小波分析在大坝安全监测数据噪声处理中的应用

The Application of Wavelets Analysis on Data Denoising of Dam Safety Monitoring

大坝安全监测数据可以视为通常意义下的时序信号,通过对其进行小波变换分析可有效地进行信噪分离。小波去噪的基本方法有模极大值去噪、基于各尺度下小波系数相关性进行去噪、阈值去噪、平移不变量小波去噪等方法,本文研究了基于Matlab中小波去噪具体算法并写出了计算程序。实例分析表明,小波分析去噪能够有效地识别监测数据的噪声,具有操作简单、不失真等优点。

The dam monitoring datas can be treated as a time series in a common sense, through wavelets analysis the datas can effectively separate signal and noise. The basic methods of wavelets analysis denoising have modulus maxima denoise, the denoising based on the correlation of different scale wavelet coefficient, threshold denoising and translation constant wavelets denoising. This paper researched specific algorithm of wavelet denoising and wrote a computer program based on the Matlab software. Examples show that the wavelets analysis denoising can effectively recognise noise of monitoring data, which have advantage of simple operation and undistortion.