CN107843406B - Cavity modal wave motion characteristic determination method based on pulse pressure correlation function - Google Patents
Cavity modal wave motion characteristic determination method based on pulse pressure correlation function Download PDFInfo
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Abstract
The invention discloses a method for determining the motion characteristics of cavity modal waves based on a pulse pressure correlation function, which comprises the following steps: firstly, drawing an autocorrelation and cross-correlation function curve by using time domain pulsating pressure data of a cavity bottom surface pulsating pressure measuring point; step two, calculating the frequency of the main mode wave by utilizing an autocorrelation function curve; and step three, determining the propagation direction and speed of the modal wave by using the cross-correlation function curve. Compared with the prior art, the invention has the following positive effects: the invention utilizes the time domain data of the cavity bottom surface pulsating pressure measuring point to calculate the autocorrelation and cross-correlation functions, analyzes the frequency characteristic, the propagation speed and the direction of the modal wave through the periodicity and the phase change of the curve peak value, and effectively makes up the defects of the traditional frequency spectrum analysis method in the time domain.
Description
Technical Field
The invention relates to the field of aerospace, in particular to a method for determining cavity modal wave motion characteristics based on a pulse pressure correlation function.
Background
When high velocity gas flows pass through the cavity, the flow at the leading edge of the cavity may experience greater separation and form a shear layer downstream, which contains the creation, development and shedding of multi-scale vortices within it. When the shedding vortex collides with the rear wall of the cavity, high-strength modal waves are induced and are propagated upwards to the flow separation area at the front edge of the cavity to excite the generation and shedding of the secondary vortex in the shearing layer, so that a flow self-sustaining oscillation circuit is formed in the cavity. The high-intensity noise induced by the flow self-sustaining oscillating circuit brings serious harm to the structure of the cavity and personnel and equipment, and the intracavity modal wave is taken as a key factor in the forming process of the self-sustaining oscillating circuit, and the space relativity and the motion characteristic of the intracavity modal wave have important significance for deeply understanding the physical mechanism of the flow sound effect in the cavity.
For the measurement of intracavity modal waves, the main current means is to install a pulsating pressure sensor on the inner wall surface of a cavity, collect time domain pulsating pressure information in an intracavity flow field, and analyze the noise characteristics in the cavity according to the time domain pulsating pressure information (the characteristics of intracavity noise load and typical frequency sound wave obtained through the pulsating pressure information are accepted at home and abroad). However, the obtained noise contains not only high-intensity modal noise components but also a large amount of broadband noise components, so that the time-frequency domain processing and correlation analysis of the pulsating pressure become the key point of the problem when the modal noise in the cavity is extracted and analyzed from the time domain information.
The traditional research method is to convert time domain pulsating pressure information into frequency domain noise frequency spectrum information through Fourier transform, effectively distinguish modal components and broadband components through amplitude change in a frequency domain range, and acquire the frequency and intensity of modal noise according to the position and amplitude of a peak value. Although the method can accurately acquire the characteristics of the main modal noise and effectively capture the information of other modal noises, the Fourier transform is used for carrying out frequency domain conversion and analysis on the time domain signal, the method mainly has the function of distinguishing different frequency modal noises, but neglects the change of the modal noise in the time dimension, and the physical analysis process of the specific presentation form of the noise characteristics, namely the propagation speed, the directivity and the like of the modal wave in the time dimension is difficult to provide.
For a capturing means of a complex wave system structure, such as a high-Speed schlieren technology, the principle that the refractive index is in direct proportion to the density of a Flow field in the propagation process of a light ray is utilized, and the motion of complex Flow structures such as shock waves, compression waves and vortex structures in a compressible Flow field is captured and analyzed through the density change in the Flow field, such as the observation results of the shock waves and the vortex structures around a Cavity in document 1(Schmit R f. fourier Analysis of high Speed shape image Images around a Mach 1.5Cavity Flow field. aiaa-2011-. However, the intensity of the modal wave is generally much smaller than the strong physical quantity in the flow field, and strong abrupt change of the flow structure and the density distribution is difficult to cause during motion propagation in the background flow field, so that the observation information of the modal wave is difficult to obtain through the schlieren technology.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a cavity modal wave motion characteristic determination method based on a pulse pressure correlation function.
The technical scheme adopted by the invention for solving the technical problems is as follows: a method for determining the motion characteristics of cavity modal waves based on a pulse pressure correlation function comprises the following steps:
step one, drawing an autocorrelation function curve and a cross-correlation function curve of different measuring points by using synchronous time domain pulsating pressure data of pulsating pressure measuring points on the bottom surface of a cavity;
step two, calculating the frequency of the main mode wave by utilizing an autocorrelation function curve;
and step three, determining the propagation direction and speed of the modal wave by using the cross-correlation function curve.
Compared with the prior art, the invention has the following positive effects:
the invention utilizes the time domain data of the cavity bottom surface pulsating pressure measuring point to calculate the autocorrelation and cross-correlation functions, analyzes the frequency characteristic, the propagation speed and the direction of the modal wave through the periodicity and the phase change of the curve peak value, and effectively makes up the defects of the traditional frequency spectrum analysis method in the time domain.
Drawings
The invention will now be described, by way of example, with reference to the accompanying drawings, in which:
FIG. 1 is a schematic diagram of the position of a cavity bottom surface pulsating pressure measuring point;
FIG. 2 is a time-domain pulse pressure autocorrelation function curve of the A2 measuring point under different Ma conditions;
FIG. 3 is a cross-correlation function curve of time-domain pulse pressure at bottom surface measuring points at different positions.
Detailed Description
A method for determining the motion characteristics of cavity modal waves based on a pulse pressure correlation function comprises the following steps:
step one, calculating a correlation function:
1. and reading synchronous time domain pulse pressure data of the cavity bottom surface pulse pressure measuring point (shown in figure 1) obtained under the same test state condition through MatLab software.
2. And calculating correlation functions of two groups of pulsating pressure time domain data by using an 'xcorr' function in a MatLab software function library, wherein the first group is from reference measuring points, and the second group is from measuring points to be analyzed. If the measuring point to be analyzed is the same as the reference measuring point, namely the measuring point and the reference measuring point are the same, the calculation result is an autocorrelation function of the pulsating pressure at the measuring point; if the two groups of data are from different measuring points, the calculation result is a cross-correlation function of the pulse pressure of the reference measuring point and the measuring point to be analyzed.
3. The auto-correlation and cross-correlation function curves are plotted by "plot functions" in MatLab software function libraries, as shown in fig. 2 and 3, respectively.
Step two, calculating the frequency of the main mode wave by utilizing a pulsating pressure autocorrelation function curve:
aiming at an autocorrelation function curve of pulsating pressure of a certain measuring point, the frequency of main modal noise is calculated through the periodic peak distribution, and the specific process is as follows:
1. and acquiring the abscissa of the periodic peak of the autocorrelation function curve of the pulse pressure data of a certain measuring point.
2. And calculating the difference between the abscissas of the two adjacent peak values, wherein the difference represents the time interval of two continuous main mode waves passing through the measuring point.
3. And calculating the reciprocal of the time interval to obtain the frequency of the main mode wave. Taking fig. 2 as an example, the calculation results are shown in the following table:
| Ma＝0.9 | Ma＝1.5 | |
| peak interval of autocorrelation function | 1ms | 0.78ms |
| Frequency of modal wave | 1000Hz | 1280Hz |
Step three, determining the propagation direction and speed of the modal wave by utilizing the cross-correlation function
And aiming at a group of correlation function curves with the same reference data, the sequence and the speed of the main mode wave passing through the measuring points can be judged according to the position of the maximum peak value of each curve.
1. For a set of correlation function curves with the same reference data, a plurality of curves are depicted in the same graph, as shown in fig. 3, with data at a point a2 as the reference data in the example.
2. The abscissa of the maximum peak in each correlation function curve is obtained.
3. According to the abscissa position of the maximum peak value, the measuring points of the data to be analyzed of the correlation function curve are sequenced from left to right, and the sequence of the main mode wave passing through different measuring points can be obtained, such as the sequence of A3-A2-A1 in FIG. 3.
4. And calculating the difference between the abscissas of the maximum peak values of different curves to obtain the time interval of the main mode wave peak value passing through different measuring points, and dividing the space distance of the measuring points by the time interval to calculate the movement speed of the mode wave in different areas. Taking fig. 3 as an example, the calculation results are shown in the following table:
the principle of the invention is as follows: the obtained pulsating pressure time domain data is comprehensively processed and analyzed, and the motion speed, the propagation frequency and the wave surface characteristics of the modal wave in the cavity are obtained by utilizing the time-space correlation analysis of the pulsating pressure on the wall surface of the cavity.
According to the invention, the correlation among data of different measuring points is analyzed through a time domain signal acquired from the cavity bottom surface pulsating pressure measuring point. The pulsating pressure sensor captures noise information in the cavity, and the correlation function reflects the consistency of two pressure time domain data. The sound wave in the cavity contains random broadband noise and periodic modal noise, and the amplitude of the modal noise with main frequency is most significant. The random noise contributes substantially no to the result of the correlation function, while the dominant mode noise contributes most to the correlation function, so that the peak of the correlation function is mainly generated by the dominant frequency mode noise.
Because the main mode wave in the cavity has strong periodicity, the autocorrelation function curve of the time domain pulsating pressure on the measuring point also has periodic peak values, but due to the interference of other modes and broadband components, the autocorrelation function curve has the maximum peak value only when the abscissa is at a point 0, and other peak values are reduced. By measuring the distance between two adjacent peak values in the autocorrelation function curve, the time interval of two adjacent main mode wave peak values passing through the measuring point can be obtained, and the frequency of the main mode noise can be calculated.
In the cross-correlation function curves of the pulse pressures at different measuring points, the peak value of the curve reflects the maximum similarity of pulse pressure signals of the two measuring points. Because the modal wave does not reach the two measuring points simultaneously, the position of the maximum peak value of the curve is not necessarily at the 0 point of the abscissa, the phase position represents the time required for the time domain data of the two measuring points to reach the maximum similarity, the time also reflects the time consumption of the modal wave in the transmission between different measuring points and the sequence of the sound wave reaching different measuring points, and the propagation speed of the modal wave can be calculated by combining the spatial distance of the two measuring points.
Claims (4)
1. A cavity modal wave motion characteristic determination method based on a pulse pressure correlation function is characterized by comprising the following steps: the method comprises the following steps:
step one, drawing an autocorrelation function curve and a cross-correlation function curve by using synchronous time domain pulsating pressure data of a cavity bottom surface pulsating pressure measuring point;
step two, calculating the frequency of the main mode wave by utilizing an autocorrelation function curve:
(1) acquiring the abscissa of the periodic peak value of the pulse pressure from the pulse pressure autocorrelation function curve;
(2) calculating the difference between the horizontal coordinates of two adjacent peak values to obtain the time interval of two continuous main mode waves passing through the measuring point;
(3) calculating the reciprocal of the time interval to obtain the frequency of the main mode wave;
and step three, determining the propagation direction and speed of the modal wave by using the cross-correlation function curve.
2. The method for determining the motion characteristics of the cavity modal waves based on the pulse pressure correlation function according to claim 1, wherein: step one, the method for drawing the pulse pressure autocorrelation function curve and the cross-correlation function curve comprises the following steps:
(1) reading synchronous time domain pulse pressure data of the cavity bottom surface pulse pressure measuring point obtained under the same test state condition through MatLab software;
(2) calculating correlation functions of two groups of pulse pressure time domain data by using an 'xcorr' function in a MatLab software function library, wherein: calculating two groups of same data from the same measuring point to obtain an autocorrelation function of the measuring point; calculating two groups of data from different measuring points to obtain a cross-correlation function of the two measuring points;
(3) and drawing an autocorrelation function curve of the pulse pressure of the same measuring point and a cross-correlation function curve of the pulse pressure of different measuring points through a plot function in a Matlab software function library.
3. The method for determining the motion characteristics of the cavity modal waves based on the pulse pressure correlation function as claimed in claim 2, wherein: the two groups of pulse pressure time domain data are respectively derived from a reference measuring point and a measuring point to be analyzed.
4. The method for determining the motion characteristics of the cavity modal waves based on the pulse pressure correlation function according to claim 1, wherein: step three, the method for determining the propagation direction and the velocity of the modal wave by using the cross-correlation function curve comprises the following steps:
(1) plotting the autocorrelation and cross-correlation function curves of a set of correlation function curves having the same reference data in the same graph;
(2) acquiring the abscissa of the maximum peak value in each correlation function curve;
(3) sequencing the measuring points of the data to be analyzed of the correlation function curve from small to large according to the abscissa position of the maximum peak value to obtain the sequence of the main mode wave passing through different measuring points;
(4) and calculating the difference between the horizontal coordinates of the maximum peak values of different curves to obtain the time interval of the main mode wave peak value passing through different measuring points, and dividing the time interval by the space distance of the measuring points to obtain the motion speed of the mode wave.
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