| 基于小波包和径向基神经网络轴承故障诊断 |
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| 引用本文： | 王国锋,王子良,秦旭达,王太勇.基于小波包和径向基神经网络轴承故障诊断[J].北京科技大学学报,2004,26(2):184-187. |
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| 作者姓名： | 王国锋 王子良 秦旭达 王太勇 |
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| 作者单位： | 1. 天津大学机械工程学院,天津,300072
2. 天津理工学院,天津,300191 |
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| 基金项目： | 国家自然科学基金
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国家重点实验室基金 |
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| 摘 要： | 针对滚动轴承故障精密诊断的需要,采用小波包分析方法提取了滚动轴承故障的特征信号.通过小波包分析将高频信号分解到8个频带中,以频带能量作为识别故障的特征向量.应用RBF径向基神经网络建立了从特征向量到故障模式之间的映射.现场采集的数据分析表明,采用小波包和神经网络相结合的方法可以比较准确地识别滚动轴承的故障.
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| 关 键 词： | 小波包 径向基神经网络 滚动轴承 精密诊断 小波包分析 径向基神经网络 轴承故障诊断 RBF Neural Networks Wavelet Packet Based Bearing Rolling Diagnosis 滚动轴承故障 比较 结合 分析表 数据 现场采集 映射 故障模式 应用 特征向量 识别 |
| 修稿时间： | 2002年11月20日 |
Accurate Diagnosis of Rolling Bearing Based on Wavelet Packet and RBF Neural Networks |
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| WANG Guofeng,WANG Ziliang,QIN Xuda,WANG Taiyong
Mechanical Engineering School,Tianjin University,Tianjin ,China Tianjin University of Technology,Tianjin ,China.Accurate Diagnosis of Rolling Bearing Based on Wavelet Packet and RBF Neural Networks[J].Journal of University of Science and Technology Beijing,2004,26(2):184-187. |
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| Authors: | WANG Guofeng WANG Ziliang QIN Xuda WANG Taiyong
Mechanical Engineering School Tianjin University Tianjin China Tianjin University of Technology Tianjin China |
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| Institution: | WANG Guofeng,WANG Ziliang,QIN Xuda,WANG Taiyong
Mechanical Engineering School,Tianjin University,Tianjin 300072,China Tianjin University of Technology,Tianjin 300191,China |
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| Abstract: | The accurate diagnosis of rolling bearing was studied. The wavelet packet analysis was used to abstract the characteristic of signals. The signals were decomposed into eight frequency bands and the information in the high band was used as a characteristic vector. RBF neural networks were used to realize the map between the feature and diagnosis. The analysis of data sampled form a workshop testified correctness of the method proposed. |
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| Keywords: | wavelet packet RBF neural network rolling bearing diagnosis |
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