| 基于高阶统计量的机械故障特征提取方法研究 |
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| 引用本文： | 张桂才,史铁林,杨叔子.基于高阶统计量的机械故障特征提取方法研究[J].华中科技大学学报(自然科学版),1999,27(3):2. |
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| 作者姓名： | 张桂才 史铁林 杨叔子 |
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| 作者单位： | 华中理工大学机械科学与工程学院 |
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| 基金项目： | 国家“九·五”攀登计划预选资助 |
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| 摘 要： | 对高阶统计量用于机械故障特征提取进行了研究.
首先利用Hilbert变换构造原始信号的解析信号,求取信号的包络，然后计算包络信号的高
阶统计量.研究表明,用高阶统计量提取信号特征，可以容易地将正常齿轮信号和齿轮裂纹、
断齿的信号分离.
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| 关 键 词： | 高阶统计量 特征提取 机械故障诊断 |
| 修稿时间： | 1998-10-29 |
A Method for Extracting Mechanical Faults Features Based on Higher-Order Statistics |
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| Zhang Guicai,Shi Tielin,Yang Shuzi.A Method for Extracting Mechanical Faults Features Based on Higher-Order Statistics[J].JOURNAL OF HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY.NATURE SCIENCE,1999,27(3):2. |
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| Authors: | Zhang Guicai Shi Tielin Yang Shuzi |
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| Abstract: | The application of higher order statistics extracting of
mechanical falut features is studied. The analytical signals are acquired by means of Hilbert
transformation of the original singals. The enveloped signals are calculated from the analytical
signals. The higher order cumulants and moments of the enveloped signals are estimated. The
results of the research show that normal gear signals, cracked gear signals and broken gear
signals can be easily separated by using higher order statistics as the signal features. |
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| Keywords: | higher order statistics feature extraction mechanical fault diagnosis |
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