Water quality on-line monitoring and prediction method for water supply pipe network

Abstract

The invention relates to a water quality on-line monitoring and prediction method for a water supply pipeline network. The method comprises the following steps of: collecting water quality rationalize physicochemical indexes of a pipe network water inlet point through an on-line monitoring instrument according to a time sequence, establishing a water quality model according to the data, wherein the water quality model is provided with an analog variable of the water quality model and a biochemical reaction equation of each analog variable; and carrying out water quality model parameter rating on the analog variable of the water quality model and the biochemical reaction equation of each analog variable according to the water quality model, and carrying out pipe network user point water quality prediction. The water supply network water quality on-line monitoring and prediction method provided by the invention realizes the in-time prediction of total bacterial count and residual chlorine concentration of each user point of the water supply network, the latest water inlet physicochemical index monitoring result is read through the pipe network, and a computer can dynamically display the transformation of water quality of each node; the capacity and efficiency that urban water-supply supervisors answer the untreated water quality fluctuation are improved; and a user point water quality prediction result output by a prediction system can receive data so as to form an assembly with a certain spatial distribution characteristic, and the prediction result distortion is avoided bringing a decision risk.

Description

technical field [0001] The invention relates to a water quality prediction of a water supply pipe network. In particular, it relates to an online water quality monitoring and prediction method for urban water supply pipe network monitoring, forecasting and risk assessment of the total number of bacteria and residual chlorine concentration indicators in the water supply pipe network. Background technique [0002] As the municipal infrastructure for the transportation and distribution of drinking water for residents, the water supply pipe network often has an important impact on the safety of drinking water for residents. According to the survey, the pass rate of my country's pipe network water quality has dropped significantly compared with the factory water, especially the pass rate of microbial indicators at user nodes is less than 90%, and microbial indicators are the most concerned issues for users of pipe network water supply. Because the urban water supply pipe network...

AI Technical Summary

Problems solved by technology

[0004] The water quality of the water supply network tends to fluctuate greatly and often exceeds the range of existing statistical data. It is difficult for the statistical prediction system to give accurate and effective water quality prediction results for user nodes, and it is impossible to predict possible water quality risks when the water quality changes significantly; The network water quality components are complex, and the single-component model ignores the influence of other important water quality indicators on a target water quality indicator, and cannot reasonably reflect the water quality status of the pipe network

That is, the existing prediction methods are difficult to meet the needs of ensuring the safety of microbial indicators at the user points of the water supply network

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