| 灰色理论与时序模型的发动机状态监测分析 |
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| 引用本文： | 王强,戴晟晖.灰色理论与时序模型的发动机状态监测分析[J].计算机工程与应用,2009,45(8):246-248. |
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| 作者姓名： | 王强 戴晟晖 |
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| 作者单位： | 东华理工大学信息工程学院,江西,抚州,344000 |
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| 基金项目： | 辽宁省教育厅高等学校科学研究项目 |
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| 摘 要： | 针对目前发动机磨损状态监测中磨粒数量预测方法存在的问题,提出了基于灰色理论与时序模型相结合的预测方法,建立了灰色时序组合模型.通过灰色GM(1,1)模型模拟数据宏观变化趋势,并用时序AR(P)模型建立了残差序列以模拟数据微观变化趋势.通过对实测数据进行检验与比较,证明该组合模型在发动机状态监测中具有更好的预报效果.
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| 关 键 词： | 灰色理论 时序模型 状态监测 |
| 收稿时间： | 2008-1-4 |
| 修稿时间： | 2008-4-15
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Engine condition monitoring based on grey auto-regressive combination model |
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| WANG Qiang,DAI Sheng-hui.Engine condition monitoring based on grey auto-regressive combination model[J].Computer Engineering and Applications,2009,45(8):246-248. |
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| Authors: | WANG Qiang DAI Sheng-hui |
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| Affiliation: | WANG Qiang,DAI Sheng-hui School of Information Engineering,Eost China Institute of Technology,Fuzhou,Jiangxi 344000,China |
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| Abstract: | Aiming at the problems of the wear condition monitoring,grey theory and auto-regressive combination forecasting model was put forward,and the combination model was build.The rough trend of the wear particle content change can be reflect-ed through grey theory,and the detail of the change can be reflected through auto-regressive model.By testing and comparing a set of Ferro graphic data,the result shows that the combination model has a better forecasting result. |
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| Keywords: | grey theory auto-regressive model condition monitoring |
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