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ABSTRACT

Stankevych O. M. Methodological backgrounds of identification of materials

fracture types by the energy parameters of acoustic emission. – Qualification scientific

work as a manuscript.

Thesis for the Doctor’s degree in Engineering Sciences by specialty 05.02.10 –

diagnostics of materials and structures (132 – materials science). – Karpenko Physico-

Mechanical Institute of National Academy of Science of Ukraine, Lviv, 2019.

The dissertation is devoted to the scientific and technical problem which consists

in the development on the basis of theoretical and experimental studies the methodo-

logical backgrounds of solids fracture diagnostics and estimation of the structural

materials state using energy parameters of acoustic emission of elastic wave.

From the literature review the brittle (quasibrittle) and ductile fracture are paid the

most attention. A brittle fracture is the most dangerous for strength of a structure or

product, because of spontaneous and fast-flowing character. Therefore, the identifica-

tion of materials fracture types of is the important problem for the efficiency increasing

of the technical diagnostics (TD) and nondestructive testing (NDT) of the industrial

objects and products. It will make it possible based on NDT data and linear fracture

mechanics approaches to make operatively and in real time a decision about operation

prolongation of the object under the test. The method of acoustic emission (AE) is the

most effective way to study the processes and stages of the development of the material

structure imperfections and to estimation the state of the objects under the test.

The combination of analytical and numerical approaches to the simulation of the

sources of the AE elastic waves with the experimental methods of their identification

makes it possible to find the relationships between the individual parameters of defects

of materials and AE elastic waves. These relationships may be used to solve the inverse

problem – determination of the defect parameters through the AE signals. Wavelet

transform (WT) is used to study structure and peculiarities of signal with the areas of

different duration and frequencies. Based on the literature analysis it may be said that

the WT of AE and magnetoacoustic (MAE) signals is effective tool for identification of