| 基于经验模态分解的机械故障欠定盲源分离方法 |
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| 引用本文： | 李志农,吕亚平,范涛,冷传广.基于经验模态分解的机械故障欠定盲源分离方法[J].航空动力学报,2009,24(8):1886-1892. |
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| 作者姓名： | 李志农 吕亚平 范涛 冷传广 |
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| 作者单位： | 郑州大学机械工程学院;河南交通职业技术学院汽车工程系; |
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| 基金项目： | 国家自然科学基金(50775208);;河南省教育厅自然科学基金(2008C460003;2006460005) |
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| 摘 要： | 针对传统的机械故障源分离方法限于非高斯、平稳和相互独立的源信号,且传感器的观测数多于源数,机械故障源信号通常不易满足这些假设的局限性,提出了一种基于经验模态分解的机械故障欠定盲源分离方法.该方法对混合观测信号进行经验模态分解,然后重组本征模函数分量作为新的观测信号进行盲源分离,仿真和实验结果表明,该方法是有效的.
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| 关 键 词： | underdetermined blind source separation empirical mode decomposition（EMD） fault diagnosis time-frequency analysis |
| 收稿时间： | 2008/7/23 0:00:00 |
| 修稿时间： | 2008/10/31 0:00:00 |
Underdetermined blind source separation method of machine faults based on empirical mode decomposition |
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| Li Zhinong.Underdetermined blind source separation method of machine faults based on empirical mode decomposition[J].Journal of Aerospace Power,2009,24(8):1886-1892. |
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| Authors: | Li Zhinong |
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| Institution: | 1.School of Mechanical Engineering;Zhengzhou University;Zhengzhou 450001;China;2.Department of Automobile Engineering;Henan Vocational and Technical College of Communications;Zhengzhou 450005;China |
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| Abstract: | The traditional mechanical fault source separation method is restricted to nongaussian,stationary and mutually independent source signals,and the number of observations is assumed to be more than the number of sources.These deficiencies may cause many problems in the application of fault diagnosis,because fault signals generally do not meet these conditions.Based on these deficiencies,an underdetermined blind separation method of machine faults based on empirical mode decomposition(EMD) was proposed.The pro... |
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| Keywords: | underdetermined blind source separation empirical mode decomposition (EMD) fault diagnosis time-frequency analysis |
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