CN108169213A - A kind of laser induced breakdown spectroscopy spectral peak element automatic identifying method - Google Patents
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Abstract
The present invention provides a kind of laser induced breakdown spectroscopy spectral peak element automatic identifying method, includes the following steps：Laser induced breakdown spectroscopy to be identified is acquired, and the correction of continuous background is carried out to spectrum；Spectral peak fitting and decomposition are carried out using the spectrum after Voigt function pair background corrections, builds the characteristic parameter vector of spectral peak signal to be identified；Establishing criteria database, obtains the spectral information of all elements under wave band identical with spectrum to be identified, and builds the characteristic parameter vector of element；The feature vector of the element spectral peak in the characteristic parameter vector of each spectral peak signal to be identified and standard database is subjected to similarity analysis respectively；According to similarity size, element corresponding with the spectral peak of similarity maximum in standard database is judged as to the element belonging to the spectral peak to be identified.The present invention can fast and accurately be suitable for simple and complex spectrum spectral peak identification.
Description
Technical field
It is a kind of induced with laser specifically the present invention relates to spectral technique fields such as sample composition and content analysis
Breakdown spectral spectral peak element automatic identifying method.
Background technology
Laser induced breakdown spectroscopy (LIBS) is a kind of spectral analysis technique, to sample composition and content analysis neck
Domain has a wide range of applications.LIBS technologies are to generate plasma using laser irradiation testee surface to obtain material composition
(qualitative analysis) and the analytical technology of concentration (quantitative analysis).
LIBS has the characteristics that real-time, quick, lossless or Non-destructive test compared to traditional spectroscopic analysis methods.
What LIBS technologies were analyzed is the emission spectrum of atom or ion, and laser induced breakdown spectroscopy usually contains a large amount of member
Plain feature spectral peak is to carry out Element detection and the premise and basis of analysis for accurately identifying for these spectral peaks.For complexity
Spectrum accurately identifies that effective spectral peak in spectrum can provide a kind of effective means for qualitative and quantitative analysis.
At present, the recognition methods of LIBS spectral peaks can substantially be summarized as three classes.The first kind is referred to as wavelength arest neighbors rule,
Basic thought is to be compared the launch wavelength of element in the wavelength information of spectral peak in experimental spectrum and standard database, with reality
The standard database element that optometry spectrum spectral peak wavelength is closer to can be judged as the corresponding element of the wavelength.Second class is simulation
Spectrum comparison method, the main thought of this method are that the fitting spectral peak of coherent element is obtained by NIST standard databases, and with reality
The spectroscopic data tested carries out paired observation to identify spectral peak element at spectral peak.Third class is correlation analysis method, the party
Method establishes the simulation spectral peak of each element using standard database, and related to the progress of actual spectrum data in a wavelength range
Property analysis, and according to correlation size determine experimental spectrum spectral peak element ownership.
Nearest neighbor method due to the influence of the factors such as material property, experimental facilities, in experimental spectrum the wavelength of spectral peak compared to
Standard database all can there are a degree of spectral peaks to deviate, the accuracy for leading to this kind of method identification is poor.Simulated spectra ratio
The spectrum obtained by database simulation this compared with method still will depend on human eye with the method that experimental spectrum compares and analyzes
Judgement, it is not only time-consuming and laborious, but also for more complicated spectrum, the reliability of identification is still difficult to ensure that.Correlation point
It is that the spectral intensity near spectral peak is simply used not consider the waveform knot of spectroscopic data in itself as feature vector to analyse fado
Structure does not consider physical link intrinsic between waveform configuration and sample parameter to be measured yet, and the related coefficient frequently resulted in is smaller (very
To being negatively correlated), so as to cause element None- identified.
Therefore, complex in material composition, there are under more overlap peak disturbed condition, realize spectral peak member between spectral peak
Element accurately identifies an always problem urgently to be resolved hurrily.Herein on the basis of existing research work, it is proposed that a kind of
The new method of laser induced breakdown spectroscopy spectral peak element automatic identification.This method is intended first with Voigt function pair spectrum
It closes, is interfered with reducing peak overlap and ambient noise；On this basis, structure include spectral peak centre wavelength, center spectral intensity,
Spectral peak characteristic parameter vector including halfwidth, spectral peak barycenter, and according to the automatic identification of similarity analysis realization spectral peak element.
Invention content
It is an object of the present invention to overcome the shortcomings of the prior art and provide a kind of laser induced breakdown spectroscopy spectral peaks
Element automatic identifying method, this method are fitted first with Voigt function pair spectrum, are made an uproar with reducing peak overlap and background
Acoustic jamming；On this basis, spectral peak of the structure including spectral peak centre wavelength, center spectral intensity, halfwidth, spectral peak barycenter
Characteristic parameter vector, and according to the automatic identification of similarity analysis realization spectral peak element.The technical solution adopted by the present invention is：
A kind of laser induced breakdown spectroscopy spectral peak element automatic identifying method, includes the following steps：
Step (a) acquires laser induced breakdown spectroscopy to be identified, and the correction of continuous background is carried out to spectrum；
Step (b) carries out spectral peak fitting and decomposition using the spectrum after Voigt function pair background corrections, and structure is to be identified
The characteristic parameter vector of spectral peak signal；
Step (c), establishing criteria database, the spectrum for obtaining all elements under wave band identical with spectrum to be identified are believed
Breath, and build the characteristic parameter vector of element；
Step (d), respectively by the element in the characteristic parameter vector of each spectral peak signal to be identified and standard database
The feature vector of spectral peak carries out similarity analysis；
Similarity calculation is defined as follows：
Wherein ci,tRepresent i-th spectral peak signal to be identified with t-th in standard database may element spectral peak signal it
Between similarity；FiRepresent the characteristic parameter vector of i-th of spectral peak signal to be identified, FtRepresent t-th of possibility in standard database
The characteristic parameter vector of the spectral peak signal of element；
According to similarity size, element corresponding with the spectral peak of similarity maximum in standard database is judged for step (e)
For the element belonging to the spectral peak to be identified.
In step (b), Voigt functions are defined as follows：
Wherein I (λ) represents the spectral intensity of af at wavelength lambda；λcCentre wavelength, I for spectral peak signalc, w represent center respectively
The halfwidth of spectral intensity and spectral peak under wavelength correspondence；θ be Gauss-Lorentz coefficient, constant of the value between (0,1)；
The spectral peak barycenter A obtained after spectrum to be identified is carried out Voigt Function Fittings is as the replacement of waveform feature parameter θ
Characteristic parameter；Therefore for a spectral peak to be identified, its characteristic parameter vector F=[I are obtainedc,λc,w,A]；
The calculating of barycenter is defined as follows：
Wherein A represents the barycenter of spectral peak of the wavelength at λ, and I (λ) represents the spectral intensity of af at wavelength lambda, [λL,λR] it is the spectrum
Section where peak.
When there are during peak overlap phenomenon, in order to obtain more accurate spectral peak characteristic parameter, Voigt functions are under at this time
Formula replaces：
Wherein l be overlapping spectrum peak number, λt、It、wtAnd θtCentre wavelength, the centre wavelength of respectively t-th spectral peak correspond to
Under spectral intensity, the halfwidth of spectral peak and Gauss-Lorentz coefficient.
The advantage of the invention is that：
1) laser induced breakdown spectroscopy spectral peak element automatic identifying method provided by the invention, is held by computer program
Row, does not need to artificially participate in, and computer can automatically realize entire spectral region the identification of effective spectral peak.
2) present invention can fast and accurately be suitable for simple and complex spectrum spectral peak and identify, be a kind of to spectrum analysis
Effective means.
3) present invention considers multiple characteristic informations of spectral peak, can effectively improve the accuracy of spectral peak identification.
4) present invention not only realizes the spectral peak identification of laser induced breakdown spectroscopy, also to the background and overlap peak in spectrum
It is corrected, so as to extract the useful information in spectrum.
Description of the drawings
Fig. 1 is the realization flow chart of steps of the present invention.
The overlap peak that Fig. 2 is the present invention judges schematic diagram.
Fig. 3 is the decomposed and reconstituted result schematic diagram that one embodiment of the present of invention is standard analog spectrum.
Fig. 4 is the spectral peak recognition result schematic diagram that one embodiment of the present of invention is simulated spectra.
Fig. 5 is the decomposed and reconstituted result schematic diagram that one embodiment of the present of invention is tealeaves spectrum.
Fig. 6 is the spectral peak recognition result schematic diagram that one embodiment of the present of invention is tealeaves spectrum.
Specific embodiment
With reference to specific drawings and examples, the invention will be further described.
The present invention proposes a kind of laser induced breakdown spectroscopy spectral peak element automatic identifying method, before spectral peak identification, meeting
The correction of continuous background and the decomposition of overlapping spectrum peak, these background spectrums and overlapping spectrum peak are carried out to original spectrum to be identified
Therefore extraction of the meeting severe jamming to spectral information to be identified can also influence the accuracy of spectral peak identification.This method includes following
Specific steps：
Step (a) acquires laser induced breakdown spectroscopy to be identified, and the correction of continuous background is carried out to spectrum；
Step (b) carries out spectral peak fitting and decomposition using the spectrum after Voigt function pair background corrections, and structure is to be identified
The characteristic parameter vector of spectral peak signal；Voigt functions are defined as follows：
Wherein I (λ) represents the spectral intensity of af at wavelength lambda；λcCentre wavelength, I for spectral peak signalc, w represent center respectively
The halfwidth of spectral intensity and spectral peak under wavelength correspondence；θ be Gauss-Lorentz coefficient, constant of the value between (0,1)；
Above formula (1) shows：The induced with laser spectrum spectral peak measured using Voigt function pairs, which is fitted, can obtain λc、Ic, w and θ totally 4
A waveform feature parameter；Utilize λc、Ic, w and θ can build the characteristic parameter vector of spectral peak signal to be identified；
In construction feature parameter vector, λc、Ic, w be reflect spectral peak wave character three important parameters, can pass through
NIST (National Institute of Standards and Technology) standard database is consulted to obtain；Without providing each member in NIST standard databases
The value of plain θ, it is contemplated that the value of waveform feature parameter θ mainly influences the distribution size of each light intensity near spectral peak, therefore will wait to know
Alternative features parameters of the spectral peak barycenter A that other spectrum obtained after Voigt Function Fittings as waveform feature parameter θ；Therefore
For a spectral peak to be identified, its characteristic parameter vector F=[I can be obtainedc,λc,w,A]；
The calculating of barycenter is defined as follows：
λ∈[λL,λR]
Wherein A represents the barycenter of spectral peak of the wavelength at λ, and I (λ) represents the spectral intensity of af at wavelength lambda, [λL,λR] it is the spectrum
Section where peak；
It is non-overlapping in each spectral peak when carrying out spectral peak fitting using Voigt function pairs spectrum to be identified and decompose, profit
The characteristic parameter of spectral peak can be obtained well with Voigt functions；But since in actually measuring, peak overlap is one general
All over phenomenon, in order to obtain more accurate spectral peak characteristic parameter, Voigt functions can be replaced by following formula at this time：
Wherein l be overlapping spectrum peak number, λt、It、wtAnd θtCentre wavelength, the centre wavelength of respectively t-th spectral peak correspond to
Under spectral intensity, the halfwidth of spectral peak and Gauss-Lorentz coefficient；
Spectral peak signal characteristic parameter vector to be identified is built to be implemented as follows：
Using consecutive points Maximum Approach in spectrum range [λ to be identifiedmin,λmax] scan for, obtain spectrum extreme value informationN is extreme point number,Wavelength location and spectral peak at respectively j-th of extreme point is strong
Degree；
The extreme point of acquisitionIn spectral peak information corresponding to existing real elements, also have noise and the intensity relatively low
Faint spectral peak (these spectral peaks usually not identify in practice)；
Remove the spectral peak of noise and the relatively low faint spectral peak of intensity, that is, invalid；The background intensity values pair of original signal can be introduced
Extreme pointCarry out judgement screening；IfFor spectral positionCorresponding background light intensity value, ifThen
Extreme pointJudgement is identified as effective spectral peak to be identified, is otherwise given up；ThIt, can be according to specific to select threshold value
Identification needs to select；
After removing noise and invalid spectral peak, all retained extreme points (spectral peak to be identified) are denoted asM is spectral peak number to be identified,It is the wave of i-th of spectral peak to be identified
Long and spectral strength；
Judge spectral peak to be identifiedWhether it is overlapping spectrum peak；IfIt is spectral peak section respectively
WithLight intensity minimum position and its intensity (shown in Figure 2)；If its slopeIt is small
In given threshold value Tk, then can determine whether spectral peak to be identifiedFor non-overlapping spectral peak, and remember that spectral peak section to be fitted isIf K >=Tk, then can determine whether spectral peak to be identifiedWithFor overlapping spectrum peak, for overlapping spectrum peak,Find light intensity minimum position and its intensity in spectral peak sectionCalculate slope
If K >=Tk, this process is repeated, until slope is less than given threshold value Tk, recording spectral peak section to be fitted is
L is treats fit interval spectral peak number；
In spectral peak section to be fittedThe curve of spectrum is fitted using formula (2), obtains It, wt,
λt, θt(t=1,2 ..., l) characteristic parameter, t=1,2 here ..., l represents i-th, i+1 respectively ..., i+l spectral peaks to be identified；
Above step is repeated, for i-th of spectral peak to be identifiedJoined using the feature that Voigt function decompositions obtain
Number builds its characteristic parameter vector Fi=[Ii,λi,wi,Ai]；
Step (c) according to NIST standard databases, obtains the spectrum of all elements under wave band identical with spectrum to be identified
Information, and build the characteristic parameter vector of element；
NIST standard databases are being utilized, when building the characteristic parameter vector of element, due to plasma electron density Ne
Unknown with electron temperature T, this is to the I in characteristic parameter vectorc, w calculating bring difficulty；It is combined herein using grid search
Similarity analysis method calculates the I in characteristic parameter vectorc、w；It is as follows：
Set the value range of plasma electron density Ne and electron temperature T as：Log (Ne)=[15,20], T=
[0.5,2](eV)；By log (Ne) according to step-length 1, T is divided according to step-length 0.25 in given range, be obtained 42 grades from
The combination of daughter electron density Ne and electron temperature T；Obtain：
uj=(log (Ne), T) ∈ (15,0.5), (15,0.75) ..., (15,2), (16,0.5) ..., (20,2) }, j
=1 ..., 42
For an any given uj=(log (Ne), T) is combined, the wavelength information λ according to spectral peak to be identifiedi, obtain
[λ in NIST standard databasesi-Δλ,λi+ Δ λ] in the range of all possible S element, calculate and obtain spectral peak feature ginseng
Number vectorWherein Δ λ may relative to standard spectrum for experimental spectrum
Wavelength shift, select Δ λ=0.2 herein；
Step (d), respectively by the element in the characteristic parameter vector of each spectral peak signal to be identified and standard database
The feature vector of spectral peak carries out similarity analysis；
Similarity calculation is defined as follows：
Wherein ci,tRepresent i-th spectral peak signal to be identified with t-th in standard database may element spectral peak signal it
Between similarity；FiRepresent the characteristic parameter vector of i-th of spectral peak signal to be identified, FtRepresent t-th of possibility in standard database
The characteristic parameter vector of the spectral peak signal of element；
It is implemented as follows：
Using i-th of spectral peak signal characteristic vector F to be identified of Cosin similarity calculationsi=[Ii,λi,wi,Ai] marked with NIST
Elemental characteristic parameter vector in quasi- databaseSimilarity；Expression formula
It is as follows：
WhereinIt represents in plasma density and electron temperature combination ujUnder the conditions of, i-th of spectral peak signal to be identified is special
Levy parameter vector FiIt may element with t-th in NIST standard databasesCosin similarities；
According to similarity size, element corresponding with the spectral peak of similarity maximum in standard database is judged for step (e)
For the element belonging to the spectral peak to be identified.
It is implemented as follows：
It, will be with spectral peak signal characteristic vector F to be identified according to similarity sizeiWith maximum similarityNIST standards
Corresponding element of the database element as spectral peak to be identified, is denoted asIts similarity is denoted asStep (c), (d) are repeated, is obtained
Obtain ujUnder the conditions of=(log (Ne), T), the elemental recognition result and its similarity of all spectral peaks to be identified
And obtain its average similarity
Above step (c), (d), (e) are repeated, obtains all ujAverage similarity under the conditions of=(log (Ne), T), choosing
Take the u corresponding to maximum average similarityjFor optimal plasma body electron density and electron temperature；Elemental recognition under the conditions of this
As a result it is final result.
In one embodiment, it realizes the spectral peak identification to simulated spectra and tealeaves spectrum, passes through induced with laser of the present invention
Breakdown spectral spectral peak element automatic identifying method preferably can carry out spectral peak identification to spectrum；Pass through background correction and overlap peak
Effective spectral peak information in spectrum to be identified can be extracted after decomposition, eliminates the dry of noise and the relatively low faint spectral peak of intensity
It disturbs, realizes the identification to effective spectral peak.
It is the design sketch identified in this example to the spectral peak of partial spectrum referring to Fig. 3~6：Wherein Fig. 3 is to by standard
The simulated spectra that database obtains carries out the result figure of background correction and overlapping peak separation；Where the dotted line signifies that is to effective spectral peak
Information carries out the reconstruct spectrum obtained after linear superposition；Fig. 4 is the recognition result to spectral peak in simulated spectra；Wherein fine dotted line mark
Failing to judge of occurring in the spectral peak identification process of element is denoted as, thick dashed line is labeled as erroneous judgement.Fig. 5 is to carry out background to tealeaves spectrum
Correction and the result figure of overlapping peak separation；The reconstruct where the dotted line signifies that effective spectral peak information obtain after linear superposition
Spectrum；Fig. 6 is the recognition result to spectral peak effective in tealeaves spectrum.It is found that the present invention can be preferably to light from more than figure
Spectral peak in spectrum is identified, and also can be automatic with overlapping spectrum peak and the complex spectrum of influence of noise for simple spectrum
Realize the identification of element spectral peak.
It should be noted last that more than specific embodiment is merely illustrative of the technical solution of the present invention and unrestricted,
Although the present invention is described in detail with reference to example, it will be understood by those of ordinary skill in the art that, it can be to the present invention
Technical solution be modified or replaced equivalently, without departing from the spirit and scope of technical solution of the present invention, should all cover
In scope of the presently claimed invention.
Claims (7)
1. a kind of laser induced breakdown spectroscopy spectral peak element automatic identifying method, which is characterized in that include the following steps：
Step (a) acquires laser induced breakdown spectroscopy to be identified, and the correction of continuous background is carried out to spectrum；
Step (b) carries out spectral peak fitting and decomposition using the spectrum after Voigt function pair background corrections, builds spectral peak to be identified
The characteristic parameter vector of signal；
Step (c), establishing criteria database obtain the spectral informations of all elements under identical with spectrum to be identified wave band, and
Build the characteristic parameter vector of element；
Step (d), respectively by the element spectral peak in the characteristic parameter vector of each spectral peak signal to be identified and standard database
Feature vector carry out similarity analysis；
Similarity calculation is defined as follows：
Wherein ci,tIt represents in i-th spectral peak signal and standard database to be identified between the spectral peak signal of t-th of possible element
Similarity；FiRepresent the characteristic parameter vector of i-th of spectral peak signal to be identified, FtRepresent t-th of possible element in standard database
Spectral peak signal characteristic parameter vector；
Element corresponding with the spectral peak of similarity maximum in standard database according to similarity size, is judged as this by step (e)
Element belonging to spectral peak to be identified.
2. laser induced breakdown spectroscopy spectral peak element automatic identifying method as described in claim 1, which is characterized in that
In step (b), Voigt functions are defined as follows：
Wherein I (λ) represents the spectral intensity of af at wavelength lambda；λcCentre wavelength, I for spectral peak signalc, w represent centre wavelength respectively
The halfwidth of spectral intensity and spectral peak under corresponding；θ be Gauss-Lorentz coefficient, constant of the value between (0,1)；
The spectral peak barycenter A obtained after spectrum to be identified is carried out Voigt Function Fittings is as the alternative features of waveform feature parameter θ
Parameter；Therefore for a spectral peak to be identified, its characteristic parameter vector F=[I are obtainedc,λc,w,A]；
The calculating of barycenter is defined as follows：
Wherein A represents the barycenter of spectral peak of the wavelength at λ, and I (λ) represents the spectral intensity of af at wavelength lambda, [λL,λR] for the spectral peak institute
Section.
3. laser induced breakdown spectroscopy spectral peak element automatic identifying method as claimed in claim 2, which is characterized in that
There are during peak overlap phenomenon, in order to obtain more accurate spectral peak characteristic parameter, Voigt functions are by following formula generation at this time
It replaces：
Wherein l be overlapping spectrum peak number, λt、It、wtAnd θtUnder centre wavelength, the centre wavelength of respectively t-th spectral peak correspond to
Spectral intensity, the halfwidth of spectral peak and Gauss-Lorentz coefficient.
4. laser induced breakdown spectroscopy spectral peak element automatic identifying method as claimed in claim 3, which is characterized in that
In step (b), the characteristic parameter vector of spectral peak signal to be identified is built, is implemented as：
Using consecutive points Maximum Approach in spectrum range [λ to be identifiedmin,λmax] scan for, obtain spectrum extreme value informationJ=1,2 ..., N, N are extreme point number,Wavelength location and spectral peak at respectively j-th of extreme point is strong
Degree；
Remove the spectral peak of noise and the relatively low faint spectral peak of intensity, that is, invalid；
After removing noise and invalid spectral peak, all retained extreme points, that is, spectral peak to be identified is denoted asM is spectral peak number to be identified,It is the wave of i-th of spectral peak to be identified
Long and spectral strength；
Judge spectral peak to be identifiedWhether it is overlapping spectrum peak；IfIt is spectral peak section respectivelyWithLight intensity minimum position and its intensity；If its slopeLess than to
Fixed threshold value Tk, then can determine whether spectral peak to be identifiedFor non-overlapping spectral peak, and remember that spectral peak section to be fitted isIf K >=Tk, then can determine whether spectral peak to be identifiedWithFor overlapping spectrum peak, for overlapping spectra
Peak,Find light intensity minimum position and its intensity in spectral peak sectionCalculate slopeIf K >=Tk, this process is repeated, until slope is less than given threshold value Tk, record and wait to intend
Closing spectral peak section isL is treats fit interval spectral peak number；
In spectral peak section to be fittedThe curve of spectrum is fitted using formula (2), obtains It, wt, λt, θt(t
=1,2 ..., l) characteristic parameter, t=1,2 here ..., l represents i-th, i+1 respectively ..., i+l spectral peaks to be identified；
Above step is repeated, for i-th of spectral peak to be identifiedThe characteristic parameter structure obtained using Voigt function decompositions
Build its characteristic parameter vector Fi=[Ii,λi,wi,Ai]。
5. laser induced breakdown spectroscopy spectral peak element automatic identifying method as claimed in claim 4, which is characterized in that
According to NIST standard databases in step (c), the characteristic parameter vector of element is built, is specifically included：
Set the value range of plasma electron density Ne and electron temperature T：Log (Ne) and T；Log (Ne) and T are pressed respectively
It is divided in given range according to respective step-length, the combination of multiple plasma electron density Ne and electron temperature T is obtained；
Obtain：uj=(log (Ne), T)；
For an any given uj=(log (Ne), T) is combined, the wavelength information λ according to spectral peak to be identifiedi, obtain NIST
[λ in standard databasei-Δλ,λi+ Δ λ] in the range of all possible S element, calculate and obtain spectral peak characteristic parameter to
AmountT=1,2 ... S, wherein Δ λ are experimental spectrum relative to the possible wave of standard spectrum
Long offset.
6. laser induced breakdown spectroscopy spectral peak element automatic identifying method as claimed in claim 5, which is characterized in that
Step (d) is implemented as follows：
Using i-th of spectral peak signal characteristic vector F to be identified of Cosin similarity calculationsi=[Ii,λi,wi,Ai] and NIST criterion numerals
According to elemental characteristic parameter vector in libraryT=1,2 ... the similarity of S；Expression formula is as follows：
WhereinIt represents in plasma density and electron temperature combination ujUnder the conditions of, i-th of spectral peak signal characteristic ginseng to be identified
Number vector FiIt may element with t-th in NIST standard databasesCosin similarities.
7. laser induced breakdown spectroscopy spectral peak element automatic identifying method as claimed in claim 6, which is characterized in that
Step (e) is implemented as follows：
It, will be with spectral peak signal characteristic vector F to be identified according to similarity sizeiWith maximum similarityNIST normal datas
Corresponding element of the library element as spectral peak to be identified, is denoted asIts similarity is denoted asStep (c), (d) are repeated, obtains uj
Under the conditions of=(log (Ne), T), the elemental recognition result and its similarity of all spectral peaks to be identifiedAnd it obtains
Obtain its average similarity
Above step (c), (d), (e) are repeated, obtains all ujAverage similarity under the conditions of=(log (Ne), T) is chosen maximum
U corresponding to average similarityjFor optimal plasma body electron density and electron temperature；Elemental recognition result under the conditions of this is
Final result.
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| CN117332258A (en) * | 2023-12-01 | 2024-01-02 | 奥谱天成(成都)信息科技有限公司 | Near infrared absorption peak identification method, system and medium based on multi-scale Lorentz |
| CN117332258B (en) * | 2023-12-01 | 2024-01-30 | 奥谱天成(成都)信息科技有限公司 | Near infrared absorption peak identification method, system and medium based on multi-scale Lorentz |
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