Ship salt-containing sewage treatment control prediction system and prediction method based on a wavelet neural network

Abstract

The invention aims to provide a ship salt-containing sewage treatment control prediction system and prediction method based on a wavelet neural network. The wavelet theory and the neural network are combined, so that the wavelet neural network completely inherits the excellent time-frequency localization characteristic of wavelet transformation and the self-learning characteristic of the neural network, and the strong nonlinear approximation capability is realized. The problems that a traditional neural network prediction model is poor in precision, low in stability and the like are solved particularly aiming at the characteristics of high nonlinearity, strong coupling, time varying, large hysteresis and complexity in the salt-containing sewage treatment process. A corresponding control strategy is provided, self-repairing is achieved while ship sewage treatment equipment is self-monitored and diagnosed, compared with other algorithms, the intelligent degree is high, and the operationcost is further saved. Experimental results show that the prediction method can well predict the pollutant removal efficiency in the high-salinity seawater, so that a feasible operation strategy is provided for the treatment of the ship salt-containing sewage.

Description

technical field [0001] The invention relates to a ship domestic sewage treatment system and method. Background technique [0002] The International Maritime Organization (IMO) has increasingly stringent requirements on the discharge of sewage from ships. Although domestic sewage treatment technology and devices are developing rapidly in our country, there are still many problems. Especially for the control problem in the treatment process, due to the characteristics of high nonlinearity, strong coupling, time variation, large hysteresis and complexity in the sewage treatment process, traditional control methods, such as switch control or PID control, can only Control a single variable, but for complex systems, effective control cannot be achieved. [0003] In view of the shortcomings of traditional control methods, in recent years, many scholars have conducted a lot of research on the control of sewage treatment and proposed many mathematical models, such as ASM series mod...

AI Technical Summary

Problems solved by technology

However, the current sewage treatment process model has a complex structure, too many undetermined parameters, poor identification, and cannot dynamically reflect the relationship between operating variables and control objectives, so it cannot be used for on-line control

In addition, because the sewage treatment process is affected by the influent water quality, temperature, pH and salinity, it has the characteristics of strong coupling and high nonlinearity, which poses challenges to the monitoring and control of the sewage treatment process.

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