| 改进奇异值分解技术在齿轮故障信号降噪中的应用 |
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| 引用本文： | 陈恩利,周桃,王翠艳.改进奇异值分解技术在齿轮故障信号降噪中的应用[J].石家庄铁道学院学报(社会科学版),2009(1):20-24. |
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| 作者姓名： | 陈恩利 周桃 王翠艳 |
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| 作者单位： | 陈恩利,周桃,Chen Enli,Zhou Tao(石家庄铁道学院,机械工程分院,河北,石家庄,050043);王翠艳,Wang Cuiyan(石家庄铁道学院,工程训练中心,河北,石家庄,050043)
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| 摘 要： | 改进了奇异值分解技术,利用仿真信号验证了改进的奇异值分解技术对齿轮故障信号提取的有效性,并从实测齿轮裂纹信号和齿轮断齿信号中提取出了故障特征信号.研究表明该方法能在强噪声背景下提取出齿轮故障信号,但强噪声对提取效果有一定影响.
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| 关 键 词： | 齿轮故障信号 噪声 奇异值分解 |
| 收稿时间： | 2008/9/5 0:00:00 |
Application of Improved Singular Value Decomposition Method in Gear Faults Signal De-noising |
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| Authors: | Chen Enli Zhou Tao Wang Cuiyan |
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| Institution: | School of Mechanical Engineering, Shijiazhuang Railway Institute;School of Mechanical Engineering, Shijiazhuang Railway Institute;Engineering Training Center, Shijiazhuang Railway Institute |
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| Abstract: | This paper improves the singular value decomposition technology, using simulation signal to verify its validity in extracting the gear fault signal, and extracting the faults characteristic signal from the crack signals and broken tooth signals. The research indicates that the method can extract gear faults signal from strong noise, but the strong noise will effect the extraction. |
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| Keywords: | gear faults signal noise singularity value decomposition |
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