论文部分内容阅读
提出小波去噪和EMD相结合的齿轮箱故障诊断的新方法。该方法首先对原始信号进行小波阈值去噪,将去噪信号利用EMD方法分解为多个IMF分量,计算各IMF分量和原信号的互相关系数,选择互相关系数较大的IMF分量进行Hilbert包络谱分析,提取故障频率。以互相关准则提取IMF分量避免了IMF分量选择的盲目性。对实测齿轮箱故障信号进行了分析,结果表明该方法能够有效地识别齿轮箱故障频率。
A new method of gear box fault diagnosis combining wavelet denoising and EMD is proposed. Firstly, the original signal is denoised by wavelet threshold, and the denoised signal is decomposed into multiple IMFs by EMD method. The cross-correlation coefficient of each IMF component and original signal is calculated. The IMF component with large cross-correlation coefficient is selected for Hilbert packet Spectrum analysis, extraction of fault frequency. Extracting IMF components by cross-correlation criterion avoids the blindness of IMF component selection. The measured gearbox fault signal is analyzed, the results show that the method can effectively identify the gearbox fault frequency.