Sewage TP soft measurement method based on self-organized particle swarm and radial basis function neural network

Abstract

The invention discloses a sewage TP (Total Phosphorus) soft measurement method during sewage treatment based on a self-organized particle swarm and a radial basis function neural network, and aims to solve the problems that during current sewage treatment, the effluent TP measurement process is complicated, the cost of instruments and equipment is high, and the reliability and the accuracy of the measurement results are low. The effluent TP soft measurement method is calibrated by real-time data, so as to predict the effluent TP during the sewage treatment process, and solve the problem that the effluent TP is difficult to measure; the results indicate that the effluent TP soft measurement method can quickly and accurately predict the concentration of effluent TP, and is favorable for strengthening delicacy management in an urban sewage treatment plant, and promoting the real-time water quality monitoring level.

Description

technical field [0001] Based on the biochemical reaction characteristics of sewage treatment, the present invention uses a self-organizing particle swarm-radial basis neural network to design a soft measurement method for total phosphorus TP in the sewage treatment process, and at the same time realizes the total phosphorus in the sewage treatment process according to the real-time collected data The online correction of the TP soft measurement method realizes the real-time measurement of the TP concentration of the effluent total phosphorus; it is an important branch of the advanced manufacturing technology field, which belongs to both the control field and the water treatment field. Background technique [0002] Phosphorus is the main factor that causes water eutrophication and algal blooms, and is the main factor that causes water environmental pollution and water eutrophication. An important measure to control water eutrophication is to treat phosphorus-rich sewage. And s...

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Problems solved by technology

However, the spectrophotometric method to measure the total phosphorus content is cumbersome. The reagents need to be used and prepared immediately, and the calibration curve needs to be drawn. The workload is heavy, and the turbidity in the water sample will directly affect the measured absorbance value. make compensation

Although methods such as gas chromatography, liquid chromatography, and electrode method have avoided the shortcomings of long measurement period, complicated manual operation, and prone to accidental errors in the detection of total phosphorus in effluent by spectrophotometry, gas chromatography, liquid chromatography Methods such as method and electrode method need to select a suitable phosphate ion selective electrode or chromatography to interact with phosphate

The mechanism and method of total phosphorus in sewage treatment can provide a basis for the process design of sewage treatment plants. However, since the influent flow rate, influent composition, pollutant concentration, weather changes and other parameters in the process of sewage treatment are all changing with time, at the same time, urban sewage The load fluctuation in the treatment process is very large, the sewage treatment process often works in a non-stationary state, the error of the mechanism method is large, and the accuracy is low, it is difficult to meet the needs of real-time detection

On the whole, the above total phosphorus detection instruments all need a certain amount of time to measure, and cannot achieve real-time detection of total phosphorus, and the equipment needs to be imported, the reagents are replaced frequently, and the maintenance cost of the equipment is high.

Although the instrument based on the mechanism method can realize the real-time prediction of total phosphorus, but the error is large and the accuracy is low, so it has not been widely used in sewage treatment plants.

Therefore, the existing total phosphorus detection technology and instruments are difficult to meet the real-time detection needs of sewage treatment plants, and new detection methods must be sought

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