CN116628407A - Data processing method and system for acquiring ion parameters of retarding potential analyzer - Google Patents
Data processing method and system for acquiring ion parameters of retarding potential analyzer Download PDFInfo
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Abstract
The invention provides a data processing method and a system for acquiring the ion parameters of a retarding potential analyzer, wherein the relationship between the ion density, the ion temperature, the ion speed and the volt-ampere characteristic curve of the retarding potential analyzer in the plasma parameters is combined, the volt-ampere characteristic curve of the retarding potential analyzer is divided into a first linear interval, a nonlinear interval and a second linear interval based on the change of curve slopes, the first linear interval is used as an ion density best fit interval, the nonlinear interval is used as an ion temperature best fit interval, a combined interval of the first linear interval and the nonlinear interval is used as an ion speed best fit interval, the calculated amount of the nonlinear least square method can be reduced to a certain extent by dividing different fit intervals, the influence of the linear fit interval on the ion temperature parameters and the ion density calculation results is avoided, and the accuracy of acquiring the plasma parameters through the volt-ampere characteristic curve of the retarding potential analyzer is improved.
Description
Technical Field
The invention belongs to the technical field related to plasma parameter diagnosis, and particularly relates to a data processing method and system for acquiring ion parameters of a retarding potential analyzer.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The retarding potential analyzer is one of important sensors in the ionosphere plasma in-situ detection engineering and is used for detecting ion density, ion temperature, ion composition and ion drift velocity in the normal direction of the sensor. The principle structure of the current retarding potential analyzer is based on a Faraday cage, the sensor of which is cylindrical, and the inside of which is a multi-layer grid structure. Ions of different energy levels in the plasma can be screened by applying electric potential to each layer of grid mesh. And collecting and recording the numerical values of the ion current electric signals of the collecting layers corresponding to different blocking voltages by utilizing the voltage control of the blocking layer grid mesh, thereby drawing the volt-ampere characteristic curve of the blocking potential analyzer. Through analysis of the volt-ampere characteristic curve, ionosphere ion parameter scientific data which are wanted by scientific researchers can be obtained through calculation.
The basic theory of analysis of the retardation analyzer curve data is based on maxwell distribution model, and the number of particles entering the sensor collection plate is controlled by screening the particle energy. The blocking grid potential is added with scanning voltage to screen ion energy, and the blocking grid is restrained from loading negative bias voltage to resist electrons. And acquiring ion current on the collecting plate to obtain a complete signal data curve. And drawing a volt-ampere characteristic curve of the retarding potential analyzer by taking the scanning voltage as a horizontal axis and the ion current value as a vertical axis.
The existing plasma parameter acquisition is realized by using a nonlinear least square method to fit and acquire the whole volt-ampere characteristic curve, however, the nonlinear least square method is very sensitive to the selection of initial parameters, and if the initial parameter values are improperly selected, the problems that a proper fitting result cannot be found, local area curve fitting is inaccurate and the like can be caused. Meanwhile, the nonlinear least square method is based on the principle that the sum of squares of errors of the whole curve is minimum, so that the curve local area fitting inaccuracy can be caused for achieving global optimum. The initial and final parts of the volt-ampere characteristic curve often have fitting curves which are not matched enough, and the nonlinear least square method has higher computational complexity compared with the linear least square method, and because an iterative algorithm is needed to optimize parameters, the nonlinear least square method is used for the whole curve, and the computational complexity is higher.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a data processing method and a system for acquiring the ion parameters of a retarding potential analyzer, wherein the volt-ampere characteristic curve of the retarding potential analyzer is divided into different sections, the best fitting section of each parameter is determined according to the relation between each ion parameter and the volt-ampere characteristic curve, the ion temperature, the ion density and the ion speed of more accurate plasmas are obtained through the best fitting section of each ion, and the influence of errors on the acquired plasma parameters caused by the fact that the fitting curve is partially inaccurate due to incorrect initial value selection of a nonlinear least square method is effectively reduced.
To achieve the above object, a first aspect of the present invention provides a data processing method for acquiring ion parameters of a retardation analyzer, including:
acquiring a scanning voltage sample point and an ion current sample point of a retarding potential analyzer, and obtaining a volt-ampere characteristic curve according to the acquired scanning voltage sample point and the acquired plasma current sample point;
determining a first linear interval, a nonlinear interval and a second linear interval on the volt-ampere characteristic curve based on a change in curve slope;
respectively fitting to obtain ion density and ion temperature based on scanning voltage in a first linear interval and a nonlinear interval and corresponding ion current sample point data;
and fitting point data based on the scanning voltages in the first linear interval and the nonlinear interval and the corresponding ion current sample points to obtain the ion velocity.
In a second aspect, the invention provides a data processing system for obtaining ion parameters of a retarding potential analyzer, comprising:
the acquisition module is used for: acquiring a scanning voltage sample point and an ion current sample point of a retarding potential analyzer, and obtaining a volt-ampere characteristic curve according to the acquired scanning voltage sample point and the acquired plasma current sample point;
the interval dividing module: determining a first linear interval, a nonlinear interval and a second linear interval on the volt-ampere characteristic curve based on a change in curve slope;
a first fitting module: respectively fitting to obtain ion density and ion temperature based on scanning voltage in a first linear interval and a nonlinear interval and corresponding ion current sample point data;
and a second fitting module: and fitting point data based on the scanning voltages in the first linear interval and the nonlinear interval and the corresponding ion current sample points to obtain the ion velocity.
A third aspect of the present invention provides a computer apparatus comprising: the system comprises a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, the processor and the memory are communicated through the bus when the computer device runs, and the machine-readable instructions are executed by the processor to execute a data processing method for acquiring ion parameters of a retarding potential analyzer.
A fourth aspect of the invention provides a computer readable storage medium having a computer program stored thereon, which when executed by a processor performs a data processing method of obtaining a retardation analyzer ion parameter.
The one or more of the above technical solutions have the following beneficial effects:
according to the invention, the relation among the ion density, the ion temperature, the ion speed and the voltammetric characteristic curve of the retarding potential analyzer is combined, the voltammetric characteristic curve of the retarding potential analyzer is divided into a first linear section, a nonlinear section and a second linear section based on the change of the curve slope, the first linear section is used as an ion density best fit section, the nonlinear section is used as an ion temperature best fit section, the combined section of the first linear section and the nonlinear section is used as an ion speed best fit section, the calculated amount of the nonlinear least square method can be reduced to a certain extent by dividing different fit sections, the problem that the fitting curve of the nonlinear least square method is not accurate enough due to the fact that the initial value is selected improperly is effectively solved, the influence of the linear fit section on ion temperature parameters and the ion density calculation result is avoided, and the accuracy of obtaining the plasma parameters through the voltammetric characteristic curve of the retarding potential analyzer is improved.
Additional aspects of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
FIG. 1 is a graph of the voltammetric characteristics of a typical retarding potential analyzer;
FIG. 2 is a plot of the volt-ampere characteristic of a non-linear least squares fit to a hysteresis potential analyzer;
FIG. 3 is a partial enlarged view of the volt-ampere characteristic curve of the retarding potential analyzer fitted by a nonlinear least square method;
FIG. 4 is a graph showing the voltage-current characteristic curve of the retarding potential analyzer according to the first embodiment;
FIG. 5 is a schematic diagram showing the interval division of the volt-ampere characteristic curve of the retarding potential analyzer according to the first embodiment;
FIG. 6 is a graph showing the relationship between the retardation analyzer curve and the ion density;
FIG. 7 is a graph showing the relationship between the voltammetric characteristic curve of a retarding potential analyzer and the ion temperature;
FIG. 8 is a graph showing the relationship between the voltammogram of a retarding potential analyzer and the ion velocity;
FIG. 9 is a graph showing the distribution of the combined intervals of the voltammetric characteristic curves of the retarding potential analyzers corresponding to the plasma parameters in the first embodiment;
FIG. 10 (a) shows that the initial Ni value is 5.3X10 12 m -3 The RPA curve based on the least square method has nonlinear fitting effect;
FIG. 10 (b) shows that the initial Ni value is 5.5X10 12 m -3 The RPA curve based on the least square method has nonlinear fitting effect;
FIG. 11 is a graph showing statistics of ion density samples according to the first embodiment;
FIG. 12 is a graph showing the first-order differential curve of the measured voltammetric characteristic curve in the first embodiment;
FIG. 13 is a graph showing the fitting effect of ion temperature sample data in the first embodiment;
FIG. 14 is a graph showing the fitting effect of ion velocity sample data in the first embodiment;
FIG. 15 is a flow chart of a plasma data processing in accordance with the first embodiment;
FIG. 16 is a schematic diagram illustrating simulation of plasma data in accordance with the first embodiment;
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention.
Embodiments of the invention and features of the embodiments may be combined with each other without conflict.
Example 1
The embodiment discloses a data processing method for acquiring ion parameters of a retarding potential analyzer, comprising the following steps:
acquiring a scanning voltage sample point and an ion current sample point of a retarding potential analyzer, and obtaining a volt-ampere characteristic curve according to the acquired scanning voltage sample point and the acquired plasma current sample point;
determining a first linear interval, a non-linear interval, and a second linear interval based on the change in slope on the volt-ampere characteristic;
respectively fitting to obtain ion density and ion temperature based on scanning voltage in a first linear interval and a nonlinear interval and corresponding ion current sample point data;
and fitting point data based on the scanning voltages in the first linear interval and the nonlinear interval and the corresponding ion current sample points to obtain the ion velocity.
Fig. 1 is a typical voltammetric characteristic curve, in which the ionospheric plasma is considered to conform to maxwell distribution, and equation (1) is satisfied with respect to the satellite in the sensor axis direction:
as calculated, when the scan bias value is U, the current contribution of the ith ion to the data curve is formula (2):
wherein K is total pass rate, A is window area, e is unit charge, N i Ion density of the ith ion, V r V is the velocity of the plasma relative to the satellite along the sensor axis as a whole r ＝V s +V dZ Wherein V is s For satellite movement speed, V dZ For the drift velocity of the plasma along the satellite orbit, the absolute potential of satellite ground relative to space plasma is U is the scanning bias value, m i For the mass of the i-th ion, erf is the error function, f i ＝V r -v g ，/>T i Is the temperature of the i-th ion.
And performing nonlinear least square fitting on the equation and the actually measured volt-ampere characteristic curve to obtain parameter data such as ion density, ion temperature, ion drift speed and the like.
Fig. 2 shows a volt-ampere characteristic curve and an actual measurement curve after nonlinear least square fitting, and it can be seen that there is often a problem that fitting curves are not fit enough at the beginning and ending parts, but for the obtained plasma parameters, ion density is only determined by the maximum amplitude of the curve, ion temperature is only determined by the broadening of the transition region, ion speed is not only influenced by the maximum amplitude of ion current, but also influenced by the slope change condition of the transition region of the volt-ampere characteristic curve. Aiming at the problems, in the embodiment, the characteristics of the curve and the relation between the characteristics of the ion parameters and the measured volt-ampere characteristic curve are combined to carry out interval division, the best fit interval of each ion parameter is determined, different plasma parameters are obtained in a fitting mode in the best fit interval, the mutual interference of the different intervals on the plasma parameters to be fitted is reduced, and the accuracy of obtaining the plasma parameter values in a fitting mode is improved. The calculation amount of the whole fitting is reduced due to the reduction of different fitting intervals and the change of fitting modes.
As shown in fig. 3, the conventional method for fitting the volt-ampere characteristic curve of the whole retarding potential analyzer by using a nonlinear least square method often has the problem that the measured curve and the fitted curve in the initial stable stage and the final stable stage of the fitted curve cannot be completely matched, and the fitting degree is better for the middle transition region.
The ion density parameter is mainly determined by the amplitude of the initial stable stage, and if the initial amplitude fails to fit the precision criterion, the ion density parameter with larger error can be obtained, so that unnecessary problems are brought to the study of the plasma fine structure.
As shown in fig. 4, from the curve of a typical retardation analyzer, the voltammetric characteristic curve is in a gentle state at first, in the maximum amplitude distribution area of the whole curve, along with the gradual rise of the scanning voltage, the ion current value of the curve gradually drops, and in a transition area, the curve in the transition area has multiple curves with different bending degrees at each point, and at this time, the voltammetric characteristic curve shows a nonlinear characteristic, and finally tends to be gentle to reach a linear section. The volt-ampere characteristic curve of the retarding potential analyzer is roughly divided into a linear section from head to tail and a nonlinear section of the middle transition section according to the curve characteristics.
As shown in fig. 5, in the present embodiment, the first linear section, the nonlinear section, and the second linear section are determined in the direction in which the scanning voltage is continuously increasing based on the change in the slope on the volt-ampere characteristic curve.
N i I.e. ion density, which determines the position of the maximum amplitude of the measured voltammetric characteristic curve, i.e. the start of the curve, which corresponds to the ion current magnitude at a lower blocking potential of the blocking grid. When the potential on the retarding grid is lower, ions at each energy level in the ionized layer plasma can freely pass through the retarding grid and reach the collecting electrode plate of the sensor to form current, so that the amplitude of the curve is the maximum stage of the whole retarding potential analyzer, and meanwhile, the quantity of the ions at each energy level in the plasma corresponds to the value of the ion density in the measured ionized layer to a certain extent.
Because the ion density is only determined by the maximum amplitude value in the initial gentle region, the initial linear gentle region is used as the ion density fitting region, so that the phenomenon of partial fitting inaccuracy of a curve caused by improper initial parameter selection of a nonlinear least square method can be effectively avoided, and the accuracy of acquiring the ion density parameters is improved. The relationship of the ideal retardation analyzer volt-ampere characteristic curve under typical Low Earth Orbit (LEO) conditions to the plasma density is shown in fig. 6.
When the whole curve is fitted by the conventional nonlinear least square method, as shown in fig. 10 (a) -10 (b), initial values of the fitting ion density Ni are set to 5.3×10, respectively 12 m -3 And 5.5X10 12 m -3 The fitting result at the time can be seen that the fitting result of the least square method also has obvious areas when the initial value is changed by only 3 percentIn addition, slight deviations from the initial values may result in sub-optimal fitting of the data curves. Therefore, the characteristic that the ion density parameter is only determined by the maximum amplitude is combined, and the specific calibration is carried out on the demarcation point of the first linear interval and the nonlinear interval at present.
The determination of the first linear interval and the nonlinear interval demarcation point is: firstly, a first-order differential curve of an actually measured blocking volt-ampere characteristic curve is drawn, a slope change value in unit time on the actually measured volt-ampere characteristic curve is determined, two points with large slope change values exist on the actually measured volt-ampere characteristic curve based on the property of a plasma parameter volt-ampere characteristic curve, the absolute value of the slope of the volt-ampere characteristic curve in a sample area corresponding to the point from an initial sample to the point with the large slope change value is smaller than a final point (namely, the point closest to the first slope change value) of the calibration value, and the boundary point of a first linear interval and a nonlinear interval is formed on the actually measured volt-ampere characteristic curve along with the increasing direction of a scanning voltage. If no demarcation point meeting the condition is found in the sample area corresponding to the maximum value of the first slope change from the initial sample on the actually measured volt-ampere characteristic curve, taking the corresponding sample point at the half width of the abscissa in the sample area as the demarcation point of the first linear interval and the nonlinear interval. As shown in fig. 11, the average value and standard deviation of the ion current are calculated by counting sample data in the first linear interval, at this time, the average value of the ion current is substituted into the formula (1) and the formula (2) as the maximum amplitude value for determining the ion density to calculate the ion density, and the statistical method can process a relatively gentle region and is also applicable to all data distribution in the linear interval, wherein when the first linear interval is counted, the sample data is preprocessed, the sample data of the ion current with the difference between the absolute value of the ion current sample data and the calculated ion current standard deviation being greater than 1 is regarded as dead spots, and the dead spots are shielded and recalculated. Thereby improving the accuracy of the parameter of ion density.
In the present embodiment, the calibration value is set to 0.1.
T i The ion temperature, a physical quantity describing the average kinetic energy of the ions, determines the retarding potential fractionSlope of the analyzer volt-ampere characteristic curve and transition region conditions. According to maxwell distribution model of ion motion, ion temperature and ion average kinetic energy are positively correlated, as ion temperature increases, ion energy broadening increases, the width of transition region of retardation analyzer increases, the slope of error function erf is smoother, thus volt-ampere characteristic curve also becomes smoother, and its morphology is shown in fig. 7. The ion temperature is mainly determined by the stretching of a nonlinear transition region of a retarding potential analyzer, the nonlinear transition region is used as a fitting region when the ion temperature is acquired, the influence of a first linear region on the ion temperature is avoided, the ion temperature parameter can be accurately fitted by using a nonlinear least square method, and in order to reduce the calculated amount of the nonlinear least square method, a gentle region subtracting the first linear region and the second linear region of the whole curve can be used as sample data points.
For the ion temperature and the normal speed along the sensor, both are influenced by a nonlinear interval, a first-order differential curve is obtained by deriving the data of the whole retarding potential analyzer, a slope change value in unit time on the actually measured volt-ampere characteristic curve is determined, according to the property of the plasma parameter volt-ampere characteristic curve, two points with large slope change values exist, the direction of increasing the scanning voltage along with the volt-ampere characteristic curve is changed along with the scanning voltage, and in a sample area behind a point with large second slope change value, the point with the absolute value of the slope of the volt-ampere characteristic curve smaller than the calibration value for the first time is the boundary point of the nonlinear interval and the second linear interval. If the sample demarcation point meeting the condition is not found in the region from the point with the large second slope change value to the end point (i.e. the last sample point according to the increasing direction of the scanning voltage), the sample point corresponding to the half width of the region is taken as the demarcation point of the nonlinear section and the second linear section.
As shown in fig. 12, the nonlinear interval is the middle area corresponding to two black sample data points on the first-order differential curve.
The ion temperature is determined by the broadening length of the nonlinear fitting region of the retarding potential analyzer, so that the most important factor affecting the ion temperature is all sample data points in the nonlinear interval. The sample points in the divided nonlinear interval are utilized to obtain the ion temperature parameters in a fitting way, so that interference caused by sample point data in the linear interval can be avoided, and more accurate ion temperature parameters can be obtained in a fitting way.
FIG. 13 shows the effect of non-linear least squares fitting of ion temperature parameters, where the non-linear least squares fitting of the entire data sample points was performed before, and where it can be seen that there is substantially no local curve fitting inaccuracy in the curve, avoiding data perturbation in the first linear fitting region, and reducing the amount of computation. In regression analysis, the determination coefficient R2 is an index for evaluating the fitting goodness of the regression model, and represents the proportion of the variance of the response variable which can be interpreted by the regression model to the variance of the total response variable, wherein the value range is 0 to 1, and in practical application, the closer the value of R2 is to 1, the better the fitting effect of the regression model to the practical observed value is, and the stronger the interpretation capability of the interpretation variable to the response variable is. Otherwise, if R2 is close to 0, the fitting effect of the regression model on the actual observed value is poor, and the interpretation capability of the interpretation variable on the response variable is weak. The judgment coefficient R2 is used as an evaluation standard for the quality of the effect of the block potential analysis voltammetry curve fitting. The effect R2 after nonlinear fitting by the least square method reaches 0.99968, the fitting curve is very close to the actually measured curve, and the accuracy of acquiring the ion temperature parameter is improved.
The ion velocity Vr also has an effect on the retarding potential analyzer collection curve, the effect of which is shown in fig. 8. As the ion velocity increases, resulting in an increase in measured ion current, a higher blocking potential needs to be applied to prevent ion penetration, and the center of the transition region and the deepest position of the error function portion will also move toward the region of higher blocking voltage. The ion velocity is affected not only by the gentle phase of the ion current, i.e. the maximum amplitude of the first linear interval, but also by the position of the transition region of the voltammetric characteristic curve, i.e. the nonlinear interval. To reduce the amount of computation, sample points of the second linear interval are deleted, and the ion velocity parameter is fitted in combination with sample data in the first linear interval and the nonlinear interval.
As shown in fig. 14, the acquisition of the velocity parameter along the sensor direction is determined by the maximum amplitude of the start and the sample data corresponding to the curve in the transition region and the slope change at the curve being relatively obvious, so that the sample point data of the first linear region and the nonlinear region of the whole curve can be combined as the data source for acquiring the ion velocity parameter. The effect R2 after nonlinear least square fitting reaches 0.92854, and the fitting effect is good. The sample point data interference of the second linear interval is avoided, and the calculated amount of the nonlinear least square method is reduced.
Aiming at the problems that the nonlinear least square method does not select proper initial parameters to be trapped in the local fitting inaccuracy and the complexity is high, in the embodiment, the curve of the traditional retarding potential analyzer is roughly divided into a first linear section, a nonlinear fitting area and a second linear section through data feature analysis of the volt-ampere characteristic curve of the retarding potential analyzer. Meanwhile, the parameter sample data interval distribution which influences ion density, ion temperature, ion drift speed and the like is considered, and a combination interval analysis method is adopted for fitting to obtain plasma parameters. From the above analysis, it is known that the ion density corresponds to the first linear section of the voltammetric characteristic curve, the ion temperature corresponds to the nonlinear section of the voltammetric characteristic curve, and the ion velocity is influenced by both the first linear section and the nonlinear section of the voltammetric characteristic curve. As shown in fig. 9, each ion parameter corresponds to a different combination interval.
As shown in fig. 15, the first-order derivative curve is obtained by first-order derivation of the measured voltammetric characteristic curve of the retarding potential analyzer, and the demarcation points of the linear fitting interval and the nonlinear interval are calibrated according to the slopes on the first-order derivative by combining the relationship between the three plasma parameters of ion density, ion temperature and ion speed and the voltammetric characteristic curve of the retarding potential analyzer. Thereby dividing the first linear interval, the nonlinear interval and the second linear interval on the blocking voltammetry curve. The ion density is obtained by fitting sample point data of a first linear section, the ion temperature is obtained by fitting sample data points corresponding to a nonlinear section, and the ion velocity is mainly obtained by fitting the first linear section and the nonlinear section. And the sample data fitting in different modes is carried out by utilizing the divided fitting intervals, so that the accuracy of acquiring different plasma parameters is improved.
As shown in fig. 16, in the upper left corner area of the interface, the data reading button is used as a setting area of an input parameter, the executable functions include reading an original volt-ampere characteristic curve, readable csv, excel, txt and other original data in various formats, the input parameter includes a window area S of a sensor, a total transmittance K of a grid, an ion mass mi, wherein the static parameter includes a vacuum dielectric constant e, an electronic mass me, a boltzmann constant kb, a default parameter setting button is used for returning the input parameter to an initial default parameter setting, a calculating button is used for calculating the input parameter by substituting the default parameter into a calculating formula, in the lower left corner area of the user interface, the output parameter includes an ion density Ni, an ion temperature Ti and an ion speed, a data one-key zero clearing button is also included, the executed functions include a plasma data parameter saving button is used for saving the input and output parameters, and the executed functions are stored in a text mode as an ion density, an ion temperature and an ion speed obtained by a retarding analyzer curve.
The other side area is a graph display area, and the graph display button Plot Show is used for executing the function of displaying corresponding curves in the four graph areas. From left to right, four graphs from top to bottom are sequentially 1, original volt-ampere characteristic graphs; 2. fitting curve and actually measured curve of ion density corresponding to the first linear interval; 3. fitting curve and measured curve of nonlinear interval corresponding to ion temperature; 4. fitting curves and measured curves of a first linear interval and a nonlinear interval corresponding to the ion velocity.
The detection of ionosphere small-scale non-uniformities has important significance for communication, navigation, power transmission and aerospace, the retarding potential analyzer is one of important means for plasma detection, the measured volt-ampere characteristic curve is divided by combining the relation between the volt-ampere characteristic curve of the retarding potential analyzer and each ion parameter, the problem that the fitting of the ion parameters is inaccurate due to the fact that initial parameters are selected improperly by a nonlinear square method is solved, the use of a combination interval reduces the calculated amount of fitting of the nonlinear square method to the whole curve to a certain extent. The method realizes the scientific treatment of the voltammogram of the retarding potential analyzer, improves the accuracy of acquiring plasma parameters, and is favorable for better diagnosing the near-earth orbit non-uniform ionosphere structure.
Example two
It is an object of the present embodiment to provide a computing device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, which processor implements the steps of the method described above when executing the program.
Example III
An object of the present embodiment is to provide a computer-readable storage medium.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the above method.
Example IV
It is an object of this embodiment to provide a data processing system for acquiring ion parameters of a retarding potential analyzer, comprising:
the acquisition module is used for: acquiring a scanning voltage sample point and an ion current sample point of a retarding potential analyzer, and obtaining a volt-ampere characteristic curve according to the acquired scanning voltage sample point and the acquired plasma current sample point;
the interval dividing module: determining a first linear interval, a non-linear interval, and a second linear interval based on the change in slope on the volt-ampere characteristic;
a first fitting module: respectively fitting to obtain ion density and ion temperature based on scanning voltage in a first linear interval and a nonlinear interval and corresponding ion current sample point data;
and a second fitting module: and fitting point data based on the scanning voltages in the first linear interval and the nonlinear interval and the corresponding ion current sample points to obtain the ion velocity.
The steps involved in the devices of the second, third and fourth embodiments correspond to those of the first embodiment of the method, and the detailed description of the embodiments can be found in the related description section of the first embodiment. The term "computer-readable storage medium" should be taken to include a single medium or multiple media including one or more sets of instructions; it should also be understood to include any medium capable of storing, encoding or carrying a set of instructions for execution by a processor and that cause the processor to perform any one of the methods of the present invention.
It will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented by general-purpose computer means, alternatively they may be implemented by program code executable by computing means, whereby they may be stored in storage means for execution by computing means, or they may be made into individual integrated circuit modules separately, or a plurality of modules or steps in them may be made into a single integrated circuit module. The present invention is not limited to any specific combination of hardware and software.
While the foregoing description of the embodiments of the present invention has been presented in conjunction with the drawings, it should be understood that it is not intended to limit the scope of the invention, but rather, it is intended to cover all modifications or variations within the scope of the invention as defined by the claims of the present invention.
Claims (10)
1. A data processing method for obtaining ion parameters of a retarding potential analyzer, comprising:
acquiring a scanning voltage sample point and an ion current sample point of a retarding potential analyzer, and obtaining a volt-ampere characteristic curve according to the acquired scanning voltage sample point and the acquired plasma current sample point;
determining a first linear interval, a nonlinear interval and a second linear interval on the volt-ampere characteristic curve based on a change in curve slope;
respectively fitting to obtain ion density and ion temperature based on scanning voltage in a first linear interval and a nonlinear interval and corresponding ion current sample point data;
and fitting point data based on the scanning voltages in the first linear interval and the nonlinear interval and the corresponding ion current sample points to obtain the ion velocity.
2. The data processing method for obtaining ion parameters of a retarding potential analyzer according to claim 1, wherein a last point on the voltammetric characteristic curve, where the absolute value of the slope of the voltammetric characteristic curve is smaller than the calibration value in a sample area corresponding to a point from the initial sample to the first slope change value, is used as a demarcation point between the first linear section and the nonlinear section.
3. A data processing method for obtaining ion parameters of a retarding potential analyzer as set forth in claim 2, wherein an average value of ion current is obtained from ion current sample data points in a first linear interval, and ion density is obtained from the average value of ion current as maxwell distribution of ions.
4. The data processing method for obtaining ion parameters of a retarding potential analyzer according to claim 1, wherein a point on the voltammetric characteristic curve having an absolute value of a slope smaller than a calibration value for the first time is used as a boundary point between the nonlinear section and the second linear section in a sample region after a point having a large second slope change value on the voltammetric characteristic curve.
5. The data processing method for obtaining the ion parameters of the retarding potential analyzer according to claim 1, wherein the fitting is performed by a nonlinear least square method based on the scanning voltage in the nonlinear interval and the corresponding ion current sample point data, and the ion temperature is obtained according to the fitted curve.
6. The data processing method for obtaining the ion parameters of the retarding potential analyzer as set forth in claim 1, wherein the fitting is performed by a nonlinear least square method according to the scanning voltage in the first linear interval and the nonlinear interval and the corresponding ion current sample point data, and the ion speed is obtained according to the fitted curve.
7. A data processing method for obtaining ion parameters of a retarding potential analyzer as set forth in claim 1, further comprising: and calculating the standard deviation of the ion current sample data in the first linear interval, and eliminating the sample data with the ion current sample data in the first linear interval larger than the standard deviation.
8. A data processing system for acquiring ion parameters of a retarding potential analyzer, comprising:
the acquisition module is used for: acquiring a scanning voltage sample point and an ion current sample point of a retarding potential analyzer, and obtaining a volt-ampere characteristic curve according to the acquired scanning voltage sample point and the acquired plasma current sample point;
the interval dividing module: determining a first linear interval, a nonlinear interval and a second linear interval on the volt-ampere characteristic curve based on a change in curve slope;
a first fitting module: respectively fitting to obtain ion density and ion temperature based on scanning voltage in a first linear interval and a nonlinear interval and corresponding ion current sample point data;
and a second fitting module: and fitting point data based on the scanning voltages in the first linear interval and the nonlinear interval and the corresponding ion current sample points to obtain the ion velocity.
9. A computer device, comprising: a processor, a memory and a bus, said memory storing machine readable instructions executable by said processor, said processor and said memory communicating via the bus when the computer device is running, said machine readable instructions when executed by said processor performing a data processing method of acquiring a retardation analyzer ion parameter as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, which when executed by a processor performs a data processing method of acquiring ion parameters of a retarding potential analyzer as claimed in any of claims 1 to 7.
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| CN117318730B (en) * | 2023-11-30 | 2024-02-23 | 山东大学 | Ionosphere data real-time acquisition and compression method, device, chip and system |
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