| 噪声环境下机械故障源的盲分离 |
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| 引用本文： | 李志农,郝伟,韩捷,何永勇,褚福磊. 噪声环境下机械故障源的盲分离[J]. 农业机械学报, 2006, 37(11): 110-113 |
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| 作者姓名： | 李志农 郝伟 韩捷 何永勇 褚福磊 |
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| 作者单位： | 郑州大学振动工程研究所,450002,郑州市;清华大学精密仪器与机械系,100084,北京市 |
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| 基金项目： | 中国博士后科学基金;河南省教育厅自然科学基金;教育部跨世纪优秀人才培养计划 |
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| 摘 要： | 在机械故障盲分离中,传感器所获得的信号常常受到未知的不同类型的噪声干扰,忽略噪声的影响往往产生很差的分离效果。为克服此不足,结合小波变换和盲源分离,提出了一种在未知强背景噪声环境下的机械故障源分离方法,即小波消噪-BSS-小波消噪方法,仿真和实验结果表明该方法是有效的。
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| 关 键 词： | 故障诊断 盲源分离 小波消噪 独立分量分析 |
| 修稿时间： | 2005-05-10 |
Blind Separation of the Mechanical Fault Sources Under the Noise Environment |
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| Li Zhinong,Hao Wei,Han Jie,He Yongyong,Chu Fulei. Blind Separation of the Mechanical Fault Sources Under the Noise Environment[J]. Transactions of the Chinese Society for Agricultural Machinery, 2006, 37(11): 110-113 |
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| Authors: | Li Zhinong Hao Wei Han Jie He Yongyong Chu Fulei |
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| Affiliation: | 1.Zhengzhou University 2.Tsinghua University |
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| Abstract: | In the blind separation of machine faults, the vibration signal from the sensors mounted on the machine is generally suffered by the disturbance from different types of unknown noise. The neglect of the noise generally causes worse effect of separation. In order to overcome this deficiency, here, by means of combining the wavelet transformation and blind source separation (BSS),a new separation method of machine fault sources under the condition of unknown noise, which is named wavelet denoising-BSS-wavelet denoising, is proposed. The simulation and experiment results show that the proposed method is very effective. |
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| Keywords: | Fault diagnosis Blind source separation Wavelet Denoising Independent component analysis |
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