HEALTH MONITORING AND PROGNOSTIC ASSESSMENT IN A FLEET CONTEXT

机译：机队环境中的健康监测和预后评估

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Prognostics aims at estimating the remaining useful life in order to plan a maintenance action before unit performances are affected. However, such goal is hard to reach since many parameters affect system's behaviour. Many approaches have been proposed to performed prognostics each of them with strength and weakness. In the present paper we propose to follow historical based prognostics together with the notion of fleet. The originality of the paper lies in the use of "similar" system historical instead of identical system historical as usually done in such approaches. In the present paper a fleet is composed of heterogeneous units (mainly components but could be systems or sub-systems) that are grouped together considering some similarities. Hence, the fleet can provide capitalized data and information coming from other members of the fleet for the prognostics. In order to achieve such a goal within a fleet-wide dimension, it is thus necessary to manage relevant knowledge arising from the fleet taking into account heterogeneities and similarities amongst components, operational context, behaviours, etc. This paper will focus mainly in the formalization of a data-driven prognostic model considering a fleet-wide approach. The model is based on a prognostic approach of the system health using Relevant Vector Machine. The proposed model is based on historical data coming from similar units of a fleet. The heterogeneity of the monitored data is treated by assessing a global health index of the units. The proposed approach is shown on a case study in the marine domain.

机译：预测旨在评估剩余的使用寿命，以便在影响设备性能之前计划维护工作。但是，由于许多参数会影响系统的性能，因此很难达到这一目标。已经提出了许多方法来执行每种方法的优点和缺点。在本文中，我们建议遵循基于历史的预测以及车队的概念。本文的独创性在于使用“类似的”系统历史记录，而不是像通常在这种方法中所做的相同的系统历史记录。在本文中，舰队由异构单元（主要是组件，但可能是系统或子系统）组成，考虑到一些相似性，这些单元被组合在一起。因此，车队可以提供来自车队其他成员的大写数据和信息来进行预测。为了在整个机队范围内实现这一目标，因此有必要管理机队产生的相关知识，并考虑组件之间的异质性和相似性，操作环境，行为等。本文将主要关注形式化考虑整个车队方法的数据驱动的预测模型。该模型基于使用相关向量机的系统健康状况的预测方法。所提出的模型基于车队类似单位的历史数据。通过评估单位的总体健康指数来处理监视数据的异质性。在海洋领域的案例研究中显示了所提出的方法。

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《Technology solutions for affordable sustainment》|2014年|247-270|共24页
会议地点 Virginia Beach VA(US)
作者
Alexandra Voisin; Gabriela Medina-Oliva; Maxime Monnin; Jean-Baptiste Leger; Benoit Iung;
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Centre de Recherche en Automatique de Nancy (CRAN), Universite de Lorraine, UMR 7039 CNRS-UHP-INPL, Faculte des Sciences-1er Cycle - BP239, 54506 Vandoeuvre-Les-Nancy Cedex - France;

PREDICT 19, Avenue de la Foret de Haye, CS 10508, 54519 Vandoeuvre-Les-Nancy, FRANCE;

PREDICT 19, Avenue de la Foret de Haye, CS 10508, 54519 Vandoeuvre-Les-Nancy, FRANCE;

PREDICT 19, Avenue de la Foret de Haye, CS 10508, 54519 Vandoeuvre-Les-Nancy, FRANCE;

Centre de Recherche en Automatique de Nancy (CRAN), Universite de Lorraine, UMR 7039 CNRS-UHP-INPL, Faculte des Sciences-1er Cycle - BP239, 54506 Vandoeuvre-Les-Nancy Cedex - France;

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正文语种 eng
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health assessment; fleet-wide; ontology; prognostics;

机译：健康评估；整个机队；本体预后;

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HEALTH MONITORING AND PROGNOSTIC ASSESSMENT IN A FLEET CONTEXT

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