| 小波包神经网络在齿轮泵故障诊断中的应用 |
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| 引用本文： | 陈中华,江四厚,王汉功,阳能军. 小波包神经网络在齿轮泵故障诊断中的应用[J]. 机床与液压, 2007, 35(11): 188-190 |
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| 作者姓名： | 陈中华 江四厚 王汉功 阳能军 |
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| 作者单位： | 第二炮兵工程学院,陕西西安,710025;第二炮兵工程学院,陕西西安,710025;第二炮兵工程学院,陕西西安,710025;第二炮兵工程学院,陕西西安,710025 |
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| 摘 要： | 采用小波包技术提取齿轮泵的振动信号的小波包能量谱及其谱熵,作为改进的BP网络的输入特征,进行齿轮泵的故障诊断.实验结果表明,该方法大大地提高了诊断的可靠性.
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| 关 键 词： | 改进BP网络 小波包能量谱 谱熵 故障诊断 |
| 文章编号： | 1001-3881（2007）11-188-3 |
| 修稿时间： | 2006-11-14 |
Application of Wavelet Package and Neural Network in Fault Diagnosis of Gear Pumps |
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| CHEN Zhonghua,JIANG Sihou,WANG Hangong,YANG Nengjun. Application of Wavelet Package and Neural Network in Fault Diagnosis of Gear Pumps[J]. Machine Tool & Hydraulics, 2007, 35(11): 188-190 |
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| Authors: | CHEN Zhonghua JIANG Sihou WANG Hangong YANG Nengjun |
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| Abstract: | Wavelet package energy spectrum and its spectrum entropy of vibration signal of gear pump were extracted by using wavelet package algorithm, making those as the input character of the improved BP neural network, the fault diagnosis of gear pump was implemented. Experimentation shows that this method can improve the reliability of the fault diagnosis system. |
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| Keywords: | Improved BP network Wavelet package energy spectrum Spectrum entropy Fault diagnosis |
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