Sewage plant water-quality monitoring early-warning method and system

Abstract

The invention discloses a sewage plant water-quality monitoring early-warning method and system. The method comprises the following steps that 1, sampling is conducted on the portion of sewage plant inflow water and the portion of effluent subjected to complete flow treatment of a sewage plant, and multiple inflow water samples and multiple corresponding effluent samples are obtained; 2, according to a three-dimensional fluorescence spectrogram of the inflow water samples and water quality indexes of the inflow water samples, a mapping relation between three-dimensional fluorescence spectrogram data and the water quality indexes of the inflow water samples is established; 3, the water quality indexes of the inflow water samples serve as input values, water quality indexes of the effluent samples serve as output values, and a BP neural network is established through training; 4, a three-dimensional fluorescence spectrogram of current inflow water is obtained; 5, the water quality index of the current inflow water is obtained through mapping relationship analysis according to the three-dimensional fluorescence spectrogram of the current inflow water, and the water quality index of the effluent corresponding to the inflow water is obtained through BP neural network prediction according to the water quality index of the current inflow water. By means of the sewage plant water-quality monitoring early-warning method and system, the anomaly of the effluent quality can be monitored in advance.

Description

【Technical field】 [0001] The invention relates to the field of water quality monitoring in sewage plants, in particular to a water quality monitoring and early warning method and system for sewage plants. 【Background technique】 [0002] With the severe damage to the ecological environment, especially the water environment, the country has gradually paid enough attention to the problem of water environment pollution. In recent years, the number of sewage treatment plants is increasing rapidly. The operation of sewage plants not only reduces the pollution of domestic sewage to surrounding rivers and lakes, but also plays an important role in restoring a good ecological environment. On this basis, the operation effect of the sewage plant has attracted widespread attention. How to effectively ensure that the effluent quality of the sewage treatment plant meets the discharge requirements stipulated by the state has become an important task at present. [0003] At present, urban ...

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Problems solved by technology

Microorganisms are easily affected by the COD concentration of influent water, nutrients such as nitrogen and phosphorus, and other toxic and harmful substances, making the treatment effect unstable, which in turn leads to excessive effluent from sewage plants

Usually, there are relatively many steps to analyze the effluent water quality, consume a lot of reagents or energy, take a long time, and it is difficult to obtain the corresponding experimental results, which is not conducive to the timely monitoring of the operation effect of the sewage treatment plant by the staff

[0004] At present, in many sewage plants, only when the water quality of the effluent has exceeded the standard will the treatment abnormality be discovered. The abnormal data before the discharge exceeds the standard cannot be used as an early warning, and the process cannot be adjusted in time, and there is a serious lag.

Some sewage treatment plants in my country often use biological treatment processes, such as activated sludge process to treat urban sewage. Since the operation and control of activated sludge process is a very complicated issue, it involves issues such as matrix degradation and microbial growth laws, and affects these laws. The relationship between the factors is non-linear, so some difficulties will often be encountered during the operation

In addition, due to the complex composition and time changes of sewage influent, even some operational experience and knowledge obtained from a certain sewage treatment plant may not be easily applicable to other sewage plants

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