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Selection and Validation of Health Indicators in Prognostics and Health Management System Design

机译:预测和健康管理系统设计中健康指标的选择和验证

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摘要

Health Monitoring is the science of system health status evaluation. In the modern industrial world, it is getting more and more importance because it is a powerful tool to increase systems dependability. It is based on the observation of some variables extracted in operation reflecting the condition of a system. The quality of health monitoring strongly depends on the selection of these variables named health indicators. However, the issue in their selection is often underestimated and their validation is, of what is known, an untreated subject. In this paper, the authors introduce a complete methodology for the selection and validation of health indicators in health monitoring systems design. Although it can be applied either downstream on real measured data or upstream on simulated data, the true interest of the method is in the latter application. Indeed, a model-based validation can be integrated in the design phases of the system development process, thereby reducing potential controller retrofit costs and useless data storage. In order to simulate the distribution of health indicators, a well known surrogate model called Kriging is utilized. Eventually, the method is tested on a benchmark system: the high pressure pump of aircraft engines fuel systems. Thanks to the method, the set of health indicators was validated in system design phases and the monitoring is now ready to be implemented for in-service operation.
机译:健康监控是系统健康状况评估的科学。在现代工业世界中,它变得越来越重要,因为它是增加系统可靠性的强大工具。它基于对操作中提取的一些变量的观察,这些变量反映了系统的状态。健康监控的质量在很大程度上取决于对这些名为健康指标的变量的选择。然而,选择他们的问题通常被低估了,并且他们的确认是未经治疗的受试者。在本文中,作者介绍了在健康监测系统设计中选择和验证健康指标的完整方法。尽管可以将其应用于实际测量数据的下游,也可以应用于模拟数据的上游,但该方法的真正目的在于后者。实际上,基于模型的验证可以集成到系统开发过程的设计阶段,从而减少潜在的控制器改造成本和无用的数据存储。为了模拟健康指标的分布,使用了一种称为Kriging的众所周知的替代模型。最终,该方法在基准系统上进行了测试:飞机发动机燃油系统的高压泵。由于采用了这种方法,因此在系统设计阶段就验证了一组健康指标,并且现在可以为运行中的操作实施监视了。

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