Soft measuring method and device for effluent COD concentrations of rural domestic sewage A2O treatment terminal

Abstract

The invention discloses a soft measuring method and a soft measuring device for effluent COD concentrations of a rural domestic sewage A2O treatment terminal. The soft measuring method regards effluent ph, incoming water conductance, effluent conductance, effluent turbidity, incoming water ammonia-nitrogen concentrations and effluent ammonia-nitrogen concentrations as input indicators for effluentCOD concentration prediction, and constructs an association model between the input indicators and the effluent COD concentrations by utilizing a BP neural network. Through simulating and verifying the BP neural network model, the test indicates that the neural network model established by the invention can predict the effluent COD concentrations in the same region quickly and precisely, and themodel has reliable prediction value for the effluent COD concentrations of A20 facilities.

Description

technical field [0001] The invention belongs to the field of environmental monitoring methods, in particular to a kind of rural domestic sewage A 2 O treatment terminal effluent COD concentration soft measurement method and device. Background technique [0002] A 2 The O process is the process type currently used in most rural domestic sewage treatment terminals. At this stage, the detection principle of large-scale online water quality monitoring equipment on the market generally adopts conventional chemical methods. This type of online monitoring equipment is expensive, requires regular replacement of chemical reagents, high cleaning and maintenance costs, and requires relatively high operating skills for maintenance personnel. High disadvantage. In recent years, the soft sensor technology based on artificial neural network has been studied at home and abroad. The main method is to use artificial neural network to establish auxiliary indicators that can be measured by c...

AI Technical Summary

Problems solved by technology

However, the existing research on soft sensing generally stays at the theoretical level, and most of them focus on a single processing terminal as the research object, and cannot realize the prediction function of other terminals in the same area.

In my country, rural domestic sewage has the characteristics of large quantity, high dispersion, high operation and maintenance costs, and great difficulty. It is obviously impractical to equip each set of terminals with the above-mentioned online monitoring equipment based on chemical methods. It also takes a lot of manpower and material resources to establish a soft-sensing model at the terminal, which is not in line with the actual situation of rural domestic sewage monitoring in my country

[0003] Since there is no simple and quick way to measure the COD concentration in water at present, the measurement of COD in the national standard method needs to go through the digestion process, and its online monitoring is difficult.

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