Water quality monitoring method and system based on full spectrum

Abstract

The invention relates to the technical field of water quality detection, and discloses a water quality monitoring method and system based on a full spectrum, light absorption value II detection at different heights is carried out on each index of water quality in a water body through the full spectrum, normalization processing is carried out on the light absorption value II and a light absorption value I in pure water to obtain an absorbance uniformity value # imgabs0 #, and the absorbance uniformity value # imgabs0 # is calculated. Correlating and weighting the light absorption value II # imgabs1 # and the absorbance uniform value # imgabs2 # at any height, establishing a multiple linear regression model, estimating a regression coefficient # imgabs3 # through a least square method, obtaining a predicted value # imgabs4 #, substituting the predicted value # imgabs4 # into a standard curve regression equation of each index, obtaining a final concentration value of each index, reducing the difference of the light absorption values at different heights during detection, and determining the concentration value of each index. The on-site water quality detection accuracy is improved.

Description

Technical Field

[0001] The present application relates to the technical field of water quality detection, and in particular to a water quality monitoring method and system based on full spectrum. Background Art

[0002] In the detection of various water quality indicators, the traditional chemical analysis method has the problems of long inspection cycle and secondary contamination of inspection reagents, while the spectroscopy method is an efficient and pollution-free detection method. According to the Lambert-Beer law, pollutants of different types and concentrations have different absorption characteristics in the ultraviolet, visible and near-infrared ranges. The characteristic absorption spectra of different water bodies can be obtained by irradiating the water body with a broadband light source (flash xenon lamp) and using a micro-spectrometer for spectrum acquisition. By obtaining the corresponding characteristic absorption spectra of a water body under different pollution states and its corresponding related water quality parameter data such as COD, NH3, TN, TP, etc., after analysis through a variety of algorithms, it is applied to the on-site monitoring of various water quality index parameter data contained in a specific water body.

[0003] When conducting on-site online testing of water bodies, there will be suspended matter that cannot be removed in the test water samples, that is, the test water samples will be affected by turbidity, which will cause light scattering and increase absorbance during the spectral detection process, resulting in low uniformity of the detected absorbance, and ultimately leading to an increase or decrease in the concentration of various water quality indicators detected, and a decrease in detection accuracy; compared with laboratory testing, on-site testing uses a large range of detection tubes to improve the detection accuracy of water bodies. The use of a large range of detection tubes will cause the presence of suspended matter in the water, and the suspended matter will be distributed at various heights in the detection tubes. The current spectral detection mainly calculates the concentration of various water quality indicators based on the absorbance value obtained by the light source at the same height, but ignores the differences in absorbance values ​​of water bodies at different heights, which increases the error effect of suspended matter on the concentration of various water quality indicators.

[0004] In view of this, a water quality monitoring method and system based on full spectrum are proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a water quality monitoring method and system based on full spectrum, which detects the absorbance values ​​Ⅱ of various water quality indicators in the water body at different heights through full spectrum, and normalizes them with the absorbance value Ⅰ in pure water to obtain the average absorbance value. , and then the absorbance value II at any height and the average absorbance Carry out correlation, weight, establish multivariate linear regression model, and estimate regression coefficients by least squares method , get the predicted value Substituting into the standard curve regression equation of each indicator, the final concentration value of each indicator is obtained, which reduces the difference in absorbance values ​​at different heights during detection and improves the accuracy of water quality detection in on-site water bodies.

[0006] In order to solve the above technical problems, the present invention adopts the following solutions: A water quality monitoring method based on full spectrum comprises the following steps: S1, obtaining the spectrum data of pure water, the spectrum data including the wavelength and the absorbance value I corresponding to each water quality index, the absorbance value I is used as the maximum upper limit value A of the absorbance uniformity corresponding to each water quality index H ; S2, obtain the absorbance values ​​at different heights during on-site water testing II: The on-site water body is tested under full spectrum conditions to obtain several absorbance values ​​corresponding to several heights of each indicator ⅡA1, A2, A3...A n ; Differences between adjacent absorbance values ​​Ⅱ among several absorbance values ​​Ⅱ, and select the maximum difference of absorbance value Ⅱ as the minimum lower limit value A of absorbance uniformity. L ; S3, obtain uniform data within the absorbance value interval II at different heights: The difference between several adjacent absorbance values ​​Ⅱ obtained at different heights in the on-site water body through full spectrum detection is used as the absorbance uniformity test value A T , according to the minimum lower limit of absorbance uniformity A L , Maximum upper limit of absorbance uniformity A H , Absorption uniformity test value A T Normalization processing is performed to obtain the average absorbance value corresponding to different heights of each indicator during on-site water body detection , the average absorbance value Uniform data used to qualitatively characterize the uniformity of absorbance during detection; S4, correct the uniform data of water indicators: The calculation process of the correlation with each water quality index is as follows: through the absorbance value II at any height and the average absorbance Calculate the correlation, where the correlation of absorbance value II is calculated by Pearson's correlation coefficient; The calculation process of the absorbance value difference is as follows: and the average absorbance Calculate the difference in absorbance values; S5, establish a multivariate linear regression model, estimate the regression coefficients by the least squares method, and calculate the calibrated prediction values ​​by the regression coefficients; S6, establishing a standard curve regression equation between standard control solutions of different concentrations of each water quality index and the absorbance value, and substituting the predicted value into the standard curve regression equation.

[0007] Further preferably, the normalization process is to treat the absorbance value I obtained by pure water detection, the maximum difference of several adjacent absorbance values ​​II obtained by detecting various indicators of the on-site water body at different heights, and the difference of several adjacent absorbance values ​​II obtained by detecting various indicators of the on-site water body at different heights as a data set for calculation processing, specifically: =(A H -A T ) / (A H - A L ); in, Indicates the average value of absorbance; A H Indicates the upper limit of absorbance uniformity; A L Indicates the lowest limit of absorbance uniformity; A T Indicates the absorbance uniformity test value.

[0008] Further preferably, the correlation of the absorbance value II is calculated by the Pearson correlation coefficient, specifically: ; in, Represents the correlation of absorbance II coefficient, , Respectively represent the absorbance value of each indicator of the on-site water body at any height Ⅱ and the average absorbance , represents the covariance, , Represents the absorbance value at any height Ⅱ and the average absorbance The standard deviation of the data set, The value of is [-1,1], A value close to 1 indicates a strong positive correlation, a value close to -1 indicates a strong negative correlation, and a value close to 0 indicates no linear correlation.

[0009] Further preferably, by any height of absorbance II and the average absorbance Calculate the difference in absorbance II ; in, Indicates the difference in absorbance value II, , Respectively represent the absorbance value II and The central absorbance value is Ⅱ.

[0010] Further preferably, the step S4 further comprises the following steps: The absorbance value II at any height between the absorbance values ​​II and the average absorbance The correlation between them is used as an edge, and the weight of the edge is calculated based on the correlation and the difference in absorbance value II to construct a graph ;in, Represents a collection of nodes. represents the combination of edges, Represents the weight set of edges; the weight of the edge is calculated by the difference between the correlation and the absorbance value II: ; ; in, Represents edge The weight of Represents the parameter that controls the effect of height difference on weight, and the edge represents the absorbance value at any height Ⅱ and the average absorbance The relationship between the nodes of the absorption coefficient, Indicates the difference in absorbance value II, Indicates the correlation of absorbance value II coefficient.

[0011] Further preferably, in step S5, the spectral data of each water quality index of the on-site water body is taken as a spectral sample, and the absorbance value II at any height in each spectral sample is taken as a matrix , taking the average absorbance value of each sample at different heights as the response vector , establish a multiple linear regression model: ; represents the regression coefficient, represents the error term.

[0012] Further preferably, the regression coefficients are estimated by the least squares method ;in, Represents the transpose of a matrix; Calibrated predicted values .

[0013] Further preferably, obtaining the standard curve regression equation comprises the following steps: S601, obtain standard reference solutions of multiple water quality indicators, dilute them at different times to obtain standard reference solutions of different water quality indicators with different concentration gradients, and test each standard reference solution in the full spectrum band to obtain multiple absorbance values ​​A S And fit the absorbance value A S -Concentration C standard curve regression equation; S602, the calibrated predicted value Substitute into the standard curve regression equation to obtain the concentration value of each water quality index.

[0014] A full-spectrum-based water quality monitoring system adopts the above-mentioned full-spectrum-based water quality monitoring method, and the full-spectrum-based water quality monitoring system includes: The water body full spectrum monitoring module is used to obtain the spectrum data of the on-site water body and pure water; the spectrum data of the on-site water body includes different heights when each water quality index is detected and the absorbance values ​​corresponding to different heights II; The water body full spectrum analysis module is used to obtain standard control solutions of different concentrations of each indicator and fit the absorbance value A S -Concentration C standard curve regression equation; after analyzing and processing the corresponding absorbance values ​​Ⅱ obtained when detecting various indicators at different heights in the on-site water body, generate the calibrated predicted value , the calibrated predicted value Substitute the absorbance value A S - The concentration values ​​of various water quality indicators are obtained from the regression equation of the concentration C standard curve; The water body full spectrum feedback module is used to feed back the concentration values ​​of various water quality indicators obtained by the water body full spectrum analysis module to the terminal for display.

[0015] Further preferably, the water body full spectrum analysis module includes: Normalization processing module, used to establish the maximum upper limit value A of the absorbance uniformity corresponding to each indicator in pure water H The minimum lower limit of the uniformity of absorbance of each indicator in the on-site water body A L Get the average absorbance value corresponding to different heights of each indicator; Weight analysis module for establishing absorbance values ​​at arbitrary heights Ⅱ and the average absorbance The correlation between them and the difference in absorbance value II were calculated, and the weight analysis of the correlation and the difference in absorbance value II was performed; Multiple linear regression model building module, used to build multiple linear regression models; A regression coefficient estimation module is used to estimate the regression coefficient based on the least squares method to obtain a calibrated prediction value; The concentration determination module of each water quality index is used to substitute the calibrated predicted value into the absorbance value A S -The concentration of each water quality index in the on-site water body is determined by the concentration C standard curve regression equation.

[0016] The beneficial effects of the present invention are as follows: the present invention establishes the minimum lower limit value A of the absorbance uniformity by obtaining the absorbance values ​​II of various indicators at different heights in the on-site water body and the absorbance values ​​I of various indicators of pure water. L, Maximum upper limit of absorbance uniformity A H , Absorption uniformity test value A T The normalization process is performed to obtain the average absorbance value. , and then through the absorbance value II at any height and the average absorbance Calculate the correlation and absorbance value difference, analyze the weight, establish a multivariate linear regression model, estimate the regression coefficient by the least squares method to obtain the calibrated predicted value, substitute the predicted value into the standard curve regression equation to obtain the concentration value of each water quality index. Reduce the difference in absorbance values ​​at different heights in the detection tube during detection, and improve the accuracy of water quality detection in the on-site water body. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of a process of a water quality monitoring method based on full spectrum provided in Example 1 of the present application; Figure 2 A schematic diagram of an implementation of S6 in a water quality monitoring method based on full spectrum provided in Example 1 of the present application; Figure 3 A schematic diagram of a full-spectrum water quality monitoring system provided in Example 2 of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] The relative arrangement of components and steps, the numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

[0020] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0021] Additionally, descriptions of well-known structures, functions, and configurations may be omitted for clarity and conciseness.One of ordinary skill in the art will recognize that various changes and modifications may be made to the examples described herein without departing from the spirit and scope of the present disclosure.

[0022] Technologies, methods, and apparatus known to ordinary technicians in the relevant field may not be discussed in detail, but where appropriate, such technologies, methods, and apparatus should be considered part of the authorization specification.

[0023] In all examples shown and discussed herein, any specific value should be interpreted as merely exemplary and not as limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0024] Example 1 A water quality monitoring method based on full spectrum, referring to Figure 1 As shown, the following steps are included: S1, obtaining the spectrum data of pure water, the spectrum data including the wavelength and the absorbance value I corresponding to each water quality index, the absorbance value I is used as the maximum upper limit value A of the absorbance uniformity corresponding to each water quality index H .

[0025] Since there is no suspended matter in pure water, when the full spectrum is used to detect the absorbance of pure water, the absorbance of pure water at any height to the light source is consistent, that is, the same absorbance value I is measured at any height, and the spectrum data measured in pure water is used as the reference for on-site water body detection. Therefore, when detecting the absorbance values ​​of multiple indicators of pure water, there is a maximum upper limit value A of the absorbance uniformity corresponding to each water quality indicator. H , through A H The highest and lowest absorbance uniformity indices were used as normalization indicators to obtain uniform absorbance data at different heights of the on-site water body.

[0026] It should be noted that the absorbance values ​​of these multiple indicators include: COD, NH3, TN, TP, etc., so there is a maximum upper limit value A of the absorbance uniformity of multiple indicators. H1 , A H2 , A H3 …A Hn ; The highest upper limit value of the absorbance uniformity of the corresponding single indicator is normalized with the lowest lower limit value of the absorbance uniformity of the corresponding indicator to obtain normalized processing data of multiple indicators.

[0027] At the same time, pure water absorbs the spectrum in the range of 200nm~850nm to obtain water quality index parameter data such as COD, NH3, TN, TP, etc., which are used for subsequent on-site water body comparison. Each water quality index has a certain absorbance in a specific band and light type. A certain correlation is established based on the absorbance value obtained after each water quality index and spectrum detection, and multiple water quality index parameter values ​​of the on-site water body are calculated through the correlation.

[0028] Specifically, the spectral data obtained after pure water testing are: A(COD), A(NH3), A(TN), A(TP), and this spectral data is used as the maximum upper limit value A of the absorbance uniformity of each indicator. H .

[0029] S2, obtain the absorbance values ​​at different heights during on-site water testing II: The on-site water body is tested under full spectrum conditions to obtain several absorbance values ​​corresponding to several heights of each indicator ⅡA1, A2, A3...A n ; Differences between adjacent absorbance values ​​Ⅱ among several absorbance values ​​Ⅱ, and select the maximum difference of absorbance value Ⅱ as the minimum lower limit value A of absorbance uniformity. L .

[0030] The absorbance value II here refers to the absorbance value data of each single indicator in water quality at different heights. Since the presence of suspended matter in the on-site water body will affect the absorbance value during detection, the absorbance value of different heights (such as h1, h2, h3…h n ) to detect absorbance, subtract the absorbance values ​​at adjacent heights to obtain multiple difference data, and select the maximum difference from the multiple difference data. The maximum difference indicates that there is a maximum change trend in the absorbance values ​​at adjacent heights, so the maximum difference can be used to calibrate that there are more suspended matter in this height range, thereby affecting the accuracy of the absorbance value and causing the concentrations of multiple water quality indicators to be affected.

[0031] The different heights here represent the heights in the longitudinal direction of the detection tube when the detection tube containing the water sample to be tested is tested by ultraviolet light, infrared light, and fluorescence bands, and the different heights are divided equally.

[0032] Specifically, the spectral data of each indicator at different heights in the on-site water body are: COD: A h1 ,A h2 ,A h3 …A hn ; NH3: 1 A h1 , 1 A h2 , 1 A h3 … 1 A hn ; TN: 2 A h1 , 2 A h2 , 2 A h3 … 2 A hn ; TP: 3 A h1 , 3 A h2 , 3 A h3 … 3 Ahn .

[0033] S3, obtain uniform data within the absorbance value interval II at different heights: The difference between several adjacent absorbance values ​​Ⅱ obtained at different heights in the on-site water body through full spectrum detection is used as the absorbance uniformity test value A T , according to the minimum lower limit of absorbance uniformity A L , Maximum upper limit of absorbance uniformity A H , Absorption uniformity test value A T Normalization processing is performed to obtain the average absorbance value corresponding to different heights of each indicator during on-site water body detection , the average absorbance value Uniform data used to qualitatively characterize the uniformity of absorbance during detection.

[0034] In some preferred embodiments, the normalization process is to treat the absorbance value I obtained by pure water detection, the maximum difference of several adjacent absorbance values ​​II obtained by detecting various indicators of the on-site water body at different heights, and the difference of several adjacent absorbance values ​​II obtained by detecting various indicators of the on-site water body at different heights as a data set for calculation and processing, specifically: =(A H -A T ) / (A H - A L ); in, Indicates the average value of absorbance; A H Indicates the upper limit of absorbance uniformity; A L Indicates the lowest limit of absorbance uniformity; A T Indicates the absorbance uniformity test value.

[0035] The maximum upper limit value A of the absorbance uniformity of pure water detection H , the minimum lower limit of absorbance uniformity for on-site water testing A L Compared with the uniform absorbance test value A in the field water sample T Normalize and get the average value of absorbance The absorbance uniformity test value A of the difference between several adjacent absorbance values ​​Ⅱ T Put it on the same scale [0,1] or [-1,1] to reduce the scale difference of absorbance values ​​Ⅱ at different heights.

[0036] It should be noted that the absorbance average value of each water quality index is normalized here, and the specific indexes are no longer listed one by one. , , , wait.

[0037] S4, correct the uniform data of water indicators: The calculation process of the correlation with each water quality index is as follows: through the absorbance value II at any height and the average absorbance Calculate the correlation, where the correlation of absorbance value II is calculated by Pearson's correlation coefficient; The calculation process of the absorbance value difference is as follows: and the average absorbance Calculate the difference in absorbance.

[0038] In some preferred embodiments, the correlation of the absorbance value II is calculated by the Pearson correlation coefficient, specifically: ; in, Represents the correlation of absorbance II coefficient, , Respectively represent the absorbance value of each indicator of the on-site water body at any height Ⅱ and the average absorbance , represents the covariance, , Represents the absorbance value at any height Ⅱ and the average absorbance The standard deviation of the data set, The value of is [-1,1], A value close to 1 indicates a strong positive correlation, a value close to -1 indicates a strong negative correlation, and a value close to 0 indicates no linear correlation.

[0039] In some preferred embodiments, by any height of absorbance II and the average absorbance Calculate the difference in absorbance II ; in, Indicates the difference in absorbance value II, , Respectively represent the absorbance value II and The central absorbance value is Ⅱ.

[0040] By calculating the absorbance value at any height Ⅱ Average absorbance The correlation between the two is analyzed to provide conditions for the subsequent prediction of the value. The difference in absorbance value II is used to analyze the difference between the two and quantify the distance between the two on the spectrum.

[0041] The step S4 further comprises the following steps: The absorbance value II at any height between the absorbance values ​​II and the average absorbance The correlation between them is used as an edge, and the weight of the edge is calculated based on the correlation and the difference in absorbance value II to construct a graph ;in, Represents a collection of nodes. represents the combination of edges, Represents the weight set of edges; the weight of the edge is calculated by the difference between the correlation and the absorbance value II; the weight of the edge is calculated by the difference between the correlation and the absorbance value II: ; ; in, Represents edge The weight of Represents the parameter that controls the effect of height difference on weight, and the edge represents the absorbance value at any height Ⅱ and the average absorbance The relationship between the nodes of the absorption coefficient, Indicates the difference in absorbance value II, Indicates the correlation of absorbance value II coefficient.

[0042] S5, establish a multivariate linear regression model, estimate the regression coefficients by the least squares method, and calculate the calibrated predicted values ​​using the regression coefficients.

[0043] Further preferably, in step S5, the spectral data of each water quality index of the on-site water body is taken as a spectral sample, and the absorbance value II at any height in each spectral sample is taken as a matrix , the average absorbance value of each sample at different heights is taken as , establish a multiple linear regression model: ; represents the regression coefficient, represents the error term.

[0044] Further preferably, the regression coefficients are estimated by the least squares method ;in, Represents the transpose of a matrix; Calibrated predicted values .

[0045] S6, establish the standard curve regression equation of different concentrations of standard reference solutions and absorbance values ​​of each water quality index, substitute the predicted value into the standard curve regression equation, and refer to Figure 2 shown.

[0046] S601, obtain standard reference solutions of multiple water quality indicators, dilute them at different times to obtain standard reference solutions of different water quality indicators with different concentration gradients, and test each standard reference solution in the full spectrum band to obtain multiple absorbance values ​​A S And fit the absorbance value A S -Concentration C standard curve regression equation; S602, the calibrated predicted value Substitute into the standard curve regression equation to obtain the concentration value of each water quality index.

[0047] Specifically, after the on-site water enters the detection tube, the absorbance values ​​Ⅱ at different heights in the detection tube are obtained. The regression coefficients in the multivariate linear regression model are estimated by the least squares method based on normalization, correlation, absorbance value Ⅱ difference, weight, and analysis. , and then converted to obtain the calibrated predicted value , this predicted value Substitute into the corresponding standard curve regression equation to obtain the final corresponding indicator concentration value.

[0048] Predicted values ​​after calibration in field water have , , , Substituting into the standard curve regression equation, the concentration values ​​obtained are C (COD), C (NH3), C (TN), and C (TP).

[0049] Example 2 This embodiment 2 is a water quality monitoring system based on full spectrum. Figure 3 , used to execute the full-spectrum-based water quality monitoring method described in Example 1, the full-spectrum-based water quality monitoring system comprises: The water body full spectrum monitoring module is used to obtain the spectrum data of the on-site water body and pure water; the spectrum data of the on-site water body includes the absorbance values ​​II corresponding to different heights when various water quality indicators are detected.

[0050] The water body full spectrum analysis module is used to obtain standard control solutions of different concentrations of each indicator and fit the absorbance value A S -Concentration C standard curve regression equation; after analyzing and processing the corresponding absorbance values ​​Ⅱ obtained when detecting various indicators at different heights in the on-site water body, generate the calibrated predicted value , the calibrated predicted value Substitute the absorbance value A S -Concentration C standard curve regression equation, the concentration values ​​of various water quality indicators are obtained.

[0051] The water body full spectrum analysis module comprises: Normalization processing module, used to establish the maximum upper limit value A of the absorbance uniformity corresponding to each indicator in pure water H The minimum lower limit of the uniformity of absorbance of each indicator in the on-site water body A L Get the average absorbance value corresponding to different heights of each indicator; Weight analysis module for establishing absorbance values ​​at arbitrary heights Ⅱ and the average absorbance The correlation between them and the difference in absorbance value II were calculated, and the weight analysis of the correlation and the difference in absorbance value II was performed; Multiple linear regression model building module, used to build multiple linear regression models; A regression coefficient estimation module is used to estimate the regression coefficient based on the least squares method to obtain a calibrated prediction value; The concentration determination module of each water quality index is used to substitute the calibrated predicted value into the absorbance value A S -The concentration of each water quality index in the on-site water body is determined by the concentration C standard curve regression equation.

[0052] The water body full spectrum feedback module is used to feed back the concentration values ​​of various water quality indicators obtained by the water body full spectrum analysis module to the terminal for display.

[0053] The above description is only a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as a preferred embodiment as above, it is not intended to limit the present invention. Any technician familiar with the profession can make some changes or modifications to equivalent embodiments of equivalent changes using the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A water quality monitoring method based on full spectrum, characterized in that: The following steps are involved: S1, obtaining the spectrum data of pure water, the spectrum data including the wavelength and the absorbance value I corresponding to each water quality index, the absorbance value I is used as the maximum upper limit value A of the absorbance uniformity corresponding to each water quality index H ; S2, obtain the absorbance values ​​at different heights during on-site water testing II: The water body on site is tested under full spectrum conditions to obtain several absorbance values ​​corresponding to several heights of each indicator ⅡA1, A2, A3 ...A n ; Differences between adjacent absorbance values ​​Ⅱ among several absorbance values ​​Ⅱ, and select the maximum difference of absorbance value Ⅱ as the minimum lower limit value A of absorbance uniformity. L ; S3, obtain uniform data within the absorbance value interval II at different heights: The difference between several adjacent absorbance values ​​Ⅱ obtained at different heights in the on-site water body through full spectrum detection is used as the absorbance uniformity test value A T , according to the minimum lower limit of absorbance uniformity A L , Maximum upper limit of absorbance uniformity A H , Absorption uniformity test value A T Normalization processing is performed to obtain the average absorbance value corresponding to different heights of each indicator during on-site water body detection , the average absorbance value Uniform data used to qualitatively characterize the uniformity of absorbance during detection; S4, correct the uniform data of water indicators: The calculation process of the correlation with each water quality index is as follows: through the absorbance value II at any height and the average absorbance Calculate the correlation, where the correlation of absorbance value II is calculated by Pearson's correlation coefficient; The calculation process of the absorbance value difference is as follows: and the average absorbance Calculate the difference in absorbance values; S5, establish a multivariate linear regression model, estimate the regression coefficients by the least squares method, and calculate the calibrated prediction values ​​by the regression coefficients; S6, establishing a standard curve regression equation between standard control solutions of different concentrations of each water quality index and the absorbance value, and substituting the predicted value into the standard curve regression equation.

2. A water quality monitoring method based on full spectrum according to claim 1, characterized in that: The normalization process is to treat the absorbance value I obtained by pure water detection, the maximum difference of several adjacent absorbance values ​​II obtained by detecting various indicators of the on-site water body at different heights, and the difference of several adjacent absorbance values ​​II obtained by detecting various indicators of the on-site water body at different heights as a data set for calculation and processing, specifically: =(A H -A T ) / (A H - A L ); in, Indicates the average value of absorbance; A H Indicates the upper limit of absorbance uniformity; A L Indicates the lowest limit of absorbance uniformity; A T Indicates the absorbance uniformity test value.

3. A water quality monitoring method based on full spectrum according to claim 1, characterized in that: The correlation of the absorbance value II is calculated by the Pearson correlation coefficient, specifically: ； in, Represents the correlation of absorbance II coefficient, , Respectively represent the absorbance value of each indicator of the on-site water body at any height Ⅱ and the average absorbance , represents the covariance, , Represents the absorbance value at any height Ⅱ and the average absorbance The standard deviation of the data set, The value of is [-1,1].

4. A water quality monitoring method based on full spectrum according to claim 3, characterized in that: Absorbance value at any height Ⅱ and the average absorbance Calculate the difference in absorbance II ; in, Indicates the difference in absorbance value II, , Respectively represent the absorbance value II and The central absorbance value is Ⅱ.

5. A water quality monitoring method based on full spectrum according to claim 4, characterized in that: The step S4 further comprises the following steps: The absorbance value II at any height between the absorbance values ​​II and the average absorbance The correlation between them is used as an edge, and the weight of the edge is calculated based on the correlation and the difference in absorbance value II to construct a graph ;in, Represents a collection of nodes. represents the combination of edges, Represents the weight set of edges; the weight of the edge is calculated by the difference between the correlation and the absorbance value II: ； ； in, Represents edge The weight of Represents the parameter that controls the effect of height difference on weight, and the edge represents the absorbance value at any height Ⅱ and the average absorbance The relationship between the nodes of the absorption coefficient, Indicates the difference in absorbance value II, Indicates the correlation of absorbance value II coefficient.

6. A water quality monitoring method based on full spectrum according to claim 4, characterized in that: In step S5, the spectral data of each water quality index of the on-site water body is taken as a spectral sample, and the absorbance value II at any height in each spectral sample is taken as a matrix , taking the average absorbance value of each sample at different heights as the response vector , establish a multiple linear regression model: ; represents the regression coefficient, represents the error term.

7. A water quality monitoring method based on full spectrum according to claim 6, characterized in that: Estimation of regression coefficients by least squares method ;in, Represents the transpose of a matrix; Calibrated predicted values .

8. A water quality monitoring method based on full spectrum according to claim 7, characterized in that: The acquisition of the standard curve regression equation includes the following steps: S601, obtain standard reference solutions of multiple water quality indicators, dilute them at different times to obtain standard reference solutions of different water quality indicators with different concentration gradients, and test each standard reference solution in the full spectrum band to obtain multiple absorbance values ​​A S And fit the absorbance value A S -Concentration C standard curve regression equation; S602, the calibrated predicted value Substitute into the standard curve regression equation to obtain the concentration value of each water quality index.

9. A water quality monitoring system based on full spectrum, characterized in that: Used to perform the full-spectrum-based water quality monitoring method according to any one of claims 1 to 8, the full-spectrum-based water quality monitoring system comprises: The water body full spectrum monitoring module is used to obtain the spectrum data of the on-site water body and pure water; the spectrum data of the on-site water body includes different heights when each water quality index is detected and the absorbance values ​​corresponding to different heights II; The water body full spectrum analysis module is used to obtain standard control solutions of different concentrations of each indicator and fit the absorbance value A S -Concentration C standard curve regression equation; after analyzing and processing the corresponding absorbance values ​​Ⅱ obtained when detecting various indicators at different heights in the on-site water body, generate the calibrated predicted value , the calibrated predicted value Substitute the absorbance value A S - The concentration values ​​of various water quality indicators are obtained from the regression equation of the concentration C standard curve; The water body full spectrum feedback module is used to feed back the concentration values ​​of various water quality indicators obtained by the water body full spectrum analysis module to the terminal for display.

10. A water quality monitoring system based on full spectrum according to claim 9, characterized in that: The water body full spectrum analysis module comprises: Normalization processing module, used to establish the maximum upper limit value A of the absorbance uniformity corresponding to each indicator in pure water H The minimum lower limit of the uniformity of absorbance of each indicator in the on-site water body A L Get the average absorbance value corresponding to different heights of each indicator; Weight analysis module for establishing absorbance values ​​at arbitrary heights Ⅱ and the average absorbance The correlation between them and the difference in absorbance value II were calculated, and the weight analysis of the correlation and the difference in absorbance value II was performed; Multiple linear regression model building module, used to build multiple linear regression models; A regression coefficient estimation module is used to estimate the regression coefficient based on the least squares method to obtain a calibrated prediction value; The concentration determination module of each water quality index is used to substitute the calibrated predicted value into the absorbance value A S -The concentration of each water quality index in the on-site water body is determined by the concentration C standard curve regression equation.

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