Diagnosis of aero-engine with early vibration fault symptom using DSmT
Qiang Li · Journal of Aerospace Power · 2012
Multisensor network information fusion method was used to diagnose the aeroengine with early vibration fault symtom,and several vibration sensors had been fixed on different positions of the aeroengine to build the multisensor network.However the information collected from different sensors would highly conflicts when early vibration fault happens,and the information fusion result get by Dempster-Shafer rule would be unreasonable,so Dezert-Smarandache theory(DSmT) was applied to solve the problem.In the early vibration fault diagnosis system proposed in this paper,firstly,a method based on the intrinsic mode functions(IMF) energy entropy was used to extract the signal's feature;secondly,basic belief assignment function was constructed based on the output of the back propagation(BP) neural network;lastly,DSmT combination rule was used to combine the different evidences and make the final decision.Two examples suggest the approach is available to solve the problem of high-conflict information fusion when early vibration fault happens,and the diagnosis results are reliable and effective.