Failure diagnosis of steam turbine-generator based on improving BP network and particle swarm optimization algorithm

In order to overcome the problems of slow rate of convergence and falling easily into local minimum in BP algorithm, this paper introduces the adaptive particle swarm optimization algorithm and combining model. The paper applies it to steam turbine-generators fault diagnosis. The experiment data shows that the algorithm converges quickly and recognizes faults efficiently; it has a reference value for faults diagnosis.