Research On Intelligent Control System Of The Partial Ventilator

Partial ventilation is an important part of coal mine ventilation system, the condition of partial ventilation directly affects the safety of coal mine production. In our country, many coal mine partial ventilation systems stay in the state of power frequency for a long time. Wind speed and air volume cannot be changed automatically according to the production environment, especially, the concentration of gas. Switching experiment of main ventilator and vice-ventilator needs manual control. In addition, the diagnosis of partial ventilator fault mainly relies on the experience of theengineers. These problems for the coal mine production not only lead to a lot of security risks, but also make a great waste of electricity. Partial ventilator intelligent control strategy will be proposed and the partial ventilator intelligent control system will be designed in this thesis. By this control system the speed of the ventilator can be adjusted automatically, and the switching of the main equipments and the fault diagnosis can also be performed automatically.Partial ventilation system is a complex nonlinear system, thus it is difficult to establish a precise mathematical model. Based on the T-S model and fuzzy control technology, this thesis transforms the expert language into fuzzy control rules, getting rid of the dependence on the accuracy of the model and realizing the intelligent control of the wind. In addition, traditional partial ventilator control technology is post-action control, cannot make timely response of gas concentration change for next moment. It makes a large number of field gas concentration data cannot be used. This paper introduces the fuzzy predictive control, which can predict gas concentration and realize partial ventilator speed regulation. The system can improve wind speed to eliminate potential danger before gas accumulation automatically.In addition, according to the situation that for a long time the coal mine mainly relies on manual experience to carry out the fault of the ventilator, the wavelet analysis and support vector machine technology will be applied to fault diagnosis. By analyzing partial ventilator vibration signal and compariing with the typical fault characteristics of the ventilator, a new method will be proposed to realize fault diagnosis and prediction for partial ventilator, which can improve the safety of coal mine production.To implement the fuzzy predictive control and fault diagnosis strategy for partial ventilator, the hardware structure of the system will be designed in this thesisr. Stm32f103 vb is chosen as the main controller of downhole control substation The substation will have the following functions: a variety of downhole data’s acquisition, processing and transmission; switching of main and standby ventilator; control of power for tunneling head and coal mining machine. Using Lab VIEW programming, PC achieves to call and run the algorithm of ventilator control and fault diagnosis.Simulation experiment will be performed in MATLAB to show that the control strategy in this paper has a good effect on the air volume control and fault diagnosis of the partial ventilator.