The application of GA-VMD denoising algorithm in [phi]-OTDR system
Fan Yang, Dongming Li, Lijun Wan, Ji Ranran, Xiaodi Wu · 2022
In the practical application of φ-OTDR system, the accuracy of the system is affected by the existence of environmental noise and so on. In order to effectively reduce the noise composition of the measured signal and better obtain the signal characteristics, this paper proposes a noise reduction method GA-VMD which combines genetic algorithm (GA) and variational mode decomposition (VMD). The method firstly optimizes the decomposition layer number (K) and penalty factor (α) of VMD by GA, and then performs multiscale permutation entropy (MPE) randomness detection of the intrinsic mode function (IMF) obtained by decomposition, so as to achieve the purpose of noise reduction. Through the processing of the measured signal, it is shown that the GA-VMD method is better than the empirical mode decomposition (EMD) and the Complementary Ensemble Empirical Mode Decomposition (CEEMD) method in terms of signal-to-noise ratio and cross-correlation coefficient. It shows that the GA-VMD algorithm is better than the EMD and CEEMDAN algorithms, which verifies the effectiveness of the method.