TO THE QUESTION OF A UNIVERSAL PROGNOSTIC DEGRADATION MODEL CREATIONFOR MINING MACHINE ENERGY-MECHANICAL EQUIPMENTY

This article summarizes the research results of a universal mathematical degradation model development suitable for predicting the process of parameter changing characterizing the technical state of different mechanical systems. In this work the analysis results of the existing methodological approaches to the development of common diagnostic criteria based on the principles of vibration diagnostics of extremely worn-out energy-mechanical equipment are considered. A detailed classification of defects in energy-mechanical equipment of mining machines, including quarry excavators, drilling rigs, mining transportation and coal-washing equipment is given. The application of specific vibration analysis methods, most suitable for effective control and development of unified diagnostic criteria for assessing the technical condition of diagnostic objects, is substantiated as part of a comprehensive diagnostic approach. It is shown that only with the wide use of modern methods of vibration diagnostics and nondestructive testing the opportunity is offered for timely detection of defects in dynamic aggregates of mining equipment and for development of predictive models for their technical condition change. The results of the conducted studies prove the possibility of universal prognostic models development suitable for performing an effective short-term prediction of technical state changes as basic simulated parameters which use single diagnostic criteria created for assessing the actual state of the diagnostic objects. The introduction of predictive modeling algorithms into practice of vibroanalysis is one of the necessary conditions for the transfer of Kuzbass fuel and energy complex industrial enterprises to the maintenance system according to it's actual technical condition. An integral basic element of the concept of such a system will be the developed set of diagnostic rules for detecting defects based on the analysis of vibration generated at the equipment operation, including more than 120 diagnostic features for major seven groups of defects.