CN119438109B - Water quality multi-parameter detection method and system based on ultraviolet-visible light spectrum method - Google Patents
Water quality multi-parameter detection method and system based on ultraviolet-visible light spectrum method Download PDFInfo
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Abstract
The invention provides a water quality multiparameter detection method and system based on ultraviolet-visible light spectrum method, which are used for detecting turbidity, chemical oxygen demand and nitrate nitrogen concentration in a water sample. According to the method, firstly, water sample spectrum data are acquired and converted into absorbance, then, influence factors of turbidity, chemical oxygen demand and nitrate nitrogen on a spectrum of a mixed sample are calculated, and a spectrum range is divided into three characteristic spectrum sections according to the influence factors, wherein the three characteristic spectrum sections correspond to the turbidity, the chemical oxygen demand and the nitrate nitrogen respectively. Finally, a multiparameter detection model is established by using a partial least squares PLS method for predicting turbidity, chemical oxygen demand and nitrate nitrogen concentration. The method avoids the interference of serious overlapping of multi-parameter spectral lines by analyzing the spectra in a segmented way, improves the detection precision by utilizing a method of fusing the first derivative spectra, and has obvious effect in the aspect of nitrate nitrogen detection. The method is simple and convenient to operate and low in cost, and provides a more effective technical means for water quality monitoring and water environment protection.
Description
Technical Field
The invention relates to the technical field of underwater environmental parameter monitoring, in particular to a water quality multi-parameter detection method and system based on ultraviolet-visible light spectrum method.
Background
In recent years, ultraviolet-visible spectroscopy, which is one of water quality detection techniques for spectroscopic analysis, has many advantages over chemical methods. For example, no digestion agent is needed, no secondary pollution is caused, the period is short, the operation and maintenance are convenient, the cost is low, and the online and in-situ measurement can be realized. The prior ultraviolet-visible spectrum method is mainly used for detecting water quality by a single-wavelength method or a double-wavelength method. However, when the components of the water sample are complex, the modeling of single wavelength or dual wavelength cannot achieve ideal effects due to the selective absorption of different components for different wavelengths.
Turbidity, chemical oxygen demand, nitrate are three important indicators for monitoring the quality of seawater. The higher the chemical oxygen demand, the higher the content of the reducing substances (such as organic matters) in the water body, and the reducing substances can reduce the content of the dissolved oxygen in the water body, so that the aquatic organisms are anoxic to death, and the water quality is spoiled and smelly. The increase of the nitrate mass concentration can have serious influence on the water ecological system, so that the water body is eutrophicated, toxic algal bloom and anoxic.
The presence of severe overlap interference phenomena in the lines of turbidity, chemical oxygen demand and nitrate nitrogen creates difficulties in determining the parameter concentrations using the ultraviolet-visible spectrum.
Disclosure of Invention
The invention overcomes the defects of the prior art, and provides a water quality multiparameter detection method and system based on ultraviolet-visible light spectrum method, which are used for detecting turbidity, chemical oxygen demand and nitrate nitrogen concentration in a water sample and avoiding the problem of serious overlapping interference phenomenon of multiparameter spectral lines.
In order to achieve the aim, the technical scheme adopted by the invention is that the water quality multi-parameter detection method based on ultraviolet-visible light spectrum method comprises the following steps:
S1, acquiring spectral data of a water sample, and converting the spectral data into absorbance;
S2, calculating influence factors of turbidity, chemical oxygen demand and nitrate nitrogen on the spectrum of the mixed sample;
s3, dividing the spectrum range into three characteristic spectrum sections according to influence factors, wherein the three characteristic spectrum sections correspond to turbidity, chemical oxygen demand and nitrate nitrogen respectively;
s4, establishing a multi-parameter detection model, and predicting turbidity, chemical oxygen demand and nitrate nitrogen concentration.
Further, step S1 includes:
S11, scanning the water sample by using an ultraviolet-visible spectrometer to obtain absorbance data of the water sample within a wavelength range of 190nm-720 nm.
S12, converting the spectrum data into absorbance by using the beer-lambert law, and using the formula: . Wherein, Is absorbance; is the intensity of the emergent light; is the intensity of incident light; transmittance is the ratio of the intensity of the outgoing light to the intensity of the incoming light.
Further, step S2 includes:
S21, calculating an influence factor of turbidity, and using the formula: , wherein, Is the influence factor of turbidity on the spectrum of the mixed solution; spectrum for the mixed solution; Is a spectrum of a mixed substance containing equal concentrations of chemical oxygen demand and nitrate nitrogen and no turbidity.
S22, calculating an influence factor of the chemical oxygen demand, and using the formula: Wherein Is the influence factor of chemical oxygen demand on the spectrum of the mixed solution; spectrum for the mixed solution; is a spectrum of a mixed substance containing equal concentration of turbidity and nitrate nitrogen and no chemical oxygen demand.
S23, calculating an influence factor of nitrate nitrogen, and using the formula: Wherein Is the influence factor of nitrate nitrogen on the spectrum of the mixed solution; For the spectrum of the mixed solution, Is a spectrum of a mixed substance containing equal concentration of turbidity and chemical oxygen demand and no nitrate nitrogen.
Further, step S3 includes:
S31, analyzing the change trend of the influence factors;
S32, dividing a characteristic spectrum segment, taking 310-720 nm as a characteristic spectrum segment of turbidity, taking 250-310 nm as a characteristic spectrum segment of chemical oxygen demand, and taking 190-250 nm as a characteristic spectrum segment of nitrate nitrogen.
Further, step S4 includes establishing a multiparameter detection model by using a partial least squares PLS method according to characteristic spectra of turbidity, chemical oxygen demand and nitrate nitrogen.
Further, when the nitrate nitrogen is analyzed by using a partial least squares PLS method, the characteristic spectrum of the nitrate nitrogen is processed, and the processing method is to fuse the first derivative spectrum.
Further, when turbidity is analyzed by using a partial least squares PLS method, referring to absorbance of a water sample with a wave band of 250-400 nm;
When analyzing chemical oxygen demand by using a partial least squares PLS method, referring to absorbance of a 220-275 nm wave band water sample;
And when the nitrate nitrogen is analyzed by using a partial least squares PLS method, referring to the absorbance of the water sample in the 195-230 nm wave band.
Preferably, the method of fusing the first derivative spectra is direct fusion, with the first derivative spectral data added to the original spectral data.
The invention also provides a water quality multi-parameter detection system based on ultraviolet-visible light spectrum method, which is used for realizing the detection method and comprises the following modules:
the data acquisition and preprocessing module is used for scanning the water sample, acquiring spectrum data and converting the spectrum data into absorbance data;
the influence factor calculation module is used for calculating influence factors of turbidity, chemical oxygen demand and nitrate nitrogen on the spectrum of the mixed solution;
The characteristic spectrum segment identification module is used for analyzing the change trend of the influence factors and dividing the characteristic spectrum segment;
the multi-parameter detection model module is used for training a model to predict by utilizing characteristic spectrums of turbidity, chemical oxygen demand and nitrate nitrogen and standard solution with known concentration;
And the nitrate nitrogen processing module is used for processing the characteristic spectrum of the nitrate nitrogen and fusing the characteristic spectrum of the nitrate nitrogen with the first derivative spectrum of the nitrate nitrogen.
The invention solves the defects existing in the background technology, and has the following beneficial effects:
(1) The invention provides a water quality multiparameter detection method based on an ultraviolet-visible light spectrum method, which can efficiently and conveniently detect three parameters of turbidity, chemical oxygen demand and nitrate nitrogen simultaneously and remarkably improve detection precision. The method is simple and convenient to operate and low in cost, and provides a more effective technical means for water quality monitoring and water environment protection.
(2) According to the water quality multi-parameter detection method based on the ultraviolet-visible light spectrum method, the influence of each component on the spectrum of the mixed water sample is calculated, the spectrum range is divided into a plurality of characteristic spectrum sections, and the characteristic spectrum sections respectively correspond to turbidity, chemical oxygen demand and nitrate nitrogen, so that a plurality of parameters can be detected simultaneously. The traditional chemical analysis method needs to independently detect turbidity, chemical oxygen demand and nitrate nitrogen, and has complex operation, but the invention does not need to independently detect, simplifies operation steps, improves detection efficiency, and can effectively reduce detection cost.
(3) According to the water quality multi-parameter detection method based on the ultraviolet-visible light spectrum method, which is provided by the invention, the details of spectrum signals are effectively enhanced by fusing the first derivative spectrum when nitrate nitrogen is analyzed, and the slope change of the spectrum is highlighted. When the components of the water sample are complex, the traditional single-wavelength method or dual-wavelength method is easy to be interfered by complex backgrounds, and by fusing the first derivative spectrum, the definition of the nitrate nitrogen signal can be improved, so that the characteristic absorption peak of the nitrate nitrogen signal is more prominent in the complex backgrounds, the background interference is effectively reduced, the detection precision and the reliability of the detection result are improved, and more accurate data support is provided for water quality safety evaluation.
(4) According to the invention, the spectrum range is divided into a plurality of characteristic spectrum sections through sectionally analyzing the spectrum, and the turbidity, the chemical oxygen demand and the nitrate nitrogen are respectively corresponding to each other, so that the simultaneous detection of multiple parameters is realized. Meanwhile, when nitrate nitrogen is analyzed, the first derivative spectrum is fused, so that the details of a spectrum signal are effectively enhanced, the background interference is reduced, the detection precision of the nitrate nitrogen with weaker spectrum signal is remarkably improved, more effective technical means are provided for water quality monitoring and water environment protection, and the method has remarkable advantages in practical application.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art;
FIG. 1 is a flow chart of a water quality multi-parameter detection method based on ultraviolet-visible light spectrum method;
FIG. 2 is a diagram showing the turbidity prediction results according to the preferred embodiment of the present invention;
FIG. 3 is a schematic diagram showing the result of predicting the chemical oxygen demand in accordance with the preferred embodiment of the present invention;
FIG. 4 is a schematic diagram of the predicted result of nitrate nitrogen in a preferred embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
In the description of the present application, it should be understood that the terms "center", "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on the drawings, are merely for convenience in describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the scope of the present application. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first", "a second", etc. may include one or more of the feature, either explicitly or implicitly. In the description of the application, unless otherwise indicated, the meaning of "a plurality" is two or more.
In the description of the present application, unless explicitly stated and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected, mechanically connected, electrically connected, directly connected, indirectly connected via an intermediate medium, or in communication between two elements. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art in a specific case.
Summary of the application:
the water quality detection method can be mainly divided into three types, namely a chemical method, a physical method and a biological sensing method.
The chemical analysis method mainly comprises a chemical analysis method and an electrochemical analysis method, wherein the chemical analysis method is based on the principle of chemical reaction, and the components in water are quantitatively or qualitatively analyzed through color change, precipitation, gas release, electrolyte solubility change and the like generated by the chemical reaction. Electrochemical analysis detects water quality based on electrochemical reaction between an electrode and a solution, and quantitatively or qualitatively analyzes components in water through a change in electrode potential.
Biosensing uses specific interactions between biomolecules and contaminants to detect water quality. The biological recognition function and the signal conversion function are combined, so that the detection of pollutants is realized.
Physical methods are mainly chromatography, mass spectrometry and direct spectrometry. Mass spectrometry is a technique for analyzing the molecular mass and structure of a substance by ionizing sample molecules, then separating them according to the molecular mass in an electric field or a magnetic field, and finally detecting and analyzing the ions. Chromatography is a technique for separation and detection based on differences in partition coefficients between stationary and mobile phases of different components in a mixture. Direct spectroscopy includes ultraviolet-visible spectroscopy, near infrared spectroscopy, raman spectroscopy, and the like, which analyze a sample based on absorption, emission, or scattering properties of a substance for light.
The existing ultraviolet-visible spectrometry for analyzing water quality parameters mainly comprises a single-wavelength analysis method, a dual-wavelength compensation method and a spectrum difference method.
The single wavelength analysis method comprises selecting a certain characteristic wavelength of a substance to be detected, and analyzing and calculating;
selecting another wavelength less affected by the substance to be measured to compensate the spectrum at the characteristic wavelength of the substance to be measured;
Spectrum Difference method in the spectrum of a mixture system, in order to know the structure of one component, the spectrum of one component can be subtracted from the spectrum of the mixture by subtracting the absorbance spectrum.
However, the chemical analysis method has the defects of complex operation, reagent consumption, secondary pollution, long measurement period, difficulty in realizing on-line detection and the like. The electrochemical analysis method has the defects of short service life, single detection index, multiple parameters, multiple sensors and detection circuits and the like. Biosensing suffers from sensor reproducibility problems. The chromatography has the defects of complex and expensive instrument, high maintenance cost, sample pretreatment, long test period and the like. Mass spectrometry also has the disadvantages of expensive equipment, complex analysis, etc. When the components of the water sample are complex, single-wavelength or dual-wavelength modeling cannot achieve ideal effects due to the selective absorption of different components for different wavelengths. The absorbance does not strictly meet the additivity in practical application, and the spectrum difference method needs to acquire compensation spectrums of all different concentrations of the solution formed by other parameters except the parameter to be measured in a measuring range in advance, so that the workload is large, and the method is not convenient and quick enough.
An exemplary method is:
as shown in fig. 1, a water quality multi-parameter detection method based on ultraviolet-visible light spectrum method comprises the following steps:
S1, acquiring spectral data of a water sample, and converting the spectral data into absorbance;
S2, calculating influence factors of turbidity, chemical oxygen demand and nitrate nitrogen on the spectrum of the mixed sample;
s3, dividing the spectrum range into three characteristic spectrum sections according to influence factors, wherein the three characteristic spectrum sections correspond to turbidity, chemical oxygen demand and nitrate nitrogen respectively;
s4, establishing a multi-parameter detection model, and predicting turbidity, chemical oxygen demand and nitrate nitrogen concentration.
Next, each step will be described in detail.
The step S1 comprises the following steps:
S11, scanning the water sample by using an ultraviolet-visible spectrometer to obtain absorbance data of the water sample within a wavelength range of 190nm-720 nm.
S12, converting the spectrum data into absorbance by using the beer-lambert law, and using the formula: . Wherein, Is absorbance; is the intensity of the emergent light; is the intensity of incident light; Transmittance (transmittance) is the intensity of emergent light ) And incident light intensity) Is a ratio of (2).
And selecting the most sensitive wavelength range for analysis according to different water quality parameters, acquiring spectral data, converting the spectral data into absorbance, and ensuring the data quality.
The step S2 comprises the following steps:
The influence factors of turbidity, chemical oxygen demand and nitrate nitrogen on the spectrum of the mixed solution are respectively calculated, namely the contribution of each component to the spectrum of the mixed sample at different wavelengths is calculated.
S21, calculating an influence factor of turbidity, and using the formula: , wherein, Is the influence factor of turbidity on the spectrum of the mixed solution; spectrum for the mixed solution; Is a spectrum of a mixed substance containing equal concentrations of chemical oxygen demand and nitrate nitrogen and no turbidity.
S22, calculating an influence factor of the chemical oxygen demand, and using the formula: Wherein Is the influence factor of chemical oxygen demand on the spectrum of the mixed solution; spectrum for the mixed solution; is a spectrum of a mixed substance containing equal concentration of turbidity and nitrate nitrogen and no chemical oxygen demand.
S23, calculating an influence factor of nitrate nitrogen, and using the formula: Wherein Is the influence factor of nitrate nitrogen on the spectrum of the mixed solution; For the spectrum of the mixed solution, Is a spectrum of a mixed substance containing equal concentration of turbidity and chemical oxygen demand and no nitrate nitrogen.
By calculating the influence factors of the parameters on the spectrum of the mixed sample, the contribution degree of each parameter in the mixed sample can be more accurately distinguished, and the possibility of cross interference is reduced.
The step S3 comprises the following steps:
S31, analyzing the change trend of the influence factors, searching a wavelength region with larger influence factors, namely, the absorption of the parameter in the region is obvious, and simultaneously, considering the influence degree of other parameters in the region, and selecting a region with smaller influence of the other parameters as much as possible.
S32, dividing the characteristic spectrum sections of turbidity, chemical oxygen demand and nitrate nitrogen according to the change trend of the influence factors.
The turbidity is selected as a characteristic spectrum band of 310-720 nm, because the influence of the turbidity on the spectrum is larger in the band range, and the influence of chemical oxygen demand and nitrate nitrogen is relatively smaller.
The chemical oxygen demand is selected as the characteristic spectrum band, because the influence of the chemical oxygen demand on the spectrum is larger and the influence of the turbidity and the nitrate nitrogen is relatively smaller in the band range.
Nitrate nitrogen is selected as a characteristic spectrum band, because in the band range, the influence of the nitrate nitrogen on the spectrum is larger, and the influence of turbidity and chemical oxygen demand is relatively smaller.
It is noted that these characteristic spectral bands are determined based on the results of an analysis of the influence factors over the entire spectral range (190 nm-720 nm) to identify which wavelength ranges are most relevant for a certain parameter, and that the absorbance data of the corresponding characteristic spectral band is selected, i.e. the characteristic spectral band data of the corresponding component is used only for subsequent analysis.
The step S4 includes:
And establishing a multi-parameter detection model by using a partial least squares PLS method. The PLS method is a regression analysis method for processing multivariate data, and can effectively process the relationship between a plurality of independent variables and a plurality of dependent variables. The specific method comprises the following steps:
Setting an independent variable matrix Absorbance data for each water sample over a specific wavelength range is included, each row representing one water sample, and each column representing absorbance values at one wavelength.
Setting a dependent variable matrixThe concentration values of parameters to be measured (turbidity, chemical oxygen demand, nitrate nitrogen) in each water sample are contained, each row represents one water sample, and each column represents the concentration of one parameter to be measured.
(1) Matrix solvingFeature vector corresponding to maximum feature valueObtaining component score vectorSum-residual matrixWherein。
(2) Matrix solvingFeature vector corresponding to maximum feature valueObtaining component score vectorSum-residual matrixWherein。
(3)......。
(4) Matrix solvingFeature vector corresponding to maximum feature valueObtaining component score vector。
Determining total decimated r components based on cross-validationObtaining a prediction modelAt the position ofThe above general least squares regression equation is: . Wherein, ,...Is a regression coefficient matrix.
Will beSubstitution intoObtaining p dependent variable partial least squares regression equations to obtain. Wherein, Satisfy the following requirements、Fr is a residual matrix representing the part of the dependent variable that cannot be interpreted by the component score vector.
Further, when a multi-parameter detection model is established, data in a specific wavelength range is selected to perform Partial Least Squares (PLS) modeling, wherein the absorbance of a water sample in a wave band of 250-400 nm is referred to when turbidity is analyzed by the partial least squares PLS method, the absorbance of a water sample in a wave band of 220-275 nm is referred to when chemical oxygen demand is analyzed by the partial least squares PLS method, and the absorbance of a water sample in a wave band of 195-230 nm is referred to when nitrate nitrogen is analyzed by the partial least squares PLS method. The selection of the above wave bands is based on further refinement of experimental data and theoretical analysis of each parameter, and the wavelength range which can most represent the parameter change is determined, so that the spectrum data used in the modeling process can be ensured to reflect the information of the target parameter best, and the selection of a more specific wave band can reduce the interference of other factors, and improve the accuracy and reliability of the model.
Further, when the partial least squares PLS method is used for analyzing the nitrate nitrogen, the characteristic spectrum of the nitrate nitrogen is processed, and the specific processing method is to fuse the first derivative spectrum. This is because nitrate nitrogen has a weak characteristic absorption peak in the ultraviolet-visible spectrum and is susceptible to complex background, and especially when other substances exist in a water sample, the spectrum signal of the nitrate nitrogen may be masked, resulting in a decrease in detection accuracy. Whereas the first derivative spectral processing can extract and highlight subtle features or signal variations in the spectrum. The derivative of the spectrum can be obtained by calculating the difference between successive spectral data points. The first derivative process can highlight slope changes or peak information in the spectrum, can reveal subtle features, edges and trends in the spectrum, and provides information about sample composition, concentration and response. By inputting spectral information into the independent variable matrix in combination with first derivative informationAnd dependent variable matrixIn the method, the identification accuracy can be effectively improved, and as the first derivative spectrum is directly obtained by calculation of the spectrum to be detected, the spectrum information of other samples without a certain component to be detected is not needed, and the method is convenient and quick. Where background refers to all other signals and noise in the spectroscopic analysis except for the target signal (i.e. the characteristic absorption peak of nitrate nitrogen). These background signals include, but are not limited to, absorption of solvents and other components, scattering effects, instrument noise, environmental factors, and sample non-uniformities. In the invention, a specific method for fusing the first derivative spectrum is direct fusion, and the first derivative spectrum data is directly added into the original spectrum data.
In one particular embodiment, seven sets of experimental samples were set, each set of experimental samples being shown as the sample true values in table 1:
TABLE 1
Seven groups of experimental sample predicted value data are obtained by using the detection method provided by the invention, and the predicted value data of each group of experimental samples are shown as sample predicted values in table 2 and fig. 2 to 4:
TABLE 2
Based on the prediction data, the model decision coefficients of the multi-parameter detection model in the present invention are shown in table 3:
TABLE 3 Table 3
R-Square represents the proportion of the model that can account for the variance of the dependent variable, ranging from 0 to 1.
The closer R-Square is to 1, the better the model is fit, and the stronger the model predictive power.
The closer R-Square is to 0, the worse the model fits, and the weaker the model predictive power.
The model determines the calculation formula of the coefficient R-Square: . The SSR is the sum of squares of the residual errors and represents the sum of squares of the difference between the predicted value and the real value, and the SST is the sum of the total squares and represents the sum of the squares of the difference between the real value and the average value of the real value.
In the embodiment, the model determination coefficients R-Square are respectively 0.99, 0.99 and 0.98, which shows that the model is well fitted to the model of turbidity, chemical oxygen demand and nitrate nitrogen, and the model prediction result is accurate. The method is characterized in that the spectrum range is divided into three characteristic spectrum sections, and the three characteristic spectrum sections correspond to turbidity (250-400 nm), chemical oxygen demand (220-275 nm) and nitrate nitrogen (195-230 nm) respectively, so that interference caused by serious overlapping of multi-parameter spectral lines is avoided. Each parameter has its specific wavelength region where the influence of the parameter on the spectrum is larger and the influence of other parameters is smaller, thereby improving the detection accuracy. Secondly, for detecting the nitrate nitrogen, a method of fusing a first derivative spectrum is particularly used, and under the condition that the absorption peak of the nitrate nitrogen is weak, the details of spectrum signals are enhanced, and the detection precision of the nitrate nitrogen is further improved.
Exemplary System:
A water quality multiparameter detection system based on ultraviolet-visible light spectrum method is used for realizing the detection method, and comprises the following modules:
the data acquisition and preprocessing module is used for scanning the water sample, acquiring spectrum data and converting the spectrum data into absorbance data;
the influence factor calculation module is used for calculating influence factors of turbidity, chemical oxygen demand and nitrate nitrogen on the spectrum of the mixed solution;
The characteristic spectrum segment identification module is used for analyzing the change trend of the influence factors and dividing the characteristic spectrum segment;
the multi-parameter detection model module is used for training a model to predict by utilizing characteristic spectrums of turbidity, chemical oxygen demand and nitrate nitrogen and standard solution with known concentration;
And the nitrate nitrogen processing module is used for processing the characteristic spectrum of the nitrate nitrogen and fusing the characteristic spectrum of the nitrate nitrogen with the first derivative spectrum of the nitrate nitrogen.
The above-described preferred embodiments according to the present invention are intended to suggest that, from the above description, various changes and modifications can be made by the person skilled in the art without departing from the scope of the technical idea of the present invention. The technical scope of the present invention is not limited to the description, but must be determined according to the scope of claims.
Claims (6)
1. A water quality multiparameter detection method based on ultraviolet-visible light spectrum method is characterized by comprising the following steps:
S1, acquiring spectral data of a water sample, and converting the spectral data into absorbance;
S2, calculating influence factors of turbidity, chemical oxygen demand and nitrate nitrogen on the spectrum of the mixed sample;
s3, dividing the spectrum range into three characteristic spectrum sections according to influence factors, wherein the three characteristic spectrum sections correspond to turbidity, chemical oxygen demand and nitrate nitrogen respectively;
S4, establishing a multi-parameter detection model by using a partial least squares PLS method according to the characteristic spectrums of turbidity, chemical oxygen demand and nitrate nitrogen, and predicting the concentration of the turbidity, the chemical oxygen demand and the nitrate nitrogen;
in step S2:
calculating an influence factor of turbidity by using the formula: , wherein, Is the influence factor of turbidity on the spectrum of the mixed solution; spectrum for the mixed solution; spectrum of mixed substances containing equal concentration of chemical oxygen demand and nitrate nitrogen and no turbidity;
the influence factor of the chemical oxygen demand is calculated by the formula: Wherein Is the influence factor of chemical oxygen demand on the spectrum of the mixed solution; spectrum for the mixed solution; Spectrum of mixed substances containing equal concentration turbidity and nitrate nitrogen and no chemical oxygen demand;
the influence factor of nitrate nitrogen is calculated by the formula: Wherein Is the influence factor of nitrate nitrogen on the spectrum of the mixed solution; For the spectrum of the mixed solution, Spectrum of mixed substances containing equal concentration turbidity and chemical oxygen demand and no nitrate nitrogen;
In step S4, when the nitrate nitrogen is analyzed by the partial least squares PLS method, the characteristic spectrum of the nitrate nitrogen is subjected to fusion first derivative spectrum processing.
2. The method for multi-parameter detection of water quality based on ultraviolet-visible light spectrum method according to claim 1, wherein step S1 comprises:
S11, scanning a water sample by using an ultraviolet-visible spectrometer to obtain absorbance data of the water sample within a wavelength range of 190nm-720 nm;
s12, converting the spectrum data into absorbance by using the beer-lambert law, and using the formula: Wherein, the method comprises the steps of, Is absorbance; is the intensity of the emergent light; is the intensity of incident light; transmittance is the ratio of the intensity of the outgoing light to the intensity of the incoming light.
3. The method for multi-parameter detection of water quality based on ultraviolet-visible light spectrum method according to claim 1, wherein step S3 comprises:
S31, analyzing the change trend of the influence factors;
S32, dividing a characteristic spectrum segment, taking 310-720 nm as a characteristic spectrum segment of turbidity, taking 250-310 nm as a characteristic spectrum segment of chemical oxygen demand, and taking 190-250 nm as a characteristic spectrum segment of nitrate nitrogen.
4. The method for multi-parameter detection of water quality based on ultraviolet-visible light spectrum method according to claim 1, wherein,
When turbidity is resolved by using a partial least squares PLS method, referring to absorbance of a water sample with a wave band of 250-400 nm;
When analyzing chemical oxygen demand by using a partial least squares PLS method, referring to absorbance of a 220-275 nm wave band water sample;
And when the nitrate nitrogen is analyzed by using a partial least squares PLS method, referring to the absorbance of the water sample in the 195-230 nm wave band.
5. The method for multi-parameter detection of water quality based on ultraviolet-visible light spectrum method according to claim 1, wherein the method of fusion of the first derivative spectrum is direct fusion, and the first derivative spectrum data is added into the original spectrum data.
6. A water quality multiparameter detection system based on ultraviolet-visible light spectrum, for implementing the detection method according to any one of claims 1 to 5, characterized by comprising the following modules:
the data acquisition and preprocessing module is used for scanning the water sample, acquiring spectrum data and converting the spectrum data into absorbance data;
the influence factor calculation module is used for calculating influence factors of turbidity, chemical oxygen demand and nitrate nitrogen on the spectrum of the mixed solution;
The characteristic spectrum segment identification module is used for analyzing the change trend of the influence factors and dividing the characteristic spectrum segment;
the multi-parameter detection model module is used for training a model to predict by utilizing characteristic spectrums of turbidity, chemical oxygen demand and nitrate nitrogen and standard solution with known concentration;
And the nitrate nitrogen processing module is used for processing the characteristic spectrum of the nitrate nitrogen and fusing the characteristic spectrum of the nitrate nitrogen with the first derivative spectrum of the nitrate nitrogen.
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