Application of the wavelet and neural technologies for processing of signals obtained during railway tracks diagnostics by the magnetic flux leakage method

In this article, the approach for detecting a transverse crack in the rail head via ANN with CWT and application created on its basis are presented. The ways of further development of the ANN for improving its work accuracy and the possibility of identification of other types of defects are also pre...

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Bibliographic Details
Main Authors:	Vitalij Nichoga, Liubomyr Vashchyshyn
Format:	Article
Language:	English
Published:	Wojskowa Akademia Techniczna, Redakcja Wydawnictw WAT, ul. gen. S. Kaliskiego 2, 00-908 Warszawa 2017-12-01
Series:	Biuletyn Wojskowej Akademii Technicznej
Subjects:	defect transverse crack CWT ANN
Online Access:	http://biuletynwat.pl/gicid/01.3001.0010.8332

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record_format	Article
spelling	doaj-ec9f468bd27b41f7a908fddcc46221322020-11-24T20:53:06ZengWojskowa Akademia Techniczna, Redakcja Wydawnictw WAT, ul. gen. S. Kaliskiego 2, 00-908 Warszawa Biuletyn Wojskowej Akademii Technicznej 1234-58652017-12-0166419520110.5604/01.3001.0010.833201.3001.0010.8332Application of the wavelet and neural technologies for processing of signals obtained during railway tracks diagnostics by the magnetic flux leakage methodVitalij Nichoga0Liubomyr Vashchyshyn1National University “Lvivska Politechnika”, Institute of Telecommunications, Radoielectronics and Electronic Engineering, 2 Profesorska Str., Lviv, 79013, UkraineNational University “Lvivska Politechnika”, Institute of Telecommunications, Radoielectronics and Electronic Engineering, 2 Profesorska Str., Lviv, 79013, UkraineIn this article, the approach for detecting a transverse crack in the rail head via ANN with CWT and application created on its basis are presented. The ways of further development of the ANN for improving its work accuracy and the possibility of identification of other types of defects are also presented. Keywords: defect, transverse crack, CWT, ANN http://biuletynwat.pl/gicid/01.3001.0010.8332defecttransverse crackCWTANN
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Vitalij Nichoga Liubomyr Vashchyshyn
spellingShingle	Vitalij Nichoga Liubomyr Vashchyshyn Application of the wavelet and neural technologies for processing of signals obtained during railway tracks diagnostics by the magnetic flux leakage method Biuletyn Wojskowej Akademii Technicznej defect transverse crack CWT ANN
author_facet	Vitalij Nichoga Liubomyr Vashchyshyn
author_sort	Vitalij Nichoga
title	Application of the wavelet and neural technologies for processing of signals obtained during railway tracks diagnostics by the magnetic flux leakage method
title_short	Application of the wavelet and neural technologies for processing of signals obtained during railway tracks diagnostics by the magnetic flux leakage method
title_full	Application of the wavelet and neural technologies for processing of signals obtained during railway tracks diagnostics by the magnetic flux leakage method
title_fullStr	Application of the wavelet and neural technologies for processing of signals obtained during railway tracks diagnostics by the magnetic flux leakage method
title_full_unstemmed	Application of the wavelet and neural technologies for processing of signals obtained during railway tracks diagnostics by the magnetic flux leakage method
title_sort	application of the wavelet and neural technologies for processing of signals obtained during railway tracks diagnostics by the magnetic flux leakage method
publisher	Wojskowa Akademia Techniczna, Redakcja Wydawnictw WAT, ul. gen. S. Kaliskiego 2, 00-908 Warszawa
series	Biuletyn Wojskowej Akademii Technicznej
issn	1234-5865
publishDate	2017-12-01
description	In this article, the approach for detecting a transverse crack in the rail head via ANN with CWT and application created on its basis are presented. The ways of further development of the ANN for improving its work accuracy and the possibility of identification of other types of defects are also presented. Keywords: defect, transverse crack, CWT, ANN
topic	defect transverse crack CWT ANN
url	http://biuletynwat.pl/gicid/01.3001.0010.8332
work_keys_str_mv	AT vitalijnichoga applicationofthewaveletandneuraltechnologiesforprocessingofsignalsobtainedduringrailwaytracksdiagnosticsbythemagneticfluxleakagemethod AT liubomyrvashchyshyn applicationofthewaveletandneuraltechnologiesforprocessingofsignalsobtainedduringrailwaytracksdiagnosticsbythemagneticfluxleakagemethod
_version_	1716798065199808512

Application of the wavelet and neural technologies for processing of signals obtained during railway tracks diagnostics by the magnetic flux leakage method

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