Application of Probabilistic Causal-effect Model based Artificial Fish-Swarm Algorithm for Fault Diagnosis in Mine Hoist

This paper presents an intelligent methodology for diagnosing incipient faults in mine hoist. As Probabilistic Causal-effect Model-Based diagnosis is an active branch of Artificial Intelligent, in this paper, the feasibility of using probabilistic causal-effect model is studied and it is applied in artificial fish-swarm algorithm (AFSA) to classify the faults of mine hoist. In probabilistic causal-effect model, we employed probability function to nonlinearly map the data into a feature space, and with it, fault diagnosis is simplified into