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构建数据驱动性能数字双胞胎,用于现实世界燃气轮机异常检测,考虑到不确定性
Yangfeifei Ma1, Xinyun Zhu2, Jilong Lu2
1College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
Sensors (Basel, Switzerland)
|August 12, 2023
概括
这项研究引入了一种用于燃气轮机发动机的新型数字双胞胎,以检测异常. 该方法有效地识别了异常的发动机性能,提高了运行可靠性和维护决策.
科学领域:
- 航空航天工程 航空航天工程
- 机械工程 机械工程
- 数据科学数据科学数据科学
背景情况:
- 燃气轮机的可靠运行至关重要.
- 现有的异常检测方法可能缺乏精度.
- 预测故障需要强大的监控系统.
研究的目的:
- 开发一种新的数据驱动的数字双胞胎,用于气轮机异常检测.
- 为了提高燃气轮机运行的可靠性和安全性.
- 支持知情的操作和维护决策.
主要方法:
- 开发了一个数据驱动的性能数字双胞胎,包括一个不确定的性能数字双胞胎 (UPDT) 和故障检测能力.
- 在UPDT模型中,预期的引擎行为是概率性的.
- 异常检测利用第一个瓦瑟斯坦距离来识别与正常运行分布的偏差.
主要成果:
- 该方法在商业轮风扇发动机数据集上获得了0.99的最大F1分数,值为0.45.
- 该方法有效地识别了个别性能信号中的异常样本和孤立的异常行为.
- 在UPDT中的不确定性量化支持健康评估和故障检测.
结论:
- 拟议的数字双胞胎方法为燃气轮机异常检测提供了一种高度有效的方法.
- 这种技术可以显著提高运行可靠性,并有助于主动维护.
- 隔离异常的能力有助于随后的故障诊断.
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