Abstract:
In order to reduce the influence of noise on the output signal of FOG, a de-noising algorithm of FOG based on modified ensemble empirical mode decomposition (MEEMD) and forward linear prediction (FLP) is proposed. Firstly, the concept of permutation entropy is introduced, and the FOG signal is decomposed and reconstructed by using MEEMD. Secondly, the low-order IMF terms of the mixed noise after decomposition is filtered and de-noised by the FLP algorithm. Finally, the signal processed by the MEEMD-FLP is reconstructed to get the result. The static test of a FOG is carried out. The experimental results show that compared with the original FOG signal, the RMSE after de-noising is reduced by 76.77%, and the standard deviation is reduced by 76.76%. It can effectively reduce the influence of noise on the FOG output signal and has higher de-noising accuracy.
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Abstract: In order to reduce the influence of noise on the output signal of FOG, a de-noising algorithm of FOG based on modified ensemble empirical mode decomposition (MEEMD) and forward linear prediction (FLP) is proposed. Firstly, the concept of permutation entropy is introduced, and the FOG signal is decomposed and reconstructed by using MEEMD. Secondly, the low-order IMF terms of the mixed noise after decomposition is filtered and de-noised by the FLP algorithm. Finally, the signal processed by the MEEMD-FLP is reconstructed to get the result. The static test of a FOG is carried out. The experimental results show that compared with the original FOG signal, the RMSE after de-noising is reduced by 76.77%, and the standard deviation is reduced by 76.76%. It can effectively reduce the influence of noise on the FOG output signal and has higher de-noising accuracy.
