Method for simultaneously detecting contents of nitrate and nitrite in water based on hybrid machine learning model

Abstract

The invention belongs to the field of spectral signal analysis, and particularly relates to a method for simultaneously detecting the contents of nitrate and nitrite in water based on a hybrid machine learning model. The method comprises the following steps of: acquiring machine spectrum data of a series of nitrate and nitrite mixed solution samples with different nitrogen contents; classifying the samples according to the optimal critical concentration to obtain four types of samples; establishing a relation model for the nitrogen content of nitrate and nitrite corresponding to each of the four types of samples and the corresponding spectrum data; screening characteristic wavelengths with high sensitivity and correlation, and establishing a regression sub-model; and acquiring the spectrum data of a to-be-detected sample, determining the category of the to-be-detected sample according to the relation model, and performing analysis and prediction by adopting a regression sub-model corresponding to the category of the to-be-detected sample to obtain the concentrations of nitrate and nitrite in the to-be-detected sample. The method provided by the invention realizes accurate and rapid detection of nitrate nitrogen and nitrite nitrogen, and can ensure the detection sensitivity under low concentration.

Description

technical field [0001] The invention belongs to the field of spectral signal analysis, in particular to a method for simultaneously detecting the contents of nitrate and nitrite in water based on a hybrid machine learning model. Background technique [0002] At present, there are a variety of nitrogen-containing compound detection technologies on the market, and there are great differences in detection principles, calculation methods, operating techniques, and application fields. The relatively mature multi-component concentration instrument analysis methods at home and abroad mainly include: electrochemistry, capillary electrophoresis, ion chromatography, biosensing and spectrophotometry. Electrochemical measurement technology is not perfect in monitoring the concentration of trace analytes, and in actual samples, due to the easy contamination of the electrode surface, the detection results are likely to be unstable. The method based on capillary electrophoresis is relativ...

AI Technical Summary

Problems solved by technology

This method is an indirect analysis for nitrate, which is time-consuming and highly dependent on the detection accuracy of nitrite. Secondly, the Griess method involves toxic chemical reagents, which are harmful to the body and pollute the environment.

Some researchers have suggested that the ultraviolet absorption spectra of nitrate and nitrite can be used to directly measure it, because the ultraviolet absorption spectra of nitrate and nitrite have similar shapes in the first half, and the absorption peak wavelengths are very close, almost overlapping , in practice, it is difficult to separate the contributions of nitrite and nitrate from the collected spectra, and the existing direct spectroscopic methods are still using traditional chemometric methods to process spectral data, facing the narrow scope of application, detection The problem of low precision

In recent years, the combination of UV spectroscopy and machine learning methods has been successfully applied to the rapid detection of various compounds, however, there is still little research on the separation of nitrate and nitrite

Preliminary experiments have shown that common machine learning models are not sensitive enough to predict components at low concentrations when faced with a mixed solution of nitrate and nitrite within a certain concentration range. Machine learning methods that still maintain the same level of accuracy

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