Abstract：In order to eliminate the noise interference, a signal denoising algorithm is proposed based on singular value decomposition (SVD) and minimum description length (MDL). The measured data are used to construct Hankel matrix and perform singular value decomposition. The signal is decomposed into a linear superposition of useful components and useless components. The MDL is used to determine the boundary between signal and noise, and the useful components are extracted to reconstruct the signal. The results of simulation and measured data show that MDL can effectively distinguish the useful component from the noise, the trend of denoising data is complete, and the noise is effectively removed. Compared with the results of wavelet hard and soft threshold denoising, the signal to noise ratio (SNR) can be increased by 12.61dB, and the root mean square error (RMSE) can be reduced by 47%.
汪倩文, 饶红疆, 何益宏. 结合奇异值分解与最小描述长度准则的变压器极化电流数据去噪方法[J]. 电气技术, 2021, 22(8): 39-44.
WANG Qianwen, RAO Hongjiang, HE Yihong. Denoising method of transformer polarization current data based on singular value decomposition and minimum description length. Electrical Engineering, 2021, 22(8): 39-44.
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2021, Vol. 22 
