Optimization of the non-stop switchover system control for the main fans used in mining applications

A stable ventilation system is an essential guarantee for the efficient production and safety of underground workers. In order to solve big changes in air quantity, gas accumulation, other problems caused by mine main fans switchover. This paper proposes a non-stop switchover based on intelligent control establishes dynamic optimization model process fans. The equilibrium optimizer algorithm improved chaos mapping opposition learning machine refraction principle model, simulation experiment carried out with MATLAB. results show that proposed method can effectively mitigate change quantity during 120 s operation, rate consistently within 0.4%, two always work interval, which proves system's high efficiency, stability safety.