CN109975262A - One kind optimizing full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method - Google Patents
One kind optimizing full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method Download PDFInfo
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Abstract
The invention discloses one kind to optimize full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method, is related to water quality inspection technique field, step includes, step 1: the building of the water sample classification method based on three-dimensional fluorescence domain integral method；Step 2: carrying out the building of COD monitoring model respectively for every a kind of acquisition water sample.Those skilled in the art is dedicated to developing the COD monitoring method of the water outlet of a kind of pair of natural environment and sewage treatment facility, and precision is higher, and adaptability is good, and on-line monitoring method without secondary pollution.
Description
Technical field
The present invention relates to water quality inspection technique fields, more particularly to a kind of three-dimensional fluorescence domain integral method that is based on to optimize full light
Spectrum monitoring COD method.
Background technique
With the continuous development of environmental protection requirement, the water drain of water body is can be realized to natural environment water body and is discharged into
The demand that matter is quickly monitored on-line is increasingly urgent to.Water chemical oxygen demand (ChemicalOxygenDemand, COD) is anti-
Reflect the important parameter of quality of water environment.The on-line monitoring technique for studying COD protects water environment for controlling, administer water pollution,
There is extremely important meaning.
Currently, water-quality COD monitoring in China's mainly acquires water sample by artificial, using laboratory chemical analysis as primary hand
Section since chemical method resolution sample needs the regular hour, and contains the heavy metals such as silver ion, chromium ion in digestion agent,
Secondary pollution is caused, detection cycle is long, and complicated for operation frequent, needs the experimenter of profession.Laboratory chemical analysis
Method is offline inspection, can not promptly and accurately reflect water pollution situation, lose validity, oneself, which is unable to satisfy, exists to water quality detection
The requirement of line, real-time.China's most of water-quality COD monitoring instruments used at present also substantially belong to chemical analysis,
It is period length, high failure rate, expensive, modernization environment measuring technical requirements can not be adapted to.
In recent years, the ultravioletvisible spectroscopy as one of the water quality inspection technique of spectrum analysis, compared to chemical method,
It has many advantages, such as.For example, without secondary pollution, the period is short without adding digestion agent, operates, is easy to maintain, it is at low cost,
Online, in situ measurement may be implemented.Compared with traditional method, ultravioletvisible spectroscopy water-quality COD detection technique has obvious
Advantage, be one of the main direction of development of modern water quality detection, to various water bodies such as surface water, sanitary sewage, industrial wastewaters
On-line checking have great importance.
The forecasting problem of water quality parameter detection, people constantly carry out research all the time, to improve the essence of prediction
Exactness and applicability, difficult point specifically include that
Traditional analysis method is compared, though ultravioletvisible spectroscopy has very big advantage, be not yet it is perfect in every way,
Also there is limitation.Theoretically, sewage without phenyl ring or unsaturated double-bond is insensitive to ultraviolet light therefore ultraviolet-and it can
Light-exposed spectrometry can fail.Moreover the reducing substances in water quality refer not only to organic matter, go back organic/inorganic substance.
The water sample of nature, when by polluting, the pollutant component in pollution sources is extremely complex, is carrying out water-quality COD
When modeling, in order to guarantee the accuracy of prediction model, need a large amount of data volume to improve entire prediction model, therefore, into
When the COD measurement of row complexity water sample, former prediction model is it is possible that deviation, and this respect needs further to improve and development.
Three-dimensional excitation-transmitting fluorescence spectroscopy technique can be to the overlapping object progress spectrum of fluorescence spectrum in multicomponent system
Identification and characterization, fluorescence spectrum sensitivity is 10-1000 times of Conventional UV-visible spectrum, can be to trace organic substance in water body
It is adequately identified and is parsed.Three-dimensional fluorescence spectrum is the collection of fluorescence intensity under the conditions of excitation, launch wavelength in a certain range
It closes, organic pollutant fluorescence information rich in.Peak-seeking method is more universal spectroscopic analysis methods, it be will have it is specific
It excites, the fluorophor of launch wavelength range is classified, it is generally recognized that different types of organic matter has its specific fluorescence
Dissolved organic matter (DOM) each component can be divided into according to the position of fluorescence peak in group, such as water body: humic acids are (visible, purple
Outside), tryptophan class, tyrosine class etc..A large number of studies show that three-dimensional fluorescence spectrum technology can be applied successfully to environment water
The identification and parsing of middle dissolved organic matter (DOM), relatively broadly for the monitoring of water bodys such as river, lake, underground water,
Water quality assessment etc..But since fluorescence peak is usually to be made of several fluorophors being overlapped mutually, some peaks may nothing
Method identification, some peaks may identify inaccuracy；In addition, peak-seeking method only considers the specific peaks in three-dimensional spectrum, a large amount of fluorescence numbers
According to not being fully used.Three-dimensional fluorescence domain integral method can effectively locate all spectroscopic datas of three-dimensional fluorescence
Reason, make full use of fluorescence data, extract effective fluorescence spectral characteristic, can the property to sewage comprehensively characterized.
Therefore, those skilled in the art is dedicated to developing the water outlet of a kind of pair of natural environment and sewage treatment facility
COD monitoring method, precision is higher, and adaptability is good, on-line monitoring method without secondary pollution.
Summary of the invention
In view of the above drawbacks of the prior art, the technical problem to be solved by the present invention is to national standard monitoring methods
Portion of reagent is poisonous and harmful, easily causes secondary pollution, and operating cost is higher；It tests and analyzes and needs certain reaction time can not be
Line monitoring；Though and ultravioletvisible spectroscopy detection COD can be with on-line real time monitoring, precision is low, applicability is also poor.
To achieve the above object, the present invention provides optimize the full spectrum monitoring side COD based on three-dimensional fluorescence domain integral method
Method, comprising the following steps:
Step 1: the building of the water sample classification method based on three-dimensional fluorescence domain integral method
The 1.1 multiple water samples of acquisition, are filtered the acquisition water sample with filter membrane；
1.2, which carry out three-dimensional fluorescence to blank water sample and the filtered acquisition water sample using sepectrophotofluorometer, swashs
Hair-emission matrix (EEM) measurement；
1.3 subtract the filtered acquisition water sample three-dimensional fluorescence EEM data three-dimensional fluorescence EEM of the blank water sample
Then data cut off Rayleigh scattering and Raman scattering by MATLAB software, obtain revised three-dimensional fluorescence EEM data；
1.4 carry out area to the revised three-dimensional fluorescence EEM data that the step 1.3 obtains using Origin13.0
Data area is divided into five regions, respectively by volume integrationRepresent aromatic series protein,Represent aromatic series egg
White matter,Represent fulvic acid class material,Represent dissolubility microbial metabolic products, Represent humic acids
Substance；
1.5 by the step 1.3 to the revised three-dimensional fluorescence EEM data divided in the step 1.4
Five regions carry out Domain Volume calculus, and calculate each Domain Volume integral and accounted in total volume integral
Than the relative amount of each Regional Representative's substance in that is, each acquisition water sample；
1.6 is different according to the accounting of substances described in every class in each acquisition water sample, using R language correlation analysis packet,
Classify to the acquisition water sample, using clustering algorithm, the acquisition water sample is divided into three classes；
Step 2: carrying out the building of COD monitoring model respectively for every a kind of acquisition water sample
2.1 use national standard monitoring method measurement filtering after it is described acquisition water sample COD value for COD measured value；
2.2 carry out purple to the blank water sample and the filtered acquisition water sample using ultraviolet-visible spectrophotometer
Outside-visible spectrum measurement obtains spectroscopic data；
2.3 subtract the spectroscopic data of the blank water sample, the light that will be obtained with the spectroscopic data of the acquisition water sample
Modal data is smoothed, the spectroscopic data that obtains that treated；
The 2.4 acquisition water samples classified according to the step 1.6, every one kind acquisition water sample choose 80% sample
This, Partial Least Squares is respectively adopted, selects suitable number of principal components, with it is described acquisition water sample the COD measured value and its
Treated, and the spectroscopic data is that every one kind acquisition water sample constructs COD prediction model respectively and obtains COD prediction
Value；
Remaining 20% samples of 2.5 every one kind acquisition water sample, its described COD measured value and the COD predicted value it
Between R squares of examination collection evaluated, the predictive ability of model is verified, to ensure the practicability of model.
Further, the filter sizes are 0.45um.
Further, the blank water sample is Milli-Q water.
Further, the sepectrophotofluorometer is Hitachi F-7000 sepectrophotofluorometer.
Further, the sepectrophotofluorometer scanning wavelength range is 200nm-600nm.
Further, five region division ranges are,For Ex < 250nm and Em < 330nm, (Ex- excitation wave
Long, Em- is launch wavelength),For Ex < 250nm and 330 < Em < 380nm,For Ex<250nm and Em>380nm,For Ex>250nm and Em<380nm,For Ex > 250nm and Em > 380nm.
Further, the clustering algorithm is K- means clustering algorithm.
Further, the ultraviolet-visible spectrophotometer is Hash DR6000 ultraviolet-visible spectrophotometer.
Further, the smoothing processing is S-G smoothing processing.
Further, the number of principal components is 3-5.
The present invention provide it is a kind of at least had based on three-dimensional fluorescence domain integral method optimization full spectrum monitoring COD method it is following
Beneficial technical effect:
1, the present invention realizes the optimization to full spectrum monitoring COD method, and precision is higher, better adaptability.
2, the present invention has many advantages, such as to monitor quickly, without chemical reagent consumption.
It is described further below with reference to technical effect of the attached drawing to design of the invention, specific structure and generation, with
It is fully understood from the purpose of the present invention, feature and effect.
Detailed description of the invention
Fig. 1 is that one kind of a preferred embodiment of the invention is based on three-dimensional fluorescence domain integral method optimization full spectrum monitoring
The three-dimensional fluorescence zoning plan of COD method.
Specific embodiment
A preferred embodiment of the present invention is introduced below with reference to Figure of description, keeps its technology contents more clear and just
In understanding.The present invention can be emerged from by many various forms of embodiments, and protection scope of the present invention not only limits
The embodiment that Yu Wenzhong is mentioned.
It is as follows based on three-dimensional fluorescence domain integral method full spectrum monitoring COD method in the present embodiment:
Step 1: the building of the water sample classification method based on three-dimensional fluorescence domain integral method
1.1 200 water samples of acquisition are filtered acquisition water sample with the filter membrane in the aperture 0.45um；
1.2 use Hitachi's F-7000 sepectrophotofluorometer to using Milli-Q water as blank water sample and filtered acquisition
Water sample carries out three-dimensional fluorescence Excitation-emission matrix (EEM) measurement, and excitation light source is 150W xenon arc lamp, and scanning wavelength range is
200-600nm, slit width 5nm, sweep bandwidth 5nm, scanning speed 12000nm/min, PMT voltage 400V, letter
It makes an uproar ratio > 110, the response time is automatic；
1.3 subtract the three-dimensional fluorescence EEM data of acquired water sample the three-dimensional fluorescence EEM data of blank water sample, then borrow
MATLAB13.0 software excision Rayleigh scattering and Raman scattering are helped, revised three-dimensional fluorescence EEM data are obtained；
1.4 carry out region product to the revised three-dimensional fluorescence EEM data that the step 1.3 obtains using Origin13.0
Point, data area is divided into five regions, as shown in Figure 1, being respectivelyRepresent aromatic series protein Ex < 250nm and Em <
330nm、Represent aromatic series protein Ex < 250nm and 330 < Em < 380nm,Represent fulvic acid class material Ex <
250nm and Em > 380nm,Represent dissolubility microbial metabolic products Ex>250nm and Em<380nm,Represent corruption
Grow acid Ex > 250nm and Em > 380nm；
1.5 by step 1.3 to revised three-dimensional fluorescence EEM data five regions that step 1.4 is divided into
Row Domain Volume calculus, and calculate each Domain Volume integral accounting in total volume integral, i.e., in each acquisition water sample
The relative amount of each Regional Representative's substance；
1.6 is different according to the accounting of every substance in each acquisition water sample, using R language correlation analysis packet, adopt to described
Collection water sample is classified, and using K- means clustering algorithm, acquisition water sample is divided into three classes, first kind water sample is 46, the second class
Water sample is 84, and third class water sample is 70；
Step 2: carrying out the building of COD monitoring model respectively for every a kind of acquisition water sample
2.1 use national standard monitoring method measurement filtering after acquire water sample COD value for COD measured value；
2.2 use Hash DR6000 ultraviolet-visible spectrophotometer to blank water sample Milli-Q water and filtered acquisition
Water sample carries out ultraviolet-visible spectrum measurement and obtains spectroscopic data；
2.3 subtract the spectroscopic data of blank water sample with the spectroscopic data of acquisition water sample, and obtained spectroscopic data is carried out S-G
Smoothing processing, the spectroscopic data that obtains that treated；
2.4 acquire the classification of water sample according to step 1.6 pair, 80% sample are chosen in every a kind of acquisition water sample, using inclined
Least square method selects number of principal components 3-5 according to different classifications, the COD measured value with acquisition water sample and its treated spectrum
Data are that every a kind of acquisition water sample constructs COD prediction model respectively and obtains COD predicted value；
2.5 every a kind of remaining 20% samples of acquisition water sample, R squares of examination collection carries out between COD measured value and COD predicted value
Evaluation, the first, second and third class water sample R square value that K- means clustering algorithm obtains is respectively 0.931,0.925,0.924.With reference to
Step 2 using all 200 acquisition water samples as one kind, therefrom select 80% sample data building model, obtain without
Classify building COD prediction model, with residue 20% sample COD measured value and its COD predictor calculation R square value be
0.893。
From embodiment data it can be concluded that the predicted value effect that the COD model modeled after classification obtains is better than non-classified structure
The COD model predication value built.
The preferred embodiment of the present invention has been described in detail above.It should be appreciated that the ordinary skill of this field is without wound
The property made labour, which according to the present invention can conceive, makes many modifications and variations.Therefore, all technician in the art
Pass through the available technology of logical analysis, reasoning, or a limited experiment on the basis of existing technology under this invention's idea
Scheme, all should be within the scope of protection determined by the claims.
Claims (10)
1. one kind optimizes full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method, which is characterized in that including following step
It is rapid:
Step 1: the building of the water sample classification method based on three-dimensional fluorescence domain integral method
The 1.1 multiple water samples of acquisition, are filtered the acquisition water sample with filter membrane；
1.2 carry out three-dimensional fluorescence excitation-hair to blank water sample and the filtered acquisition water sample using sepectrophotofluorometer
Penetrate matrix (EEM) measurement；
1.3 subtract the filtered acquisition water sample three-dimensional fluorescence EEM data three-dimensional fluorescence EEM number of the blank water sample
According to then cutting off Rayleigh scattering and Raman scattering by MATLAB software, obtain revised three-dimensional fluorescence EEM data；
1.4 carry out region product to the revised three-dimensional fluorescence EEM data that the step 1.3 obtains using Origin13.0
Point, data area is divided into five regions, respectively regionRepresent aromatic series protein, regionRepresent aromatic series protein,
RegionRepresent fulvic acid class material, regionRepresent dissolubility microbial metabolic products, regionRepresent humic acid material；
1.5 by the step 1.3 to the institute that is divided in the step 1.4 of the revised three-dimensional fluorescence EEM data
It states five regions and carries out Domain Volume calculus, and calculate each Domain Volume integral accounting in total volume integral,
The relative amount of each every substance of Regional Representative in i.e. each acquisition water sample；
The accounting of 1.6 substances according to every class in each acquisition water sample is different, using R language correlation analysis packet, to institute
It states acquisition water sample to classify, using clustering algorithm, the acquisition water sample is divided into three classes；
Step 2: carrying out the building of COD monitoring model respectively for every a kind of acquisition water sample
2.1 use national standard monitoring method measurement filtering after it is described acquisition water sample COD value for COD measured value；
2.2 using ultraviolet-visible spectrophotometers it is ultraviolet to the blank water sample and the progress of the filtered acquisition water sample-can
See that spectroscopic assay obtains spectroscopic data；
2.3 subtract the spectroscopic data of the blank water sample, the spectrum number that will be obtained with the spectroscopic data of the acquisition water sample
According to being smoothed, the spectroscopic data that obtains that treated；
The 2.4 acquisition water samples classified according to the step 1.6, every one kind acquisition water sample choose 80% sample, point
Not Cai Yong Partial Least Squares, select suitable number of principal components, with it is described acquisition water sample the COD measured value and its processing after
The spectroscopic data be every one kind acquisition water sample construct COD prediction model respectively and obtain COD predicted value；
2.5 every remaining 20% samples of one kind acquisition water sample are flat R between its described COD measured value and the COD predicted value
Side's examination collection is evaluated, and the predictive ability of model is verified, to ensure the practicability of model.
2. optimizing full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method as described in claim 1, feature exists
In in the step 1.1, the filter sizes are 0.45um.
3. optimizing full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method as described in claim 1, feature exists
In in the step 1.2, the blank water sample is Milli-Q water.
4. optimizing full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method as described in claim 1, feature exists
In in the step 1.2, the sepectrophotofluorometer is Hitachi F-7000 sepectrophotofluorometer.
5. optimizing full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method as described in claim 1, feature exists
In in the step 1.2, the sepectrophotofluorometer scanning wavelength range is 200nm-600nm.
6. optimizing full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method as described in claim 1, feature exists
In in the step 1.4, five region division ranges are regionFor Ex < 250nm and Em < 330nm, (Ex- excitation wave
Long, Em- is launch wavelength), regionFor Ex < 250nm and 330 < Em < 380nm, regionFor Ex<250nm and Em>380nm, area
DomainFor Ex>250nm and Em<380nm, regionFor Ex > 250nm and Em > 380nm.
7. optimizing full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method as described in claim 1, feature exists
In in the step 1.6, the clustering algorithm is K- means clustering algorithm.
8. optimizing full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method as described in claim 1, feature exists
In in the step 2.2, the ultraviolet-visible spectrophotometer is Hash DR6000 ultraviolet-visible spectrophotometer.
9. optimizing full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method as described in claim 1, feature exists
In in the step 2.3, the smoothing processing is S-G smoothing processing.
10. optimizing full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method as described in claim 1, feature exists
In in the step 2.4, the number of principal components is 3-5.
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| CN111982878A (en) * | 2020-08-24 | 2020-11-24 | 安徽思环科技有限公司 | Water pollution analysis method based on ultraviolet visible spectrum and three-dimensional fluorescence spectrum |
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| CN114460055A (en) * | 2022-02-14 | 2022-05-10 | 上海交通大学 | Method and device for monitoring COD (chemical oxygen demand) by using clustering-regression-based spectroscopy |
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| CN113916847B (en) * | 2021-07-20 | 2024-04-09 | 江苏省扬州环境监测中心 | Water quality detection method based on spectrum technology and linear support vector algorithm |
| CN114136900A (en) * | 2021-11-03 | 2022-03-04 | 江苏省扬州环境监测中心 | Water quality detection method combining ultraviolet visible light absorption spectrum technology |
| CN114136900B (en) * | 2021-11-03 | 2024-04-09 | 江苏省扬州环境监测中心 | Water quality detection method combining ultraviolet and visible light absorption spectrum technology |
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| CN115598317A (en) * | 2022-10-24 | 2023-01-13 | 哈尔滨工业大学（Cn） | Method for monitoring chemical oxygen demand concentration in water by utilizing dissolved organic matter components and spectral index |
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