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JOURNALS // Modelirovanie i Analiz Informatsionnykh Sistem // Archive

Model. Anal. Inform. Sist., 2021 Volume 28, Number 1, Pages 74–88 (Mi mais736)

This article is cited in 2 papers

Computing methodologies and applications

An algorithm for correcting levels of useful signals on interpretation of eddy-current defectograms

E. V. Kuzmina, O. E. Gorbunovb, P. O. Plotnikovb, V. A. Tyukinb, V. A. Bashkinab

a P. G. Demidov Yaroslavl State University, 14 Sovetskaya str., Yaroslavl 150003, Russia
b Center of Innovative Programming, NDDLab, 144 Soyuznaya str., Yaroslavl 150008, Russia

Abstract: To ensure traffic safety of railway transport, non-destructive tests of rails are regularly carried out by using various approaches and methods, including eddy-current flaw detection methods. An automatic analysis of large data sets (defectograms) that come from the corresponding equipment is an actual problem. The analysis means a process of determining the presence of defective sections along with identifying structural elements of railway tracks in defectograms. This article continues the cycle of works devoted to the problem of automatic recognizing images of defects and structural elements of rails in eddy-current defectograms. In the process of forming these images, only useful signals are taken into account, the threshold levels of amplitudes of which are determined automatically from eddy-current data. The previously used algorithm for finding threshold levels was focused on situations in which the vast majority of signals coming from the flaw detector is a rail noise. A signal is considered useful and is subject to further analysis if its amplitude is twice the corresponding noise threshold. The article is devoted to the problem of correcting threshold levels, taking into account the need to identify extensive surface defects of rails. An algorithm is proposed for finding the values of threshold levels of rail noise amplitudes with their subsequent correction in the case of a large number of useful signals from extensive defects. Examples of the algorithm's operation on real eddy-current data are given.

Keywords: nondestructive testing, eddy current testing, rail flaw detection, automated analysis of defectograms.

UDC: 004.021

MSC: 68T09

Received: 21.10.2020
Revised: 17.02.2021
Accepted: 12.03.2021

DOI: 10.18255/1818-1015-2021-1-74-88



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