CN109323757B - A method of estimation bubble population is to propeller sound source characteristics frequency inhibiting effect - Google Patents
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Abstract
The invention discloses a kind of estimation bubble populations to the method for propeller sound source characteristics frequency inhibiting effect, comprising: (1) acquires the propeller noise signal of different operating conditions；(2) noise signal cyclostationary characteristic function is calculated, obtains circulating density spectrum；(3) the corresponding circulating density spectrum of two kinds of operating conditions a little remove, or using minimum two norm methods, obtain the circulating density spectrum of bubble transmission function；(4) it is composed according to the circulating density that step (2) obtains, calculates circulation coherence spectrum, construct the enhancing envelope spectrum under logarithmic coordinates；(5) according to enhancing envelope spectrum judging characteristic frequency, the corresponding slice of characteristic frequency is done to the circulating density spectrum of bubble transmission function, obtains bubble population transmission function；(6) according to bubble population transmission function, estimate bubble population to the size of propeller sound source characteristics frequency inhibiting effect.Using the present invention, available more accurate transmission function, to preferably analyze bubble population isolation effect.
Description
Technical Field
The invention belongs to the field of signal processing and feature extraction, and particularly relates to a method for estimating the suppression effect of a bubble group on the characteristic frequency of a propeller sound source.
Background
The transparent bubbles in water have the characteristics of easy deformation, splitting, fusion and the like, and the acoustic characteristics of the water containing the bubbles are obviously different from those of pure water. Because the bubble group is a strong scatterer in water, the bubble group has strong attenuation and scattering effects on the transmitted sound waves. When the bubbles in water resonate, the attenuation effect of sound waves close to the resonance frequency of the bubbles is more obvious. But the transfer function characteristics of the bubble groups are difficult to directly describe by mathematical formulas. Therefore, the research on the acoustic characteristics of the bubble groups in the water has extremely important scientific significance and application prospect.
An approximation is that the bubble transfer function at the eigenfrequency is of priority, so a three-dimensional analysis tool is needed to simultaneously represent the eigenfrequency and the continuous nature of the transfer function, and then cyclostationarity becomes a good choice.
Cyclostationary signal processing is an emerging technology for signal processing that has recently emerged. A cyclostationary signal is a signal in which the signal contains hidden period information. The cyclostationary signal is one of the non-stationary signals, and is closer to the actual signal, especially the signal generated by the rotating machine, than the conventional detection method.
The conventional rotary machine fault detection method in the field of signal processing mainly comprises Fourier transform, short-time Fourier transform, wavelet transform, second-generation wavelet transform, multi-wavelet transform and the like, and is characterized by being based on the inner product principle, namely, characteristic waveform basis function signal decomposition, aiming at flexibly applying a basis function matched with a characteristic waveform to better process signals and extract fault characteristics so as to realize fault diagnosis.
However, the following disadvantages and shortcomings exist in the prior art: fault detection methods such as fourier transform, short-time fourier transform, wavelet transform, second-generation wavelet transform, multi-wavelet transform and the like are all established on the basis of assuming that signals are stationary signals, but in reality, the signals are often non-stationary signals, so that the detection methods all have unreasonable places and are unrealistic. Meanwhile, due to theoretical limitations, the conventional detection methods are difficult to detect some important characteristics of the rotating machine, such as blade passing frequency BPF, blade specific frequency BRF and the like, and have great limitations.
Disclosure of Invention
The invention provides a method for estimating the inhibition effect of a bubble group on the characteristic frequency of a propeller sound source, which can express more characteristics of the sound isolation effect of a propeller under the bubble group, the obtained transfer function is more accurate, and the method has practical guiding significance for further signal processing and verification of the sound isolation effect of the bubble group.
A method of estimating the eigenfrequency suppression of a propeller sound source by a bubble swarm, comprising the steps of:
(1) acquiring propeller noise signals under two working conditions of bubbles and no bubbles underwater;
(2) importing the collected noise signals into a program, and calculating by using a cyclostationary feature function to obtain a cyclic density spectrum of two working conditions;
(3) performing point division on the corresponding cycle density spectrums in the working conditions with bubbles and without bubbles, or adopting a minimum two-norm method to obtain the cycle density spectrum of the bubble transfer function;
(4) according to the circulating density spectrums of the two working conditions obtained in the step (2), normalization is carried out to obtain circulating coherent spectrums of the two working conditions, and then an enhanced envelope spectrum under a logarithmic coordinate is further constructed;
(5) judging characteristic frequency according to the obtained enhanced envelope spectrum, and slicing the circulating density spectrum of the bubble transfer function corresponding to the characteristic frequency to obtain a bubble group transfer function;
(6) and estimating the size of the inhibition effect of the bubble group on the characteristic frequency of the propeller sound source according to the obtained bubble group transfer function.
The method can show more characteristics of the sound isolation effect of the propeller under the bubble group, the obtained characteristic frequency is closer to the essence of the propeller noise, and the size of the inhibition effect of the bubble group on the characteristic frequency of the propeller sound source can be analyzed through the obtained bubble group transfer function.
In the step (2), the cyclostationary feature function is:
alpha is a cycle frequency, f is a frequency spectrum frequency; x is a signal to be detected; x is the frequency spectrum of the signal X; x*The complex conjugate of X is shown.
Wherein the mathematical expression of the amplitude modulation model of x is:
Aithe amplitude corresponding to each characteristic frequency; alpha is alpha i2 times the characteristic frequency; t represents time; n represents the number.
In the step (3), the mathematical formula of the transfer model is as follows:
y(t)＝x(t)*h(t)+v(t)
wherein, y (t) is the received signal, x (t) is the sound source noise signal, h (t) is the transfer function time domain model, v (t) is the background noise signal, and is the convolution symbol.
The mathematical formula of the corresponding cyclostationary relationship is:
wherein:
the cyclic density spectrum of the bubble transfer function.
It is derived as follows:
the convolution and linear properties from the fourier transform are:
according to the stationarity of background noise, there are
Let the variance be δ2Then the cyclic density spectrum of the received signal is:
when H (f) is a broad band, the approximation is considered
In particular, in a muffled water pool, it can be considered that when C approaches 0:
therefore, for the cyclic density spectrum of the bubble transfer function, it can be approximated as:
note: wherein,for the transfer of bubblesThe cyclic density spectrum of the transfer function,
is a circulating density spectrum corresponding to the working condition of bubbles,the circulating density spectrum is corresponding to the bubble-free working condition. The above operation is the point division of the corresponding point of the circulating density spectrum in the working condition with bubbles and without bubbles, and when the calculation result is an extra-large value, the point is regarded as a dead point, and the interpolation is carried out by using the nearby points.
Further, the minimum two-norm method, which minimizes the following calculation amount for estimation, may be employed
Wherein,for an optimal estimation of the circulating density spectrum of the bubble transfer function,
is a circulating density spectrum corresponding to the working condition of bubbles,
the circulating density spectrum corresponding to the bubble-free working condition,
the cyclic density spectrum of the bubble transfer function.
In the step (4), the mathematical expression of the cyclic coherence spectrum is as follows:
wherein,the circular coherent spectrum corresponding to the working condition of the bubble,
is a circulating density spectrum corresponding to the working condition of bubbles,the circulation density spectrum with the circulation frequency of 0 corresponding to the working condition with bubbles.
In the step (4), the detailed steps of constructing the enhancement envelope spectrum under the logarithmic coordinate are as follows:
(4-1) calculating function values corresponding to all cycle frequencies of the enhancement envelope spectrum; the mathematical expression of the enhanced envelope spectrum is as follows:
wherein,
the spectrum is a circular coherent spectrum corresponding to the working condition with bubbles.
(4-2) calculating the function value by taking 10 logarithms to obtain a sound pressure level, setting a value-taking interval according to the obtained logarithm function value range, and assigning the rest logarithm function values as corresponding most values;
and (4-3) constructing an enhancement envelope spectrum under a logarithmic coordinate according to the corresponding coordinate point and the function value.
In the step (5), the characteristic frequency is comprehensively judged according to the obvious peak value, the interference frequency, the harmonic frequency and the like of the enhanced envelope spectrum.
The invention overcomes the difficulty that the passing frequency and the blade ratio frequency of the blade cannot be detected or are not obvious when the traditional detection method processes the cyclostationary signal, can show more characteristics of the sound isolation effect of the propeller under the bubble group, and can further obtain a transfer function by means of cyclostationary analysis, thereby analyzing the bubble group isolation effect.
The characteristic frequency obtained according to the amplitude modulation model is closer to the essence of propeller noise, the propeller noise signal can be restored to a certain degree, the obtained transfer function is more accurate, and the method has practical guiding significance for further signal processing and verification of the bubble swarm sound isolation effect.
Drawings
FIG. 1 is a schematic flow chart of a method for estimating the suppression effect of a bubble group on the characteristic frequency of a propeller sound source according to the present invention;
FIG. 2 is a graph of the spectrum of a bubble free population of a four-bladed propeller at 5Hz rpm;
FIG. 3 is a graph of the spectrum of a four-bladed propeller with bubble clusters at a 5Hz frequency of rotation;
FIG. 4 is an enhanced envelope spectrum of a bubble free population of the four-bladed propeller at 5Hz frequency rotation;
FIG. 5 is an enhanced envelope spectrum of a four-bladed propeller with bubble clusters at a frequency of 5Hz rotation;
FIG. 6 is an enhanced envelope spectrum of a bubble free population of the four-bladed propeller at 20Hz rotation frequency;
FIG. 7 is an enhanced envelope spectrum of a four-bladed propeller with bubble populations at 20Hz frequency;
FIG. 8 is a graph of transfer functions calculated for bubble populations of a four-bladed propeller at a frequency of 5 Hz;
FIG. 9 is a graph of the transfer function calculated for the air bubble population at 20Hz rotation frequency for the four-bladed propeller.
Detailed Description
In order to more specifically describe the present invention, the following detailed description is provided for the technical solution of the present invention with reference to the accompanying drawings and the specific embodiments.
As shown in fig. 1, a method for estimating the suppression effect of a bubble group on the characteristic frequency of a propeller sound source comprises the following steps:
and S01, collecting the noise of different underwater working conditions by using the hydrophone, wherein the noise comprises a working condition without bubble groups and a working condition with bubble groups.
S02, setting corresponding parameters in the program, introducing the collected signals into the program, and calculating the circulating density spectrum:
wherein: alpha is a cycle frequency, f is a frequency spectrum frequency; x is a signal to be detected; x is the frequency spectrum of the signal X; x*The complex conjugate of X is shown.
Where the mathematical expression of the amplitude modulation model for x is:
wherein: a. theiThe amplitude corresponding to each characteristic frequency; alpha is alpha i2 times the characteristic frequency; t represents time; n represents the number.
And S03, dividing the points of the circulating density spectrum of the bubble-containing working condition by the points of the circulating density spectrum of the bubble-free working condition in a one-to-one correspondence mode, or estimating the minimum two-norm to obtain the circulating density spectrum of the bubble transfer function.
When the points of the circulating density spectrum under the bubble-free working condition are divided by the points of the circulating density spectrum under the bubble-free working condition in a one-to-one correspondence manner, the circulating density spectrum of the bubble transfer function can be approximately considered as follows:
wherein,
is a cyclic density spectrum of the bubble transfer function,
is a circulating density spectrum corresponding to the working condition of bubbles,
the circulating density spectrum is corresponding to the bubble-free working condition.
The formula using the minimum two-norm method is:
wherein,
for an optimal estimation of the circulating density spectrum of the bubble transfer function,is a circulating density spectrum corresponding to the working condition of bubbles,
the circulating density spectrum corresponding to the bubble-free working condition,
is a cyclic density spectrum of a bubble transfer function by
Estimate with minimum calculation amount
S04, calculating a function value corresponding to each cycle frequency of the enhancement envelope spectrum according to the following formula by using the cycle density function calculated by the cycle stationary characteristic function in the S02:
and S05, obtaining the sound pressure level by taking 10 logarithm calculation and the like for the function value, setting the most value limit according to the obtained logarithm function value range, and constructing the enhancement envelope spectrum under the logarithmic coordinate according to the corresponding coordinate point and the function value.
S06, storing the enhanced envelope spectrum of the actual data, including two working conditions of bubble group-free and bubble group-containing, and the enhanced envelope spectrum of the bubble group property obtained by calculation; and deducing characteristic frequency according to the obvious peak value of the enhanced envelope spectrum and according to the characteristics of interference frequency, harmonic frequency and the like.
And S07, directly comparing the sound pressure levels at typical frequencies such as characteristic frequency, interference frequency, harmonic frequency and the like on the enhanced envelope spectrum on the basis of S06, and slicing the enhanced envelope spectrum of the bubble groups at the corresponding cycle frequency to obtain the transfer function of the bubble groups.
And S08, constructing a simulation signal by the obtained characteristic frequency, and comparing the simulation signal with the detection result of the stored actual data after the circulation smoothing processing to verify the correctness of the extracted characteristic.
In order to embody the advantages and the characteristics of the method in the field of detection of the pump noise isolation effect of the bubble groups, the four-blade propeller is adopted for testing.
Firstly, acquiring and processing noise signals of a bubble-free group and a bubble group of a propeller under a normal working condition of 5Hz respectively, wherein a bubble-free group spectrogram obtained through the traditional fast Fourier transform is shown in figure 2, and a bubble group spectrogram is shown in figure 3, so that the characteristic frequency and certain frequency doubling detection effects are poor by using the traditional fast Fourier transform; the enhanced envelope spectra obtained after the cyclostationary processing are respectively shown in fig. 4 and 5, the obtained graphs conform to the expectation of the rotating mechanical property of the propeller, and the axial frequency of 5Hz, the blade frequency of 20Hz corresponding to the four-blade propeller, the harmonic frequency, the interference frequency and the like of the four-blade propeller are respectively detected. In addition, by comparing fig. 4 and fig. 5, it is apparent that the bubble group has a significant suppression effect on the propeller noise in the low frequency band.
Further, according to the method, the collected noise signal is subjected to feature extraction, and another working condition signal is simulated
The simulated signal is processed by the same cyclostationary processing method, the obtained enhanced envelope spectrum is shown in fig. 6 and 7, the axial frequency, the blade frequency, the harmonic frequency thereof, the interference frequency and the like can be clearly obtained, and the comparison between fig. 6 and 7 also shows that the bubble group pairs are obviously seen in the low frequency bandThe propeller noise has obvious inhibiting effect. The transfer functions of the two groups of air bubble groups corresponding to the frequencies at the characteristic frequency are respectively shown in fig. 8 and 9, the sound pressure of the low-frequency part (below 1000 Hz) in the two figures is below 0dB, and the inhibiting effect of the air bubble groups on the characteristic frequency of the propeller is verified.
By contrast, it has been found that the amplitude and frequency are somewhat similar, but not exactly identical, across the enhanced envelope spectrum. Considering the difference between the simulation signal and the actual signal and the incompleteness of frequency feature extraction, the simulation signal essentially reveals the correctness of the model of the bubble group on the pump noise isolation effect and the superiority of feature extraction to a certain extent, and has practical guiding significance for further data processing and production practice.
The embodiments described in this specification are only for illustrative purposes and are not intended to limit the invention, the scope of the invention should not be limited to the specific embodiments described in the embodiments, and any modifications, substitutions, changes, etc. within the spirit and principle of the invention are included in the scope of the invention.
Claims (5)
1. A method of estimating the eigenfrequency suppression of a propeller sound source by a bubble swarm, comprising:
(1) acquiring propeller noise signals under two working conditions of bubbles and no bubbles underwater;
(2) importing the collected noise signals into a program, and calculating by using a cyclostationary feature function to obtain a cyclic density spectrum of two working conditions; the cyclostationary feature function is:
wherein, alpha is a cycle frequency, and f is a frequency spectrum frequency; x is a signal to be detected; x is the frequency spectrum of the signal X; x*Represents the complex conjugate of X;
(3) performing point division on the corresponding cycle density spectrums in the working conditions with bubbles and without bubbles, or adopting a minimum two-norm method to obtain the cycle density spectrum of the bubble transfer function;
(4) according to the circulating density spectrums of the two working conditions obtained in the step (2), normalization is carried out to obtain circulating coherent spectrums of the two working conditions, and then an enhanced envelope spectrum under a logarithmic coordinate is further constructed; the detailed steps for constructing the enhancement envelope spectrum under the logarithmic coordinate are as follows:
(4-1) calculating function values corresponding to all cycle frequencies of the enhancement envelope spectrum; the mathematical expression of the enhanced envelope spectrum is as follows:
wherein,
a cyclic coherence spectrum corresponding to a bubble working condition;
(4-2) calculating the function value by taking 10 logarithms to obtain a sound pressure level, setting a value-taking interval according to the obtained logarithm function value range, and assigning the rest logarithm function values as corresponding most values;
(4-3) constructing an enhancement envelope spectrum under a logarithmic coordinate according to the corresponding coordinate point and the function value;
(5) judging characteristic frequency according to the obtained enhanced envelope spectrum, and slicing the circulating density spectrum of the bubble transfer function corresponding to the characteristic frequency to obtain a bubble group transfer function;
(6) and estimating the size of the inhibition effect of the bubble group on the characteristic frequency of the propeller sound source according to the obtained bubble group transfer function.
2. The method for estimating the suppression effect of the bubble group on the characteristic frequency of the propeller sound source according to claim 1, wherein in the step (3), when the corresponding cycle density spectrums in the bubble-containing and bubble-free working conditions are subjected to point division, the cycle density spectrum of the bubble transfer function is:
wherein,
is a cyclic density spectrum of the bubble transfer function,
is a circulating density spectrum corresponding to the working condition of bubbles,
a circulating density spectrum corresponding to a bubble-free working condition; the above operation is the point division of the corresponding point, but the calculated value is considered as a dead point when the calculated value is an extra-large value, and the interpolation is carried out by using the nearby points.
3. The method for estimating the characteristic frequency suppression effect of the bubble group on the propeller sound source according to claim 1, wherein in the step (3), the formula adopting the minimum two-norm method is as follows:
wherein,
for an optimal estimation of the circulating density spectrum of the bubble transfer function,is a circulating density spectrum corresponding to the working condition of bubbles,
the circulating density spectrum corresponding to the bubble-free working condition,a cyclic density spectrum that is a bubble transfer function; when in useIs obtained when the calculated amount of (A) is minimum
4. The method for estimating the suppression effect of the bubble group on the characteristic frequency of the propeller sound source according to claim 1, wherein in the step (4), the mathematical expression of the cyclic coherence spectrum is as follows:
wherein,
the circular coherent spectrum corresponding to the working condition of the bubble,
is a circulating density spectrum corresponding to the working condition of bubbles,
the circulation density spectrum with the circulation frequency of 0 corresponding to the working condition with bubbles.
5. The method for estimating the suppression effect of the bubble swarm on the characteristic frequency of the propeller sound source according to claim 1, wherein in the step (5), the characteristic frequency is comprehensively judged according to an obvious peak value of an emphasis envelope spectrum, an interference frequency and a harmonic frequency.
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