TY - JOUR
AU - Wang, Yuhang
AB - [ZPW-2000A joint-less frequency shift automatic block system has a crucial and realistic significance in maintaining the safety of railway transportation. The traditional fault diagnosis for ZPW-2000A is inefficient and troublesome. A new fault diagnosis method was proposed based on BP neural network, Particle Swarm Optimization Algorithm and Genetic Algorithm (PSO-GA-BP). In order to compare with the diagnostic performance of PSO-GA-BP, some other hybrid algorithms were also simulated. It came to the conclusion that PSO-GA-BP algorithm was more effective in convergent rate, convergent accuracy and diagnostic accuracy according to the simulation results. The PSO-GA-BP neural network is efficient, convenient and provides a new approach to fault diagnosis.]
TI - Electrical, Information Engineering and Mechatronics 2011: Fault Diagnosis of ZPW-2000A System Based on PSO-GA-BP Algorithm
DA - 2012-03-13
UR - https://www.deepdyve.com/lp/springer-journals/electrical-information-engineering-and-mechatronics-2011-fault-zuGIDD8eoH
DP - DeepDyve
ER -