Fault Diagnosis of Hydro-turbine Generating Unit using Modified AFSA-based Rough Set Theory
Xing Xin, Hust Manufacturing · Journal of Hubei University of Technology · 2012
Due to the fact that the traditional artificial intelligence methods cannot effectively and timely analysis or can not be accurately diagnosed or misdiagnosed because of the ill-conditioned problem caused by inefficient discretization approaches,based on a large number of on-site monitoring data,a method based on rough set theory integrated with improved artificial fish-swarm algorithm(AFSA) was presented in this paper for fault diagnosis of hydro-turbine generating unit.Firstly,the improved artificial fish-swarm algorithm was used to discrete continuous attribute,and then the rough set theory was used to reduce the decision table.Therefore,the rules could be ued to diagnose the faults.The simulation results indicated that the method increased the diagnosis accuracy.