基于第二代小波变换的旋转机械振动信号去噪

旋转机械故障振动信号存在不同形式的波形特征,传统小波去噪中,小波分解的结果与所采用的小波基函数有关,选用不适当的小波基函数会冲淡振动信号的局部特征信息,而造成原始信号的部分有用的细节信息丢失。为了克服上述缺陷,提出一种基于第二代小波变换的振动信号预处理方法,即针对分析信号的局部特征,以预测方差最小为目标,对每个样本选择最佳的预测算子,使小波基函数始终能够匹配信号的局部特征。仿真试验表明,该方法克服了传统小波去噪中降噪信号丢失了部分细节信息的缺点,不仅可有效去除振动信号的噪声,而且能够为保留信号的局部信息。

Denoising Method and Fault Diagnosis of Rotating Machinery Vibrating Signal Based on Second Generation Wavelet Transform

There is different characteristics of signal in the fault vibrating signal of rotating machiner- y.In the denoising of traditional wavelet tansform,the result of wavelet decomposing is related with wave- let basis function.And the adopted wavelet which is ill-suihed for original signal can delute the local char- acteristic of vibrating signal ,and lost some useful detail information of original signal.In order to over- come mentioned limitation,a pre-processing method based on second generation wavelet transform for vi- brating signal is adopted.According to the local characteristics of signal and the selection criterion of minimizing the squared error ,an optimal predicting operator is selected for a transforming sample so that the used wavelet basis function can always fit the local characteristics of the signal.The simulation showed that the proposed method could overcome the denoising disadvantage of traditional wavelet transform.It not only can filter noise from original signal effectively,but also can hold local characteristics of original signal in the denoised signals.