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Bayesian Network Combined Fuzzy C-means Methodology for Turbine Blades Fatigue Performance Evaluation

机译:贝叶斯网络结合模糊C均值方法评估涡轮叶片疲劳性能

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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 bladesȁ9; fatigue degradation.
机译:本文提出了一种基于贝叶斯网络组合模糊C型算法的汽轮机叶片疲劳性能评价模型。贝叶斯网络被视为一种评估疲劳性能的分类技术。模糊C均值算法应用于对疲劳性能值进行集群分析,使其离散。进行对某种汽轮机叶片的低循环疲劳试验。实验结果良好地检查了评估模型的有效性。该方法的方法显着提供了一种可能的方法,可以帮助运营商和工程师在进行在线监测刀片ȁ9;疲劳降解。

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