Sine fitting multiharmonic algorithms implemented by artificial neural networks

Abstract

A new method for spectral analysis, based on ADALINE artificial neural networks (ANNs), is proposed. The network is able to calculate accurately the fundamental frequency and the harmonic content of the input signal. This method is especially useful in high precision digital measurement systems in which periodical signals are involved, i.e. digital watt meters. Most of these system use spectrum analysis algorithms for the computation of the magnitudes of interest. The traditional spectrum analysis methods require synchronous sampling, which introduce limitations to the sampling circuitry. Sine-fitting multiharmonics algorithms resolve the hardware limitations concerning the synchronous sampling but have some limitations with regard to the phase of the array of samples. The new implementation of sine-fitting multiharmonics algorithms based in ANN, eliminates these limitations. © Springer-Verlag Berlin Heidelberg 2007.