Intelligent control algorithm for analyzing ecological oxygenation of river channel based on parameter uncertainty

Abstract

The invention discloses an intelligent control algorithm for analyzing ecological oxygenation of a river channel based on parameter uncertainty. The invention discloses a riverway oxygenation algorithm based on a deep learning algorithm. The riverway oxygenation algorithm comprises the following steps: 1) collecting parameters; 2) estimating a dissolved oxygen balance model; 3) determining n objective functions for performing model parameter uncertainty analysis; 4) substituting into a dissolved oxygen balance model for calculation; 5) comparing to obtain a dominant parameter set corresponding to the Pareto set under the target function; 6) drawing a joint probability density function, and performing two-parameter uncertainty analysis; 7) drawing probability density distribution of each parameter in the dominant set; 8) calculating the oxygen demand of the river channel; and 9) determining the oxygenation amount of the equipment according to the oxygen demand of the river and the oxygenation efficiency of the equipment. The method overcomes the defects that in an existing technical scheme, an oxygenation device cannot be accurately controlled according to multi-parameter data, and a simple linear mathematical model can only be judged through artificial experience or applied mechanically, so that the aim of accurately controlling oxygenation according to the parameters such as the river water flow speed, the river water quality and the environmental influence factors is achieved.

Description

technical field [0001] The invention relates to the field of river ecological management, in particular to an intelligent control algorithm for analyzing river ecological aeration based on parameter uncertainty. Background technique [0002] Surface river governance is a very complex system, and its governance process is affected by many factors. Among them, the aeration of the river is a very critical part of the treatment of the polluted river. Aeration can produce excellent treatment results due to the low energy consumption, which is deeply compatible with the benefit principle of low input and high output. Since the 1950s, aeration has been widely used in the treatment of polluted rivers and lakes in developed countries. Therefore, the development and research on aeration equipment is very important for river management, and efficient and advanced aeration equipment can help improve the overall water treatment efficiency. [0003] Patent document CN111982746A disclose...

AI Technical Summary

Problems solved by technology

There are problems such as rapid changes in physical and chemical properties and fluctuations in dissolved oxygen in river water bodies. It is difficult to grasp the laws in a short period of time, and it is impossible to make corresponding adjustments according to the actual needs of current water flow velocity changes, temperature changes, water quality changes, and water bodies in wet and dry seasons.

[0004] Although some existing automatic aeration devices are equipped with dissolved oxygen sensors, which can read the dissolved oxygen concentration in water in real time, it is difficult to determine the position and quantity of dissolved oxygen sensors, and there is a problem of hysteresis in instrument detection; the installation position of dissolved oxygen sensors If it is too close, the aeration device will be shut down within a very short time after it is started, and the actual range of action of the aeration device cannot be realized

[0005] The parameters of the aeration system for river channel regulation are high in digits, strong coupling, highly nonlinear, and the dissolved oxygen in the water is unstable, so it is difficult for the system to reach equilibrium in a short period of time. Therefore, an intelligent aeration algorithm for river channels based on deep learning is proposed. and devices to realize the precise control and automatic control of the total amount of aeration. On the premise of reaching the water quality index, it can ensure the stability of the water quality, eliminate the redundancy of the aeration amount, reduce the power consumption, and meet the development needs of the modern ecological environment.

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