Study of Fault Diagnosis of Integrate of D-S Evidence Theory Based on Neural Network for Turbine

Abstract

A fault diagnosis method of integrate of D-S evidential theory based on neural network was presented for turbine. In this method, preliminary diagnosis of fault information with BP and RBF network constitute the initial diagnosis layer; then, the each result of preliminary diagnosis as a body of evidence are fused under the D-S evidential theory for obtaining diagnostic results. Compared to a single diagnosis method, the simulation results show that the proposed method can effectively diagnose the vibration fault of turbine, can avoid misdiagnosis, and has good application prospects.