Title :
Research on fault diagnosis method of steam turbine generator unit based on multilayer information fusion
Author_Institution :
Hebei Univ. of Eng., Handan, China
Abstract :
Based on the idea of Multilayer information fusion technology, and from the reality of equipment fault diagnosis, We established neural network evidence fusion fault diagnosis system which is based on information fusion technology. Neural network has good nonlinear mapping ability, and d-s evidence theory has unique advantages in the expression of uncertainty. Both of the two methods have been widely used in the field of fault diagnosis. That is, through the effective combination of the fault feature information, use the seeds of neural network from different sides for equipment fault diagnosis of preliminary, then applying the preliminary diagnosis to Dempster - Shafer theory evidence for decision fusion. The diagnosis example indicates that, after fault feature information fusion, the credibility of the diagnostic increased significantly, and can effectively improve the diagnosis rate.
Keywords :
fault diagnosis; inference mechanisms; neural nets; power engineering computing; sensor fusion; steam turbines; uncertainty handling; Dempster-Shafer theory; d-s evidence theory; decision fusion; fault diagnosis method; multilayer information fusion technology; neural network evidence fusion; nonlinear mapping ability; steam turbine generator unit; Films; Oscillators; Reliability; Rotors; Shafts; D-S evidence theory; Multilayer information fusion; fault diagnosis; steam turbine generator unit;
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2013 4th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-4997-0
DOI :
10.1109/ICSESS.2013.6615478