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Algorithm for the extraction of selected rail track ballast degradation using machine vision

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A number of physical methods are used to survey railway track ballast to assess its degradation as a function of deposition. Simulation tests on track models are also conducted. These testing methods, which are generally labour-intensive and expensive, provide an accurate understanding of the extent of ballast degradation. However, the impact of inadequate maintenance can be observed, even on the surface. Therefore, it seems natural in this case to use image registration. State-of-the-art machine vision systems of track geometry cars provide the means to do this. Obtained ballast images provide a baseline for evaluating its level in relation to sleepers. However, no information is available on other signs of track degradation, such as overgrown vegetation (weeds) or the so-called local muddy areas, which are generally a consequence of poor drainage and a lack of subgrade insulation. These degradations are observed to generate distinctive colour images that are superimposed on the overall image of the ballast surface. They differ in colour and shape. Hence, the authors used this phenomenon to develop an algorithm for the extraction of ballast degradation images based on RGB imaging. Surface descriptors have also been offered to assess these degradations. Extensive measurement material from the railway lines was used to conduct survey experiments based on the examples. The results clearly demonstrate the high success rate of the applied method.
Czasopismo
Rocznik
Strony
129--141
Opis fizyczny
Bibliogr. 40 poz.
Twórcy
autor
  • WSEI University; Projektowa 4, 20-209 Lublin, Poland
  • Kazimierz Pulaski University of Technology and Humanities in Radom; Malczewskiego 29, 26-600 Radom, Poland
  • Rzeszów University of Technology; al. Powstańców Warszawy 12, 35-959 Rzeszów, Poland
Bibliografia
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  • 5. Asadzadeh, S.M. & Galeazzi, R. & Hovad, E. & Andersen, J.F. & Thyregod, C. & Rodrigues, A.F.S. Ballast degradation modelling for turnouts based on track recording car. Data Proceedings of the European Conference of the Prognostics and Health Management Society. 2018. Vol. 4(1).
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f96344c6-6426-4bd1-b87c-107f629d4a97
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