CN111351762A - Ultraviolet-visible light full-wavelength scanning sewage quality on-line rapid detection method and application - Google Patents
Ultraviolet-visible light full-wavelength scanning sewage quality on-line rapid detection method and application Download PDFInfo
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Abstract
The invention relates to an ultraviolet-visible light full-wavelength scanning online rapid detection method and application for sewage quality, wherein a full-waveband spectrum detection system is used for scanning the sewage in full waveband, a submerged type direct scanning water body is adopted, and the obtained spectrum absorption information of the sewage is transmitted to the full-waveband spectrum detection system; detection system utilizing full-band spectrumCalculating an absorption full spectrum diagram of the sewage; obtaining a multiple regression equation of each substance to be detected by utilizing a full-waveband spectrum detection system through multiple regression equation model fitting, wherein the multiple regression equation model is as follows: y isn＝A1*x1+A2*x2+…+A210*x210+…+An*xn(n 215-; wherein, YnFor the target parameter prediction value, A1‑AnThe coefficients of the corresponding wavelengths of the models are obtained; and detecting the water quality parameter value by using a full-waveband spectrum detection system. The simultaneous detection of various substances is realized, the detection time is as short as 15s, and the result can be obtained.
Description
Technical Field
The invention belongs to the technical field of sewage quality information detection, and particularly relates to an ultraviolet-visible light full-wavelength scanning sewage quality on-line rapid detection method and application.
Background
The information in this background section is only for enhancement of understanding of the general background of the invention and is not necessarily to be construed as an admission or any form of suggestion that this information forms the prior art that is already known to a person of ordinary skill in the art.
The water environment pollution is closely related to human life and production activities, and not only affects human health, but also affects human activities. As one of the key links in the water environment quality guarantee system, the operation effect of the sewage treatment plant determines the pollution degree of the water environment. Under the condition of energy supply shortage worldwide, the sewage treatment plant needs to meet the dual requirements of good treatment effect and high treatment efficiency. The operation cost of sewage plant mainly includes energy consumption (electricity charge), chemical agent consumption, etc., and important water quality parameters (such as Chemical Oxygen Demand (COD) and Nitrate (NO)) in sewage treatment3N), etc.) and the sewage plant operation intelligent control means, thereby providing possibility for the sewage plant to dynamically control the equipment operation and the chemical dosage, and further achieving the purposes of reducing the sewage treatment operation cost and improving the sewage treatment operation efficiency.
With the recent progress of automatic control theory and technical equipment, industrial automation has been developed greatly. However, the water quality on-line detection system widely used in China at present still operates according to the flow of automatic sampling, analysis testing and data analysis and transmission, and the on-line monitoring of the sewage water quality is limited by the problems of high instrument cost, poor reliability and serious delay of data acquisition time, so that the automation and intelligent development of sewage treatment plants is limited.
Disclosure of Invention
Aiming at the problems in the prior art, the invention aims to provide an ultraviolet-visible light full-wavelength scanning online rapid detection method and application for sewage quality. The invention utilizes the ultraviolet visible full spectrum data of the sewage, comprehensively analyzes the relation between the full spectrum and the water quality parameters based on the statistical principle, establishes a multiple regression equation model taking the water quality parameters as output values, and realizes the simultaneous on-line rapid detection of various water quality parameters.
In order to solve the technical problems, the technical scheme of the invention is as follows:
in a first aspect, an ultraviolet-visible light full-wavelength scanning online rapid detection method for sewage quality comprises the following specific steps:
carrying out full-waveband scanning on the sewage, adopting immersion type direct scanning water body, obtaining the spectral absorption information of the sewage and transmitting the spectral absorption information to a full-waveband spectral detection system;
calculating an absorption full spectrum diagram of the sewage;
obtaining a multiple regression equation of each substance to be measured through multiple regression equation model fitting, wherein the multiple regression equation model is as follows: y isn＝A1*x1+A2*x2+…+A210*x210+…+An*xn(ii) a Wherein n is 215-nFor the target parameter prediction value, A1-AnThe coefficients of the corresponding wavelengths of the models are obtained; the wavelength range of 200-737.5nm, x1-xnThe wavelength of the incident light is selected in the whole wave band, and the wavelength interval of the incident light is 2-3 nm;
and combining the absorption full spectrogram with a multiple regression equation model of each substance to obtain a water quality parameter value.
The invention utilizes the wavelength of the full wave band to directly scan and detect the water body, and realizes more accurate water quality detection compared with the modeling by using a specific wave band.
In a second aspect, the full-waveband spectrum detection system comprises a full-waveband spectrum scanner, a spectrum controller and a data terminal, wherein a data output end of the full-waveband spectrum scanner is connected with the spectrum controller, the spectrum controller is electrically connected with the data terminal, the full-waveband spectrum scanner is immersed in a water body for detection, the spectrum controller analyzes and calculates an absorption full-spectrum diagram of sewage according to radiation absorption information transmitted by a spectrometer, and meanwhile, a multiple regression equation model is embedded inside the full-waveband spectrum scanner, so that corresponding target water quality parameter values can be synchronously analyzed and calculated.
In a third aspect, the above-mentioned online rapid detection method for sewage quality is applied to sewage detection.
The water quality parameters of various substances can be detected simultaneously, and the detection time is as short as 15s, so that the result can be obtained.
The invention has the beneficial effects that:
(1) the invention solves the problem of serious time lag of data acquisition of the traditional online water quality monitoring system, the detection process of the invention does not need to sample, and the time for outputting full spectrum data and calculating water quality parameters is about 15 s; the cleaning work of the equipment is carried out by adopting the compressed air cleaning machine, the cleaning period is determined according to the water quality condition, the cleaning time is about 20S (can be set), the detection efficiency is greatly improved, and the real-time acquisition of water quality parameters is realized.
(2) According to the invention, water quality parameter information is obtained through a multiple regression equation model based on full spectrum data, chemical analysis is not needed in the detection process, the consumption of chemical agents is greatly saved, and the purpose of environmental friendliness is realized.
(3) The invention has high automation degree and less daily management and maintenance work, also has the function of remotely monitoring the real-time running state and real-time water quality parameters of the system on line, and brings convenience to the operation and management personnel of the sewage plant.
(4) The detection period of the invention is minimum 2Min, the invention realizes continuous on-line detection, and can simultaneously detect and output COD and Nitrate (NO)3-N), Phosphate (PO)4P), and the like, so that operation management personnel of the sewage plant can master the operation effect of the process conveniently.
(5) The real-time water quality parameters obtained by the invention are beneficial to further optimizing treatment process conditions, improving automation level and realizing intelligent management by combining an intelligent control means in a sewage plant.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the invention and not to limit the invention.
FIG. 1 is a diagram of an actual equipment installation of the detection method of the present invention;
FIG. 2 is a schematic flow chart of the detection method of the present invention;
FIG. 3 is a UV-Vis spectrum of 90 water samples of example 1;
FIG. 4 is a graph of the model internal cross-validation root mean square error of example 1;
FIG. 5 is a graph showing the average contribution of each absorbance to the COD value in the COD prediction model of example 1;
FIG. 6 is a graph of the average contribution of each absorbance to the nitrate value for the nitrate prediction model;
FIG. 7 is a graph comparing COD predicted values with measured values;
FIG. 8 is a graph comparing predicted values and measured values of nitrate;
the system comprises a 1-full-waveband spectrum scanner, a 2-air compression cleaning machine, a 21-cleaning valve, a 22-air compressor, a 3-spectrometer controller and a 4-data terminal.
Detailed Description
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
In a first aspect, an ultraviolet-visible light full-wavelength scanning online rapid detection method for sewage quality comprises the following specific steps:
carrying out full-waveband scanning on the sewage, adopting immersion type direct scanning water body, obtaining the spectral absorption information of the sewage and transmitting the spectral absorption information to a full-waveband spectral detection system;
calculating an absorption full spectrum diagram of the sewage;
obtaining a multiple regression equation of each substance to be measured through multiple regression equation model fitting, wherein the multiple regression equation model is as follows: y isn＝A1*x1+A2*x2+…+A210*x210+…+An*xn(ii) a Wherein n is 215-nFor the target parameter prediction value, A1-AnThe coefficients of the corresponding wavelengths of the models are obtained; the wavelength range of 200-737.5nm, x1-xnThe wavelength of the incident light is selected in the whole wave band, and the wavelength interval of the incident light is 2-3 nm;
and combining the absorption full spectrogram with a multiple regression equation model of each substance to obtain a water quality parameter value.
To reduce equation complexity and improve computational efficiency, full spectrum spectra can be prescreened from individual bands (x)1,x2,…xn) The wavelength with the most obvious spectral absorption is selected. As shown in fig. 3
Different indexes to be detected such as COD, turbidity, chromaticity and the like have the wave band ranges with the highest inertia and the most obvious spectrum absorption, and part of irrelevant wave bands can be screened out in advance during model construction, so that the modeling efficiency is improved.
Compared with the method for selecting specific wave band modeling, the method for detecting the quality of the sewage by using the full wave band has the advantages that the accuracy of a COD (chemical oxygen demand) and nitrate model can be further corrected by selecting a proper pretreatment method in combination with the characteristic wave band absorption of suspended matters and chromaticity.
In some embodiments of the present invention, the full-band scanning has a wavelength range of 200 to 750nm and a wavelength interval of 2.5 nm.
In some embodiments of the present invention, the multiple regression equation model is obtained by fitting a Principal Component Regression (PCR) method or a Partial Least Squares Regression (PLSR) method; preferably PLSR. According to the invention, by comparing the measured values of PLSR and PCR with the standard values and performing error analysis, the fitting effect of the multiple regression equation model of PLSR is better, and the obtained water quality parameter value is more accurate.
In some embodiments of the present invention, the fitting is performed by:
firstly, determining whether the sewage needs to be subjected to spectrum pretreatment according to a spectrogram;
if spectrum pretreatment is needed, the pretreatment is carried out first and then modeling is carried out;
determining model parameters of the optimal fitting effect;
then, within the full wave band of 200-737.5nm, outputting coefficients of a multiple regression equation according to parameters of the optimal fitting effect;
and (4) evaluating the prediction capability of the model.
Preferably, the model parameters are the optimal principal component number, the method for determining the optimal principal component number is determined according to the contribution rate of each principal component of the model and the result of the internal one-out-of-one cross validation root mean square error, and the number of the principal components when the contribution rate of the principal components is accumulated to reach more than 95% and the cross validation Root Mean Square Error (RMSE) is the minimum number is the optimal principal component number.
Preferably, the model prediction capability is based on goodness of fit (R)2) And Root Mean Square Error (RMSEP) determination.
According to the invention, the full-wave band is used for detecting the light absorbance, the characteristic spectrum absorption of the water sample can be obtained by observing the spectrogram, the influence of suspended substances in the water sample on the spectrum can be obtained, whether the spectrum has a base line translation or shift phenomenon or not and the absorption condition of the suspended substances and the chromaticity in the water sample in the wavelength range can be obtained, so that whether the spectrum pretreatment is needed or not is judged, and the accuracy of the spectrum detection is improved.
In a second aspect, the full-waveband spectrum detection system comprises a full-waveband spectrum scanner, a spectrum controller and a data terminal, wherein the data output end of the full-waveband spectrum scanner is connected with the spectrum controller, the spectrum controller is electrically connected with the data terminal, the full-waveband spectrum scanner is immersed in a water body for detection, the spectrum controller analyzes and calculates an absorption full-spectrum diagram of sewage according to radiation absorption information transmitted by a spectrometer, and meanwhile, a multiple regression equation model is embedded inside the full-waveband spectrum detection system, so that corresponding target water quality parameter values can be synchronously analyzed and calculated.
As shown in fig. 2, the full-band spectrometer adopts immersion (directly immersed in a liquid medium) to scan, then transmits the detected absorbance information to the spectrum controller, then the spectrum controller obtains a spectrogram according to the absorbance information, and calculates to obtain a concentration value, the time consumption of the whole process is about 15s, the time is short, the working effect is improved, and then the water quality parameters are transmitted to the data terminal.
The spectrum controller adopted by the invention is matched equipment of the spectrometer.
The spectrum controller can be connected with a network through various communication protocols (such as Ethernet, Wireless Local Area Network (WLAN) and 3G module), and operations such as remote setting of measurement parameters, monitoring of processing effect and the like can be carried out on line through a data terminal. Meanwhile, the spectrum controller supports analog output, Modbus, Profibus, SDI12 and other modes of online parameter information and system logs, and also supports downloading of locally stored data by using a USB drive.
The data terminal is a computer or a computer system, is used for remotely monitoring the running state of the system on line and browsing real-time water quality parameter values, and has the function of continuously storing the measured data to the local. The data terminal can be located in a sewage plant control room, and a user can also use a PC to operate outside the plant.
In some embodiments of the present invention, the full-band spectrum detection system further includes an air compression cleaning machine, the air compression cleaning machine includes an air compressor and a cleaning valve, the air compressor is connected to the spectrum controller through a cable, the air compressor receives an instruction from the spectrum controller, and the air compressor is connected to the cleaning valve, the cleaning valve and the full-band spectrum scanner through air hoses.
According to the invention, the full-wave-band spectrum scanner is cleaned by the air compression cleaning machine.
In some embodiments of the present invention, the cleaning cycle of the full-band spectral scanner by the air compressor cleaner is 50-70min, and the cleaning time is 15-25 s. The cleaning period and the cleaning time can be set according to actual conditions.
In some embodiments of the invention, data analysis software is set in the spectrometer controller, and the data analysis software is R, SAS, SPSS, etc.; preferably R software. The software can analyze and process data.
In a third aspect, the above-mentioned online rapid detection method for sewage quality is applied to sewage detection.
The detection method of the invention can simultaneously detect various pollutants in water, preferably COD and the concentration of metal salt, wherein the metal salt is nitrate or phosphate.
Preferably, the detection time is 14-20 s.
Interpretation of terms:
the Principal Component Analysis (PCA) method recombines a plurality of independent new variables by analyzing and calculating a data matrix, and all the characteristics of the original data matrix can be represented by using a few of the variables, thereby realizing the dimension reduction. The several newly composed variables are called principal components, which are converted from original variables, and are sequentially arranged as a first principal component, a second principal component and the like according to the decreasing order of the acquired variance. The principal component regression method (PCR method) selects the first few principal components meeting the target requirements as independent variables to perform multiple regression modeling.
The Partial Least Squares (PLSR) method has the main advantages of solving the problem of multiple correlations, requiring a small sample size and being useful for predictive analysis. The PLSR method integrates multiple linear regression, canonical correlation analysis and principal component analysis, and the idea is as follows: first, independent principal components t are extracted from independent variables and dependent variables respectively1And u1At the same time, request t1For u is paired1With maximum interpretability, then establishing a principal component t1Multiple regression equations with dependent variables. Compared with the PCR method, the PLSR method has the advantages that a circulating information decomposition and extraction method is adopted, so that the information of the dependent variable can be better summarized while the components are extracted, and the interference of spectral noise is eliminated.
Goodness of fit R2And the fitting degree of the regression straight line to the observed value is referred to.
The root mean square error is the square root of the ratio of the square of the deviation of the predicted value from the true value to the number of observations n.
R2The larger the RMSEP, the smaller the RMSEP, the better the fitting effect of the model, and the higher the prediction precision.
The invention will be further illustrated by the following examples
Example 1
The multiple regression equation model is:
Yn＝An-1*x1+An-2*x2+…+An-215*x215+An-216*x216(n ═ 1, 2, 3, 4); wherein n respectively corresponds to a PCR method COD model, a PLSR method COD model, a PCR method nitrate model, a PLSR method nitrate model and YnFor the target parameter prediction value, An-1-An-216The coefficient of the wavelength corresponding to each model (for example, when n is 1, A)n-1Is A1-1Represents the COD model x of the PCR method1Coefficient (d); the model is constructed by adopting 216 absorbances of 200-737.5nm in total, and x is1-x216The wavelength interval of the incident light is 2.5nm for the selected wavelength of the incident light in the full wavelength band. The symbols in the equation are defined as shown in table 1:
TABLE 1 multiple regression model calculation equations each symbol definition
The experimental water samples are taken from the effluent of a secondary sedimentation tank and the total effluent of tertiary treatment of a certain sewage treatment plant in Qingdao, and the total number of the experimental water samples is 90. COD and Nitrate (NO) of samples in the laboratory3-N) content was quantitatively analyzed, and the corresponding analytical methods and ranges of chemically measured values are shown in Table 2. The COD and nitrate content of the water sample is low, the highest concentration of the total suspended solids is measured to be 6mg/L, and the influence on the scattering interference of the spectrum is small. Experiment 79 groups of data of 90 groups of samples were randomly selected for model training, and the other 11 groups were used for detecting model accuracy.
TABLE 2 COD and nitrate analysis methods and chemical measurement value ranges
As shown in fig. 1 and fig. 2, the specific process of detection is as follows:
the COD and nitrate multiple regression equation model of the present invention was imported into spectrometer controller 3.
The spectrometer controller 3 is provided with device operating parameters.
The air compression cleaning machine 2 of the automatic cleaning equipment is connected, and the installation schematic diagram is shown in figure 3;
connecting the full-waveband spectrum scanner 1 with a spectrometer controller 3 through a probe cable, performing spectrometer calibration work, and keeping a measurement window clean during the calibration work;
and placing the full-waveband spectrum scanner 1 in the effluent of the secondary sedimentation tank of the sewage plant, and carrying out continuous measurement with the period of 2 Min. The wastewater must flood the measurement window of the spectrometer, the optical path of which remains vertical (if installed in the activated sludge aeration basin, the optical path of the measurement window should remain horizontal and the measurement window partially up).
The spectrometer controller 3 receives the spectrum information transmitted by the full-waveband spectrum scanner 1, and automatically analyzes and calculates the full-waveband spectrogram of the sewage, the COD concentration and the nitrate concentration.
Establishing network connection between the spectrometer controller 3 and the data terminal 4;
the calibration types include: 1. performing an offset correction using a point, requiring spectral measurements and laboratory measurements of a sample; 2. performing linear calibration using two points, requiring spectral measurements and laboratory measurements of two samples, recommending the selection of a lower concentration and a higher concentration sample; 3. at least three sample spectral measurements and laboratory measurements are required to perform linearity correction using multiple points.
The automatic cleaning operation that the cleaning cycle is 1h, and the cleaning time is 20 s/time is carried out to the measurement window of full-wave band spectrum scanner 1, and air compression cleaning machine 2 includes purge valve 21 and air compressor machine 22, and the purge valve passes through air piping connection with full-wave band spectrum scanner, purge valve and spectrum appearance controller electric connection.
The connection mode supports Ethernet, Wireless Local Area Network (WLAN) and 3G module. After the network connection is established, a user only needs to input the IP address of the spectrometer controller 3 in a web browser, and the purposes of remotely operating the controller and monitoring the running condition of equipment and simultaneously monitoring various real-time water quality parameters can be achieved on line. Meanwhile, the measurement data is continuously transmitted to the connected data terminal 4, and the measurement result and the log information stored locally in the data terminal 4 can also be downloaded to the USB driver.
The specific model establishing process and the model comparing process are as follows:
(1) the ultraviolet-visible (UV-vis) spectra of 90 samples are shown in FIG. 3, where each curve represents the absorption spectrum of one sample. The wave band of the effective signals obtained by the spectrum is 200-737.5nm, the interval of each absorbance is 2.5nm, and the total number of the absorbances is 216. The absorption of a water sample is mainly concentrated on a wave band of 200-425 nm, the spectrum absorption of the wave band of 425-737.5 nm is little, the wavelength of 215nm and 375nm have obvious characteristic absorption, and the absorption peaks of 250nm and 422.5nm are smaller. The water sample in the research has low suspended matter concentration, small influence on spectrum, good spectrogram stability, almost no base line translation or shift phenomenon, and only a small amount of absorption in 380-737.5 nm characteristic absorption bands of suspended matter and chromaticity. The invention constructs a regression relation equation between the absorbance of 79 water samples at each wavelength of a 200-737.5nm waveband and the concentration values of COD and nitrate of the corresponding water samples based on a PCR method and a PLSR method.
As can be seen from the foregoing, the PCR model and the PLSR model require the selection of the optimal number of components (factors) to ensure the optimal prediction accuracy and good sensitivity of the models. The model component (factor) number is determined according to the contribution rate of each component of the model and the result of cross-validation of the root mean square error by an internal leave-one-out method. The component contribution rate is the percentage of the variance of the principal component in the total variance of the data change, the component contribution rate is accumulated to more than 95%, the number of the components when the root mean square error of the cross validation is minimum is the optimal component number, and the fitting effect of the model is the best at the moment.
Evaluation of model prediction capability based on prediction goodness of fit (R)2) And Root Mean Square Error (RMSEP) determination. Goodness of fit R2The fitting degree of the regression line to the observed value is indicated; the root mean square error is the square root of the ratio of the square of the deviation between the predicted value and the true value to the observation frequency n; r2The larger the RMSEP, the smaller the RMSEP, the better the fitting effect of the model, and the higher the prediction precision.
The inside one-out-of-the-box cross validation root mean square deviation of the two water quality parameter prediction models is shown in fig. 4, and it can be seen from the graph that the cross validation Root Mean Square Error (RMSE) of the prediction models is in a descending trend along with the increase of the number of main components (factors), the descending trend of the PCR model RMSE of COD is obviously slowed down after the number of main components reaches 3, the RMSE value is changed slightly, and a small-amplitude ascending trend appears after the number reaches the minimum value; the RMSE of the nitrate model has a similar trend of variation, and after the principal component number reaches 3, the RMSE fluctuates around the minimum value. The contribution rate and the cumulative contribution rate of each principal component (factor) are shown in table 3, and it can be seen from the table that the first principal component of the PCR model of COD obtains 80.60% of the total variance of change, the second principal component obtains 12.40% of the total variance, the third principal component obtains 6.60% of the total variance, and the cumulative contribution rate of the first 3 principal components reaches 99.60%, which is enough to replace the information of the original variables; meanwhile, when the number of the main components is 3, the corresponding RMSE value of the PCR model is small, and the number of the components of the PCR model of COD is determined to be 3. Similarly, the number of PLSR model factors for determining COD is 4; the number of major components of the nitrate PCR model was 3, and the number of PLSR model factors was 3.
TABLE 3 model principal component (factor) contribution table
(2) Tables 4, 5, 6, and 7 show the coefficients of the multivariate regression equation for the COD model and the nitrate model based on the PCR method and the PLSR method, respectively, using the foregoing values to determine the number of principal components (factors), and the absolute values of the coefficients reflect the weight of the corresponding absorbance to some extent.
TABLE 4 multivariate regression equation coefficients for predicting COD concentration by PCR method
TABLE 5 multivariate regression equation coefficients for COD concentration prediction by PLSR method
TABLE 6 multivariate regression equation coefficients for predicting nitrate concentration by PCR method
TABLE 7 prediction of nitrate multiple regression equation coefficients by PLSR method
(3) And multiplying the regression equation coefficient by the absorbance of 79 wavelengths corresponding to the modeling spectrum, and dividing by 79 to obtain the average contribution value of each absorbance to the water quality parameter, wherein in the figure 5, the average contribution values of each absorbance in the 200-420 nm waveband of the COD prediction model to the COD value are shown, and the average contribution values of the absorbance in the 420-737.5 nm waveband are all less than 1, so that the average contribution values are not shown in the figure. As can be seen from the figure, in the COD prediction model adopting the PCR method, the wave band which has positive correlation with the COD value is mainly concentrated in the wave band of 205-290 nm, the absorbances of the wave band of 322.5-420 nm all have negative correlation, the wavelength of the positive maximum contribution value is 215nm, the wavelength of the negative maximum contribution value is 200nm, the absolute value of the contribution value which is 5.7% (1mg/L) greater than the maximum contribution value is uniformly distributed in the wave band of 200-420 nm, and the wavelength of the contribution value which is 10% (1.726mg/L) greater than the maximum contribution value is mainly concentrated in 200-277.5 nm. Compared with a PCR method, the COD prediction model adopting the PLSR method has similar laws in contribution values, the wave band which is positively correlated with the COD value is mainly concentrated in the wave band of 205-290 nm, the absorbance of the wave band of 322.5-420 nm basically has negative correlation, the wavelength of the positive maximum contribution value is 207.5nm, the wavelength of the negative maximum contribution value is 217.5nm, and the wavelength of which the absolute value of the contribution value is more than 10% (1.943mg/L) of the maximum contribution value is mainly concentrated in 200-277.5 nm. Meanwhile, the variances of 89 absorbance COD contribution values by the PCR method and the PLSR method were 10.72 and 21.97, respectively. Therefore, the characteristic absorption waveband of COD is mainly in the waveband of 200-420 nm, and a COD prediction model adopting the PLSR method has higher sensitivity, so that the prediction precision is better.
The average contribution value of the absorbance of the nitrate prediction model in the 200-350 nm waveband to the COD value is shown in FIG. 6, and the average contribution values of the absorbance in the 350-737.5 nm waveband are all less than 1, so that the average contribution values are not shown in the figure. As can be seen from the figure, in the nitrate prediction model adopting the PCR method and the PLSR method, the wave bands which are positively correlated with the nitrate value are concentrated in the wavelength range of 200-222.5 nm, the absorbances of the wave bands of 322.5-420 nm are all negatively correlated, the absolute values of the absorbance contribution values of the wave bands are all less than 0.0045mg/L, and the characteristic absorption wave band of the nitrate is mainly in the wavelength range of 200-222.5 nm. The variances of the 89 absorbance nitrate contribution values by the PCR method and the PLSR method were 0.00102 and 0.00109, respectively, and the PLSR method was relatively large and was the same as the COD model.
(4) The relationship between the predicted results and the measured values of the COD multiple regression equation using 11 sets of sample data is shown in FIG. 6, and the relationship between the predicted results and the measured values of the nitrate multiple regression equation is shown in FIGS. 7 and 8. Goodness of fit from prediction (R)2) And the result of root mean square deviation (RMSEP), the PLSR method is superior to the PCR method, and a model constructed by using the PLSR method obtains higher R2And lower R of RMSEP, COD model2And RMSEP 0.900 and 3.982mg/L, respectively, R of the nitrate model2And RMSEP was 0.797 and 0.067mg/L, respectively. The model constructed by the PLSR method has the advantages of reducing RMSEP, and the accuracy (RMSEP) is respectively improved by 25 percent and 23 percent. Compared with the COD model, the nitrate model has poor prediction capability because the nitrate content of the water sample is low and the relative error of the prediction result is large. In general, the model constructed by the PLSR method has higher prediction capability, RMSEP is 3.982 and 0.067 respectively, and the purpose of rapidly detecting the content of COD and nitrate in sewage on line can be realized.
Example 1 realizes simultaneous detection of two substances in sewage, obtains a spectrogram through a full spectrum scanner, and then obtains water quality parameters of the substances through a multiple regression equation model of each substance built in a spectrometer controller in combination with the spectrogram.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An ultraviolet-visible light full-wavelength scanning online rapid detection method for sewage quality is characterized in that: the method comprises the following specific steps:
carrying out full-waveband scanning on the sewage, adopting immersion type direct scanning water body, obtaining the spectral absorption information of the sewage and transmitting the spectral absorption information to a full-waveband spectral detection system;
calculating an absorption full spectrum diagram of the sewage;
obtaining a multiple regression equation of each substance to be measured through multiple regression equation model fitting, wherein the multiple regression equation model is as follows: y isn＝A1*x1+A2*x2+…+A210*x210+…+An*xn(ii) a Wherein n is 215-nFor the target parameter prediction value, A1-AnThe coefficients of the corresponding wavelengths of the models are obtained; the wavelength range of 200-737.5nm, x1-xnThe wavelength of the incident light is selected in the whole wave band, and the wavelength interval of the incident light is 2-3 nm;
and combining the absorption full spectrogram with a multiple regression equation model of each substance to obtain a water quality parameter value.
2. The online rapid detection method for sewage quality by ultraviolet-visible light full-wavelength scanning according to claim 1, characterized in that: the wavelength range of the full-wave-band scanning is 200-750 nm, and the wavelength interval is 2.5 nm.
3. The online rapid detection method for sewage quality by ultraviolet-visible light full-wavelength scanning according to claim 1, characterized in that: the multiple regression equation model is obtained by fitting through a principal component regression method or a partial least square regression method; preferably PLSR.
4. The online rapid detection method for sewage quality by ultraviolet-visible light full-wavelength scanning according to claim 3, characterized in that: the fitting process is as follows:
firstly, determining whether the sewage needs to be subjected to spectrum pretreatment according to a spectrogram;
if spectrum pretreatment is needed, the pretreatment is carried out first and then modeling is carried out;
determining model parameters of the optimal fitting effect;
then, within the full wave band of 200-737.5nm, outputting coefficients of a multiple regression equation according to parameters of the optimal fitting effect;
and (4) evaluating the prediction capability of the model.
5. The ultraviolet-visible light full-wavelength scanning online rapid detection method for sewage quality according to claim 4, characterized in that:
the method for determining the optimal main component number comprises the following steps: determining according to the contribution rate of each principal component of the model and the result of cross validation root-mean-square error of an internal one-out-of-one method, wherein the cumulative sum of the contribution rates of the components reaches more than 95%, and the number of the components when the cross validation root-mean-square error is minimum is the optimal principal component number; the evaluation of the model prediction capability is determined according to the goodness of fit and the root mean square error;
alternatively, the model prediction capability is determined from goodness-of-fit and root mean square error.
6. A full-band spectrum detection system is characterized in that: the system comprises a full-wave-band spectrum scanner, a spectrum controller and a data terminal, wherein the data output end of the full-wave-band spectrum scanner is connected with the spectrum controller, the spectrum controller is electrically connected with the data terminal, the full-wave-band spectrum scanner is immersed in a water body for detection, the spectrum controller analyzes and calculates an absorption full spectrogram of sewage according to radiation absorption information transmitted by a spectrometer, and meanwhile, a multiple regression equation model is embedded inside the spectrum controller, so that the corresponding target water quality parameter value can be synchronously analyzed and calculated.
7. The full-band spectral detection system of claim 6, wherein: the full-waveband spectrum detection system further comprises an air compression cleaning machine, the air compression cleaning machine comprises an air compressor and a cleaning valve, the air compressor is connected with the spectrum controller through a cable, the air compressor receives instructions of the spectrum controller, and the air compressor is connected with the cleaning valve, the cleaning valve and the full-waveband spectrum scanner through air hoses.
8. The ultraviolet-visible light full-wavelength scanning online rapid detection method for sewage quality according to claim 6, characterized in that: data analysis software is arranged in the spectrometer controller, and the data analysis software is R, SAS, SPSS and the like; preferably R software.
9. The use of the ultraviolet-visible full-wavelength scanning online rapid detection method for wastewater quality according to claims 1-5 in wastewater detection.
10. The application of the ultraviolet-visible light full-wavelength scanning online rapid detection method for the quality of sewage water in sewage detection is characterized in that: the application of the method in detecting COD and the concentration of metal salt in the sewage is realized, and the metal salt is nitrate or phosphate;
or the detection time is 14-20 s.
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