| 基于小波除噪与时-频指数分布的故障诊断新技术 |
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| 引用本文： | 王新晴,王耀华,熊云. 基于小波除噪与时-频指数分布的故障诊断新技术[J]. 解放军理工大学学报(自然科学版), 2001, 2(2): 59-61 |
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| 作者姓名： | 王新晴 王耀华 熊云 |
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| 作者单位： | 解放军理工大学工程兵工程学院 江苏南京210007(王新晴,王耀华),解放军理工大学工程兵工程学院 江苏南京210007(熊云) |
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| 摘 要： | 通过快速的小波任意尺度的分解,为具体分析与实现原始信号的信噪分离与干扰成分的剔除提供了有效手段,而改进的指数时－频分析技术能够同时实现时域与域的高分辨分析,有效地压缩交叉干扰项,从时域的相位时间特征与步域的尖谱特征的结合途径揭示了信号的构成本质,为故障诊断提供了强有力的工具。
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| 关 键 词： | 小波多尺度分析 指数分布 故障诊断 机械设备 时域 频域 信噪分离 |
| 文章编号： | 1009-3443(2001)02-0059-03 |
| 修稿时间： | 2000-07-19 |
New Technology for Fault Diagnosis Based onWavelet Denoisingand Exponential Time -Frequency Distribution |
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| WANG Xin-qing,WANG Yao-hua and XIONG Yun. New Technology for Fault Diagnosis Based onWavelet Denoisingand Exponential Time -Frequency Distribution[J]. Journal of PLA University of Science and Technology(Natural Science Edition), 2001, 2(2): 59-61 |
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| Authors: | WANG Xin-qing WANG Yao-hua XIONG Yun |
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| Affiliation: | Engineering Institute of Engineering Corps, PLA Univ. of Sci. & Tech., Nanjing 210007, China;Engineering Institute of Engineering Corps, PLA Univ. of Sci. & Tech., Nanjing 210007, China;Engineering Institute of Engineering Corps, PLA Univ. of Sci. & Tech., Nanjing 210007, China |
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| Abstract: | An effective tool is provided by fast wavelet multi-resolution analysis (wavelet MRA) for analyzing and canceling disturbing components in original signal. The modified exponential time-frequency distribution(MED) can suppress cross-terms and cancel noise further more. High resolution in both time and frequency domains is provided by MED, so the essential structure of a signal is revealed clearly according to the "time" behavior, together with "frequency" behavior in one figure. According to the analysis of algorithm and fault diagnosis example, the joint of wavelet MRA and MED is a powerful tool for fault diagnosis. |
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| Keywords: | wavelet multi-resolution analysis denoising exponential distribution fault diagnosis |
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