城市深基坑沉降监测数据处理应用研究

Application Research on Data Processing of Urban Deep Foundation Pit Settlement Monitoring

文章针对城市深基坑监测高精度监测数据存在误差难以剔除问题,选择三种常见的数据处理方法,对比分析各方法的特点,择优选择更适合深基坑沉降监测数据处理的方法。研究结果表明,线性回归分析只能获得沉降监测数据的变化趋势,无法保留监测数据的更多细节,而FFT变换和小波滤波在处理深基坑沉降监测数据时都表现出了优势,但通过残差和误差率对比分析,小波滤波是更适合深基坑沉降监测数据的处理方法。

This paper focuses on the problem of errors in urban deep foundation pit monitoring data that are difficult to eliminate.Three common data processing methods are selected,and the characteristics of each method is compared and analyzed to select the most suitable method for deep foundation pit settlement monitoring data processing.The results indicate that linear regression analysis can only obtain the trend of settlement monitoring data and cannot retain more details of the monitoring data.FFT transform and wavelet filtering have shown advantages in processing deep foundation pit settlement monitoring data.However,through residual and error ratio analysis,wavelet filtering is a more suitable processing method for deep foundation pit settlement monitoring data.