Development of an Approach to Preprocessing of Black-and-White Images for Electrical Equipment Diagnostics

Diagnostics of electrical equipment (EE) involves a variety of interrelated parameters which are analyzed using different types of diagnostics. For the most accurate assessment of the influence of parameters on EE performance and the influence on each other, it is necessary to analyze a large amount of data. But, despite the large amount of statistical data for EE diagnostics, the most illustrative type is still the graphical representation of the dependence of parameter changes in time or the dependence of parameters on each other. The scientific novelty of this approach is to develop an algorithm for preprocessing of black-and-white images with the complex use of the following methods: spline interpolation, component-by-component subtraction and adaptive binarization under conditions of heterogeneous data. Using methods in combination provides improving the informativeness in decision-making situations, as well as the knowledge completeness and reliability of conclusions regarding EE technical condition. The approach proposed for processing of black-and-white images is needed to determine the deviations in the EE operation and prevent its premature failure.