CN104132922A - Method for detecting orange chrome yellow concentration of heavy metal-containing concentrated alkali liquid - Google Patents

Abstract

The invention discloses a method for detecting an orange chrome yellow concentration of a heavy metal-containing concentrated alkali liquid. The method utilizes heavy metal-containing concentrated alkali liquids having different orange chrome yellow concentrations as test samples and comprises the following steps of acquiring Raman spectrums of all the test samples in a set wave-number range under the condition of a silicon wafer as a substrate, respectively determining calibration wave numbers by a successive projection algorithm and a multivariate linear regression analysis method according to the Raman spectrums of all the test samples, constructing a concentration-intensity ratio first linear regression model as a calibration model by the orange chrome yellow concentrations of all the test samples and ratios of peak intensities at the calibration wave numbers to peak intensity at the 520cm<-1>, and measuring an orange chrome yellow concentration of a sample to be tested by the calibration model. Raman test analysis proves that the method has simple processes, is free of tedious and time-consuming sample preparation processes, avoids other source-caused interference and guarantees orange chrome yellow test accuracy. Through use of silicon as contrast, test accuracy is greatly improved.

Description

The detection method of chrome Orange concentration in one heavy metal species high alkali liquid body

Technical field

The present invention relates to chrome Orange Concentration Detection field, be specifically related to the detection method of chrome Orange concentration in a heavy metal species high alkali liquid body.

Background technology

Chrome Orange is the wherein a kind of of lead chromate yellow, a kind of pigment as oiliness synthetic resin coating, printing-ink, watercolor and greasepaint, the inorganic coloring pigment of coloured paper, rubber and plastic products, because it has perfect pigment applications performance, relatively cheap price and complete color and luster scope, be therefore widely used.Its main chemical compositions is plumbous chromate, plumbous chromate is huge to the harm of human body, can cause anaemia, renal damage, saturnism, dermatitis, eczema, chrome ulceration of the nose and skin ulcer etc., IARC (IARC) lists the chemical substance carcinogenic to the mankind in by " chromium and some chromium compound ".And 1 ton of lead chromate yellow pigment of every production approximately gives off 120-150 ton waste water, in waste water, generally contain the suspension over discharging standards 5-10 times of above lead, chromium ion and compound thereof.The improvement of waste water is mainly by regulating the pH value of liquid, makes lead, chromium ion reaction generate precipitation, to reach the effect of removal.

At present the detection of chrome Orange in liquid is mainly evaluated by heavy metals such as lead, chromium in mensuration liquid, main detection method mainly contains: atomic absorption spectrography (AAS), inductively coupled plasma method, atomic fluorescence spectrometry and stripping voltammetry etc.

Atomic absorption spectrography (AAS) is that the ground state atom based on tested element in vapor phase is measured a kind of method of tested constituent content in sample to the absorption intensity of its atomic resonance radiation.The advantage of this method is that selectivity is strong, highly sensitive, analyst coverage is wide, but can not analyze when multielement detects simultaneously, and the detection sensitivity of refractory element is poor, and for the sample analysis of matrix complexity, remaining some interference problem needs to solve.

Inductively coupled plasma method mainly comprises inductively coupled plasma atomic emission spectrum (ICP-AES) method and inductivity coupled plasma mass spectrometry (ICP-MS) method.ICP-AES be the high temperature that produces of high frequency induction current by reaction gas heating, ionization, utilize the characteristic spectral line that element sends to measure, it highly sensitive, disturbs littlely, linear wide, can measure simultaneously or sequentially Determination of multiple metal elements; Inductive coupling plasma mass (ICP-MS) analytical technology is by inductive coupling plasma and mass spectrometry, utilize inductive coupling plasma to make sample vaporization, by metal separation to be measured out, thereby entering people's mass spectrum measures, by ion specific charge, carry out qualitative analysis, semi-quantitative analysis, the quantitative test of inorganic elements, carry out multiple element and isotopic mensuration simultaneously, there is the detectability lower than atomic absorption method, it is state-of-the-art method in trace element analysis field, but expensive, vulnerable to pollution.

The principle of atomic fluorescence spectrometry (AFS) is that atomic vapour absorbs the optical radiation of certain wavelength and is excited, excited atom is launched the optical radiation of certain wavelength subsequently by excitation process, under certain experiment condition, its radiation intensity is directly proportional to atomic concentration.The features such as atomic fluorescence spectrometry has highly sensitive, and selectivity is strong, and the few and method of sample size is simple; But it is extensive not enough that its weak point is range of application.

Stripping voltammetry claims again reverse stripping polarography, this method is to make tested material, the electrolysis regular hour under the current potential for the treatment of measured ion polarographic analysis generation limiting current, then change the current potential of electrode, make to be enriched in the material stripping again on this electrode, according to resulting volt-ampere curve in process in leaching, carry out quantitative test.The sensitivity of the method is very high, thus in ultrapure material analysis, there is practical value, but affect a lot of because have of Stripping Currents, as enrichment time, stirring rate and electric potential scanning speed etc.

Above method is all the existence that is tested and appraised heavy metal lead and chromium in solution, and then infers chrome Orange content residual in liquid, but in liquid handling process, cannot get rid of other sources of lead, chromium.So, depend merely on the detection of heavy metal lead and chromium and cannot determine that plumbous in liquid, chromium necessarily derives from chrome Orange.And while detecting in order to upper method, need to use a large amount of reagent and carry out pre-treatment, process is loaded down with trivial details, cannot accomplish fast detecting.In addition, at present in chrome Orange wastewater treatment process, the monitoring of remaining chrome Orange rarely seen report also in each flow process.

Summary of the invention

For the deficiencies in the prior art, the invention provides the detection method of chrome Orange concentration in a heavy metal species high alkali liquid body.

The detection method of chrome Orange concentration in one heavy metal species high alkali liquid body, comprising:

(1) using the heavy metal concentrated base liquid of different chrome Orange concentration as test sample book, obtain each test sample book and in setting wave-number range, take the Raman spectrum of silicon chip during as substrate;

(2) according to the Raman spectrum of all test sample books, adopt respectively successive projection algorithm to extract some stack features peak, the quantity at every stack features peak is different, while adopting successive projection algorithm with 520cm ^-1the column vector at place is as initial projection vector;

(3) utilize multi-element linear regression method to determine the checking root-mean-square error at each stack features peak, select a stack features peak of checking root-mean-square error minimum as characteristic fingerprint peak, and using characteristic fingerprint peak as calibration wave number, according to the chrome Orange concentration of each test sample book, and the strong and 520cm in the peak at each calibration wave number place in corresponding Raman spectrum ^-1the first linear regression model (LRM) that the strong ratio in peak at place builds concentration-strength ratio is as calibration model;

Described linear regression model (LRM) is:

Y＝13.82-0.162λ ₁+0.116λ ₂+0.664λ ₃+0.221λ ₄+0.375λ ₅-0.217λ ₆-0.306λ ₇+0.08664λ ₈-0.745λ ₉+0.136λ ₁₀-0.01071λ ₁₁+0.07594λ ₁₂，

Wherein, λ ₁, λ ₂, λ ₃, λ ₄, λ ₅, λ ₆, λ ₇, λ ₈, λ ₉, λ ₁₀, λ ₁₁and λ ₁₂be respectively 2688cm ^-1, 2032cm ^-1, 1417cm ^-1, 1188cm ^-1, 1145cm ^-1, 1102cm ^-1, 1085cm ^-1, 1066cm ^-1, 1056cm ^-1, 849cm ^-1, 515cm ^-1and 152cm ^-1strong and the 520cm in the peak at place ^-1the strong ratio in peak at place;

(4) obtain sample to be tested and in setting wave-number range, take the Raman spectrum of silicon chip during as substrate, calculate the strong and 520cm in the peak at each calibration wave number place in this Raman spectrum ^-1the strong ratio in peak at place, and substitution calibration model calculates the concentration of chrome Orange in sample to be tested.

Raman spectrum is the molecular structure characterization technology of setting up based on Ramam effect, originate from crystal or molecular vibration (and lattice vibration) and rotate, the position of Raman line, intensity and live width can provide the information of molecular vibration, rotation aspect, can realize accordingly " the fingerprint discriminating " of some chemical bond and functional group in molecule.Raman spectrum, as the means of testing of molecular level, is easy to realize the Components identification analysis of COMPLEX MIXED objects system.Rely on and detect the method comparison that belongs to plumbous and chromium element with other, utilize Raman detection can guarantee that lead and the chromium element of test derive from chrome Orange, and then guaranteed the accuracy of the chrome Orange of test, avoided the interference in other sources.

Heavy metal concentrated base liquid of the present invention refers to the NaOH solution of heavy metal more.

Silicon chip in the present invention adopts monocrystalline silicon piece more, and with test sample book surface of contact be polished surface, be conducive to strengthen 520cm ^-1the Raman vibration at place.

In the present invention when successive projection algorithm, by the characteristic peak (520cm of silicon ^-1the peak at place) column vector, as initial projection vector, has been guaranteed when processing large data sample, the uniqueness of result, and the while has also been accelerated the processing speed of data greatly.On the other hand, in modeling process, selected the silicon substrate that does not affect solution structure character, with its characteristic peak as reference, by intensity and the 520cm at each characteristic fingerprint peak of test sample book ^-1the strong ratio in peak at place builds calibration model, can realize the half-quantitative detection of Raman spectrum, has greatly improved the accuracy of test.

Multiple linear regression analysis is for studying dependence between a dependent variable and one group of independent variable, in step (3) according to the result of linear regression analysis, select a stack features peak of root-mean-square error minimum as characteristic fingerprint peak, to calculate the concentration of chrome Orange in sample to be tested, the accuracy that can improve measurement result.

Described step (1) comprises the steps:

(1-1) silicon chip is inserted after container bottom, in container, inject test sample book;

(1-2) container that is marked with test sample book is placed on to the Raman spectrum of testing this test sample book on the objective table of micro-Raman spectroscopy.

Obtain while take the Raman spectrum (Raman spectrum) that silicon chip is substrate, can directly sample evenly be spread upon on silicon chip, then the silicon chip of evenly smearing is placed on to the Raman spectrum of test sample book on the objective table of micro-Raman spectroscopy.But because liquid has mobility, and needed test sample book amount is micro-, and liquid surface exists tension force, directly smears and cannot guarantee the smooth of sample surfaces, easily experiment is impacted.Secondly, adopt while smearing, the amount of the test sample book that very difficult guarantor smears at every turn just equates, thereby has test error.In the present invention, utilize container to hold test sample book, be convenient to test sample book to carry out quantitatively, also can making surfacing, be conducive to reduce the test error causing because of test condition.

In the present invention, be that guaranteed discharge is identical, all container filled with at every turn, then utilize scraper plate along container top surface, unnecessary liquid to be removed.

Conventionally adopt hydrostatic column, corresponding, described silicon chip is circular, and the little 1～2mm of internal diameter of silicon chip diameter container.

While carrying out Raman test, for guaranteeing to collect the Raman vibration of silicon substrate, make silicon chip can cover whole container bottom as far as possible, and try not to scan the point near container edge when test.If when technical conditions allow, can directly Si sheet be welded in to the bottom in container, or adopt the container of silicon materials.

In the present invention, the test condition of Raman test is as follows: testing laser wavelength is 532nm, and testing laser power is 25mv, and the time shutter is 1s, and exposure frequency is 1 time, and gathering aperture is 20 μ m, and object lens are 20 times, and number of scan points is 30.

As preferably, the quantity of test sample book is 50～150.

By the Raman spectrum of some test sample books, be difficult to determine accurately separately the characteristic fingerprint peak of chrome Orange, in the present invention, by large sample is carried out to statistical analysis, can find out accurately chrome Orange and vibrate relevant characteristic fingerprint peak.Conventionally sample number is more, and it is more accurate that characteristic fingerprint peak is judged, but can cause like this calculated amount large, and efficiency is low.Therefore the number needs of test sample book will be considered according to actual conditions, can not be too high, and can not be too low.In addition, for ease of realizing all test sample books, can be divided into some groups (being generally 5～7 groups), the chrome Orange concentration of each group is identical, and the chrome Orange concentration between is not on the same group carried out gradient setting.

As preferably, setting wave-number range is 112.3～2717.2cm ^-1.

In heavy metal concentrated base liquid, the vibration peak relevant to chrome Orange is distributed in this wave-number range, therefore by setting this 112.3～2717.2cm ^-1wave-number range scanning.

In each stack features peak of described step (2), the number of characteristic peak is 5～15.

The group of the characteristic peak that extraction obtains is several to be set according to actual conditions, on the same group in the number of characteristic peak not different, take into account the accuracy of modeling efficiency and the model of model, the number of characteristic peak is set as to 5～15, every group of characteristic peak number comprising is all different.

After building calibration model in described step (3), also comprise renewal calibration wave number and calibration model, the calibration model after renewal is:

Y＝10.208-0.143λ ₁+1.027λ ₃-0.712λ ₉+0.133λ ₁₀-0.01302λ ₁₁+0.06173λ ₁₂。

Update method is as follows:

The first described linear regression model (LRM) is carried out to variance analysis screening calibration wave number, and using the calibration wave number after screening as final calibration wave number, according to the chrome Orange concentration of all test sample books, and the peak at each calibration wave number place after screening is strong and 520cm ^-1the second linear regression model (LRM) that the strong ratio in peak at place builds concentration-strength ratio is as calibration model.

By the first linear regression model (LRM) is carried out to variance analysis, characteristic fingerprint peak is screened, determine and obtain final calibration wave number, further improve the accuracy of calibration model, and then reduce the concentration value of final test and the deviation between actual concentrations value.

In the present invention, do not make specified otherwise, Y all represents the content of chrome Orange in test sample book, and its unit is mg/ml.

Compared with prior art, tool of the present invention has the following advantages:

(1) utilize Raman test to analyze, can guarantee that lead and the chromium element of test derives from chrome Orange, and then guaranteed the accuracy of the chrome Orange of test, avoided the interference in other sources;

(2) utilize silicon chip as substrate, on the one hand, because the detected object of this experiment is liquid, with silicon chip as substrate, the focusing in can conveniently testing; On the other hand, the signal peak of silicon chip is single, mainly at 520cm ^-1place, disturbs few to the signal of test sample book; Meanwhile, with intensity and the 520cm at each characteristic fingerprint peak of test sample book ^-1the strong ratio in peak at place builds calibration model, can realize the half-quantitative detection of Raman spectrum, has greatly improved the accuracy of test;

(3) simple to operate, avoided traditional chrome Orange content measurement extraction, the sample preparation process loaded down with trivial details, consuming time such as clear up, for the concentration of remaining chrome Orange in Real-Time Monitoring chrome Orange wastewater treatment process fast and effeciently provides effective means, have a good application prospect.

Embodiment

Below in conjunction with specific embodiment and comparative example, describe the present invention.

Take respectively 1g, 0.8g, 0.6g, 0.4g, 0.2g chrome Orange in 50ml beaker, with transfer pipet, move into 10mlNaOH strong solution, with glass bar, fully stir and evenly mix, after standing over night, be mixed with the liquid sample of 5 concentration gradients.Each concentration level is got 15 samples, and the total of 5 concentration gradients obtains 75 test sample books.

Embodiment 1

The detection method of chrome Orange concentration in one heavy metal species high alkali liquid body, comprising:

(1) using the heavy metal concentrated base liquid of different chrome Orange concentration as test sample book, obtain each test sample book at 2717.2cm ^-1～112.3cm ^-1take the Raman spectrum of silicon chip during as substrate in wave-number range.

In the present embodiment, adopt the 96 flat double dish in hole (aperture: 6.4mm, floorages: 0.32cm ², volume is 0.36ml) and as container, a hole is as a container.It is 5mm that a diameter is placed in the bottom in every hole first, thickness is the circular silicon chip of 0.5mm, with transfer pipet, pipettes 0.4ml liquid in double dish hole, with scraper plate, along double dish edge, unnecessary liquid is removed, then double dish is placed on glass sheet, stand-by.

The container that fills test sample book is placed on to the Raman spectrum of testing each test sample book on the objective table of micro-Raman spectroscopy.The test condition of each sample is identical, all as follows:

Testing laser wavelength is 532nm, and testing laser power is 25mv, and the time shutter is 1s, and exposure frequency is 1 time, and gathering aperture is 20 μ m, and object lens are 20 times, and number of scan points is 30.

(2) according to the Raman spectrum of all test sample books, adopt respectively successive projection algorithm to extract some stack features peak, the quantity at every stack features peak is different, while adopting successive projection algorithm with 520cm ^-1the column vector at place is as initial projection vector;

According to the number K of the number M of test sample book (M=75 in the present embodiment) and wave number, forming size is the spectrum matrix X of M * K, the element x in spectrum matrix X _ijbe i test sample book at the intensity level of the Raman peaks at j wave number place, wave number corresponding to j=1 wave number is maximum, reduces backward successively.

Successive projection algorithm (SPA algorithm) is a kind of forward direction circulation system of selection, one row group corresponding to its any one wavelength from spectrum matrix X starts as projection vector, each circulation, calculate the projection of this projection vector on vector corresponding to the wavelength not being selected into, again the wavelength of the mould maximum of projection vector is incorporated into wavelength combinations, until circulation N time.The wavelength being newly selected into each time, all minimum with previous linear relationship.

In the present embodiment, need to extract altogether 11 stack features peaks, the number of the characteristic peak that each stack features peak comprises is respectively 5,6 ... 15.For each stack features peak, all adopt SPA method to extract, the number of remembering every stack features peak is N, and SPA method comprises the steps:

(2-1) initialization: n=1 (iteration for the first time), 520cm in spectrum matrix X ^-1corresponding element forms a column vector as projection vector, and initial projection vector, is designated as X _{k (0)}(be j=k (0), and k (0) wave number is 520cm ^-1);

(2-2) S set is defined as: $S=\{j,1\&le;j\&le;K,j\&NotElement;\{k\left(0\right),...,k(n-1)\left\}\right\},$ The i.e. column vector of not selected afferent echo long-chain also, wherein, k (n-1) represents the column vector at the maximal projection place that the n time iteration elected, according to formula:

Px _j＝x _j-(x _j ^Tx _k(n-1))x _k(n-1)(x ^T _k(n-1)x _k(n-1)) ^-1，

Calculate respectively X _jprojection in S set in column vector corresponding to each wave number, and according to formula:

k(n)＝arg(max||Px _j||，j∈S)

Determine the value of the j of projection maximum, and be designated as k (n), wherein || Px _j|| for projection vector is at X _jon the mould of projection;

If (2-3) n<N, makes n=n+1, and return to step (2-1), and with X _{k (n)}as initial projection vector, otherwise stop, and using wave number corresponding to each maximal projection as the position at characteristic peak place, and then obtain except 520cm ^-1a stack features peak that comprises in addition N characteristic peak outward.

(3) respectively N characteristic peak of each group set up to linear regression model (LRM), by multi-element linear regression method, judge the quality of institute's established model, select a stack features peak of minimum RMSEP as characteristic fingerprint peak.Using the characteristic fingerprint peak selected as calibration wave number, according to the chrome Orange concentration of each test sample book, and the strong and 520cm in the peak at each calibration wave number place in corresponding Raman spectrum ^-1the first linear regression model (LRM) that the strong ratio in peak at place builds concentration-strength ratio is as calibration model;

The first linear regression model (LRM) obtaining in the present embodiment is:

Y＝13.82-0.162λ ₁+0.116λ ₂+0.664λ ₃+0.221λ ₄+0.375λ ₅-0.217λ ₆-0.306λ ₇+0.08664λ ₈-0.745λ ₉+0.136λ ₁₀-0.01071λ ₁₁+0.07594λ ₁₂

Wherein, λ ₁, λ ₂, λ ₃, λ ₄, λ ₅, λ ₆, λ ₇, λ ₈, λ ₉, λ ₁₀, λ ₁₁and λ ₁₂be respectively 2688cm ^-1, 2032cm ^-1, 1417cm ^-1, 1188cm ^-1, 1145cm ^-1, 1102cm ^-1, 1085cm ^-1, 1066cm ^-1, 1056cm ^-1, 849cm ^-1, 515cm ^-1and 152cm ^-1strong and the 520cm in the peak at place ^-1the strong ratio in peak at place;

(4) obtain sample to be tested and in setting wave-number range, take the Raman spectrum of silicon chip during as substrate, calculate the strong and 520cm in the peak at each calibration wave number place in this Raman spectrum ^-1the strong ratio in peak at place, and substitution calibration model calculates the concentration of chrome Orange in sample to be tested.

Utilize calibration model as shown in table 1 to predicting the outcome of the chrome Orange concentration of these 25 samples to be tested, the related coefficient of model is 0.973043, and root-mean-square error is 6.936540.Illustrate that this model can realize effective detection of chrome Orange concentration in concentrated NaOH solution.

Table 1

Embodiment 2

Identical with embodiment 1, difference is also to comprise renewal calibration wave number and calibration model after building calibration model in step (3), and update method is as follows:

The first linear regression model (LRM) is carried out to variance analysis screening calibration wave number, and using the calibration wave number after screening as final calibration wave number, and according to the chrome Orange concentration of all test sample books, and the peak at each calibration wave number place after screening in Raman spectrum is strong and 520cm ^-1the second linear regression model (LRM) that the strong ratio in peak at place builds concentration-strength ratio is as the calibration model after upgrading.

Calibration model is carried out to variance analysis, and result is as shown in table 2

Table 2

Table 2 disclosing solution number variable λ ₂₀₃₂, λ ₁₁₈₈, λ ₁₁₄₅, λ ₁₁₀₂, λ ₁₀₈₅, λ ₁₀₆₆(sample is at wave number 2032cm ^-1, 1188cm ^-1, 1145cm ^-1, 1102cm ^-1, 1085cm ^-1, 1066cm ^-1the raman spectrum strength at place) level of signifiance P>0.05, shows wave number variable λ ₂₀₃₂, λ ₁₁₈₈, λ ₁₁₄₅, λ ₁₁₀₂, λ ₁₀₈₅, λ ₁₀₆₆with dependent variable Y (concentration of chrome Orange in concentrated base liquid) without significant correlation, therefore wave number 2032cm ^-1, 1188cm ^-1, 1145cm ^-1, 1102cm ^-1, 1085cm ^-1, 1066cm ^-1be not suitable for for setting up the measurement model of chrome Orange concentration in heavy metal concentrated base liquid.Finally be left 2688cm ^-1, 1417cm ^-1, 1056cm ^-1, 849cm ^-1, 515cm ^-1, 152cm ^-1six wave numbers are as final calibration wave number, and re-establish linear regression model (LRM) as the calibration model after upgrading according to this this six calibration wave numbers.

In the present embodiment, the calibration model after renewal is:

Y＝10.208-0.143λ ₁+1.027λ ₃-0.712λ ₉+0.133λ ₁₀-0.01302λ ₁₁+0.06173λ ₁₂。

Utilize the calibration model after upgrading as shown in table 3 to predicting the outcome of the chrome Orange concentration of these 25 samples to be tested, the related coefficient of model is 0.967918, and root-mean-square error is 7.890795.Illustrate that this model can realize effective detection of chrome Orange concentration in concentrated NaOH solution.

Table 3

Comparative example

Choose contiguous six wavelength and be respectively 647nm, 785nm, 1085nm, 1188nm, 1417nm, 1806m, sets up for measuring the calibration model of heavy metal concentrated base liquid chrome Orange concentration based on these six wavelength:

Y＝-29.787+0.09762λ ₁₈₀₆/λ ₅₂₀+0.333λ ₁₄₁₇/λ ₅₂₀-0.289λ ₁₁₈₈/λ ₅₂₀-1.039λ ₁₀₈₅/λ ₅₂₀+3.038λ ₇₈₅/λ ₅₂₀-1.990λ ₆₄₇/λ ₅₂₀。

Utilize detected value and the actual value of chrome Orange concentration in the sample heavy metal concentrated base liquid that this calibration model calculates as shown in table 4, the prediction related coefficient of this calibration model is 0.816487, and successful is worse than the prediction related coefficient 0.967918 of institute of the present invention extracting method.

Table 4

Above-described embodiment has been described in detail technical scheme of the present invention and beneficial effect; be understood that and the foregoing is only most preferred embodiment of the present invention; be not limited to the present invention; all any modifications of making within the scope of principle of the present invention, supplement and be equal to replacement etc., within all should being included in protection scope of the present invention.

Claims (8)

1. the detection method of chrome Orange concentration in a heavy metal species high alkali liquid body, is characterized in that, comprising:

(1) using the heavy metal concentrated base liquid of different chrome Orange concentration as test sample book, obtain each test sample book and in setting wave-number range, take the Raman spectrum of silicon chip during as substrate;

(2) according to the Raman spectrum of all test sample books, adopt respectively successive projection algorithm to extract some stack features peak, the quantity at every stack features peak is different, while adopting successive projection algorithm with 520cm ^-1the column vector at place is as initial projection vector;

(3) utilize multi-element linear regression method to determine the checking root-mean-square error at each stack features peak, select a stack features peak of checking root-mean-square error minimum as characteristic fingerprint peak, and using characteristic fingerprint peak as calibration wave number, according to the chrome Orange concentration of each test sample book, and the strong and 520cm in the peak at each calibration wave number place in corresponding Raman spectrum ^-1the first linear regression model (LRM) that the strong ratio in peak at place builds concentration-strength ratio is as calibration model;

Described linear regression model (LRM) is:

Y＝13.82-0.162λ ₁+0.116λ ₂+0.664λ ₃+0.221λ ₄+0.375λ ₅-0.217λ ₆-0.306λ ₇+0.08664λ ₈-0.745λ ₉+0.136λ ₁₀-0.01071λ ₁₁+0.07594λ ₁₂，

Wherein, λ ₁, λ ₂, λ ₃, λ ₄, λ ₅, λ ₆, λ ₇, λ ₈, λ ₉, λ ₁₀, λ ₁₁and λ ₁₂be respectively 2688cm ^-1, 2032cm ^-1, 1417cm ^-1, 1188cm ^-1, 1145cm ^-1, 1102cm ^-1, 1085cm ^-1, 1066cm ^-1, 1056cm ^-1, 849cm ^-1, 515cm ^-1and 152cm ^-1strong and the 520cm in the peak at place ^-1the strong ratio in peak at place;

(4) obtain sample to be tested and in setting wave-number range, take the Raman spectrum of silicon chip during as substrate, calculate the strong and 520cm in the peak at each calibration wave number place in this Raman spectrum ^-1the strong ratio in peak at place, and substitution calibration model calculates the concentration of chrome Orange in sample to be tested.

2. the detection method of chrome Orange concentration in heavy metal concentrated base liquid as claimed in claim 1, is characterized in that, described step (1) comprises the steps:

(1-1) silicon chip is inserted after container bottom, in container, inject test sample book;

(1-2) container that is marked with test sample book is placed on to the Raman spectrum of testing this test sample book on the objective table of micro-Raman spectroscopy.

3. the detection method of chrome Orange concentration in heavy metal concentrated base liquid as claimed in claim 2, is characterized in that, described silicon chip is circular, and the little 1～2mm of internal diameter of silicon chip diameter container.

4. the detection method of chrome Orange concentration in heavy metal concentrated base liquid as claimed in claim 1, is characterized in that, the quantity of test sample book is 50～150.

5. the detection method of chrome Orange concentration in heavy metal concentrated base liquid as claimed in claim 1, is characterized in that, setting wave-number range is 112.3～2717.2cm ^-1.

6. the detection method of chrome Orange concentration in heavy metal concentrated base liquid as claimed in claim 1, is characterized in that, in each stack features peak of described step (2), the number of characteristic peak is 5～15.

7. the detection method of chrome Orange concentration in the heavy metal concentrated base liquid as described in any one claim in claim 1～6, it is characterized in that, after building calibration model in described step (3), also comprise renewal calibration wave number and calibration model, the calibration model after renewal is:

Y＝10.208-0.143λ ₁+1.027λ ₃-0.712λ ₉+0.133λ ₁₀-0.01302λ ₁₁+0.06173λ ₁₂。

8. the detection method of chrome Orange concentration in heavy metal concentrated base liquid as claimed in claim 7, is characterized in that, update method is as follows:

The first described linear regression model (LRM) is carried out to variance analysis screening calibration wave number, and using the calibration wave number after screening as final calibration wave number, according to the chrome Orange concentration of all test sample books, and the peak at each calibration wave number place after screening is strong and 520cm ^-1the second linear regression model (LRM) that the strong ratio in peak at place builds concentration-strength ratio is as calibration model.