An Efficient Algorithm for Finding a Threshold of Useful Signals in the Analysis of Magnetic and Eddy Current Defectograms
https://doi.org/10.18255/1818-1015-2018-4-382-387
Abstract
To ensure traffic safety of railway transport, non-destructive testing of rails is regularly carried out by using various approaches and methods, including magnetic and eddy current flaw detection methods. An automatic analysis of large data sets (defectgrams) that come from the corresponding equipment is still an actual problem. The analysis means a process of determining the presence of defective sections along with identifying structural elements of railway tracks on defectograms. At the same time, under the conditions of significant volumes of incoming information, fast and efficient algorithms of data analysis are of most interest. This article is an addition to the previous article devoted to the problem of automatic determination of a threshold level of amplitudes of useful signals (from defects and structural elements of a railway track) during the analysis of defectograms (records) of magnetic and eddy current flaw detectors, which contains an algorithm for finding the threshold level of a rail noise and its theoretical justification with examples of its operation on several fragments of real magnetic and eddy current defectograms. The article presents a simple and effective implementation of the algorithm, which is successfully used in practice for the automatic analysis of magnetic and eddy current defectograms.
About the Authors
Egor V. KuzminRussian Federation
doctor of science, associate professor
Oleg E. Gorbunov
Russian Federation
PhD, general director
Petr O. Plotnikov
Russian Federation
production engineer
Vadim A. Tyukin
Russian Federation
head of software development
References
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Review
For citations:
Kuzmin E.V., Gorbunov O.E., Plotnikov P.O., Tyukin V.A. An Efficient Algorithm for Finding a Threshold of Useful Signals in the Analysis of Magnetic and Eddy Current Defectograms. Modeling and Analysis of Information Systems. 2018;25(4):382-387. (In Russ.) https://doi.org/10.18255/1818-1015-2018-4-382-387