Application of Correlation and Coherence Functions in Diagnostic Systems

Abstract

Main problem in operation of diagnostic systems of power transmission systems is analysis of the energy of these harmonic components of the signal, which could be considered as diagnostic symptoms. Measured values can be affected i.a. by energy of random effects or other, less important components of the signal. Coherence and correlation functions are ones of classical methods of signal analysis being applied to analyze deterministic signals affected by random noise. In time domain autocorrelation function allows to determine time cohesion between adjacent fragments of analyzed process, shifted by different time values. In the paper author describes the method of minimization the impact of disturbances on signals being analyzed using basic properties of autocorrelation function. For the analysis of deterministic phenomena (including nonlinear) ordinary coherence function was applied. Showed examples were implemented and solved in MATLAB environment. The method was verified by analysis of model signals and signals (vibration accelerations) recorded on real object.