CN112986169A - Ultraviolet spectrum pollutant classification detection method based on sampling contourlet transformation - Google Patents
Ultraviolet spectrum pollutant classification detection method based on sampling contourlet transformation Download PDFInfo
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- 239000003344 environmental pollutant Substances 0.000 title claims abstract description 63
- 231100000719 pollutant Toxicity 0.000 title claims abstract description 63
- 238000001514 detection method Methods 0.000 title claims abstract description 30
- 238000002211 ultraviolet spectrum Methods 0.000 title claims abstract description 18
- 238000005070 sampling Methods 0.000 title claims abstract description 15
- 230000009466 transformation Effects 0.000 title abstract description 5
- 238000001228 spectrum Methods 0.000 claims abstract description 35
- 238000013145 classification model Methods 0.000 claims abstract description 16
- 238000012545 processing Methods 0.000 claims abstract description 15
- 238000004458 analytical method Methods 0.000 claims abstract description 6
- 238000005259 measurement Methods 0.000 claims abstract description 5
- 239000011159 matrix material Substances 0.000 claims description 44
- 238000012360 testing method Methods 0.000 claims description 36
- 238000000034 method Methods 0.000 claims description 22
- 230000003595 spectral effect Effects 0.000 claims description 22
- 238000009499 grossing Methods 0.000 claims description 11
- 238000006243 chemical reaction Methods 0.000 claims description 9
- 238000004422 calculation algorithm Methods 0.000 claims description 6
- KMUONIBRACKNSN-UHFFFAOYSA-N potassium dichromate Chemical compound [K+].[K+].[O-][Cr](=O)(=O)O[Cr]([O-])(=O)=O KMUONIBRACKNSN-UHFFFAOYSA-N 0.000 claims description 6
- 238000012549 training Methods 0.000 claims description 6
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 6
- 239000002957 persistent organic pollutant Substances 0.000 claims description 3
- 238000012706 support-vector machine Methods 0.000 claims description 3
- 238000004448 titration Methods 0.000 claims description 3
- 230000002596 correlated effect Effects 0.000 claims description 2
- 230000009286 beneficial effect Effects 0.000 abstract description 4
- 238000002835 absorbance Methods 0.000 abstract description 2
- 230000008569 process Effects 0.000 description 5
- 230000009471 action Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 230000002349 favourable effect Effects 0.000 description 2
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000004611 spectroscopical analysis Methods 0.000 description 1
- 238000000870 ultraviolet spectroscopy Methods 0.000 description 1
- 238000007704 wet chemistry method Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/33—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using ultraviolet light
Abstract
The invention discloses an ultraviolet spectrum pollutant classification detection method based on sampling contourlet transformation, which comprises the following steps: firstly, measuring known pollutants; step two, establishing a classification model; step three, obtaining a sample; step four, concentration measurement; step five, detecting the spectrum; step six, data processing; step seven, establishing a concentration model; step eight, classified detection; step nine, concentration determination; the invention not only detects and classifies the pollutants contained in the sample through the classification model, but also obtains the concentration of the pollutants according to the absorbance of ultraviolet rays by utilizing the concentration model, thereby being beneficial to improving the practicability of the invention, rapidly distinguishing the pollutant types through a spectrum direct contrast analysis method and being beneficial to improving the working efficiency.
Description
Technical Field
The invention relates to the technical field of water quality monitoring, in particular to an ultraviolet spectrum pollutant classification detection method based on sampling contourlet transformation.
Background
Ultraviolet spectroscopy, also known as ultraviolet and visible spectroscopy, abbreviated as UV, is one of the most widely used methods for determining molecular structures in organic chemistry.
The application range of the ultraviolet spectrum is very wide, along with the continuous progress of modern science and technology, the ultraviolet spectrum pollutant classification detection method also has application in water quality detection, the pollutant classification detection in water on the market generally adopts a wet chemistry method, secondary pollution is very easy to cause, thereby the ultraviolet spectrum pollutant classification detection method based on sampling contourlet transform is produced, however, the classification detection method on the market is easily influenced by stray light in a detection sample in the detection process, the detection result is interfered, the detection error is increased, the pollution type in the sample is detected singly during detection, the concentration of the pollutant cannot be judged, the practicability is lower, time and labor are wasted in the classification detection process, and the efficiency of classification detection is greatly reduced.
Disclosure of Invention
The invention aims to provide a method for classifying and detecting ultraviolet spectrum pollutants based on sampling contourlet transformation, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: an ultraviolet spectrum pollutant classification detection method based on sampling profile wave conversion comprises the following steps: firstly, measuring known pollutants; step two, establishing a classification model; step three, obtaining a sample; step four, concentration measurement; step five, detecting the spectrum; step six, data processing; step seven, establishing a concentration model; step eight, classified detection; step nine, concentration determination;
in the first step, firstly, a UV spectrometer is used for detecting and analyzing a standard water sample containing a single pollutant to obtain the spectral characteristics of the standard pollutant, and a spectral matrix of the standard pollutant is established as a reference;
in the second step, the spectrum matrix of the standard pollutant obtained in the first step is brought into a support vector machine, and a classification model is obtained through continuous iterative learning of data;
in the third step, a plurality of unknown pollutants to be detected are obtained as samples;
in the fourth step, the unknown pollutant sample in the third step is divided into an experimental sample and a test sample according to the proportion of 7: 3, the COD value of the experimental sample is measured by using a potassium dichromate titration method, and a data matrix of the COD value of the experimental sample is generated;
in the fifth step, the experimental sample and the test sample in the fourth step are respectively measured by using a UV spectrometer to obtain the spectral characteristics of the unknown pollutants, and the spectral matrix of the experimental sample and the spectral matrix of the test sample are respectively established;
in the sixth step, the spectrum matrix of the experimental sample and the spectrum matrix of the test sample obtained in the fifth step are respectively subjected to smoothing treatment, derivative treatment and SNV treatment, and the obtained spectrum matrix is reserved after the treatment is finished;
in the seventh step, the spectrum matrix of the experimental sample processed in the sixth step is used as a training set, the spectrum matrix of the test sample is used as a test set, and the training set and the data matrix of the COD value of the experimental sample measured in the third step are respectively subjected to iterative computation by using a computer to obtain a concentration model;
in the eighth step, the spectrum matrix of the test sample obtained in the fifth step is substituted into the classification model obtained in the second step, so that the pollutant types in the test sample are obtained;
and in the ninth step, substituting the spectrum matrix of the test sample obtained in the fifth step into the concentration model obtained in the seventh step to obtain the pollutant concentration data of the test sample.
According to the technical scheme, in the sixth step, the algorithm of the smoothing processing is a moving average method or a Savitzky-Go-lay convolution smoothing method.
According to the above technical solution, in the sixth step, the derivative processing is one of a first derivative and a second derivative.
According to the above technical solution, in the sixth step, the SNV processing formula is: where is the average of the ith sample, m is the number of wavelength points of the ultraviolet spectral curve, and i is the number of samples.
According to the technical scheme, in the seventh step, the COD value is used as the concentration index of the organic pollutants.
According to the above technical solution, in the seventh step, an algorithm of iterative computation is partial least squares PLS.
According to the above technical solution, in the eighth step, the classification method of the classification model is a spectral direct contrast analysis method, that is, a spectral matrix of the test sample and a reference matrix of a single pollutant are linearly correlated, a fitting straight line is used as a standard, and if the standard is more than 0.99, the single pollutant is present in the test sample.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the method, the sample data is subjected to smoothing processing, derivative processing and SNV processing, so that the interference of noise and scattering in the sample is greatly reduced, the phenomena of superposition and interference among spectrums are reduced, the definition of the spectrums is improved, and the error of classification measurement is reduced.
2. The invention not only detects and classifies the pollutants contained in the sample through the classification model, but also obtains the concentration of the pollutants according to the absorbance of ultraviolet rays by using the concentration model, thereby being beneficial to improving the practicability of the invention.
3. The invention rapidly distinguishes the pollutant types by a spectral direct comparison analysis method, is favorable for improving the working efficiency, and is favorable for improving the accuracy by adopting the fitted straight line for comparison.
Drawings
The accompanying drawings, which 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 principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention provides a technical solution: an ultraviolet spectrum pollutant classification detection method based on sampling profile wave conversion comprises the following steps: firstly, measuring known pollutants; step two, establishing a classification model; step three, obtaining a sample; step four, concentration measurement; step five, detecting the spectrum; step six, data processing; step seven, establishing a concentration model; step eight, classified detection; step nine, concentration determination;
in the first step, firstly, a UV spectrometer is used for detecting and analyzing a standard water sample containing a single pollutant to obtain the spectral characteristics of the standard pollutant, and a spectral matrix of the standard pollutant is established as a reference;
in the second step, the spectrum matrix of the standard pollutant obtained in the first step is brought into a support vector machine, and a classification model is obtained through continuous iterative learning of data;
in the third step, a plurality of unknown pollutants to be detected are obtained as samples;
in the fourth step, the unknown pollutant sample in the third step is divided into an experimental sample and a test sample according to the proportion of 7: 3, the COD value of the experimental sample is measured by using a potassium dichromate titration method, and a data matrix of the COD value of the experimental sample is generated;
in the fifth step, the experimental sample and the test sample in the fourth step are respectively measured by using a UV spectrometer to obtain the spectral characteristics of the unknown pollutants, and the spectral matrix of the experimental sample and the spectral matrix of the test sample are respectively established;
in the sixth step, the spectrum matrix of the experimental sample and the spectrum matrix of the test sample obtained in the fifth step are respectively subjected to smoothing treatment, derivative treatment and SNV treatment, the treatment is standby after the treatment is finished, the algorithm of the smoothing treatment is a moving average method or a Savitzky-Go-lay convolution smoothing method, the derivative treatment is one of a first derivative or a second derivative, and the formula of the SNV treatment is as follows: wherein, the average value of the ith sample is shown, m is the number of wavelength points of the ultraviolet spectrum curve, and i is the number of samples;
in the seventh step, the spectrum matrix of the experimental sample processed in the sixth step is used as a training set, the spectrum matrix of the test sample is used as a test set, the training set and the data matrix of the COD value of the experimental sample measured in the third step are respectively subjected to iterative computation by using a computer, and the iterative computation algorithm is Partial Least Squares (PLS), so as to obtain a concentration model, and the COD value is used as the concentration index of the organic pollutants;
in the eighth step, the spectrum matrix of the test sample obtained in the fifth step is substituted into the classification model obtained in the second step, so as to obtain the pollutant types in the test sample, and the classification method of the classification model is a spectrum direct contrast analysis method, namely, the spectrum matrix of the test sample is linearly related to a reference matrix of a single pollutant, a fitting straight line is used as a standard, and if the number of the fitting straight line is more than 0.99, the single pollutant is contained in the test sample;
and in the ninth step, substituting the spectrum matrix of the test sample obtained in the fifth step into the concentration model obtained in the seventh step to obtain the pollutant concentration data of the test sample.
Based on the above, the method has the advantages that the noise of the data is reduced by smoothing the sample data, the superposition and the interference of the spectrum are reduced by derivative processing, the definition of the spectrum is improved by SNV processing, the error of classification detection is favorably reduced, the pollutants are favorably classified and the concentration of the pollutants is favorably calculated respectively by a classification model and a concentration model, the practicability is favorably improved, and the classification is favorably realized by using a spectrum direct contrast analysis method in the classification process, so that the working efficiency is favorably improved.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. 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 (7)
1. An ultraviolet spectrum pollutant classification detection method based on sampling profile wave conversion comprises the following steps: firstly, measuring known pollutants; step two, establishing a classification model; step three, obtaining a sample; step four, concentration measurement; step five, detecting the spectrum; step six, data processing; step seven, establishing a concentration model; step eight, classified detection; step nine, concentration determination; the method is characterized in that:
in the first step, firstly, a UV spectrometer is used for detecting and analyzing a standard water sample containing a single pollutant to obtain the spectral characteristics of the standard pollutant, and a spectral matrix of the standard pollutant is established as a reference;
in the second step, the spectrum matrix of the standard pollutant obtained in the first step is brought into a support vector machine, and a classification model is obtained through continuous iterative learning of data;
in the third step, a plurality of unknown pollutants to be detected are obtained as samples;
in the fourth step, the unknown pollutant sample in the third step is divided into an experimental sample and a test sample according to the proportion of 7: 3, the COD value of the experimental sample is measured by using a potassium dichromate titration method, and a data matrix of the COD value of the experimental sample is generated;
in the fifth step, the experimental sample and the test sample in the fourth step are respectively measured by using a UV spectrometer to obtain the spectral characteristics of the unknown pollutants, and the spectral matrix of the experimental sample and the spectral matrix of the test sample are respectively established;
in the sixth step, the spectrum matrix of the experimental sample and the spectrum matrix of the test sample obtained in the fifth step are respectively subjected to smoothing treatment, derivative treatment and SNV treatment, and the obtained spectrum matrix is reserved after the treatment is finished;
in the seventh step, the spectrum matrix of the experimental sample processed in the sixth step is used as a training set, the spectrum matrix of the test sample is used as a test set, and the training set and the data matrix of the COD value of the experimental sample measured in the third step are respectively subjected to iterative computation by using a computer to obtain a concentration model;
in the eighth step, the spectrum matrix of the test sample obtained in the fifth step is substituted into the classification model obtained in the second step, so that the pollutant types in the test sample are obtained;
and in the ninth step, substituting the spectrum matrix of the test sample obtained in the fifth step into the concentration model obtained in the seventh step to obtain the pollutant concentration data of the test sample.
2. The ultraviolet spectrum pollutant classification detection method based on sampling profile wave conversion as claimed in claim 1, characterized in that: in the sixth step, the algorithm of the smoothing processing is a moving average method or a Savitzky-Go-lay convolution smoothing method.
3. The ultraviolet spectrum pollutant classification detection method based on sampling profile wave conversion as claimed in claim 1, characterized in that: in the sixth step, the derivative processing is one of a first derivative and a second derivative.
4. The ultraviolet spectrum pollutant classification detection method based on sampling profile wave conversion as claimed in claim 1, characterized in that: in the sixth step, the formula of the SNV processing is as follows: where is the average of the ith sample, m is the number of wavelength points of the ultraviolet spectral curve, and i is the number of samples.
5. The ultraviolet spectrum pollutant classification detection method based on sampling profile wave conversion as claimed in claim 1, characterized in that: and in the seventh step, the COD value is used as the concentration index of the organic pollutants.
6. The ultraviolet spectrum pollutant classification detection method based on sampling profile wave conversion as claimed in claim 1, characterized in that: in the seventh step, the algorithm of iterative computation is partial least squares PLS.
7. The ultraviolet spectrum pollutant classification detection method based on sampling profile wave conversion as claimed in claim 1, characterized in that: in the step eight, the classification method of the classification model is a spectral direct contrast analysis method, that is, the spectral matrix of the test sample and the reference matrix of the single pollutant are linearly correlated, a fitting straight line is used as a standard, and if the standard is more than 0.99, the single pollutant is contained in the test sample.
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