小波阈值去噪法在非稳定信号处理中的应用

高大建筑物和工业设施等的变形监测数据一般都是含噪的信号,需要对其进行降噪处理,获取其准确的变形信息,以便掌握真实的变形情况。由于监测数据都是非稳定的信号,通常采用小波阈值降噪法对其处理,但传统的软硬阈值进行降噪的效果不佳,需对其进行改进。文中采用3种改进的小波阈值降噪法与传统的方法进行比较,通过对信噪比和均方差的分析,获得适合于变形监测数据的非稳定信号的降噪方法。

Application of wavelet denoising method in non-stable signal

Tall buildings and industrial facilities such as deformation monitoring data are generally noisy signals which need denoising, and accurate information in order to grasp the real deformation. For monitoring data are non-stable signals, usually the wavelet threshold denoising method is applied, but the traditional soft and hard thresholds prove an ineffective denoising. Three improved wavelet threshold denoising methods are compared with traditional methods as in the analysis of variance and mean SNR in order to obtain a deformation monitoring data denoising method for non-stationary signals.