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Physics of failure-based reliability prediction of turbine blades using multi-source information fusion

机译:使用多源信息融合的涡轮机叶片的失效可靠性预测物理

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摘要

Fatigue and fracture of turbine blades are fatal to aero engines. Reliability prediction of aero engines is indispensable to guarantee their safety. For turbine blades of aero engines, most recent research works only focus on the number of cycles and excavate information from a single source. To remove these limitations, a Physics of failure-based reliability prediction method using multi-source information fusion has been developed in this paper to predict the reliability of turbine blades of aero engines. In the proposed method, the fuzzy theory is employed to represent uncertainties involved in prediction. Case studies of reliability prediction under fuzzy stress with and without fuzzy strength are conducted by using a dynamic stress-strength interference model which takes types of cycles of aero engines into consideration. Results indicate that the proposed method is better in line with engineering practice and more flexible in decision making and it can predict the reliability of aero engine turbine blades to be an interval by utilizing the proposed linear fusion algorithm. In addition, the predicted interval contains results that are predicted by other commonly used information fusion methods Hence, the proposed method conduces to remove confusion made by selection of multiple methods. (C) 2018 Elsevier B.V. All rights reserved.
机译:涡轮叶片的疲劳和骨折是Aero发动机的致命。 Aero发动机的可靠性预测是不可或缺的,可以保证其安全性。对于Aero发动机的涡轮机叶片,最近的研究工作仅关注周期数并从单个来源挖掘信息。为了消除这些限制,本文开发了使用多源信息融合的故障基可靠性预测方法的物理学,以预测航空发动机涡轮叶片的可靠性。在所提出的方法中,采用模糊理论代表了预测所涉及的不确定性。通过使用动态应力 - 强度干扰模型进行模糊应力在模糊应力下的可靠性预测的案例研究,考虑到Aero发动机的周期循环。结果表明,该方法符合工程实践更好,在决策中更灵活,并且它可以通过利用所提出的线性融合算法来预测航空发动机涡轮机叶片的可靠性。另外,预测的间隔包含由其他常用的信息融合方法预测的结果,因此该方法可涉及通过选择多种方法而消除混淆。 (c)2018 Elsevier B.v.保留所有权利。

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