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首页> 外文会议>Advanced machinery technology symposium: advanced Naval machinery - an integrated solution >Machinery Life Cycle Cost Reduction Using CBM+ Predictive Maintenance Strategies
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Machinery Life Cycle Cost Reduction Using CBM+ Predictive Maintenance Strategies

机译：使用CBM +预测性维护策略降低机械生命周期成本

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摘要

Innovative technological advances in weapons systems, such as the Electromagnetic (EM) Railgun, have created research challenges in advanced sophisticated warfare that will drive the need to investigate predictive maintenance enablers such as diagnostics and prognostics while preserving its operational capabilities at low cost. Such endeavors greatly mitigate concerns regarding the rapid rise in degradation and catastrophic failure of machinery aboard naval vessels. In recent times, failure events have placed the spotlight on the unintentional consequences of inadequate maintenance practices that no longer fully support product life cycle sustainment. The subsequent impact to the operation and support logistics footprint are attributed to budgets and outdated maintenance strategies that do not take advantage of the current and future processing capability of large amounts of data and micro sized sensors in Navy systems. In this paper, we examine the nature of an electrically powered rotating machine to demonstrate how CBM+ predictive maintenance strategies within the Prognostics Health Management (PHM) framework address these maintenance gaps and allow for the planning of maintenance activities based on evidence of need. This predictive maintenance paradigm is the cornerstone of the modern high tech effort to reduce risk of machinery failures, increase operational availability and reduce life cycle costs.
机译：武器系统的创新技术进步，例如电磁（EM）轨道炮，在先进的复杂战争中提出了研究挑战，这将推动研究诸如诊断和预测等预测性维护要素的需求，同时以低成本保持其作战能力。这样的努力大大减轻了人们对海军舰船上的机械的迅速退化和灾难性故障的担忧。近年来，故障事件已引起人们的关注，即不充分的维护实践所带来的意外后果已不再完全支持产品生命周期的维持。对运营和后勤足迹的后续影响归因于预算和过时的维护策略，它们没有利用海军系统中当前和将来处理大量数据和微型传感器的能力。在本文中，我们检查了电动旋转机械的性质，以证明Prognostics Health Management（PHM）框架内的CBM +预测性维护策略如何解决这些维护差距，并允许根据需要的证据来计划维护活动。这种预测性维护范例​​是现代高科技努力的基石，以减少机械故障的风险，提高运营可用性并降低生命周期成本。

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