Water quality detection and treatment method

Abstract

The invention discloses a water quality detection and treatment method. The method comprises the following steps: S1, collecting water quality data of a water source to be detected; s2, preparing data, classifying the collected water quality data by taking to-be-detected time as a reference, and obtaining a training set D comprising at least part of water quality data before the to-be-detected time and a to-be-detected data set T comprising the water quality data of the to-be-detected time; s3, obtaining classification thresholds of normal and abnormal water quality data categories based on the training set D, and establishing a KNN prediction model according to the classification thresholds; and S4, substituting a to-be-detected data set T into the KNN prediction model, and outputting a prediction result. And S5, treating the water according to the prediction result. According to the invention, the accuracy of result output can be ensured, and the efficiency of anomaly recognition is improved.

Description

technical field [0001] The invention relates to the field of water quality detection, in particular to a water quality detection and processing method. Background technique [0002] With the development of society, the problem of water pollution has become more and more prominent, and the prevention and control of water pollution in various regions is very important. However, China has a vast territory and developed water systems in some areas, and the workload of water pollution prevention and control is huge and cumbersome. [0003] How to judge abnormalities in water quality detection and treatment methods, and determine abnormal events through abnormalities, so as to prevent the waste of human resources caused by false positives and false positives, is very necessary. [0004] The current detection methods for abnormal drainage water quality are mainly artificially set. Artificially set a normal value in the background of the operating software based on real-time emiss...

AI Technical Summary

Problems solved by technology

This method is simple and convenient to apply, but the accuracy of abnormal event judgment is low. During execution, affected by the online detection equipment, the detection data is unstable, and frequent alarms are prone to occur, resulting in information overload, which brings great impact to actual work. workload

And because there are many standards for the implementation of water environment discharge, and the actual industrial environment is complex, the reference standards are even more complicated. Often multiple standards are implemented in one project, which also makes it difficult to implement artificially set values.

[0005] and the drainage is often time-sensitive. The discharge of a day may exceed the normal value in a certain period of time, and the normal value in a certain period of time. The discharge situation is complicated and the discharge There are many influencing factors such as time and emissions, and it is not easy to equate abnormal values ​​with abnormal events

Images