Research on the Safety Fault Diagnosis System of Mine Based on Information Fusion

Abstract

 The failure of any equipment in coal mine will directly affect the safety of coal mine staff and directly threaten the safe operation of the mine. When coal mine equipment is running in a complex and changeable environment, a single fault feature is difficult to accurately reflect the fault, which is easy to lead to misjudgment and missed judgment. Using a combination of AHP and evidence theory can improve the accuracy and reliability of the evaluation. This method determines the weight of each evaluation factor through AHP. In this process, D-S evidence theory is used to fuse and modify the expert scoring data. The synthesis rule of D-S evidence theory is used to determine the risk value of coal mine equipment. The experimental results show that: compared with the single signal fault diagnosis method, this method can diagnose the equipment fault more effectively, improve the accuracy of fault diagnosis, and be applied in the fields with higher requirements for fault identification accuracy. The method is applied to the safety risk assessment of the mine. The results show that the mine construction is at a good level, which is consistent with the mine construction and verifies the model's credibility.