Analysis of acoustic signals in increments for functional diagnostics of multi-drive units

Abstract

The current trend in the development of mechatronic systems is the use of multi-drive frame configurations. Such objects, as a rule, consist of a large number of interacting elements. The relative displacements of these elements generate vibrations that can critically affect the operation of precision mechatronic systems. This can lead to limiting operating conditions of the equipment, and in some cases, its failure. An effective means of preventing accidents, identifying critical modes of operation, diagnosing faults in equipment of electromechanical systems are the methods of functional diagnostics.Methods of functional diagnostics in real time require a large number of calculations, mathematical modeling of the object, processing a large amount of information, which leads to the mandatory use of computer technology. The main methods of processing the measurement results are the Fourier and Laplace transforms, classical methods for analyzing time series, multiple-scale wavelet analysis, etc. The disadvantage of the approaches used is computational complexity in the implementation of discrete transformations and the need for significant amounts of memory to store reference values. The considered methods are based on the analysis of the original signal, however, the increments of the signal of different orders may also be informative.The aim of the research is to develop methods for analyzing acoustic signals generated by working equipment of electromechanical complexes, in increments suitable for use in functional diagnostics systems when monitoring the operating modes of electric drives.In the process of research, an analysis of acoustic noise signals from a working multi-drive unit, obtained as a result of a series of experiments at two high-speed modes, was performed. To speed up the process of analyzing signals and eliminate their redundancy, a data aggregation method has been applied. The degree of permissible aggregation is determined using a multi-scale analysis. The developed method for analyzing aggregated acoustic signals in increments in phase space can be used for functional diagnostics of multi-drive units.