Airflow Optimizing Control Research Based on Genetic Algorithm During Mine Fire Period

Abstract

Mine fire is a very complex physicochemical process. Once it happens, there are lots of poisonous and harmful gas ingredients while the oxygen density is greatly reduced. Such gas will cause poison, suffocation or death if it is inhaled. As we know, the main cause of great amount of person losses during mine fire is fume poison and suffocation. Additionally, the fume caused by the fire will block the vision and decrease the visibility, which will impede human evacuation and fire fighting. Moreover, due to the turbulent airflow of ventilation network during mine fire period, it is easy to cause the gas and coal dust explosion. So it is very important for the evacuation of miners and mining salvation to research the air flow control during mine fire.

In this paper, Genetic Algorithm (GA) is used to solve wind-flow quantitative optimizing control. And in “Introduction” we introduce some researches of airflow control of mining fire. In “Main Principles of Airflow Control During Mine Fire Period”, the fundamental principles of airflow control during mine fire are introduced. The airflow optimizing control models are introduced in “Nonlinear Programming Model of Air Current Optimum Control During Mine Fire Period”. In “Computation of Nonlinear Programming of Airflow Control During Mining Fire Period”, the computation methods and the selection of relative parameters of the control model are discussed. Finally, a computation example is given.