ α; and, determining a microphone number required for signal interpolation according to the periodicity of the rotation angle:
wherein the content of the first and second substances,
meaning taking the largest integer no greater than x,
representing that the minimum integer not less than x is taken, mod represents the remainder;
s23: calculating a signal interpolation weight of the microphone acquisition signal at each sampling moment based on the angle compensation value and the rotation angle:
ρ2＝1-ρ1。
in linearly interpolating the acoustic signal collected by the microphone based on the signal interpolation weight to form an interpolated signal, and converting the interpolated signal into a moving coordinate system rotating in synchronization with the sound source signal,
the interpolation signal under the moving coordinate system is: p is a radical of formulamV(t)＝ρ1pm2(t)+ρ2pm1(t)；
Wherein p ism1(t) is a microphone m1The collected signal, pm2(t) is a microphone m2The collected signals.
Specifically, step S2 is a process of calculating a microphone angle compensation value and a signal interpolation weight according to the rotation speed of the sound source, performing linear interpolation on the collected sound signals, and converting the signals collected by the microphones into a moving coordinate system rotating synchronously with the sound source.
More specifically, step S2 needs to perform the following steps:
step (2-a): defining the position right above the microphone array as an initial position, and the clockwise direction as a positive direction, and calculating the angle of each microphone
Step (2-b): at each signal sampling time, according to the rotation angular velocity Lambda of the sound source, calculating the sound source from the collection starting time t0To the sampling time t1Angle of rotation of the middle
Calculating an angle compensation value theta of each microphonem＝θm0+ α. Determining the number of the microphone required by signal interpolation according to the periodicity of the rotation angle:
wherein the content of the first and second substances,
meaning taking the largest integer no greater than x,
meaning taking the smallest integer no less than x, mod denotes taking the remainder.
Step (2-c): calculating interpolation weight rho of microphone collection signal at each sampling moment2：
ρ2＝1-ρ1 (4)
Performing linear interpolation on the sound signals, and converting the signals collected by each microphone into a dynamic coordinate system synchronously rotating with the sound source:
pmV(t)＝ρ1pm2(t)+ρ2pm1(t) (5)
wherein p ism1(t) is a microphone m1The collected signal, pm2(t) is a microphone m2The collected signals.
In the embodiments shown in fig. 1, fig. 2, fig. 3, fig. 4, and fig. 5, step S3 is a process of converting the interpolated signal in the moving coordinate system to the frequency domain by using discrete fourier transform to form a sound pressure vector, and constructing the inverse acoustic problem of the rotating sound source under the non-uniform flow condition based on the sound pressure vector; in this embodiment, the process of converting the interpolated signal in the moving coordinate system to the frequency domain by using discrete fourier transform to form a sound pressure vector includes:
converting the interpolated signal to the frequency domain using a discrete fourier transform to form a frequency domain signal:
according to a preselected frequency fcExtracting corresponding frequency components in the frequency domain signal to form a sound pressure vector:
in this embodiment, the process of constructing the inverse acoustic problem of the rotating sound source under the non-uniform flow condition based on the sound pressure vector includes:
determining a sound source reconstruction area based on the microphone array and discretizing to form a reconstruction network;
performing series expansion on the velocity potentials of the position of the microphone and the position of the reconstruction grid to obtain a Fourier expansion;
and calculating equivalent wave number and harmonic coefficient based on the Fourier expansion, establishing a transmission matrix, and forming a rotary sound source acoustic inverse problem under the condition of non-uniform flow.
Determining a sound source reconstruction area based on the microphone array and discretizing to form a reconstruction network; the process of performing series expansion on the velocity potentials of the position of the microphone and the position of the reconstruction grid to obtain a fourier expansion includes:
creating a coordinate system based on the microphone array, and acquiring the position coordinate r of each microphone by taking the center of the microphone array as the origin of the coordinate systemm＝(Xmcosθmsinφm,Xmcosθmcosφm,Xmsinθm)；
Determining a position coordinate r of a reconstruction network based on the position coordinates of the individual microphonesn＝(X’ncosθ’nsinφ’n,X’ncosθ’ncosφ’n,X’nsinθ’n) (N =1,2, \ 8230;, N), and performing a series expansion of the velocity potentials at the location of the microphone and at the location of the reconstruction grid to obtain a microphone fourier expansion and a reconstruction grid fourier expansion, respectively; wherein the content of the first and second substances,
the microphone fourier expansion is:
wherein the coefficient of the number of stages
Is an imaginary unit.
The reconstructed network fourier expansion is:
wherein the coefficient of the number of stages
In the process of calculating equivalent wave number and harmonic coefficient based on the Fourier expansion, establishing a transmission matrix and forming a rotating sound source acoustic inverse problem under the condition of non-uniform flow, the method comprises the following steps:
establishing an acoustic inverse problem under the condition of non-uniform flow in the moving coordinate system based on the Fourier expansion formula:
p＝Gq+k
wherein q = [ q ]1,q2,…,qN]TIs a sound source intensity vector, each element in the sound source intensity vector representing the sound source intensity of each reconstruction grid point in the reconstruction grid; k = [ k ]1,k2,…,kM]TIs a noise vector; the transmission matrix G of size mxn comprises the elements:
wherein the equivalent wave number is
Harmonic coefficient of
ξn() Is a Bessel function of a first ball of order n;
Specifically, step S3 first converts the interpolated signal into the frequency domain using discrete fourier transform:
according to a selected frequency fcExtracting corresponding frequency components in the frequency domain signal to form a sound pressure vector
And then, determining a sound source reconstruction area, discretizing, performing series expansion on the velocity potentials of the position of the microphone and the position of the reconstruction grid, calculating equivalent wave number and harmonic coefficient in a cylindrical coordinate system, establishing a transmission matrix, and forming the acoustic inverse problem of the rotary sound source under the non-uniform flow condition.
More specifically, step S3 performs the following steps:
step (3-a): determining a sound source reconstruction area, discretizing, dividing the reconstruction area into N reconstruction grids, and establishing a seat as shown in figure 2A coordinate system with origin coordinates at the center of the microphones and position coordinates of each microphone as rm＝(Xmcosθmsinφm,Xmcosθmcosφm,Xmsinθm) The position coordinates of the reconstruction grid are r'n＝(X’ncosθ’nsinφ’n,X’ncosθ’ncosφ’n,X’nsinθ’n) (N =1,2, \8230;, N). Performing Fourier expansion on the velocity potential of the position where the microphone is located:
wherein the coefficient of the number of stages
Is an imaginary unit.
Performing Fourier series expansion on the velocity potential of the position of the reconstruction grid:
wherein the coefficient of the number of stages
Step (3-b): recording the Mach number of the flow field as Ma, c0＝1,cβ＝–j2πfcMaФβ’/c(β≠0)，d0＝1,dβ＝j2πfcMaФ–βC (β ≠ 0), sets up the acoustic inverse problem under non-uniform flow conditions in a rotating coordinate system:
p＝Gq+k (9)
where c is the speed of sound, q = [ q ]1,q2,…,qN]TIs a sound source intensity vector, each element represents the sound source intensity of the reconstructed mesh point, k = [ k =1,k2,…,kM]TIs the direction of noiseThe transmission matrix G of size mxn comprises the elements:
wherein the equivalent wave number
Harmonic coefficient
ξn() Is an n-th order first ball Bessel function,
is a second-class spherical Hankel function of n orders, a polynomial product term
Is the | alpha | and n-order continuous Legendre function.
In the embodiments shown in fig. 1, fig. 2, fig. 3, fig. 4, and fig. 5, step S4 is a process of solving the inverse acoustic problem based on a predetermined regularization parameter to obtain a position and an intensity of the sound source signal, so as to identify a rotational moving sound source under a non-uniform flow condition; wherein the content of the first and second substances,
solving the acoustic inverse problem based on predetermined regularization parameters to obtain the position and intensity of the sound source signal, realizing the process of identifying the rotary moving sound source under the condition of non-uniform flow, comprising:
determining a regularization parameter λ>0, rewriting the acoustic inverse problem by a 1-norm sparse regularization method to form a normalized inverse problem
Solving the standardized inverse problem by adopting a CVX (composite matrix laboratory) optimization tool box based on an MATLAB (matrix laboratory) platform to obtain a value of a sound source intensity vector q; wherein the non-zero element index in the values of the sound source intensity vector q represents the position where the sound source signal is located, and the numerical value of the element represents the intensity of the sound source signal.
Specifically, step S4 is to first determine a regularization parameter λ >0, and rewrite the acoustic inverse problem into the following form by using a 1-norm sparse regularization method:
the problems are solved by adopting a CVX optimization tool box based on an MATLAB platform, so that a sound source intensity vector q is obtained, the non-zero element index in the vector q represents the position of a sound source, and the numerical value of the element represents the sound source intensity, so that the rotary moving sound source under the condition of non-uniform flow is identified.
The numerical simulation conditions are shown in FIG. 4, three frequencies fcA point sound source of =4000Hz rotates counterclockwise (as viewed from the positive z-axis direction) around O ' (0 m, 0.75m) at an angular velocity of Λ =80 π rad/s in the X ' -y ' plane with a radius of rotation Xs=0.2M, the sound source intensity is 80dB, M =52 uniformly distributed microphones are included in the microphone array parallel to the sound source rotation plane, the center of the array is located at the coordinate origin O (0m, 0m), and the radius X of the array ism=0.6m, an infinitely long rigid cylinder is placed between the source and the array, with radius a =0.2m, with the center of the section in the y-z plane at O "(0 m,0.4 m), and a uniform potential flow in the x-z plane flows along an angle α =20 °, creating a non-uniform flow field around the cylinder due to interference of the cylinder with the air flow. And selecting a reconstruction area as a rectangular area with x being more than or equal to-0.5 m and less than or equal to 0.5m and y being more than or equal to-0.5 m and less than or equal to 0.5m in a plane where a sound source is positioned, and dividing the rectangular area into N =1681 reconstruction grids which are uniformly distributed. Gaussian noise is added to the signal collected by the microphone to make the signal-to-noise ratio
Where n is noise, the regularization parameter λ =0.5 is set empirically.
In the method for identifying the rotary moving sound source in the non-uniform flow field, the sound source identification result is shown in fig. 5, the rectangular frame represents the real position of the sound source, and it can be seen that three sound sources can be identified at the real position, the sound source positioning error is very small, the intensity estimated values of the three sound sources are 78.1dB close to the real intensity, and the relative error is 1.9%. The above results indicate that the technical scheme in the method for identifying the rotating dynamic sound source in the non-uniform flow field in the embodiment of the invention can realize accurate positioning of the rotating dynamic sound source in the non-uniform flow field and estimation of the intensity of the sound source, and can obtain very accurate identification results under the condition of containing noise.
In summary, the method for identifying the rotary moving sound source in the non-uniform flow field, provided by the invention, comprises the steps of firstly collecting and storing a sound source signal in rotary motion in the non-uniform flow field by using a microphone array, and then calculating an angle compensation value of a microphone according to the rotating speed of the sound source signal; acquiring a signal interpolation weight according to the angle compensation value, performing linear interpolation on an acoustic signal acquired by a microphone according to the signal interpolation weight to form an interpolation signal, converting the interpolation signal into a moving coordinate system which rotates synchronously with the acoustic source signal, converting the interpolation signal in the moving coordinate system into a frequency domain by using discrete Fourier transform to form a sound pressure vector, constructing a rotary acoustic source acoustic inverse problem under the non-uniform flow condition based on the sound pressure vector, and solving the acoustic inverse problem based on a predetermined regularization parameter to acquire the position and the intensity of the acoustic source signal to realize the identification of the rotary moving acoustic source under the non-uniform flow condition; therefore, the signals collected by the microphones in the array are subjected to synchronous motion conversion in an interpolation mode, the discrete signals can be conveniently subjected to numerical calculation, the influence of the motion of the sound source on the signal stability is eliminated, the rotary motion sound source is favorably identified, and conditions are created for the application of the sound source identification method under the existing stable conditions; the potential function of the non-uniform flow field is decomposed by using a special function and a series expansion mode, so that a sound source item and other items in the acoustic inverse problem are decoupled, the problem that the prior art is not suitable for sound source identification in the non-uniform flow field condition is solved, and the accuracy of sound source identification in the actual condition is improved; meanwhile, the method can be used for observing signals in a non-uniform flow field which widely exists in practical conditions, and the acoustic inverse problem is solved by a sparse regularization method, so that the high-resolution rotary motion sound source identification is realized, and an accurate result can be obtained under the condition of noise.
As shown in fig. 6, the present invention further provides a system 100 for identifying a rotational moving sound source in an uneven flow field, so as to implement the method for identifying a rotational moving sound source in an uneven flow field, including:
the signal acquisition unit 101 is used for acquiring and storing sound source signals which rotate in a non-uniform flow field by using a microphone array;
a signal compensation unit 102, configured to calculate an angle compensation value of a microphone in a microphone array according to a rotation speed of the sound source signal; acquiring a signal interpolation weight according to the angle compensation value, performing linear interpolation on an acoustic signal acquired by a microphone according to the signal interpolation weight to form an interpolation signal, and converting the interpolation signal into a dynamic coordinate system which rotates synchronously with the acoustic source signal;
an inverse problem constructing unit 103, configured to convert the interpolation signal in the moving coordinate system to a frequency domain by using discrete fourier transform, so as to form a sound pressure vector, and construct a rotary sound source acoustic inverse problem under a non-uniform flow condition based on the sound pressure vector;
and the inverse problem solving unit 104 is configured to solve the acoustic inverse problem based on a predetermined regularization parameter to obtain a position and intensity of the sound source signal, so as to identify a rotational moving sound source under a non-uniform flow condition.
The specific implementation method is not specifically limited, and will not be described herein again, and reference may be made to a specific embodiment of the method for identifying a rotating moving sound source in a non-uniform flow field.
As described above, in the system for identifying a rotary moving sound source in a non-uniform flow field, firstly, the signal acquisition unit 101 acquires and stores a sound source signal in a rotary motion in the non-uniform flow field by using the microphone array, and then the signal compensation unit 102 calculates an angle compensation value of the microphone according to the rotation speed of the sound source signal; acquiring a signal interpolation weight according to the angle compensation value, performing linear interpolation on an acoustic signal acquired by a microphone according to the signal interpolation weight to form an interpolation signal, converting the interpolation signal into a moving coordinate system which rotates synchronously with the acoustic source signal, converting the interpolation signal in the moving coordinate system into a frequency domain by using discrete Fourier transform through an inverse problem construction unit 103 to form an acoustic pressure vector, constructing a rotating acoustic source acoustic inverse problem under a non-uniform flow condition based on the acoustic pressure vector, and solving the acoustic inverse problem through an inverse problem solving unit 104 based on a predetermined regularization parameter to acquire the position and the intensity of the acoustic source signal, so that the identification of the rotating moving acoustic source under the non-uniform flow condition is realized; therefore, the signals collected by the microphones in the array are subjected to synchronous motion conversion in an interpolation mode, the discrete signals can be conveniently subjected to numerical calculation, the influence of the motion of the sound source on the signal stability is eliminated, the rotary motion sound source is favorably identified, and conditions are created for the application of the sound source identification method under the existing stable conditions; the potential function of the non-uniform flow field is decomposed by using a special function and a series expansion mode, so that a sound source item and other items in the acoustic inverse problem are decoupled, the problem that the prior art is not suitable for sound source identification in the non-uniform flow field condition is solved, and the accuracy of sound source identification in the actual condition is improved; meanwhile, the method can be used for observing signals in a non-uniform flow field which widely exists in practical conditions, and the acoustic inverse problem is solved by a sparse regularization method, so that the high-resolution rotary motion sound source identification is realized, and an accurate result can be obtained under the condition of noise.
The system and method for identifying a rotating sound source in a non-uniform flow field according to the present invention are described above by way of example with reference to the accompanying drawings. However, it will be understood by those skilled in the art that various modifications may be made to the system and method for identifying a rotational motion sound source in a non-uniform flow field, which are proposed by the present invention, without departing from the scope of the present invention. Accordingly, the scope of the invention should be determined from the content of the appended claims.
Claims (10)
1. A method for identifying a rotary moving sound source in a non-uniform flow field is characterized by comprising the following steps:
collecting and storing sound source signals which rotate in a non-uniform flow field by using a microphone array;
calculating an angle compensation value of a microphone in the microphone array according to the rotating speed of the sound source signal; acquiring a signal interpolation weight according to the angle compensation value, performing linear interpolation on the sound signal acquired by the microphone according to the signal interpolation weight to form an interpolation signal, and converting the interpolation signal into a dynamic coordinate system synchronously rotating with the sound source signal;
converting the interpolation signal in the moving coordinate system to a frequency domain by utilizing discrete Fourier transform to form a sound pressure vector, and constructing a rotary sound source acoustic inverse problem under the non-uniform flow condition based on the sound pressure vector;
and solving the acoustic inverse problem based on the predetermined regularization parameters to obtain the position and the strength of the sound source signal, so as to realize the identification of the rotary moving sound source under the non-uniform flow condition.
2. The method for identifying a rotating dynamic sound source in a non-uniform flow field according to claim 1, wherein the microphone array comprises a microphone array with M microphones; wherein, the first and the second end of the pipe are connected with each other,
time domain signals p with the same length collected by all microphones in the microphone arraym(t) (M =1,2, \8230;, M) constitutes a sound pressure matrix P = [ P ]1(t),p2(t),…,pM(t)]T(ii) a m represents each microphone in the microphone array.
3. The method for identifying a rotating moving sound source in a non-uniform flow field according to claim 2, wherein an angle compensation value of a microphone is calculated according to the rotating speed of the sound source signal; the process of obtaining the signal interpolation weight according to the angle compensation value comprises the following steps:
defining a position right above the microphone array as an initial position, and taking the clockwise direction of the microphone array as a positive direction to calculate the angle of each microphone in the microphone array
Calculating the time t from the collection of the sound source according to the rotation angular velocity Lambda of the sound source signal0To the sampling time t1Angle of rotation of the middle
And calculating an angle compensation value theta of each microphone according to the angle and the rotation anglem＝θm0+ α; and, determining a microphone number required for signal interpolation according to the periodicity of the rotation angle:
wherein the content of the first and second substances,
meaning taking the largest integer no greater than x,
representing that the minimum integer not less than x is taken, mod represents the remainder;
calculating a signal interpolation weight p of the microphone acquisition signal at each sampling instant based on the angle compensation value and the rotation angle2：
ρ2＝1-ρ1。
4. The method for identifying a rotating moving sound source in a non-uniform flow field according to claim 3, wherein in the process of linearly interpolating the acoustic signals collected by the microphones based on the signal interpolation weights to form interpolated signals and converting the interpolated signals into a moving coordinate system rotating synchronously with the sound source signals,
the interpolation signal under the moving coordinate system is: p is a radical ofmV(t)＝ρ1pm2(t)+ρ2pm1(t)；
Wherein p ism1(t) is a microphone m1The collected signal, pm2(t) is a microphone m2The collected signals.
5. The method for identifying a rotating moving sound source in a non-uniform flow field according to claim 4, wherein the process of converting the interpolated signal in the moving coordinate system into a frequency domain by using discrete fourier transform to form a sound pressure vector comprises:
converting the interpolated signal to the frequency domain using a discrete fourier transform to form a frequency domain signal:
according to a preselected frequency fcExtracting corresponding frequency components in the frequency domain signal to form a sound pressure vector:
6. the method for identifying the rotating sound source in the non-uniform flow field according to claim 5, wherein the process of constructing the acoustic inverse problem of the rotating sound source under the non-uniform flow condition based on the sound pressure vector comprises:
determining a sound source reconstruction area based on the microphone array and discretizing to form a reconstruction network;
performing series expansion on the velocity potentials of the position of the microphone and the position of the reconstruction grid to obtain a Fourier expansion;
and calculating equivalent wave number and harmonic coefficient based on the Fourier expansion, establishing a transmission matrix, and forming a rotary sound source acoustic inverse problem under the condition of non-uniform flow.
7. The method for identifying the rotary moving sound source in the non-uniform flow field according to claim 6, wherein a sound source reconstruction area is determined based on the microphone array and discretized to form a reconstruction network; the process of performing series expansion on the velocity potentials of the position of the microphone and the position of the reconstruction grid to obtain a fourier expansion includes:
creating a coordinate system based on the microphone array, and acquiring the position coordinate r of each microphone by taking the center of the microphone array as the origin of the coordinate systemm＝(Xmcosθmsinφm,Xmcosθmcosφm,Xmsinθm)；
Determining a position coordinate r of a reconstruction network based on the position coordinates of the individual microphonesn＝(X’ncosθ’nsinφ’n,X’ncosθ’ncosφ’n,X’nsinθ’n) (N =1,2, \ 8230;, N), and performing a series expansion of the velocity potentials at the location of the microphone and at the location of the reconstruction grid to obtain a microphone fourier expansion and a reconstruction grid fourier expansion, respectively; wherein the content of the first and second substances,
the microphone fourier expansion is:
wherein the coefficient of the number of stages
Is an imaginary unit.
The reconstructed network fourier expansion is:
wherein the coefficient of the order
8. The method for identifying the rotating sound source in the non-uniform flow field according to claim 7, wherein in the process of calculating equivalent wave number and harmonic coefficient based on the fourier expansion, establishing a transmission matrix, and forming an inverse problem of the rotating sound source acoustics under the non-uniform flow condition, the method comprises:
establishing an acoustic inverse problem under the condition of non-uniform flow in the moving coordinate system based on the Fourier expansion formula:
p＝Gq+k
wherein q = [ q ]1,q2,…,qN]TIs a sound source intensity vector, each element in the sound source intensity vector representing the sound source intensity of each reconstruction grid point in the reconstruction grid; k = [ k ]1,k2,…,kM]TIs a noise vector; the transmission matrix G of size mxn comprises the elements:
wherein the equivalent wave number is
Harmonic coefficient of
ξn() Is a Bessel function of a first class ball of order n;
9. The method for identifying the rotating dynamic sound source in the non-uniform flow field according to claim 8, wherein the process of solving the inverse acoustic problem based on the predetermined regularization parameters to obtain the position and the strength of the sound source signal to identify the rotating dynamic sound source under the non-uniform flow condition includes:
determining a regularization parameter λ>0, rewriting the acoustic inverse problem by a 1-norm sparse regularization method to form a normalized inverse problem
Solving the standardized inverse problem by adopting a CVX (composite matrix laboratory) optimization tool box based on an MATLAB (matrix laboratory) platform to obtain a value of a sound source intensity vector q; wherein the non-zero element index in the values of the sound source intensity vector q represents the position where the sound source signal is located, and the numerical value of the element represents the intensity of the sound source signal.
10. A system for identifying a rotational moving sound source in an uneven flow field, which is characterized by implementing the method for identifying a rotational moving sound source in an uneven flow field according to any one of claims 1 to 9, and comprises:
the signal acquisition unit is used for acquiring and storing sound source signals which rotate in the non-uniform flow field by using the microphone array;
the signal compensation unit is used for calculating an angle compensation value of a microphone in the microphone array according to the rotating speed of the sound source signal; acquiring a signal interpolation weight according to the angle compensation value, performing linear interpolation on the sound signal acquired by the microphone according to the signal interpolation weight to form an interpolation signal, and converting the interpolation signal into a dynamic coordinate system which rotates synchronously with the sound source signal;
the inverse problem construction unit is used for converting the interpolation signal in the moving coordinate system to a frequency domain by utilizing discrete Fourier transform to form a sound pressure vector and constructing a rotary sound source acoustic inverse problem under the non-uniform flow condition based on the sound pressure vector;
and the inverse problem solving unit is used for solving the acoustic inverse problem based on the predetermined regularization parameters so as to obtain the position and the strength of the sound source signal, and realizing the identification of the rotary moving sound source under the non-uniform flow condition.
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