Authors: P.B. Guericke

Title of the article: Adaptive predictive modeling of the degradation of the technical condition of rotating equipment mining shovels, based on the analysis of vibration parameters

Year: 2015, Issue: 6, Pages: 70-77

Branch of knowledge: Mining machines

Index UDK: 53.083(430.1)

DOI: -

Abstract: This paper analyzes the experience of the development of mathematical models to predict changes in the technical condition of complex mechanical systems. Is a detailed classification of defects dynamic equipment mining shovels on which justified the use of specific methods of vibration analysis most suitable for effective control and the development of common diagnostic criteria for changes in the technical condition of the objects of diagnosis. As part of this work the necessity for a comprehensive diagnostic approach to assess the technical condition of the mechanisms in the parameters of the generated vibrations. It is shown that only with the extensive use of modern methods of vibration analysis and nondestructive testing are given the opportunity for early detection of defects dynamic units mining shovels and develop predictive models change their technical condition. Research results prove categorically the possibility of establishing of adequate models of changes in the state suitable for the implementation of short term forecasting, the development of which is a necessary base for high-quality transition repair and maintenance departments of industrial enterprises in the service system technology on its actual technical condition. The platform for the implementation of elements of the concept of this system will be developed complex of diagnostic rules detecting defects on the analysis of parameters of mechanical vibrations, and created adaptive predictive models of defects, suitable to describe the degradation of the status of a wide number of typical units used in the construction of mining equipment.

Key words: vibration analysis predictive modeling valuation of mechanical vibrations maintenance management mining shovels

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