关键词: 小波分析, 去噪, 数据处理, 阈值, 重构层数

Abstract: There inevitably exists noise in observation data obtained in deformation monitoring. How to extract diagnostic information from noise data sequence and improve deformation monitoring precision is the critical technology among the deformation monitoring system. This paper applies the wavelet theory method to study the denoise effect with the monitoring data, which mainly focuses on studies of the influence of the denoise method (algorism), wavelet base function and threshold value. The data processed by hard threshold value is rougher than that by soft threshold value. And the soft threshold value has a better effect. The threshold value and wavelet base function have an important influence. It achieves a good effect by forced denoise, and the select of reconstruction scale also has an important influence on filtering.

Key words: Wavelet analysis, Denoise, Data processing, Threshold value, Reconstruction scale