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Bayesian network combined fuzzy c-means methodology for turbine blades fatigue performance evaluation

  • Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a fatigue performance evaluation model for steam turbine blades based on Bayesian network combined fuzzy c-means algorithm was proposed. Bayesian network was viewed as a classification technique to evaluate fatigue performance. Fuzzy c-means algorithm was applied to perform cluster analysis of fatigue performance values and made them discrete. Low-cycle fatigue tests on certain kind of steam turbine blades were performed. Experiment results well examined the validity of the evaluation model. The proposed methodology significantly provided a possible approach to assist operators and engineers in carrying out online monitoring of blades' fatigue degradation.

Original languageEnglish
Title of host publicationProceedings - International Conference on Future Power and Energy Engineering, ICFPEE 2010
Pages87-90
Number of pages4
DOIs
StatePublished - 2010
Event2010 International Conference on Future Power and Energy Engineering, ICFPEE 2010 - Shenzhen, China
Duration: 26 Jun 201027 Jun 2010

Publication series

NameProceedings - International Conference on Future Power and Energy Engineering, ICFPEE 2010

Conference

Conference2010 International Conference on Future Power and Energy Engineering, ICFPEE 2010
Country/TerritoryChina
CityShenzhen
Period26/06/1027/06/10

Keywords

  • Bayesian network
  • Fuzzy c-means
  • Turbine blades
  • fatigue performance evaluation
  • online monitoring

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