Research on Fault Diagnosis of Mine Ventilator Bearing based on Cross Entropy Algorithm

In the construction and production of coal mines, the mine fan is obviously very important, and its function is to ensure the safety of the underground workers in the mine. If the mine fan fails, it will cause inestimable losses and bring subsequent problems. Therefore, it is necessary to study the safe use and operation of mine ventilator. Aiming at the common bearing failures of mine ventilators, this paper innovates a fault diagnosis model based on rough set attribute reduction and cross entropy algorithm. Through the study of the model, the following conclusions are drawn: This paper combines rough set attribute reduction and cross entropy algorithm, which is very good for fault detection of mine fan bearings, and can be considered in actual production.