Application Of Expert Self - Learning Control Of Dissolved Oxygen Content

With the process of city gradually accelerated, the development of municipal engineering project has been paid more and more attention. Among them, the sewage treatment is one of the typical characteristics of municipal engineering project, simultaneously it also has the processing of complex process, continuous operation of continuous production line. This shows that the sewage treatment with traditional metallurgical production line automation control complexity, and has a large market, completes the automatic control system of city sewage treatment has great value of popularizationBased on the background of sewage treatment, on the one hand, developed the automatic control system of sewage treatment of the whole process, on the other hand, according to the difficulty of accurate aeration sewage, the development of the intelligent control system, while satisfying the requirements of the dissolved oxygen content, reduce the power output of the blower as far as possible, so as to achieve the purpose of energy saving. The core of the automatic control system of sewage treatment for the AB company’s 1756 PLC series, configuration software using FactoryTalk SE. Other hardware includes IO module, network module, instrument, actuator, low voltage electrical components etc.. Through the design, detail drawings of the electrical cabinet assembly and field programming and debugging, has completed the automatic control system.The design and preparation of self learning control algorithm of dissolved oxygen in sewage in aeration. When the dissolved oxygen content does not meet the control requirements, according to the size of deviation of the corresponding self learning table is revised, with new control variables after correction for control, and the new parameters are saved to the self learning table.At the same time, the intelligent control algorithm is put after the success of debugging of automatic control. To control the output calculation of the current state can be self learning control system, regulating valve comprises a blower power and six aeration tank opening, at the same time, can also control not HERSHEY’S analysis, the control parameter more reasonable save to self learning table for later use, control. This automatic control process is realized in the process of aeration blower electric energy saving.The expert from learning has great promotion value of intelligent control, can be used in the control of similar projects, as long as the process variables and the control variables and there is a linear relationship can under certain conditions.