首页> 外文会议>IEEE International Workshop on Metrology for Aerospace >The CoDeF structure: A way to evaluate Ai including failures caused by multiple minor degradations
【24h】

The CoDeF structure: A way to evaluate Ai including failures caused by multiple minor degradations

机译:CoDeF结构:一种评估Ai的方法,包括由多个较小的退化引起的故障

获取原文

摘要

Recent developments in the Logistic Engineering field are expanding the range of analysis for Operational Availability (Ao) from purely statistical models to include prognostic models. The prognostic method allows to obtain data on otherwise costly to test failure mechanics, while also providing information on the component degradation physics and their performance alteration. Failure in a system is commonly considered to be dependent on the detected malfunctioning of one or more items, as per the standard FMECA approach. A system failure though may also be caused by the concurrent degradation of multiple items performances which brings the system performance below a critical level. The performance degradation of those items is insufficient to trigger an alarm, which leads to cases of system failures with all components nominally in a working state. By using the degradation data obtained by the new prognostic models this paper introduces an analysis (named CoDeF) alternative to the RBD (Reliability Block Diagram). This approach is potentially able to take into consideration this latter type of system failure in the determination of the system Ai.
机译:物流工程领域的最新发展正在将运营可用性(Ao)的分析范围从纯粹的统计模型扩展到包括预测模型。这种预后方法可以获取用于测试故障力学的成本高昂的数据,同时还可以提供有关组件退化物理及其性能变化的信息。根据标准FMECA方法,通常认为系统故障取决于检测到的一项或多项故障。但是,系统故障也可能是由于多项性能同时降低而导致的,这会使系统性能降至关键水平以下。这些项目的性能下降不足以触发警报,从而导致系统故障,所有组件都名义上处于工作状态。通过使用新的预测模型获得的降级数据,本文介绍了一种替代RBD(可靠性框图)的分析方法(称为CoDeF)。该方法潜在地能够在确定系统Ai时考虑后一种类型的系统故障。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号