| 基于区间的小波包振动信号特征提取方法研究 |
| |
| 引用本文： | 黄强,刘永长,叶晓明.基于区间的小波包振动信号特征提取方法研究[J].车用发动机,2003(4):49-51. |
| |
| 作者姓名： | 黄强 刘永长 叶晓明 |
| |
| 作者单位： | 华中科技大学,湖北,武汉,430074 |
| |
| 摘 要： | 基于小波分析与神经网络的振动信号故障诊断方法,提出采用基于区间小波包分解方法来提取振动信号的特征向量来取代传统的小波包分解方法,并以295柴油机进排气系统故障诊断为例验证采用该方法的有效性,结果表明,基于区间的小波包特征提取方法较传统方法能大大提高进排气系统的故障识别率。
|
| 关 键 词： | 柴油机 小波包 神经网络 特征提取 |
| 文章编号： | 1001-2222(2003)04-0049-03 |
| 修稿时间： | 2002年12月23日 |
Wavelet Packet Method Based on Sections of Picking-up Characteristic from Vibration Signals |
| |
| HUANG Qiang,LIU Yong-chang,YE Xiao-ming.Wavelet Packet Method Based on Sections of Picking-up Characteristic from Vibration Signals[J].Vehicle Engine,2003(4):49-51. |
| |
| Authors: | HUANG Qiang LIU Yong-chang YE Xiao-ming |
| |
| Abstract: | In the fault diagnosis based on Wavelet Analysis and Neural Networks, the wavelet packet method based on sections is used to replace the traditional one to pick-up characteristics of vibration signals.Then the efficiency of this method is validated on the inlet and exhaust systems fault diagnosis of 295 Diesel Engine.The result shows that wavelet packet method based on sections of picking-up characteristic can improve the veracity of fault diagnosis. |
| |
| Keywords: | diesel engine wavelet packet neural networks picking-up characteristic |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
