| 多维非平稳时间序列在机床主轴故障诊断中的应用 |
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| 引用本文： | 周尧,洪荣晶,李磊,李俊超.多维非平稳时间序列在机床主轴故障诊断中的应用[J].机床与液压,2007,35(6):228-230. |
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| 作者姓名： | 周尧 洪荣晶 李磊 李俊超 |
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| 作者单位： | 南京工业大学机械与动力工程学院,南京,210009 |
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| 摘 要： | 采用ARIMA模型将数控机床主轴故障初期的非平稳时间序列转化成标准平稳时间序列,然后利用多维自回归(AR)模型进行数据处理与趋势预测,并分析了基于多维自回归序列参数估计的Yule-Walker算法以及FPE阶次判定准则.实测数据的计算结果表明:经稳态处理后的多维AR时序模型能够很好地拟合数控机床主轴故障模型,预测的精度符合要求.
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| 关 键 词： | 机床主轴 多维AR模型 Yule-Walker 非平稳 平稳时间序列 机床主轴 故障诊断 应用 Spindle Fault Diagnosis Time Series Multidimensional 精度 趋势预测 故障模型 合数 时序模型 数据处理 稳态 结果 计算 实测数据 判定准则 阶次 |
| 文章编号： | 1001-3881（2007）6-228-3 |
| 修稿时间： | 2006-06-16 |
Application of Multidimensional Non-stationary Time Series on Fault Diagnosis of Spindle |
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| ZHOU Yao,HONG Rongjing,LI Lei,LI Junchao.Application of Multidimensional Non-stationary Time Series on Fault Diagnosis of Spindle[J].Machine Tool & Hydraulics,2007,35(6):228-230. |
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| Authors: | ZHOU Yao HONG Rongjing LI Lei LI Junchao |
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| Affiliation: | School of Mechanical and Power Engineering, Nanjing University of Technology, Nanjing 210009, China |
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| Abstract: | The non-stationary time series,obtained during spindle running in ill conditions,was transformed into standard normal stationary time series using ARIMA model,and the AR model was used in data processing and forecasting.Yule-Walker algorithms and rank confirmation with final prediction error(FPE)were analyzed based on the multidimensional autoregressive parameter estimation.The experimental results show that stabilized multidimensional AR model can simulate spindle fault model,and meet the needs of forecasting. |
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| Keywords: | Spindle Multidimensional autoregressive model Yule-Walker Non-stationary |
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