Abstract

Most of the oil and gas equipment complex is subjected to cyclic-variable, mechanical, thermal loads and corrosive-active environment. These effects causing a change in the structural statr of the metal contribute to the accelerated development of defects, especially in places with stress concentrators, which ultimately lead to the constructions destruction.
 Available ultrasonic, electromagnetic, and eddy-current non-destructive testing methods are currently aimed at solving defect detection problems. However, it is more important to timely identify the initial stage of the process of damage accumulation in a metal by determining changes in the structural state of the metal.
 The article proposes a methodology for studies of steel structural changes arising in the process of exploitation and their impact on mechanical characteristics. A reasonable choice of the optimal indicator characterizing the image of the acoustic structural noise of the material obtained by applying ultrasonic flaw detector in a complete set with piezoelectric converters with a phased array is substantiated. The complex of physical and mechanical parameters of the investigated samples are measured and the results obtained were analyzed. The modern methods of determination of mechanical characteristics of steels are considered, their deficiencies are determined and the methods of their optimization are proposed. The regression-correlation analysis of the experimental studies results was carried out, which resulted in the equation of dependence between a set of non-destructive control parameters and mechanical characteristics of steels was obtained.
 In order to verify the adequacy of the proposed model and to establish the possibility of controlling the casing and tubing on the samples made, series of experimental studies were carried out, which confirmed the reliability of the resulting calculation model for determining the mechanical characteristics of the steels by using two informative parameters, namely hardness and integral density of images of acoustic structural noise.

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