Information Support for Identification of the Technical State of Electric Power Facilities

This chapter deals with the actual scientific and applied task of identifying the state of operating electric power objects, which have worked out more than 80% of their regulatory resource to date. Proposed information support for such identification based on the use of the information resource of the noise signal, which is formed during the operation of the object. The noise signal, which is a stochastic spatial noise field, most integrally reflects the state of the electric power object. For practical use, information support for identification is proposed, a mathematical model of the noise signal is substantiated in the form of a linear stationary random process as a put in component of the studied noise field. Such a model describes the physical process of the noise signal of an object and is a color stochastic noise obtained by converting the current stationary white noise by a linear filter. Color noise is characterized by infinitely separated distribution laws, including Gaussian and Poisson laws. It is proposed to use the density of the noise signal distribution law as characteristics of the object state identification, the statistical evaluation of which is carried out to process the realizations of a linear stationary process with using a system of Pearson curves. Algorithmic software for statistical estimation of empirical noise signal densities of the system of Pearson curves for practical use has been developed.