Compound Uncertainty Quantification and Aggregation for Reliability Assessment in Industrial Maintenance
Compound Uncertainty Quantification and Aggregation for Reliability Assessment in Industrial Maintenance
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DOI：
10.3390/machines11050560
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发表时间：
2023-05
期刊：
影响因子：
2.6
通讯作者：
Alex Grenyer;J. Erkoyuncu;S. Addepalli;Yifan Zhao
中科院分区：
文献类型：
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作者：
Alex Grenyer;J. Erkoyuncu;S. Addepalli;Yifan Zhao
现代工程系统的技术复杂性不断增加，需要从定量和定性的角度进行复合不确定性量化。本文提出了一个复合不确定性量化和聚合 (CUQA) 框架，用于确定复合输出以及通过全局敏感性分析确定最大不确定性贡献。这在两个案例研究中得到了验证：定制热交换器试验台和模拟涡轮风扇发动机。结果证明了复合不确定性的有效测量以及对系统可靠性的个体影响。进一步的工作将得出预测服务中不确定性的方法，并将该框架与更复杂的案例研究相结合。
The mounting increase in the technological complexity of modern engineering systems requires compound uncertainty quantification, from a quantitative and qualitative perspective. This paper presents a Compound Uncertainty Quantification and Aggregation (CUQA) framework to determine compound outputs along with a determination of the greatest uncertainty contribution via global sensitivity analysis. This was validated in two case studies: a bespoke heat exchanger test rig and a simulated turbofan engine. The results demonstrated the effective measurement of compound uncertainty and the individual impact on system reliability. Further work will derive methods to predict uncertainty in-service and the incorporation of the framework with more complex case studies.