标准化诊断贡献指数 (NDCI) 集成到多目标传感器优化框架 (MOSOF) -一个环境控制系统案例
Burak Suslu1, Fakhre Ali1, Ian K Jennions1
1Integrated Vehicle Health Management Centre, School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK.
Sensors (Basel, Switzerland)
|May 14, 2025
概括
本研究将标准化诊断贡献指数 (NDCI) 引入航空航天系统的传感器优化框架. 改进的方法提高了对航空公司和MRO等利益相关方的诊断效率和传感器选择.
科学领域:
- 航空航天工程 航空航天工程
- 系统工程 系统工程
- 数据科学数据科学数据科学
背景情况:
- 有效的传感器优化对于航空航天领域的诊断,资源管理和维护至关重要.
- 现有的方法可能无法完全满足特定应用需求或利益相关者的不同要求.
研究的目的:
- 将标准化诊断贡献指数 (NDCI) 纳入多目标传感器优化框架 (MOSOF).
- 加强航空航天系统的传感器优化,考虑多个利益相关方的观点 (OEM,航空公司,MRO).
- 通过一种新的优化方法,提高诊断效率并减少传感器冗余.
主要方法:
- 在MOSOF中使用了多目标遗传算法.
- 从使用SESAC平台的波音737-800环境控制系统 (ECS) 模拟数据中得出的NDCI.
- 分析了四种故障模式中的传感器性能,并根据最小冗余最大相关性 (mRMR) 方法进行了评估.
主要成果:
- NDCI-MOSOF确定了一个最佳的三个传感器组,超过了mRMR的六个传感器解决方案.
- 为所有利益相关者证明了诊断效率的显著改善.
- 扩大了传感器配置的解决方案空间,优先考虑诊断价值而不是单纯的冗余性.
结论:
- 增强的NDCI-MOSOF为下一代传感器优化提供了一个可扩展的,多利益相关者解决方案.
- 这种方法对于推进复杂的航空航天系统的预测性维护至关重要.
- 这种集成在确定针对特定诊断需求量身定制的最佳传感器集方面具有明显的优势.
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