A PREDICTIVE TOOL FOR REMAINING USEFUL LIFE ESTIMATION OF ROTATING MACHINERY COMPONENTS

机译：保留旋转机械组件使用寿命的预测工具

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This paper introduces a model for multiple degradation features of an individual component. The maximum likelihood approach is employed to estimate the model parameters. Afterwards, a proportional hazards model is presented, which considers hard failures and multiple degradation features simultaneously. The integrated model enables us to predict the mean remaining useful life of a component based on on-line degradation information. An example for bearing prognostic is provided to demonstrate the proposed models in practical use.

机译：本文介绍了单个组件的多个降级特征的模型。采用最大似然法估计模型参数。之后，提出了比例风险模型，该模型同时考虑了硬故障和多种退化特征。集成模型使我们能够基于在线降级信息来预测组件的平均剩余使用寿命。提供了轴承预后的示例，以证明所建议的模型在实际使用中。

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《ASME(American Society of Mechanical Engineers) International Design Engineering Technical Conferences and Computers and Information in Engineering Conference 2005(DETC2005) vol.1: Biennial Conference on Mechanical Vibration and Noisen pt.A; 20050924-28;》|2005年|P.509-515|共7页
会议地点 Long BeachCA(US)
作者
Haitao Liao; Hai Qiu; Jay Lee; Daming Lin; Dragan Banjevic; Andrew Jardine;
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作者单位

Center for Intelligent Maintenance Systems, University of Cincinnati, 598 Rhodes Hall, Cincinnati, OH 45221;

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原文格式 PDF
正文语种 eng
中图分类工业设计;计算技术、计算机技术;
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机译：一种用于剩余旋转机械组件的有用寿命估计的预测工具
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7. Predicting remaining useful life of rotating machinery based artificial neural network [O] . Mahamad Abd Kadir, Saon Sharifah, Hiyama Takashi 2010

机译：基于人工神经网络预测旋转机械的剩余使用寿命

A PREDICTIVE TOOL FOR REMAINING USEFUL LIFE ESTIMATION OF ROTATING MACHINERY COMPONENTS

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