Kondratieva I. Optimization of control processes of technological equipment functional diagnostics

The dissertation is devoted to solving the problem of increasing the efficiency of control processes of technological equipment functional diagnostics in real time due to the development and practical implementation of methods for estimating the parameters of technical conditions and emergency operation of detecting electromechanical assemblies without dismantling the characteristics of vibrating processes which accompany their functioning. The effectiveness of acoustic diagnostic methods is due not only to the organic connection of information contained in the vibration signal with the dynamic processes of excitation and propagation of oscillations in the structure, but also the ability to automate the processes of recording and processing information using modern technology and diagnostic procedures based on mathematical apparatus theory of pattern recognition. The expediency of using as a signal model an autoregressive moving average model for the analysis of sound signals in which stationary properties are violated is substantiated. Based on the analysis of the data recorded by the measurement results, it is possible to identify the level of tension of the equipment and assess the complexity of the operational situation. The problem of building mathematical models on the basis of which it is possible to adequately identify the intensity of work and the state of the equipment is solved. The procedure for identifying the parameters of the signal model by the recurrent least squares method is given, which allows to analyze the state of the equipment in real time. The analysis of the statistical properties of acoustic signals revealed the normality of the law of distribution of the registered time series and the dependence of the numerical characteristics of the process on the operating modes and the degree of equipment load. By means of logic-time processing the informativeness of the signal in some frequency ranges is estimated. When determining the frequency ranges of informativeness by performing a series of calculations, the appropriate value of the frame length and the threshold setting parameter was found. The results of the application of multiple-scale analysis (calculation of variance, self-similarity parameter, Hirst parameter) depending on the degree of aggregation allowed to determine the limiting degree of aggregation for the studied signal. The integration of functional diagnostic systems based on the analysis of acoustic signals in the control systems of complex multi-drive systems opens the possibility in real time to evaluate and identify critical modes of electromechanical equipment and time to generate control actions that allow to stabilize the operation of production facilities.