摘要
软阈值小波降噪是一种常用的非平稳信号特征提取方法。为了改进软阈值小波降噪法的性能,提出一种基于软阈值和二进小波变换模极大值的新小波降噪方法。首先,对信号进行二进小波变换,再对小波系数进行软阈值处理;然后,选择由信号产生的小波系数模极大值点;最后,用交替投影算法重建信号。理论分析表明,该方法能有效地降低软阈值小波降噪法的误差下界。仿真试验表明,该方法提高了降噪结果的信噪比,且较好地保留了信号中的奇异性。将该方法和二进小波变换软阈值降噪法结合起来,应用于滚动轴承故障振动信号降噪。结果表明,该方法能有效地提取到信号中的冲击特征。
Wavelet denoising based on soft thresholding is a commonly used approach for feature extraction of nonstationary signals.A new wavelet denoising method based on soft thresholding and the dyadic wavelet transform modulus maxima is proposed in order to improve the performance of the wavelet denoising method based on soft thresholding.Firstly,the proposed method performs the dyadic wavelet transform on the signal,and the wavelet coefficients are processed by soft thresholding.Then,the modulus maxima of wavelet coefficients are selected.Finally,the denoised signal is reconstructed by the alternating projection algorithm.Theoretical analysis shows that the proposed method can effectively reduce the lower bound of denoising error of the wavelet denoising method based on soft thresholding.Experiments prove that the new method improve signal-tonoise ratios of the denoised results and well reserve the singularities of the original signal.Both the proposed method and the soft thresholding denoising method based on the dyadic wavelet transform are used to denoise the vibration signal of a roller bearing.Results show that the proposed method more effectively extracts the impulse feature of the signal.
出处
《振动．测试与诊断》
EI
CSCD
北大核心
2011年第5期543-547,共5页
Journal of Vibration,Measurement & Diagnosis
基金
中央高校基本科研业务费专项基金资助项目(编号:LDJZR10280007)
关键词
二进小波变换
软阈值模极大值
降噪误差下界
奇异性
dyadic wavelet transform soft thresholding modulus maxima lower bound of denoising error singularity
