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Application of Bayesian networks in prognostics for a new Integrated Vehicle Health Management concept

机译:贝叶斯网络在车辆综合管理新概念预测中的应用

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The aeronautics industry is attempting to implement important changes to its maintenance strategy. The article presents a new framework for making final decision on aeroplane maintenance actions. It empha sizes on the use of prognostics within this global framework to replace corrective and Preventive Main tenance practise for a predictive maintenance to minimize the cost of the maintenance support and to increase aircraft/fleet operability. The main objective of the article is to show the Bayesian network model as a useful technique for prognosis. The specific use case for predicting brake wear on the plane is developed based on this technique. The network allows estimate brake wear from the aircraft opera tional plan. This model, together with other models to make predictions for various components of the aeroplane (that should be monitored) offers a forward-looking approach of the status of the plane, allow ing later the evaluation of different operational plans based on operational risk assessment and economic cost of each one of them depending on the scheduled checks.
机译:航空业正在尝试对其维护策略进行重要的更改。本文提出了一个新的框架,可以对飞机维护行动做出最终决定。它强调在此全球框架内使用预测技术来替代纠正性和预防性主要维护实践,以进行预测性维护,从而最大程度地减少维护支持的成本并提高飞机/机队的可操作性。本文的主要目的是显示贝叶斯网络模型作为一种有用的预后技术。基于此技术,开发了用于预测飞机上制动器磨损的特定用例。该网络允许根据飞机运行计划估算制动器的磨损。该模型与其他模型一起对飞机的各个组成部分(应进行监视)进行预测,从而提供了飞机状态的前瞻性方法,允许以后根据运营风险评估对不同的运营计划进行评估,每个人的经济成本取决于预定的检查。

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