CN109142296A - The black smelly quick identification measuring method of urban water-body based on multi-source optical spectrum feature - Google Patents
The black smelly quick identification measuring method of urban water-body based on multi-source optical spectrum feature Download PDFInfo
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Abstract
The invention discloses the black and odorous waters based on multi-source characteristic spectrum quickly to identify measuring method.Water body humic acid, albuminoid, the black smelly precursor organic concentration of oils are parsed using three-dimensional fluorescence spectrum, it is parsed using uv-visible absorption spectra and obtains turbidity, coloration, the black smelly correlation water parameter of nitrate, obtain COD, BOD, TOC water quality overall target using adsorption and fluorescence spectra fusion inverting;In conjunction with dissolved oxygen and water temperature parameters, is tested by a large amount of different type in city water bodys and training, black and odorous water level measurement algorithm model of the foundation based on data-driven realize that black and odorous water grade quickly identifies measurement.The method overcome " monitoring index is single, organic indicator lacks, ammonia nitrogen needs sampling-off-line measurement " problems existing for " city black and odorous water renovation guide " regulation black and odorous water monitoring method, and it is the agent that has the characteristics that be excused from an examination, quick without sample pretreatment, measurement, it is quickly and effectively black and odorous water measurement means.
Description
Technical field
The present invention relates to resource and environments, city environmental protection technical field, more particularly to based on multi-source optical spectrum feature
The black smelly quick identification measuring method of urban water-body.
Background technique
Black and odorous water, which refers to, to be presented unpleasant color and (or) distributes the water body for making us foreign odor.Black and odorous water is
The extreme phenomenon of organic contamination, when a large amount of organic pollutants enter water body, in a large amount of oxygen of biochemical action consumption of aerobic microbiological
Gas, causes water hypoxia, anaerobic bacteria mass propagation, and organic matter anaerobic degradation is ammonia nitrogen, humus, hydrogen sulfide, methane and sulphur
Alcohol etc. leads to water body blackening, fouls.Since different black and odorous water ingredients are not quite similar, complex genesis, so far both at home and abroad still
Without deterministic evaluation method and standard, also without deterministic black smelly Judging index and monitoring method.
Conventional black smelly monitoring method is divided into following three classes: first, sensory experience method, using human visual, olfactory organoleptic with
Water body chroma and stink are index, by water body be divided into without it is black it is smelly, duskiness is smelly, black smelly 4 grades of black smelly and depth, this method letter
It is single direct, but influenced by personal sensor difference and subjective factor.Second, pollutant concentration limit value method chooses transparency, dissolution
4 oxygen, oxidation-reduction potential and ammonia nitrogen indexs are determined as that corresponding grade is black smelly when any index concentration reaches limit value.It is listed
In index, in addition to ammonia nitrogen index, other water quality parameters have mature live sensor apparatus, therefore this method is simple and easy, suitable
Large area generaI investigation is closed, is " city black and odorous water renovation guide " specified black and odorous water monitoring method, but due to " monitoring index
Single, ammonia nitrogen sampling-off-line measurement, organic matter overall target missing " also strongly limits this method and differentiates black and odorous water
Accuracy.Third, comprehensive assessment, by comprehensive monitoring water temperature, dissolved oxygen, COD, BOD, total
Phosphorus, total nitrogen, ammonia nitrogen and inorganic metal ion introduce multiple-factor Weighted Index and evaluate black and odorous water grade.This method Comprehensive
The smelly environmental factor of water body blackening, evaluation black and odorous water degree that can be more accurate, but need to employ specialized laboratory's analysis
Equipment, it is measurement period length, heavy workload, at high cost, it is difficult to meet the quick monitoring requirements of black and odorous water of China's substantial amounts.
Compared with conventional ground monitoring means, in recent years, black and odorous water remote sensing monitoring technology is received significant attention.Remote sensing hand
Section identifies black and odorous water according to water body chroma index, and the spatial distribution characteristic of black and odorous water can be presented, and has dynamic, fast
The features such as speed, a wide range of monitoring, but remote sensing image optical characteristics is limited, can monitor " black " and be difficult to perceive " smelly ", limitation
It is also apparent from.Therefore, it is to grasp black and odorous water generation, development and evolution process in time, quickly, comprehensively, is badly in need of development scene fastly
Fast black and odorous water identifies measuring method, provides effective technology hand for grasp black and odorous water inventory and black smelly renovation decision in time
Section.
Summary of the invention
The object of the invention is to remedy the disadvantages of known techniques, and it is black to provide the urban water-body based on multi-source optical spectrum feature
Smelly quick identification measuring method.
The present invention is achieved by the following technical solutions:
The black smelly quick identification measuring method of urban water-body based on multi-source optical spectrum feature, comprising the following steps:
(1) using three-dimensional fluorescence spectrum parsing obtain water body humic acid in black smelly precursor, albuminoid, oils concentration;Utilize purple
Outside-visible absorption spectra parsing obtains turbidity, coloration, the nitrate parameter value of black smelly correlation water;Using fluorescence spectrum and inhale
It receives spectrum fusion inverting and obtains COD, BOD, TOC water quality overall target, and integrated dissolved oxygen and water temperature parameters;
(2) comparison sensory experience method water body blacks and smelly index, selects the blackening factor from These parameters by clustering
With the smelly factor of cause;
(3) measured by different type water body, established respectively using artificial neural network the blackening factor and nigrescence grade, cause it is smelly because
Data-driven model between sub and smelly grade, comprehensive water body nigrescence grade and smelly grade realize that the identification of black and odorous water grade is surveyed
It is fixed.
It is as described in step (1) to obtain water body humic acid, albuminoid, oil in black smelly precursor using three-dimensional fluorescence spectrum parsing
The concentration of class, the specific method is as follows: the three-dimensional fluorescence spectrum by measuring water body humic acid, albuminoid, three type organic of oils,
Establish the standard three-dimensional fluorescence data library of black smelly precursor organic matter;Multicomponent organic matter aliasing is determined using frequency spectrum Local method
The chemical order of fluorescence spectrum is based on standard three-dimensional fluorescence data library, utilizes alternately three linear and comprehensive similarity index calculations
Method, parsing obtain the concentration of water body humic acid, albuminoid, three type organic of oils in practical water body.
It is as described in step (1) using uv-visible absorption spectra parsing obtain the turbidity of black smelly correlation water, coloration,
Nitrate parameter value, the specific method is as follows: based on the relationship between suspended matter scattered light intensity and wavelength, with Mie scattering model
Based on, visible range absorption spectra is fitted, analyzing water body turbidity, suspended particulate matter concentration information;In 240 ~ 380nm
Organic matter characteristic absorption spectrum area calculates suspended particulate substance extinction spectra first with Mie scattering model, does bias control acquisition
Organic matter absorption spectrum recycles organic matter to absorb dactylogram, and it is total to calculate acquisition organic matter by Partial Least Squares Regression algorithm
Amount and water body chroma information;In 200 ~ 240nm nitrate characteristic absorption spectrum area, suspended particulate substance scattering model and organic is utilized
Object dactylogram calculates suspended matter extinction spectra and organic matter absorption spectrum, makees the absorption spectrum that bias control obtains nitrate,
Water body nitrate concentration is obtained by linear regression again.
COD, BOD, TOC water quality synthesis is obtained using adsorption and fluorescence spectra fusion inverting described in step (1) to refer to
Mark, and integrated dissolved oxygen and water temperature parameters, the specific method is as follows: passing through the linear dependence between spectral intensity and overall target point
Analysis extracts correlation strong characteristic fluorescence spectrum and absorption spectrum area, establishes the standard fusion spectroscopic data of water quality overall target
Library is based on standard fusion spectra database, merges spectrum using the water body of non-negative weighted least square algorithm parsing actual measurement, obtains
Water body COD, BOD, TOC water quality overall target concentration.
Comprehensive water body nigrescence grade described in step (3) and smelly grade realize that the identification of black and odorous water grade measures, specifically
Method is as follows: obtaining different type water body humic acid, albuminoid, oils three classes using water body three-dimensional fluorescence spectrum and absorption spectrum
Organic concentration, water turbidity, coloration, nitrate water quality indicator and COD, BOD, TOC water quality overall target, in conjunction with dissolution
Oxygen, temperature information select blackening, cause smelly key factor as input quantity, the water body nigrescence grade obtained with sensory experience method,
Smelly grade is output quantity, and the black and odorous water grade identification measurement mould based on data-driven is established using BP artificial neural network
Type.
The invention has the advantages that the present invention overcomes the black and odorous water monitorings of " city black and odorous water renovation guide " regulation
Existing for method the problems such as " monitoring index is single, organic indicator lacks, ammonia nitrogen needs sampling-off-line measurement ", and has and be excused from an examination
Agent, without sample pretreatment, measurement is quick the features such as, be quickly and effectively black and odorous water measurement means.
Detailed description of the invention
Fig. 1 is measuring method schematic diagram of the present invention.
Specific embodiment
As shown in Figure 1, the black smelly quick identification measuring method of urban water-body based on multi-source optical spectrum feature, including following step
It is rapid:
(1) using three-dimensional fluorescence spectrum parsing obtain water body humic acid in black smelly precursor, albuminoid, oils concentration;Utilize purple
Outside-visible absorption spectra parsing obtains turbidity, coloration, the nitrate parameter value of black smelly correlation water;Using fluorescence spectrum and inhale
It receives spectrum fusion inverting and obtains COD, BOD, TOC water quality overall target, and integrated dissolved oxygen and water temperature parameters;
(2) comparison sensory experience method water body blacks and smelly index, selects the blackening factor from These parameters by clustering
With the smelly factor of cause;
(3) measured by different type water body, established respectively using artificial neural network the blackening factor and nigrescence grade, cause it is smelly because
Data-driven model between sub and smelly grade, comprehensive water body nigrescence grade and smelly grade realize that the identification of black and odorous water grade is surveyed
It is fixed.
It is as described in step (1) to obtain water body humic acid, albuminoid, oil in black smelly precursor using three-dimensional fluorescence spectrum parsing
The concentration of class, the specific method is as follows: the easily biodegradable organics such as humic acid, albuminoid, oils are to cause black and odorous water main matter.
By measuring the three-dimensional fluorescence spectrum of water body humic acid, albuminoid, three type organic of oils, the mark of black smelly precursor organic matter is established
Quasi- three-dimensional fluorescence spectrum database;The chemical order that multicomponent organic matter aliasing fluorescence spectrum is determined using frequency spectrum Local method, is based on
Standard three-dimensional fluorescence data library, using alternately three linear and comprehensive similarity exponentiation algorithms, parsing is obtained in practical water body
The concentration of water body humic acid, albuminoid, three type organic of oils.
It is as described in step (1) using uv-visible absorption spectra parsing obtain the turbidity of black smelly correlation water, coloration,
Nitrate parameter value, the specific method is as follows: the absorption spectrum in ultraviolet-visible spectrum area contains black and odorous water related substances abundant
Characteristic absorption information, wherein 200 ~ 240nm is nitrate characteristic absorption wave band, 200 ~ 380nm is organic matter characteristic absorption wave band,
And suspended matter scattering delustring influences to be distributed whole spectral regions.Therefore, it can accurately be obtained by spectrum piecewise analytic and compensation correction
The water quality indicators such as turbidity, coloration, nitrate.Based on the relationship between suspended matter scattered light intensity and wavelength, with Mie scattering model
Based on, visible range absorption spectra is fitted, analyzing water body turbidity, suspended particulate matter concentration information;In 240 ~ 380nm
Organic matter characteristic absorption spectrum area calculates suspended particulate substance extinction spectra first with Mie scattering model, does bias control acquisition
Organic matter absorption spectrum recycles organic matter to absorb dactylogram, and it is total to calculate acquisition organic matter by Partial Least Squares Regression algorithm
Amount and water body chroma information;In 200 ~ 240nm nitrate characteristic absorption spectrum area, suspended particulate substance scattering model and organic is utilized
Object dactylogram calculates suspended matter extinction spectra and organic matter absorption spectrum, makees the absorption spectrum that bias control obtains nitrate,
Water body nitrate concentration is obtained by linear regression again.
COD, BOD, TOC water quality synthesis is obtained using adsorption and fluorescence spectra fusion inverting described in step (1) to refer to
Mark, and integrated dissolved oxygen and water temperature parameters, the specific method is as follows: COD, BOD, TOC etc. especially have as evaluation water body situation
The composite target of machine object pollution situation all contains associated feature letter in water body three-dimensional fluorescence spectrum and absorption spectrum
Breath.By the linear dependence analysis between spectral intensity and overall target, correlation strong characteristic fluorescence spectrum and absorption are extracted
Spectral regions establish the standard fusion spectra database of water quality overall target, are based on standard fusion spectra database, are added using non-negative
The water body for weighing least-squares algorithm parsing actual measurement merges spectrum, obtains water body COD, BOD, TOC water quality overall target concentration.
Comprehensive water body nigrescence grade described in step (3) and smelly grade realize that the identification of black and odorous water grade measures, specifically
Method is as follows: black and odorous water is organic contamination extreme performance, is caused by large amount of organic anaerobic degradation.But the black smelly water of different type
Body ingredient is not quite similar, black smelly specific Forming Mechanism is complicated, by Analysis of Environmental Factors, is difficult to accurately using physico-chemical analysis method
Description.The prediction technique of data-driven is to establish the optimal mathematical relationship between inputoutput data as the black box side of target
Method, especially suitable for rule or the indefinite system research of mechanism.It is obtained not using water body three-dimensional fluorescence spectrum and absorption spectrum
Same type water body humic acid, albuminoid, oils three classes organic concentration, water turbidity, coloration, nitrate water quality indicator, and
COD, BOD, TOC water quality overall target select blackening, cause smelly key factor as input in conjunction with dissolved oxygen, temperature information
Amount, the water body nigrescence grade obtained using sensory experience method, smelly grade are based on as output quantity using the foundation of BP artificial neural network
The black and odorous water grade of data-driven identifies rating model.
Claims (5)
1. the black smelly quick identification measuring method of urban water-body based on multi-source optical spectrum feature, it is characterised in that: the following steps are included:
(1) using three-dimensional fluorescence spectrum parsing obtain water body humic acid in black smelly precursor, albuminoid, oils concentration;Utilize purple
Outside-visible absorption spectra parsing obtains turbidity, coloration, the nitrate parameter value of black smelly correlation water;Using fluorescence spectrum and inhale
It receives spectrum fusion inverting and obtains COD, BOD, TOC water quality overall target, and integrated dissolved oxygen and water temperature parameters;
(2) comparison sensory experience method water body blacks and smelly index, selects the blackening factor from These parameters by clustering
With the smelly factor of cause;
(3) measured by different type water body, established respectively using artificial neural network the blackening factor and nigrescence grade, cause it is smelly because
Data-driven model between sub and smelly grade, comprehensive water body nigrescence grade and smelly grade realize that the identification of black and odorous water grade is surveyed
It is fixed.
2. the black smelly quick identification measuring method of the urban water-body according to claim 1 based on multi-source optical spectrum feature, special
Sign is: as described in step (1) to obtain water body humic acid, albuminoid, oil in black smelly precursor using three-dimensional fluorescence spectrum parsing
The concentration of class, the specific method is as follows: the three-dimensional fluorescence spectrum by measuring water body humic acid, albuminoid, three type organic of oils,
Establish the standard three-dimensional fluorescence data library of black smelly precursor organic matter;Multicomponent organic matter aliasing is determined using frequency spectrum Local method
The chemical order of fluorescence spectrum is based on standard three-dimensional fluorescence data library, utilizes alternately three linear and comprehensive similarity index calculations
Method, parsing obtain the concentration of water body humic acid, albuminoid, three type organic of oils in practical water body.
3. the black smelly quick identification measuring method of the urban water-body according to claim 1 based on multi-source optical spectrum feature, special
Sign is: turbidity, coloration, the nitre as described in step (1) that black smelly correlation water is obtained using uv-visible absorption spectra parsing
Hydrochlorate parameter value, the specific method is as follows: based on the relationship between suspended matter scattered light intensity and wavelength, being with Mie scattering model
Basis is fitted visible range absorption spectra, analyzing water body turbidity, suspended particulate matter concentration information;Have in 240 ~ 380nm
Ji Wu characteristic absorption spectrum area calculates suspended particulate substance extinction spectra first with Mie scattering model, and doing bias control is had
Machine object absorption spectrum recycles organic matter to absorb dactylogram, is calculated by Partial Least Squares Regression algorithm and obtains total amount of organic
With water body chroma information;In 200 ~ 240nm nitrate characteristic absorption spectrum area, suspended particulate substance scattering model and organic matter are utilized
Dactylogram calculates suspended matter extinction spectra and organic matter absorption spectrum, makees the absorption spectrum that bias control obtains nitrate, then
Water body nitrate concentration is obtained by linear regression.
4. the black smelly quick identification measuring method of the urban water-body according to claim 1 based on multi-source optical spectrum feature, special
Sign is: obtaining COD, BOD, TOC water quality synthesis using adsorption and fluorescence spectra fusion inverting described in step (1) and refers to
Mark, and integrated dissolved oxygen and water temperature parameters, the specific method is as follows: passing through the linear dependence between spectral intensity and overall target point
Analysis extracts correlation strong characteristic fluorescence spectrum and absorption spectrum area, establishes the standard fusion spectroscopic data of water quality overall target
Library is based on standard fusion spectra database, merges spectrum using the water body of non-negative weighted least square algorithm parsing actual measurement, obtains
Water body COD, BOD, TOC water quality overall target concentration.
5. the black smelly quick identification measuring method of the urban water-body according to claim 1 based on multi-source optical spectrum feature, special
Sign is: comprehensive water body nigrescence grade described in step (3) and smelly grade realize that the identification of black and odorous water grade measures, specific side
Method is as follows: obtaining different type water body humic acid, albuminoid, oils three classes using water body three-dimensional fluorescence spectrum and absorption spectrum has
Machine object concentration, water turbidity, coloration, nitrate water quality indicator and COD, BOD, TOC water quality overall target, in conjunction with dissolved oxygen,
Temperature information selects blackening, causes smelly key factor as input quantity, the water body nigrescence grade obtained with sensory experience method, hair
Smelly grade is output quantity, establishes the black and odorous water grade based on data-driven using BP artificial neural network and identifies rating model.
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Cited By (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109975262A (en) * | 2019-04-15 | 2019-07-05 | 上海交通大学 | One kind optimizing full spectrum monitoring COD method based on three-dimensional fluorescence domain integral method |
CN110688909A (en) * | 2019-09-05 | 2020-01-14 | 南京有春科技有限公司 | Method, device and equipment for identifying urban black and odorous water body and storage medium |
CN110702656A (en) * | 2019-10-24 | 2020-01-17 | 燕山大学 | Vegetable oil pesticide residue detection method based on three-dimensional fluorescence spectrum technology |
CN110987955A (en) * | 2019-12-05 | 2020-04-10 | 南京师范大学 | Urban black and odorous water body grading method based on decision tree |
CN111157476A (en) * | 2020-02-21 | 2020-05-15 | 中国科学院合肥物质科学研究院 | Quantitative inversion method for water quality multi-parameter ultraviolet-visible absorption spectrum |
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CN112881353A (en) * | 2021-01-11 | 2021-06-01 | 江西师范大学 | Method and device for measuring concentration of soluble organic carbon in water body |
CN112903945A (en) * | 2021-02-26 | 2021-06-04 | 珠江水利委员会珠江水利科学研究院 | Urban black and odorous water body identification method based on conventional water quality parameters |
CN113077019A (en) * | 2021-06-07 | 2021-07-06 | 芯视界(北京)科技有限公司 | Pollution type identification method and device and storage medium |
CN113588617A (en) * | 2021-08-02 | 2021-11-02 | 清华大学 | Water quality multi-feature early warning traceability system and method |
CN114216884A (en) * | 2021-11-03 | 2022-03-22 | 湖北文理学院 | Method for measuring content of humic acid in breeding wastewater |
CN114368795A (en) * | 2021-12-31 | 2022-04-19 | 天健创新(北京)监测仪表股份有限公司 | Online black and odorous water body multi-mode identification method and system |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104034684A (en) * | 2014-06-05 | 2014-09-10 | 北京金达清创环境科技有限公司 | Water quality multi-index detection method on basis of ultraviolet-visible absorption spectrum |
CN106198424A (en) * | 2016-09-28 | 2016-12-07 | 深圳市七善科技有限公司 | A kind of based on full spectral water quality on-line monitoring equipment and monitoring method thereof |
CN106841072A (en) * | 2017-03-30 | 2017-06-13 | 莱森光学(深圳)有限公司 | A kind of method differentiated for algae with algae proliferation non-destructive monitoring situation |
CN106874948A (en) * | 2017-02-08 | 2017-06-20 | 武汉海卓科科技有限公司 | A kind of black smelly water automatic identification and appraisal procedure |
CN105488488B (en) * | 2015-12-10 | 2018-12-21 | 中国科学院遥感与数字地球研究所 | City black and odorous water remote sensing recognition method and device |
-
2018
- 2018-08-16 CN CN201810932133.0A patent/CN109142296A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104034684A (en) * | 2014-06-05 | 2014-09-10 | 北京金达清创环境科技有限公司 | Water quality multi-index detection method on basis of ultraviolet-visible absorption spectrum |
CN105488488B (en) * | 2015-12-10 | 2018-12-21 | 中国科学院遥感与数字地球研究所 | City black and odorous water remote sensing recognition method and device |
CN106198424A (en) * | 2016-09-28 | 2016-12-07 | 深圳市七善科技有限公司 | A kind of based on full spectral water quality on-line monitoring equipment and monitoring method thereof |
CN106874948A (en) * | 2017-02-08 | 2017-06-20 | 武汉海卓科科技有限公司 | A kind of black smelly water automatic identification and appraisal procedure |
CN106841072A (en) * | 2017-03-30 | 2017-06-13 | 莱森光学(深圳)有限公司 | A kind of method differentiated for algae with algae proliferation non-destructive monitoring situation |
Non-Patent Citations (4)
Title |
---|
傅大放 等: "《自生动态生物膜技术》", 28 February 2015, 东南大学出版社 * |
吴德操 等: "基于Mie散射的水体紫外-可见光谱浊度干扰补偿", 《光学学报》 * |
徐明德 等: "基于BP神经网络-隶属度的河流黑臭评价研究", 《数学的实践与认识》 * |
武晓莉 等: "多源光谱信息融合在水质分析中的应用", 《分析化学》 * |
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