Identification of automatic systems for acoustic emission diagnostics
DOI:
https://doi.org/10.31471/1993-9981-2020-1(44)-35-45Keywords:
automation, diagnostics, control, acoustic emission.Abstract
The difficulties of automation control, which are connected with variability of input parameters and complexity of mathematical description of internal dynamic processes in the controlled object, are noted. The features of categorical concepts of automation of control of acoustic-emission diagnostics control are formulated and marked: control object, control system, control functions. The mathematical formalism of modeling the energy spectrum of acoustic emission signals is presented. A discrete and continuous approach to describing the oscillatory properties of the internal structure of a material under load is used. The structural model of the basic stages of management is offered, which includes multidimensional input of diagnostics information, ensuring the controllability of products, informatization of diagnostic parameters, direct measurements, identification of the current state of the object. Functional purposes of the acoustic emission diagnostics system have been determined. On the basis of generalization of information on experimental studies of the effect of stresses under uniaxial loading and four-point bending on the parameters of acoustic emission signals, data on the influence of deformation processes on the information parameters of AE steels and composite materials were investigated and systematized. Areas of their application and rational use are established. It is noted that most of the experimental works in domestic and foreign practice are devoted to the influence on the material of one type of deformation measurements of the structure of materials, while during the operation of structures the material is subjected to a complex effect of complex loads. An algorithm for identification of systems for automatic control of acoustic emission diagnostics has been developed, which differs taking into account the variety of factors affecting the initial variables, the complexity of their interactions and estimates using expert evaluation, system analysis and simulation modeling.
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