基于奇异值和奇异向量的振动信号降噪方法

针对复杂的转子振动信号中同时存在随机噪声干扰和工频噪声干扰的问题,提出了基于奇异值和奇异向量相结合的降噪方法。首先,对振动信号进行奇异值分解(singular value decomposition,简称SVD),根据奇异值谱确定振动信号有效奇异值阶次;其次,对有效阶次范围内的奇异向量进行快速傅里叶变换(fast Fourier transform,简称FFT),依据幅值谱筛选出对应于工频噪声的奇异向量;最后,利用其余的奇异值和奇异向量进行重构得到降噪的时域信号。通过仿真信号和工程试验信号对该方法进行了验证,结果表明,基于奇异值和奇异向量相结合的降噪方法,不但能有效降低振动信号中的随机噪声干扰,还能有效降低工频噪声干扰,同常用的陷波器方法相比所提出方法具有明显优势。

Noise Reduction Method of Vibration Signal Based on Singular Value and Singular Vector

In the light of coexistence of random noise and power interference noise in rotor vibration signals, the noise reduction method based on the combination of singular value and singular vector is proposed. First, the signals processed with signal value decomposition (SVD) method, the effective order of singular value can be obtained from singular value spectrum, in this way the random noise can be reduced. From the relationship between singular value and singular vector we can get the corresponding singular vectors. Then, these singular vectors are calculated with fast Fourier transformation (FFT). The singular vectors corresponding to the power interference are filtered based on the FFT amplitude spectrum feature. Finally, the time-domain signal with all the other singular values and singular vector are reconstructed to reduce the random noise and power interference noise in the target signals. Simulation experimental results demonstrate that the proposed method can effectively reduce the random noise and power interference noise, which is obviously superior to the notch filter method.