Title :
Identification of signals of electromagnetic rail-flaw detection system using artificial neural networks
Author_Institution :
Electron. Means of Inf. & Comput. Technol. Dept., L´´viv Polytech. Nat. Univ., L´´viv, Ukraine
Abstract :
In this paper the results of the study on the identification of objects of railway canvas by certain signs using neural network technology are considered.
Keywords :
flaw detection; neural nets; object detection; railway engineering; signal detection; artificial neural networks; electromagnetic rail flaw detection system; object identification; railway canvas; signal identification; Artificial neural networks; Automation; Electromagnetics; Metals; Object recognition; Rail transportation; Rails; Non-destructive testing; artificial neural networks; automation; rail-flaw detection;
Conference_Titel :
Perspective Technologies and Methods in MEMS Design (MEMSTECH), 2011 Proceedings of VIIth International Conference on
Conference_Location :
Polyana
Print_ISBN :
978-1-4577-0639-4
Electronic_ISBN :
978-966-2191-18-9
