Intelligent monitoring method and system for wastewater treatment based on ga-dbn network
A wastewater treatment system and wastewater treatment technology, applied in general control systems, control/regulation systems, adaptive control, etc., can solve problems such as difficulty in ensuring network optimization, affecting algorithm implementation and optimization effects, etc., to promote efficient and stable operation. , to achieve the effect of diagnosis and optimization, to enhance network stability and operability
Active Publication Date: 2022-06-07
SOUTH CHINA NORMAL UNIVERSITY +1
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The deep belief network DBN model is a typical deep learning algorithm, which can more accurately perceive the internal laws of object evolution, but it is difficult to guarantee the optimal network, and there are parameter selection and optimization in the process of wastewater treatment prediction, diagnosis and optimization control. Many problems, such as algorithm implementation and optimization effect
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[0089] The intelligent monitoring method of wastewater treatment based on GA-DBN network, such as figure 1 Based on the relationship between the effluent quality of the wastewater treatment system and the influent indicators and model control parameters, the method makes full use of the genetic algorithm GA's ability to macroscopically search for optimal solutions and the deep belief network DBN's ability to accurately perceive the internal laws of object evolution. Create a water quality soft measurement model based on GA-DBN, predict the COD and SS concentration of the wastewater treatment effluent, intelligently control the wastewater treatment system, regulate the effluent quality in real time, and promote the efficient and stable operation of the wastewater treatment system. In addition, because the GA-DBN fusion model not only has a strong feature learning ability, but also can use adaptive learning rules to design the entire network to complete the adaptive change of the...
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The invention discloses an intelligent monitoring method for wastewater treatment based on a GA-DBN network, which comprises the following steps: selecting suitable parameters of a wastewater treatment system as input independent variables and output variables; using iterative optimization calculations to obtain the optimal hidden value of each layer of the deep belief network DBN Contains the number of layers of nodes; use the genetic algorithm GA to screen out the optimal input independent variable; build a fusion model based on the genetic algorithm-deep belief network GA-DBN; train the model, and use the trained model to perform real-time soft sensing on the output variables of the wastewater treatment system , obtain diagnostic results, and guide the optimization of wastewater treatment processes. The genetic-deep belief network GA-DBN fusion model and system constructed by the present invention can be used to predict water quality parameters such as COD and SS concentrations in the wastewater treatment system, realize intelligent monitoring and diagnosis of water quality in the wastewater treatment system, and promote efficient and stable operation of the wastewater treatment system.
Description
technical field [0001] The invention relates to the research field of wastewater treatment and control, in particular to an intelligent monitoring method and system for wastewater treatment based on a GA-DBN network. Background technique [0002] The current wastewater treatment generally goes through primary physicochemical and secondary biochemical processes. The primary physicochemical treatment is mainly used to remove SS and a small amount of COD and BOD; the secondary biochemical treatment is used to remove most of the COD and BOD. In order to monitor the stability of the wastewater treatment system and improve the compliance rate of wastewater discharge, real-time monitoring of indicators such as effluent COD and SS is required. The wastewater treatment process is complex and the mechanism is not yet fully understood. It is difficult to effectively predict and control the effluent quality with an accurate mathematical model. [0003] In order to solve the problem tha...
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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 黄明智牛国强易晓辉李小勇应光国石青松
Owner SOUTH CHINA NORMAL UNIVERSITY