运用小波函数对曲轴冲击响应中不同特征信号的提取

Study on Extraction of Feature Signal from Crankshaft Shock Response Signal Using Wavelet Analysis

采用小波分解消噪重构的方法实质上是采用了一个具有多个通道的带通滤波器,每一层分解相当于改变其通频带,获得不同频率的信号输出。与采用有限时间低通数字滤波器相比,采用小波变换更为突出的是可以从小波分解过程看到信号不同频率分量的变化趋势与特征,即可以看到冲击响应信号的变化特征。针对设计的曲轴轴承冲击试验装置进行了冲击试验,采集得到的原始位移信号中包含曲轴转子的位移,以及各种干扰的噪声。为了有效区分信号中曲轴转子的位移信号、冲击位移信号和干扰的噪声,利用信息信号和噪声信号在小波变换下具有截然不同的奇异性,对测量得到的位移测量数据进行小波不同层次的分解并进行小波去噪和重构,得到了所需要的各种信号。

The multi resolution method of signal decomposing,denoising and reconstructing with wavelet analysis essentially is using a multi-scale band-pass filter to changes its coherent frequency band and get different frequency signal output.Compared with limited time digital low-pass filter,the feature and the change tendency of different frequency component of the signals could be seen in the decomposition process with wavelet analysis.A shock test to the designed crankshaft bearing was carried on in this paper,the original displacement signals obtained contained either the displacement signals of crankshaft rotor,or various noise signals.For the sake of distinguishing displacement signals,shock displacement signals of crankshaft rotor and the noise signals effectively,using the completely different oddity of wavelet transform for information signal and noise signal,the useful feature signals can be gotten from the measured displacement data of the crankshaft rotor by the method of wavelet decomposing,deoising and reconstructing of signals.