Application of higher-order spectra for signal processing in electrical power engineering

During recent years higher order statistics (HOS) have found a wide applicability in many diverse fields, e.g.: biomedicine, seismic data processing, harmonic retrieval and adaptive filtering. In power spectrum estimation, the signal under consideration is processed in such a way, that the distribution of power among its frequency is estimated and phase relations between the frequency components are suppressed. Higher order statistics known as cumulants, and their associated Fourier transforms, known as polyspectra, reveal not only amplitude information about a signal, but also phase information. If a non-Gaussian signal is received along with additive Gaussian noise, a transformation to higher order cumulant domain eliminates the noise. These are some methods for estimation of signal components, based on HOS. In the paper we apply the MUSIC method (Multiple Signal Classification), both for the correlation and the 4th order cumulant, to investigate the state of asynchronous running of synchronous machines. When the investigated signal is distorted by a coloured noise the exact results can be achieved by applying cumulants