Sewage Treatment Control System Based On LabVIEW And Research Of Soft Sensor Modeling

Wastewater treatment in China started later compared to developed countries, with the prevalence of low efficiency, high energy consumption, low degree of automation problems. Many kinds of equipment for wastewater treatment process and their operating procedures are cumbersome, complex and diverse process. Therefore, to achieve automatic control of water treatment system is necessary; to ensure processing quality, improve water efficiency is not the missing link. Therefore, the design meets the requirements of the sewage treatment process, with a centralized and remote monitoring, control and manage the integration of the integrated control system is important.This subject is for a dairy sewage treatment plant. I analysis the process, and according to the demand of control, determined three control structures based on field manual, the control room automation and remote monitoring of the Internet. Select Siemens industrial computer as a PC station, Siemens S7-300 as PLC station. Built an OPC server with Siemens SIMATIC.NET, it can be connected to PLC, and uses SQL Server to support data acquisition, device control, real-time curve display, history, fault alarm and other basic monitoring functions.System not only achieves real-time monitoring and control, but it also can be operated through the browser in real-time remote monitoring. In addition, the system through the GSM (global system of mobile communication), managers can use the phone in the global industrial field via SMS query the parameters, and the system in the event of failure is able to send messages and e-mail to notification a number of managers automatically.Finally, the paper builds a soft sensor modeling to research the BOD parameter with RBF neural network method. With a variety of data collected by sensors and instrumentation, LabVIEW could call Matlab neural network toolbox with the MathScript Node, to realize a hybrid programming model for BOD measurement simulation. It can adjust in the program input parameter in real-time, output simulation results in a variety of ways. Simulation results show that the model achieved more accurate online prediction of BOD concentrations. The basis for the timely adjustment of control strategies to reduce failure, put the amount of savings in pharmaceutical, achieve the purpose of running economically.