Noise reduction analysis of high slope deformation data based on the EMD-SG model

The accuracy of high slope deformation data is crucial for slope stability assessment and disaster warning. However, a large amount of noise often exists in the actual monitoring data, which affects the quality of the data and the reliability of the analysis results. In view of this, this paper proposes a noise cancellation method for high slope deformation data based on empirical modal decomposition and SG filtering. Firstly, the original deformation data are decomposed into a number of intrinsic modal functions (IMFs) using EMD, then the decomposed IMF components are processed by SG filtering respectively, and finally the filtered IMF components are reconstructed to obtain the deformation data after noise cancellation. The effectiveness and superiority of the method is verified by processing and analyzing the deformation data of actual high slopes.