基于小波去噪法的基坑监测数据处理

受各种因素影响,地铁基坑监测数据除含有真实变形信息外,还存在噪声。应用MATLAB实现小波分析对监测数据的去噪处理和粗差探测仿真实验。实例表明,选取恰当的小波基函数和小波分解层数,通过小波分析的带通滤波的功能,能够对原始信号有效分频,从而在不同尺度上将粗差和噪声分离达到识别的效果。去噪之后的信号曲线有较好的光滑性,更能反映基坑周边土体的变形规律。

The Processing of Foundation Pit Monitoring Date Based on Wavelet De-noising Method

Affected by various factors,the monitoring data of subway foundation pit also has noises except the real deformation information.It is introduced application of the wavelet analysis of MATLAB to deal with the noise and make the gross error detection simulation experiment on the monitoring data.The instance shows that,to select the appropriate wavelet basis function and wavelet decomposition layers can make effective frequency division to the original signal through the wavelet analysis bandpass filter function,thus we can separate the gross error and noise in different scale to achieve the effect of recognition.The signal curve has good smoothness after de-noising,it can reflect the deformation law of soil around the foundation pit better.