CN104132927B - The detection method of lemon chrome concentration in one heavy metal species high alkali liquid body - Google Patents
The detection method of lemon chrome concentration in one heavy metal species high alkali liquid body Download PDFInfo
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Abstract
The invention discloses the detection method of lemon chrome concentration in a heavy metal species high alkali liquid body, the method is using the heavy metal concentrated base liquid of different lemon chrome concentration as test sample, obtain each test sample Raman spectrum when setting in wave-number range with silicon chip as substrate, and according to the Raman spectrum of all test samples, it is respectively adopted successive projection algorithm and multi-element linear regression method determines calibration wave number, in lemon chrome concentration according to each test sample, and corresponding Raman spectrum, the peak at each calibration wave number is strong and 520cm‑1The strong ratio in peak at place builds the linear regression model (LRM) of concentration strengths ratio as calibration model, utilizes calibration model measurement to obtain the concentration of lemon chrome in sample to be tested.Raman test is utilized to be analyzed, simple to operate, it is not necessary to carry out loaded down with trivial details, time-consuming Sample Preparation Procedure, the interference simultaneously avoiding other sources and then the accuracy of the lemon chrome that ensure that test, and the accuracy of test is substantially increased as a comparison with silicon.
Description
Technical field
The present invention relates to lemon chrome Concentration Detection field, be specifically related to a heavy metal species high alkali liquid body
The detection method of middle lemon chrome concentration.
Background technology
Lemon chrome is the one of which of lead chromate yellow, is a kind of as oiliness synthetic resin coating, off-set oil
Ink, watercolor and the pigment of greasepaint, the inorganic colored pigments of coloured paper, rubber and plastic, owing to it has
There is perfect pigment application performance, the price of relative moderate and complete color and luster scope, therefore obtained wide
General application.Its main chemical compositions is plumbous chromate, and plumbous chromate is huge to the harm of human body, can draw
Playing anemia, renal damage, lead poisoning, dermatitis, eczema, chrome ulceration of the nose and skin ulcer etc., international cancer grinds
Study carefully center (IARC) and " chromium and some chromium compound " is listed in the chemical substance carcinogenic to the mankind.
And often produce 1 ton of lead chromate yellow pigment and about give off 120-150 ton waste water, waste water typically contains and exceedes
The float of more than discharging standards 5-10 times lead, chromium ion and compound thereof.The improvement of waste water
It is mainly the pH value by regulating liquid, makes the reaction of lead, chromium ion generate precipitation, to reach removal
Effect.
Mainly next by measuring the heavy metal such as lead, chromium in liquid to the detection of lemon chrome in liquid at present
Evaluation, main detection method mainly has: atomic absorption spectrography (AAS), inductively coupled plasma method,
Atomic fluorescence spectrometry and stripping voltammetry etc..
Atomic absorption spectrography (AAS) is that ground state atom based on element tested in vapor phase is to its atomic resonance spoke
The absorption intensity penetrated is to measure a kind of method of tested constituent content in sample.The advantage of this method is selectivity
By force, highly sensitive, analyst coverage wide, but can not analyze when multielement detects, refractory element simultaneously
Detection sensitivity poor, for the sample analysis that matrix is complicated, remaining some interference problem needs to solve.
Inductively coupled plasma method mainly includes inductively coupled plasma atomic emission spectrum (ICP-AES)
Method and inductivity coupled plasma mass spectrometry (ICP-MS) method.ICP-AES is that high frequency induction current produces
High temperature reaction gas is heated, ionization, the characteristic spectral line utilizing element to send is measured, it sensitive
Degree height, disturbs little, the widest, can measure Determination of multiple metal elements simultaneously or sequentially；Inductive coupling plasma
Body constitution spectrum (ICP-MS) analytical technology is by inductive coupling plasma and mass spectrometry, utilizes inductive coupling
Plasma makes sample vaporization, is separated by metal to be measured, thus enters people's mass spectrum and be measured, and passes through
Ion charge-mass ratio carries out the qualitative analysis of inorganic elements, semi-quantitative analysis, quantitative analysis, carries out many simultaneously
Plant element and isotopic mensuration, there is the detection limit lower than atomic absorption method, be trace element analysis
State-of-the-art method in field, but expensive, vulnerable to pollution.
The principle of atomic fluorescence spectrometry (AFS) is that atomic vapour absorbs the light radiation of certain wavelength and quilt
Exciting, excited atom launches the light radiation of certain wavelength subsequently by excitation process, in certain experiment
Under the conditions of, its radiant intensity is directly proportional to atomic concentration.Atomic fluorescence spectrometry has highly sensitive, choosing
Selecting property is strong, and sample size is few and the method feature such as simply；But it is the most extensive that its weak point is range of application.
Stripping voltammetry is also known as reverse stripping polarography, and this method is to make tested material, to be measured from
It is electrolysed the regular hour under the current potential of sub-polarographic analysis generation carrying current, then changes the current potential of electrode,
Make the enrichment dissolution again of material on this electrode, enter according to the volt-ampere curve obtained by process in leaching
Row quantitative analysis.The sensitivity of the method is the highest, therefore has practical value in ultrapure material analysis, but
It is affect Stripping Currents a lot of because have, such as enrichment time, mixing speed and potential scan rate etc..
Above method is all by identifying heavy metal lead and the existence of chromium in solution, and then infers in liquid
The lemon chrome content of residual, but in Liquid-treatment processes, it is impossible to get rid of other sources of lead, chromium.
So, the detection depending merely on heavy metal lead and chromium cannot determine that lead in liquid, chromium necessarily derive from lemon chrome.
And needing to use substantial amounts of reagent when detecting by above method and carry out pre-treatment, process is loaded down with trivial details, it is impossible to do
To quickly detection.Additionally, at present in lemon chrome wastewater treatment process, remaining Fructus Citri Limoniae in each flow process
The monitoring of chrome yellow is also rarely reported.
Summary of the invention
For the deficiencies in the prior art, the invention provides lemon chrome in a heavy metal species high alkali liquid body dense
The detection method of degree.
The detection method of lemon chrome concentration in one heavy metal species high alkali liquid body, including:
(1) using the heavy metal concentrated base liquid of different lemon chrome concentration as test sample, each is obtained
The test sample Raman spectrum when setting in wave-number range with silicon chip as substrate；
(2) according to the Raman spectrum of all test samples, it is respectively adopted successive projection algorithm and extracts some
Stack features peak, the quantity at every stack features peak is different, with 520cm during employing successive projection algorithm-1The row at place
Vector is as initial projections vector；
(3) multi-element linear regression method is utilized to determine the checking root-mean-square error at each stack features peak, choosing
Select the minimum stack features peak of checking root-mean-square error as characteristic fingerprint peak, and using characteristic fingerprint peak as
Calibration wave number, according to the lemon chrome concentration of each test sample, and in corresponding Raman spectrum, each is fixed
Peak at mark wave number is strong and 520cm-1The strong ratio in peak at place builds the first linear regression of concentration-strength ratio
Model is as calibration model；
Described linear regression model (LRM) is:
Y=88.767+0.127 λ1-0.161λ2+0.173λ3-0.251λ4+0.189λ5-0.484λ6
+0.131λ7+0.01395λ8+0.01625λ9
Wherein, λ1、λ2、λ3、λ4、λ5、λ6、λ7、λ8And λ9It is respectively 2195cm-1、1678cm-1、
1222cm-1、1217cm-1、1123cm-1、990cm-1、844cm-1、532cm-1And 112cm-1
The peak at place is strong and 520cm-1The strong ratio in peak at place；
(4) obtain the sample to be tested Raman spectrum when setting in wave-number range with silicon chip as substrate, count
Calculate in this Raman spectrum that the peak at each calibration wave number is strong and 520cm-1The strong ratio in peak at place, and substitute into
Calibration model is calculated the concentration of lemon chrome in sample to be tested.
Raman spectrum is the molecular structure characterization technology set up based on Raman effect, originate from crystal or
Molecular vibration (and lattice vibration) and rotation, the position of Raman line, intensity and live width can provide molecule to shake
Information in terms of dynamic, rotation, can realize accordingly some chemical bond and functional group in molecule " fingerprint reflects
Not ".Raman spectrum is as the means of testing of molecular level, it is easy to accomplish the composition of COMPLEX MIXED objects system
Identification and analysis.Compare with other methods relying on detection to belong to lead and chromium element, utilize Raman detection to protect
Lead and the chromium element of card test derive from lemon chrome, and then ensure that the accuracy of the lemon chrome of test,
Avoid the interference in other sources.
The heavy metal concentrated base liquid of the present invention refers to the NaOH solution of heavy metal more.
Silicon chip many employings monocrystalline silicon piece in the present invention, and be burnishing surface with test sample contact surface, favorably
In strengthening 520cm-1The Raman vibration at place.
In the present invention when successive projection algorithm, by the characteristic peak (520cm of silicon-1Place peak) row to
Measure as initial projections vector, it is ensured that when processing big data sample, the uniqueness of result, the most also
It is greatly accelerated the processing speed of data.On the other hand, in modeling process, pick and do not affect solution
The silicon substrate of structural property, with its characteristic peak as reference, by each characteristic fingerprint peak of test sample
Intensity and 520cm-1The ratio that the peak at place is strong builds calibration model, it is possible to achieve the semidefinite of Raman spectrum
Amount detection, substantially increases the accuracy of test.
Multiple linear regression analysis is used to study the interdependent pass between a dependent variable and one group of independent variable
System, result according to linear regression analysis in step (3), select that root-mean-square error is minimum one group
Characteristic peak calculates the concentration of lemon chrome in sample to be tested as characteristic fingerprint peak, it is possible to increase measurement result
Accuracy.
Described step (1) comprises the steps:
(1-1), after silicon chip being inserted container bottom, in container, test sample is injected；
(1-2) container being marked with test sample is placed on the object stage of micro-Raman spectroscopy test
The Raman spectrum of this test sample.
When obtaining Raman spectrum (Raman spectrum) with silicon chip as substrate, can be directly by sample standard deviation
Even spread upon on silicon chip, then the silicon chip of uniform application is placed on the object stage of micro-Raman spectroscopy
The Raman spectrum of test sample.But owing to liquid has mobility, and required test sample amount is
Trace, liquid surface also exists tension force, directly smears and cannot guarantee the smooth of sample surfaces, easily to reality
Test and impact.Secondly, when employing is smeared, it is difficult to ensure that the amount of the test sample every time smeared just phase
Deng, thus there is test error.The present invention utilize container hold test sample, it is simple to test sample
Carry out quantitatively, it is also possible to make surfacing, beneficially reduce the test error caused because of test condition.
The present invention is guaranteed discharge is identical, the most all container is filled, then utilize scraper plate along container top surface
Remove unnecessary liquid.
Generally using hydrostatic column, accordingly, described silicon chip is circular, and silicon chip diameter container
Internal diameter little 1～2mm.
When carrying out Raman test, for guaranteeing to collect the Raman vibration of silicon substrate, make as far as possible
Silicon chip can cover whole container bottom, and tries not to scan the point near container edge when test.
If technical conditions allow, the bottom that can directly Si sheet be welded in container, or use silicon materials
Container.
In the present invention, the test condition of Raman test is as follows: testing laser wavelength is 532nm, test
Laser power is 25mv, and time of exposure is 1s, and exposure frequency is 1 time, and gathering aperture is 20 μm,
Object lens are 20 times, and number of scan points is 30.
As preferably, the quantity of test sample is 50～150.
Raman spectrum separately through some test sample is difficult to determine accurately the spy of lemon chrome
Levy fingerprint peaks, by large sample is carried out statistical analysis in the present invention, it is possible to find out lemon chrome accurately
The characteristic fingerprint peak that yellow vibration is relevant.Generally sample number is the most, and it is the most accurate that characteristic fingerprint peak judges, but
So can cause computationally intensive, efficiency is low.Therefore the quantity of test sample needs to consider according to practical situation,
Can not be the highest, can not be the lowest.It addition, some groups can be divided into (to lead to for ease of realizing all test samples
It is often 5～7 groups), the lemon chrome concentration of each group is identical, and the lemon chrome concentration between different groups is entered
Row gradient is arranged.
As preferably, set wave-number range as 112.3～2717.2cm-1。
In heavy metal concentrated base liquid, the vibration peak relevant to lemon chrome is distributed in this wave-number range, therefore
By set this 112.3～2717.2cm-1Wave-number range scanning.
In described step (2) each stack features peak, the number of characteristic peak is 5～15.
The group extracting the characteristic peak obtained is several according to practical situation setting, and in different groups, the number of characteristic peak is mutual
Differ, take into account the modeling efficiency of model and the accuracy of model, the number of characteristic peak is set as
5～15, the characteristic peak number that often group comprises is the most different.
Also include updating calibration wave number and calibration model after described step (3) builds calibration model, more
Calibration model after Xin is:
Y=88.972+0.123 λ1-0.133λ2-0.399λ6+0.132λ7+0.01296λ8。
Update method is as follows:
The first described linear regression model (LRM) is carried out variance analysis screening calibration wave number, and by after screening
Calibration wave number is as final calibration wave number, according to the lemon chrome concentration of all test samples, and sieve
The peak at each calibration wave number after choosing is strong and 520cm-1The ratio that the peak at place is strong builds concentration-strength ratio
Second linear regression model (LRM) is as calibration model.
By the first linear regression model (LRM) is carried out variance analysis, characteristic fingerprint peak is screened, determine
To final calibration wave number, improve the accuracy of calibration model further, and then reduce the dense of final test
Deviation between angle value and actual concentrations value.
Not making specified otherwise in the present invention, Y all represents the content of lemon chrome in test sample, its unit
For mg/ml.
Compared with prior art, present invention have the advantage that
(1) Raman test is utilized to be analyzed, it is possible to ensure that the lead of test and chromium element derive from lemon
Lemon chrome yellow, and then ensure that the accuracy of the lemon chrome of test, it is to avoid the interference in other sources；
(2) utilize silicon chip as substrate, on the one hand, owing to this detection tested is to liking liquid, to use
Silicon chip is as substrate, the focusing in can conveniently testing；On the other hand, the signal peak of silicon chip is single, main
Will be at 520cm-1Place is few to the signal disturbing of test sample；Meanwhile, with each feature of test sample
The intensity of fingerprint peaks and 520cm-1The ratio that the peak at place is strong builds calibration model, it is possible to achieve Raman spectrum
Half-quantitative detection, substantially increase the accuracy of test；
(3) simple to operate, it is to avoid the extraction of traditional lemon chrome content measurement, clear up etc. loaded down with trivial details,
Time-consuming Sample Preparation Procedure, for remaining in monitoring lemon chrome wastewater treatment process the most in real time
The concentration of lemon chrome provides effective means, has a good application prospect.
Detailed description of the invention
Describe the present invention below in conjunction with specific embodiment and comparative example.
Weigh 1g, 0.8g, 0.6g, 0.4g, 0.2g lemon chrome respectively in 50ml beaker, with moving liquid
Pipe moves into 10mlNaOH concentrated solution, is sufficiently stirred for mixing with Glass rod, after standing overnight, is configured to 5
The liquid sample of individual Concentraton gradient.Each concentration level takes 15 samples, adding up to of 5 Concentraton gradient
To 75 test samples.
Embodiment 1
The detection method of lemon chrome concentration in one heavy metal species high alkali liquid body, including:
(1) using the heavy metal concentrated base liquid of different lemon chrome concentration as test sample, each is obtained
Test sample is at 2717.2cm-1～112.3cm-1With silicon chip for Raman spectrum during substrate in wave-number range.
The present embodiment uses the 96 flat culture dish in hole (aperture: 6.4mm, floor space: 0.32cm2,
Volume is 0.36ml) as container, a hole is i.e. as a container.First the bottom in every hole is placed
One piece of a diameter of 5mm, thickness is the circular silicon chip of 0.5mm, with pipet pipette 0.4ml liquid in
In culture dish hole, along culture dish edge, unnecessary liquid is removed with scraper plate, then culture dish is placed
On the glass sheet, stand-by.
The container filling test sample is placed on the object stage of micro-Raman spectroscopy and tests each survey
Sample Raman spectrum originally.The test condition of each sample is identical, as follows:
Testing laser wavelength is 532nm, and testing laser power is 25mv, and time of exposure is 1s, exposure
Number of times is 1 time, and gathering aperture is 20 μm, and object lens are 20 times, and number of scan points is 30.
(2) according to the Raman spectrum of all test samples, it is respectively adopted successive projection algorithm and extracts some
Stack features peak, the quantity at every stack features peak is different, with 520cm during employing successive projection algorithm-1The row at place
Vector is as initial projections vector；
Number M (M=75 in the present embodiment) according to test sample and the number K composition size of wave number
For the light spectrum matrix X of M × K, the element x in light spectrum matrix XijFor i-th test sample in jth
The intensity level of the Raman peaks at individual wave number, the wave number maximum that j=1 wave number is corresponding, reduce the most backward.
Successive projection algorithm (SPA algorithm) is a kind of forward direction circulation system of selection, and it is from light spectrum matrix X
In string group corresponding to any one wavelength start as projection vector, circulate every time, calculate this projection to
Amount projection on the vector that the wavelength not being selected into is corresponding, then wavelength maximum for the mould of projection vector is introduced
To wavelength combinations, until circulation n times.The wavelength being newly selected into, all with previous linear relationship
Little.
The present embodiment needs altogether to extract 11 stack features peaks, the characteristic peak that each stack features peak comprises
Number respectively 5,6 ... 15.SPA method is all used to extract for each stack features peak, note
The number at every stack features peak is N, then SPA method comprises the steps:
(2-1) initialize: n=1 (iteration for the first time), 520cm in light spectrum matrix X-1Corresponding unit
Element one column vector of composition is as projection vector, and i.e. initial projections vector, is designated as Xk(0)(i.e. j=k (0),
And kth (0) wave number is 520cm-1)；
(2-2) set S is defined as:The most not by
Selecting the column vector into wavelength chain, wherein, k (n-1) represents the maximal projection institute that nth iteration is elected
Column vector, according to formula:
Pxj=xj-(xj Txk(n-1))xk(n-1)(xT k(n-1)xk(n-1))-1,
Calculate X respectivelyjThe projection in column vector that each wave number is corresponding in S gathers, and according to formula:
K (n)=arg (max | | Pxj| |, j ∈ S)
Determine the value of the j of projection maximum, and be designated as k (n), wherein | | Pxj| | for projection vector at XjOn
The mould of projection；
If (2-3) n < N, then make n=n+1, and return step (2-1), and with Xk(n)As initially
Projection vector, otherwise stops, and using wave number corresponding to each maximal projection as the position at characteristic peak place,
And then obtain except 520cm-1Outward, a stack features peak of N number of characteristic peak is additionally comprised.
(3) respectively each group of N number of characteristic peak is set up linear regression model (LRM), use multiple linear regression
Analytic process judges the quality of institute's established model, selects a stack features peak of RMSEP of minimum as feature
Fingerprint peaks.Using select characteristic fingerprint peak as calibration wave number, according to the lemon chrome of each test sample
In concentration, and corresponding Raman spectrum, the peak at each calibration wave number is strong and 520cm-1The strong ratio in peak at place
Value builds the linear regression model (LRM) of concentration-strength ratio as calibration model；
The linear regression model (LRM) obtained in the present embodiment is:
Y=88.767+0.127 λ1-0.161λ2+0.173λ3-0.251λ4+0.189λ5-0.484λ6
+0.131λ7+0.01395λ8+0.01625λ9
Wherein, λ1、λ2、λ3、λ4、λ5、λ6、λ7、λ8And λ9It is respectively 2195cm-1、1678cm-1、
1222cm-1、1217cm-1、1123cm-1、990cm-1、844cm-1、532cm-1And 112cm-1
The peak at place is strong and 520cm-1The strong ratio in peak at place；
(4) obtain the sample to be tested Raman spectrum when setting in wave-number range with silicon chip as substrate, count
Calculate in this Raman spectrum that the peak at each calibration wave number is strong and 520cm-1The strong ratio in peak at place, and substitute into
Calibration model is calculated the concentration of lemon chrome in sample to be tested.
Utilize calibration model predicting the outcome such as table 1 institute to the lemon chrome concentration of these 25 samples to be tested
Showing, the correlation coefficient of model is 0.990125, and root-mean-square error is 5.269907.Illustrate that this model can
Realize effective detection of lemon chrome concentration in concentrated NaOH solution.
Table 1
Embodiment 2
Same as in Example 1, except that also include after step (4) builds calibration model updating
Calibration wave number and calibration model, update method is as follows:
First calibration model is carried out variance analysis screening calibration wave number, and the calibration wave number after screening is made
For final calibration wave number, and according to the lemon chrome concentration of all test samples, and in Raman spectrum
The peak at each calibration wave number after screening is strong and 520cm-1The ratio that the peak at place is strong builds concentration-strength ratio
Linear regression model (LRM) as update after calibration model.
Calibration model before updating is carried out variance analysis, and result is as shown in table 2
Table 2
Table 2 shows wave number variable λ1222、λ1123、λ112(sample is in wave number 1222cm-1、1123cm-1、
112cm-1Place raman spectrum strength) significant level P > 0.05, show wave number variable
λ1222、λ1123、λ112With dependent variable Y (concentration of lemon chrome in concentrated base liquid) without significant correlation,
Therefore wave number 1222cm-1、1123cm-1、112cm-1Be not suitable for for setting up lemon chrome in concentrated base liquid dense
The measurement model of degree.Simultaneously in wave number 1217cm-1The Raman spectrum curve at place does not has significant characteristic peak,
Therefore also reject.Finally it is left 2195cm-1、1678cm-1、990cm-1、844cm-1、532cm-1Five
Individual wave number is as finally calibrating wave number, and re-establishes linear regression model (LRM) work according to these five calibration wave numbers
For the calibration model after updating.
In the present embodiment, the calibration model after renewal is:
Y=88.972+0.123 λ1-0.133λ2-0.399λ6+0.132λ7+0.01296λ8。
Utilize calibration model the predicting the outcome to the lemon chrome concentration of these 25 samples to be tested after updating
As shown in table 3, the correlation coefficient of model is 0.990983, and root-mean-square error is 5.040833.This is described
Model is capable of effective detection of lemon chrome concentration in concentrated NaOH solution.
Table 3
Comparative example
Choose neighbouring five wavelength and be respectively 816nm, 1123nm, 1217nm, 1927nm, 2430nm,
Set up for measuring the calibration model of lemon chrome concentration in heavy metal concentrated base liquid based on these five wavelength:
Y=41.700768+0.308 λ2430/λ520+0.385λ1927/λ520-0.561λ1217/
λ520-1.982λ1123/λ520+0.435λ816/λ520。
Utilize the inspection of lemon chrome concentration in this calibration model calculated sample heavy metal concentrated base liquid
Measured value is as shown in table 4 with actual value, and the prediction related coefficient of this calibration model is 0.867349, and effect is bright
Significant difference is in the prediction related coefficient 0.990983 of institute of the present invention extracting method.
Table 4
Technical scheme and beneficial effect have been carried out in detail by above-described detailed description of the invention
Explanation, it should be understood that the foregoing is only presently most preferred embodiment of the invention, is not limited to this
Bright, all made in the spirit of the present invention any amendment, supplement and equivalent etc., all should wrap
Within being contained in protection scope of the present invention.
Claims (8)
1. the detection method of lemon chrome concentration in a heavy metal species high alkali liquid body, it is characterised in that including:
(1) using the heavy metal concentrated base liquid of different lemon chrome concentration as test sample, each is obtained
The test sample Raman spectrum when setting in wave-number range with silicon chip as substrate；
(2) according to the Raman spectrum of all test samples, it is respectively adopted successive projection algorithm and extracts some
Stack features peak, the quantity at every stack features peak is different, with 520cm during employing successive projection algorithm-1The row at place
Vector is as initial projections vector；
(3) multi-element linear regression method is utilized to determine the checking root-mean-square error at each stack features peak, choosing
Select the minimum stack features peak of checking root-mean-square error as characteristic fingerprint peak, and using characteristic fingerprint peak as
Calibration wave number, according to the lemon chrome concentration of each test sample, and in corresponding Raman spectrum, each is fixed
Peak at mark wave number is strong and 520cm-1The strong ratio in peak at place builds the first linear regression of concentration-strength ratio
Model is as calibration model；
The first described linear regression model (LRM) is:
Y=88.767+0.127 λ1-0.161λ2+0.173λ3-0.251λ4+0.189λ5-0.484λ6
+0.131λ7+0.01395λ8+0.01625λ9
Wherein, λ1、λ2、λ3、λ4、λ5、λ6、λ7、λ8And λ9It is respectively 2195cm-1、1678cm-1、
1222cm-1、1217cm-1、1123cm-1、990cm-1、844cm-1、532cm-1And 112cm-1
The peak at place is strong and 520cm-1The strong ratio in peak at place；
(4) obtain the sample to be tested Raman spectrum when setting in wave-number range with silicon chip as substrate, count
Calculate in this Raman spectrum that the peak at each calibration wave number is strong and 520cm-1The strong ratio in peak at place, and substitute into
Calibration model is calculated the concentration of lemon chrome in sample to be tested.
2. the detection method of lemon chrome concentration in heavy metal concentrated base liquid as claimed in claim 1, its
Being characterised by, described step (1) comprises the steps:
(1-1), after silicon chip being inserted container bottom, in container, test sample is injected；
(1-2) container being marked with test sample is placed on the object stage of micro-Raman spectroscopy test
The Raman spectrum of this test sample.
3. the detection method of lemon chrome concentration in heavy metal concentrated base liquid as claimed in claim 2, its
Being characterised by, described silicon chip is circular, and the internal diameter little 1～2mm of silicon chip diameter container.
4. the detection method of lemon chrome concentration in heavy metal concentrated base liquid as claimed in claim 1, its
Being characterised by, the quantity of test sample is 50～150.
5. the detection method of lemon chrome concentration in heavy metal concentrated base liquid as claimed in claim 1, its
It is characterised by, sets wave-number range as 112.3～2717.2cm-1。
6. the detection method of lemon chrome concentration in heavy metal concentrated base liquid as claimed in claim 1, its
Being characterised by, in described step (2) each stack features peak, the number of characteristic peak is 5～15.
7. Fructus Citri Limoniae in the heavy metal concentrated base liquid as described in any one claim in claim 1～6
The detection method of chrome yellow concentration, it is characterised in that also wrap after building calibration model in described step (3)
Including renewal calibration wave number and calibration model, the calibration model after renewal is:
Y=88.972+0.123 λ1-0.133λ2-0.399λ6+0.132λ7+0.01296λ8。
8. the detection method of lemon chrome concentration in heavy metal concentrated base liquid as claimed in claim 7, its
Being characterised by, update method is as follows:
The first described linear regression model (LRM) is carried out variance analysis screening calibration wave number, and by after screening
Calibration wave number is as final calibration wave number, according to the lemon chrome concentration of all test samples, and sieve
The peak at each calibration wave number after choosing is strong and 520cm-1The ratio that the peak at place is strong builds concentration-strength ratio
Second linear regression model (LRM) is as calibration model.
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| JP5077886B2 (en) * | 2008-02-08 | 2012-11-21 | 独立行政法人産業技術総合研究所 | SERS particles comprising noble metal nanoparticle composite and method for producing the same |
| CN101403696A (en) * | 2008-10-21 | 2009-04-08 | 浙江大学 | Method for measuring gasoline olefin content based on Raman spectrum |
| CN102890079B (en) * | 2012-10-14 | 2015-09-16 | 江苏省理化测试中心 | Laser Raman spectroscopy technology detects the method for art green in tealeaves fast |
| CN103901014B (en) * | 2014-03-10 | 2016-04-20 | 华南师范大学 | Multiple linear regression matching obtains the method for real cell Raman spectrum |
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