Harmonic Detection Algorithm for Traction Power Supply System Based on ICEEMDAN and Teager Energy Operator - XIE Zeen (Kongzhi Yu Xinxi Jishu)
In view that the conventional harmonic detection algorithms cannot support analysis on nonlinear and non-stationary harmonics in the traction power supply systems, this paper proposes a harmonic detection algorithm based on the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and Teager energy operator (TEO). The first step is to process the signal to be detected into a set of intrinsic mode function (IMF) components through ICEEMDAN, and then obtain the true IMF components by filtering out the false ones. Then, performing TEO demodulation on each IMF component can generate the variation charts of amplitude and frequency of harmonic components over time. It is revealed through analysis that ICEEMDAN, as an improved algorithm for empirical mode decomposition (EMD), an important step in the Hilbert-Huang transform (HHT), has the best effect in suppressing mode aliasing, compared with other improved algorithms of EMD. Thanks to its good adaptability, it also has good performance in processing nonlinear and non-stationary signals. On the other hand, TEO can accurately detect the instantaneous amplitude and frequency of harmonics, and quickly respond to signal changes. The proposed algorithm was simulated and analyzed by constructing harmonic signals of the traction network characteristics. The results show that the average detection errors of amplitude and frequency were 3.56% and 1.74% respectively when analyzing steady-state current harmonics, and 3.39% and 2.44% respectively when analyzing transient current harmonics. This indicates that the algorithm proposed in this paper can accurately detect the amplitude and frequency of harmonics in the traction power supply systems, and can accurately locate harmonic signal singularity.