Research On The Automatic Control Technology Of Marine Reverse Osmosis Seawater Desalination

The traditional marine reverse osmosis seawater desalination equipment not only has the big volume but the high energy consumption,and its operation still rely on manual control,which lead to low efficiency,scattered information and poor real-time feedback.Therefore,the research on the seawater desalination device based on the automatic control system has been conducted to improve the efficiency of marine desalination plant and reduce the energy consumption.The application of singlechip microcomputer control technology of seawater desalination system is studied in this paper.Firstly,the weakness of reverse osmosis system on the seawater desalinating was reviewed,and studied with a lot of operating principle about the device design.Then a scheme of control system based on STC12C5A60S2 is proposed.The principle of the hardware circuit was designed,the PCB and HMI were made to make the collection and processing of the performance parameters of marine desalination system work.Finally,the programs of data acquisition,data processing and human-computer interaction interface program was designed to realize the automatic control of the marine reverse osmosis seawater desalination plant.The nonlinearity,hysteresis and time-varying of marine RO desalination system is analyzed.The effects of feed concentration,influent flow rate,temperature and pressure on the system energy consumption,fresh water flow and water production conductance were studied by uniform orthogonal test.Neural network based on MEA-BP was established,and 80% of the experimental data are used as learning samples,the rest as the test samples.Based on the experimental data,the performance prediction model of marine reverse osmosis seawater desalination system was obtained.Comparing with the predicted value and the experimental value,it concluded that the MEA-BP model can be applied to predict the performance of marine reverse osmosis seawater desalination system.The average relative error of the energy consumption,fresh water flow and water conductivity was 8.70%,6.58% and 11.85% respectively,increased by 31.06%,27.11% and 5.38% respectively to the single BP model.Inputting the data to predict,the device is in high efficiency when the influent flow rate is 600~650L/h,the temperature is between 30~35? and the pressure is between 5.5~6.0MPa.Therefore,it has a high precision and speed to optimize the operating parameters based on this model which could reduce the energy consumption of the system in the actual operation.