结合CEEMDAN的改进小波阈值地下水温观测数据去噪方法

Research on Denoising Method of Groundwater Temperature Observation Data Using the Improved Wavelet Threshold Denoising Combined with CEEMDAN

提出一种结合自适应噪声完备集合经验模态分解方法(CEEMDAN)的改进小波阈值降噪算法,用于地下水温观测数据的去噪。在利用该方法与传统的去噪方法分别对仿真信号进行降噪后发现,该去噪方法性能更优,并且在对实际采集到的含有噪声及异常突变的地下水温数据进行处理方面,也展现出比传统单一滤波手段更好的效果。

We propose an improved wavelet threshold de-noising algorithm combined with adaptive noise complete set empirical mode decomposition(CEEMDAN)for the de-noising of groundwater temperature observation data.After using this method and the traditional denoising method to denoise the simulation signal respectively,we find that the proposed denoising method has better performance,and shows better effects than the traditional single filtering method in processing the actually collected groundwater temperature data containing noise and abnormal mutation.