基于混合不确定性量化与概率故障物理建模的高温结构寿命预测

项目名称： 基于混合不确定性量化与概率故障物理建模的高温结构寿命预测

项目编号： No.11302044

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 数理科学和化学

项目作者： 朱顺鹏

作者单位： 电子科技大学

项目金额： 28万元

中文摘要： 对重大装备高温结构进行寿命预测是保证其安全、可靠、有效运行的基础，寿命预测结论的可信性与多源不确定信息的处理和概率故障物理建模的过程密切相关，这也是高温结构寿命预测与健康管理的核心和难点。本项目针对高温结构寿命预测中多源不确定信息的小子样、动态性和不完备情况，以及承受载荷的时变性和多失效模式交互作用的复杂性等问题，以某型号航空发动机涡轮盘为应用对象，将随机集理论、模型验证与确认、Bayes推理与概率故障物理技术相结合，研究能够融合试验数据/定期检测数据/数值仿真结果/现场监测数据等多源信息并同时量化其蕴含的随机不确定性和认知不确定性的概率寿命预测方法，形成考虑多失效模式的交互作用并在时变载荷作用下的概率故障物理寿命预测理论，构建高温结构性能（寿命和可靠性）预测仿真平台，为高温构件的结构设计、安全评定和健康监测提供新的方法，对提高我国重大装备的可靠定寿预测能力并制定最优维修策略具有实用价值。

中文关键词： 高温结构；疲劳；寿命预测；不确定性；概率故障物理

英文摘要： Life prediction of high-temperature structures is a primary work ensuring safety and effectiveness of major equipments. The credibility of life prediction results is highly dependent on the processing of multi-source uncertain information and probabilistic Physics of Failure (PoF)-based modeling, which plays a critical role in the prognostics and health management of high-temperature structures. In consideration that life prediction of high-temperature structures are often faced with small sample test, dynamic, and imcomplete multi-source uncertain information under time-variant loading and multiple failure modes. This project investigates an application with an aircraft turbine disk, by means of random set theory, Bayes inference theory, model Verification and Validation (V&V) and probabilistic PoF-based technique, with the aim of such key scientific issues as follows: an integrated multi-source information fusion method dealing with test data, periodic inspections, numerical simulation results and field data for probabilistic life prediction is put forward based on the quantification of aleatory and epistemic uncertainty; a probabilistic PoF-based life prediction framework is presented for high-temperature structures under time-variant loading and multiple failure modes. Furthermore, a probabilistic PoF-based

英文关键词： High-temperature structures；fatigue；life prediction；uncertainty；Probabilistic Physics of Failure