CN106909532A  A kind of method and system of the relevance of analysis ground total electric field and airborne particle thing Size  Google Patents
A kind of method and system of the relevance of analysis ground total electric field and airborne particle thing Size Download PDFInfo
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 CN106909532A CN106909532A CN201710035258.9A CN201710035258A CN106909532A CN 106909532 A CN106909532 A CN 106909532A CN 201710035258 A CN201710035258 A CN 201710035258A CN 106909532 A CN106909532 A CN 106909532A
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Abstract
The invention discloses a kind of analysis ground total electric field and the method for the relevance of airborne particle thing Size, it is characterised in that methods described includes：Ground total electric field data and airborne particle thing particle diameter modal data are obtained respectively, and the ground total electric field data and the airborne particle thing particle diameter modal data are standardized respectively；Decorrelative transformation is carried out to the ground total electric field data and the airborne particle thing particle diameter modal data respectively；Canonical correlation analysis are carried out to the ground total electric field data by decorrelative transformation and airborne particle thing particle diameter modal data respectively, the canonical correlation coefficient of ground total electric field data and the canonical correlation coefficient of airborne particle thing particle diameter modal data is obtained；And canonical correlation coefficient respectively to the ground total electric field data and the canonical correlation coefficient of the airborne particle thing particle diameter modal data are analyzed, and judge the relevance of the ground total electric field data and airborne particle thing particle diameter modal data.
Description
Technical field
The present invention relates to technical field of HVDC transmission, and more particularly, to one kind analysis ground total electric field
With the method and system of the relevance of airborne particle thing Size.
Background technology
With the economic sustained and rapid development of China, particularly energy demand, the sustainable growth of electric power resource demand.But China
Electric power resource generally Xi Duodong is few, northern many south are few, with distribution and the unbalanced feature of demand.Therefore it is to realize electric power resource
Distribute rationally, China is by " transferring electricity from the west to the east, north and south supply mutually, national network " as the strategic objective of power network development.This means need
Build extensive, remote, efficient power transmission engineering, high voltage dc transmission technology turn into realize this target it is only it
Choosing.
During HVDC transmission line transmission electric energy, because wire electrical discharge inevitably results from corona current, wireless
Electrical interference, audible noise and total electric field etc., cause electric energy loss and other environmental problems.In order to by UHVDC Transmission Lines
Ground total electric field is controlled in the reasonable scope, and urgent need researching DC circuit ground total electric field is associated with airborne particle thing
System, is subsequently to carry out airborne particle thing to study ready to the Influencing Mechanism of ground total electric field.
The content of the invention
In order to solve the above problems, according to an aspect of the invention, there is provided a kind of analysis ground total electric field and sky
The method of the relevance of middle particle size spectrum, methods described includes：
Ground total electric field data and airborne particle thing particle diameter modal data are obtained respectively, and respectively to ground synthesis electricity
Field data and the airborne particle thing particle diameter modal data are standardized；
Decorrelative transformation is carried out to the ground total electric field data and the airborne particle thing particle diameter modal data respectively；
Typical case is carried out to the ground total electric field data by decorrelative transformation and airborne particle thing particle diameter modal data respectively
Correlation analysis, obtain the canonical correlation coefficient of ground total electric field data and the canonical correlation of airborne particle thing particle diameter modal data
Coefficient；
Canonical correlation coefficient respectively to the ground total electric field data and the airborne particle thing particle diameter modal data
Canonical correlation coefficient is analyzed, and judges the relevance of the ground total electric field data and airborne particle thing particle diameter modal data.
Preferably, wherein described enter to the ground total electric field data and the airborne particle thing particle diameter modal data respectively
Row decorrelative transformation includes：
The ground total electric field data and the corresponding matrix data of the airborne particle thing particle diameter modal data are entered respectively
Line translation or rank transformation, obtain corresponding stepped matrix；
Calculate the correlation matrix R=[r of the ground total electric field data or the particle size modal data_{ij}],
And strong correlation weight matrix A=[a are calculated according to the correlation matrix R_{ij}],
Wherein, τ is strong correlation coefficient threshold, is strong correlation if two coefficient correlations of variable are more than τ；If two changes
The coefficient correlation of amount is less than τ, then for weak related or uncorrelated；
The corresponding variable of the maximum weight of the often capable weight sum of strong correlation weight matrix A is proposed respectively, obtain through
Cross the ground total electric field data and airborne particle thing particle diameter modal data of decorrelative transformation.
Preferably, wherein described respectively to the ground total electric field data and airborne particle thing particle diameter by decorrelative transformation
Modal data carries out canonical correlation analysis, obtains the canonical correlation coefficient and airborne particle thing Size of ground total electric field data
The canonical correlation coefficient of data includes：
By by the ground total electric field data of decorrelative transformation and airborne particle thing particle diameter modal data respectively by sample set X
Represented with Y, wherein the ground total electric field data are made up of the ground total electric field of p various location, it is described aerial
Particle size modal data is made up of the particle size spectrum of q differentgrain diameter size, has N number of observation for each variable
Value, the sample set X and Y is expressed as：
Order vector α=[α_{1},α_{2},…,α_{p}]^{T}With β=[β_{1},β_{2},…,β_{q}]^{T}The allusion quotation of sample set X and Y linear combination is represented respectively
Type coefficient correlation, then linear combinationAndMaximize relevance function：
Canonical correlation analysis is expressed as following optimization problem：
Using Lagrange multiplier methods, the Lagrange functions for obtaining are as follows：
Partial derivative is asked to α and β respectively, is madeObtain：
The covariance matrix Σ of marker samples collection X and Y_{11}=XX^{T},Σ_{22}=YY^{T}And Crosscovariance Σ_{12}=XY^{T},
Σ_{21}=YX^{T}, α and β is calculated respectively.
Preferably, wherein described respectively to the canonical correlation coefficient and the airborne particle of the ground total electric field data
The canonical correlation coefficient of thing particle diameter modal data is analyzed, and judges the ground total electric field data and airborne particle thing Size
The relevance of data includes：
Canonical correlation coefficient respectively to the ground total electric field data and the airborne particle thing particle diameter modal data
Canonical correlation coefficient takes absolute value；
The absolute value is compared with canonical correlation coefficient threshold value respectively, and the ground is judged according to comparative result
The relevance of total electric field data and airborne particle thing particle diameter modal data, if the absolute value of canonical correlation coefficient is more than canonical correlation
Coefficient threshold, then illustrate that the corresponding variable of the canonical correlation coefficient is strong with the relevance of another data；If canonical correlation coefficient
Absolute value be less than canonical correlation coefficient threshold value, then illustrate associating for the corresponding variable of the canonical correlation coefficient and another data
Property is weak.
According to another aspect of the present invention, there is provided a kind of analysis ground total electric field and airborne particle thing Size
The system of relevance, the system includes：Standardization unit, decorrelative transformation unit, canonical correlation coefficient computing unit
With relevance determining unit.
The standardization unit, obtains ground total electric field data and airborne particle thing particle diameter modal data respectively, and
The ground total electric field data and the airborne particle thing particle diameter modal data are standardized respectively；
The decorrelative transformation unit, respectively to the ground total electric field data and the airborne particle thing Size number
According to carrying out decorrelative transformation；
The canonical correlation coefficient computing unit, respectively to the ground total electric field data by decorrelative transformation and in the air
Particle size modal data carries out canonical correlation analysis, obtain ground total electric field data canonical correlation coefficient and aerial
The canonical correlation coefficient of grain thing particle diameter modal data；
The relevance determining unit, the respectively canonical correlation coefficient to the ground total electric field data and described aerial
The canonical correlation coefficient of particle size modal data is analyzed, and judges the ground total electric field data and airborne particle thing grain
The relevance of footpath modal data.
Preferably, wherein described enter to the ground total electric field data and the airborne particle thing particle diameter modal data respectively
Row decorrelative transformation includes：
The ground total electric field data and the corresponding matrix data of the airborne particle thing particle diameter modal data are entered respectively
Line translation or rank transformation, obtain corresponding stepped matrix；
Calculate the correlation matrix R=[r of the ground total electric field data or the particle size modal data_{ij}],
And strong correlation weight matrix A=[a are calculated according to the correlation matrix R_{ij}],
Wherein, τ is strong correlation coefficient threshold, is strong correlation if two coefficient correlations of variable are more than τ；If two changes
The coefficient correlation of amount is less than τ, then for weak related or uncorrelated；
The corresponding variable of the maximum weight of the often capable weight sum of strong correlation weight matrix A is proposed respectively, obtain through
Cross the ground total electric field data and airborne particle thing particle diameter modal data of decorrelative transformation.
Preferably, wherein described respectively to the ground total electric field data and airborne particle thing particle diameter by decorrelative transformation
Modal data carries out canonical correlation analysis, obtains the canonical correlation coefficient and airborne particle thing Size of ground total electric field data
The canonical correlation coefficient of data includes：
By by the ground total electric field data of decorrelative transformation and airborne particle thing particle diameter modal data respectively by sample set X
Represented with Y, wherein the ground total electric field data are made up of the ground total electric field of p various location, it is described aerial
Particle size modal data is made up of the particle size spectrum of q differentgrain diameter size, has N number of observation for each variable
Value, the sample set X and Y is expressed as：
Order vector α=[α_{1},α_{2},…,α_{p}]^{T}With β=[β_{1},β_{2},…,β_{q}]^{T}The allusion quotation of sample set X and Y linear combination is represented respectively
Type coefficient correlation, then linear combinationAndMaximize relevance function：
Canonical correlation analysis is expressed as following optimization problem：
Using Lagrange multiplier methods, the Lagrange functions for obtaining are as follows：
Partial derivative is asked to α and β respectively, is madeObtain：
The covariance matrix Σ of marker samples collection X and Y_{11}=XX^{T},Σ_{22}=YY^{T}And Crosscovariance Σ_{12}=XY^{T},
Σ_{21}=YX^{T}, α and β is calculated respectively.
Preferably, wherein described respectively to the canonical correlation coefficient and the airborne particle of the ground total electric field data
The canonical correlation coefficient of thing particle diameter modal data is analyzed, and judges the ground total electric field data and airborne particle thing Size
The relevance of data includes：
Canonical correlation coefficient respectively to the ground total electric field data and the airborne particle thing particle diameter modal data
Canonical correlation coefficient takes absolute value；
The absolute value is compared with canonical correlation coefficient threshold value respectively, and the ground is judged according to comparative result
The relevance of total electric field data and airborne particle thing particle diameter modal data, if the absolute value of canonical correlation coefficient is more than canonical correlation
Coefficient threshold, then illustrate that the corresponding variable of the canonical correlation coefficient is strong with the relevance of another data；If canonical correlation coefficient
Absolute value be less than canonical correlation coefficient threshold value, then illustrate associating for the corresponding variable of the canonical correlation coefficient and another data
Property is weak.
The beneficial effects of the present invention are：
1. the present invention employs decorrelation method to the variable of some strong incidence relations of data inside, and data are eliminated with this
Internal strong incidence relation is on another group of relevance influence of data.
2. the present invention using canonical correlation analysis analysis two groups of abilities of variable to carry out data incidence relation divide
Analysis, have effectively achieved the correlation analysis between amount data complicated and changeable.
3. technical scheme only considers data in itself, to experiment condition and every group of data variable number etc. without specific
It is required that, highly versatile.
Brief description of the drawings
By reference to the following drawings, illustrative embodiments of the invention can be more fully understood by：
Fig. 1 is the analysis ground total electric field and the relevance of airborne particle thing Size according to embodiment of the present invention
The flow chart of method 100；
Fig. 2 is the signal of the ground total electric field data and airborne particle thing particle diameter modal data according to embodiment of the present invention
Figure；
Fig. 3 is the schematic diagram of the correlation matrix of the ground total electric field data according to embodiment of the present invention；
Fig. 4 is the schematic diagram of the correlation matrix of the airborne particle thing particle diameter modal data according to embodiment of the present invention；
Fig. 5 is the ground total electric field data and airborne particle thing Size after the decorrelation according to embodiment of the present invention
The schematic diagram of data；
Fig. 6 is the strong phase of the canonical variable in the ground total electric field data according to embodiment of the present invention and its dependent variable
The schematic diagram of pass relation；
Fig. 7 is canonical variable and its dependent variable in the airborne particle thing particle diameter modal data according to embodiment of the present invention
The schematic diagram of strong correlation relation；
Fig. 8 is the canonical correlation system of the ground total electric field data of four various locations according to embodiment of the present invention
Several schematic diagrames；
Fig. 9 is the typical case of the airborne particle thing particle diameter modal data of five kinds of differentgrain diameter sizes according to embodiment of the present invention
The schematic diagram of coefficient correlation；
Figure 10 be according to the ground total electric field data and airborne particle thing particle diameter modal data of embodiment of the present invention most
The corresponding scatter diagram of excellent linear combination；
Figure 11 is the analysis ground total electric field and the relevance of airborne particle thing Size according to embodiment of the present invention
System 1100 structural representation.
Specific embodiment
With reference now to accompanying drawing, illustrative embodiments of the invention are introduced, however, the present invention can use many different shapes
Formula is implemented, and is not limited to embodiment described herein, there is provided these embodiments are to disclose at large and fully
The present invention, and fully pass on the scope of the present invention to person of ordinary skill in the field.For showing for being illustrated in the accompanying drawings
Term in example property implementation method is not limitation of the invention.In the accompanying drawings, identical cells/elements are attached using identical
Icon is remembered.
Unless otherwise indicated, term (including scientific and technical terminology) used herein has to person of ordinary skill in the field
It is common to understand implication.Further it will be understood that the term limited with usually used dictionary, is appreciated that and it
The linguistic context of association area has consistent implication, and is not construed as Utopian or excessively formal meaning.
A kind of analysis ground total electric field and the method for the relevance of airborne particle thing Size that the present invention is provided are bases
Proposed in canonical correlation analysis, associated making full use of canonical correlation analysis two groups of abilities of variable of analysis to carry out data
The analysis of relation.Wherein, by the method for decorrelation, the internal strong incidence relation of data is eliminated to another group of association of data
Property influence, finally have effectively achieved the correlation analysis between amount data complicated and changeable.
Fig. 1 is the analysis ground total electric field and the relevance of airborne particle thing Size according to embodiment of the present invention
The flow chart of method 100.As indicated with 1, the method for the relevance of shown analysis ground total electric field and airborne particle thing Size
100 since step 101 place, and ground total electric field data and airborne particle thing particle diameter modal data are obtained respectively in step 101, and
The ground total electric field data and the airborne particle thing particle diameter modal data are standardized respectively.According to Fig. 2
The ground total electric field data of embodiment of the present invention and the schematic diagram of airborne particle thing particle diameter modal data.As shown in Fig. 2 described
The upper figure of schematic diagram is 12 sample set X of the ground total electric field data of diverse location, wherein, abscissa represents that 500 are adopted
At the sample moment, ordinate is electric field intensity value, and the broken line of different colours represents under diverse location that electric field changes with time situation；Under
Figure is 17 kinds of sample set Y of the airborne particle thing particle diameter modal data of differentgrain diameter size, wherein, the sampling instant shown in abscissa
Corresponding with the sampling instant of sample set X identical, ordinate is particle size modal data, and the broken line of different colours represents different grains
The particulate matter of footpath size changes with time situation.First have to ground total electric field data and airborne particle thing particle diameter modal data
It is standardized respectively so that all variables have zeromean and standard variance characteristic.Assuming that for electric field data or particulate matter
A certain variable x in data, it is assumed that N number of observation of variable is x=[x_{1},x_{2},…,x_{N}]^{T}.Then the data after standardization are：
Wherein,It is the average of variable,It is the variance of variable.
Preferably, in step 102 respectively to the ground total electric field data and the airborne particle thing particle diameter modal data
Carry out decorrelative transformation.Preferably, wherein described respectively to the ground total electric field data and the airborne particle thing particle diameter
Modal data carries out decorrelative transformation to be included：Respectively to the ground total electric field data and the airborne particle thing particle diameter modal data
Corresponding matrix data enters line translation or rank transformation, obtains corresponding stepped matrix；Calculate the ground total electric field data
Or the correlation matrix R=[r of the particle size modal data_{ij}], and strong correlation is calculated according to the correlation matrix R
Weight matrix A=[a_{ij}],
Wherein, τ is strong correlation coefficient threshold, is strong correlation if two coefficient correlations of variable are more than τ；If two changes
The coefficient correlation of amount is less than τ, then for weak related or uncorrelated；And respectively by the often capable weight of strong correlation weight matrix A it
Variable corresponding with maximum weight is proposed, obtained by ground total electric field data and airborne particle the thing grain of decorrelative transformation
Footpath modal data.Fig. 3 is the schematic diagram of the correlation matrix of the ground total electric field data according to embodiment of the present invention.As schemed
Shown in 3, the electricfield intensity under corresponding two positions in 12 diverse locations is represented respectively, strength factor is from 0.75 to 1.Wherein color
The color of block is deeper, and the relevance of the electricfield intensity under corresponding two positions of expression is stronger；The color of color lump is more shallow, and it is right to represent
The relevance of the electricfield intensity under two positions answered is weaker.Fig. 4 is the airborne particle thing particle diameter according to embodiment of the present invention
The schematic diagram of the correlation matrix of modal data.As shown in figure 4, representing two kinds of particle sizes in 17 in differentgrain diameter respectively
The corresponding coefficient correlation of particulate matter.Wherein, the color of color lump is deeper, represents the particle size spectrum of corresponding two kinds of particle sizes
The relevance of data is stronger；The color of color lump is more shallow, represents the pass of the particle size modal data of corresponding two kinds of particle sizes
Connection property is weaker.Decorrelation operation is carried out to the strong correlation amount in ground total electric field data or particle size modal data, specifically
Comprise the following steps：Given strong correlation coefficient threshold τ, when two coefficient correlations of variable are more than τ, then regards as strong correlation,
Otherwise it is weak related or uncorrelated；Calculate the correlation matrix R=of ground total electric field data or particle size modal data
[r_{ij}], strong correlation weight matrix A=[a are calculated according to correlation matrix R_{ij}], wherein：
The often capable weight sum of strong correlation weight matrix A is calculated, weight limit and corresponding variable are canonical variable
And propose, and the variable of strong correlation is rejected therewith；Repeat the above steps, until all of variable is suggested or is rejected, then
The data set that all variables being suggested are constituted is then the data after decorrelation.Fig. 5 is going according to embodiment of the present invention
The schematic diagram of ground total electric field data and airborne particle thing particle diameter modal data after correlation.As shown in figure 5, upper figure is to extract
4 exemplary positions under ground total electric field data, wherein, abscissa represents 500 sampling instants, and ordinate is electricfield intensity
Value, the broken line of different colours represents after decorrelation under 4 exemplary positions that electric field changes with time situation；Figure below is extracted
5 kinds of particle size modal datas of typical particle diameter size, wherein, during the sampling of sampling instant and electric field data shown in abscissa
Carve correspondence identical, ordinate is particle size modal data, the broken line of different colours represents 5 kinds of typical particle diameter sizes after decorrelation
Particulate matter change with time situation.Fig. 6 is the typical case's change in the ground total electric field data according to embodiment of the present invention
The schematic diagram of the strong correlation relation of amount and its dependent variable.As shown in fig. 6, the schematic diagram is the allusion quotation of position 3,7,10 and 12 4
The strong correlation relation of type position and its dependent variable, wherein each exemplary position one color lump color of correspondence, each position correspondence one
Individual color lump color, representing the ground total electric field of the position that the position represents with color lump has very strong dependency relation.According to Fig. 7
The signal of the strong correlation relation of canonical variable and its dependent variable in the airborne particle thing particle diameter modal data of embodiment of the present invention
Figure.As shown in fig. 7, the schematic diagram be in particle size modal data 6,11,13,15 and 17 5 kind of canonical variable and other
The strong correlation relation of variable, wherein each canonical variable correspondence one color lump color, each particle size all with a color lump
Correspondence, representing the particle size spectrum of the particle size that the position represents with color lump has very strong dependency relation.
Preferably, in step 103 respectively to ground total electric field data and airborne particle the thing grain by decorrelative transformation
Footpath modal data carries out canonical correlation analysis, obtains the canonical correlation coefficient and airborne particle thing particle diameter of ground total electric field data
The canonical correlation coefficient of modal data.Preferably, wherein it is described respectively to the ground total electric field data by decorrelative transformation and
Airborne particle thing particle diameter modal data carries out canonical correlation analysis, obtains the canonical correlation coefficient and sky of ground total electric field data
The canonical correlation coefficient of middle particle size modal data includes：
By by the ground total electric field data of decorrelative transformation and airborne particle thing particle diameter modal data respectively by sample set X
Represented with Y, wherein the ground total electric field data are made up of the ground total electric field of p various location, it is described aerial
Particle size modal data is made up of the particle size spectrum of q differentgrain diameter size, has N number of observation for each variable
Value, the sample set X and Y is expressed as：
Order vector α=[α_{1},α_{2},…,α_{p}]^{T}With β=[β_{1},β_{2},…,β_{q}]^{T}The allusion quotation of sample set X and Y linear combination is represented respectively
Type coefficient correlation, then linear combinationAndMaximize relevance function：
Canonical correlation analysis is expressed as following optimization problem：
Using Lagrange multiplier methods, the Lagrange functions for obtaining are as follows：
Partial derivative is asked to α and β respectively, is madeObtain：
The covariance matrix Σ of marker samples collection X and Y_{11}=XX^{T},Σ_{22}=YY^{T}And Crosscovariance Σ_{12}=XY^{T},
Σ_{21}=YX^{T}, α and β is calculated respectively.Fig. 8 is the ground synthesis electricity of four various locations according to embodiment of the present invention
The schematic diagram of the canonical correlation coefficient of field data.As shown in figure 8, open circle represents the position given up during decorrelation, it is real
Numerical value where heart circle represents the absolute value of the corresponding canonical correlation coefficient in the position, i.e., the ground synthesis at position 3,7,10 and 12
The absolute value of the canonical correlation coefficient α of electric field data, the scope of coefficient correlation absolute value is 0 to 1.Fig. 9 is according to of the invention real
Apply the schematic diagram of the canonical correlation coefficient of the airborne particle thing particle diameter modal data of five kinds of differentgrain diameter sizes of mode.Such as Fig. 9 institutes
Show, numerical value where open circle represents the particle diameter given up during decorrelation, solid rim represents the corresponding canonical correlation of the particle diameter
The absolute value of coefficient, i.e., 6,11,13,15 and the corresponding canonical correlation coefficient β of 17 5 kind of particle size modal data absolute value,
The scope of coefficient correlation absolute value is 0 to 1.
Figure 10 be according to the ground total electric field data and airborne particle thing particle diameter modal data of embodiment of the present invention most
The corresponding scatter diagram of excellent linear combination.As shown in Figure 10, it is linear combinationWith
Distribution on two dimensional surface, abscissa represents that, by the electric field data after linear combination, ordinate is represented by linear combination
Particulate count evidence afterwards, electric field data is corresponding with particulate count evidence under each discrete point represents a certain sampling instant.Wherein, from
Scatterplot is distributed near the angular bisector of one or three quadrants, illustrates that linear combination x, y have strong correlation.
Preferably, in step 104 canonical correlation coefficient respectively to the ground total electric field data and described aerial
The canonical correlation coefficient of grain thing particle diameter modal data is analyzed, and judges the ground total electric field data and airborne particle thing particle diameter
The relevance of modal data.Preferably, wherein the canonical correlation coefficient respectively to the ground total electric field data and described
The canonical correlation coefficient of airborne particle thing particle diameter modal data is analyzed, and judges the ground total electric field data and airborne particle
The relevance of thing particle diameter modal data includes：
Canonical correlation coefficient respectively to the ground total electric field data and the airborne particle thing particle diameter modal data
Canonical correlation coefficient takes absolute value；
The absolute value is compared with canonical correlation coefficient threshold value respectively, and the ground is judged according to comparative result
The relevance of total electric field data and airborne particle thing particle diameter modal data, if the absolute value of canonical correlation coefficient is more than canonical correlation
Coefficient threshold, then illustrate that the corresponding variable of the canonical correlation coefficient is strong with the relevance of another data；If canonical correlation coefficient
Absolute value be less than canonical correlation coefficient threshold value, then illustrate associating for the corresponding variable of the canonical correlation coefficient and another data
Property is weak.
The variable got rid of in for being operated in decorrelation, they are not examined due to strong correlation in canonical variable
Consider, thus their influences to another data set are identical with the influence degree of its correspondence canonical variable.
Figure 11 is the analysis ground total electric field and the relevance of airborne particle thing Size according to embodiment of the present invention
System 1100 structural representation.As shown in figure 11, the pass of analysis ground total electric field and airborne particle thing Size
The system 1100 of connection property includes：Standardization unit 1101, decorrelative transformation unit 1102, canonical correlation coefficient computing unit
1103 and relevance determining unit 1104.Preferably, ground total electric field is obtained respectively in the standardization unit 1101
Data and airborne particle thing particle diameter modal data, and respectively to the ground total electric field data and the airborne particle thing Size
Data are standardized.
Preferably, in the decorrelative transformation unit 1102 respectively to ground total electric field data and described aerial
Grain thing particle diameter modal data carries out decorrelative transformation.Preferably, wherein described respectively to ground total electric field data and described
Airborne particle thing particle diameter modal data carries out decorrelative transformation to be included：
The ground total electric field data and the corresponding matrix data of the airborne particle thing particle diameter modal data are entered respectively
Line translation or rank transformation, obtain corresponding stepped matrix；
Calculate the correlation matrix R=[r of the ground total electric field data or the particle size modal data_{ij}],
And strong correlation weight matrix A=[a are calculated according to the correlation matrix R_{ij}],
Wherein, τ is strong correlation coefficient threshold, is strong correlation if two coefficient correlations of variable are more than τ；If two changes
The coefficient correlation of amount is less than τ, then for weak related or uncorrelated；
The corresponding variable of the maximum weight of the often capable weight sum of strong correlation weight matrix A is proposed respectively, obtain through
Cross the ground total electric field data and airborne particle thing particle diameter modal data of decorrelative transformation.
Preferably, electricity is synthesized to the ground by decorrelative transformation respectively in the canonical correlation coefficient computing unit 1103
Field data and airborne particle thing particle diameter modal data carry out canonical correlation analysis, obtain the canonical correlation of ground total electric field data
The canonical correlation coefficient of coefficient and airborne particle thing particle diameter modal data.Preferably, wherein described respectively to by decorrelative transformation
Ground total electric field data and airborne particle thing particle diameter modal data carry out canonical correlation analysis, obtain ground total electric field number
According to canonical correlation coefficient and the canonical correlation coefficient of airborne particle thing particle diameter modal data include：
By by the ground total electric field data of decorrelative transformation and airborne particle thing particle diameter modal data respectively by sample set X
Represented with Y, wherein the ground total electric field data are made up of the ground total electric field of p various location, it is described aerial
Particle size modal data is made up of the particle size spectrum of q differentgrain diameter size, has N number of observation for each variable
Value, the sample set X and Y is expressed as：
Order vector α=[α_{1},α_{2},…,α_{p}]^{T}With β=[β_{1},β_{2},…,β_{q}]^{T}The allusion quotation of sample set X and Y linear combination is represented respectively
Type coefficient correlation, then linear combinationAndMaximize relevance function：
Canonical correlation analysis is expressed as following optimization problem：
Using Lagrange multiplier methods, the Lagrange functions for obtaining are as follows：
Partial derivative is asked to α and β respectively, is madeObtain：
The covariance matrix Σ of marker samples collection X and Y_{11}=XX^{T},Σ_{22}=YY^{T}And Crosscovariance Σ_{12}=XY^{T},
Σ_{21}=YX^{T}, α and β is calculated respectively.
Preferably, in the relevance determining unit 1104 respectively to the canonical correlation system of the ground total electric field data
Number and the canonical correlation coefficient of the airborne particle thing particle diameter modal data are analyzed, judge the ground total electric field data with
The relevance of airborne particle thing particle diameter modal data.Preferably, wherein described respectively to the typical case of the ground total electric field data
The canonical correlation coefficient of coefficient correlation and the airborne particle thing particle diameter modal data is analyzed, and judges the ground total electric field
The relevance of data and airborne particle thing particle diameter modal data includes：Respectively to the canonical correlation system of the ground total electric field data
The canonical correlation coefficient of number and the airborne particle thing particle diameter modal data takes absolute value；And by the absolute value respectively with typical case
Correlation coefficient threshold is compared, and judges the ground total electric field data and airborne particle thing Size according to comparative result
The relevance of data, if the absolute value of canonical correlation coefficient is more than canonical correlation coefficient threshold value, illustrates the canonical correlation system
The corresponding variable of number is strong with the relevance of another data；If the absolute value of canonical correlation coefficient is less than canonical correlation coefficient threshold value,
Then illustrate that the corresponding variable of the canonical correlation coefficient is weak with the relevance of another data.
The present invention is described by reference to a small amount of implementation method.However, it is known in those skilled in the art, as
What subsidiary Patent right requirement was limited, except the present invention other embodiments disclosed above equally fall of the invention
In the range of.
Normally, all terms for using in the claims are all solved according to them in the usual implication of technical field
Release, unless clearly defined in addition wherein.It is all of to be all opened ground with reference to " one/described/be somebody's turn to do [device, component etc.] "
At least one of described device, component etc. example is construed to, unless otherwise expressly specified.Any method disclosed herein
Step need not all be run with disclosed accurate order, unless explicitly stated otherwise.
Claims (8)
1. the method for the relevance of a kind of analysis ground total electric field and airborne particle thing Size, it is characterised in that the side
Method includes：
Ground total electric field data and airborne particle thing particle diameter modal data are obtained respectively, and respectively to the ground total electric field number
It is standardized according to the airborne particle thing particle diameter modal data；
Decorrelative transformation is carried out to the ground total electric field data and the airborne particle thing particle diameter modal data respectively；
Canonical correlation is carried out to the ground total electric field data by decorrelative transformation and airborne particle thing particle diameter modal data respectively
Property analysis, obtain the canonical correlation coefficient of ground total electric field data and the canonical correlation system of airborne particle thing particle diameter modal data
Number；
Canonical correlation coefficient respectively to the ground total electric field data and the typical case of the airborne particle thing particle diameter modal data
Coefficient correlation is analyzed, and judges the relevance of the ground total electric field data and airborne particle thing particle diameter modal data.
2. method according to claim 1, it is characterised in that described respectively to ground total electric field data and described
Airborne particle thing particle diameter modal data carries out decorrelative transformation to be included：
The ground total electric field data and the corresponding matrix data of the airborne particle thing particle diameter modal data are become respectively
Change or rank transformation, obtain corresponding stepped matrix；
Calculate the correlation matrix R=[r of the ground total electric field data or the particle size modal data_{ij}], and root
Strong correlation weight matrix A=[a are calculated according to the correlation matrix R_{ij}],
Wherein, τ is strong correlation coefficient threshold, is strong correlation if two coefficient correlations of variable are more than τ；
If two coefficient correlations of variable are less than τ, for weak related or uncorrelated；
The corresponding variable of the maximum weight of the often capable weight sum of strong correlation weight matrix A is proposed respectively, was obtained through the past
The ground total electric field data and airborne particle thing particle diameter modal data of relevant treatment.
3. method according to claim 1, it is characterised in that described that electricity is synthesized to the ground by decorrelative transformation respectively
Field data and airborne particle thing particle diameter modal data carry out canonical correlation analysis, obtain the canonical correlation of ground total electric field data
The canonical correlation coefficient of coefficient and airborne particle thing particle diameter modal data includes：
By by the ground total electric field data of decorrelative transformation and airborne particle thing particle diameter modal data respectively by sample set X and Y
To represent, wherein the ground total electric field data are made up of the ground total electric field of p various location, the airborne particle
Thing particle diameter modal data is made up of the particle size spectrum of q differentgrain diameter size, has N number of observation, institute for each variable
Sample set X and Y is stated to be expressed as：
Order vector α=[α_{1},α_{2},…,α_{p}]^{T}With β=[β_{1},β_{2},…,β_{q}]^{T}The typical phase of sample set X and Y linear combination is represented respectively
Relation number, then linear combinationAndMaximize relevance function：
Canonical correlation analysis is expressed as following optimization problem：
Using Lagrange multiplier methods, the Lagrange functions for obtaining are as follows：
Partial derivative is asked to α and β respectively, is madeObtain：
The covariance matrix Σ of marker samples collection X and Y_{11}=XX^{T},Σ_{22}=YY^{T}And Crosscovariance Σ_{12}=XY^{T},Σ_{21}=
YX^{T}, α and β is calculated respectively.
4. method according to claim 1, it is characterised in that described respectively to the typical case of the ground total electric field data
The canonical correlation coefficient of coefficient correlation and the airborne particle thing particle diameter modal data is analyzed, and judges the ground total electric field
The relevance of data and airborne particle thing particle diameter modal data includes：
Canonical correlation coefficient respectively to the ground total electric field data and the typical case of the airborne particle thing particle diameter modal data
Coefficient correlation takes absolute value；
The absolute value is compared with canonical correlation coefficient threshold value respectively, and the ground synthesis is judged according to comparative result
The relevance of electric field data and airborne particle thing particle diameter modal data, if the absolute value of canonical correlation coefficient is more than canonical correlation coefficient
Threshold value, then illustrate that the corresponding variable of the canonical correlation coefficient is strong with the relevance of another data；If canonical correlation coefficient is exhausted
Canonical correlation coefficient threshold value is less than to value, then illustrates the relevance of the corresponding variable of the canonical correlation coefficient and another data
It is weak.
5. the system of the relevance of a kind of analysis ground total electric field and airborne particle thing Size, it is characterised in that the system
System includes：Standardization unit, decorrelative transformation unit, canonical correlation coefficient computing unit and relevance determining unit,
The standardization unit, obtains ground total electric field data and airborne particle thing particle diameter modal data respectively, and respectively
The ground total electric field data and the airborne particle thing particle diameter modal data are standardized；
The ground total electric field data and the airborne particle thing particle diameter modal data are entered by the decorrelative transformation unit respectively
Row decorrelative transformation；
The canonical correlation coefficient computing unit, respectively to the ground total electric field data and airborne particle by decorrelative transformation
Thing particle diameter modal data carries out canonical correlation analysis, obtains the canonical correlation coefficient and airborne particle thing of ground total electric field data
The canonical correlation coefficient of particle diameter modal data；
The relevance determining unit, respectively to the canonical correlation coefficient and the airborne particle of the ground total electric field data
The canonical correlation coefficient of thing particle diameter modal data is analyzed, and judges the ground total electric field data and airborne particle thing Size
The relevance of data.
6. system according to claim 5, it is characterised in that described respectively to ground total electric field data and described
Airborne particle thing particle diameter modal data carries out decorrelative transformation to be included：
The ground total electric field data and the corresponding matrix data of the airborne particle thing particle diameter modal data are become respectively
Change or rank transformation, obtain corresponding stepped matrix；
Calculate the correlation matrix R=[r of the ground total electric field data or the particle size modal data_{ij}], and root
Strong correlation weight matrix A=[a are calculated according to the correlation matrix R_{ij}],
Wherein, τ is strong correlation coefficient threshold, is strong correlation if two coefficient correlations of variable are more than τ；If two variables
Coefficient correlation is less than τ, then for weak related or uncorrelated；
The corresponding variable of the maximum weight of the often capable weight sum of strong correlation weight matrix A is proposed respectively, was obtained through the past
The ground total electric field data and airborne particle thing particle diameter modal data of relevant treatment.
7. system according to claim 5, it is characterised in that described that electricity is synthesized to the ground by decorrelative transformation respectively
Field data and airborne particle thing particle diameter modal data carry out canonical correlation analysis, obtain the canonical correlation of ground total electric field data
The canonical correlation coefficient of coefficient and airborne particle thing particle diameter modal data includes：
By by the ground total electric field data of decorrelative transformation and airborne particle thing particle diameter modal data respectively by sample set X and Y
To represent, wherein the ground total electric field data are made up of the ground total electric field of p various location, the airborne particle
Thing particle diameter modal data is made up of the particle size spectrum of q differentgrain diameter size, has N number of observation, institute for each variable
Sample set X and Y is stated to be expressed as：
Order vector α=[α_{1},α_{2},…,α_{p}]^{T}With β=[β_{1},β_{2},…,β_{q}]^{T}The typical phase of sample set X and Y linear combination is represented respectively
Relation number, then linear combinationAndMaximize relevance function：
Canonical correlation analysis is expressed as following optimization problem：
Using Lagrange multiplier methods, the Lagrange functions for obtaining are as follows：
Partial derivative is asked to α and β respectively, is madeObtain：
The covariance matrix Σ of marker samples collection X and Y_{11}=XX^{T},Σ_{22}=YY^{T}And Crosscovariance Σ_{12}=XY^{T},Σ_{21}=
YX^{T}, α and β is calculated respectively.
8. system according to claim 5, it is characterised in that described respectively to the typical case of the ground total electric field data
The canonical correlation coefficient of coefficient correlation and the airborne particle thing particle diameter modal data is analyzed, and judges the ground total electric field
The relevance of data and airborne particle thing particle diameter modal data includes：
Canonical correlation coefficient respectively to the ground total electric field data and the typical case of the airborne particle thing particle diameter modal data
Coefficient correlation takes absolute value；
The absolute value is compared with canonical correlation coefficient threshold value respectively, and the ground synthesis is judged according to comparative result
The relevance of electric field data and airborne particle thing particle diameter modal data, if the absolute value of canonical correlation coefficient is more than canonical correlation coefficient
Threshold value, then illustrate that the corresponding variable of the canonical correlation coefficient is strong with the relevance of another data；If canonical correlation coefficient is exhausted
Canonical correlation coefficient threshold value is less than to value, then illustrates the relevance of the corresponding variable of the canonical correlation coefficient and another data
It is weak.
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US4329053A (en) *  19750226  19820511  Nasa  Frequencyscanning particle size spectrometer 
CN102967541A (en) *  20121122  20130313  中国石油大学(北京)  Device and method suitable for online detection of particulate matters in hightemperature gas pipeline 
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