CN1482436A - Process for identifying non-stable acoustical source characteristic applying principal component analyzing technique - Google Patents

Process for identifying non-stable acoustical source characteristic applying principal component analyzing technique Download PDF

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CN1482436A
CN1482436A CNA031294065A CN03129406A CN1482436A CN 1482436 A CN1482436 A CN 1482436A CN A031294065 A CNA031294065 A CN A031294065A CN 03129406 A CN03129406 A CN 03129406A CN 1482436 A CN1482436 A CN 1482436A
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蒋伟康
万泉
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Shanghai Jiaotong University
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Abstract

A process for identifying non-stable acoustical source characteristic applying principal component analyzing technique comprising, determining the number and location of the reference source, arranging the reference source microphone array to extract the reference source signal, then designing the microphone array to perform scanning survey to the holographic plane, gathering holographic plane data, then using principal component analysis technique of the circulating stable acoustic field for separating the part acoustic field of the acoustic source, and by rebuilding holographic near-field of the circulation stable acoustic field, a three-dimensional sound field distribution can also be obtained, thus realizing the vision of the acoustic source route of transmission.

Description

Adopt the method for principal component analysis (PCA) technology identification non-stationary sound source characteristic
Technical field
What the present invention relates to is a kind of method of identifying sound source characteristic, and particularly a kind of method of utilizing the principal component analysis (PCA) part sound field separation technique identification non-stationary sound source characteristic of cyclo-stationary sound field belongs to noise field in the physics class.
Background technology
Understanding to the noise source characteristic is the prerequisite of control noise, therefore, in order to control noise effectively, before noise reduction measure is implemented, must at first carry out the noise source diagnosis, determines each position, overriding noise seedbed, and characteristic.Along with the development of modern signal processing technology ground, spectral analysis technology, relevant and partial coherence analysis technology, sound intensity analytical technology and sound near-field holography technology etc. have obtained developing by leaps and bounds.Find by literature search, M.A.Tomlinson is at " Applied Acoustics " (57 (1999): write articles " Partialsource discrimination near field acoustic holography " (" applied acoustics " 243-261), part source identification in the near field acoustic holography), this article has proposed the part sound source isolation technics of near field acoustic holography principal component analysis (PCA), can diagnose noise source effectively.But these technology can only be analyzed steady sound field, therefore, are necessary to propose new technology, are used for the analysis of non-stationary sound field.Yet, for general non-stationary sound field, become when the statistical property parameter of acoustical signal is, thereby also replace ensemble average with regard to unrenewable time average, make data acquisition very difficult, be difficult to analyze the characteristic of sound field.
The cyclo-stationary signal is the special non-stationary signal of a class because the cyclic stationary of self uniqueness, make single acquisition to record have the cycle ergodic property, overcome this defective of non-stationary signal, simplified the difficulty that non-stationary signal is analyzed.The cyclo-stationary signal has crucial realistic meaning in engineering is used, for example rotating machinery is because the physical arrangement of symmetry or near symmetrical and periodic working motion pattern, its sound field has the obvious periodic time varying characteristic, and acoustical signal has cyclostationarity.In further retrieving, find as yet and the identical or similar bibliographical information of theme of the present invention.
Summary of the invention
The objective of the invention is to overcome deficiency of the prior art, a kind of method that adopts principal component analysis (PCA) technology identification non-stationary sound source characteristic is provided, achieve and obtain the part sound field that each sound source forms respectively, near-field holography by the cyclo-stationary sound field is rebuild, can also obtain three-dimensional sound field by the measurement data on the plane and distribute, realize that each sound source route of transmission is visual.
The present invention is achieved by the following technical solutions, the present invention is in the occasion of the steady sound field of complex loops of a plurality of sound sources generations, adopt the theoretical alternative traditional Fourier techniques of cyclo-stationary, obtain being applicable to the principal component analysis (PCA) technology of cyclo-stationary sound field, and it part sound field that is used for the cyclo-stationary sound field separated, method is as follows: at first determine the quantity and the position of reference source, and arrange and extract reference source signal by the reference source microphone array; Design microphone array again holographic facet is carried out scanning survey, gather the holographic facet data; Then, utilize the principal component analysis (PCA) technology of cyclo-stationary sound field, separate the part sound field of each sound source.
Below the inventive method is done further to limit, method step is as follows:
1, determines the quantity and the position of reference source, and arrange and extract reference source signal by the reference source microphone array.For this reason, need to determine the number K and the position of reference source, can adopt the near field compbined test analysis (or claiming inclined to one side odd value analysis) of steady sound field to obtain.
2, arrange holographic facet measuring microphone array,, can on whole hologram plane, arrange microphone if port number is abundant; If port number is not enough, microphone can be arranged to linear array, measure in the enterprising line scanning of whole holographic facet; In the holographic facet data acquisition, utilize the reference source array to gather the reference source acoustical signal.During measurement, the acoustical signal of the whole microphone passages of synchronous acquisition, recording storage suppose that the holographic facet port number is Q in computing machine, magnetic tape recorder or other equipment.
3, analyze the acoustical signal of being gathered, choose the frequency and the cycle frequency that can reflect sound field characteristic, can analyze the spectral density function of each reference source signal and select.
4, utilize the holographic facet time domain acoustical signal data collect and the time domain acoustical signal data of reference source, calculate reference source signal on selected frequency f and the cycle frequency α from composing relevant density matrix
Figure A0312940600051
, and the relevant density matrix of cross-spectrum of reference source signal and holographic facet upper sensor signal With Can calculate the relevant density matrix of the spectrum that obtains acoustical signal on the holographic facet by these three the relevant density matrix of spectrum , computing method are suc as formula (1): [ S pp α ( f ) ] Q × Q = [ S pr α ( f ) ] Q × K [ S rr α ( f ) ] K × K - 1 [ S rp α ( f ) ] K × Q - - - ( 1 )
5, the relevant density matrix of reference source spectrum is done svd, and the relational expression (1) between the relevant density matrix of spectrum of the relevant density matrix of spectrum that utilizes acoustical signal on the holographic facet and reference source acoustical signal, can separate the part sound field that obtains each sound source: [ S rr α ( f ) ] = VDV H - - - ( 2 ) [ S pp α ( f ) ] i = [ S pr α ( f ) ] V * [ D ] i - 1 V - 1 [ S rp α ( f ) ] i = 1,2 , . . . , L - - - ( 3 )
Wherein [D] iMatrix is i the diagonal element of eigenvalue matrix D, and other diagonal element zero setting obtains, and has reflected i physical sound sources (being reference source in fact) physical characteristics.
Figure A0312940600062
In diagonal element represent the auto spectral density correlation matrix of the part sound field of i physical sound sources (being actually reference sound source) on hologram plane.
The present invention has substantive distinguishing features and marked improvement, the present invention utilizes the periodicity of the uniqueness of cyclo-stationary sound field, on the basis of cyclo-stationary theory and principal component analysis (PCA) technology, invented circulation principal component analysis (PCA) part sound field separation technique, can analyze the steady sound field of complex loops that a plurality of cyclo-stationary sound sources form, obtain the part sound field that each sound source forms respectively; Near-field holography by the cyclo-stationary sound field is rebuild, and can also be obtained three-dimensional sound field by the measurement data on the plane and distribute, and realizes that each sound source route of transmission is visual.
Embodiment
Provide following examples in conjunction with the inventive method content:
1, supposes known sound source number and position, adopt two loudspeaker sounding to form two cyclo-stationary sound sources, arrange two microphones, extract reference source signal.
The driving source of loudspeaker is:
Vsourcel=Acos(2πf 1t)*noise(t)
Vsource2=B(1+Ccos(2πf bt))*cos(2πf at)
Wherein, A=10, B=C=1, f1=600, f a=600, f b=200, noise is the logical white noise of band.
2,15 microphones are arranged to linear array, measure, form 15 * 15 holographic facet array in the enterprising line scanning of whole holographic facet; In the holographic facet data acquisition, utilize the reference source array to gather the reference source acoustical signal.During measurement, the acoustical signal of the whole microphone passages of synchronous acquisition, recording storage is in computing machine or other equipment.
3, analyze the acoustical signal of being gathered in the laboratory playback, choose the frequency f=200Hz and the cycle frequency alpha=1200Hz that can reflect sound field characteristic.
4, utilize holographic facet data and the reference source data that collect, analyze selected frequency f and compose relevant density matrix certainly with the reference source signal on the cycle frequency α , the relevant density matrix of cross-spectrum of reference source signal and holographic facet upper sensor signal
Figure A0312940600064
5, separate the part sound field that obtains each sound source.
6, utilize the near-field holography reconstruction formula of cyclo-stationary sound field to carry out sound field rebuilding, to obtain the three-dimensional information of each sound source part sound field.
By analysis, find that separating effect is very good, can analyze significantly to obtain two sound sources sound field separately when two reference source signal coherences that obtain are smaller.But when two reference source signal coherences that obtain were very strong, separating effect was just poor, analyzed the information that two part sound fields that obtain have comprised two sound sources simultaneously.For this reason, adopt the svd reset technique to handle reference source signal, eliminated the coherence between them, improved the separating effect of part sound field.

Claims (3)

1, a kind of method that adopts principal component analysis (PCA) technology identification non-stationary sound source characteristic, it is characterized in that, the occasion of the steady sound field of complex loops that produces in a plurality of sound sources, adopt the theoretical alternative traditional Fourier techniques of cyclo-stationary, obtain being applicable to the principal component analysis (PCA) technology of cyclo-stationary sound field, and it part sound field that is used for the cyclo-stationary sound field separated, method is as follows: quantity and the position of at first determining reference source, and layout reference source microphone array, extract reference source signal, design microphone array again holographic facet is carried out scanning survey, gather the holographic facet data, then, utilize the principal component analysis (PCA) technology of cyclo-stationary sound field, separate the part sound field of each sound source.
2, the method for employing principal component analysis (PCA) technology identification non-stationary sound source characteristic according to claim 1 is characterized in that, below the present invention is further limited, and its concrete steps are:
1) adopts the near field compbined test analysis of steady sound field or claim number K and the position that inclined to one side odd value analysis obtains reference source, and arrange and extract reference source signal by the reference source microphone array;
2) arrange holographic facet measuring microphone array, if port number is abundant, on whole hologram plane, arrange microphone, otherwise microphone is arranged to linear array, measure in the enterprising line scanning of whole holographic facet, in the holographic facet data acquisition, utilize the reference source array to gather the reference source acoustical signal, during measurement, the acoustical signal of the whole microphone passages of synchronous acquisition, recording storage is in computing machine, magnetic tape recorder or other equipment, and establishing the holographic facet port number is Q;
3) analyze the acoustical signal of being gathered, select to reflect the frequency and the cycle frequency of sound field characteristic by the spectral density function of analyzing each reference source signal;
4) the holographic facet time domain acoustical signal data that collect and the time domain acoustical signal data of reference source are calculated selected frequency f and are composed relevant density matrix certainly with the reference source signal on the cycle frequency α , and the relevant density matrix of cross-spectrum of reference source signal and holographic facet upper sensor signal
Figure A0312940600022
With
Figure A0312940600023
,, calculate the relevant density matrix of the spectrum that obtains acoustical signal on the holographic facet by these three the relevant density matrix of spectrum
Figure A0312940600024
, computing method are suc as formula (1): [ S pp α ( f ) ] Q × Q = [ S pr α ( f ) ] Q × K [ S rr α ( f ) ] K × K - 1 [ S rp α ( f ) ] K × Q - - - ( 1 )
5) the relevant density matrix of reference source spectrum is done svd, and the relational expression (1) between the relevant density matrix of spectrum of the relevant density matrix of spectrum that adopts acoustical signal on the holographic facet and reference source acoustical signal, separation obtains the part sound field of each sound source: [ S rr α ( f ) ] = VDV H - - - ( 2 ) [ S pp α ( f ) ] i = [ S pr α ( f ) ] V * [ D ] i - 1 V - 1 [ S rp α ( f ) ] i = 1,2 , . . . , L - - - ( 3 )
Wherein [D] iMatrix is i the diagonal element of eigenvalue matrix D, and other diagonal element zero setting obtains, and has reflected i physical sound sources physical characteristics, In diagonal element represent the auto spectral density correlation matrix of the part sound field of i physical sound sources on hologram plane.
3, the method for employing principal component analysis (PCA) technology identification non-stationary sound source characteristic according to claim 1 and 2, it is characterized in that, adopt cyclo-stationary sound field near-field holography method for reconstructing, the various piece sound field that separation obtains is carried out holographic reconstruction, obtain the three-dimensional information of each sound source, realize that each sound source route of transmission is visual.
CN 03129406 2003-06-19 2003-06-19 Process for identifying non-stable acoustical source characteristic applying principal component analyzing technique Expired - Fee Related CN1202408C (en)

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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101566496B (en) * 2009-06-05 2010-09-01 合肥工业大学 Method for sound field separation by double plane vibration speed measurement and equivalent source method
CN101846594A (en) * 2010-06-22 2010-09-29 上海交通大学 Fault detection device based on beam forming acoustic-image mode recognition and detection method thereof
CN101251412B (en) * 2008-04-17 2010-10-06 上海交通大学 Method for rebuilding circulation calm sound source by overlapping spherical wave
CN101359043B (en) * 2008-09-05 2011-04-27 清华大学 Determining method for sound field rebuilding plane in acoustics video camera system
CN102121847A (en) * 2010-12-16 2011-07-13 合肥工业大学 Method for reestablishing transient sound field
CN105844114A (en) * 2016-04-28 2016-08-10 广西科技大学 Non-conformal measurement near field acoustic holography sound field rebuilding method
CN106052849A (en) * 2016-05-20 2016-10-26 西南交通大学 Method of identifying non-stationary abnormal noise source in automobile
CN109580224A (en) * 2018-12-28 2019-04-05 北京中科东韧科技有限责任公司 Rolling bearing fault method of real-time

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CN100442030C (en) * 2006-10-27 2008-12-10 合肥工业大学 A separating method for sound field

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101251412B (en) * 2008-04-17 2010-10-06 上海交通大学 Method for rebuilding circulation calm sound source by overlapping spherical wave
CN101359043B (en) * 2008-09-05 2011-04-27 清华大学 Determining method for sound field rebuilding plane in acoustics video camera system
CN101566496B (en) * 2009-06-05 2010-09-01 合肥工业大学 Method for sound field separation by double plane vibration speed measurement and equivalent source method
CN101846594A (en) * 2010-06-22 2010-09-29 上海交通大学 Fault detection device based on beam forming acoustic-image mode recognition and detection method thereof
CN102121847A (en) * 2010-12-16 2011-07-13 合肥工业大学 Method for reestablishing transient sound field
CN105844114A (en) * 2016-04-28 2016-08-10 广西科技大学 Non-conformal measurement near field acoustic holography sound field rebuilding method
CN106052849A (en) * 2016-05-20 2016-10-26 西南交通大学 Method of identifying non-stationary abnormal noise source in automobile
CN106052849B (en) * 2016-05-20 2020-02-18 西南交通大学 Method for identifying non-stationary abnormal noise source in automobile
CN109580224A (en) * 2018-12-28 2019-04-05 北京中科东韧科技有限责任公司 Rolling bearing fault method of real-time

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