Fault diagnosis of hydropower unit based on AFSA-BP neural network and rough set
Xutao Wu · Ningxia Electric Power · 2012
The neural network combined with the rough set optimized by artificial fish swarm is ap plied to the fault diagnosis of hydroelectric units.We use the clustering characteristics of the artificial fish swarm algorithm to improve the attribute reduction of rough set and reduce the fault information of hydropower units to obtain the key fault features.And,the BP neural network is used to diagnose the fault information processed by the modified rough set.The experimental result shows that the method can reduce the dimension of the neural network inputs and simplifying the structure of the neural net work,andeffectivelyimprovetheaccuracyofthe fault diagnosis.