Research On Mine Ventilation System Of Switched Reluctance Drive Based On Neural Networks

Ventilation network is an important part of coal production. Whether it is in proper working order or not has great effect on mine safety production. Generally speaking, two ways are used to solve the problem of mine ventilation system regulation and control. They are the optimization of mine ventilation network and the regulation of air quantity.Mine ventilation network calculation software is used to solve the problem of how to optimize mine ventilation network and then make a dynamic monitoring towards the whole mine ventilation system. Through the using of mine ventilation network calculation software we also can get optimum wind velocity pressure and optimum parameters of all kinds of regulation measures. At last, optimum ventilation network is obtained.Switched reluctance motor is used as power source of mine ventilation and switched reluctance drive is used to regulate air quantity.Direct Torque Control is used to solve these problems exist in switched reluctance motor such as big noise,big torque ripple and so on . The simulation results show that torque ripple has been controlled by Direct Torque Control and the noise is reduced. In order to make the speed control system structure more simple, safer and more reliable, this paper presents a new approach to the position sensorless control of switched reluctance machine base on Generalized Regression Neural Network. The simulation results show that it controls very well using this methed.At last, the hardware circuit of ventilation speed control system is designed, in which TMS320F2812 DSP is as the core controller. The design of SRM control circuit includes the main control module, power converter, current detection module, voltage detection module and protection module,and process flow diagrams are drawed.