CN-120706307-B - Multi-scale correlated space dimension analysis method for jet reactor under negative pressure condition

CN120706307BCN 120706307 BCN120706307 BCN 120706307BCN-120706307-B

Abstract

The invention discloses a multi-scale associated dimension analysis method of a jet reactor under a negative pressure condition, which is used for carrying out systematic research on nonlinear dynamics characteristics of a flow field in the jet impact reactor by introducing a phase space reconstruction and attractor analysis method, namely an associated dimension method. Phase space reconstruction techniques reconstruct time series data into tracks in Gao Weixiang space by a delayed embedding method, revealing the intrinsic dynamics of the system. The attractors act as geometric structures in the phase space, reflect the long-term dynamics of the system, and their shape and distribution can provide important clues for understanding the complexity of the flow field. Through phase space reconstruction attractor analysis, chaotic behavior, fractal characteristics and attractor geometric structures in a flow field can be identified, so that theoretical support is provided for optimizing reactor design and operation conditions.

Inventors

QIU FACHENG
LI WENSHENG
CHEN YOUPENG
YAN HONGYING
LI KEYAN
DONG YINGYING
HU YUQIAN
Hu Lingxing
PENG YAOHUA
QIN FEI
CHENG ZHILIANG

Assignees

重庆理工大学

Dates

Publication Date: 20260505
Application Date: 20250617

Claims (7)

1. A method for analyzing the multi-scale associated space dimension of a jet reactor under a negative pressure condition, which is characterized by comprising the following steps: collecting time series pressure signals under different negative pressure conditions for the negative pressure jet reactor; Performing multi-scale decomposition on the acquired pressure signals based on a wavelet transformation method to obtain multi-scale pressure signals; Carrying out phase space reconstruction attractors on multi-scale pressure signals under different negative pressure conditions based on a phase space reconstruction method to obtain phase space reconstruction attractors under different scales, wherein the phase space reconstruction attractors are carried out on the multi-scale pressure signals under different negative pressure conditions based on the phase space reconstruction method to obtain phase space reconstruction attractors under different scales; Acquiring nonlinear characteristics and dynamic behaviors of a flow field under different negative pressure conditions through phase space reconstruction attractor image comparison and correlation dimension analysis; The phase space reconstruction is carried out according to the obtained optimal time delay and saturation embedding dimension, and specifically comprises the following steps: For one of One-dimensional scalar time series of dimensional chaotic attractors N is the time series length, if the dimension is embedded Satisfy the following requirements Reconstructing an attractor which is topologically equivalent to the original system by a delay embedding method; reconstructing a phase space from the obtained optimal time delay and saturation embedding dimensions: Wherein, the Is the saturated embedding dimension which is the number of dimensions, Is the optimal delay time; Nonlinear characteristics and dynamic behaviors of the flow field under different negative pressure conditions are obtained through phase space reconstruction attractor image comparison and correlation dimension analysis, and the method specifically comprises the following steps: In MATLAB, correlationDimension functions are used to calculate the correlation dimension of the time series Based on Grassberger-Procaccia algorithm; Correlation dimension By fitting And (3) with The slope obtained for the linear part of (a): wherein the integral is correlated Representing the probability that the distance between the point pairs is smaller than r in the phase space, wherein r is a preset distance threshold between the point pairs.
2. The method for analyzing the multi-scale correlated space dimension of the jet reactor under the negative pressure condition according to claim 1, wherein the method for acquiring the time series pressure signals under different negative pressure conditions for the negative pressure jet reactor specifically comprises the following steps: And the pressure signals of the negative pressure area and the slow flow area are respectively collected under the condition of different negative pressure values at the top.
3. The method for analyzing the multi-scale associated space dimension of the jet reactor under the negative pressure condition according to claim 1, wherein the method for analyzing the acquired pressure signals in a multi-scale manner based on a wavelet transformation method is characterized by comprising the following steps of: the Symlet7 wavelet transformation is adopted to carry out multi-scale decomposition on the acquired pressure signals, and the decomposition process is used for decomposing the signals based on a scale function and a wavelet function.
4. The method for analyzing the multi-scale correlated space dimension of the jet reactor under the negative pressure condition according to claim 1, wherein the optimal time delay is determined by quantifying the dependency relationship of two time sequences under different time delays based on a mutual information method, and the method specifically comprises the following steps: given a time sequence And Calculating different delays Delayed mutual information Wherein Is shown at the time point Upper part of the cylinder And at the point of time Upper part of the cylinder Mutual information between the two; Drawing delayed mutual information Along with it Finding the first local minimum point, and the delay tau corresponding to the corresponding point is the optimal time delay.
5. The method for analyzing the multi-scale correlated space dimension of the jet reactor under the negative pressure condition according to claim 1, wherein the method for determining the saturated embedding dimension of the time sequence based on the Cao algorithm comprises the following steps: For embedding dimension of Defining statistics : Wherein, the Is the length of the time series, Is the optimal time delay calculated according to the mutual information method, Is a time series prediction value obtained by local linear fitting, In order to embed the dimensions of the dimensions, Is the time sequence length; by calculating different embedding dimensions d And (3) with When (when) And Initial follow-up Increase and become larger, and at a certain point The positions are not changed significantly any more and tend to be stable, then the corresponding I.e. as the saturated embedding dimension m.
6. A negative pressure jet reactor multi-scale correlated dimension analysis system, the system comprising: the pressure signal acquisition module is used for acquiring time series pressure signals under different negative pressure conditions of the negative pressure jet reactor; The multi-scale decomposition module is used for carrying out multi-scale decomposition on the acquired pressure signals based on a wavelet transformation method to obtain multi-scale pressure signals; the phase space reconstruction module is used for carrying out phase space reconstruction attractors on the multi-scale pressure signals under different negative pressure conditions based on a phase space reconstruction method to obtain phase space reconstruction attractor images under different scales; Carrying out phase space reconstruction attractors on multi-scale pressure signals under different negative pressure conditions based on a phase space reconstruction method to obtain phase space reconstruction attractors under different scales, wherein the phase space reconstruction attractors are carried out on the multi-scale pressure signals under different negative pressure conditions based on the phase space reconstruction method to obtain phase space reconstruction attractors under different scales; The analysis module is used for acquiring nonlinear characteristics and dynamic behaviors of the flow field under different negative pressure conditions through phase space reconstruction attractor image comparison and correlation dimension analysis; The phase space reconstruction is carried out according to the obtained optimal time delay and saturation embedding dimension, and specifically comprises the following steps: For one of One-dimensional scalar time series of dimensional chaotic attractors N is the time series length, if the dimension is embedded Satisfy the following requirements Reconstructing an attractor which is topologically equivalent to the original system by a delay embedding method; reconstructing a phase space from the obtained optimal time delay and saturation embedding dimensions: Wherein, the Is the saturated embedding dimension which is the number of dimensions, Is the optimal delay time; Nonlinear characteristics and dynamic behaviors of the flow field under different negative pressure conditions are obtained through phase space reconstruction attractor image comparison and correlation dimension analysis, and the method specifically comprises the following steps: In MATLAB, correlationDimension functions are used to calculate the correlation dimension of the time series Based on Grassberger-Procaccia algorithm; Correlation dimension By fitting And (3) with The slope obtained for the linear part of (a): wherein the integral is correlated Representing the probability that the distance between the point pairs is smaller than r in the phase space, wherein r is a preset distance threshold between the point pairs.
7. An electronic device, comprising a processor and a memory; The memory is used for storing one or more program instructions; the processor is configured to execute one or more program instructions for performing the steps of the method for multi-scale spatial correlation dimension analysis of a jet reactor under a negative pressure condition according to any one of claims 1 to 5.

Description

Multi-scale correlated space dimension analysis method for jet reactor under negative pressure condition Technical Field The invention relates to the technical field of jet reactors, in particular to a multi-scale correlated space dimension analysis method of a jet reactor under a negative pressure condition. Background The flow field inside the jet impact reactor has obvious nonlinearity and chaos characteristics, and the movement of the fluid shows complex periodic and aperiodic behaviors. In recent years, with the development of nonlinear dynamics theory, phase space reconstruction and attractor analysis are gradually becoming powerful tools for studying complex flow field characteristics. Through phase space reconstruction, one-dimensional pressure signal data can be mapped into Gao Weixiang space, so that the periodicity and stability of the flow field are revealed. In jet impingement reactors, the complexity of the flow field is mainly reflected in the phenomena of turbulent multi-scale structure, vortex generation and evolution, periodic oscillation of fluid and the like. By phase space reconstruction attractor analysis, nonlinear mechanisms in the jet impingement reactor flow field can be identified and theoretical support is provided for the design and operation of the reactor. But current jet impingement studies under negative pressure are less well studied. Disclosure of Invention The invention provides a multi-scale correlated dimension analysis method of a jet reactor under a negative pressure condition, which is used for carrying out systematic research on nonlinear dynamics characteristics of a flow field in the jet impact reactor, and comprehensively revealing nonlinear characteristics and dynamics behaviors of pressure signals under different negative pressure conditions through phase space reconstruction of an attractor image and correlated dimension analysis. According to a first aspect, in one embodiment there is provided a method of multi-scale spatial correlation dimension analysis of a jet reactor under negative pressure, the method comprising: collecting time series pressure signals under different negative pressure conditions for the negative pressure jet reactor; Performing multi-scale decomposition on the acquired pressure signals based on a wavelet transformation method to obtain multi-scale pressure signals; carrying out phase space reconstruction attractors on the multi-scale pressure signals under different negative pressure conditions based on a phase space reconstruction method to obtain phase space reconstruction attractor images under different scales; and acquiring nonlinear characteristics and dynamic behaviors of the flow field under different negative pressure conditions through phase space reconstruction attractor image comparison and correlation dimension analysis. Further, the method for collecting the time series pressure signals under different negative pressure conditions for the negative pressure jet reactor specifically comprises the following steps: And the pressure signals of the negative pressure area and the slow flow area are respectively collected under the condition of different negative pressure values at the top. Further, the method for performing multi-scale decomposition on the collected pressure signals based on the wavelet transformation method to obtain multi-scale pressure signals specifically comprises the following steps: the Symlet7 wavelet transformation is adopted to carry out multi-scale decomposition on the acquired pressure signals, and the decomposition process is used for decomposing the signals based on a scale function and a wavelet function. Further, based on a phase space reconstruction method, carrying out phase space reconstruction on the multi-scale pressure signals under different negative pressure conditions to obtain phase space reconstruction attractor images under different scales, which specifically comprises the following steps: determining an optimal time delay by quantifying the dependency of two time sequences under different time delays based on a mutual information method; Determining a saturated embedding dimension of the time sequence based on a Cao algorithm; and carrying out phase space reconstruction according to the obtained optimal time delay and the saturation embedding dimension. Further, based on the mutual information method, the optimal time delay is determined by quantifying the dependency relationship of two time sequences under different time delays, and specifically includes: given a time sequence AndCalculating different delaysDelayed mutual informationWhereinIs shown at the time pointUpper part of the cylinderAnd at the point of timeUpper part of the cylinderMutual information between the two; Drawing delayed mutual information Along with itFinding the first local minimum point, and the delay tau corresponding to the corresponding point is the optimal time delay. Further, determining the saturated em