Measurement parameter prediction and sewage treatment control method based on deep learning

Abstract

The invention relates to a measurement parameter prediction and sewage treatment control method based on deep learning. The method comprises the following steps: step 1, acquiring real-time sewage treatment online instrument measurement time sequence data; step 2, performing data cleaning and wavelet transform on the time series data to obtain high-frequency components of each level; step 3, respectively processing the high-frequency components of each level, inputting the processed high-frequency components into the trained GRU neural network model, and outputting prediction results corresponding to the high-frequency components of each level; step 4, processing the prediction results corresponding to the high-frequency components of all the levels again and then combining the results towavelet reconstruction to acquire measurement parameters subjected to prediction; and step 5, performing corresponding control action on the corresponding control link of the sewage treatment according to the measurement parameters subjected to the prediction treatment. Compared with the prior art, the invention has the advantages that parameters can be relatively accurately estimated in advance,control lag is avoided, meanwhile, the measurement frequency can be reduced, and the cost is reduced.

Description

technical field [0001] The invention relates to the technical field of sewage treatment measurement and control, in particular to a deep learning-based measurement parameter prediction and sewage treatment control method. Background technique [0002] With the wave of "standard upgrading and transformation" set off in recent years, in order to meet the increasingly stringent discharge standards, the sewage treatment with a relatively low degree of automation has gradually added online instruments. [0003] However, the current sewage treatment online instrument has the characteristics of long measurement time and high measurement maintenance cost (measurement needs to consume measurement drugs, and measurement cost increases with the increase of measurement frequency), which not only increases operating costs, but also causes control measures due to long measurement time The relative hysteresis will cause the water outlet to be unstable. Contents of the invention [0004]...

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Problems solved by technology

[0003] However, the current sewage treatment online instrument has the characteristics of long measurement time and high measurement maintenance cost (measurement needs to consume measurement drugs, and measurement cost increases with the increase of measurement frequency), which not only increases operating costs, but also causes control measures due to long measurement time Relative hysteresis will cause unstable water outlet

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