Title :
Selection of optimum maintenance strategy for power plant equipment based on evidential reasoning and FMEA
Author :
Dong, Y.L. ; Gu, Y.J. ; Dong, X.F.
Author_Institution :
Key Lab. of Condition Monitoring & Control for Power Plant Equip. of Minist. of Educ., North China Electr. Power Univ., Beijing, China
Abstract :
Aiming at the problem that it is difficult to select optimum maintenance strategy for power plant equipment, a method based on criticality evaluation and failure mode characteristic analysis is put forward. In the method, the uncertainty and incompletion of criticality evaluation factors are completely considered, qualitative and quantitative evidences are integrated and their acquisition and transformation method is put forward based on constructing criticality evaluation multiple-attribute decision tree. Then a decision tree criticality evaluation model is established, a corresponding evidential reasoning algorithm is deduced, and the equipment in power plant is ranked by criticality. Integrating the results of criticality evaluation and failure mode and effect analysis (FMEA), the decision model of selecting optimum maintenance strategy of power plant equipment is established and applied in a fossil-fired power station. It is shown by the instance that this method is feasible and effective, can select optimum maintenance strategy for power plant equipment.
Keywords :
case-based reasoning; decision trees; fault diagnosis; maintenance engineering; power apparatus; power engineering computing; thermal power stations; FMEA; criticality evaluation multiple-attribute decision tree; evidential reasoning algorithm; failure mode and effect analysis; fossil-fired power station; optimum maintenance strategy; power plant equipment; Availability; Costs; Decision trees; Failure analysis; Laboratories; Power generation; Predictive maintenance; Preventive maintenance; Safety devices; Uncertainty; Power plant equipment; evidential reasoning; failure mode and effect analysis; maintenance strategy;
Conference_Titel :
Industrial Engineering and Engineering Management, 2008. IEEM 2008. IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-2629-4
Electronic_ISBN :
978-1-4244-2630-0
DOI :
10.1109/IEEM.2008.4737992