Dynamic Deformation Signal Extracting Model Based on a Dyadic Wavelet Transform
Jian Wang, Jingxiang Gao, Cao De-xin, Jiuyun Sun · Journal of China University of Mining and Technology · 2007
The dyadic wavelet transform theory was introduced to study dynamic deformation analysis model in this paper. The technique process for signal extraction and gross error recognition and recovery of dynamic deformation was put forward,B_3-spline wavelet function was chosed for experimental analysis to denoise the dynamic deformation signal using fast dyadic wavelet decomposition based on a trous algorithm.Soft-threshold noise reduction algorithm was applied to separate deformation trend taking triple-mean square error as the threshold of detail signals and gross error was recognized at detail scales,then the actural deformation signal is obtained after gross error recovery.The results show that the proposed model can efficiently extract deformation signal which is better than that using median filter.The isolated,dispersed and regional gross errors are discerned at the second detail scale of dyadic wavelet decomposition at one time and the positioning precision is better than that using Mallat algorithm,especially for the boundary of regional gross error,which can be explained by the shift-invariant of dyadic wavelet transform.