Fault Diagnosis Based on Particle Swarm Optimization by Artificial Immunisation Algorithm

Particle swarm optimization (PSO) is a new general machine-learning tool under the evolutionary algorithms (EAs) and gained lots of attention in various engineering applications, this paper presents an intelligent methodology for diagnosing incipient faults in mine hoist. Artificial immunisation algorithm (AIA) is used to optimise the parameters in PSO in this paper. The AIA is a new optimisation method based on the biologic immune principle of human being and other living beings. It can effectively avoid the premature convergence and guarantees the variety of solution. With the parameters optimised by AIA, the total capability of the PSO classifier is improved. The fault diagnosis of mine hosit shows that the PSO optimised by AIA can give higher recognition accuracy than the normal PSO.