Vibration Fault Diagnosis of Hydroelectric Generating Sets Based on Information Fusion Technology
Xiong We · Yellow River · 2014
For the reasons of low vibration fault diagnosis accuracy of traditional diagnosis methods on hydroelectric generating sets,a method of particle swarm optimization neural network model combined with evidence theory was applied. The two parallel particle swarm optimization neural networks were used to carry on local fault diagnosis and acquire independent evidences each other for the different vibration fault symptom domains of hydroelectric generating sets,then the evidence theory was employed to fuse evidences. Experimental results show that the method is good to im prove the reliability of the diagnosis and decrease the diagnostic uncertainty.