CN102306236A - Multivariable analysis method based on angle measurement - Google Patents
Multivariable analysis method based on angle measurement Download PDFInfo
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- CN102306236A CN102306236A CN201110188187A CN201110188187A CN102306236A CN 102306236 A CN102306236 A CN 102306236A CN 201110188187 A CN201110188187 A CN 201110188187A CN 201110188187 A CN201110188187 A CN 201110188187A CN 102306236 A CN102306236 A CN 102306236A
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Abstract
The invention discloses a multivariable analysis method based on angle measurement, and relates to a method for noncontact analysis on products. The method comprises the following steps: measuring a measured sample and a measured component to obtain the multipoint strength measurement value of the measured sample and the measured component; converting the multipoint strength measurement value of the measured sample and the measured component into an angle metric of the measured sample and the measured component; selecting a modeling sample; converting the multipoint strength measurement value of the measured sample and the measured component into the angle metric of the modeling sample and the measured component; building a multivariable regression model by taking the measured component content of the modeling sample as a dependent variable and the angle metric of the modeling sample and the measured component as an independent variable; and substituting the angle metric of the measured sample and the measured component into the multivariable regression model to predict the content of the measured component in the whole hybrid system. According to the multivariable analysis method, requirement on the environment in the analysis operation is obviously lowered, complexity of instrument can be reduced, and the multivariable analysis method is suitable for chemical analysis, process analysis and instrument analysis.
Description
Technical field
The present invention relates to a kind of multivariable technique that is used for product is carried out the method, particularly a kind of suitable multicomponent system of noncontact analysis based on angle tolerance.
Background technology
Process analysis technique is divided into five stage: off-line (off-line analysis), at-line (near line analysis), on-line (on-line analysis with the development of metering system; On-line analysis), in-line (in-line analysis) and Noninvasive (noncontact analysis), wherein on-line is divided into intermittent (being interrupted) and continuous (continuously) again.The in-line stage refers to measured matter to be taken out and carry out pre-service; Noncontact is analyzed then and when measuring, more is difficult to measured object is handled and operated; Even analyze desired reproducibility analysis environments usually and all possibly be difficult to satisfy, so these stages have proposed very high requirement to analytical approach.Common analysis is very strict to the reappeared requirement of environment, is example with the photometric analysis, and its quantitative basis is a langbobier law, and it is stable to require to see through light path, and this is very harsh requirement for the noncontact analysis; In recent years, reflection or scatterometry obtain paying attention in noncontact is analyzed, and compare with transmission measurement, and the flexible operation degree has increased, but environmental impact factor is more, needs sample units such as configuration integrating sphere, has increased the complexity of instrument; Laser raman is the interested important means of non-contact analysis; It quantitatively is difficult that the factors such as variations in refractive index that but light source power changes, concentration of specimens causes cause directly relatively the Raman spectrum band strength; It has been generally acknowledged that add in mark be effective method, but the essence that internal standard method operation and noncontact are analyzed is contradiction.That is to say, adopt the quantivative approach of band intensity in noncontact is analyzed, to run into very big obstacle, be necessary to propose a kind of new quantivative approach, to adapt to the growth requirement of analytical technology.
Summary of the invention
The technical matters that the present invention will solve is: a kind of multivariable technique based on angle tolerance that adapts to multicomponent system is provided, to overcome increase instrument complexity that prior art exists, to be subjected to the bigger weak point of such environmental effects.
The ultimate principle that the present invention solves the problems of the technologies described above: each component based on multicomponent system can correspond to single vector in the space, and system is the space that a plurality of vectors constitute.The space also can be described as tested component vector a and not contain this vectorial lineoid B, and a tested sample s who comprises tested component and other components can be expressed as a vector between between tested component vector sum lineoid in the system, as shown in Figure 1.
A meets at b with plane and B that s opens, and like Fig. 2, the length of vector is represented the response intensity or the content of measured object; If the content of measured object a is low more in the system, the angle theta of tested sample s and a is just big more, otherwise just more little.Therefore, can be determined in the space under the situation of description, angle theta can be used as quantitative target.
The angle of vector can use the dot product formula to calculate:
The matrix description system that present multivariate statistical analysis adopts intensity level to constitute, when rank of matrix surpassed the space dimensionality of system, system just can be determined description.Definite description that the matrix that the present invention proposes to adopt angle value to constitute comes the implementation space, when the rank of matrix that constitutes when angle value surpassed the dimension in system space, this matrix was also confirmed the description in space.
Fig. 3 is the spectrum that the intensity level of m wavelength points constitutes, and is divided into n interval, if system contains p kind component, to the requirement of m and n is:
So, vectorial a and s are split into { a
1..., a
i..., a
nAnd { s
1..., s
i..., s
n, the angle between each vector:
The m of an a and s intensity level is converted to n angle value { θ
1..., θ
i..., θ
n.
The technical scheme that the present invention solves the problems of the technologies described above is: a kind of multivariable technique based on angle tolerance; It is characterized in that: this method is through qualitative or quantitative apparatus measures tested sample of material and tested component, obtains the multiple spot intensity measurements of tested sample and tested component; And the multiple spot intensity measurements of tested sample and tested component is converted into the differences in angle value of tested sample and tested component; Choose quantity several modeling samples greater than the mixed system number of components; Tested component is known in the relative content of whole mixed system in the modeling sample; The multiple spot intensity measurements of modeling sample and tested component is converted into the differences in angle value of modeling sample and tested component; Then with the tested component concentration in the modeling sample as dependent variable; The matrix that the differences in angle value of modeling sample and tested component constitutes is set up the multivariate regression model as independent variable; This multivariate regression model of differences in angle value substitution with tested sample and tested component can predict the content of tested component in whole mixed system.
Further technical scheme of the present invention is: this method may further comprise the steps:
SA1, confirm tested sample s and tested component a, and definition cutting interval number n, wherein n＞mixed system number of components p;
SA2, measuring unit qualitative through material or quantitative instrument are measured tested component a and tested sample s, obtain the multiple spot intensity measurements of tested component a and the multiple spot intensity measurements of tested sample s;
SA3, with measurement point be divided into n interval, then the multiple spot intensity measurements of tested component a is split into { a
1..., a
i..., a
n; The multiple spot intensity measurements of tested sample s is split into { s
1..., s
i..., s
n;
SA4, ask for included angle cosine between tested sample s and each the tested component a:
SA5, ask for the differences in angle value { θ of tested sample s and each tested component a
1..., θ
i..., θ
n;
B, modeling:
SB1, choose several modeling sample S of quantity greater than mixed system number of components p, tested component a is known in the relative content of whole mixed system among the modeling sample S;
SB2, measuring unit qualitative through material or quantitative instrument are measured modeling sample S, obtain the multiple spot intensity measurements of modeling sample S;
SB3, the intensity value of modeling sample S and tested component a transferred to the differences in angle value of modeling sample S and tested component a;
SB4, with the content of tested component a among the modeling sample S as dependent variable, the matrix that the differences in angle value of modeling sample S and tested component a is constituted adopts the multivariate statistics homing method to set up the multivariate regression model as independent variable;
C, prediction:
This multivariate regression model of differences in angle value substitution with tested component a and tested sample s; Can predict the content of tested component a in the whole mixed system of tested sample s; The predict the outcome analysis result display unit output of or quantitative instrument qualitative from material, EO.
Owing to adopt said structure, the present invention based on the multivariable technique of angle tolerance compared with prior art, have following beneficial effect:
1, significantly reduced in the analysis operation environment requirement:
Because the tolerance conversion method that the present invention proposes has been avoided causing the infeasible problem of multivariable analysis because of response intensity changes; Like spectral analysis; As long as the spectral shape that obtains is consistent; And because external factor; For example variation of the distance of measuring distance, the intensity of light source etc.; The Strength Changes that causes can not exert an influence to multivariate regression model accurately; Therefore; The present invention has significantly reduced in the analysis operation environment requirement, and contactless on-the site analysis and on-line analysis etc. are significant for accomplishing.
But the complexity of 2 lowering apparatus:
Because the present invention in use, need not to increase in addition other operating instrument, also need not to dispose sample units such as integrating sphere, thereby but the complexity of lowering apparatus.
3, operating process is simple:
Operating process of the present invention is fairly simple, is easy in chemical analysis, process analysis procedure analysis, instrumental analysis, to relate under the situation of apparatus measures strength fluctuation use.
Below, in conjunction with accompanying drawing and embodiment the present invention's the technical characterictic based on the multivariable technique of angle tolerance is further described.
Description of drawings
Fig. 1: tested component a in the multicomponent system, do not contain the lineoid B of a and comprise the graph of a relation between the tested sample s of tested component a and other components;
Fig. 2: the graph of a relation between tested component a and tested sample s and the angle theta;
The spectrogram that the intensity level of Fig. 3: a m wavelength points constitutes;
Fig. 4: the present invention's FB(flow block) based on the multivariable technique steps A of angle tolerance,
Fig. 5: the present invention's FB(flow block) based on the multivariable technique step B of angle tolerance,
The Raman spectrogram of Fig. 6: embodiment one said mensuration;
The model working curve diagram of Fig. 7: embodiment one said employing modeling gained of the present invention,
Horizontal ordinate among Fig. 7 is an actual value, and ordinate is a predicted value;
The model working curve diagram of Fig. 8: embodiment one said direct employing Raman spectrogram modeling gained,
Horizontal ordinate among Fig. 8 is an actual value, and ordinate is a predicted value.
Embodiment
Embodiment one:
A kind of multivariable technique based on angle tolerance, this method is through qualitative or quantitative apparatus measures tested sample of material and tested component, obtains the multiple spot intensity measurements of tested sample and tested component; And the multiple spot intensity measurements of tested sample and tested component is converted into the differences in angle value of tested sample and tested component; Choose quantity several modeling samples greater than the mixed system number of components; Tested component is known in the relative content of whole mixed system in the modeling sample; The multiple spot intensity measurements of modeling sample and tested component is converted into the differences in angle value of modeling sample and tested component; Then with the tested component concentration in the modeling sample as dependent variable; The matrix that the differences in angle value of modeling sample and tested component constitutes is set up the multivariate regression model as independent variable; This multivariate regression model of differences in angle value substitution with tested sample and tested component can predict the content of tested component in whole mixed system.
The concrete steps that above-mentioned multivariable technique based on angle tolerance is used for analyzing monoethylene glycol, propylene glycol, alcohol mixture monoethylene glycol content are following:
The intensity of A, tested sample and tested component is to the conversion of the tolerance of angle, FB(flow block) as shown in Figure 4:
SA1, confirm tested sample s and tested component a, and definition cutting interval number n, wherein n＞mixed system number of components p:
With monoethylene glycol, propylene glycol, three kinds of components of ethanol, according to tested component a---monoethylene glycol is from 0 to 5.0mL, prepares the potpourri of n=11 content of cutting interval number at interval according to 0.5mL, to 10mL, obtains tested sample s with propylene glycol and any proportioning constant volume of ethanol;
SA2, measuring unit qualitative through material or quantitative instrument are measured tested component a and tested sample s, obtain the multiple spot intensity measurements of tested component a and the multiple spot intensity measurements of tested sample s:
Through spectrometer with 785nm laser excitation tested sample s; Measuring unit through spectrometer is measured the Raman spectrogram; Fixation measuring distance not during mensuration; Be as the criterion can detect Raman signal; Obtain the multiple spot intensity measurements of tested component monoethylene glycol and the multiple spot intensity measurements of tested sample s, the spectrogram of gained as shown in Figure 6;
SA3, with measurement point be divided into n interval, then the multiple spot intensity measurements of tested component a is split into { a
1..., a
i..., a
n; The multiple spot intensity measurements of tested sample s is split into { s
1..., s
i..., s
n;
SA3, ask for included angle cosine between tested sample s and each the tested component a:
；
SA4, ask for the differences in angle value { θ of tested sample s and each tested component a
1..., θ
i..., θ
n;
B, modeling, FB(flow block) be as shown in Figure 5:
SB1, choose several modeling sample S of quantity greater than mixed system number of components p, tested component a is known in the relative content of whole mixed system among the modeling sample S;
SB2, measuring unit qualitative through material or quantitative instrument are measured modeling sample S, obtain the multiple spot intensity measurements of modeling sample S;
SB3, the intensity value of modeling sample S and tested component a transferred to the differences in angle value of modeling sample S and tested component a;
SB4, with the content of the serial volume of tested component a monoethylene glycol among the modeling sample S as dependent variable; The matrix that the differences in angle value of modeling sample S and tested component a is constituted adopts the multivariate statistics homing method of partial least squares regression to set up the multivariate regression model as independent variable;
C, prediction:
This multivariate regression model of differences in angle value substitution with tested component a and tested sample s; Gained model working curve diagram as shown in Figure 7; Can predict the content of tested component a in the whole mixed system of tested sample s; The predict the outcome analysis result display unit output of or quantitative instrument qualitative from material, EO.
For the multivariable technique based on angle tolerance with the present invention compares with adopting existing Raman spectrogram modeling analysis method; The inventor also with reference to the accompanying drawings the Raman spectrogram shown in 6 carry out the modeling of direct Raman spectrogram; The model working curve diagram of gained as shown in Figure 8; By finding out among this Fig. 8; Directly the modeling of Raman spectrogram can reflect the variation tendency of content; But corresponding relation is relatively poor, can not realize accurately quantitatively; And among Fig. 7, adopt angle tolerance of the present invention modeling, and showed good corresponding relation, can satisfy accurately quantitative requirement.
As a kind of conversion of present embodiment one, the present invention's the multivariable technique based on angle tolerance also can be used for analyzing the tested component concentration in other potpourri.
Claims (2)
1. multivariable technique based on angle tolerance, it is characterized in that: this method is through qualitative or quantitative apparatus measures tested sample of material and tested component, obtains the multiple spot intensity measurements of tested sample and tested component; And the multiple spot intensity measurements of tested sample and tested component is converted into the differences in angle value of tested sample and tested component; Choose quantity several modeling samples greater than the mixed system number of components; Tested component is known in the relative content of whole mixed system in the modeling sample; The multiple spot intensity measurements of modeling sample and tested component is converted into the differences in angle value of modeling sample and tested component; Then with the tested component concentration in the modeling sample as dependent variable; The matrix that the differences in angle value of modeling sample and tested component constitutes is set up the multivariate regression model as independent variable; This multivariate regression model of differences in angle value substitution with tested sample and tested component can predict the content of tested component in whole mixed system.
2. the multivariable technique based on angle tolerance according to claim 1, it is characterized in that: this method may further comprise the steps:
The intensity of A, tested sample and tested component is changed to the tolerance of angle:
SA1, confirm tested sample s and tested component a, and definition cutting interval number n, wherein n＞mixed system number of components p;
SA2, measuring unit qualitative through material or quantitative instrument are measured tested component a and tested sample s, obtain the multiple spot intensity measurements of tested component a and the multiple spot intensity measurements of tested sample s;
SA3, with measurement point be divided into n interval, then the multiple spot intensity measurements of tested component a is split into { a
1..., a
i..., a
n; The multiple spot intensity measurements of tested sample s is split into { s
1..., s
i..., s
n;
SA4, ask for included angle cosine between tested sample s and each the tested component a:
SA5, ask for the differences in angle value { θ of tested sample s and each tested component a
1..., θ
i..., θ
n;
B, modeling:
SB1, choose several modeling sample S of quantity greater than mixed system number of components p, tested component a is known in the relative content of whole mixed system among the modeling sample S;
SB2, measuring unit qualitative through material or quantitative instrument are measured modeling sample S, obtain the multiple spot intensity measurements of modeling sample S;
SB3, the intensity value of modeling sample S and tested component a transferred to the differences in angle value of modeling sample S and tested component a;
SB4, with the content of tested component a among the modeling sample S as dependent variable, the matrix that the differences in angle value of modeling sample S and tested component a is constituted adopts the multivariate statistics homing method to set up the multivariate regression model as independent variable;
C, prediction:
This multivariate regression model of differences in angle value substitution with tested component a and tested sample s; Can predict the content of tested component a in the whole mixed system of tested sample s; The predict the outcome analysis result display unit output of or quantitative instrument qualitative from material, EO.
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| CN103472028A (en) * | 2013-09-22 | 2013-12-25 | 广西科技大学 | Method for determining content of components in blended fiber |
| CN104462818A (en) * | 2014-12-08 | 2015-03-25 | 天津大学 | Embedding manifold regression model based on Fisher criterion |
| CN108235733A (en) * | 2017-12-29 | 2018-06-29 | 深圳达闼科技控股有限公司 | Substance identification and cloud system based on Raman spectrum |
| CN105844646B (en) * | 2016-04-01 | 2019-04-05 | 广西科技大学 | Spectral mixture consistency checking method |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN104462818B (en) * | 2014-12-08 | 2017-10-10 | 天津大学 | A kind of insertion manifold regression model based on Fisher criterions |
| CN105844646B (en) * | 2016-04-01 | 2019-04-05 | 广西科技大学 | Spectral mixture consistency checking method |
| CN108235733A (en) * | 2017-12-29 | 2018-06-29 | 深圳达闼科技控股有限公司 | Substance identification and cloud system based on Raman spectrum |
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