Method and system for predicting dosage of tap water coagulant

Abstract

The invention provides a method and a system for predicting the dosage of a coagulant in tap water. The method comprises the following steps: S1, establishing a coagulant dosage calculation model by using a deep learning algorithm; and S2, inputting the influence factors of the tap water coagulant dosage into the coagulant dosage calculation model, and predicting the coagulant dosage. The invention provides a method for calculating the dosage of a medicament for optimal control of a coagulant adding system in a tap water treatment process, solves the problem that the dosage of the coagulant is difficult to accurately calculate, and has important significance for optimizing the dosage of the coagulant, stabilizing the turbidity of effluent after precipitation treatment and guaranteeing the safety of the quality of supplied water.

Description

technical field [0001] The invention relates to the field of water purification technology, in particular to a method and system for predicting the dosage of coagulant for tap water. Background technique [0002] In the production process of waterworks using surface water as the water source, the process control and optimization of the coagulation and sedimentation process has always been a technical difficulty. Among them, the amount of coagulant dosage is the automation and fine control of the entire coagulation treatment process. Top priority for optimization. Normally, the coagulation and sedimentation process is located at the front end of the tap water treatment process. By adding a coagulant to the raw water, the impurity particles in the water form larger flocs, which are removed through sedimentation and filtration processes. Under normal circumstances, the turbidity of raw water is tens to hundreds of NTU. After coagulation, sedimentation, and filtration, the turb...

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Problems solved by technology

However, in addition to the factors affecting the dosage of coagulant listed in the patent, the dosage of coagulant is also significantly affected by factors such as the pH of the source water, the stirring intensity during the coagulation process, and the target value of turbidity after settling. , due to factors such as complex climatic conditions and the number of algae, the pH of the source water fluctuates in a large range from 6 to 9. The stirring intensity during the coagulation process directly affects the time and size of the alum flowers, and indirectly affects the precipitation of the alum flowers. Therefore, there is a large error between the calculation results of the model established by ignoring the pH of the source water, the stirring intensity and the target value of the turbidity after settling and the actual pharmaceutical demand, which will adversely affect the actual use effect

[0006] In addition, the coagulant dosing process of the waterworks is complex, involving multiple processes such as physics and chemistry. From the dosing of coagulant, through coagulation, flocculation, coagulation, and precipitation, the system has large time lag and large inertia, etc. This makes the influence of the selected model input variable on the predicted target variable lag, that is, the result of the predicted target variable is not only affected by the current value of the input variable, but also affected by the input variable within a certain period of time, so , the value of a single influencing factor should be a time series value

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