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首页> 外文期刊>Mechanical systems and signal processing >Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression
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Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression

机译：基于回归支持向量机的涡轮叶片尖端径向游隙的分布式协同概率设计

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摘要

To improve the computational precision and efficiency of probabilistic design for mechanical dynamic assembly like the blade-tip radial running clearance (BTRRC) of gas turbine, a distribution collaborative probabilistic design method-based support vector machine of regression (SR)(called as DCSRM) is proposed by integrating distribution collaborative response surface method and support vector machine regression model. The mathematical model of DCSRM is established and the probabilistic design idea of DCSRM is introduced. The dynamic assembly probabilistic design of aeroengine high-pressure turbine (HPT) BTRRC is accomplished to verify the proposed DCSRM. The analysis results reveal that the optimal static blade-tip clearance of HPT is gained for designing BTRRC, and improving the performance and reliability of aeroengine. The comparison of methods shows that the DCSRM has high computational accuracy and high computational efficiency in BTRRC probabilistic analysis. The present research offers an effective way for the reliability design of mechanical dynamic assembly and enriches mechanical reliability theory and method.
机译：为了提高机械动力总成如燃气轮机的叶尖径向游隙（BTRRC）的概率设计的计算精度和效率，基于分布协同概率设计方法的回归支持向量机（SR）（称为DCSRM）结合分布协同响应面法和支持向量机回归模型提出了一种改进方法。建立了DCSRM的数学模型，并介绍了DCSRM的概率设计思想。完成了航空发动机高压涡轮（HPT）BTRRC的动态装配概率设计，以验证所提出的DCSRM。分析结果表明，在设计BTRRC时，可以获得最佳的HPT静叶尖间隙，从而提高了航空发动机的性能和可靠性。方法的比较表明，DCSRM在BTRRC概率分析中具有较高的计算精度和较高的计算效率。本研究为机械动力装配的可靠性设计提供了一种有效的方法，并丰富了机械可靠性的理论和方法。

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