Research On The Intelligent Control System Of Partial Ventilator In High Gassy Mine

The system of partial ventilator in coal mine is an important link related to the safety of coal mine production.Good aeration in tunneling face can be ensured by the normal operation of this system,which provides a safe production environment for underground workers.The research object of this topic is Huopu Coal Mine,which is a high gas mine.With complexed air demand calculation system,the gas emission is large and irregular,so it can not be calculated and predicted in real time.The speed regulation algorithm of system for partial ventilator is backward,and it can not achieve effective speed regulation of partial ventilator.Lacking emergency power supply device,the control system of partial ventilator has certain security risks.Therefore,the research and design of control system for partial ventilator is carried out in this topic to solve the above problems.Generally,the calculation of air demand in system of ventilator is based on the formula regularly.In high gas mines,the gas concentration changes rapidly,and the accurate prediction of air demand can not be achieved.Therefore,according to the parameters of gas,coal dust,temperature and humidity,the Elman neural network prediction method based on genetic algorithm optimization is put forward,which realizes the real-time prediction of air demand and provides data support for speed regulation of ventilator.System of partial ventilator is a complex non-linear system.and it is difficult to achieve good speed regulation by conventional methods.In this paper,a T-S fuzzy control strategy using neural network as identification component is proposed.According to the predicted air demand,the control of ventilator is realized,which has good speed control effect.Controller of system for partial ventilator lacks effective emergency power supply equipment,and the problem of gas accumulation can not be solved because of the power failure of control system in high gas environment.Therefore,redundant power supply system is designed for the controller,UPS emergency power supply is added,and Elman neural network is used to predict the remaining capacity of batteries.Battery management system is designed to manage the battery parameters of UPS and ensure the reliability of power supply.Finally,the intelligent control system of partial ventilator is designed,and the hardware structure of the system is added.LabVIEW software is used to design theupper computer monitoring system,which can monitor the status of the control system of partial ventilator and the redundant power supply system.