| 基于小波包分析的旋转机械故障诊断研究 |
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| 引用本文： | 石磊,王红军,吴国新.基于小波包分析的旋转机械故障诊断研究[J].北京机械工业学院学报,2010,25(3):43-47. |
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| 作者姓名： | 石磊 王红军 吴国新 |
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| 作者单位： | 北京信息科技大学机电工程学院,北京,100192;北京信息科技大学现代测控技术教育部重点实验室,北京,100192 |
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| 基金项目： | 北京市自然基金项目，"高档数控机床与基础制造装备"科技重大专项 |
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| 摘 要： | 故障信号的特征提取，是故障诊断的关键。通过以德比契斯（Daubechies）小波为基函数的二进小波变换、采用Mallat快速算法的小波包对故障信号进行特征提取。利用小波包对实验数据进行分析，其结果具有良好的时频局部化特性，能对非线性信号进行有效识别。
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| 关 键 词： | 旋转机械 故障诊断 小波包分析 特征提取 |
Research on fault diagnosis of rotating machinery based on wavelet packet analysis |
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| SHI Lei,WANG Hong-jun,WU Guo-xin.Research on fault diagnosis of rotating machinery based on wavelet packet analysis[J].Journal of Beijing Institute of Machinery,2010,25(3):43-47. |
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| Authors: | SHI Lei WANG Hong-jun WU Guo-xin |
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| Affiliation: | 1.School of Electromechanical Engineering, Beijing Information Science and Technology University, Beijing 100192, China 2. Key Laboratory of Modern Measurement ＆ Control Technology, Ministry of Education, Beijing Information Science and Technology University, Beijing 100192, China) |
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| Abstract: | Signal feature extraction is the key to fault diagnosis. In this paper, through dyadic wavelet transform which uses Daubechies wavelet as basic function,wavelet packet of Mallat fast algorithm is applied to extract characteristics of fault signal. Analyzing the experimental data with wavelet packet are analyzed. The result has good localization characteristics, and can identify non - stationary signal effectively. |
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| Keywords: | rotating machinery wavelet packet analysis fault diagnosis feature extration |
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