Using Wavelet Hybrid Self-Organizing Feature Map Network for V-I Based Multiple Harmonic Sources Classification

摘要

This paper proposes a method using non-linear voltage-current characteristics for multiple harmonic sources classification using wavelet hybrid neural network (WHNN). Typical voltage-current characteristics of harmonic sources are non-linear closed curves in the time-domain, referring to the converters, reactors, and non-linear loads. The hybrid neural network is a two-subnetwork architecture, consisting of wavelet layer and a self-organizing feature map (SOFM) network connected in cascade. The effectiveness of the proposed method is demonstrated by numerical tests. The results of multiple harmonic sources show the computational efficiency and accurate classification.