CN108225283A - A kind of interior wave monitoring system and method based on Nonlinear Dynamical Characteristics - Google Patents
A kind of interior wave monitoring system and method based on Nonlinear Dynamical Characteristics Download PDFInfo
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Abstract
The invention discloses a kind of interior waves based on Nonlinear Dynamical Characteristics to monitor system and method, including pressure data acquisition and transmission module：Wave pressure data is obtained, and transmit it to workbench using pressure sensor；Data analysis and processing module：The tidal level information contained in data is filtered out with high-pass filter, obtains containing only the time series of wave pressure field information, using sliding window interception time sequence, and uses Nonlinear Dynamical Characteristics parameter association dimension D2Quantitatively portray its complexity；Interior wave discrimination module：Work as D2When not restrained with embedded dimension increase, interior wave Nonlinear Dynamical Characteristics are not met, wave does not occur in judgement；Work as D2When converging to stationary value with embedded dimension increase, meet interior wave Nonlinear Dynamical Characteristics, wave arrives in system judgement.The method of the present invention program is simple, and interior wave accuracy of judgement is effective, can especially avoid failing to judge for wave in weak energy.
Description
Technical field
The present invention relates to marine monitoring fields, and in particular to a kind of based on wave pressure signal Nonlinear Dynamical Characteristics
Internal wave of ocean monitors system and method.
Background technology
Internal wave of ocean is a kind of Small and Medium Sized wave phenomenon betided inside stratified ocean, to the quality, dynamic in ocean
Amount, the transmission of energy and Global climate change play an important role；Internal wave of ocean generate, propagate and disappear decline during it is caused
Energy exchange have important influence to ocean dynamics process；In addition, internal wave of ocean can lead to Strong shear stream, to marine stone
The safety of the ocean engineerings correlation operations such as oil exploitation has potential threaten.
At present, internal wave of ocean is mainly detected by chain type anchor system's system and synthetic aperture radar (SAR)：The former is based on
The parameters such as temperature, salinity and the speed of the sensor measurement of different depth portray interior wave, are the main of interior wave mechanics parameter
Observation method；The latter is gathered based on the width for generating surface layer flow field respectively at interior wave wave crest and trough dissipates phenomenon with width, so as to cause
The change of extra large surface roughness forms light and dark striated structure in SAR image, is the important hand of interior wave dynamic monitoring
Section.
Pressure sensor is to lay extensive mature equipment in current oceanographic observation system, can also be obtained using pressure observation net
Wave information in obtaining.At present, using pressure sensor extraction internal wave of ocean information method rely primarily on time domain plethysmographic signal and
Spectrum signature carries out analysis extraction, and this method can not effectively differentiate wave in weak intensity.
The present invention will propose that a kind of interior wave based on wave pressure signal Nonlinear Dynamical Characteristics monitors system and method
Overcome the problems, such as of the existing technology.
Invention content
It is special based on wave pressure signal nonlinear kinetics the present invention provides one kind in order to overcome existing technological deficiency
The interior wave monitoring system and method for sign.
The technical scheme is that：
A kind of interior wave monitoring system based on Nonlinear Dynamical Characteristics, including pressure data acquisition and transmission module, number
According to analysis and processing module and Nei Bo discrimination modules；The pressure data obtains and transmission module, for realizing the data of pressure
Acquisition and transmission；Pressure data acquisition and transmission module are transmitted to the number of workbench by the data analysis and processing module
According to carrying out, tidal level filters out and Nonlinear Dynamical Characteristics are analyzed；The interior wave discrimination module, according to data analysis and processing module
Analysis result, whether wave arrives in differentiation.
Further, in the data analysis and processing module, by the pressure sensor for being placed in certain depth in seawater
Wave pressure data is recorded, real-time Data Transmission is recycled or lasts data transmission two ways and pass to workbench.
Further, the data analysis using high-pass digital filter in processing module, being filtered.
Further, in the data analysis and processing module, correlation dimension D can be used in nonlinear dynamic analysis method2,
The correlation dimension D2The complexity of phase space reconstruction can quantitatively be portrayed.
Further, the interior wave discrimination module is according to correlation dimension D2Wave arrives in anomalous variation prompting.
Further, when interior wave passes through, the correlation dimension D of wave pressure signal time series2With the increase of Embedded dimensions
A relatively low stationary value will be converged to.
The method of interior wave monitoring system based on Nonlinear Dynamical Characteristics, includes the following steps：
Step 1)：In pressure data acquisition and transmission module, the pressure sensor in tidal wave instrument is utilized to record hydraulic pressure number
According to data transmission concentrates transmission mode to reach workbench by satellite real-time Data Transmission or historical data；
Step 2)：In data process＆analysis method module, by step 1) data that reach workbench are filtered,
Filtered pressure signal time series x (t1),x(t2),x(t3) ..., wherein x (ti)∈R,ti=t0+ i* Δ t, i=0,
1 ..., ∞, Δ t is the sampling interval, using nonlinear dynamic analysis method, by delay time sequence phase space reconstruction, by
The phase space vector of reconstruct calculates correlation dimension D2The concrete analysis step of nonlinear parameter is as follows：
By time series x (ti), phase space reconstruction can be obtained：
Xi=[x (ti),x(ti-τ),...,x(ti-(d-1)τ)]T, (1)
Wherein, τ is delay time, and d is tieed up to be embedded；Delay time determines that minimum embedding dimension size is led to by mutual information method
It crosses Cao-Method to determine, D is tieed up using nonlinear kinetics parameter association2The complexity of phase space reconstruction is quantitatively described；
Correlation dimension D is calculated by the time series that length is N2, computational methods are as follows：
Wherein, r is by the search radius taken in calculating, and C (W, N, r) is correlation integral, and computational methods are as follows：
Wherein, the value of W is optimal delay τ；θ (x) is Heaviside functions, is met：
D can be obtained by the slope for calculating lnC (W, N, r)-lnr spaces inner curve2, when length of time series N is enough
When big, D2Value can increase with the increase of Embedded dimensions, finally converge on a stationary value, this value is required correlation dimension
Number D2；
Step 3)：To step 2) in filtered pressure wave time series, use window width as 2000 points of slip
Window interception time sequence, sliding step are 1000 data points, calculate correlation dimension D2It changes with time；Normally without interior wave
When, correlation dimension D2Persistently keep higher value；When there is interior wave to arrive, the value of correlation dimension will be converged to the increase of embedded dimension
Lower value.
Further, when taking correlation dimension D2When being 12, normally without interior wave when, correlation dimension D2More than 8；It is arrived when there is interior wave
When coming, correlation dimension D2Less than 4.
Further, in step 2, the high-pass filter of removal tidal level information is second order Butterworth digital filter.
The beneficial effects of the invention are as follows：
(1) method is simple, and cost is relatively low, and wave energy in weak energy is enough reduced and is failed to judge, and can reduce mistake to strong energy perturbation
Sentence；(2) real-time wireless transmissions technology is combined, it can be achieved that wave monitors in real-time online；(3) in addition, it is contemplated that pressure sensor is real
Border application in interior wave detection data efficiency of transmission problem, by nonlinear method judge in the wave period of right time, only the period is wrapped
Low-dimensional signal containing interior wave carries out harmonic analysis, and remote transmission after compression will be greatly improved data transmission efficiency, utilize pressure
Observe in reticular tissue has potential application value in wave detection.
Description of the drawings
Fig. 1 is that a kind of interior wave monitoring system based on wave pressure signal Nonlinear Dynamical Characteristics of the present invention is shown
It is intended to；
Fig. 2 filters out the seawater pressure time signal of tidal level information；
Fig. 3 is correlation dimension D2With the change curve schematic diagram of embedded dimension；
Fig. 4 is (a) time-frequency figure, (b) energy spectrum, (c) correlation dimension D of pressure wave time series2Change with the sampling time
Schematic diagram.
Specific embodiment
Below in conjunction with the accompanying drawings and specific embodiment makees further specifically the objectives, technical solutions, and advantages of the present invention
It is bright.But the scope of the present invention is not limited to this.
Embodiment
A kind of internal wave of ocean monitoring system based on wave pressure signal Nonlinear Dynamical Characteristics is as shown in Figure 1.Specifically
Including：(1) pressure data acquisition and transmission module；(2) data analysis and processing module；(3) interior wave discrimination module.
Wherein, pressure data acquisition and transmission module record wave pressure data, then be transmitted to work using pressure sensor
Make platform；Preferably, hydraulic pressure data, sample frequency 1Hz are recorded using the pressure sensor in tidal wave instrument；Preferably, data
Transmission can concentrate transmission mode to reach workbench by satellite real-time Data Transmission or historical data.
Wherein, the specific implementation method of data process＆analysis method module is as follows：
Tidal level information is filtered out using filtering method, filtered pressure signal oscillogram is as shown in Figure 2.Preferably, with two
Rank Butterworth digital filter is filtered.
To filtered pressure signal time series x (t1),x(t2),x(t3) ... (wherein x (ti)∈R,ti=t0+i*
Δ t, i=0,1 ..., ∞, Δ t are the sampling interval), using nonlinear dynamic analysis method, reconstructed by delay time sequence
Phase space by the phase space vector reconstructed, calculates correlation dimension D2Nonlinear parameter.It is as follows to make a concrete analysis of step：
By time series x (ti), phase space reconstruction can be obtained：
Xi=[x (ti),x(ti-τ),...,x(ti-(d-1)τ)]T, (1)
Wherein, τ is delay time, and d is tieed up to be embedded.Preferably, delay time can be determined by mutual information method, minimum embedding
Enter to tie up size and be determined by Cao-Method.
Further, D is tieed up using nonlinear kinetics parameter association2The complexity of phase space reconstruction is quantitatively described.
Correlation dimension D is calculated by the time series that length is N2, computational methods are as follows：
Wherein, r is by the search radius taken in calculating, and C (W, N, r) is correlation integral, and computational methods are as follows：
Wherein, the value of W is optimal delay τ.θ (x) is Heaviside functions, is met：
D can be obtained by the slope for calculating lnC (W, N, r)-lnr spaces inner curve2, when length of time series N is enough
When big, D2Value can increase with the increase of Embedded dimensions, finally converge on a stationary value, this value is required correlation dimension
Number.
Attached drawing 3 show the correlation dimension D of Nei Bo and the wave pressure signal without interior wave2It is advised with the variation of embedded dimension
Rule.It can be seen from the figure that when pressure signal does not include interior wave, complexity is higher, and corresponding correlation dimension is with insertion
Dimension, which increases, not to be restrained；When interior wave arrives, the complexity of pressure wave signal is relatively low, and corresponding correlation dimension is relatively low.As right
Than for the random noise signal of an input, it is also to show as not restraining to calculate correlation dimension with the increase of Embedded dimensions.
This is exactly the basic principle that wave differentiates in the present invention realizes.
In addition, the implementation of interior wave discrimination module is：To filtered pressure wave time series, use window width for
2000 points of sliding window interception time sequence, sliding step are 1000 data points, calculate correlation dimension D2It changes with time.
When normally without interior wave, correlation dimension persistently keeps higher value, correlation dimension value when the embedded dimension of such as acquisition is 12, and consistently greater than 8；When
When having interior wave arrival, the value of correlation dimension will converge to lower value, generally less than 4 with the increase of embedded dimension.In order to illustrate this side
Method can be used for wave in real-time online and differentiate that Fig. 4 (c) gives correlation dimension versus time curve.It can from Fig. 4 (c)
To find out, correlation dimension jumps to one by not convergent higher dimensionality (being 8.5 when embedded dimension is 12 hourly values) when interior wave passes through
A relatively low convergence dimension (mean value 2.7).It is more more effective than conventional method in order to embody this method, we illustrate time frequency analysis
The analysis result of method and energy spectrometry, as shown in Fig. 4 (a), Fig. 4 (b).By comparing as it can be seen that conventional method is in second
Wave can not accurate judgement, and nonlinear parameter D2It is very sensitive to the response of wave signal in faint energy.
Present invention is not limited to the embodiments described above, in the case of without departing substantially from design principle of the present invention, art technology
Any conspicuously improved, replacement or deformation that personnel can make all belong to the scope of protection of the present invention.
Claims (9)
1. a kind of interior wave monitoring system based on Nonlinear Dynamical Characteristics, it is characterised in that：It obtains and passes including pressure data
Defeated module, data analysis and processing module and Nei Bo discrimination modules；The pressure data obtains and transmission module, for realizing pressure
The data acquisition and transmission of power；Pressure data is obtained and transmission module is transmitted to work by the data analysis and processing module
The data progress tidal level of platform filters out and Nonlinear Dynamical Characteristics analysis；The interior wave discrimination module, according to data analysis with
The analysis result of processing module, whether wave arrives in differentiation.
2. a kind of interior wave monitoring system based on Nonlinear Dynamical Characteristics according to claim 1, it is characterised in that：It is described
Data analysis is in processing module, wave pressure data, then profit are recorded by the pressure sensor for being placed in certain depth in seawater
With real-time Data Transmission or last data transmission two ways and pass to workbench.
3. a kind of interior wave monitoring system based on Nonlinear Dynamical Characteristics according to claim 1, it is characterised in that：It is described
Data analysis using high-pass digital filter in processing module, being filtered.
4. a kind of interior wave monitoring system based on Nonlinear Dynamical Characteristics according to claim 1, it is characterised in that：It is described
In data analysis and processing module, correlation dimension D can be used in nonlinear dynamic analysis method2, the correlation dimension D2It can quantitatively carve
Draw the complexity of phase space reconstruction.
5. a kind of interior wave monitoring system based on Nonlinear Dynamical Characteristics according to claim 4, it is characterised in that：It is described
Interior wave discrimination module is according to correlation dimension D2Wave arrives in anomalous variation prompting.
6. a kind of interior wave monitoring system based on Nonlinear Dynamical Characteristics according to claim 4, it is characterised in that：Interior wave
When passing through, the correlation dimension D of wave pressure signal time series2A relatively low stabilization will be converged to the increase of Embedded dimensions
Value.
7. the method for the interior wave monitoring system according to any one of claims 1 to 6 based on Nonlinear Dynamical Characteristics,
It is characterized in that：Include the following steps：
Step 1)：In pressure data acquisition and transmission module, the pressure sensor in tidal wave instrument is utilized to record hydraulic pressure data, number
Transmission mode is concentrated to reach workbench by satellite real-time Data Transmission or historical data according to transmission；
Step 2)：In data process＆analysis method module, by step 1) data that reach workbench are filtered, filter
Pressure signal time series x (t afterwards1),x(t2),x(t3) ..., wherein x (ti)∈R,ti=t0+ i* Δ t, i=0,1 ...,
∞, Δ t are the sampling interval, using nonlinear dynamic analysis method, by delay time sequence phase space reconstruction, by what is reconstructed
Phase space vector calculates correlation dimension D2The concrete analysis step of nonlinear parameter is as follows：
By time series x (ti), phase space reconstruction can be obtained：
Xi=[x (ti),x(ti-τ),...,x(ti-(d-1)τ)]T, (1)
Wherein, τ is delay time, and d is tieed up to be embedded；Delay time determines that minimum embedding dimension size passes through by mutual information method
Cao-Method is determined, D is tieed up using nonlinear kinetics parameter association2The complexity of phase space reconstruction is quantitatively described；It is logical
It crosses the time series that length is N and calculates correlation dimension D2, computational methods are as follows：
Wherein, r is by the search radius taken in calculating, and C (W, N, r) is correlation integral, and computational methods are as follows：
Wherein, the value of W is optimal delay τ；θ (x) is Heaviside functions, is met：
D can be obtained by the slope for calculating lnC (W, N, r)-lnr spaces inner curve2, when length of time series N is sufficiently large,
D2Value can increase with the increase of Embedded dimensions, finally converge on a stationary value, this value is required correlation dimension D2；
Step 3)：To step 2) in filtered pressure wave time series, use window width for 2000 points sliding window cut
Time series is taken, sliding step is 1000 data points, calculates correlation dimension D2It changes with time；When normally without interior wave, close
Join dimension D2Persistently keep higher value；When there is interior wave to arrive, the value of correlation dimension will converge to relatively low with the increase of embedded dimension
Value.
8. the method for the interior wave monitoring system according to claim 7 based on Nonlinear Dynamical Characteristics, which is characterized in that
When taking correlation dimension D2When being 12, normally without interior wave when, correlation dimension D2More than 8；When there is interior wave to arrive, correlation dimension D2It is small
In 4.
9. the method for the interior wave monitoring system according to claim 7 based on Nonlinear Dynamical Characteristics, which is characterized in that
In step 2, the high-pass filter of removal tidal level information is second order Butterworth digital filter.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114646304A (en) * | 2022-03-11 | 2022-06-21 | 广州海洋地质调查局 | Ocean internal wave identification method based on multi-beam data |
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| CN114646304A (en) * | 2022-03-11 | 2022-06-21 | 广州海洋地质调查局 | Ocean internal wave identification method based on multi-beam data |
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