欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
提出了一种改进的经验模态分解（Empirical Mode Decomposition,EMD）的故障诊断方法。即将小波包降噪、相关系数原理及选择不同消失矩的db系小波降噪与EMD分解结合在一起的改进方法,其步骤是对故障信号先进行小波包降噪预处理;再进行EMD得到一系列IMF;计算各个IMF与原始信号的相关系数得到需要重复降噪的有效集;根据有效集中IMF的突变性强弱来选择不同消失矩的db系小波进行重复降噪;重构信号并且生成功率谱。实验结果表明,该方法很好地去除了混杂在故障信号中的噪声,提高了信噪比,可以很好地区分出齿轮箱的齿轮和轴承是正常状态还是发生了断齿故障。
英文摘要：
An improved empirical mode decomposition（ EMD） method of fault diagnosis is presented,Which combined with the wavelet packet denoising,the correlation coefficient principle,the wavelet denoising with selecting different db vanishing moments and the EMD decomposition. The first,the fault signal is pretreated by wavelet packet denoising; then the fault signal is processed by the EMD decomposition to get a series of IMF,by calculating the correlation coefficient of each IMP with the original signal,the effective sets which need to repeat denoising are obtained. According to the mutation strength of the effective concentration IMF by selecting db wavelet with different vanishing moments,the noise reduction is repeated; Finally the signal is reconstructed and the power spectrum is generated. The experimental results show that this method can remove the noise which mixed in the fault signal,improve the signal to noise ratio,tell the faults of the gear and the bearing from the normal condition.
同期刊论文项目
同项目期刊论文
Failure mode effect and criticality analysis of the underground mining environment detector test sys
期刊信息
位置：