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.
Highlights
To ensure tra c safety of railway transport, non-destructive tests of rails are regularly carried out by using various approaches and methods, including eddy-current aw detection methods
An automatic analysis of large data sets that come from the corresponding equipment is an actual problem. e analysis means a process of determining the presence of defective sections along with identifying structural elements of railway tracks in defectograms. is 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. e previously used algorithm for nding threshold levels was focused on situations in which the vast majority of signals coming from the aw detector is a rail noise
Summary
G. Demidov Yaroslavl State University, 14 Sovetskaya str., Yaroslavl 150003, Russia. Is 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. E 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 nding 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.
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